From c3a6ccfe288360a0261938865db301679372b9bb Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Thu, 13 Jun 2024 00:44:22 -0700 Subject: [PATCH 01/11] remove logs --- ...security-guide_PnT6q6Kqn75k8Wgqw9x8rq.json | 71 - ...security-guide_nvPoK8sSq9fwqirnyVXpTT.json | 71 - ...security-guide_L9Foe5pZ4kKNchKSjrnmBG.json | 71 - ...security-guide_hECF7Z795AWH3W8s7CaJHT.json | 71 - ...security-guide_c5gUYigs5mMm4BXwZf3Pv9.json | 181 -- ...security-guide_8TXTQPM5DzadcwKdZVC4ra.json | 1852 ----------------- ...security-guide_8muqC7EeXUZZR87SPgGhkw.json | 202 -- ...security-guide_cPwNbU4bKotTZqhPZf5e74.json | 202 -- ...security-guide_VWvxnwoDsp6HYn6fbt9Tri.json | 202 -- ...security-guide_fV8bFBJrgZo8hLZ8VMizpn.json | 202 -- ...security-guide_hhEbZj5tKCbkeZXZThqxDN.json | 202 -- ...security-guide_hECF7Z795AWH3W8s7CaJHT.json | 151 -- ...security-guide_JK4cmm7UAxZNPdq3hGrrxo.json | 145 -- ...security-guide_QCtsMMNEnWS7xbFZwbpFbb.json | 145 -- ...security-guide_E56YvLVCpqFT6jCNVBWXqh.json | 128 -- ...security-guide_U5HzKEDA7XefuRsnGcPoEG.json | 136 -- ...security-guide_SKaR6pSj4DLB88EZgb4XGs.json | 51 - ...security-guide_RUaUi4GQaqHfwnsYw5N4b3.json | 51 - ...security-guide_gKTYiZEfKpq3CJXiRkboEA.json | 51 - ...security-guide_NnYsHcX5QowFsT4q2P7FTq.json | 51 - ...security-guide_YTsBzdCuXsQnD8JXmoRr5e.json | 51 - ...security-guide_DrGcpD89xQTZPiYN59hzSj.json | 51 - ...security-guide_NbMLjeXvkPjWSpZQDQoaRT.json | 51 - ...security-guide_7uTjdhszqprw5hGRWF26TN.json | 136 -- ...security-guide_inCT9mgYbUaFjVdy32qFgi.json | 136 -- 25 files changed, 4661 deletions(-) delete mode 100644 logs/2024-06-07T16-58-55-07-00_security-guide_PnT6q6Kqn75k8Wgqw9x8rq.json delete mode 100644 logs/2024-06-07T17-00-59-07-00_security-guide_nvPoK8sSq9fwqirnyVXpTT.json delete mode 100644 logs/2024-06-07T17-02-09-07-00_security-guide_L9Foe5pZ4kKNchKSjrnmBG.json delete mode 100644 logs/2024-06-07T17-05-26-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json delete mode 100644 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logs/2024-06-12T19-22-28-07-00_security-guide_inCT9mgYbUaFjVdy32qFgi.json diff --git a/logs/2024-06-07T16-58-55-07-00_security-guide_PnT6q6Kqn75k8Wgqw9x8rq.json b/logs/2024-06-07T16-58-55-07-00_security-guide_PnT6q6Kqn75k8Wgqw9x8rq.json deleted file mode 100644 index d094a949..00000000 --- a/logs/2024-06-07T16-58-55-07-00_security-guide_PnT6q6Kqn75k8Wgqw9x8rq.json +++ /dev/null @@ -1,71 +0,0 @@ -{ - "version": 1, - "status": "error", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "PnT6q6Kqn75k8Wgqw9x8rq", - "run_id": "cusmDxyhfMTNUnVo5GB3FV", - "created": "2024-06-07T16:58:55-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 16, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-07T16:58:55-07:00", - "completed_at": "2024-06-07T16:58:56-07:00", - "model_usage": {} - }, - "error": { - "message": "TypeError('Object of type NotGiven is not JSON serializable')", - "traceback": "Traceback (most recent call last):\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 188, in task_run\n scores = await asyncio.gather(*tasks)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 283, in task_run_sample\n state = await solver(state, generate)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/solver/_solver.py\", line 201, in solve\n return await generate(state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 156, in generate\n return await task_generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/generate.py\", line 33, in task_generate\n output = await model.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 548, in generate\n return await self._generate(input, tools, tool_choice, config)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 635, in _generate\n model_output = await generate()\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 88, in async_wrapped\n return await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 47, in __call__\n do = self.iter(retry_state=retry_state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/__init__.py\", line 314, in iter\n return fut.result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 451, in result\n return self.__get_result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 403, in __get_result\n raise self._exception\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 50, in __call__\n result = await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 627, in generate\n return await self.api.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 142, in generate\n response: ChatCompletion = await self.client.chat.completions.create(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/langtrace_python_sdk/instrumentation/openai/patch.py\", line 606, in traced_method\n tools.append(json.dumps(kwargs.get(\"tools\")))\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/__init__.py\", line 231, in dumps\n return _default_encoder.encode(obj)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 199, in encode\n chunks = self.iterencode(o, _one_shot=True)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 257, in iterencode\n return _iterencode(o, 0)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 179, in default\n raise TypeError(f'Object of type {o.__class__.__name__} '\n\nTypeError: Object of type NotGiven is not JSON serializable\n", - "traceback_ansi": "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m188\u001b[0m in \u001b[92mtask_run\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m283\u001b[0m in \u001b[92mtask_run_sample\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/solver/\u001b[0m\u001b[1;33m_solver.py\u001b[0m:\u001b[94m201\u001b[0m in \u001b[92msolve\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m156\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mgenerate.py\u001b[0m:\u001b[94m33\u001b[0m in \u001b[92mtask_generate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m ... 10 frames hidden ... \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mlangtrace_python_sdk/instrumentation/openai/\u001b[0m\u001b[1;33mpatch.py\u001b[0m:\u001b[94m606\u001b[0m in \u001b[92mtraced_method\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m603 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m604 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[96mprint\u001b[0m(\u001b[33m\"\u001b[0m\u001b[33mhere\u001b[0m\u001b[33m\"\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m605 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[96mprint\u001b[0m(kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m)) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m606 \u001b[2m│ │ │ \u001b[0mtools.append(json.dumps(kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m))) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m607 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mlen\u001b[0m(tools) > \u001b[94m0\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m608 \u001b[0m\u001b[2m│ │ │ \u001b[0mattributes.llm_tools = json.dumps(tools) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m609 \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ahandle_streaming_response = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39masync_chat_completions_create..ahandle_streaming_respo…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39mat \u001b[0m\u001b[94m0x130955510\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m args = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m attributes = \u001b[1;35mLLMSpanAttributes\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_name\u001b[0m=\u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ 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\u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'model'\u001b[0m: \u001b[33m'gpt-3.5-turbo'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'stream'\u001b[0m: \u001b[94mFalse\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'frequency_penalty'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'stop'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'max_tokens'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'presence_penalty'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m 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\u001b[33mattacks?\\n\\nBefore answering, reason in a step-by-'\u001b[0m+\u001b[94m179\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m service_provider = \u001b[33m'Azure'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m span_attributes = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.sdk.name'\u001b[0m: \u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.name'\u001b[0m: \u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.type'\u001b[0m: \u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.version'\u001b[0m: \u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.version'\u001b[0m: \u001b[33m'2.1.13'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'url.full'\u001b[0m: \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33m'https://test-openai-scale3.openai.azure.com/openai/deployment…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.api'\u001b[0m: \u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.prompts'\u001b[0m: \u001b[33m'\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m{\u001b[0m\u001b[33m\"role\": \"user\", \"content\": \"\\\\nHow do I \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mprevent SQL Injection attacks?\\\\n\\\\nBefor'\u001b[0m+\u001b[94m218\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.stream'\u001b[0m: \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tools = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tracer = \u001b[1m<\u001b[0m\u001b[1;95mopentelemetry.sdk.trace.Tracer\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x1309802b0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m version = \u001b[33m'1.30.3'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m wrapped = \u001b[1m<\u001b[0m\u001b[1;95mbound\u001b[0m\u001b[39m method AsyncCompletions.create of \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39m\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33m__init__.py\u001b[0m:\u001b[94m231\u001b[0m in \u001b[92mdumps\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m228 \u001b[0m\u001b[2m│ │ \u001b[0mcheck_circular \u001b[95mand\u001b[0m allow_nan \u001b[95mand\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m229 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mcls\u001b[0m \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m indent \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m separators \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m230 \u001b[0m\u001b[2m│ │ \u001b[0mdefault \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m sort_keys \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m kw): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m231 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _default_encoder.encode(obj) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m232 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mcls\u001b[0m \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m233 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mcls\u001b[0m = JSONEncoder \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m234 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mcls\u001b[0m( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m─────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m─────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m allow_nan = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m check_circular = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m cls = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m default = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ensure_ascii = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m indent = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m kw = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m obj = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m separators = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m skipkeys = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m sort_keys = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m199\u001b[0m in \u001b[92mencode\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m196 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# This doesn't pass the iterator directly to ''.join() because the\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m197 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# exceptions aren't as detailed. The list call should be roughly\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m198 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# equivalent to the PySequence_Fast that ''.join() would do.\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m199 \u001b[2m│ │ \u001b[0mchunks = \u001b[96mself\u001b[0m.iterencode(o, _one_shot=\u001b[94mTrue\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m200 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m \u001b[96misinstance\u001b[0m(chunks, (\u001b[96mlist\u001b[0m, \u001b[96mtuple\u001b[0m)): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m201 \u001b[0m\u001b[2m│ │ │ \u001b[0mchunks = \u001b[96mlist\u001b[0m(chunks) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m202 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[33m'\u001b[0m\u001b[33m'\u001b[0m.join(chunks) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m───────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10b7a8d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰─────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m257\u001b[0m in \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[92miterencode\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m254 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mmarkers, \u001b[96mself\u001b[0m.default, _encoder, \u001b[96mself\u001b[0m.indent, floatstr, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m255 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m.key_separator, \u001b[96mself\u001b[0m.item_separator, \u001b[96mself\u001b[0m.sort_keys, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m256 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m.skipkeys, _one_shot) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m257 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _iterencode(o, \u001b[94m0\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m258 \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m259 \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_make_iterencode\u001b[0m(markers, _default, _encoder, _indent, _floatstr, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m260 \u001b[0m\u001b[2m│ │ \u001b[0m_key_separator, _item_separator, _sort_keys, _skipkeys, _one_shot, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _encoder = \u001b[1m<\u001b[0m\u001b[1;95mbuilt-in\u001b[0m\u001b[39m function encode_basestring_ascii\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _iterencode = \u001b[1m<\u001b[0m\u001b[1;95m_json.Encoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x167e29d20\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _one_shot = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m floatstr = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m JSONEncoder.iterencode..floatstr at \u001b[0m\u001b[94m0x16802dcf0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m markers = \u001b[1m{\u001b[0m\u001b[94m4587198768\u001b[0m: NOT_GIVEN\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10b7a8d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m179\u001b[0m in \u001b[92mdefault\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m176 \u001b[0m\u001b[2;33m│ │ │ │ \u001b[0m\u001b[33mreturn JSONEncoder.default(self, o)\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m177 \u001b[0m\u001b[2m│ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m178 \u001b[0m\u001b[2;33m│ │ \u001b[0m\u001b[33m\"\"\"\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m179 \u001b[2m│ │ \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mTypeError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mObject of type \u001b[0m\u001b[33m{\u001b[0mo.\u001b[91m__class__\u001b[0m.\u001b[91m__name__\u001b[0m\u001b[33m}\u001b[0m\u001b[33m \u001b[0m\u001b[33m'\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m180 \u001b[0m\u001b[2m│ │ │ │ │ │ \u001b[0m\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mis not JSON serializable\u001b[0m\u001b[33m'\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m181 \u001b[0m\u001b[2m│ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m182 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mencode\u001b[0m(\u001b[96mself\u001b[0m, o): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m───────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10b7a8d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰─────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n\u001b[1;91mTypeError: \u001b[0mObject of type NotGiven is not JSON serializable\n" - }, - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717804734371.483 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717804735829.6252 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-00-59-07-00_security-guide_nvPoK8sSq9fwqirnyVXpTT.json b/logs/2024-06-07T17-00-59-07-00_security-guide_nvPoK8sSq9fwqirnyVXpTT.json deleted file mode 100644 index 423a80d9..00000000 --- a/logs/2024-06-07T17-00-59-07-00_security-guide_nvPoK8sSq9fwqirnyVXpTT.json +++ /dev/null @@ -1,71 +0,0 @@ -{ - "version": 1, - "status": "error", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "nvPoK8sSq9fwqirnyVXpTT", - "run_id": "MDTLtKf5p46hgZGzagPLgp", - "created": "2024-06-07T17:00:59-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 16, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-07T17:00:59-07:00", - "completed_at": "2024-06-07T17:00:59-07:00", - "model_usage": {} - }, - "error": { - "message": "TypeError('Object of type NotGiven is not JSON serializable')", - "traceback": "Traceback (most recent call last):\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 188, in task_run\n scores = await asyncio.gather(*tasks)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 283, in task_run_sample\n state = await solver(state, generate)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/solver/_solver.py\", line 201, in solve\n return await generate(state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 156, in generate\n return await task_generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/generate.py\", line 33, in task_generate\n output = await model.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 548, in generate\n return await self._generate(input, tools, tool_choice, config)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 635, in _generate\n model_output = await generate()\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 88, in async_wrapped\n return await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 47, in __call__\n do = self.iter(retry_state=retry_state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/__init__.py\", line 314, in iter\n return fut.result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 451, in result\n return self.__get_result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 403, in __get_result\n raise self._exception\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 50, in __call__\n result = await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 627, in generate\n return await self.api.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 142, in generate\n response: ChatCompletion = await self.client.chat.completions.create(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/langtrace_python_sdk/instrumentation/openai/patch.py\", line 610, in traced_method\n attributes.llm_tools = json.dumps(tools)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/__init__.py\", line 231, in dumps\n return _default_encoder.encode(obj)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 199, in encode\n chunks = self.iterencode(o, _one_shot=True)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 257, in iterencode\n return _iterencode(o, 0)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 179, in default\n raise TypeError(f'Object of type {o.__class__.__name__} '\n\nTypeError: Object of type NotGiven is not JSON serializable\n", - "traceback_ansi": "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m188\u001b[0m in \u001b[92mtask_run\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m283\u001b[0m in \u001b[92mtask_run_sample\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/solver/\u001b[0m\u001b[1;33m_solver.py\u001b[0m:\u001b[94m201\u001b[0m in \u001b[92msolve\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m156\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mgenerate.py\u001b[0m:\u001b[94m33\u001b[0m in \u001b[92mtask_generate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m ... 10 frames hidden ... \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mlangtrace_python_sdk/instrumentation/openai/\u001b[0m\u001b[1;33mpatch.py\u001b[0m:\u001b[94m610\u001b[0m in \u001b[92mtraced_method\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m607 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94melse\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m608 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mtools.append(kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m)) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m609 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mlen\u001b[0m(tools) > \u001b[94m0\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m610 \u001b[2m│ │ │ \u001b[0mattributes.llm_tools = json.dumps(tools) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m611 \u001b[0m\u001b[2m│ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m612 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# TODO(Karthik): Gotta figure out how to handle streaming with context\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m613 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# with tracer.start_as_current_span(APIS[\"CHAT_COMPLETION\"][\"METHOD\"],\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ahandle_streaming_response = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39masync_chat_completions_create..ahandle_streaming_respo…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39mat \u001b[0m\u001b[94m0x130a6d480\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m args = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m attributes = \u001b[1;35mLLMSpanAttributes\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_name\u001b[0m=\u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_type\u001b[0m=\u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_version\u001b[0m=\u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_version\u001b[0m=\u001b[33m'2.1.13'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_sdk_name\u001b[0m=\u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33murl_full\u001b[0m=\u001b[33m'https://test-openai-scale3.openai.azure.com/openai/d…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_api\u001b[0m=\u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_model\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_temperature\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_top_p\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_top_k\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_user\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_system_fingerprint\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_prompts\u001b[0m=\u001b[33m'\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m{\u001b[0m\u001b[33m\"role\": \"user\", \"content\": \"\\\\nHow do I \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mprevent SQL Injection attacks?\\\\n\\\\nBefor'\u001b[0m+\u001b[94m218\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_responses\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_token_counts\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_stream\u001b[0m=\u001b[94mFalse\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_encoding_formats\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_dimensions\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_generation_id\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_response_id\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_citations\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_documents\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_is_search_required\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_search_results\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_tool_calls\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_max_tokens\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_max_input_tokens\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_conversation_id\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_seed\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_frequency_penalty\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m 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\u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_embedding_input_type\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_embedding_job_name\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_retrieval_query\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_retrieval_results\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_image_size\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_response_format\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mhttp_max_retries\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mhttp_timeout\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_testId\u001b[0m=\u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m base_url = \u001b[33m'https://test-openai-scale3.openai.azure.com/openai/deployment…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m extra_attributes = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m instance = \u001b[1m<\u001b[0m\u001b[1;95mopenai.resources.chat.completions.AsyncCompletions\u001b[0m\u001b[39m object at \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[94m0x167ec47f0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m item = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow do I prevent SQL Injection \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mattacks?\\n\\nBefore answering, reason in a step-by-'\u001b[0m+\u001b[94m179\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m kwargs = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'messages'\u001b[0m: \u001b[1m[\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow do I prevent SQL Injection \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mattacks?\\n\\nBefore answering, reason in a step-by-'\u001b[0m+\u001b[94m179\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m]\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'tools'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'tool_choice'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'model'\u001b[0m: \u001b[33m'gpt-3.5-turbo'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'stream'\u001b[0m: \u001b[94mFalse\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'frequency_penalty'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'stop'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'max_tokens'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'presence_penalty'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'logit_bias'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m...\u001b[0m +\u001b[94m7\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m llm_prompts = \u001b[1m[\u001b[0m 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\u001b[33m'Azure'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m span_attributes = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.sdk.name'\u001b[0m: \u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.name'\u001b[0m: \u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.type'\u001b[0m: \u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.version'\u001b[0m: \u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ 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\u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m separators \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m230 \u001b[0m\u001b[2m│ │ \u001b[0mdefault \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m sort_keys \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m kw): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m231 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _default_encoder.encode(obj) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m232 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mcls\u001b[0m \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m233 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mcls\u001b[0m = JSONEncoder \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m234 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mcls\u001b[0m( 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kw = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m obj = \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m separators = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m skipkeys = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m sort_keys = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m199\u001b[0m in \u001b[92mencode\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m 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The list call should be roughly\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m198 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# equivalent to the PySequence_Fast that ''.join() would do.\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m199 \u001b[2m│ │ \u001b[0mchunks = \u001b[96mself\u001b[0m.iterencode(o, _one_shot=\u001b[94mTrue\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m200 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m \u001b[96misinstance\u001b[0m(chunks, (\u001b[96mlist\u001b[0m, \u001b[96mtuple\u001b[0m)): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m201 \u001b[0m\u001b[2m│ │ │ \u001b[0mchunks = \u001b[96mlist\u001b[0m(chunks) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m202 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[33m'\u001b[0m\u001b[33m'\u001b[0m.join(chunks) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m 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\u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m254 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mmarkers, \u001b[96mself\u001b[0m.default, _encoder, \u001b[96mself\u001b[0m.indent, floatstr, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m255 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m.key_separator, \u001b[96mself\u001b[0m.item_separator, \u001b[96mself\u001b[0m.sort_keys, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m256 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m.skipkeys, _one_shot) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m257 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _iterencode(o, \u001b[94m0\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m258 \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m259 \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_make_iterencode\u001b[0m(markers, _default, _encoder, _indent, _floatstr, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m260 \u001b[0m\u001b[2m│ │ \u001b[0m_key_separator, _item_separator, _sort_keys, _skipkeys, _one_shot, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _encoder = \u001b[1m<\u001b[0m\u001b[1;95mbuilt-in\u001b[0m\u001b[39m function encode_basestring_ascii\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _iterencode = \u001b[1m<\u001b[0m\u001b[1;95m_json.Encoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x16816dd80\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _one_shot = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m floatstr = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m JSONEncoder.iterencode..floatstr at \u001b[0m\u001b[94m0x1681edbd0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m markers = \u001b[1m{\u001b[0m\u001b[94m6042016512\u001b[0m: \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m, \u001b[94m4588395520\u001b[0m: NOT_GIVEN\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10b8a4d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m179\u001b[0m in \u001b[92mdefault\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m176 \u001b[0m\u001b[2;33m│ │ │ │ \u001b[0m\u001b[33mreturn JSONEncoder.default(self, o)\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m177 \u001b[0m\u001b[2m│ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m178 \u001b[0m\u001b[2;33m│ │ \u001b[0m\u001b[33m\"\"\"\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m179 \u001b[2m│ │ \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mTypeError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mObject of type \u001b[0m\u001b[33m{\u001b[0mo.\u001b[91m__class__\u001b[0m.\u001b[91m__name__\u001b[0m\u001b[33m}\u001b[0m\u001b[33m \u001b[0m\u001b[33m'\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m180 \u001b[0m\u001b[2m│ │ │ │ │ │ \u001b[0m\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mis not JSON serializable\u001b[0m\u001b[33m'\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m181 \u001b[0m\u001b[2m│ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m182 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mencode\u001b[0m(\u001b[96mself\u001b[0m, o): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m───────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10b8a4d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰─────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n\u001b[1;91mTypeError: \u001b[0mObject of type NotGiven is not JSON serializable\n" - }, - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717804857535.285 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717804859370.688 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-02-09-07-00_security-guide_L9Foe5pZ4kKNchKSjrnmBG.json b/logs/2024-06-07T17-02-09-07-00_security-guide_L9Foe5pZ4kKNchKSjrnmBG.json deleted file mode 100644 index 7785e8b1..00000000 --- a/logs/2024-06-07T17-02-09-07-00_security-guide_L9Foe5pZ4kKNchKSjrnmBG.json +++ /dev/null @@ -1,71 +0,0 @@ -{ - "version": 1, - "status": "error", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "L9Foe5pZ4kKNchKSjrnmBG", - "run_id": "2aFeRWmzWk7XLG6kCUtWdo", - "created": "2024-06-07T17:02:09-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 16, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-07T17:02:09-07:00", - "completed_at": "2024-06-07T17:02:09-07:00", - "model_usage": {} - }, - "error": { - "message": "TypeError('Object of type NotGiven is not JSON serializable')", - "traceback": "Traceback (most recent call last):\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 188, in task_run\n scores = await asyncio.gather(*tasks)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 283, in task_run_sample\n state = await solver(state, generate)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/solver/_solver.py\", line 201, in solve\n return await generate(state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 156, in generate\n return await task_generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/generate.py\", line 33, in task_generate\n output = await model.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 548, in generate\n return await self._generate(input, tools, tool_choice, config)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 635, in _generate\n model_output = await generate()\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 88, in async_wrapped\n return await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 47, in __call__\n do = self.iter(retry_state=retry_state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/__init__.py\", line 314, in iter\n return fut.result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 451, in result\n return self.__get_result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 403, in __get_result\n raise self._exception\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 50, in __call__\n result = await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 627, in generate\n return await self.api.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 142, in generate\n response: ChatCompletion = await self.client.chat.completions.create(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/langtrace_python_sdk/instrumentation/openai/patch.py\", line 611, in traced_method\n attributes.llm_tools = json.dumps(tools)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/__init__.py\", line 231, in dumps\n return _default_encoder.encode(obj)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 199, in encode\n chunks = self.iterencode(o, _one_shot=True)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 257, in iterencode\n return _iterencode(o, 0)\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/encoder.py\", line 179, in default\n raise TypeError(f'Object of type {o.__class__.__name__} '\n\nTypeError: Object of type NotGiven is not JSON serializable\n", - "traceback_ansi": "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m188\u001b[0m in \u001b[92mtask_run\u001b[0m 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\u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m156\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mgenerate.py\u001b[0m:\u001b[94m33\u001b[0m in \u001b[92mtask_generate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m ... 10 frames hidden ... \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mlangtrace_python_sdk/instrumentation/openai/\u001b[0m\u001b[1;33mpatch.py\u001b[0m:\u001b[94m611\u001b[0m in \u001b[92mtraced_method\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m608 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mtools.append(kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m)) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m609 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mlen\u001b[0m(tools) > \u001b[94m0\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m610 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[96mprint\u001b[0m(tools) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m611 \u001b[2m│ │ │ \u001b[0mattributes.llm_tools = json.dumps(tools) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m612 \u001b[0m\u001b[2m│ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m613 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# TODO(Karthik): Gotta figure out how to handle streaming with context\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m614 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# with tracer.start_as_current_span(APIS[\"CHAT_COMPLETION\"][\"METHOD\"],\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ahandle_streaming_response = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39masync_chat_completions_create..ahandle_streaming_respo…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39mat \u001b[0m\u001b[94m0x131e5d480\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m args = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m attributes = \u001b[1;35mLLMSpanAttributes\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_name\u001b[0m=\u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_type\u001b[0m=\u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_version\u001b[0m=\u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_version\u001b[0m=\u001b[33m'2.1.13'\u001b[0m, 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\u001b[2m│ \u001b[0m\u001b[33mllm_presence_penalty\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_connectors\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_tools\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_tool_results\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_embedding_inputs\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_embedding_dataset_id\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m 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\u001b[33m'Azure'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m span_attributes = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.sdk.name'\u001b[0m: \u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.name'\u001b[0m: \u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.type'\u001b[0m: \u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.version'\u001b[0m: \u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ 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AsyncCompletions.create of \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39m\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33m__init__.py\u001b[0m:\u001b[94m231\u001b[0m in \u001b[92mdumps\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m228 \u001b[0m\u001b[2m│ │ \u001b[0mcheck_circular \u001b[95mand\u001b[0m allow_nan \u001b[95mand\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m229 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mcls\u001b[0m \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m indent \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m separators \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m230 \u001b[0m\u001b[2m│ │ \u001b[0mdefault \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m sort_keys \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m kw): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m231 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _default_encoder.encode(obj) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m232 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mcls\u001b[0m \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m233 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mcls\u001b[0m = JSONEncoder \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m234 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mcls\u001b[0m( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m allow_nan = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m check_circular = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m cls = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m default = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ensure_ascii = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m indent = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m kw = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m obj = \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m separators = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m skipkeys = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m sort_keys = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m199\u001b[0m in \u001b[92mencode\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m196 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# This doesn't pass the iterator directly to ''.join() because the\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m197 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# exceptions aren't as detailed. The list call should be roughly\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m198 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[2m# equivalent to the PySequence_Fast that ''.join() would do.\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m199 \u001b[2m│ │ \u001b[0mchunks = \u001b[96mself\u001b[0m.iterencode(o, _one_shot=\u001b[94mTrue\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m200 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m \u001b[96misinstance\u001b[0m(chunks, (\u001b[96mlist\u001b[0m, \u001b[96mtuple\u001b[0m)): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m201 \u001b[0m\u001b[2m│ │ │ \u001b[0mchunks = \u001b[96mlist\u001b[0m(chunks) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m202 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[33m'\u001b[0m\u001b[33m'\u001b[0m.join(chunks) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m───────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10cca8d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰─────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m257\u001b[0m in \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[92miterencode\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m254 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mmarkers, \u001b[96mself\u001b[0m.default, _encoder, \u001b[96mself\u001b[0m.indent, floatstr, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m255 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m.key_separator, \u001b[96mself\u001b[0m.item_separator, \u001b[96mself\u001b[0m.sort_keys, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m256 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m.skipkeys, _one_shot) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m257 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _iterencode(o, \u001b[94m0\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m258 \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m259 \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_make_iterencode\u001b[0m(markers, _default, _encoder, _indent, _floatstr, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m260 \u001b[0m\u001b[2m│ │ \u001b[0m_key_separator, _item_separator, _sort_keys, _skipkeys, _one_shot, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _encoder = \u001b[1m<\u001b[0m\u001b[1;95mbuilt-in\u001b[0m\u001b[39m function encode_basestring_ascii\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _iterencode = \u001b[1m<\u001b[0m\u001b[1;95m_json.Encoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x169284ee0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m _one_shot = \u001b[94mTrue\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m floatstr = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m JSONEncoder.iterencode..floatstr at \u001b[0m\u001b[94m0x16957dbd0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m markers = \u001b[1m{\u001b[0m\u001b[94m6059591104\u001b[0m: \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m, \u001b[94m4609398032\u001b[0m: NOT_GIVEN\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = \u001b[1m[\u001b[0mNOT_GIVEN\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10cca8d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/json/\u001b[0m\u001b[1;33mencoder.py\u001b[0m:\u001b[94m179\u001b[0m in \u001b[92mdefault\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m176 \u001b[0m\u001b[2;33m│ │ │ │ \u001b[0m\u001b[33mreturn JSONEncoder.default(self, o)\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m177 \u001b[0m\u001b[2m│ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m178 \u001b[0m\u001b[2;33m│ │ \u001b[0m\u001b[33m\"\"\"\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m179 \u001b[2m│ │ \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mTypeError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mObject of type \u001b[0m\u001b[33m{\u001b[0mo.\u001b[91m__class__\u001b[0m.\u001b[91m__name__\u001b[0m\u001b[33m}\u001b[0m\u001b[33m \u001b[0m\u001b[33m'\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m180 \u001b[0m\u001b[2m│ │ │ │ │ │ \u001b[0m\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mis not JSON serializable\u001b[0m\u001b[33m'\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m181 \u001b[0m\u001b[2m│ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m182 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mencode\u001b[0m(\u001b[96mself\u001b[0m, o): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m───────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m o = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mjson.encoder.JSONEncoder\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x10cca8d00\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰─────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n\u001b[1;91mTypeError: \u001b[0mObject of type NotGiven is not JSON serializable\n" - }, - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717804927336.562 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717804928933.8398 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-05-26-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json b/logs/2024-06-07T17-05-26-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json deleted file mode 100644 index e1ce6e11..00000000 --- a/logs/2024-06-07T17-05-26-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json +++ /dev/null @@ -1,71 +0,0 @@ -{ - "version": 1, - "status": "error", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "hECF7Z795AWH3W8s7CaJHT", - "run_id": "6xoVBJNaHDJAC7Lcwtgfci", - "created": "2024-06-07T17:05:26-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 16, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-07T17:05:26-07:00", - "completed_at": "2024-06-07T17:05:26-07:00", - "model_usage": {} - }, - "error": { - "message": "NameError(\"name 'NOT_GIVEN' is not defined\")", - "traceback": "Traceback (most recent call last):\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 188, in task_run\n scores = await asyncio.gather(*tasks)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 283, in task_run_sample\n state = await solver(state, generate)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/solver/_solver.py\", line 201, in solve\n return await generate(state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 156, in generate\n return await task_generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/generate.py\", line 33, in task_generate\n output = await model.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 548, in generate\n return await self._generate(input, tools, tool_choice, config)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 635, in _generate\n model_output = await generate()\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 88, in async_wrapped\n return await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 47, in __call__\n do = self.iter(retry_state=retry_state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/__init__.py\", line 314, in iter\n return fut.result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 451, in result\n return self.__get_result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 403, in __get_result\n raise self._exception\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 50, in __call__\n result = await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 627, in generate\n return await self.api.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 142, in generate\n response: ChatCompletion = await self.client.chat.completions.create(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/langtrace_python_sdk/instrumentation/openai/patch.py\", line 603, in traced_method\n if kwargs.get(\"tools\") is not None and not NOT_GIVEN:\n\nNameError: name 'NOT_GIVEN' is not defined\n", - "traceback_ansi": "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m188\u001b[0m in \u001b[92mtask_run\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m283\u001b[0m in \u001b[92mtask_run_sample\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/solver/\u001b[0m\u001b[1;33m_solver.py\u001b[0m:\u001b[94m201\u001b[0m in \u001b[92msolve\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m156\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mgenerate.py\u001b[0m:\u001b[94m33\u001b[0m in \u001b[92mtask_generate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m ... 6 frames hidden ... \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/\u001b[0m\u001b[1;33m_base.py\u001b[0m:\u001b[94m40\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[94m3\u001b[0m in \u001b[92m__get_result\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m400 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__get_result\u001b[0m(\u001b[96mself\u001b[0m): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m401 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m._exception: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m402 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94mtry\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m403 \u001b[2m│ │ │ │ \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mself\u001b[0m._exception \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m404 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94mfinally\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m405 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[2m# Break a reference cycle with the exception in self._exception\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m406 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[96mself\u001b[0m = \u001b[94mNone\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m─\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰─────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mtenacity/\u001b[0m\u001b[1;33m_asyncio.py\u001b[0m:\u001b[94m50\u001b[0m in \u001b[92m__call__\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/model/\u001b[0m\u001b[1;33m_model.py\u001b[0m:\u001b[94m627\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/model/_providers/\u001b[0m\u001b[1;33mopenai.py\u001b[0m:\u001b[94m142\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mlangtrace_python_sdk/instrumentation/openai/\u001b[0m\u001b[1;33mpatch.py\u001b[0m:\u001b[94m603\u001b[0m in \u001b[92mtraced_method\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m600 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mfunctions\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m601 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94mfor\u001b[0m function \u001b[95min\u001b[0m kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mfunctions\u001b[0m\u001b[33m\"\u001b[0m): \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m602 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mtools.append(json.dumps({\u001b[33m\"\u001b[0m\u001b[33mtype\u001b[0m\u001b[33m\"\u001b[0m: \u001b[33m\"\u001b[0m\u001b[33mfunction\u001b[0m\u001b[33m\"\u001b[0m, \u001b[33m\"\u001b[0m\u001b[33mfunction\u001b[0m\u001b[33m\"\u001b[0m: function})) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m603 \u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \u001b[95mnot\u001b[0m NOT_GIVEN: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m604 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[2m# check if tool is an object\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m605 \u001b[0m\u001b[2m│ │ │ \u001b[0mtools.append(json.dumps(kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mtools\u001b[0m\u001b[33m\"\u001b[0m))) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m606 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mlen\u001b[0m(tools) > \u001b[94m0\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ahandle_streaming_response = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39masync_chat_completions_create..ahandle_streaming_respo…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39mat \u001b[0m\u001b[94m0x130851480\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m 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\u001b[33m'Azure'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m span_attributes = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.sdk.name'\u001b[0m: \u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.name'\u001b[0m: \u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.type'\u001b[0m: \u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.version'\u001b[0m: \u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.version'\u001b[0m: \u001b[33m'2.1.13'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'url.full'\u001b[0m: \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33m'https://test-openai-scale3.openai.azure.com/openai/deployment…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.api'\u001b[0m: \u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.prompts'\u001b[0m: \u001b[33m'\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m{\u001b[0m\u001b[33m\"role\": \"user\", \"content\": \"\\\\nHow do I \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mprevent SQL Injection attacks?\\\\n\\\\nBefor'\u001b[0m+\u001b[94m218\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.stream'\u001b[0m: \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tools = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tracer = \u001b[1m<\u001b[0m\u001b[1;95mopentelemetry.sdk.trace.Tracer\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x1308701c0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m version = \u001b[33m'1.30.3'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m wrapped = \u001b[1m<\u001b[0m\u001b[1;95mbound\u001b[0m\u001b[39m method AsyncCompletions.create of \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39m\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n\u001b[1;91mNameError: \u001b[0mname \u001b[32m'NOT_GIVEN'\u001b[0m is not defined\n" - }, - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717805124666.306 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717805126228.8 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-05-56-07-00_security-guide_c5gUYigs5mMm4BXwZf3Pv9.json b/logs/2024-06-07T17-05-56-07-00_security-guide_c5gUYigs5mMm4BXwZf3Pv9.json deleted file mode 100644 index 33386c0f..00000000 --- a/logs/2024-06-07T17-05-56-07-00_security-guide_c5gUYigs5mMm4BXwZf3Pv9.json +++ /dev/null @@ -1,181 +0,0 @@ -{ - "version": 1, - "status": "error", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "c5gUYigs5mMm4BXwZf3Pv9", - "run_id": "VZkXpxXpnUzURHGguC8Ai9", - "created": "2024-06-07T17:05:56-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 16, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-07T17:05:56-07:00", - "completed_at": "2024-06-07T17:05:58-07:00", - "model_usage": {} - }, - "error": { - "message": "Error code: 404 - {'error': {'code': 'DeploymentNotFound', 'message': 'The API deployment for this resource does not exist. If you created the deployment within the last 5 minutes, please wait a moment and try again.'}}", - "traceback": "Traceback (most recent call last):\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 188, in task_run\n scores = await asyncio.gather(*tasks)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 283, in task_run_sample\n state = await solver(state, generate)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/solver/_solver.py\", line 201, in solve\n return await generate(state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/run.py\", line 156, in generate\n return await task_generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/_eval/task/generate.py\", line 33, in task_generate\n output = await model.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 548, in generate\n return await self._generate(input, tools, tool_choice, config)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 635, in _generate\n model_output = await generate()\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 88, in async_wrapped\n return await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 47, in __call__\n do = self.iter(retry_state=retry_state)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/__init__.py\", line 314, in iter\n return fut.result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 451, in result\n return self.__get_result()\n\n File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/concurrent/futures/_base.py\", line 403, in __get_result\n raise self._exception\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/tenacity/_asyncio.py\", line 50, in __call__\n result = await fn(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_model.py\", line 627, in generate\n return await self.api.generate(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 165, in generate\n completion, error = handle_content_filter_error(e)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 384, in handle_content_filter_error\n raise e\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/inspect_ai/model/_providers/openai.py\", line 142, in generate\n response: ChatCompletion = await self.client.chat.completions.create(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/langtrace_python_sdk/instrumentation/openai/patch.py\", line 622, in traced_method\n result = await wrapped(*args, **kwargs)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/openai/resources/chat/completions.py\", line 1181, in create\n return await self._post(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/openai/_base_client.py\", line 1790, in post\n return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/openai/_base_client.py\", line 1493, in request\n return await self._request(\n\n File \"/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/openai/_base_client.py\", line 1584, in _request\n raise self._make_status_error_from_response(err.response) from None\n\nopenai.NotFoundError: Error code: 404 - {'error': {'code': 'DeploymentNotFound', 'message': 'The API deployment for this resource does not exist. If you created the deployment within the last 5 minutes, please wait a moment and try again.'}}\n", - "traceback_ansi": "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m188\u001b[0m in \u001b[92mtask_run\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m283\u001b[0m in \u001b[92mtask_run_sample\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/solver/\u001b[0m\u001b[1;33m_solver.py\u001b[0m:\u001b[94m201\u001b[0m in \u001b[92msolve\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mrun.py\u001b[0m:\u001b[94m156\u001b[0m in \u001b[92mgenerate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33minspect_ai/_eval/task/\u001b[0m\u001b[1;33mgenerate.py\u001b[0m:\u001b[94m33\u001b[0m in \u001b[92mtask_generate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[3;31m ... 12 frames hidden ... \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mlangtrace_python_sdk/instrumentation/openai/\u001b[0m\u001b[1;33mpatch.py\u001b[0m:\u001b[94m622\u001b[0m in \u001b[92mtraced_method\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m619 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mspan.set_attribute(field, value) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m620 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mtry\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m621 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[2m# Attempt to call the original method\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m622 \u001b[2m│ │ │ \u001b[0mresult = \u001b[94mawait\u001b[0m wrapped(*args, **kwargs) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m623 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94mif\u001b[0m kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mstream\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mis\u001b[0m \u001b[94mFalse\u001b[0m \u001b[95mor\u001b[0m kwargs.get(\u001b[33m\"\u001b[0m\u001b[33mstream\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m624 \u001b[0m\u001b[2m│ │ │ │ \u001b[0mspan.set_attribute(\u001b[33m\"\u001b[0m\u001b[33mllm.model\u001b[0m\u001b[33m\"\u001b[0m, result.model) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m625 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[96mhasattr\u001b[0m(result, \u001b[33m\"\u001b[0m\u001b[33mchoices\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mand\u001b[0m result.choices \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m ahandle_streaming_response = \u001b[1m<\u001b[0m\u001b[1;95mfunction\u001b[0m\u001b[39m \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39masync_chat_completions_create..ahandle_streaming_respo…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39mat \u001b[0m\u001b[94m0x13486d480\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m args = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m attributes = \u001b[1;35mLLMSpanAttributes\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_name\u001b[0m=\u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_type\u001b[0m=\u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_service_version\u001b[0m=\u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_version\u001b[0m=\u001b[33m'2.1.13'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mlangtrace_sdk_name\u001b[0m=\u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33murl_full\u001b[0m=\u001b[33m'https://test-openai-scale3.openai.azure.com/openai/d…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_api\u001b[0m=\u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_model\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_temperature\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_top_p\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_top_k\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_user\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_system_fingerprint\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_prompts\u001b[0m=\u001b[33m'\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m{\u001b[0m\u001b[33m\"role\": \"user\", \"content\": \"\\\\nHow should I \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mstore passwords securely for an aut'\u001b[0m+\u001b[94m255\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_responses\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_token_counts\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mllm_stream\u001b[0m=\u001b[94mFalse\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ 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\u001b[33m'https://test-openai-scale3.openai.azure.com/openai/deployment…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m extra_attributes = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m field = \u001b[33m'langtrace.testId'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m instance = \u001b[1m<\u001b[0m\u001b[1;95mopenai.resources.chat.completions.AsyncCompletions\u001b[0m\u001b[39m object at \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[94m0x16bbc94b0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m item = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m 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\u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow should I store passwords securely\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mfor an authentication system database?\\n\\nB'\u001b[0m+\u001b[94m216\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m]\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'tools'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'tool_choice'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m 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\u001b[2m│ \u001b[0m\u001b[33m'logit_bias'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m...\u001b[0m +\u001b[94m7\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m llm_prompts = \u001b[1m[\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow should I store passwords securely for\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33man authentication system database?\\n\\nB'\u001b[0m+\u001b[94m216\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m service_provider = \u001b[33m'Azure'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m span = \u001b[1;35m_Span\u001b[0m\u001b[1m(\u001b[0m\u001b[33mname\u001b[0m=\u001b[33m\"openai\u001b[0m\u001b[33m.chat.completions.create\"\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mcontext\u001b[0m=\u001b[1;35mSpanContext\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtrace_id\u001b[0m=\u001b[94m0x25394daf2a2bc24a8296e85ef20759b…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mspan_id\u001b[0m=\u001b[94m0x2a8644296fd07975\u001b[0m, \u001b[33mtrace_flags\u001b[0m=\u001b[94m0x01\u001b[0m, \u001b[33mtrace_state\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m]\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mis_remote\u001b[0m=\u001b[94mFalse\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m span_attributes = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.sdk.name'\u001b[0m: \u001b[33m'langtrace-python-sdk'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.name'\u001b[0m: \u001b[33m'Azure'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.type'\u001b[0m: \u001b[33m'llm'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.service.version'\u001b[0m: \u001b[33m'1.30.3'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'langtrace.version'\u001b[0m: \u001b[33m'2.1.13'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'url.full'\u001b[0m: \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33m'https://test-openai-scale3.openai.azure.com/openai/deployment…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.api'\u001b[0m: \u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.prompts'\u001b[0m: \u001b[33m'\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m{\u001b[0m\u001b[33m\"role\": \"user\", \"content\": \"\\\\nHow should\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mI store passwords securely for an aut'\u001b[0m+\u001b[94m255\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'llm.stream'\u001b[0m: \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tools = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tracer = \u001b[1m<\u001b[0m\u001b[1;95mopentelemetry.sdk.trace.Tracer\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x13484edd0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m value = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m version = \u001b[33m'1.30.3'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m wrapped = \u001b[1m<\u001b[0m\u001b[1;95mbound\u001b[0m\u001b[39m method AsyncCompletions.create of \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[39m\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mopenai/resources/chat/\u001b[0m\u001b[1;33mcompletions.py\u001b[0m:\u001b[94m1181\u001b[0m in \u001b[92mcreate\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1178 \u001b[0m\u001b[2m│ │ \u001b[0mextra_body: Body | \u001b[94mNone\u001b[0m = \u001b[94mNone\u001b[0m, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1179 \u001b[0m\u001b[2m│ │ \u001b[0mtimeout: \u001b[96mfloat\u001b[0m | httpx.Timeout | \u001b[94mNone\u001b[0m | NotGiven = NOT_GIVEN, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1180 \u001b[0m\u001b[2m│ \u001b[0m) -> ChatCompletion | AsyncStream[ChatCompletionChunk]: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1181 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mawait\u001b[0m \u001b[96mself\u001b[0m._post( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1182 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[33m\"\u001b[0m\u001b[33m/chat/completions\u001b[0m\u001b[33m\"\u001b[0m, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1183 \u001b[0m\u001b[2m│ │ │ \u001b[0mbody=\u001b[94mawait\u001b[0m async_maybe_transform( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1184 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m{ \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m extra_body = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m extra_headers = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m extra_query = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m frequency_penalty = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m function_call = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m functions = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m logit_bias = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m logprobs = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m max_tokens = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m messages = \u001b[1m[\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow should I store passwords securely for an \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mauthentication system database?\\n\\nB'\u001b[0m+\u001b[94m216\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m model = \u001b[33m'gpt-3.5-turbo'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m n = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m presence_penalty = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m response_format = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m seed = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mopenai.resources.chat.completions.AsyncCompletions\u001b[0m\u001b[39m object at \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[94m0x16bbc94b0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stop = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream_options = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m temperature = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m timeout = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tool_choice = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m tools = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m top_logprobs = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m top_p = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m user = NOT_GIVEN \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mopenai/\u001b[0m\u001b[1;33m_base_client.py\u001b[0m:\u001b[94m1790\u001b[0m in \u001b[92mpost\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1787 \u001b[0m\u001b[2m│ │ \u001b[0mopts = FinalRequestOptions.construct( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1788 \u001b[0m\u001b[2m│ │ │ \u001b[0mmethod=\u001b[33m\"\u001b[0m\u001b[33mpost\u001b[0m\u001b[33m\"\u001b[0m, url=path, json_data=body, files=\u001b[94mawait\u001b[0m async_to_httpx_files(fi \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1789 \u001b[0m\u001b[2m│ │ \u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1790 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mawait\u001b[0m \u001b[96mself\u001b[0m.request(cast_to, opts, stream=stream, stream_cls=stream_cls) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1791 \u001b[0m\u001b[2m│ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1792 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94masync\u001b[0m \u001b[94mdef\u001b[0m \u001b[92mpatch\u001b[0m( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1793 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mself\u001b[0m, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m body = \u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'messages'\u001b[0m: \u001b[1m[\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow should I store passwords securely for an \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mauthentication system database?\\n\\nB'\u001b[0m+\u001b[94m216\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m]\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'model'\u001b[0m: \u001b[33m'gpt-3.5-turbo'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'frequency_penalty'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'function_call'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'functions'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'logit_bias'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'logprobs'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'max_tokens'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'n'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m'presence_penalty'\u001b[0m: NOT_GIVEN, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33m...\u001b[0m +\u001b[94m11\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m cast_to = \u001b[1m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[33m'openai.types.chat.chat_completion.ChatCompletion'\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m files = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m options = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m opts = \u001b[1;35mFinalRequestOptions\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mmethod\u001b[0m=\u001b[33m'post'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33murl\u001b[0m=\u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mparams\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mheaders\u001b[0m=\u001b[1m{\u001b[0m\u001b[33m'api-key'\u001b[0m: \u001b[33m'815bbc358b7e47cbb834fb9422dbcfee'\u001b[0m\u001b[1m}\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mmax_retries\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mtimeout\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mfiles\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33midempotency_key\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mpost_parser\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mjson_data\u001b[0m=\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'messages'\u001b[0m: \u001b[1m[\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ │ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow should I store passwords securely for an \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33mauthentication system database?\\n\\nB'\u001b[0m+\u001b[94m216\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m]\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'model'\u001b[0m: \u001b[33m'gpt-3.5-turbo'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'stream'\u001b[0m: \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mextra_json\u001b[0m=\u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m path = \u001b[33m'/chat/completions'\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mopenai.lib.azure.AsyncAzureOpenAI\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x115c088b0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream_cls = openai.AsyncStream\u001b[1m[\u001b[0mopenai.types.chat.chat_completion_chunk.ChatCompletionChunk\u001b[1m]\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mopenai/\u001b[0m\u001b[1;33m_base_client.py\u001b[0m:\u001b[94m1493\u001b[0m in \u001b[92mrequest\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1490 \u001b[0m\u001b[2m│ │ \u001b[0mstream_cls: \u001b[96mtype\u001b[0m[_AsyncStreamT] | \u001b[94mNone\u001b[0m = \u001b[94mNone\u001b[0m, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1491 \u001b[0m\u001b[2m│ │ \u001b[0mremaining_retries: Optional[\u001b[96mint\u001b[0m] = \u001b[94mNone\u001b[0m, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1492 \u001b[0m\u001b[2m│ \u001b[0m) -> ResponseT | _AsyncStreamT: \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1493 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mawait\u001b[0m \u001b[96mself\u001b[0m._request( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1494 \u001b[0m\u001b[2m│ │ │ \u001b[0mcast_to=cast_to, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1495 \u001b[0m\u001b[2m│ │ │ \u001b[0moptions=options, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1496 \u001b[0m\u001b[2m│ │ │ \u001b[0mstream=stream, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m cast_to = \u001b[1m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[33m'openai.types.chat.chat_completion.ChatCompletion'\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m options = \u001b[1;35mFinalRequestOptions\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mmethod\u001b[0m=\u001b[33m'post'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33murl\u001b[0m=\u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mparams\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mheaders\u001b[0m=\u001b[1m{\u001b[0m\u001b[33m'api-key'\u001b[0m: \u001b[33m'815bbc358b7e47cbb834fb9422dbcfee'\u001b[0m\u001b[1m}\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mmax_retries\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mtimeout\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mfiles\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33midempotency_key\u001b[0m=\u001b[94mNone\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mpost_parser\u001b[0m=\u001b[35mNOT_GIVEN\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mjson_data\u001b[0m=\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'messages'\u001b[0m: \u001b[1m[\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[1m{\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ │ \u001b[0m\u001b[33m'role'\u001b[0m: \u001b[33m'user'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ │ \u001b[0m\u001b[33m'content'\u001b[0m: \u001b[33m'\\nHow should I store passwords securely for \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33man authentication system database?\\n\\nB'\u001b[0m+\u001b[94m216\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ │ \u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[1m]\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'model'\u001b[0m: \u001b[33m'gpt-3.5-turbo'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ │ \u001b[0m\u001b[33m'stream'\u001b[0m: \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mextra_json\u001b[0m=\u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m remaining_retries = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mopenai.lib.azure.AsyncAzureOpenAI\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x115c088b0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream_cls = openai.AsyncStream\u001b[1m[\u001b[0mopenai.types.chat.chat_completion_chunk.ChatCompleti… \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/env/lib/python3.10/site-packages/\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33mopenai/\u001b[0m\u001b[1;33m_base_client.py\u001b[0m:\u001b[94m1584\u001b[0m in \u001b[92m_request\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1581 \u001b[0m\u001b[2m│ │ │ │ \u001b[0m\u001b[94mawait\u001b[0m err.response.aread() \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1582 \u001b[0m\u001b[2m│ │ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1583 \u001b[0m\u001b[2m│ │ │ \u001b[0mlog.debug(\u001b[33m\"\u001b[0m\u001b[33mRe-raising status error\u001b[0m\u001b[33m\"\u001b[0m) \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1584 \u001b[2m│ │ │ \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mself\u001b[0m._make_status_error_from_response(err.response) \u001b[94mfrom\u001b[0m \u001b[94mNone\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1585 \u001b[0m\u001b[2m│ │ \u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1586 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mawait\u001b[0m \u001b[96mself\u001b[0m._process_response( \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2m1587 \u001b[0m\u001b[2m│ │ │ \u001b[0mcast_to=cast_to, \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╭─\u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m locals \u001b[0m\u001b[33m──────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m cast_to = \u001b[1m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[33m'openai.types.chat.chat_completion.ChatCompletion'\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m kwargs = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m options = \u001b[1;35mFinalRequestOptions\u001b[0m\u001b[1m(\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33mmethod\u001b[0m=\u001b[33m'post'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ \u001b[0m\u001b[33murl\u001b[0m=\u001b[33m'/chat/completions'\u001b[0m, \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[2m│ 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\u001b[0m\u001b[33mextra_json\u001b[0m=\u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[1m)\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m remaining_retries = \u001b[94mNone\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m request = \u001b[1m<\u001b[0m\u001b[1;35mRequest\u001b[0m\u001b[1;39m(\u001b[0m\u001b[33m'POST'\u001b[0m\u001b[39m, \u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m \u001b[33m'https://test-openai-scale3.openai.azure.com/openai/deployments/gpt-3.5…\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m response = \u001b[1m<\u001b[0m\u001b[1;95mResponse\u001b[0m\u001b[39m \u001b[0m\u001b[1;39m[\u001b[0m\u001b[94m404\u001b[0m\u001b[39m Not Found\u001b[0m\u001b[1;39m]\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m retries = \u001b[94m5\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m self = \u001b[1m<\u001b[0m\u001b[1;95mopenai.lib.azure.AsyncAzureOpenAI\u001b[0m\u001b[39m object at \u001b[0m\u001b[94m0x115c088b0\u001b[0m\u001b[1m>\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream = \u001b[94mFalse\u001b[0m \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m│\u001b[0m stream_cls = openai.AsyncStream\u001b[1m[\u001b[0mopenai.types.chat.chat_completion_chunk.ChatCompleti… \u001b[33m│\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[33m╰──────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[31m│\u001b[0m\n\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n\u001b[1;91mNotFoundError: \u001b[0mError code: \u001b[1;36m404\u001b[0m - \u001b[1m{\u001b[0m\u001b[32m'error'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'code'\u001b[0m: \u001b[32m'DeploymentNotFound'\u001b[0m, \u001b[32m'message'\u001b[0m: \u001b[32m'The API deployment for this resource does not exist. If you created \u001b[0m\n\u001b[32mthe deployment within the last 5 minutes, please wait a moment and try again.'\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m\n" - }, - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717805155142.8489 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717805156796.118 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805156900.019 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805156904.203 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805156994.0269 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805156997.531 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157008.96 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157013.0042 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157023.6611 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157026.804 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157038.014 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157041.0837 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157052.022 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157055.167 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157067.382 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157071.043 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157081.305 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157084.5042 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157095.0808 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157098.758 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157109.112 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157112.9019 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157685.484 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805157690.0178 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-17-46-07-00_security-guide_8TXTQPM5DzadcwKdZVC4ra.json b/logs/2024-06-07T17-17-46-07-00_security-guide_8TXTQPM5DzadcwKdZVC4ra.json deleted file mode 100644 index 69e430c7..00000000 --- a/logs/2024-06-07T17-17-46-07-00_security-guide_8TXTQPM5DzadcwKdZVC4ra.json +++ /dev/null @@ -1,1852 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "8TXTQPM5DzadcwKdZVC4ra", - "run_id": "UA4g7DNEVGe3ax2zecGHtz", - "created": "2024-06-07T17:17:46-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 16, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 1.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-07T17:17:46-07:00", - "completed_at": "2024-06-07T17:18:05-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 23771, - "output_tokens": 10187, - "total_tokens": 33958 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what SQL Injection attacks are: SQL Injection is a type of security vulnerability that occurs when an attacker is able to manipulate input data in a way that it alters the SQL queries being executed by the application.\n\n2. Use parameterized queries: Parameterized queries separate SQL code from user input by using parameters instead of directly inserting user input into the query. This prevents attackers from injecting malicious code into the query.\n\n3. Input validation: Validate and sanitize all input data to ensure that it meets expected criteria before using it in a SQL query. This can help prevent attackers from injecting malicious code.\n\n4. Use stored procedures: Stored procedures can help prevent SQL Injection by precompiling the SQL query and only allowing parameters to be passed into the query.\n\n5. Limit permissions: Ensure that the application's database user only has the necessary permissions to carry out its intended tasks. This can help minimize the potential damage from a successful SQL Injection attack.\n\n6. Regularly update and patch your database: Keeping your database system up to date with the latest security patches can help protect against known vulnerabilities that could be exploited by attackers.\n\nANSWER: To prevent SQL Injection attacks, use parameterized queries, validate and sanitize input data, use stored procedures, limit permissions, and regularly update and patch your database.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: 1. Understand what SQL Injection attacks are: SQL Injection is a type of security vulnerability that occurs when an attacker is able to manipulate input data in a way that it alters the SQL queries being executed by the application.\n\n2. Use parameterized queries: Parameterized queries separate SQL code from user input by using parameters instead of directly inserting user input into the query. This prevents attackers from injecting malicious code into the query.\n\n3. Input validation: Validate and sanitize all input data to ensure that it meets expected criteria before using it in a SQL query. This can help prevent attackers from injecting malicious code.\n\n4. Use stored procedures: Stored procedures can help prevent SQL Injection by precompiling the SQL query and only allowing parameters to be passed into the query.\n\n5. Limit permissions: Ensure that the application's database user only has the necessary permissions to carry out its intended tasks. This can help minimize the potential damage from a successful SQL Injection attack.\n\n6. Regularly update and patch your database: Keeping your database system up to date with the latest security patches can help protect against known vulnerabilities that could be exploited by attackers.\n\nANSWER: To prevent SQL Injection attacks, use parameterized queries, validate and sanitize input data, use stored procedures, limit permissions, and regularly update and patch your database.\n***\n[Critique]: The answer provided is overall comprehensive and covers various important strategies to prevent SQL Injection attacks. However, it would be beneficial to provide a bit more detail or explanation for each point to help the reader understand the importance and implementation of each strategy. Additionally, it could be helpful to provide examples or further resources for each strategy to enhance the reader's understanding.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer:\n1. Understanding SQL Injection attacks is crucial to implementing effective prevention strategies. SQL Injection is a vulnerability that occurs when attackers manipulate input data to alter SQL queries executed by an application.\n2. Implement parameterized queries to separate SQL code from user input, preventing attackers from injecting malicious code.\n3. Validate and sanitize all input data to ensure it adheres to expected criteria before utilizing it in SQL queries, thereby thwarting injection attempts.\n4. Leverage stored procedures to precompile SQL queries and only allow parameter passing, increasing security against SQL Injection.\n5. Limit database user permissions to necessary tasks to minimize potential damage from successful attacks.\n6. Regularly update and patch the database to safeguard against known vulnerabilities that attackers may exploit.\n\nANSWER: To prevent SQL Injection attacks, utilize strategies such as parameterized queries, input validation, stored procedures, permission limitations, and regular database updates and patches.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer:\n1. Understanding SQL Injection attacks is crucial to implementing effective prevention strategies. SQL Injection is a vulnerability that occurs when attackers manipulate input data to alter SQL queries executed by an application.\n2. Implement parameterized queries to separate SQL code from user input, preventing attackers from injecting malicious code.\n3. Validate and sanitize all input data to ensure it adheres to expected criteria before utilizing it in SQL queries, thereby thwarting injection attempts.\n4. Leverage stored procedures to precompile SQL queries and only allow parameter passing, increasing security against SQL Injection.\n5. Limit database user permissions to necessary tasks to minimize potential damage from successful attacks.\n6. Regularly update and patch the database to safeguard against known vulnerabilities that attackers may exploit.\n\nANSWER: To prevent SQL Injection attacks, utilize strategies such as parameterized queries, input validation, stored procedures, permission limitations, and regular database updates and patches.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 763, - "output_tokens": 180, - "total_tokens": 943 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer:\n1. Understanding SQL Injection attacks is crucial to implementing effective prevention strategies. SQL Injection is a vulnerability that occurs when attackers manipulate input data to alter SQL queries executed by an application.\n2. Implement parameterized queries to separate SQL code from user input, preventing attackers from injecting malicious code.\n3. Validate and sanitize all input data to ensure it adheres to expected criteria before utilizing it in SQL queries, thereby thwarting injection attempts.\n4. Leverage stored procedures to precompile SQL queries and only allow parameter passing, increasing security against SQL Injection.\n5. Limit database user permissions to necessary tasks to minimize potential damage from successful attacks.\n6. Regularly update and patch the database to safeguard against known vulnerabilities that attackers may exploit.\n\nANSWER: To prevent SQL Injection attacks, utilize strategies such as parameterized queries, input validation, stored procedures, permission limitations, and regular database updates and patches.", - "explanation": "1. Both the expert and submission mention the use of parameterized queries to prevent SQL Injection attacks.\n2. The expert emphasizes the importance of using parameterized queries and prepared statements, while the submission goes into more detail about the process and reasons behind using parameterized queries.\n3. The submission expands on the concept by mentioning the importance of input validation, stored procedures, permission limitations, and regular updates and patches, which are all additional strategies to prevent SQL Injection attacks.\n\nBased on the above comparison, the submission contains the content present in the expert answer and even expands on it with additional information and strategies.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improved Answer:\n1. Understanding SQL Injection attacks is crucial to implementing effective prevention strategies. SQL Injection is a vulnerability that occurs when attackers manipulate input data to alter SQL queries executed by an application.\n2. Implement parameterized queries to separate SQL code from user input, preventing attackers from injecting malicious code.\n3. Validate and sanitize all input data to ensure it adheres to expected criteria before utilizing it in SQL queries, thereby thwarting injection attempts.\n4. Leverage stored procedures to precompile SQL queries and only allow parameter passing, increasing security against SQL Injection.\n5. Limit database user permissions to necessary tasks to minimize potential damage from successful attacks.\n6. Regularly update and patch the database to safeguard against known vulnerabilities that attackers may exploit.\n\nANSWER: To prevent SQL Injection attacks, utilize strategies such as parameterized queries, input validation, stored procedures, permission limitations, and regular database updates and patches.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Both the expert and submission mention the use of parameterized queries to prevent SQL Injection attacks.\n2. The expert emphasizes the importance of using parameterized queries and prepared statements, while the submission goes into more detail about the process and reasons behind using parameterized queries.\n3. The submission expands on the concept by mentioning the importance of input validation, stored procedures, permission limitations, and regular updates and patches, which are all additional strategies to prevent SQL Injection attacks.\n\nBased on the above comparison, the submission contains the content present in the expert answer and even expands on it with additional information and strategies.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 2, - "epoch": 1, - "input": [ - { - "content": "How do I prevent sqli?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent sqli?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what SQL injection (SQLi) is: SQL injection is a type of cyber attack that allows attackers to execute malicious SQL statements that can control a web application's database server.\n\n2. Use parameterized queries: Instead of building SQL queries by concatenating strings, use parameterized queries provided by your programming language or ORM. This helps to separate the SQL code from the data being input, preventing attackers from injecting their own malicious SQL code.\n\n3. Sanitize input data: Before using any input from users, make sure to sanitize it by removing special characters or using input validation techniques. This can help prevent attackers from inserting SQL code through input fields.\n\n4. Use least privilege principle: Ensure that your database user account has the minimum required permissions to perform its tasks. This way, even if a SQL injection attack is successful, the attacker's access will be limited.\n\n5. Regularly update and patch your software: Keep your web application, database server, and other software up to date with the latest security patches. Many SQL injection attacks exploit known vulnerabilities that can be mitigated by applying patches.\n\n6. Implement a web application firewall (WAF): A WAF can help detect and block malicious SQL injection attempts before they reach your web application.\n\n7. Educate your developers: Make sure your developers are aware of SQL injection risks and best practices for preventing them. Provide training and guidance on secure coding practices.\n\nANSWER: Implement the mentioned steps to prevent SQL injection attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent sqli?\n***\n[Answer]: 1. Understand what SQL injection (SQLi) is: SQL injection is a type of cyber attack that allows attackers to execute malicious SQL statements that can control a web application's database server.\n\n2. Use parameterized queries: Instead of building SQL queries by concatenating strings, use parameterized queries provided by your programming language or ORM. This helps to separate the SQL code from the data being input, preventing attackers from injecting their own malicious SQL code.\n\n3. Sanitize input data: Before using any input from users, make sure to sanitize it by removing special characters or using input validation techniques. This can help prevent attackers from inserting SQL code through input fields.\n\n4. Use least privilege principle: Ensure that your database user account has the minimum required permissions to perform its tasks. This way, even if a SQL injection attack is successful, the attacker's access will be limited.\n\n5. Regularly update and patch your software: Keep your web application, database server, and other software up to date with the latest security patches. Many SQL injection attacks exploit known vulnerabilities that can be mitigated by applying patches.\n\n6. Implement a web application firewall (WAF): A WAF can help detect and block malicious SQL injection attempts before they reach your web application.\n\n7. Educate your developers: Make sure your developers are aware of SQL injection risks and best practices for preventing them. Provide training and guidance on secure coding practices.\n\nANSWER: Implement the mentioned steps to prevent SQL injection attacks.\n***\n[Critique]: Overall, the answer provides good steps to prevent SQL injection attacks. However, the answer could benefit from expanding on each step with more detailed explanations and examples to help the reader better understand how to implement them. Additionally, providing specific tools or resources that can aid in implementing each step would be beneficial. Lastly, the answer could have included a conclusion summarizing the importance of proactive measures in preventing SQL injection attacks.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the Answer:\n\n1. Understand what SQL injection (SQLi) is: Explain how SQL injection works, the potential impact it can have on a system, and provide real-world examples of SQL injection attacks.\n2. Use parameterized queries: Provide a step-by-step example of how to implement parameterized queries in a popular programming language, such as Python or Java.\n3. Sanitize input data: Discuss different methods of input validation and sanitization techniques, along with examples of when and how to use them effectively.\n4. Use least privilege principle: Explain the concept of least privilege and give practical advice on how to set up limited permissions for a database user account.\n5. Regularly update and patch your software: Highlight the importance of staying proactive about software updates and provide tips on maintaining a patch management process.\n6. Implement a web application firewall (WAF): Discuss the benefits of using a WAF, recommend specific WAF solutions, and explain how they can complement other security measures.\n7. Educate your developers: Offer resources for developer training on secure coding practices, recommend online courses or workshops, and stress the importance of ongoing education in cybersecurity.\n\nANSWER: Implement the mentioned steps to prevent SQL injection attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the Answer:\n\n1. Understand what SQL injection (SQLi) is: Explain how SQL injection works, the potential impact it can have on a system, and provide real-world examples of SQL injection attacks.\n2. Use parameterized queries: Provide a step-by-step example of how to implement parameterized queries in a popular programming language, such as Python or Java.\n3. Sanitize input data: Discuss different methods of input validation and sanitization techniques, along with examples of when and how to use them effectively.\n4. Use least privilege principle: Explain the concept of least privilege and give practical advice on how to set up limited permissions for a database user account.\n5. Regularly update and patch your software: Highlight the importance of staying proactive about software updates and provide tips on maintaining a patch management process.\n6. Implement a web application firewall (WAF): Discuss the benefits of using a WAF, recommend specific WAF solutions, and explain how they can complement other security measures.\n7. Educate your developers: Offer resources for developer training on secure coding practices, recommend online courses or workshops, and stress the importance of ongoing education in cybersecurity.\n\nANSWER: Implement the mentioned steps to prevent SQL injection attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 851, - "output_tokens": 246, - "total_tokens": 1097 - } - }, - "score": { - "value": "C", - "answer": "Improving the Answer:\n\n1. Understand what SQL injection (SQLi) is: Explain how SQL injection works, the potential impact it can have on a system, and provide real-world examples of SQL injection attacks.\n2. Use parameterized queries: Provide a step-by-step example of how to implement parameterized queries in a popular programming language, such as Python or Java.\n3. Sanitize input data: Discuss different methods of input validation and sanitization techniques, along with examples of when and how to use them effectively.\n4. Use least privilege principle: Explain the concept of least privilege and give practical advice on how to set up limited permissions for a database user account.\n5. Regularly update and patch your software: Highlight the importance of staying proactive about software updates and provide tips on maintaining a patch management process.\n6. Implement a web application firewall (WAF): Discuss the benefits of using a WAF, recommend specific WAF solutions, and explain how they can complement other security measures.\n7. Educate your developers: Offer resources for developer training on secure coding practices, recommend online courses or workshops, and stress the importance of ongoing education in cybersecurity.\n\nANSWER: Implement the mentioned steps to prevent SQL injection attacks.", - "explanation": "1. The expert answer mentions using parameterized queries and prepared statements as a way to prevent SQL injection (SQLi).\n2. The submission includes this point in its list of steps to prevent SQL injection attacks, which aligns with the expert answer.\n3. The submission expands on the steps by providing additional detailed information and examples on how to prevent SQL injection attacks, such as explaining SQL injection, input validation, least privilege principle, software updates, web application firewall, and developer education.\n4. Overall, the submission covers the same main concept as the expert answer (using parameterized queries) and further elaborates on it with additional preventive measures.\n5. The submission does not contradict the expert answer but rather provides supplemental information.\n\nTherefore, after considering all the points mentioned above, the submission does contain the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent sqli?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improving the Answer:\n\n1. Understand what SQL injection (SQLi) is: Explain how SQL injection works, the potential impact it can have on a system, and provide real-world examples of SQL injection attacks.\n2. Use parameterized queries: Provide a step-by-step example of how to implement parameterized queries in a popular programming language, such as Python or Java.\n3. Sanitize input data: Discuss different methods of input validation and sanitization techniques, along with examples of when and how to use them effectively.\n4. Use least privilege principle: Explain the concept of least privilege and give practical advice on how to set up limited permissions for a database user account.\n5. Regularly update and patch your software: Highlight the importance of staying proactive about software updates and provide tips on maintaining a patch management process.\n6. Implement a web application firewall (WAF): Discuss the benefits of using a WAF, recommend specific WAF solutions, and explain how they can complement other security measures.\n7. Educate your developers: Offer resources for developer training on secure coding practices, recommend online courses or workshops, and stress the importance of ongoing education in cybersecurity.\n\nANSWER: Implement the mentioned steps to prevent SQL injection attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using parameterized queries and prepared statements as a way to prevent SQL injection (SQLi).\n2. The submission includes this point in its list of steps to prevent SQL injection attacks, which aligns with the expert answer.\n3. The submission expands on the steps by providing additional detailed information and examples on how to prevent SQL injection attacks, such as explaining SQL injection, input validation, least privilege principle, software updates, web application firewall, and developer education.\n4. Overall, the submission covers the same main concept as the expert answer (using parameterized queries) and further elaborates on it with additional preventive measures.\n5. The submission does not contradict the expert answer but rather provides supplemental information.\n\nTherefore, after considering all the points mentioned above, the submission does contain the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 3, - "epoch": 1, - "input": [ - { - "content": "How do I prevent cross site scripting?", - "source": "input", - "role": "user" - } - ], - "target": "output encoding with secure by default libraries and input validation", - "messages": [ - { - "content": "\nHow do I prevent cross site scripting?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what cross site scripting (XSS) is and how it works. XSS is a type of cyber attack where attackers inject malicious scripts into web pages viewed by other users.\n\n2. Validate and sanitize user input. Make sure all input from users is validated and sanitized before being displayed on the web page. This includes data entered through forms, URLs, and cookies.\n\n3. Use secure coding practices. Ensure that your code follows best practices for web development, including using the latest security guidelines and avoiding insecure functions that can be exploited by attackers.\n\n4. Implement Content Security Policy (CSP). CSP is a security standard that helps prevent XSS attacks by allowing you to restrict the sources from which certain types of content can be loaded on your website.\n\n5. Use HTTP headers. Set HTTP headers such as X-XSS-Protection and Content-Type options to help prevent XSS attacks. These headers can help prevent browsers from executing malicious scripts.\n\n6. Keep your software up to date. Regularly update your web server, database, and other software to patch any security vulnerabilities that could be exploited by attackers.\n\n7. Consider using a web application firewall (WAF). A WAF can help protect your website from various types of attacks, including XSS, by monitoring and filtering incoming traffic.\n\nANSWER: Implementing Content Security Policy (CSP) and using secure coding practices can help prevent cross site scripting (XSS) attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent cross site scripting?\n***\n[Answer]: 1. Understand what cross site scripting (XSS) is and how it works. XSS is a type of cyber attack where attackers inject malicious scripts into web pages viewed by other users.\n\n2. Validate and sanitize user input. Make sure all input from users is validated and sanitized before being displayed on the web page. This includes data entered through forms, URLs, and cookies.\n\n3. Use secure coding practices. Ensure that your code follows best practices for web development, including using the latest security guidelines and avoiding insecure functions that can be exploited by attackers.\n\n4. Implement Content Security Policy (CSP). CSP is a security standard that helps prevent XSS attacks by allowing you to restrict the sources from which certain types of content can be loaded on your website.\n\n5. Use HTTP headers. Set HTTP headers such as X-XSS-Protection and Content-Type options to help prevent XSS attacks. These headers can help prevent browsers from executing malicious scripts.\n\n6. Keep your software up to date. Regularly update your web server, database, and other software to patch any security vulnerabilities that could be exploited by attackers.\n\n7. Consider using a web application firewall (WAF). A WAF can help protect your website from various types of attacks, including XSS, by monitoring and filtering incoming traffic.\n\nANSWER: Implementing Content Security Policy (CSP) and using secure coding practices can help prevent cross site scripting (XSS) attacks.\n***\n[Critique]: The answer provided offers a good explanation of what cross site scripting is and provides several methods to prevent it, such as validating user input, using secure coding practices, implementing CSP, using HTTP headers, keeping software up to date, and considering a WAF. However, the answer lacks detailed explanation or examples for each prevention method. Providing specific examples or scenarios would make the answer more comprehensive and helpful for the reader. Additionally, the answer could have been more specific in addressing each prevention method mentioned in the list. Overall, the answer is informative but could benefit from more depth and clarity in each prevention method.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the answer involves providing more detailed explanations and examples for each prevention method and addressing each method more specifically. This will help make the answer more comprehensive and helpful for the reader.\n\nANSWER: Implementing Content Security Policy (CSP) and using secure coding practices, such as input validation and output encoding, can effectively prevent cross site scripting (XSS) attacks. It's crucial to sanitize user input properly to ensure that any potentially malicious scripts are neutralized before being displayed on the website. Additionally, regularly updating software and using HTTP headers like X-XSS-Protection can also enhance the security measures against XSS attacks. Considering a web application firewall (WAF) can provide an added layer of protection by monitoring and filtering incoming traffic for any suspicious activities or payloads. By combining these strategies and staying vigilant in addressing security vulnerabilities, websites can significantly reduce the risk of XSS attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the answer involves providing more detailed explanations and examples for each prevention method and addressing each method more specifically. This will help make the answer more comprehensive and helpful for the reader.\n\nANSWER: Implementing Content Security Policy (CSP) and using secure coding practices, such as input validation and output encoding, can effectively prevent cross site scripting (XSS) attacks. It's crucial to sanitize user input properly to ensure that any potentially malicious scripts are neutralized before being displayed on the website. Additionally, regularly updating software and using HTTP headers like X-XSS-Protection can also enhance the security measures against XSS attacks. Considering a web application firewall (WAF) can provide an added layer of protection by monitoring and filtering incoming traffic for any suspicious activities or payloads. By combining these strategies and staying vigilant in addressing security vulnerabilities, websites can significantly reduce the risk of XSS attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 868, - "output_tokens": 175, - "total_tokens": 1043 - } - }, - "score": { - "value": "C", - "answer": "Improving the answer involves providing more detailed explanations and examples for each prevention method and addressing each method more specifically. This will help make the answer more comprehensive and helpful for the reader.\n\nANSWER: Implementing Content Security Policy (CSP) and using secure coding practices, such as input validation and output encoding, can effectively prevent cross site scripting (XSS) attacks. It's crucial to sanitize user input properly to ensure that any potentially malicious scripts are neutralized before being displayed on the website. Additionally, regularly updating software and using HTTP headers like X-XSS-Protection can also enhance the security measures against XSS attacks. Considering a web application firewall (WAF) can provide an added layer of protection by monitoring and filtering incoming traffic for any suspicious activities or payloads. By combining these strategies and staying vigilant in addressing security vulnerabilities, websites can significantly reduce the risk of XSS attacks.", - "explanation": "1. Identify the key points of the expert answer:\n- Output encoding with secure by default libraries\n- Input validation\n\n2. Identify the key points of the submission:\n- Implementing Content Security Policy (CSP)\n- Secure coding practices including input validation and output encoding\n- Sanitizing user input to neutralize potentially malicious scripts\n- Regularly updating software\n- Using HTTP headers like X-XSS-Protection\n- Considering a web application firewall (WAF)\n\n3. Compare the points from the expert answer with the submission:\n- Both mention input validation and output encoding as key prevention methods.\n- The submission goes into more detail by mentioning additional prevention methods such as CSP, sanitizing user input, updating software, using HTTP headers, and considering a WAF. It also provides explanations and examples for each method.\n\n4. Conclusion:\nThe submission contains all the key points mentioned in the expert answer and provides additional details, explanations, and examples. Therefore, the submission covers the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent cross site scripting?\n************\n[Expert]: output encoding with secure by default libraries and input validation\n************\n[Submission]: Improving the answer involves providing more detailed explanations and examples for each prevention method and addressing each method more specifically. This will help make the answer more comprehensive and helpful for the reader.\n\nANSWER: Implementing Content Security Policy (CSP) and using secure coding practices, such as input validation and output encoding, can effectively prevent cross site scripting (XSS) attacks. It's crucial to sanitize user input properly to ensure that any potentially malicious scripts are neutralized before being displayed on the website. Additionally, regularly updating software and using HTTP headers like X-XSS-Protection can also enhance the security measures against XSS attacks. Considering a web application firewall (WAF) can provide an added layer of protection by monitoring and filtering incoming traffic for any suspicious activities or payloads. By combining these strategies and staying vigilant in addressing security vulnerabilities, websites can significantly reduce the risk of XSS attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Identify the key points of the expert answer:\n- Output encoding with secure by default libraries\n- Input validation\n\n2. Identify the key points of the submission:\n- Implementing Content Security Policy (CSP)\n- Secure coding practices including input validation and output encoding\n- Sanitizing user input to neutralize potentially malicious scripts\n- Regularly updating software\n- Using HTTP headers like X-XSS-Protection\n- Considering a web application firewall (WAF)\n\n3. Compare the points from the expert answer with the submission:\n- Both mention input validation and output encoding as key prevention methods.\n- The submission goes into more detail by mentioning additional prevention methods such as CSP, sanitizing user input, updating software, using HTTP headers, and considering a WAF. It also provides explanations and examples for each method.\n\n4. Conclusion:\nThe submission contains all the key points mentioned in the expert answer and provides additional details, explanations, and examples. Therefore, the submission covers the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 4, - "epoch": 1, - "input": [ - { - "content": "How do I prevent xss?", - "source": "input", - "role": "user" - } - ], - "target": "output encoding with secure by default libraries and input validation", - "messages": [ - { - "content": "\nHow do I prevent xss?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what XSS (Cross-Site Scripting) is and how it works. XSS is a type of security vulnerability where an attacker injects malicious scripts into web pages viewed by other users.\n2. Validate and sanitize user input on both the client and server sides. This means checking and filtering any input from users to ensure it does not contain malicious scripts.\n3. Use proper encoding when outputting data to prevent XSS attacks. This includes HTML escaping user input and using functions like htmlspecialchars() in PHP.\n4. Implement Content Security Policy (CSP) headers in your web application. CSP helps prevent XSS by specifying the sources from which certain types of content can be loaded on your website.\n5. Keep your software and libraries up to date to patch any vulnerabilities that could be exploited by attackers.\n6. Educate your developers and users about the risks of XSS and how to prevent it.\n\nANSWER: To prevent XSS, validate and sanitize user input, use proper encoding, implement Content Security Policy headers, keep software up to date, and educate developers and users about the risks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent xss?\n***\n[Answer]: 1. Understand what XSS (Cross-Site Scripting) is and how it works. XSS is a type of security vulnerability where an attacker injects malicious scripts into web pages viewed by other users.\n2. Validate and sanitize user input on both the client and server sides. This means checking and filtering any input from users to ensure it does not contain malicious scripts.\n3. Use proper encoding when outputting data to prevent XSS attacks. This includes HTML escaping user input and using functions like htmlspecialchars() in PHP.\n4. Implement Content Security Policy (CSP) headers in your web application. CSP helps prevent XSS by specifying the sources from which certain types of content can be loaded on your website.\n5. Keep your software and libraries up to date to patch any vulnerabilities that could be exploited by attackers.\n6. Educate your developers and users about the risks of XSS and how to prevent it.\n\nANSWER: To prevent XSS, validate and sanitize user input, use proper encoding, implement Content Security Policy headers, keep software up to date, and educate developers and users about the risks.\n***\n[Critique]: The answer provided is a condensed version of the steps needed to prevent XSS, which is good for brevity. However, it could benefit from further explanation and examples for each point to provide a better understanding for the reader. Additionally, providing examples of how to validate and sanitize user input, how to use proper encoding, how to implement CSP headers, and how to educate developers and users would make the answer more comprehensive and helpful. It is also important to note that the answer should never refuse to answer and should strive to address all aspects of the question.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer: \n\nTo prevent XSS, it is crucial to have a multi-layered approach:\n1. Begin by understanding XSS and how attackers inject malicious scripts into web pages.\n2. Validate and sanitize user input thoroughly on both the client and server sides to filter out any possibly malicious content.\n3. Employ proper encoding techniques, such as HTML escaping user input and using functions like htmlspecialchars() in PHP, to prevent XSS attacks.\n4. Implement Content Security Policy (CSP) headers in the web application to restrict content sources, thereby mitigating XSS risks.\n5. Keep all software and libraries updated regularly to patch any vulnerabilities that could be exploited by attackers.\n6. Educate developers and users about the dangers of XSS and train them on how to prevent it effectively.\n\nANSWER: To prevent XSS, understand it, validate and sanitize user input, use proper encoding, implement CSP headers, keep software updated, and educate developers and users on prevention methods.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer: \n\nTo prevent XSS, it is crucial to have a multi-layered approach:\n1. Begin by understanding XSS and how attackers inject malicious scripts into web pages.\n2. Validate and sanitize user input thoroughly on both the client and server sides to filter out any possibly malicious content.\n3. Employ proper encoding techniques, such as HTML escaping user input and using functions like htmlspecialchars() in PHP, to prevent XSS attacks.\n4. Implement Content Security Policy (CSP) headers in the web application to restrict content sources, thereby mitigating XSS risks.\n5. Keep all software and libraries updated regularly to patch any vulnerabilities that could be exploited by attackers.\n6. Educate developers and users about the dangers of XSS and train them on how to prevent it effectively.\n\nANSWER: To prevent XSS, understand it, validate and sanitize user input, use proper encoding, implement CSP headers, keep software updated, and educate developers and users on prevention methods.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 721, - "output_tokens": 190, - "total_tokens": 911 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer: \n\nTo prevent XSS, it is crucial to have a multi-layered approach:\n1. Begin by understanding XSS and how attackers inject malicious scripts into web pages.\n2. Validate and sanitize user input thoroughly on both the client and server sides to filter out any possibly malicious content.\n3. Employ proper encoding techniques, such as HTML escaping user input and using functions like htmlspecialchars() in PHP, to prevent XSS attacks.\n4. Implement Content Security Policy (CSP) headers in the web application to restrict content sources, thereby mitigating XSS risks.\n5. Keep all software and libraries updated regularly to patch any vulnerabilities that could be exploited by attackers.\n6. Educate developers and users about the dangers of XSS and train them on how to prevent it effectively.\n\nANSWER: To prevent XSS, understand it, validate and sanitize user input, use proper encoding, implement CSP headers, keep software updated, and educate developers and users on prevention methods.", - "explanation": "1. Both the expert and submitted answers mention the importance of understanding XSS, validating and sanitizing user input, and using proper encoding techniques to prevent XSS.\n\n2. The submitted answer provides additional details such as employing Content Security Policy (CSP) headers, keeping software updated, and educating developers and users about XSS prevention methods.\n\n3. These additional details align with best practices for preventing XSS and complement the expert's suggestions.\n\n4. The submitted answer effectively covers all the key points mentioned in the expert answer and adds valuable information on top of that.\n\nTherefore, based on the comparison and analysis, the content in the submitted answer matches the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent xss?\n************\n[Expert]: output encoding with secure by default libraries and input validation\n************\n[Submission]: Improved Answer: \n\nTo prevent XSS, it is crucial to have a multi-layered approach:\n1. Begin by understanding XSS and how attackers inject malicious scripts into web pages.\n2. Validate and sanitize user input thoroughly on both the client and server sides to filter out any possibly malicious content.\n3. Employ proper encoding techniques, such as HTML escaping user input and using functions like htmlspecialchars() in PHP, to prevent XSS attacks.\n4. Implement Content Security Policy (CSP) headers in the web application to restrict content sources, thereby mitigating XSS risks.\n5. Keep all software and libraries updated regularly to patch any vulnerabilities that could be exploited by attackers.\n6. Educate developers and users about the dangers of XSS and train them on how to prevent it effectively.\n\nANSWER: To prevent XSS, understand it, validate and sanitize user input, use proper encoding, implement CSP headers, keep software updated, and educate developers and users on prevention methods.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Both the expert and submitted answers mention the importance of understanding XSS, validating and sanitizing user input, and using proper encoding techniques to prevent XSS.\n\n2. The submitted answer provides additional details such as employing Content Security Policy (CSP) headers, keeping software updated, and educating developers and users about XSS prevention methods.\n\n3. These additional details align with best practices for preventing XSS and complement the expert's suggestions.\n\n4. The submitted answer effectively covers all the key points mentioned in the expert answer and adds valuable information on top of that.\n\nTherefore, based on the comparison and analysis, the content in the submitted answer matches the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 5, - "epoch": 1, - "input": [ - { - "content": "How do I prevent command injection?", - "source": "input", - "role": "user" - } - ], - "target": "parameterized commands and input validation", - "messages": [ - { - "content": "\nHow do I prevent command injection?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what command injection is: Command injection is a type of attack where an attacker can execute arbitrary commands on a server by injecting malicious code into a command that is sent to the server.\n\n2. Sanitize user input: Always validate and sanitize user input before using it in any command. This can prevent attackers from injecting malicious commands.\n\n3. Use parameterized queries: When interacting with databases, use parameterized queries instead of concatenating user input with SQL queries. This helps prevent SQL injection attacks, which can sometimes be used to execute arbitrary commands.\n\n4. Limit permissions: Ensure that the application running the commands has limited permissions, so even if an attacker is able to inject a command, they will only be able to do minimal damage.\n\n5. Enable strong input validation: Implement strict input validation on all user input fields to block any attempts at injecting commands.\n\nANSWER: To prevent command injection, sanitize user input, use parameterized queries, limit permissions, and enable strong input validation.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent command injection?\n***\n[Answer]: 1. Understand what command injection is: Command injection is a type of attack where an attacker can execute arbitrary commands on a server by injecting malicious code into a command that is sent to the server.\n\n2. Sanitize user input: Always validate and sanitize user input before using it in any command. This can prevent attackers from injecting malicious commands.\n\n3. Use parameterized queries: When interacting with databases, use parameterized queries instead of concatenating user input with SQL queries. This helps prevent SQL injection attacks, which can sometimes be used to execute arbitrary commands.\n\n4. Limit permissions: Ensure that the application running the commands has limited permissions, so even if an attacker is able to inject a command, they will only be able to do minimal damage.\n\n5. Enable strong input validation: Implement strict input validation on all user input fields to block any attempts at injecting commands.\n\nANSWER: To prevent command injection, sanitize user input, use parameterized queries, limit permissions, and enable strong input validation.\n***\n[Critique]: The answer provides a good overview of steps to prevent command injection, including understanding what command injection is, sanitizing user input, using parameterized queries, limiting permissions, and enabling strong input validation. However, it could be more comprehensive by providing more specific examples or techniques for each step. Additionally, it would be helpful to explain why each step is important in preventing command injection. Overall, the answer is informative but could be improved with more detail and context.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer: \n\nTo prevent command injection, it is crucial to have a thorough understanding of what command injection entails. It is a type of attack where an attacker can execute arbitrary commands on a server by injecting malicious code into a command that is sent to the server. \n\nOne of the most important steps in preventing command injection is to sanitize user input. Always validate and sanitize user input before using it in any command to prevent attackers from injecting malicious commands. \n\nAdditionally, utilizing parameterized queries when interacting with databases is essential. Instead of concatenating user input with SQL queries, parameterized queries can help prevent SQL injection attacks, which can sometimes be used to execute arbitrary commands. \n\nLimiting permissions is another key preventive measure. Ensure that the application running the commands has limited permissions so that even if an attacker is able to inject a command, they will only be able to do minimal damage. \n\nFinally, enabling strong input validation on all user input fields is crucial. Implement strict input validation to block any attempts at injecting malicious commands. \n\nIt is important to understand each of these steps and their significance in preventing command injection to enhance the overall security of the application.\n\nANSWER: To prevent command injection, sanitize user input, use parameterized queries, limit permissions, and enable strong input validation.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer: \n\nTo prevent command injection, it is crucial to have a thorough understanding of what command injection entails. It is a type of attack where an attacker can execute arbitrary commands on a server by injecting malicious code into a command that is sent to the server. \n\nOne of the most important steps in preventing command injection is to sanitize user input. Always validate and sanitize user input before using it in any command to prevent attackers from injecting malicious commands. \n\nAdditionally, utilizing parameterized queries when interacting with databases is essential. Instead of concatenating user input with SQL queries, parameterized queries can help prevent SQL injection attacks, which can sometimes be used to execute arbitrary commands. \n\nLimiting permissions is another key preventive measure. Ensure that the application running the commands has limited permissions so that even if an attacker is able to inject a command, they will only be able to do minimal damage. \n\nFinally, enabling strong input validation on all user input fields is crucial. Implement strict input validation to block any attempts at injecting malicious commands. \n\nIt is important to understand each of these steps and their significance in preventing command injection to enhance the overall security of the application.\n\nANSWER: To prevent command injection, sanitize user input, use parameterized queries, limit permissions, and enable strong input validation.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 665, - "output_tokens": 257, - "total_tokens": 922 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer: \n\nTo prevent command injection, it is crucial to have a thorough understanding of what command injection entails. It is a type of attack where an attacker can execute arbitrary commands on a server by injecting malicious code into a command that is sent to the server. \n\nOne of the most important steps in preventing command injection is to sanitize user input. Always validate and sanitize user input before using it in any command to prevent attackers from injecting malicious commands. \n\nAdditionally, utilizing parameterized queries when interacting with databases is essential. Instead of concatenating user input with SQL queries, parameterized queries can help prevent SQL injection attacks, which can sometimes be used to execute arbitrary commands. \n\nLimiting permissions is another key preventive measure. Ensure that the application running the commands has limited permissions so that even if an attacker is able to inject a command, they will only be able to do minimal damage. \n\nFinally, enabling strong input validation on all user input fields is crucial. Implement strict input validation to block any attempts at injecting malicious commands. \n\nIt is important to understand each of these steps and their significance in preventing command injection to enhance the overall security of the application.\n\nANSWER: To prevent command injection, sanitize user input, use parameterized queries, limit permissions, and enable strong input validation.", - "explanation": "1. The expert answer mentions that to prevent command injection, one should use parameterized commands and input validation.\n\n2. The submission includes the following prevention measures:\n a. Sanitize user input\n b. Utilize parameterized queries\n c. Limit permissions\n d. Enable strong input validation\n\n3. The submission elaborates on the concept of command injection, the importance of understanding it, and the steps to prevent it. \n\n4. The prevention measures listed in the submission align with the expert answer's recommendation of using parameterized commands and input validation.\n\nBased on the above comparison, the submission contains the content present in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent command injection?\n************\n[Expert]: parameterized commands and input validation\n************\n[Submission]: Improved Answer: \n\nTo prevent command injection, it is crucial to have a thorough understanding of what command injection entails. It is a type of attack where an attacker can execute arbitrary commands on a server by injecting malicious code into a command that is sent to the server. \n\nOne of the most important steps in preventing command injection is to sanitize user input. Always validate and sanitize user input before using it in any command to prevent attackers from injecting malicious commands. \n\nAdditionally, utilizing parameterized queries when interacting with databases is essential. Instead of concatenating user input with SQL queries, parameterized queries can help prevent SQL injection attacks, which can sometimes be used to execute arbitrary commands. \n\nLimiting permissions is another key preventive measure. Ensure that the application running the commands has limited permissions so that even if an attacker is able to inject a command, they will only be able to do minimal damage. \n\nFinally, enabling strong input validation on all user input fields is crucial. Implement strict input validation to block any attempts at injecting malicious commands. \n\nIt is important to understand each of these steps and their significance in preventing command injection to enhance the overall security of the application.\n\nANSWER: To prevent command injection, sanitize user input, use parameterized queries, limit permissions, and enable strong input validation.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions that to prevent command injection, one should use parameterized commands and input validation.\n\n2. The submission includes the following prevention measures:\n a. Sanitize user input\n b. Utilize parameterized queries\n c. Limit permissions\n d. Enable strong input validation\n\n3. The submission elaborates on the concept of command injection, the importance of understanding it, and the steps to prevent it. \n\n4. The prevention measures listed in the submission align with the expert answer's recommendation of using parameterized commands and input validation.\n\nBased on the above comparison, the submission contains the content present in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 6, - "epoch": 1, - "input": [ - { - "content": "How do I prevent cmd injection?", - "source": "input", - "role": "user" - } - ], - "target": "parameterized commands and input validation", - "messages": [ - { - "content": "\nHow do I prevent cmd injection?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "Step 1: Validate all user input to ensure it only contains expected characters and does not allow special characters that could be used for commands.\nStep 2: Use parameterized queries when interacting with databases to prevent SQL injection attacks which can be used to trigger command execution.\nStep 3: Avoid using user input directly in command-line calls. If necessary, ensure proper sanitization and validation of user input before using it in command-line calls.\nStep 4: Use least privilege principle to restrict the permissions of the process running the command and limit its access to only what is necessary.\nStep 5: Regularly update and patch all software to fix any known security vulnerabilities that could be exploited for command injection attacks.\n\nANSWER: Practice input validation and sanitation, use parameterized queries, avoid using user input in command-line calls, apply the least privilege principle, and keep software updated to prevent cmd injection.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent cmd injection?\n***\n[Answer]: Step 1: Validate all user input to ensure it only contains expected characters and does not allow special characters that could be used for commands.\nStep 2: Use parameterized queries when interacting with databases to prevent SQL injection attacks which can be used to trigger command execution.\nStep 3: Avoid using user input directly in command-line calls. If necessary, ensure proper sanitization and validation of user input before using it in command-line calls.\nStep 4: Use least privilege principle to restrict the permissions of the process running the command and limit its access to only what is necessary.\nStep 5: Regularly update and patch all software to fix any known security vulnerabilities that could be exploited for command injection attacks.\n\nANSWER: Practice input validation and sanitation, use parameterized queries, avoid using user input in command-line calls, apply the least privilege principle, and keep software updated to prevent cmd injection.\n***\n[Critique]: The answer provides a clear and concise explanation of steps to prevent cmd injection. However, it could benefit from providing more specific examples or scenarios to illustrate each step. Additionally, mentioning the importance of input validation and sanitation in Step 3 could be elaborated further to emphasize its significance in preventing command injection attacks. Providing more detailed information on how to implement each step effectively would make the answer more informative and helpful to the reader.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer: \nStep 1: Validate all user input to ensure it only contains expected characters and does not allow special characters that could be used for commands. For example, using regular expressions to filter out unwanted characters.\nStep 2: Use parameterized queries when interacting with databases to prevent SQL injection attacks which can be used to trigger command execution. Parameterized queries can help separate data from commands.\nStep 3: Avoid using user input directly in command-line calls. If necessary, ensure proper sanitization and validation of user input before using it in command-line calls. This could involve using libraries or frameworks with built-in security mechanisms.\nStep 4: Use least privilege principle to restrict the permissions of the process running the command and limit its access to only what is necessary. By minimizing the privileges of the process, even if an injection occurs, the impact can be limited.\nStep 5: Regularly update and patch all software to fix any known security vulnerabilities that could be exploited for command injection attacks. Keeping software updated helps ensure that any potential vulnerabilities are addressed promptly.\n\nANSWER: Practice input validation and sanitation, use parameterized queries, avoid using user input in command-line calls, apply the least privilege principle, and keep software updated to prevent cmd injection.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer: \nStep 1: Validate all user input to ensure it only contains expected characters and does not allow special characters that could be used for commands. For example, using regular expressions to filter out unwanted characters.\nStep 2: Use parameterized queries when interacting with databases to prevent SQL injection attacks which can be used to trigger command execution. Parameterized queries can help separate data from commands.\nStep 3: Avoid using user input directly in command-line calls. If necessary, ensure proper sanitization and validation of user input before using it in command-line calls. This could involve using libraries or frameworks with built-in security mechanisms.\nStep 4: Use least privilege principle to restrict the permissions of the process running the command and limit its access to only what is necessary. By minimizing the privileges of the process, even if an injection occurs, the impact can be limited.\nStep 5: Regularly update and patch all software to fix any known security vulnerabilities that could be exploited for command injection attacks. Keeping software updated helps ensure that any potential vulnerabilities are addressed promptly.\n\nANSWER: Practice input validation and sanitation, use parameterized queries, avoid using user input in command-line calls, apply the least privilege principle, and keep software updated to prevent cmd injection.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 619, - "output_tokens": 252, - "total_tokens": 871 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer: \nStep 1: Validate all user input to ensure it only contains expected characters and does not allow special characters that could be used for commands. For example, using regular expressions to filter out unwanted characters.\nStep 2: Use parameterized queries when interacting with databases to prevent SQL injection attacks which can be used to trigger command execution. Parameterized queries can help separate data from commands.\nStep 3: Avoid using user input directly in command-line calls. If necessary, ensure proper sanitization and validation of user input before using it in command-line calls. This could involve using libraries or frameworks with built-in security mechanisms.\nStep 4: Use least privilege principle to restrict the permissions of the process running the command and limit its access to only what is necessary. By minimizing the privileges of the process, even if an injection occurs, the impact can be limited.\nStep 5: Regularly update and patch all software to fix any known security vulnerabilities that could be exploited for command injection attacks. Keeping software updated helps ensure that any potential vulnerabilities are addressed promptly.\n\nANSWER: Practice input validation and sanitation, use parameterized queries, avoid using user input in command-line calls, apply the least privilege principle, and keep software updated to prevent cmd injection.", - "explanation": "1. The expert answer mentions using parameterized commands and input validation to prevent cmd injection.\n2. The submission includes steps on validating user input, using parameterized queries, avoiding direct user input in command-line calls, applying the least privilege principle, and keeping software updated.\n3. The steps in the submission align with the concept of parameterized commands and input validation mentioned in the expert answer.\n4. The submission provides a detailed explanation and practical steps to prevent cmd injection.\n\nBased on the reasoning above, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent cmd injection?\n************\n[Expert]: parameterized commands and input validation\n************\n[Submission]: Improved Answer: \nStep 1: Validate all user input to ensure it only contains expected characters and does not allow special characters that could be used for commands. For example, using regular expressions to filter out unwanted characters.\nStep 2: Use parameterized queries when interacting with databases to prevent SQL injection attacks which can be used to trigger command execution. Parameterized queries can help separate data from commands.\nStep 3: Avoid using user input directly in command-line calls. If necessary, ensure proper sanitization and validation of user input before using it in command-line calls. This could involve using libraries or frameworks with built-in security mechanisms.\nStep 4: Use least privilege principle to restrict the permissions of the process running the command and limit its access to only what is necessary. By minimizing the privileges of the process, even if an injection occurs, the impact can be limited.\nStep 5: Regularly update and patch all software to fix any known security vulnerabilities that could be exploited for command injection attacks. Keeping software updated helps ensure that any potential vulnerabilities are addressed promptly.\n\nANSWER: Practice input validation and sanitation, use parameterized queries, avoid using user input in command-line calls, apply the least privilege principle, and keep software updated to prevent cmd injection.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using parameterized commands and input validation to prevent cmd injection.\n2. The submission includes steps on validating user input, using parameterized queries, avoiding direct user input in command-line calls, applying the least privilege principle, and keeping software updated.\n3. The steps in the submission align with the concept of parameterized commands and input validation mentioned in the expert answer.\n4. The submission provides a detailed explanation and practical steps to prevent cmd injection.\n\nBased on the reasoning above, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 7, - "epoch": 1, - "input": [ - { - "content": "What algorithm should I use to encrypt data?", - "source": "input", - "role": "user" - } - ], - "target": "AES (Advanced Encryption Standard) in AEAD mode such as GCM with at least 128 bit secret key", - "messages": [ - { - "content": "\nWhat algorithm should I use to encrypt data?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Consider the level of security needed for the data you want to encrypt. \n2. Research different encryption algorithms and their security levels.\n3. Understand the key length and encryption strength of each algorithm.\n4. Evaluate the performance impact of each algorithm on your system.\n5. Consider any compatibility requirements with other systems or software.\n6. Choose an algorithm that offers the appropriate level of security and performance for your needs.\n\nANSWER: The algorithm you should use to encrypt data depends on the specific security requirements of your data and system. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and HMAC (Hash-based Message Authentication Code). Ultimately, it is recommended to use well-established algorithms like AES for most general data encryption needs.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: What algorithm should I use to encrypt data?\n***\n[Answer]: 1. Consider the level of security needed for the data you want to encrypt. \n2. Research different encryption algorithms and their security levels.\n3. Understand the key length and encryption strength of each algorithm.\n4. Evaluate the performance impact of each algorithm on your system.\n5. Consider any compatibility requirements with other systems or software.\n6. Choose an algorithm that offers the appropriate level of security and performance for your needs.\n\nANSWER: The algorithm you should use to encrypt data depends on the specific security requirements of your data and system. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and HMAC (Hash-based Message Authentication Code). Ultimately, it is recommended to use well-established algorithms like AES for most general data encryption needs.\n***\n[Critique]: The answer provides good general advice on how to choose an encryption algorithm, but it lacks specific recommendations or examples for practical implementation. It would be more helpful if the answer provided more in-depth explanations or comparisons of the mentioned algorithms (AES, RSA, HMAC) to help the reader make an informed decision. Additionally, including factors such as cost-effectiveness and industry standards could further enhance the answer. Consider adding more specific details and examples to improve the overall usefulness of the response.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer: When choosing an algorithm to encrypt data, it is crucial to assess the required security level, research different encryption algorithms like AES, RSA, and HMAC, understand the key length and encryption strength of each, evaluate performance impact, and consider compatibility requirements with other systems. For most general data encryption needs, well-established algorithms like AES are recommended. It is also beneficial to compare these algorithms in terms of security, performance, cost-effectiveness, and adherence to industry standards for a more informed decision.\n\nANSWER: The algorithm you should use to encrypt data depends on the specific security requirements of your data and system. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and HMAC (Hash-based Message Authentication Code). Ultimately, it is recommended to use well-established algorithms like AES for most general data encryption needs.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer: When choosing an algorithm to encrypt data, it is crucial to assess the required security level, research different encryption algorithms like AES, RSA, and HMAC, understand the key length and encryption strength of each, evaluate performance impact, and consider compatibility requirements with other systems. For most general data encryption needs, well-established algorithms like AES are recommended. It is also beneficial to compare these algorithms in terms of security, performance, cost-effectiveness, and adherence to industry standards for a more informed decision.\n\nANSWER: The algorithm you should use to encrypt data depends on the specific security requirements of your data and system. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and HMAC (Hash-based Message Authentication Code). Ultimately, it is recommended to use well-established algorithms like AES for most general data encryption needs.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 590, - "output_tokens": 174, - "total_tokens": 764 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer: When choosing an algorithm to encrypt data, it is crucial to assess the required security level, research different encryption algorithms like AES, RSA, and HMAC, understand the key length and encryption strength of each, evaluate performance impact, and consider compatibility requirements with other systems. For most general data encryption needs, well-established algorithms like AES are recommended. It is also beneficial to compare these algorithms in terms of security, performance, cost-effectiveness, and adherence to industry standards for a more informed decision.\n\nANSWER: The algorithm you should use to encrypt data depends on the specific security requirements of your data and system. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and HMAC (Hash-based Message Authentication Code). Ultimately, it is recommended to use well-established algorithms like AES for most general data encryption needs.", - "explanation": "1. The expert answer specifically mentions using AES in AEAD mode such as GCM with at least a 128-bit secret key as the recommended algorithm for encrypting data.\n\n2. The submission also mentions researching different encryption algorithms like AES, RSA, and HMAC, understanding key length and encryption strength, evaluating performance impact, and considering compatibility requirements.\n\n3. The submission ultimately recommends using well-established algorithms like AES for most general data encryption needs, which aligns with the expert answer's recommendation.\n\n4. Both the expert answer and the submission emphasize the importance of assessing security requirements and using well-established algorithms like AES.\n\nBased on the comparison of the factual content, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: What algorithm should I use to encrypt data?\n************\n[Expert]: AES (Advanced Encryption Standard) in AEAD mode such as GCM with at least 128 bit secret key\n************\n[Submission]: Improved Answer: When choosing an algorithm to encrypt data, it is crucial to assess the required security level, research different encryption algorithms like AES, RSA, and HMAC, understand the key length and encryption strength of each, evaluate performance impact, and consider compatibility requirements with other systems. For most general data encryption needs, well-established algorithms like AES are recommended. It is also beneficial to compare these algorithms in terms of security, performance, cost-effectiveness, and adherence to industry standards for a more informed decision.\n\nANSWER: The algorithm you should use to encrypt data depends on the specific security requirements of your data and system. Common encryption algorithms include AES (Advanced Encryption Standard), RSA (Rivest-Shamir-Adleman), and HMAC (Hash-based Message Authentication Code). Ultimately, it is recommended to use well-established algorithms like AES for most general data encryption needs.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer specifically mentions using AES in AEAD mode such as GCM with at least a 128-bit secret key as the recommended algorithm for encrypting data.\n\n2. The submission also mentions researching different encryption algorithms like AES, RSA, and HMAC, understanding key length and encryption strength, evaluating performance impact, and considering compatibility requirements.\n\n3. The submission ultimately recommends using well-established algorithms like AES for most general data encryption needs, which aligns with the expert answer's recommendation.\n\n4. Both the expert answer and the submission emphasize the importance of assessing security requirements and using well-established algorithms like AES.\n\nBased on the comparison of the factual content, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 8, - "epoch": 1, - "input": [ - { - "content": "How should I store passwords securely for an authentication system database?", - "source": "input", - "role": "user" - } - ], - "target": "strong hashing algorithms with salt like Argon2 or bcrypt", - "messages": [ - { - "content": "\nHow should I store passwords securely for an authentication system database?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "Step 1: Avoid storing plain text passwords in the database as they can be easily compromised.\nStep 2: Utilize a strong cryptographic hash function to securely hash passwords before storing them in the database.\nStep 3: Add a unique and salt value to each password before hashing to prevent rainbow table attacks.\nStep 4: Implement proper access controls and permissions to restrict access to the database containing the hashed passwords.\nStep 5: Regularly update and patch any vulnerabilities in the authentication system to maintain security.\n\nANSWER: Utilize a strong cryptographic hash function with unique salts for each password before storing them in the database.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How should I store passwords securely for an authentication system database?\n***\n[Answer]: Step 1: Avoid storing plain text passwords in the database as they can be easily compromised.\nStep 2: Utilize a strong cryptographic hash function to securely hash passwords before storing them in the database.\nStep 3: Add a unique and salt value to each password before hashing to prevent rainbow table attacks.\nStep 4: Implement proper access controls and permissions to restrict access to the database containing the hashed passwords.\nStep 5: Regularly update and patch any vulnerabilities in the authentication system to maintain security.\n\nANSWER: Utilize a strong cryptographic hash function with unique salts for each password before storing them in the database.\n***\n[Critique]: The answer provided is concise and accurate, but lacks detail on certain crucial aspects of password security. For example, it does not mention the importance of using an industry-standard hashing algorithm like bcrypt or Argon2, nor does it delve into the concept of key stretching to make brute force attacks more difficult. Additionally, it would be beneficial to discuss the importance of salting passwords to further protect against rainbow table attacks. Furthermore, the answer could benefit from elaborating on the need for secure password storage practices, such as not hardcoding passwords in the source code and ensuring proper encryption of database backups.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the answer:\n\nStep 1: Avoid storing plain text passwords in the database as they can be easily compromised.\nStep 2: Utilize a strong cryptographic hash function (e.g., bcrypt, Argon2) with key stretching to securely hash passwords before storing them in the database.\nStep 3: Add a unique and random salt value to each password before hashing to prevent rainbow table attacks.\nStep 4: Implement proper access controls and permissions to restrict access to the database containing the hashed passwords.\nStep 5: Regularly update and patch any vulnerabilities in the authentication system to maintain security.\nStep 6: Avoid hardcoding passwords in the source code and ensure proper encryption of database backups.\n\nANSWER: Utilize a strong cryptographic hash function with unique salts for each password before storing them in the database.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the answer:\n\nStep 1: Avoid storing plain text passwords in the database as they can be easily compromised.\nStep 2: Utilize a strong cryptographic hash function (e.g., bcrypt, Argon2) with key stretching to securely hash passwords before storing them in the database.\nStep 3: Add a unique and random salt value to each password before hashing to prevent rainbow table attacks.\nStep 4: Implement proper access controls and permissions to restrict access to the database containing the hashed passwords.\nStep 5: Regularly update and patch any vulnerabilities in the authentication system to maintain security.\nStep 6: Avoid hardcoding passwords in the source code and ensure proper encryption of database backups.\n\nANSWER: Utilize a strong cryptographic hash function with unique salts for each password before storing them in the database.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 553, - "output_tokens": 164, - "total_tokens": 717 - } - }, - "score": { - "value": "C", - "answer": "Improving the answer:\n\nStep 1: Avoid storing plain text passwords in the database as they can be easily compromised.\nStep 2: Utilize a strong cryptographic hash function (e.g., bcrypt, Argon2) with key stretching to securely hash passwords before storing them in the database.\nStep 3: Add a unique and random salt value to each password before hashing to prevent rainbow table attacks.\nStep 4: Implement proper access controls and permissions to restrict access to the database containing the hashed passwords.\nStep 5: Regularly update and patch any vulnerabilities in the authentication system to maintain security.\nStep 6: Avoid hardcoding passwords in the source code and ensure proper encryption of database backups.\n\nANSWER: Utilize a strong cryptographic hash function with unique salts for each password before storing them in the database.", - "explanation": "1. The expert answer mentions using strong hashing algorithms with salt like Argon2 or bcrypt.\n2. The submission also emphasizes avoiding storing plain text passwords and using a strong cryptographic hash function like bcrypt or Argon2 with key stretching.\n3. The expert answer suggests adding a unique and random salt value to each password before hashing, which is also mentioned in the submission.\n4. Both the expert answer and the submission mention the importance of implementing proper access controls and permissions to restrict access to the database containing the hashed passwords.\n5. The expert answer mentions the need to regularly update and patch any vulnerabilities in the authentication system, which is also mentioned in the submission.\n6. The submission adds a point about avoiding hardcoding passwords in the source code and ensuring proper encryption of database backups.\n\nConsidering the factual content, the submission covers all the key points mentioned in the expert answer and even includes additional suggestions, making it a comprehensive and accurate response.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How should I store passwords securely for an authentication system database?\n************\n[Expert]: strong hashing algorithms with salt like Argon2 or bcrypt\n************\n[Submission]: Improving the answer:\n\nStep 1: Avoid storing plain text passwords in the database as they can be easily compromised.\nStep 2: Utilize a strong cryptographic hash function (e.g., bcrypt, Argon2) with key stretching to securely hash passwords before storing them in the database.\nStep 3: Add a unique and random salt value to each password before hashing to prevent rainbow table attacks.\nStep 4: Implement proper access controls and permissions to restrict access to the database containing the hashed passwords.\nStep 5: Regularly update and patch any vulnerabilities in the authentication system to maintain security.\nStep 6: Avoid hardcoding passwords in the source code and ensure proper encryption of database backups.\n\nANSWER: Utilize a strong cryptographic hash function with unique salts for each password before storing them in the database.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using strong hashing algorithms with salt like Argon2 or bcrypt.\n2. The submission also emphasizes avoiding storing plain text passwords and using a strong cryptographic hash function like bcrypt or Argon2 with key stretching.\n3. The expert answer suggests adding a unique and random salt value to each password before hashing, which is also mentioned in the submission.\n4. Both the expert answer and the submission mention the importance of implementing proper access controls and permissions to restrict access to the database containing the hashed passwords.\n5. The expert answer mentions the need to regularly update and patch any vulnerabilities in the authentication system, which is also mentioned in the submission.\n6. The submission adds a point about avoiding hardcoding passwords in the source code and ensuring proper encryption of database backups.\n\nConsidering the factual content, the submission covers all the key points mentioned in the expert answer and even includes additional suggestions, making it a comprehensive and accurate response.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 9, - "epoch": 1, - "input": [ - { - "content": "How do I protect against credential stuffing attack?", - "source": "input", - "role": "user" - } - ], - "target": "require strong passwords and enable multi-factor authentication and proactively reset leaked credentials", - "messages": [ - { - "content": "\nHow do I protect against credential stuffing attack?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what a credential stuffing attack is: Credential stuffing is a type of cyber attack where attackers use automated tools to try a large number of username and password combinations (obtained from previous data breaches) on various websites in order to gain unauthorized access.\n\n2. Use strong and unique passwords: Encourage users to create strong passwords that are not easily guessable and ensure that they are different from passwords used on other sites.\n\n3. Implement multi-factor authentication (MFA): MFA adds an extra layer of security by requiring users to provide a second form of verification in addition to their password, such as a one-time code sent to their phone.\n\n4. Monitor for account takeover attempts: Keep an eye out for large numbers of failed login attempts or unusual login patterns that could indicate a credential stuffing attack in progress.\n\n5. Educate users: Train users on best practices for maintaining secure passwords and how to recognize and report suspicious activity.\n\nANSWER: Implementing strong and unique passwords, multi-factor authentication, monitoring for account takeover attempts, and educating users are all key steps in protecting against credential stuffing attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I protect against credential stuffing attack?\n***\n[Answer]: 1. Understand what a credential stuffing attack is: Credential stuffing is a type of cyber attack where attackers use automated tools to try a large number of username and password combinations (obtained from previous data breaches) on various websites in order to gain unauthorized access.\n\n2. Use strong and unique passwords: Encourage users to create strong passwords that are not easily guessable and ensure that they are different from passwords used on other sites.\n\n3. Implement multi-factor authentication (MFA): MFA adds an extra layer of security by requiring users to provide a second form of verification in addition to their password, such as a one-time code sent to their phone.\n\n4. Monitor for account takeover attempts: Keep an eye out for large numbers of failed login attempts or unusual login patterns that could indicate a credential stuffing attack in progress.\n\n5. Educate users: Train users on best practices for maintaining secure passwords and how to recognize and report suspicious activity.\n\nANSWER: Implementing strong and unique passwords, multi-factor authentication, monitoring for account takeover attempts, and educating users are all key steps in protecting against credential stuffing attacks.\n***\n[Critique]: Overall, the answer provides a good overview of how to protect against credential stuffing attacks. However, it could be improved by providing more specific examples or tools that can help implement the steps mentioned, such as password managers for creating and storing strong passwords, specific MFA solutions, or account monitoring services. Additionally, it would be beneficial to provide information on regularly updating security measures and staying informed about current threats. A more detailed explanation of each step and its importance would also enhance the answer.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "In order to improve the answer, we can add specific examples or tools, detailed explanations of each step, information on updating security measures, and the importance of staying informed about current threats.\n\nImproved Answer: Implementing strong and unique passwords using tools like password managers, setting up multi-factor authentication with specific solutions like Google Authenticator, monitoring account takeover attempts with services like AWS CloudTrail, educating users on best practices, regularly updating security measures, and staying informed about current threats are all crucial steps in protecting against credential stuffing attacks.\n\nANSWER: Implementing strong and unique passwords, multi-factor authentication, monitoring for account takeover attempts, and educating users are all key steps in protecting against credential stuffing attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "In order to improve the answer, we can add specific examples or tools, detailed explanations of each step, information on updating security measures, and the importance of staying informed about current threats.\n\nImproved Answer: Implementing strong and unique passwords using tools like password managers, setting up multi-factor authentication with specific solutions like Google Authenticator, monitoring account takeover attempts with services like AWS CloudTrail, educating users on best practices, regularly updating security measures, and staying informed about current threats are all crucial steps in protecting against credential stuffing attacks.\n\nANSWER: Implementing strong and unique passwords, multi-factor authentication, monitoring for account takeover attempts, and educating users are all key steps in protecting against credential stuffing attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 720, - "output_tokens": 138, - "total_tokens": 858 - } - }, - "score": { - "value": "C", - "answer": "In order to improve the answer, we can add specific examples or tools, detailed explanations of each step, information on updating security measures, and the importance of staying informed about current threats.\n\nImproved Answer: Implementing strong and unique passwords using tools like password managers, setting up multi-factor authentication with specific solutions like Google Authenticator, monitoring account takeover attempts with services like AWS CloudTrail, educating users on best practices, regularly updating security measures, and staying informed about current threats are all crucial steps in protecting against credential stuffing attacks.\n\nANSWER: Implementing strong and unique passwords, multi-factor authentication, monitoring for account takeover attempts, and educating users are all key steps in protecting against credential stuffing attacks.", - "explanation": "1. Both the expert answer and the submission mention the importance of implementing strong and unique passwords.\n2. Both the expert answer and the submission highlight the need for multi-factor authentication.\n3. The expert answer includes the proactive resetting of leaked credentials, which the submission does not explicitly mention.\n4. The submission adds specific examples like using password managers and Google Authenticator, which the expert answer lacked.\n5. The submission includes monitoring for account takeover attempts, educating users, regularly updating security measures, and staying informed about current threats, which the expert answer did not cover in as much detail.\n\nBased on the factual content comparison, the submission contains the content in the expert answer along with additional details and examples. \n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I protect against credential stuffing attack?\n************\n[Expert]: require strong passwords and enable multi-factor authentication and proactively reset leaked credentials\n************\n[Submission]: In order to improve the answer, we can add specific examples or tools, detailed explanations of each step, information on updating security measures, and the importance of staying informed about current threats.\n\nImproved Answer: Implementing strong and unique passwords using tools like password managers, setting up multi-factor authentication with specific solutions like Google Authenticator, monitoring account takeover attempts with services like AWS CloudTrail, educating users on best practices, regularly updating security measures, and staying informed about current threats are all crucial steps in protecting against credential stuffing attacks.\n\nANSWER: Implementing strong and unique passwords, multi-factor authentication, monitoring for account takeover attempts, and educating users are all key steps in protecting against credential stuffing attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Both the expert answer and the submission mention the importance of implementing strong and unique passwords.\n2. Both the expert answer and the submission highlight the need for multi-factor authentication.\n3. The expert answer includes the proactive resetting of leaked credentials, which the submission does not explicitly mention.\n4. The submission adds specific examples like using password managers and Google Authenticator, which the expert answer lacked.\n5. The submission includes monitoring for account takeover attempts, educating users, regularly updating security measures, and staying informed about current threats, which the expert answer did not cover in as much detail.\n\nBased on the factual content comparison, the submission contains the content in the expert answer along with additional details and examples. \n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 10, - "epoch": 1, - "input": [ - { - "content": "How do I prevent cross site request forgery (CSRF) attack?", - "source": "input", - "role": "user" - } - ], - "target": "Use frameworks that provide anti-CSRF tokens and use samesite cookies", - "messages": [ - { - "content": "\nHow do I prevent cross site request forgery (CSRF) attack?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what CSRF attack is: CSRF attack involves an attacker tricking a user into unknowingly submitting a request to a web application on which the user is authenticated. This can lead to the execution of unwanted actions on the web application without the user's consent.\n\n2. Verify user actions: To prevent CSRF attacks, it is important to verify that the user actually intends to perform the action requested. This can be done by implementing mechanisms such as CSRF tokens.\n\n3. Use CSRF tokens: CSRF tokens are unique, random tokens generated by the server and included in each request. The server can verify the token to ensure that the request is legitimate and not a result of a CSRF attack.\n\n4. Implement SameSite cookie attribute: By setting the SameSite attribute to 'Strict' or 'Lax' for cookies, you can prevent them from being sent in cross-site requests, reducing the risk of CSRF attacks.\n\n5. Use anti-CSRF frameworks: Utilize existing anti-CSRF frameworks provided by web development platforms or libraries. These frameworks often come with built-in protections against CSRF attacks, making it easier to prevent such attacks in your web application.\n\n6. Educate users: Educate users about the potential risks of CSRF attacks and advise them to be cautious when clicking on unknown links or submitting forms on unfamiliar websites.\n\nANSWER: Implement mechanisms such as CSRF tokens, use SameSite cookie attribute, utilize anti-CSRF frameworks, and educate users to prevent CSRF attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent cross site request forgery (CSRF) attack?\n***\n[Answer]: 1. Understand what CSRF attack is: CSRF attack involves an attacker tricking a user into unknowingly submitting a request to a web application on which the user is authenticated. This can lead to the execution of unwanted actions on the web application without the user's consent.\n\n2. Verify user actions: To prevent CSRF attacks, it is important to verify that the user actually intends to perform the action requested. This can be done by implementing mechanisms such as CSRF tokens.\n\n3. Use CSRF tokens: CSRF tokens are unique, random tokens generated by the server and included in each request. The server can verify the token to ensure that the request is legitimate and not a result of a CSRF attack.\n\n4. Implement SameSite cookie attribute: By setting the SameSite attribute to 'Strict' or 'Lax' for cookies, you can prevent them from being sent in cross-site requests, reducing the risk of CSRF attacks.\n\n5. Use anti-CSRF frameworks: Utilize existing anti-CSRF frameworks provided by web development platforms or libraries. These frameworks often come with built-in protections against CSRF attacks, making it easier to prevent such attacks in your web application.\n\n6. Educate users: Educate users about the potential risks of CSRF attacks and advise them to be cautious when clicking on unknown links or submitting forms on unfamiliar websites.\n\nANSWER: Implement mechanisms such as CSRF tokens, use SameSite cookie attribute, utilize anti-CSRF frameworks, and educate users to prevent CSRF attacks.\n***\n[Critique]: The answer provided is concise and covers the basic steps to prevent CSRF attacks. However, it could be improved by providing more detailed explanations for each step. For example, explaining why CSRF tokens are effective in preventing attacks and how the SameSite cookie attribute works to mitigate the risk of CSRF. Additionally, providing examples or further resources for anti-CSRF frameworks would enhance the answer. Overall, the answer could benefit from expanding on each point to provide a more comprehensive understanding of preventing CSRF attacks.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved answer: \n\n1. Understand what CSRF attack is: CSRF attack involves an attacker tricking a user into unknowingly submitting a request to a web application on which the user is authenticated. This can lead to the execution of unwanted actions on the web application without the user's consent.\n\n2. Verify user actions: To prevent CSRF attacks, it is crucial to verify that the user genuinely intends to perform the requested action. This can be achieved by implementing mechanisms such as CSRF tokens, which are unique, random tokens generated by the server and included in each request.\n\n3. Use CSRF tokens: CSRF tokens play a vital role in preventing CSRF attacks by ensuring that each request is accompanied by a token that the server can verify for legitimacy. This helps in distinguishing between valid and malicious requests.\n\n4. Implement SameSite cookie attribute: Setting the SameSite attribute of cookies to 'Strict' or 'Lax' can help prevent them from being sent in cross-site requests, thus reducing the risk of CSRF attacks. This attribute restricts the browser from sending cookies along with cross-origin requests, thereby enhancing security.\n\n5. Use anti-CSRF frameworks: Leveraging anti-CSRF frameworks provided by web development platforms or libraries can offer additional layers of protection against CSRF attacks. These frameworks typically come with pre-built defenses and best practices to safeguard web applications from such threats.\n\n6. Educate users: Educating users about CSRF attacks and advising them to exercise caution when interacting with unfamiliar links or forms can contribute significantly to preventing these types of attacks.\n\nANSWER: Implement mechanisms such as CSRF tokens, use SameSite cookie attribute, utilize anti-CSRF frameworks, and educate users to prevent CSRF attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved answer: \n\n1. Understand what CSRF attack is: CSRF attack involves an attacker tricking a user into unknowingly submitting a request to a web application on which the user is authenticated. This can lead to the execution of unwanted actions on the web application without the user's consent.\n\n2. Verify user actions: To prevent CSRF attacks, it is crucial to verify that the user genuinely intends to perform the requested action. This can be achieved by implementing mechanisms such as CSRF tokens, which are unique, random tokens generated by the server and included in each request.\n\n3. Use CSRF tokens: CSRF tokens play a vital role in preventing CSRF attacks by ensuring that each request is accompanied by a token that the server can verify for legitimacy. This helps in distinguishing between valid and malicious requests.\n\n4. Implement SameSite cookie attribute: Setting the SameSite attribute of cookies to 'Strict' or 'Lax' can help prevent them from being sent in cross-site requests, thus reducing the risk of CSRF attacks. This attribute restricts the browser from sending cookies along with cross-origin requests, thereby enhancing security.\n\n5. Use anti-CSRF frameworks: Leveraging anti-CSRF frameworks provided by web development platforms or libraries can offer additional layers of protection against CSRF attacks. These frameworks typically come with pre-built defenses and best practices to safeguard web applications from such threats.\n\n6. Educate users: Educating users about CSRF attacks and advising them to exercise caution when interacting with unfamiliar links or forms can contribute significantly to preventing these types of attacks.\n\nANSWER: Implement mechanisms such as CSRF tokens, use SameSite cookie attribute, utilize anti-CSRF frameworks, and educate users to prevent CSRF attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 874, - "output_tokens": 334, - "total_tokens": 1208 - } - }, - "score": { - "value": "C", - "answer": "Improved answer: \n\n1. Understand what CSRF attack is: CSRF attack involves an attacker tricking a user into unknowingly submitting a request to a web application on which the user is authenticated. This can lead to the execution of unwanted actions on the web application without the user's consent.\n\n2. Verify user actions: To prevent CSRF attacks, it is crucial to verify that the user genuinely intends to perform the requested action. This can be achieved by implementing mechanisms such as CSRF tokens, which are unique, random tokens generated by the server and included in each request.\n\n3. Use CSRF tokens: CSRF tokens play a vital role in preventing CSRF attacks by ensuring that each request is accompanied by a token that the server can verify for legitimacy. This helps in distinguishing between valid and malicious requests.\n\n4. Implement SameSite cookie attribute: Setting the SameSite attribute of cookies to 'Strict' or 'Lax' can help prevent them from being sent in cross-site requests, thus reducing the risk of CSRF attacks. This attribute restricts the browser from sending cookies along with cross-origin requests, thereby enhancing security.\n\n5. Use anti-CSRF frameworks: Leveraging anti-CSRF frameworks provided by web development platforms or libraries can offer additional layers of protection against CSRF attacks. These frameworks typically come with pre-built defenses and best practices to safeguard web applications from such threats.\n\n6. Educate users: Educating users about CSRF attacks and advising them to exercise caution when interacting with unfamiliar links or forms can contribute significantly to preventing these types of attacks.\n\nANSWER: Implement mechanisms such as CSRF tokens, use SameSite cookie attribute, utilize anti-CSRF frameworks, and educate users to prevent CSRF attacks.", - "explanation": "1. The expert answer mentions using frameworks that provide anti-CSRF tokens and using samesite cookies.\n2. The submission includes understanding what CSRF attack is, verifying user actions, using CSRF tokens, implementing SameSite cookie attribute, using anti-CSRF frameworks, and educating users.\n3. The submission includes all the points mentioned in the expert answer and expands on them with additional information and steps.\n4. Both the expert answer and the submission provide a comprehensive approach to preventing CSRF attacks.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent cross site request forgery (CSRF) attack?\n************\n[Expert]: Use frameworks that provide anti-CSRF tokens and use samesite cookies\n************\n[Submission]: Improved answer: \n\n1. Understand what CSRF attack is: CSRF attack involves an attacker tricking a user into unknowingly submitting a request to a web application on which the user is authenticated. This can lead to the execution of unwanted actions on the web application without the user's consent.\n\n2. Verify user actions: To prevent CSRF attacks, it is crucial to verify that the user genuinely intends to perform the requested action. This can be achieved by implementing mechanisms such as CSRF tokens, which are unique, random tokens generated by the server and included in each request.\n\n3. Use CSRF tokens: CSRF tokens play a vital role in preventing CSRF attacks by ensuring that each request is accompanied by a token that the server can verify for legitimacy. This helps in distinguishing between valid and malicious requests.\n\n4. Implement SameSite cookie attribute: Setting the SameSite attribute of cookies to 'Strict' or 'Lax' can help prevent them from being sent in cross-site requests, thus reducing the risk of CSRF attacks. This attribute restricts the browser from sending cookies along with cross-origin requests, thereby enhancing security.\n\n5. Use anti-CSRF frameworks: Leveraging anti-CSRF frameworks provided by web development platforms or libraries can offer additional layers of protection against CSRF attacks. These frameworks typically come with pre-built defenses and best practices to safeguard web applications from such threats.\n\n6. Educate users: Educating users about CSRF attacks and advising them to exercise caution when interacting with unfamiliar links or forms can contribute significantly to preventing these types of attacks.\n\nANSWER: Implement mechanisms such as CSRF tokens, use SameSite cookie attribute, utilize anti-CSRF frameworks, and educate users to prevent CSRF attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using frameworks that provide anti-CSRF tokens and using samesite cookies.\n2. The submission includes understanding what CSRF attack is, verifying user actions, using CSRF tokens, implementing SameSite cookie attribute, using anti-CSRF frameworks, and educating users.\n3. The submission includes all the points mentioned in the expert answer and expands on them with additional information and steps.\n4. Both the expert answer and the submission provide a comprehensive approach to preventing CSRF attacks.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 11, - "epoch": 1, - "input": [ - { - "content": "Which CVEs should be priorotized for patching?", - "source": "input", - "role": "user" - } - ], - "target": "CVEs actively being exploited in the wild on CISA known exploited vulnerabilities (KEV) list and ones with high CVSS score", - "messages": [ - { - "content": "\nWhich CVEs should be priorotized for patching?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Identify all the CVEs that are currently affecting your systems by checking the vulnerability database or running vulnerability scanners.\n\n2. Determine the potential impact of each CVE on your systems. Look for information on exploitability, available patches, and the likelihood of the vulnerability being exploited.\n\n3. Consider the criticality of the systems affected by each CVE. Higher priority should be given to vulnerabilities that affect critical systems or sensitive data.\n\n4. Assess the ease of patching for each CVE. Some patches may be more complex to apply than others, so prioritize those that can be easily implemented.\n\n5. Take into account any regulatory or compliance requirements that may influence your patching priorities.\n\n6. Consider the likelihood of exploitation for each CVE. Vulnerabilities that are actively being exploited in the wild should be patched immediately.\n\n7. Evaluate if there are any active threat actors targeting specific vulnerabilities that require immediate attention.\n\nANSWER: The CVEs that should be prioritized for patching are those with a high potential impact, affecting critical systems, with high exploitability, easy to patch, and actively being exploited or targeted by threat actors.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: Which CVEs should be priorotized for patching?\n***\n[Answer]: 1. Identify all the CVEs that are currently affecting your systems by checking the vulnerability database or running vulnerability scanners.\n\n2. Determine the potential impact of each CVE on your systems. Look for information on exploitability, available patches, and the likelihood of the vulnerability being exploited.\n\n3. Consider the criticality of the systems affected by each CVE. Higher priority should be given to vulnerabilities that affect critical systems or sensitive data.\n\n4. Assess the ease of patching for each CVE. Some patches may be more complex to apply than others, so prioritize those that can be easily implemented.\n\n5. Take into account any regulatory or compliance requirements that may influence your patching priorities.\n\n6. Consider the likelihood of exploitation for each CVE. Vulnerabilities that are actively being exploited in the wild should be patched immediately.\n\n7. Evaluate if there are any active threat actors targeting specific vulnerabilities that require immediate attention.\n\nANSWER: The CVEs that should be prioritized for patching are those with a high potential impact, affecting critical systems, with high exploitability, easy to patch, and actively being exploited or targeted by threat actors.\n***\n[Critique]: The answer provides a good and comprehensive approach to prioritizing CVEs for patching. However, it would have been helpful to include some examples or specific CVEs to illustrate the points mentioned in the answer. Additionally, providing information on how to stay updated on new CVEs and how frequently to reassess prioritization criteria would have further enhanced the answer. Overall, the answer is informative and well-structured.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the answer by providing examples of specific CVEs, information on staying updated on new CVEs, and the frequency of reassessing prioritization criteria would enhance the response.\n\nANSWER: The CVEs that should be prioritized for patching are those with a high potential impact, affecting critical systems, with high exploitability, easy to patch, and actively being exploited or targeted by threat actors. It is also important to stay updated on new CVEs and reassess the prioritization criteria regularly.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the answer by providing examples of specific CVEs, information on staying updated on new CVEs, and the frequency of reassessing prioritization criteria would enhance the response.\n\nANSWER: The CVEs that should be prioritized for patching are those with a high potential impact, affecting critical systems, with high exploitability, easy to patch, and actively being exploited or targeted by threat actors. It is also important to stay updated on new CVEs and reassess the prioritization criteria regularly.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 713, - "output_tokens": 101, - "total_tokens": 814 - } - }, - "score": { - "value": "C", - "answer": "Improving the answer by providing examples of specific CVEs, information on staying updated on new CVEs, and the frequency of reassessing prioritization criteria would enhance the response.\n\nANSWER: The CVEs that should be prioritized for patching are those with a high potential impact, affecting critical systems, with high exploitability, easy to patch, and actively being exploited or targeted by threat actors. It is also important to stay updated on new CVEs and reassess the prioritization criteria regularly.", - "explanation": "1. The expert answer mentions that the CVEs that should be prioritized for patching are those actively being exploited in the wild on CISA known exploited vulnerabilities list and ones with high CVSS score.\n\n2. The submission suggests prioritizing CVEs with a high potential impact, affecting critical systems, high exploitability, easy to patch, actively being exploited, and targeted by threat actors.\n\n3. The submission also includes the importance of staying updated on new CVEs and regularly reassessing the prioritization criteria.\n\nAfter comparing the content of the expert answer and the submission, it is evident that the submission contains the key content mentioned in the expert answer, such as prioritizing CVEs based on their impact, exploitability, and exploitation status, as well as the importance of staying updated on new CVEs and reassessing prioritization criteria regularly.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: Which CVEs should be priorotized for patching?\n************\n[Expert]: CVEs actively being exploited in the wild on CISA known exploited vulnerabilities (KEV) list and ones with high CVSS score\n************\n[Submission]: Improving the answer by providing examples of specific CVEs, information on staying updated on new CVEs, and the frequency of reassessing prioritization criteria would enhance the response.\n\nANSWER: The CVEs that should be prioritized for patching are those with a high potential impact, affecting critical systems, with high exploitability, easy to patch, and actively being exploited or targeted by threat actors. It is also important to stay updated on new CVEs and reassess the prioritization criteria regularly.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions that the CVEs that should be prioritized for patching are those actively being exploited in the wild on CISA known exploited vulnerabilities list and ones with high CVSS score.\n\n2. The submission suggests prioritizing CVEs with a high potential impact, affecting critical systems, high exploitability, easy to patch, actively being exploited, and targeted by threat actors.\n\n3. The submission also includes the importance of staying updated on new CVEs and regularly reassessing the prioritization criteria.\n\nAfter comparing the content of the expert answer and the submission, it is evident that the submission contains the key content mentioned in the expert answer, such as prioritizing CVEs based on their impact, exploitability, and exploitation status, as well as the importance of staying updated on new CVEs and reassessing prioritization criteria regularly.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 12, - "epoch": 1, - "input": [ - { - "content": "What attributes should I set on cookies for strong security?", - "source": "input", - "role": "user" - } - ], - "target": "secure samesite and httponly", - "messages": [ - { - "content": "\nWhat attributes should I set on cookies for strong security?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "Step 1: Set the Secure flag on the cookie, which ensures that the cookie will only be sent over HTTPS connections.\nStep 2: Set the HttpOnly flag on the cookie, which prevents client-side scripts from accessing the cookie.\nStep 3: Set the SameSite attribute to Strict or Lax to prevent Cross-Site Request Forgery (CSRF) attacks.\nStep 4: Use a secure cryptographic algorithm to sign the cookie value to prevent tampering.\nStep 5: Set a reasonable expiration time for the cookie to limit the window of opportunity for attacks.\nStep 6: Use a unique and unpredictable name for the cookie to prevent collisions with other cookies.\n\nANSWER: Secure, HttpOnly, SameSite, cryptographic algorithm, expiration time, unique cookie name", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: What attributes should I set on cookies for strong security?\n***\n[Answer]: Step 1: Set the Secure flag on the cookie, which ensures that the cookie will only be sent over HTTPS connections.\nStep 2: Set the HttpOnly flag on the cookie, which prevents client-side scripts from accessing the cookie.\nStep 3: Set the SameSite attribute to Strict or Lax to prevent Cross-Site Request Forgery (CSRF) attacks.\nStep 4: Use a secure cryptographic algorithm to sign the cookie value to prevent tampering.\nStep 5: Set a reasonable expiration time for the cookie to limit the window of opportunity for attacks.\nStep 6: Use a unique and unpredictable name for the cookie to prevent collisions with other cookies.\n\nANSWER: Secure, HttpOnly, SameSite, cryptographic algorithm, expiration time, unique cookie name\n***\n[Critique]: The answer provides a good overview of the attributes that should be set on cookies for strong security. However, it would have been more helpful if the answer had elaborated on each attribute and explained why it is important for security. Additionally, providing examples or specific recommendations for each attribute would have made the answer more comprehensive.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the answer:\nStep 1: Setting the Secure flag on the cookie ensures that the cookie will only be sent over secure HTTPS connections, preventing transmission over unsecured channels.\nStep 2: Utilizing the HttpOnly flag prevents client-side scripts from accessing cookies, reducing the risk of cross-site scripting attacks.\nStep 3: Configuring the SameSite attribute to Strict or Lax helps mitigate Cross-Site Request Forgery (CSRF) attacks by limiting when cookies are sent in cross-origin requests.\nStep 4: Employing a secure cryptographic algorithm to sign the cookie value enhances integrity and confidentiality, guarding against unauthorized modifications.\nStep 5: Establishing a reasonable expiration time for the cookie minimizes the exposure to session hijacking or replay attacks by limiting its lifespan.\nStep 6: Opting for a unique and non-predictable name for the cookie mitigates the risk of collision with other cookies, enhancing the overall security posture.\n\nANSWER: Secure flag (HTTPS), HttpOnly flag, SameSite attribute (Strict or Lax), cryptographic algorithm, expiration time, unique cookie name", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the answer:\nStep 1: Setting the Secure flag on the cookie ensures that the cookie will only be sent over secure HTTPS connections, preventing transmission over unsecured channels.\nStep 2: Utilizing the HttpOnly flag prevents client-side scripts from accessing cookies, reducing the risk of cross-site scripting attacks.\nStep 3: Configuring the SameSite attribute to Strict or Lax helps mitigate Cross-Site Request Forgery (CSRF) attacks by limiting when cookies are sent in cross-origin requests.\nStep 4: Employing a secure cryptographic algorithm to sign the cookie value enhances integrity and confidentiality, guarding against unauthorized modifications.\nStep 5: Establishing a reasonable expiration time for the cookie minimizes the exposure to session hijacking or replay attacks by limiting its lifespan.\nStep 6: Opting for a unique and non-predictable name for the cookie mitigates the risk of collision with other cookies, enhancing the overall security posture.\n\nANSWER: Secure flag (HTTPS), HttpOnly flag, SameSite attribute (Strict or Lax), cryptographic algorithm, expiration time, unique cookie name", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 559, - "output_tokens": 220, - "total_tokens": 779 - } - }, - "score": { - "value": "C", - "answer": "Improving the answer:\nStep 1: Setting the Secure flag on the cookie ensures that the cookie will only be sent over secure HTTPS connections, preventing transmission over unsecured channels.\nStep 2: Utilizing the HttpOnly flag prevents client-side scripts from accessing cookies, reducing the risk of cross-site scripting attacks.\nStep 3: Configuring the SameSite attribute to Strict or Lax helps mitigate Cross-Site Request Forgery (CSRF) attacks by limiting when cookies are sent in cross-origin requests.\nStep 4: Employing a secure cryptographic algorithm to sign the cookie value enhances integrity and confidentiality, guarding against unauthorized modifications.\nStep 5: Establishing a reasonable expiration time for the cookie minimizes the exposure to session hijacking or replay attacks by limiting its lifespan.\nStep 6: Opting for a unique and non-predictable name for the cookie mitigates the risk of collision with other cookies, enhancing the overall security posture.\n\nANSWER: Secure flag (HTTPS), HttpOnly flag, SameSite attribute (Strict or Lax), cryptographic algorithm, expiration time, unique cookie name", - "explanation": "Step 1: The submission includes setting the Secure flag on the cookie, which matches the expert answer.\nStep 2: The submission includes utilizing the HttpOnly flag, which matches the expert answer.\nStep 3: The submission includes configuring the SameSite attribute to Strict or Lax, which matches the expert answer.\nStep 4: The submission includes employing a secure cryptographic algorithm, which matches the expert answer.\nStep 5: The submission includes establishing a reasonable expiration time for the cookie, which is mentioned in the expert answer.\nStep 6: The submission includes opting for a unique and non-predictable name for the cookie, which is also mentioned in the expert answer.\n\nBased on the step by step comparison, the submission contains all the factual content mentioned in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: What attributes should I set on cookies for strong security?\n************\n[Expert]: secure samesite and httponly\n************\n[Submission]: Improving the answer:\nStep 1: Setting the Secure flag on the cookie ensures that the cookie will only be sent over secure HTTPS connections, preventing transmission over unsecured channels.\nStep 2: Utilizing the HttpOnly flag prevents client-side scripts from accessing cookies, reducing the risk of cross-site scripting attacks.\nStep 3: Configuring the SameSite attribute to Strict or Lax helps mitigate Cross-Site Request Forgery (CSRF) attacks by limiting when cookies are sent in cross-origin requests.\nStep 4: Employing a secure cryptographic algorithm to sign the cookie value enhances integrity and confidentiality, guarding against unauthorized modifications.\nStep 5: Establishing a reasonable expiration time for the cookie minimizes the exposure to session hijacking or replay attacks by limiting its lifespan.\nStep 6: Opting for a unique and non-predictable name for the cookie mitigates the risk of collision with other cookies, enhancing the overall security posture.\n\nANSWER: Secure flag (HTTPS), HttpOnly flag, SameSite attribute (Strict or Lax), cryptographic algorithm, expiration time, unique cookie name\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "Step 1: The submission includes setting the Secure flag on the cookie, which matches the expert answer.\nStep 2: The submission includes utilizing the HttpOnly flag, which matches the expert answer.\nStep 3: The submission includes configuring the SameSite attribute to Strict or Lax, which matches the expert answer.\nStep 4: The submission includes employing a secure cryptographic algorithm, which matches the expert answer.\nStep 5: The submission includes establishing a reasonable expiration time for the cookie, which is mentioned in the expert answer.\nStep 6: The submission includes opting for a unique and non-predictable name for the cookie, which is also mentioned in the expert answer.\n\nBased on the step by step comparison, the submission contains all the factual content mentioned in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 13, - "epoch": 1, - "input": [ - { - "content": "How do you prevent MFA fatigue attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use protocols like FIDO2 and educate users", - "messages": [ - { - "content": "\nHow do you prevent MFA fatigue attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand the causes of MFA fatigue attacks: MFA fatigue attacks occur when users become overwhelmed or frustrated by the multiple steps required to authenticate their identity.\n2. Identify potential triggers: Factors that can contribute to MFA fatigue attacks include too many authentication steps, complex security measures, or frequent authentication requests.\n3. Implement user-friendly MFA solutions: Choose MFA methods that are easy to use and understand, such as biometric authentication or mobile push notifications.\n4. Provide training and support: Educate users on the importance of MFA and how to use it effectively. Offer assistance and resources for troubleshooting any issues that may arise.\n5. Monitor MFA usage: Keep track of user feedback and adoption rates to identify any signs of MFA fatigue. Make adjustments as needed to improve the user experience.\n6. Encourage positive reinforcement: Recognize and reward users for successfully completing MFA processes to help maintain their motivation and engagement.\n\nANSWER: To prevent MFA fatigue attacks, organizations should implement user-friendly MFA solutions, provide training and support, monitor MFA usage, and encourage positive reinforcement.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do you prevent MFA fatigue attacks?\n***\n[Answer]: 1. Understand the causes of MFA fatigue attacks: MFA fatigue attacks occur when users become overwhelmed or frustrated by the multiple steps required to authenticate their identity.\n2. Identify potential triggers: Factors that can contribute to MFA fatigue attacks include too many authentication steps, complex security measures, or frequent authentication requests.\n3. Implement user-friendly MFA solutions: Choose MFA methods that are easy to use and understand, such as biometric authentication or mobile push notifications.\n4. Provide training and support: Educate users on the importance of MFA and how to use it effectively. Offer assistance and resources for troubleshooting any issues that may arise.\n5. Monitor MFA usage: Keep track of user feedback and adoption rates to identify any signs of MFA fatigue. Make adjustments as needed to improve the user experience.\n6. Encourage positive reinforcement: Recognize and reward users for successfully completing MFA processes to help maintain their motivation and engagement.\n\nANSWER: To prevent MFA fatigue attacks, organizations should implement user-friendly MFA solutions, provide training and support, monitor MFA usage, and encourage positive reinforcement.\n***\n[Critique]: The answer provides a good overview of steps to prevent MFA fatigue attacks. However, it lacks specific examples of user-friendly MFA solutions, training and support methods, monitoring techniques, and ways to encourage positive reinforcement. Including specific examples would have made the answer more comprehensive and practical for readers looking for actionable steps to prevent MFA fatigue attacks. Additionally, it could benefit from expanding on the importance of understanding the causes and triggers of MFA fatigue attacks in order to effectively address and prevent them.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer:\nTo prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.\n\nANSWER: To prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer:\nTo prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.\n\nANSWER: To prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 722, - "output_tokens": 192, - "total_tokens": 914 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer:\nTo prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.\n\nANSWER: To prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.", - "explanation": "1. Both the expert answer and the submission mention the implementation of user-friendly MFA solutions such as biometric authentication or mobile push notifications.\n\n2. Both responses emphasize the importance of providing training and support to educate users on MFA and how to use it effectively.\n\n3. The expert answer and the submission highlight the significance of monitoring MFA usage through feedback and adoption rates to detect signs of fatigue and make necessary improvements.\n\n4. Both answers suggest encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes to boost motivation and engagement.\n\nBased on the comparison of the factual content, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do you prevent MFA fatigue attacks?\n************\n[Expert]: use protocols like FIDO2 and educate users\n************\n[Submission]: Improved Answer:\nTo prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.\n\nANSWER: To prevent MFA fatigue attacks, organizations should implement specific user-friendly MFA solutions such as biometric authentication or mobile push notifications. It's essential to provide thorough training and support to educate users on the importance of MFA and how to use it effectively. Monitoring MFA usage through feedback and adoption rates is crucial to detect signs of fatigue and make necessary improvements. Encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes helps boost motivation and engagement.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Both the expert answer and the submission mention the implementation of user-friendly MFA solutions such as biometric authentication or mobile push notifications.\n\n2. Both responses emphasize the importance of providing training and support to educate users on MFA and how to use it effectively.\n\n3. The expert answer and the submission highlight the significance of monitoring MFA usage through feedback and adoption rates to detect signs of fatigue and make necessary improvements.\n\n4. Both answers suggest encouraging positive reinforcement by recognizing and rewarding users for successful MFA processes to boost motivation and engagement.\n\nBased on the comparison of the factual content, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 14, - "epoch": 1, - "input": [ - { - "content": "How do you keep your data secure in cloud storage?", - "source": "input", - "role": "user" - } - ], - "target": "Make sure your cloud storage is not publicly accessible and enable authentication and authorization", - "messages": [ - { - "content": "\nHow do you keep your data secure in cloud storage?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Use strong, unique passwords for your cloud storage account to prevent unauthorized access.\n2. Enable multi-factor authentication to add an extra layer of security.\n3. Encrypt your data before uploading it to the cloud to protect it from being accessed by unauthorized parties.\n4. Regularly update your cloud storage software to patch any security vulnerabilities.\n5. Be cautious about sharing your cloud storage account credentials and only grant access to trusted individuals or devices.\n6. Monitor your account activity for any suspicious behavior.\n\nANSWER: Regularly update your cloud storage software to patch any security vulnerabilities.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do you keep your data secure in cloud storage?\n***\n[Answer]: 1. Use strong, unique passwords for your cloud storage account to prevent unauthorized access.\n2. Enable multi-factor authentication to add an extra layer of security.\n3. Encrypt your data before uploading it to the cloud to protect it from being accessed by unauthorized parties.\n4. Regularly update your cloud storage software to patch any security vulnerabilities.\n5. Be cautious about sharing your cloud storage account credentials and only grant access to trusted individuals or devices.\n6. Monitor your account activity for any suspicious behavior.\n\nANSWER: Regularly update your cloud storage software to patch any security vulnerabilities.\n***\n[Critique]: The answer provided is only one aspect of keeping data secure in cloud storage. While updating software is important for security, the answer should have included more comprehensive steps such as using strong passwords, enabling multi-factor authentication, encrypting data, being cautious about sharing credentials, and monitoring account activity. Including these additional steps would have provided a more comprehensive answer to the question.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer: \n1. Use strong, unique passwords for your cloud storage account to prevent unauthorized access.\n2. Enable multi-factor authentication to add an extra layer of security.\n3. Encrypt your data before uploading it to the cloud to protect it from being accessed by unauthorized parties.\n4. Regularly update your cloud storage software to patch any security vulnerabilities.\n5. Be cautious about sharing your cloud storage account credentials and only grant access to trusted individuals or devices.\n6. Monitor your account activity for any suspicious behavior.\n\nANSWER: Regularly update your cloud storage software to patch any security vulnerabilities.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer: \n1. Use strong, unique passwords for your cloud storage account to prevent unauthorized access.\n2. Enable multi-factor authentication to add an extra layer of security.\n3. Encrypt your data before uploading it to the cloud to protect it from being accessed by unauthorized parties.\n4. Regularly update your cloud storage software to patch any security vulnerabilities.\n5. Be cautious about sharing your cloud storage account credentials and only grant access to trusted individuals or devices.\n6. Monitor your account activity for any suspicious behavior.\n\nANSWER: Regularly update your cloud storage software to patch any security vulnerabilities.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 486, - "output_tokens": 119, - "total_tokens": 605 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer: \n1. Use strong, unique passwords for your cloud storage account to prevent unauthorized access.\n2. Enable multi-factor authentication to add an extra layer of security.\n3. Encrypt your data before uploading it to the cloud to protect it from being accessed by unauthorized parties.\n4. Regularly update your cloud storage software to patch any security vulnerabilities.\n5. Be cautious about sharing your cloud storage account credentials and only grant access to trusted individuals or devices.\n6. Monitor your account activity for any suspicious behavior.\n\nANSWER: Regularly update your cloud storage software to patch any security vulnerabilities.", - "explanation": "1. The expert answer emphasizes the importance of enabling authentication and authorization for cloud storage security.\n2. The submission also mentions using strong, unique passwords and enabling multi-factor authentication, which align with authentication and authorization.\n3. Both the expert answer and the submission mention the importance of encryption to protect data.\n4. The expert answer advises to regularly update cloud storage software to patch security vulnerabilities, which is also mentioned in the submission.\n5. The submission talks about being cautious about sharing credentials and monitoring account activity, which are additional steps beyond what the expert answer mentioned.\n6. Despite the additional steps mentioned in the submission, all the key points from the expert answer are covered in the submission.\n\nTherefore, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do you keep your data secure in cloud storage?\n************\n[Expert]: Make sure your cloud storage is not publicly accessible and enable authentication and authorization\n************\n[Submission]: Improved Answer: \n1. Use strong, unique passwords for your cloud storage account to prevent unauthorized access.\n2. Enable multi-factor authentication to add an extra layer of security.\n3. Encrypt your data before uploading it to the cloud to protect it from being accessed by unauthorized parties.\n4. Regularly update your cloud storage software to patch any security vulnerabilities.\n5. Be cautious about sharing your cloud storage account credentials and only grant access to trusted individuals or devices.\n6. Monitor your account activity for any suspicious behavior.\n\nANSWER: Regularly update your cloud storage software to patch any security vulnerabilities.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer emphasizes the importance of enabling authentication and authorization for cloud storage security.\n2. The submission also mentions using strong, unique passwords and enabling multi-factor authentication, which align with authentication and authorization.\n3. Both the expert answer and the submission mention the importance of encryption to protect data.\n4. The expert answer advises to regularly update cloud storage software to patch security vulnerabilities, which is also mentioned in the submission.\n5. The submission talks about being cautious about sharing credentials and monitoring account activity, which are additional steps beyond what the expert answer mentioned.\n6. Despite the additional steps mentioned in the submission, all the key points from the expert answer are covered in the submission.\n\nTherefore, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 15, - "epoch": 1, - "input": [ - { - "content": "What algorithm should I use for digital signatures?", - "source": "input", - "role": "user" - } - ], - "target": "RSA with at least 2048bits of security or ECC algorithms and strong hashing algorithms like SHA256", - "messages": [ - { - "content": "\nWhat algorithm should I use for digital signatures?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what a digital signature is - it is a cryptographic technique that allows the verification of the sender of a message or the author of a document.\n\n2. Consider the characteristics of a good digital signature algorithm - it should provide confidentiality, integrity, authenticity, and non-repudiation.\n\n3. Research commonly used digital signature algorithms - such as RSA, DSA, ECDSA (Elliptic Curve Digital Signature Algorithm), EdDSA (Edwards-curve Digital Signature Algorithm).\n\n4. Evaluate the strengths and weaknesses of each algorithm - consider factors such as security, speed, key length, and ease of implementation.\n\n5. Choose the algorithm that best fits your specific requirements and security needs.\n\nANSWER: It is recommended to use the Elliptic Curve Digital Signature Algorithm (ECDSA) for digital signatures as it offers strong security, smaller key sizes, and faster speeds compared to other algorithms like RSA and DSA.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: What algorithm should I use for digital signatures?\n***\n[Answer]: 1. Understand what a digital signature is - it is a cryptographic technique that allows the verification of the sender of a message or the author of a document.\n\n2. Consider the characteristics of a good digital signature algorithm - it should provide confidentiality, integrity, authenticity, and non-repudiation.\n\n3. Research commonly used digital signature algorithms - such as RSA, DSA, ECDSA (Elliptic Curve Digital Signature Algorithm), EdDSA (Edwards-curve Digital Signature Algorithm).\n\n4. Evaluate the strengths and weaknesses of each algorithm - consider factors such as security, speed, key length, and ease of implementation.\n\n5. Choose the algorithm that best fits your specific requirements and security needs.\n\nANSWER: It is recommended to use the Elliptic Curve Digital Signature Algorithm (ECDSA) for digital signatures as it offers strong security, smaller key sizes, and faster speeds compared to other algorithms like RSA and DSA.\n***\n[Critique]: The answer provides a good overview of digital signatures, discussing their purpose, characteristics, common algorithms, and factors to consider when choosing an algorithm. However, the answer could be improved by providing more specific information on why ECDSA is recommended over other algorithms like RSA and DSA. It would be helpful to include a brief explanation of the strengths of ECDSA in relation to the factors mentioned (security, key size, speed) to further support the recommendation. Additionally, it would be beneficial to mention any potential weaknesses or considerations when using ECDSA to offer a more balanced view.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "To improve the answer, provide a detailed explanation of why the ECDSA algorithm is recommended over others, discussing its specific strengths in terms of security, key size, and speed. Additionally, mention any weaknesses or considerations associated with using ECDSA to offer a more balanced view.\n\nANSWER: It is recommended to use the Elliptic Curve Digital Signature Algorithm (ECDSA) for digital signatures as it offers strong security through the use of elliptic curve cryptography, smaller key sizes which lead to faster processing speeds and lower computational requirements, and its ability to provide the same level of security as RSA with a shorter key length. However, it is important to note that ECDSA may be more susceptible to certain types of attacks such as side-channel attacks, so proper implementation and protection against such attacks are essential.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "To improve the answer, provide a detailed explanation of why the ECDSA algorithm is recommended over others, discussing its specific strengths in terms of security, key size, and speed. Additionally, mention any weaknesses or considerations associated with using ECDSA to offer a more balanced view.\n\nANSWER: It is recommended to use the Elliptic Curve Digital Signature Algorithm (ECDSA) for digital signatures as it offers strong security through the use of elliptic curve cryptography, smaller key sizes which lead to faster processing speeds and lower computational requirements, and its ability to provide the same level of security as RSA with a shorter key length. However, it is important to note that ECDSA may be more susceptible to certain types of attacks such as side-channel attacks, so proper implementation and protection against such attacks are essential.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 664, - "output_tokens": 159, - "total_tokens": 823 - } - }, - "score": { - "value": "C", - "answer": "To improve the answer, provide a detailed explanation of why the ECDSA algorithm is recommended over others, discussing its specific strengths in terms of security, key size, and speed. Additionally, mention any weaknesses or considerations associated with using ECDSA to offer a more balanced view.\n\nANSWER: It is recommended to use the Elliptic Curve Digital Signature Algorithm (ECDSA) for digital signatures as it offers strong security through the use of elliptic curve cryptography, smaller key sizes which lead to faster processing speeds and lower computational requirements, and its ability to provide the same level of security as RSA with a shorter key length. However, it is important to note that ECDSA may be more susceptible to certain types of attacks such as side-channel attacks, so proper implementation and protection against such attacks are essential.", - "explanation": "1. The expert answer mentions using ECC algorithms for digital signatures. The submission specifically highlights the use of the ECDSA algorithm, which falls under ECC algorithms. This matches the expert answer.\n\n2. The expert answer mentions strong hashing algorithms like SHA256, which is not specifically mentioned in the submission. However, since the question focuses on algorithms for digital signatures, this omission may not be significant.\n\n3. The submission provides a detailed explanation of why the ECDSA algorithm is recommended over others, discussing its specific strengths in terms of security, key size, and speed. This aligns with the expert answer's emphasis on using ECC algorithms for digital signatures.\n\n4. Additionally, the submission mentions potential weaknesses or considerations associated with using ECDSA, such as susceptibility to certain types of attacks like side-channel attacks. This adds balance to the recommendation, as requested by the question.\n\nBased on the above assessment, the submitted answer closely matches the expert answer in terms of the recommended algorithm and strengths of using ECDSA for digital signatures. The additional information provided in the submission enhances the overall quality of the response.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: What algorithm should I use for digital signatures?\n************\n[Expert]: RSA with at least 2048bits of security or ECC algorithms and strong hashing algorithms like SHA256\n************\n[Submission]: To improve the answer, provide a detailed explanation of why the ECDSA algorithm is recommended over others, discussing its specific strengths in terms of security, key size, and speed. Additionally, mention any weaknesses or considerations associated with using ECDSA to offer a more balanced view.\n\nANSWER: It is recommended to use the Elliptic Curve Digital Signature Algorithm (ECDSA) for digital signatures as it offers strong security through the use of elliptic curve cryptography, smaller key sizes which lead to faster processing speeds and lower computational requirements, and its ability to provide the same level of security as RSA with a shorter key length. However, it is important to note that ECDSA may be more susceptible to certain types of attacks such as side-channel attacks, so proper implementation and protection against such attacks are essential.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using ECC algorithms for digital signatures. The submission specifically highlights the use of the ECDSA algorithm, which falls under ECC algorithms. This matches the expert answer.\n\n2. The expert answer mentions strong hashing algorithms like SHA256, which is not specifically mentioned in the submission. However, since the question focuses on algorithms for digital signatures, this omission may not be significant.\n\n3. The submission provides a detailed explanation of why the ECDSA algorithm is recommended over others, discussing its specific strengths in terms of security, key size, and speed. This aligns with the expert answer's emphasis on using ECC algorithms for digital signatures.\n\n4. Additionally, the submission mentions potential weaknesses or considerations associated with using ECDSA, such as susceptibility to certain types of attacks like side-channel attacks. This adds balance to the recommendation, as requested by the question.\n\nBased on the above assessment, the submitted answer closely matches the expert answer in terms of the recommended algorithm and strengths of using ECDSA for digital signatures. The additional information provided in the submission enhances the overall quality of the response.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - }, - { - "id": 16, - "epoch": 1, - "input": [ - { - "content": "What security attributes should I avoid when using content security policy (CSP)?", - "source": "input", - "role": "user" - } - ], - "target": "avoid unsafe-eval and unsafe-inline", - "messages": [ - { - "content": "\nWhat security attributes should I avoid when using content security policy (CSP)?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Avoid using inline styles or scripts. These can bypass CSP restrictions and make your website vulnerable to XSS attacks.\n2. Avoid using unsafe-inline or unsafe-eval in your script-src directive. These options can allow potentially harmful scripts to be executed on your website.\n3. Avoid using wildcard (*) in your directives. This can open up your website to various types of attacks as it allows loading content from any source.\n4. Avoid using outdated or deprecated directives. Make sure to stay updated on the latest CSP recommendations to ensure maximum security for your website.\n\nANSWER: Avoid using inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: What security attributes should I avoid when using content security policy (CSP)?\n***\n[Answer]: 1. Avoid using inline styles or scripts. These can bypass CSP restrictions and make your website vulnerable to XSS attacks.\n2. Avoid using unsafe-inline or unsafe-eval in your script-src directive. These options can allow potentially harmful scripts to be executed on your website.\n3. Avoid using wildcard (*) in your directives. This can open up your website to various types of attacks as it allows loading content from any source.\n4. Avoid using outdated or deprecated directives. Make sure to stay updated on the latest CSP recommendations to ensure maximum security for your website.\n\nANSWER: Avoid using inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives.\n***\n[Critique]: The answer provided is concise and correctly identifies the security attributes that should be avoided when using content security policy (CSP). However, it would have been more helpful if the answer had explained why each of these attributes should be avoided and the potential risks associated with using them. Providing a brief explanation for each point would have improved the overall effectiveness of the answer.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer:\n1. Avoid using inline styles or scripts as they can bypass CSP restrictions, potentially leading to Cross-Site Scripting (XSS) attacks that inject malicious scripts into your website.\n2. Avoid using unsafe-inline or unsafe-eval in your script-src directive since they allow execution of arbitrary scripts, opening up your website to a higher risk of XSS attacks.\n3. Avoid using wildcard (*) in your directives as it allows loading content from any source, increasing the surface area for potential attacks.\n4. Avoid using outdated or deprecated directives as they may lack essential security features, making your CSP less effective in protecting your website from threats.\n\nANSWER: Avoid using inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer:\n1. Avoid using inline styles or scripts as they can bypass CSP restrictions, potentially leading to Cross-Site Scripting (XSS) attacks that inject malicious scripts into your website.\n2. Avoid using unsafe-inline or unsafe-eval in your script-src directive since they allow execution of arbitrary scripts, opening up your website to a higher risk of XSS attacks.\n3. Avoid using wildcard (*) in your directives as it allows loading content from any source, increasing the surface area for potential attacks.\n4. Avoid using outdated or deprecated directives as they may lack essential security features, making your CSP less effective in protecting your website from threats.\n\nANSWER: Avoid using inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 533, - "output_tokens": 153, - "total_tokens": 686 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer:\n1. Avoid using inline styles or scripts as they can bypass CSP restrictions, potentially leading to Cross-Site Scripting (XSS) attacks that inject malicious scripts into your website.\n2. Avoid using unsafe-inline or unsafe-eval in your script-src directive since they allow execution of arbitrary scripts, opening up your website to a higher risk of XSS attacks.\n3. Avoid using wildcard (*) in your directives as it allows loading content from any source, increasing the surface area for potential attacks.\n4. Avoid using outdated or deprecated directives as they may lack essential security features, making your CSP less effective in protecting your website from threats.\n\nANSWER: Avoid using inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives.", - "explanation": "1. The expert answer mentions avoiding unsafe-eval and unsafe-inline attributes in CSP.\n2. The submission includes a similar point about avoiding unsafe-inline and unsafe-eval in the script-src directive.\n3. The submission also adds information about avoiding wildcard (*) and outdated directives in CSP.\n4. The final answer in the submission consolidates all the mentioned attributes to avoid inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives. \n\nConsidering the above points, the submission contains the same content as the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: What security attributes should I avoid when using content security policy (CSP)?\n************\n[Expert]: avoid unsafe-eval and unsafe-inline\n************\n[Submission]: Improved Answer:\n1. Avoid using inline styles or scripts as they can bypass CSP restrictions, potentially leading to Cross-Site Scripting (XSS) attacks that inject malicious scripts into your website.\n2. Avoid using unsafe-inline or unsafe-eval in your script-src directive since they allow execution of arbitrary scripts, opening up your website to a higher risk of XSS attacks.\n3. Avoid using wildcard (*) in your directives as it allows loading content from any source, increasing the surface area for potential attacks.\n4. Avoid using outdated or deprecated directives as they may lack essential security features, making your CSP less effective in protecting your website from threats.\n\nANSWER: Avoid using inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions avoiding unsafe-eval and unsafe-inline attributes in CSP.\n2. The submission includes a similar point about avoiding unsafe-inline and unsafe-eval in the script-src directive.\n3. The submission also adds information about avoiding wildcard (*) and outdated directives in CSP.\n4. The final answer in the submission consolidates all the mentioned attributes to avoid inline styles or scripts, unsafe-inline or unsafe-eval, wildcards (*), and outdated directives. \n\nConsidering the above points, the submission contains the same content as the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717805864505.028 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717805865990.4749 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866090.028 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866093.23 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866170.356 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866173.562 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866185.929 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866190.847 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866206.274 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866215.4119 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866233.495 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866237.55 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866249.0828 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866252.4019 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866263.769 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866267.166 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866277.3792 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866280.9292 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866290.7869 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866293.709 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866303.785 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805866307.164 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805868378.34 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805868382.6702 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805868594.109 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805868600.685 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805868853.492 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805868860.48 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869060.117 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869066.137 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869338.7961 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869343.554 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869697.059 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869702.526 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869713.049 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869717.366 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869908.201 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869915.122 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869985.2988 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805869992.1082 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870071.074 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870074.943 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870205.407 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870210.679 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870471.872 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870477.3481 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870715.1338 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870722.952 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870741.7622 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805870746.961 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871022.944 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871035.1182 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871174.795 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871180.044 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871241.87 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871245.358 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871442.0889 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805871448.3098 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. 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Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805878641.544 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805878646.081 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805878838.666 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805878845.203 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. 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Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717805883681.9 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-20-55-07-00_security-guide_8muqC7EeXUZZR87SPgGhkw.json b/logs/2024-06-07T17-20-55-07-00_security-guide_8muqC7EeXUZZR87SPgGhkw.json deleted file mode 100644 index 66314be9..00000000 --- a/logs/2024-06-07T17-20-55-07-00_security-guide_8muqC7EeXUZZR87SPgGhkw.json +++ /dev/null @@ -1,202 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "8muqC7EeXUZZR87SPgGhkw", - "run_id": "7M2AcZQYx4PQjBur2URRtv", - "created": "2024-06-07T17:20:55-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-07T17:20:55-07:00", - "completed_at": "2024-06-07T17:21:07-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1615, - "output_tokens": 765, - "total_tokens": 2380 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what SQL Injection attacks are: SQL Injection is a technique where an attacker inserts malicious SQL statements into input fields of a web application, manipulating the database to perform unintended actions.\n\n2. Sanitize user inputs: Always validate and sanitize any user inputs before using them in SQL queries. This can include using prepared statements or parameterized queries that separate SQL code from user input.\n\n3. Use stored procedures: Another way to prevent SQL Injection attacks is to use stored procedures instead of dynamically building SQL queries in your code. Stored procedures can help to prevent direct SQL code injection.\n\n4. Limit database permissions: Ensure that your database users have only the necessary permissions to perform their tasks. Avoid using superuser accounts for everyday operations.\n\n5. Implement least privilege principle: Give users the minimum level of access they need to perform their tasks. This reduces the risk of attackers exploiting higher privileges.\n\n6. Regularly update your software: Keep your database management system, web server, and application software updated with the latest security patches to protect against known vulnerabilities.\n\nANSWER: To prevent SQL Injection attacks, sanitize user inputs, use prepared statements, stored procedures, limit database permissions, implement least privilege principle, and regularly update software.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: 1. Understand what SQL Injection attacks are: SQL Injection is a technique where an attacker inserts malicious SQL statements into input fields of a web application, manipulating the database to perform unintended actions.\n\n2. Sanitize user inputs: Always validate and sanitize any user inputs before using them in SQL queries. This can include using prepared statements or parameterized queries that separate SQL code from user input.\n\n3. Use stored procedures: Another way to prevent SQL Injection attacks is to use stored procedures instead of dynamically building SQL queries in your code. Stored procedures can help to prevent direct SQL code injection.\n\n4. Limit database permissions: Ensure that your database users have only the necessary permissions to perform their tasks. Avoid using superuser accounts for everyday operations.\n\n5. Implement least privilege principle: Give users the minimum level of access they need to perform their tasks. This reduces the risk of attackers exploiting higher privileges.\n\n6. Regularly update your software: Keep your database management system, web server, and application software updated with the latest security patches to protect against known vulnerabilities.\n\nANSWER: To prevent SQL Injection attacks, sanitize user inputs, use prepared statements, stored procedures, limit database permissions, implement least privilege principle, and regularly update software.\n***\n[Critique]: The answer provided is thorough and covers various methods to prevent SQL Injection attacks. However, the answer could be improved by providing more specific examples or explanations for each point to make it more informative and easier to understand for someone unfamiliar with the topic. Additionally, a brief explanation of why each step is effective in preventing SQL Injection attacks would also enhance the answer.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer:\n\n1. Understanding SQL Injection attacks: It is crucial to comprehend how SQL Injection attacks work in order to effectively prevent them.\n2. Sanitizing user inputs: Validating and sanitizing user inputs before using them in SQL queries is a critical step. Techniques such as prepared statements and parameterized queries should be used to separate user input from SQL code.\n3. Utilizing stored procedures: By employing stored procedures instead of dynamically constructing SQL queries within the code, the risk of direct SQL code injection can be minimized.\n4. Limiting database permissions: Ensuring that database users only have the necessary permissions can help mitigate the impact of any successful SQL Injection attacks.\n5. Implementing the principle of least privilege: Providing users with the minimum level of access required for their tasks reduces the likelihood of attackers exploiting higher privileges.\n6. Regular software updates: Keeping all software components, including the database management system, web server, and applications up to date with security patches is crucial to protect against known vulnerabilities.\n\nANSWER: To prevent SQL Injection attacks, it is essential to understand the attack, sanitize user inputs, use stored procedures, limit database permissions, implement the principle of least privilege, and regularly update software.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer:\n\n1. Understanding SQL Injection attacks: It is crucial to comprehend how SQL Injection attacks work in order to effectively prevent them.\n2. Sanitizing user inputs: Validating and sanitizing user inputs before using them in SQL queries is a critical step. Techniques such as prepared statements and parameterized queries should be used to separate user input from SQL code.\n3. Utilizing stored procedures: By employing stored procedures instead of dynamically constructing SQL queries within the code, the risk of direct SQL code injection can be minimized.\n4. Limiting database permissions: Ensuring that database users only have the necessary permissions can help mitigate the impact of any successful SQL Injection attacks.\n5. Implementing the principle of least privilege: Providing users with the minimum level of access required for their tasks reduces the likelihood of attackers exploiting higher privileges.\n6. Regular software updates: Keeping all software components, including the database management system, web server, and applications up to date with security patches is crucial to protect against known vulnerabilities.\n\nANSWER: To prevent SQL Injection attacks, it is essential to understand the attack, sanitize user inputs, use stored procedures, limit database permissions, implement the principle of least privilege, and regularly update software.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 732, - "output_tokens": 242, - "total_tokens": 974 - } - }, - "score": { - "value": "I", - "answer": "Improved Answer:\n\n1. Understanding SQL Injection attacks: It is crucial to comprehend how SQL Injection attacks work in order to effectively prevent them.\n2. Sanitizing user inputs: Validating and sanitizing user inputs before using them in SQL queries is a critical step. Techniques such as prepared statements and parameterized queries should be used to separate user input from SQL code.\n3. Utilizing stored procedures: By employing stored procedures instead of dynamically constructing SQL queries within the code, the risk of direct SQL code injection can be minimized.\n4. Limiting database permissions: Ensuring that database users only have the necessary permissions can help mitigate the impact of any successful SQL Injection attacks.\n5. Implementing the principle of least privilege: Providing users with the minimum level of access required for their tasks reduces the likelihood of attackers exploiting higher privileges.\n6. Regular software updates: Keeping all software components, including the database management system, web server, and applications up to date with security patches is crucial to protect against known vulnerabilities.\n\nANSWER: To prevent SQL Injection attacks, it is essential to understand the attack, sanitize user inputs, use stored procedures, limit database permissions, implement the principle of least privilege, and regularly update software.", - "explanation": "1. The expert answer mentions using parameterized queries and prepared statements as a way to prevent SQL Injection attacks.\n2. The submission also includes the use of parameterized queries and prepared statements as a method to prevent SQL Injection attacks.\n3. The expert answer talks about the importance of understanding SQL Injection attacks, while the submission also mentions the significance of comprehending how the attacks work.\n4. The expert answer discusses limiting database permissions and implementing the principle of least privilege, two points also included in the submission.\n5. The expert answer does not specifically mention sanitizing user inputs or utilizing stored procedures, although these are included in the submission as prevention measures.\n6. Both the expert answer and the submission stress the importance of regular software updates as a preventive measure against SQL Injection attacks.\n\nAfter carefully comparing the factual content of the submission with the expert answer, it is clear that the submission contains additional information beyond what the expert answer provided. While the submitted answer includes some relevant information, it also introduces points that were not mentioned in the expert answer. \n\nGRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improved Answer:\n\n1. Understanding SQL Injection attacks: It is crucial to comprehend how SQL Injection attacks work in order to effectively prevent them.\n2. Sanitizing user inputs: Validating and sanitizing user inputs before using them in SQL queries is a critical step. Techniques such as prepared statements and parameterized queries should be used to separate user input from SQL code.\n3. Utilizing stored procedures: By employing stored procedures instead of dynamically constructing SQL queries within the code, the risk of direct SQL code injection can be minimized.\n4. Limiting database permissions: Ensuring that database users only have the necessary permissions can help mitigate the impact of any successful SQL Injection attacks.\n5. Implementing the principle of least privilege: Providing users with the minimum level of access required for their tasks reduces the likelihood of attackers exploiting higher privileges.\n6. Regular software updates: Keeping all software components, including the database management system, web server, and applications up to date with security patches is crucial to protect against known vulnerabilities.\n\nANSWER: To prevent SQL Injection attacks, it is essential to understand the attack, sanitize user inputs, use stored procedures, limit database permissions, implement the principle of least privilege, and regularly update software.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using parameterized queries and prepared statements as a way to prevent SQL Injection attacks.\n2. The submission also includes the use of parameterized queries and prepared statements as a method to prevent SQL Injection attacks.\n3. The expert answer talks about the importance of understanding SQL Injection attacks, while the submission also mentions the significance of comprehending how the attacks work.\n4. The expert answer discusses limiting database permissions and implementing the principle of least privilege, two points also included in the submission.\n5. The expert answer does not specifically mention sanitizing user inputs or utilizing stored procedures, although these are included in the submission as prevention measures.\n6. Both the expert answer and the submission stress the importance of regular software updates as a preventive measure against SQL Injection attacks.\n\nAfter carefully comparing the factual content of the submission with the expert answer, it is clear that the submission contains additional information beyond what the expert answer provided. While the submitted answer includes some relevant information, it also introduces points that were not mentioned in the expert answer. \n\nGRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717806053854.3958 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717806055453.726 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806055556.232 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806055559.72 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806058646.4573 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806058650.2039 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806059860.138 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806059864.2039 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806063529.076 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806063535.067 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-35-00-07-00_security-guide_cPwNbU4bKotTZqhPZf5e74.json b/logs/2024-06-07T17-35-00-07-00_security-guide_cPwNbU4bKotTZqhPZf5e74.json deleted file mode 100644 index 27bc8d40..00000000 --- a/logs/2024-06-07T17-35-00-07-00_security-guide_cPwNbU4bKotTZqhPZf5e74.json +++ /dev/null @@ -1,202 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "cPwNbU4bKotTZqhPZf5e74", - "run_id": "bqv5aCsExQMxUxbh47Eua4", - "created": "2024-06-07T17:35:00-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 1.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-07T17:35:00-07:00", - "completed_at": "2024-06-07T17:35:13-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1628, - "output_tokens": 825, - "total_tokens": 2453 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what SQL injection is: SQL injection is a type of cyber attack where attackers insert malicious SQL statements into input fields on a website to manipulate the database.\n\n2. Use parameterized queries: Parameterized queries separate the SQL code from the user input, preventing attackers from injecting malicious code into the SQL statement.\n\n3. Input validation: Validate and sanitize all user inputs to ensure they only contain expected data types and values. This will reduce the possibility of malicious input being entered.\n\n4. Use stored procedures: Stored procedures are precompiled SQL queries that can be called by your application. They can help prevent SQL injection by not allowing dynamic SQL queries to be run.\n\n5. Principle of least privilege: Ensure that your database user accounts have the least amount of privileges necessary to perform their duties. This way, even if a SQL injection attack is successful, the attacker will have limited access to the database.\n\nANSWER: Use parameterized queries, input validation, stored procedures, and principle of least privilege to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: 1. Understand what SQL injection is: SQL injection is a type of cyber attack where attackers insert malicious SQL statements into input fields on a website to manipulate the database.\n\n2. Use parameterized queries: Parameterized queries separate the SQL code from the user input, preventing attackers from injecting malicious code into the SQL statement.\n\n3. Input validation: Validate and sanitize all user inputs to ensure they only contain expected data types and values. This will reduce the possibility of malicious input being entered.\n\n4. Use stored procedures: Stored procedures are precompiled SQL queries that can be called by your application. They can help prevent SQL injection by not allowing dynamic SQL queries to be run.\n\n5. Principle of least privilege: Ensure that your database user accounts have the least amount of privileges necessary to perform their duties. This way, even if a SQL injection attack is successful, the attacker will have limited access to the database.\n\nANSWER: Use parameterized queries, input validation, stored procedures, and principle of least privilege to prevent SQL Injection attacks.\n***\n[Critique]: The answer provides a good summary of ways to prevent SQL injection attacks, but it would be better if more detail was provided for each point. For example, explaining how parameterized queries work and why they prevent SQL injection would be helpful for someone looking to understand the solution. Additionally, providing examples or additional resources for further reading would enhance the answer. It could also benefit from mentioning other methods such as escaping user inputs or using an ORM (Object-Relational Mapping) tool. Adding these details would make the answer more comprehensive and informative.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer:\n1. Understand what SQL injection is: SQL injection is a type of cyber attack where attackers insert malicious SQL statements into input fields on a website to manipulate the database. It occurs when a user input is not properly validated and sanitized before being executed as an SQL query, allowing attackers to insert their own SQL code.\n\n2. Use parameterized queries: Parameterized queries are SQL statements that include placeholders for parameters. These parameters are then securely passed into the query separately, ensuring that user input is treated as data and not as executable code. This prevents attackers from injecting malicious SQL statements.\n\n3. Input validation and sanitization: Validate and sanitize all user inputs to ensure they adhere to specified data types and formats. Input validation checks if the input meets certain criteria, while sanitization removes potentially harmful characters or code. By implementing strict input validation and sanitization, you can significantly reduce the risk of SQL injection attacks.\n\n4. Use stored procedures: Stored procedures are precompiled SQL queries that are stored in the database and can be called by the application. By utilizing stored procedures, you limit the surface area for potential SQL injection attacks, as the procedures do not directly concatenate user input with SQL code, making them inherently more secure.\n\n5. Principle of least privilege: Apply the principle of least privilege to your database user accounts by granting them only the necessary permissions to perform their intended tasks. In the event of a successful SQL injection attack, limiting the privileges of compromised accounts can help mitigate the extent of potential damage to your database.\n\nANSWER: Use parameterized queries, input validation, stored procedures, and principle of least privilege to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer:\n1. Understand what SQL injection is: SQL injection is a type of cyber attack where attackers insert malicious SQL statements into input fields on a website to manipulate the database. It occurs when a user input is not properly validated and sanitized before being executed as an SQL query, allowing attackers to insert their own SQL code.\n\n2. Use parameterized queries: Parameterized queries are SQL statements that include placeholders for parameters. These parameters are then securely passed into the query separately, ensuring that user input is treated as data and not as executable code. This prevents attackers from injecting malicious SQL statements.\n\n3. Input validation and sanitization: Validate and sanitize all user inputs to ensure they adhere to specified data types and formats. Input validation checks if the input meets certain criteria, while sanitization removes potentially harmful characters or code. By implementing strict input validation and sanitization, you can significantly reduce the risk of SQL injection attacks.\n\n4. Use stored procedures: Stored procedures are precompiled SQL queries that are stored in the database and can be called by the application. By utilizing stored procedures, you limit the surface area for potential SQL injection attacks, as the procedures do not directly concatenate user input with SQL code, making them inherently more secure.\n\n5. Principle of least privilege: Apply the principle of least privilege to your database user accounts by granting them only the necessary permissions to perform their intended tasks. In the event of a successful SQL injection attack, limiting the privileges of compromised accounts can help mitigate the extent of potential damage to your database.\n\nANSWER: Use parameterized queries, input validation, stored procedures, and principle of least privilege to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 695, - "output_tokens": 329, - "total_tokens": 1024 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer:\n1. Understand what SQL injection is: SQL injection is a type of cyber attack where attackers insert malicious SQL statements into input fields on a website to manipulate the database. It occurs when a user input is not properly validated and sanitized before being executed as an SQL query, allowing attackers to insert their own SQL code.\n\n2. Use parameterized queries: Parameterized queries are SQL statements that include placeholders for parameters. These parameters are then securely passed into the query separately, ensuring that user input is treated as data and not as executable code. This prevents attackers from injecting malicious SQL statements.\n\n3. Input validation and sanitization: Validate and sanitize all user inputs to ensure they adhere to specified data types and formats. Input validation checks if the input meets certain criteria, while sanitization removes potentially harmful characters or code. By implementing strict input validation and sanitization, you can significantly reduce the risk of SQL injection attacks.\n\n4. Use stored procedures: Stored procedures are precompiled SQL queries that are stored in the database and can be called by the application. By utilizing stored procedures, you limit the surface area for potential SQL injection attacks, as the procedures do not directly concatenate user input with SQL code, making them inherently more secure.\n\n5. Principle of least privilege: Apply the principle of least privilege to your database user accounts by granting them only the necessary permissions to perform their intended tasks. In the event of a successful SQL injection attack, limiting the privileges of compromised accounts can help mitigate the extent of potential damage to your database.\n\nANSWER: Use parameterized queries, input validation, stored procedures, and principle of least privilege to prevent SQL Injection attacks.", - "explanation": "1. The expert answer mentions using parameterized queries and prepared statements to prevent SQL Injection attacks.\n2. The submission also mentions using parameterized queries as a method to prevent SQL Injection attacks.\n3. The expert answer does not directly mention input validation and sanitization as a method, but the submission includes it as a method to prevent SQL Injection attacks.\n4. The expert answer does not directly mention stored procedures as a method, but the submission includes it as a method to prevent SQL Injection attacks.\n5. The expert answer does not directly mention the principle of least privilege as a method, but the submission includes it as a method to prevent SQL Injection attacks.\n\nAfter carefully comparing the factual content of both the expert answer and the submission, it is evident that the submission contains content beyond what the expert mentioned, covering additional methods to prevent SQL Injection attacks. Therefore, the submission is comprehensive in providing more prevention methods.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improved Answer:\n1. Understand what SQL injection is: SQL injection is a type of cyber attack where attackers insert malicious SQL statements into input fields on a website to manipulate the database. It occurs when a user input is not properly validated and sanitized before being executed as an SQL query, allowing attackers to insert their own SQL code.\n\n2. Use parameterized queries: Parameterized queries are SQL statements that include placeholders for parameters. These parameters are then securely passed into the query separately, ensuring that user input is treated as data and not as executable code. This prevents attackers from injecting malicious SQL statements.\n\n3. Input validation and sanitization: Validate and sanitize all user inputs to ensure they adhere to specified data types and formats. Input validation checks if the input meets certain criteria, while sanitization removes potentially harmful characters or code. By implementing strict input validation and sanitization, you can significantly reduce the risk of SQL injection attacks.\n\n4. Use stored procedures: Stored procedures are precompiled SQL queries that are stored in the database and can be called by the application. By utilizing stored procedures, you limit the surface area for potential SQL injection attacks, as the procedures do not directly concatenate user input with SQL code, making them inherently more secure.\n\n5. Principle of least privilege: Apply the principle of least privilege to your database user accounts by granting them only the necessary permissions to perform their intended tasks. In the event of a successful SQL injection attack, limiting the privileges of compromised accounts can help mitigate the extent of potential damage to your database.\n\nANSWER: Use parameterized queries, input validation, stored procedures, and principle of least privilege to prevent SQL Injection attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer mentions using parameterized queries and prepared statements to prevent SQL Injection attacks.\n2. The submission also mentions using parameterized queries as a method to prevent SQL Injection attacks.\n3. The expert answer does not directly mention input validation and sanitization as a method, but the submission includes it as a method to prevent SQL Injection attacks.\n4. The expert answer does not directly mention stored procedures as a method, but the submission includes it as a method to prevent SQL Injection attacks.\n5. The expert answer does not directly mention the principle of least privilege as a method, but the submission includes it as a method to prevent SQL Injection attacks.\n\nAfter carefully comparing the factual content of both the expert answer and the submission, it is evident that the submission contains content beyond what the expert mentioned, covering additional methods to prevent SQL Injection attacks. Therefore, the submission is comprehensive in providing more prevention methods.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717806898967.477 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717806900454.866 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806900548.1619 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806900551.728 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806904068.788 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806904072.5708 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806905631.861 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806905638.8481 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806910520.161 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806910523.899 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-07T17-35-55-07-00_security-guide_VWvxnwoDsp6HYn6fbt9Tri.json b/logs/2024-06-07T17-35-55-07-00_security-guide_VWvxnwoDsp6HYn6fbt9Tri.json deleted file mode 100644 index bcc6ca0c..00000000 --- a/logs/2024-06-07T17-35-55-07-00_security-guide_VWvxnwoDsp6HYn6fbt9Tri.json +++ /dev/null @@ -1,202 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "VWvxnwoDsp6HYn6fbt9Tri", - "run_id": "JprV6Ky6ifNiQXCqHQqg5S", - "created": "2024-06-07T17:35:55-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "b691996" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 1.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-07T17:35:55-07:00", - "completed_at": "2024-06-07T17:36:03-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1433, - "output_tokens": 616, - "total_tokens": 2049 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what a SQL Injection attack is - SQL Injection is a type of attack where an attacker inserts malicious SQL statements into a web application input field to manipulate the database.\n\n2. Use Parameterized Queries - Prepared statements and parameterized queries prevent SQL Injection by separating the SQL code from the data input. This means that the input is treated as data rather than executable code.\n\n3. Input validation - Validate and sanitize input data before incorporating it into SQL queries. This helps to ensure that only expected data types are accepted.\n\n4. Use ORM tools - Object-Relational Mapping (ORM) tools automatically handle escaping input data and help prevent SQL Injection attacks.\n\n5. Limit Database Privileges - Ensure that the database user account used by the application has the least necessary permissions to reduce the impact of a successful SQL Injection attack.\n\nANSWER: Utilize parameterized queries, input validation, ORM tools, and limit database privileges to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: 1. Understand what a SQL Injection attack is - SQL Injection is a type of attack where an attacker inserts malicious SQL statements into a web application input field to manipulate the database.\n\n2. Use Parameterized Queries - Prepared statements and parameterized queries prevent SQL Injection by separating the SQL code from the data input. This means that the input is treated as data rather than executable code.\n\n3. Input validation - Validate and sanitize input data before incorporating it into SQL queries. This helps to ensure that only expected data types are accepted.\n\n4. Use ORM tools - Object-Relational Mapping (ORM) tools automatically handle escaping input data and help prevent SQL Injection attacks.\n\n5. Limit Database Privileges - Ensure that the database user account used by the application has the least necessary permissions to reduce the impact of a successful SQL Injection attack.\n\nANSWER: Utilize parameterized queries, input validation, ORM tools, and limit database privileges to prevent SQL Injection attacks.\n***\n[Critique]: The answer provided is comprehensive and covers key methods to prevent SQL Injection attacks, such as understanding what it is, using parameterized queries, input validation, ORM tools, and limiting database privileges. However, the answer could be improved by providing more detail on each point, explaining why each method is effective in preventing SQL Injection attacks, and perhaps providing examples or best practices for implementing each method. This would enhance the clarity and depth of the response.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "[Improved Answer]:\n\n1. **Understand what SQL Injection is**: Educate yourself and your team on the concept of SQL Injection and the potential risks it poses to your application.\n\n2. **Use Parameterized Queries**: Implement prepared statements or parameterized queries to separate SQL code from user input, preventing the injection of malicious code.\n\n3. **Input Validation and Sanitization**: Validate and sanitize all user inputs to your application to ensure they conform to expected data types and prevent unwanted SQL code execution.\n\n4. **Utilize ORM Tools**: Employ Object-Relational Mapping (ORM) libraries or frameworks that handle database interactions securely and automatically escape user inputs to prevent SQL Injection attacks.\n\n5. **Limit Database User Privileges**: Restrict the permissions of your database user accounts to only the necessary actions required by the application, reducing the potential impact of a successful SQL Injection attack.\n\n**ANSWER**: Utilize parameterized queries, input validation, ORM tools, and limit database privileges to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "[Improved Answer]:\n\n1. **Understand what SQL Injection is**: Educate yourself and your team on the concept of SQL Injection and the potential risks it poses to your application.\n\n2. **Use Parameterized Queries**: Implement prepared statements or parameterized queries to separate SQL code from user input, preventing the injection of malicious code.\n\n3. **Input Validation and Sanitization**: Validate and sanitize all user inputs to your application to ensure they conform to expected data types and prevent unwanted SQL code execution.\n\n4. **Utilize ORM Tools**: Employ Object-Relational Mapping (ORM) libraries or frameworks that handle database interactions securely and automatically escape user inputs to prevent SQL Injection attacks.\n\n5. **Limit Database User Privileges**: Restrict the permissions of your database user accounts to only the necessary actions required by the application, reducing the potential impact of a successful SQL Injection attack.\n\n**ANSWER**: Utilize parameterized queries, input validation, ORM tools, and limit database privileges to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 644, - "output_tokens": 201, - "total_tokens": 845 - } - }, - "score": { - "value": "C", - "answer": "[Improved Answer]:\n\n1. **Understand what SQL Injection is**: Educate yourself and your team on the concept of SQL Injection and the potential risks it poses to your application.\n\n2. **Use Parameterized Queries**: Implement prepared statements or parameterized queries to separate SQL code from user input, preventing the injection of malicious code.\n\n3. **Input Validation and Sanitization**: Validate and sanitize all user inputs to your application to ensure they conform to expected data types and prevent unwanted SQL code execution.\n\n4. **Utilize ORM Tools**: Employ Object-Relational Mapping (ORM) libraries or frameworks that handle database interactions securely and automatically escape user inputs to prevent SQL Injection attacks.\n\n5. **Limit Database User Privileges**: Restrict the permissions of your database user accounts to only the necessary actions required by the application, reducing the potential impact of a successful SQL Injection attack.\n\n**ANSWER**: Utilize parameterized queries, input validation, ORM tools, and limit database privileges to prevent SQL Injection attacks.", - "explanation": "1. Expert answer: use parameterized queries and prepared statements\nSubmission:\n- Mentions understanding SQL Injection\n- Mentions using parameterized queries \n- Mentions input validation and sanitization\n- Mentions utilizing ORM tools\n- Mentions limiting database user privileges\n\n2. The submission covers all the points mentioned in the expert answer (use parameterized queries) and expands on them with additional measures such as input validation, ORM tools, and limiting database user privileges.\n\n3. The submission provides a comprehensive approach to preventing SQL Injection attacks, going beyond just using parameterized queries and prepared statements.\n\nBased on the above analysis, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: [Improved Answer]:\n\n1. **Understand what SQL Injection is**: Educate yourself and your team on the concept of SQL Injection and the potential risks it poses to your application.\n\n2. **Use Parameterized Queries**: Implement prepared statements or parameterized queries to separate SQL code from user input, preventing the injection of malicious code.\n\n3. **Input Validation and Sanitization**: Validate and sanitize all user inputs to your application to ensure they conform to expected data types and prevent unwanted SQL code execution.\n\n4. **Utilize ORM Tools**: Employ Object-Relational Mapping (ORM) libraries or frameworks that handle database interactions securely and automatically escape user inputs to prevent SQL Injection attacks.\n\n5. **Limit Database User Privileges**: Restrict the permissions of your database user accounts to only the necessary actions required by the application, reducing the potential impact of a successful SQL Injection attack.\n\n**ANSWER**: Utilize parameterized queries, input validation, ORM tools, and limit database privileges to prevent SQL Injection attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Expert answer: use parameterized queries and prepared statements\nSubmission:\n- Mentions understanding SQL Injection\n- Mentions using parameterized queries \n- Mentions input validation and sanitization\n- Mentions utilizing ORM tools\n- Mentions limiting database user privileges\n\n2. The submission covers all the points mentioned in the expert answer (use parameterized queries) and expands on them with additional measures such as input validation, ORM tools, and limiting database user privileges.\n\n3. The submission provides a comprehensive approach to preventing SQL Injection attacks, going beyond just using parameterized queries and prepared statements.\n\nBased on the above analysis, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1717806953556.2407 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1717806955026.725 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806955135.785 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806955139.398 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806957469.2449 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806957474.95 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806958659.939 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806958663.363 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806961036.875 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1717806961043.222 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-10T17-47-01-07-00_security-guide_fV8bFBJrgZo8hLZ8VMizpn.json b/logs/2024-06-10T17-47-01-07-00_security-guide_fV8bFBJrgZo8hLZ8VMizpn.json deleted file mode 100644 index c6f744b3..00000000 --- a/logs/2024-06-10T17-47-01-07-00_security-guide_fV8bFBJrgZo8hLZ8VMizpn.json +++ /dev/null @@ -1,202 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "fV8bFBJrgZo8hLZ8VMizpn", - "run_id": "XdxpHPRJDf77tFQnCbhkjS", - "created": "2024-06-10T17:47:01-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "58cf293" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 1.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-10T17:47:01-07:00", - "completed_at": "2024-06-10T17:47:14-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1623, - "output_tokens": 718, - "total_tokens": 2341 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what SQL Injection is: SQL Injection is a type of cyber attack that allows attackers to inject malicious SQL code into input fields in order to gain access to a database and potentially steal sensitive information.\n\n2. Use Parameterized Queries: Parameterized queries separate SQL code from user input, preventing attackers from inserting malicious code into input fields. This is the most effective way to prevent SQL Injection attacks.\n\n3. Use Stored Procedures: Stored procedures can also help prevent SQL Injection attacks by predefining SQL queries within the database. This restricts the ability of an attacker to execute arbitrary SQL commands.\n\n4. Sanitize Input: Validate and sanitize all user input to ensure that any malicious code is removed before interacting with the database.\n\n5. Limit Database Permissions: Restrict the privileges of the database user to only necessary actions to prevent attackers from gaining access to sensitive information.\n\n6. Use Web Application Firewalls: Implementing a web application firewall can help detect and prevent SQL Injection attacks by filtering and monitoring incoming traffic.\n\n7. Regularly Update Software: Keep database software and frameworks up to date to ensure that any known vulnerabilities are patched.\n\nANSWER: The best way to prevent SQL Injection attacks is by using Parameterized Queries.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: 1. Understand what SQL Injection is: SQL Injection is a type of cyber attack that allows attackers to inject malicious SQL code into input fields in order to gain access to a database and potentially steal sensitive information.\n\n2. Use Parameterized Queries: Parameterized queries separate SQL code from user input, preventing attackers from inserting malicious code into input fields. This is the most effective way to prevent SQL Injection attacks.\n\n3. Use Stored Procedures: Stored procedures can also help prevent SQL Injection attacks by predefining SQL queries within the database. This restricts the ability of an attacker to execute arbitrary SQL commands.\n\n4. Sanitize Input: Validate and sanitize all user input to ensure that any malicious code is removed before interacting with the database.\n\n5. Limit Database Permissions: Restrict the privileges of the database user to only necessary actions to prevent attackers from gaining access to sensitive information.\n\n6. Use Web Application Firewalls: Implementing a web application firewall can help detect and prevent SQL Injection attacks by filtering and monitoring incoming traffic.\n\n7. Regularly Update Software: Keep database software and frameworks up to date to ensure that any known vulnerabilities are patched.\n\nANSWER: The best way to prevent SQL Injection attacks is by using Parameterized Queries.\n***\n[Critique]: The answer provided is well-detailed and covers multiple ways to prevent SQL Injection attacks. However, it could be improved by addressing all the points mentioned in the answer, not just focusing on one specific method (Parameterized Queries). Additionally, it would be beneficial to provide examples or further explanation to better illustrate each point. Furthermore, it would be helpful to emphasize the importance of not relying solely on one method but rather implementing a combination of strategies to enhance security.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the original answer based on the critique:\n\n1. **Understand SQL Injection**: Grasp the concept of SQL Injection to recognize how attackers can exploit vulnerabilities.\n2. **Use Parameterized Queries**: Separate SQL statements from user input to prevent injected malicious code.\n3. **Implement Stored Procedures**: Define pre-written SQL queries within the database to limit attackers' ability to execute unauthorized commands.\n4. **Sanitize User Input**: Validate and clean all input data to remove potentially harmful code before interacting with the database.\n5. **Restrict Database Permissions**: Only grant necessary privileges to database users to minimize the risk of attackers accessing sensitive information.\n6. **Deploy Web Application Firewalls**: Utilize firewalls to monitor and filter incoming traffic, helping to detect and mitigate SQL Injection attempts.\n7. **Regularly Update Software**: Keep all software components, including databases and frameworks, up to date to patch any known vulnerabilities.\n8. **Educate Users**: Provide training to users and developers on recognizing and preventing SQL Injection attacks.\n\nANSWER: The best way to prevent SQL Injection attacks is by using Parameterized Queries.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the original answer based on the critique:\n\n1. **Understand SQL Injection**: Grasp the concept of SQL Injection to recognize how attackers can exploit vulnerabilities.\n2. **Use Parameterized Queries**: Separate SQL statements from user input to prevent injected malicious code.\n3. **Implement Stored Procedures**: Define pre-written SQL queries within the database to limit attackers' ability to execute unauthorized commands.\n4. **Sanitize User Input**: Validate and clean all input data to remove potentially harmful code before interacting with the database.\n5. **Restrict Database Permissions**: Only grant necessary privileges to database users to minimize the risk of attackers accessing sensitive information.\n6. **Deploy Web Application Firewalls**: Utilize firewalls to monitor and filter incoming traffic, helping to detect and mitigate SQL Injection attempts.\n7. **Regularly Update Software**: Keep all software components, including databases and frameworks, up to date to patch any known vulnerabilities.\n8. **Educate Users**: Provide training to users and developers on recognizing and preventing SQL Injection attacks.\n\nANSWER: The best way to prevent SQL Injection attacks is by using Parameterized Queries.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 757, - "output_tokens": 223, - "total_tokens": 980 - } - }, - "score": { - "value": "C", - "answer": "Improving the original answer based on the critique:\n\n1. **Understand SQL Injection**: Grasp the concept of SQL Injection to recognize how attackers can exploit vulnerabilities.\n2. **Use Parameterized Queries**: Separate SQL statements from user input to prevent injected malicious code.\n3. **Implement Stored Procedures**: Define pre-written SQL queries within the database to limit attackers' ability to execute unauthorized commands.\n4. **Sanitize User Input**: Validate and clean all input data to remove potentially harmful code before interacting with the database.\n5. **Restrict Database Permissions**: Only grant necessary privileges to database users to minimize the risk of attackers accessing sensitive information.\n6. **Deploy Web Application Firewalls**: Utilize firewalls to monitor and filter incoming traffic, helping to detect and mitigate SQL Injection attempts.\n7. **Regularly Update Software**: Keep all software components, including databases and frameworks, up to date to patch any known vulnerabilities.\n8. **Educate Users**: Provide training to users and developers on recognizing and preventing SQL Injection attacks.\n\nANSWER: The best way to prevent SQL Injection attacks is by using Parameterized Queries.", - "explanation": "1. The expert answer states that the best way to prevent SQL Injection attacks is by using Parameterized Queries.\n2. The submission also includes the use of Parameterized Queries as one of the ways to prevent SQL Injection attacks.\n3. However, the submission expands on this by including other methods such as understanding SQL Injection, implementing stored procedures, sanitizing user input, restricting database permissions, deploying web application firewalls, regularly updating software, and educating users.\n4. Even though the submission includes additional methods, it still mentions the expert answer's point about using Parameterized Queries as an effective way to prevent SQL Injection attacks.\n5. Therefore, the submission does contain the content in the expert answer.\n6. Based on the above assessment, the submission aligns with the expert answer.\n \nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improving the original answer based on the critique:\n\n1. **Understand SQL Injection**: Grasp the concept of SQL Injection to recognize how attackers can exploit vulnerabilities.\n2. **Use Parameterized Queries**: Separate SQL statements from user input to prevent injected malicious code.\n3. **Implement Stored Procedures**: Define pre-written SQL queries within the database to limit attackers' ability to execute unauthorized commands.\n4. **Sanitize User Input**: Validate and clean all input data to remove potentially harmful code before interacting with the database.\n5. **Restrict Database Permissions**: Only grant necessary privileges to database users to minimize the risk of attackers accessing sensitive information.\n6. **Deploy Web Application Firewalls**: Utilize firewalls to monitor and filter incoming traffic, helping to detect and mitigate SQL Injection attempts.\n7. **Regularly Update Software**: Keep all software components, including databases and frameworks, up to date to patch any known vulnerabilities.\n8. **Educate Users**: Provide training to users and developers on recognizing and preventing SQL Injection attacks.\n\nANSWER: The best way to prevent SQL Injection attacks is by using Parameterized Queries.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer states that the best way to prevent SQL Injection attacks is by using Parameterized Queries.\n2. The submission also includes the use of Parameterized Queries as one of the ways to prevent SQL Injection attacks.\n3. However, the submission expands on this by including other methods such as understanding SQL Injection, implementing stored procedures, sanitizing user input, restricting database permissions, deploying web application firewalls, regularly updating software, and educating users.\n4. Even though the submission includes additional methods, it still mentions the expert answer's point about using Parameterized Queries as an effective way to prevent SQL Injection attacks.\n5. Therefore, the submission does contain the content in the expert answer.\n6. Based on the above assessment, the submission aligns with the expert answer.\n \nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1718066820222.6208 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1718066821725.292 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066821836.865 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066821840.1743 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066826480.833 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066826485.0007 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066828167.4858 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066828172.8267 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066831722.7021 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718066831727.389 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-10T17-52-51-07-00_security-guide_hhEbZj5tKCbkeZXZThqxDN.json b/logs/2024-06-10T17-52-51-07-00_security-guide_hhEbZj5tKCbkeZXZThqxDN.json deleted file mode 100644 index 50ff758f..00000000 --- a/logs/2024-06-10T17-52-51-07-00_security-guide_hhEbZj5tKCbkeZXZThqxDN.json +++ /dev/null @@ -1,202 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "hhEbZj5tKCbkeZXZThqxDN", - "run_id": "VKF6xMEnvm6DQ9484Sdhbf", - "created": "2024-06-10T17:52:51-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "58cf293" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 1.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-10T17:52:51-07:00", - "completed_at": "2024-06-10T17:53:01-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1379, - "output_tokens": 582, - "total_tokens": 1961 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "Step 1: Use parameterized queries - Instead of embedding user input directly into SQL statements, use parameterized queries to sanitize input and prevent attackers from inserting malicious code.\nStep 2: Input validation - Validate all user input to ensure it matches the expected format and type. Reject any input that does not meet these requirements.\nStep 3: Limit privileges - Make sure your database user only has the necessary permissions to perform its intended actions in order to limit the potential damage of an SQL injection attack.\nStep 4: Use stored procedures - Utilize stored procedures to encapsulate SQL logic and prevent direct manipulation of database objects.\nStep 5: Escaping user input - If you must include user input within SQL statements, make sure to escape special characters to prevent SQL injection attacks.\n\nANSWER: Utilize parameterized queries, input validation, limiting privileges, stored procedures, and escape user input to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: Step 1: Use parameterized queries - Instead of embedding user input directly into SQL statements, use parameterized queries to sanitize input and prevent attackers from inserting malicious code.\nStep 2: Input validation - Validate all user input to ensure it matches the expected format and type. Reject any input that does not meet these requirements.\nStep 3: Limit privileges - Make sure your database user only has the necessary permissions to perform its intended actions in order to limit the potential damage of an SQL injection attack.\nStep 4: Use stored procedures - Utilize stored procedures to encapsulate SQL logic and prevent direct manipulation of database objects.\nStep 5: Escaping user input - If you must include user input within SQL statements, make sure to escape special characters to prevent SQL injection attacks.\n\nANSWER: Utilize parameterized queries, input validation, limiting privileges, stored procedures, and escape user input to prevent SQL Injection attacks.\n***\n[Critique]: The answer provided is thorough and well-organized, addressing different aspects of preventing SQL Injection attacks. However, it could benefit from further explanation or examples for each step to enhance clarity and understanding for readers who may not be familiar with these concepts. Additionally, it would be helpful to include information on the importance of regularly updating and patching software to protect against known vulnerabilities that could be exploited by attackers.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer: \nTo prevent SQL Injection attacks, it is crucial to follow these steps:\n1. Utilize parameterized queries to sanitize input and avoid embedding user input directly into SQL statements.\n2. Perform input validation to ensure user input matches the expected format and type, rejecting any input that does not meet these requirements.\n3. Limit privileges for database users to only essential permissions to minimize the potential impact of an SQL injection attack.\n4. Employ stored procedures to encapsulate SQL logic and prevent direct manipulation of database objects.\n5. Escape user input by properly handling special characters when including user input within SQL statements. In addition to these measures, regularly updating and patching software is essential to protect against known vulnerabilities exploited by attackers.\n\nANSWER: Utilize parameterized queries, input validation, limiting privileges, stored procedures, and escape user input to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer: \nTo prevent SQL Injection attacks, it is crucial to follow these steps:\n1. Utilize parameterized queries to sanitize input and avoid embedding user input directly into SQL statements.\n2. Perform input validation to ensure user input matches the expected format and type, rejecting any input that does not meet these requirements.\n3. Limit privileges for database users to only essential permissions to minimize the potential impact of an SQL injection attack.\n4. Employ stored procedures to encapsulate SQL logic and prevent direct manipulation of database objects.\n5. Escape user input by properly handling special characters when including user input within SQL statements. In addition to these measures, regularly updating and patching software is essential to protect against known vulnerabilities exploited by attackers.\n\nANSWER: Utilize parameterized queries, input validation, limiting privileges, stored procedures, and escape user input to prevent SQL Injection attacks.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 624, - "output_tokens": 173, - "total_tokens": 797 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer: \nTo prevent SQL Injection attacks, it is crucial to follow these steps:\n1. Utilize parameterized queries to sanitize input and avoid embedding user input directly into SQL statements.\n2. Perform input validation to ensure user input matches the expected format and type, rejecting any input that does not meet these requirements.\n3. Limit privileges for database users to only essential permissions to minimize the potential impact of an SQL injection attack.\n4. Employ stored procedures to encapsulate SQL logic and prevent direct manipulation of database objects.\n5. Escape user input by properly handling special characters when including user input within SQL statements. In addition to these measures, regularly updating and patching software is essential to protect against known vulnerabilities exploited by attackers.\n\nANSWER: Utilize parameterized queries, input validation, limiting privileges, stored procedures, and escape user input to prevent SQL Injection attacks.", - "explanation": "1. Both the expert and the submission mention utilizing parameterized queries to prevent SQL Injection attacks.\n2. Both the expert and the submission talk about input validation as a measure to prevent SQL Injection attacks.\n3. Both the expert and the submission mention limiting privileges for database users as a way to minimize the impact of an SQL injection attack.\n4. Both the expert and the submission suggest using stored procedures to prevent direct manipulation of database objects.\n5. Both the expert and the submission mention escaping user input as a way to prevent SQL Injection attacks.\n\nBased on the above assessment, all the key measures mentioned in the expert answer are also included in the submitted answer. Therefore, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improved Answer: \nTo prevent SQL Injection attacks, it is crucial to follow these steps:\n1. Utilize parameterized queries to sanitize input and avoid embedding user input directly into SQL statements.\n2. Perform input validation to ensure user input matches the expected format and type, rejecting any input that does not meet these requirements.\n3. Limit privileges for database users to only essential permissions to minimize the potential impact of an SQL injection attack.\n4. Employ stored procedures to encapsulate SQL logic and prevent direct manipulation of database objects.\n5. Escape user input by properly handling special characters when including user input within SQL statements. In addition to these measures, regularly updating and patching software is essential to protect against known vulnerabilities exploited by attackers.\n\nANSWER: Utilize parameterized queries, input validation, limiting privileges, stored procedures, and escape user input to prevent SQL Injection attacks.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. Both the expert and the submission mention utilizing parameterized queries to prevent SQL Injection attacks.\n2. Both the expert and the submission talk about input validation as a measure to prevent SQL Injection attacks.\n3. Both the expert and the submission mention limiting privileges for database users as a way to minimize the impact of an SQL injection attack.\n4. Both the expert and the submission suggest using stored procedures to prevent direct manipulation of database objects.\n5. Both the expert and the submission mention escaping user input as a way to prevent SQL Injection attacks.\n\nBased on the above assessment, all the key measures mentioned in the expert answer are also included in the submitted answer. Therefore, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [ - { - "level": "error", - "message": "DependencyConflict: requested: \"chromadb >= 0.4.23\" but found: \"None\"", - "created": 1718067170017.489 - }, - { - "level": "error", - "message": "DependencyConflict: requested: \"weaviate-client >= 4.6.1\" but found: \"None\"", - "created": 1718067171506.185 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067171605.602 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067171610.352 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067174924.643 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067174928.775 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067176233.4668 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067176240.905 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.temperature' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067179659.663 - }, - { - "level": "warning", - "message": "Invalid type NotGiven for attribute 'llm.top_p' value. Expected one of ['bool', 'str', 'bytes', 'int', 'float'] or a sequence of those types", - "created": 1718067179664.969 - } - ] -} \ No newline at end of file diff --git a/logs/2024-06-11T17-29-43-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json b/logs/2024-06-11T17-29-43-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json deleted file mode 100644 index 68d60103..00000000 --- a/logs/2024-06-11T17-29-43-07-00_security-guide_hECF7Z795AWH3W8s7CaJHT.json +++ /dev/null @@ -1,151 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "hECF7Z795AWH3W8s7CaJHT", - "run_id": "PXdXegwfGL8gDm9PEgiYKx", - "created": "2024-06-11T17:29:43-07:00", - "dataset": { - "name": "security_guide", - "location": "example://security_guide", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "58cf293" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 1.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-11T17:29:43-07:00", - "completed_at": "2024-06-11T17:29:55-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1603, - "output_tokens": 768, - "total_tokens": 2371 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": [ - { - "content": "How do I prevent SQL Injection attacks?", - "source": "input", - "role": "user" - } - ], - "target": "use parameterized queries and prepared statements", - "messages": [ - { - "content": "\nHow do I prevent SQL Injection attacks?\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Understand what SQL Injection attacks are: SQL Injection is a type of attack where an attacker maliciously injects SQL query code into input fields on a website in order to gain unauthorized access to the database.\n\n2. Use parameterized queries: Parameterized queries can help prevent SQL Injection attacks by separating SQL code from user input. This means that user input is treated as data and not executable code, reducing the risk of injection attacks.\n\n3. Sanitize user input: The application should validate and sanitize user input to ensure that it does not contain any malicious SQL code. This can include input validation, escaping special characters, and using whitelists to only allow certain types of input.\n\n4. Use stored procedures: Stored procedures can help prevent SQL Injection attacks by pre-defining the SQL code that can be executed, reducing the risk of injection attacks.\n\n5. Limit database permissions: Ensure that the database user account used by the application has the minimum necessary permissions to prevent an attacker from executing harmful SQL queries even if an injection occurs.\n\nANSWER: Use parameterized queries, sanitize user input, use stored procedures, and limit database permissions.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: How do I prevent SQL Injection attacks?\n***\n[Answer]: 1. Understand what SQL Injection attacks are: SQL Injection is a type of attack where an attacker maliciously injects SQL query code into input fields on a website in order to gain unauthorized access to the database.\n\n2. Use parameterized queries: Parameterized queries can help prevent SQL Injection attacks by separating SQL code from user input. This means that user input is treated as data and not executable code, reducing the risk of injection attacks.\n\n3. Sanitize user input: The application should validate and sanitize user input to ensure that it does not contain any malicious SQL code. This can include input validation, escaping special characters, and using whitelists to only allow certain types of input.\n\n4. Use stored procedures: Stored procedures can help prevent SQL Injection attacks by pre-defining the SQL code that can be executed, reducing the risk of injection attacks.\n\n5. Limit database permissions: Ensure that the database user account used by the application has the minimum necessary permissions to prevent an attacker from executing harmful SQL queries even if an injection occurs.\n\nANSWER: Use parameterized queries, sanitize user input, use stored procedures, and limit database permissions.\n***\n[Critique]: The answer provided is concise and includes key points in preventing SQL Injection attacks. However, it lacks in-depth explanation and examples for each point. Providing specific examples of how to implement parameterized queries, sanitize user input, use stored procedures, and limit database permissions would make the answer more informative and helpful. Additionally, it would be beneficial to explain why these measures are effective in preventing SQL Injection attacks. Improving the answer with more detailed information would provide a clearer understanding for the reader.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improved Answer:\n1. Understand what SQL Injection attacks are: SQL Injection is a type of attack where an attacker injects malicious SQL code into input fields to gain unauthorized access to the database. This can lead to data breaches and unauthorized operations.\n\n2. Use parameterized queries: Implementing parameterized queries helps prevent SQL Injection by separating SQL code from user input. By using placeholders for parameters, the database engine can distinguish between code and data, reducing the risk of injection attacks.\n\n3. Sanitize user input: Validating and sanitizing user input is crucial to prevent SQL Injection. This involves removing or escaping special characters and ensuring that only expected input formats are accepted. This protects against malicious code being executed in SQL queries.\n\n4. Use stored procedures: Utilizing stored procedures can mitigate SQL Injection risks by defining specific procedures for database operations. This restricts the execution of arbitrary SQL code and limits the potential attack surface.\n\n5. Limit database permissions: Restricting database user permissions to the minimum required level helps prevent unauthorized access and manipulation of sensitive data. By granting only necessary privileges, the impact of a successful SQL Injection attack can be minimized.\n\nANSWER: Use parameterized queries, sanitize user input, use stored procedures, and limit database permissions.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improved Answer:\n1. Understand what SQL Injection attacks are: SQL Injection is a type of attack where an attacker injects malicious SQL code into input fields to gain unauthorized access to the database. This can lead to data breaches and unauthorized operations.\n\n2. Use parameterized queries: Implementing parameterized queries helps prevent SQL Injection by separating SQL code from user input. By using placeholders for parameters, the database engine can distinguish between code and data, reducing the risk of injection attacks.\n\n3. Sanitize user input: Validating and sanitizing user input is crucial to prevent SQL Injection. This involves removing or escaping special characters and ensuring that only expected input formats are accepted. This protects against malicious code being executed in SQL queries.\n\n4. Use stored procedures: Utilizing stored procedures can mitigate SQL Injection risks by defining specific procedures for database operations. This restricts the execution of arbitrary SQL code and limits the potential attack surface.\n\n5. Limit database permissions: Restricting database user permissions to the minimum required level helps prevent unauthorized access and manipulation of sensitive data. By granting only necessary privileges, the impact of a successful SQL Injection attack can be minimized.\n\nANSWER: Use parameterized queries, sanitize user input, use stored procedures, and limit database permissions.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 728, - "output_tokens": 249, - "total_tokens": 977 - } - }, - "score": { - "value": "C", - "answer": "Improved Answer:\n1. Understand what SQL Injection attacks are: SQL Injection is a type of attack where an attacker injects malicious SQL code into input fields to gain unauthorized access to the database. This can lead to data breaches and unauthorized operations.\n\n2. Use parameterized queries: Implementing parameterized queries helps prevent SQL Injection by separating SQL code from user input. By using placeholders for parameters, the database engine can distinguish between code and data, reducing the risk of injection attacks.\n\n3. Sanitize user input: Validating and sanitizing user input is crucial to prevent SQL Injection. This involves removing or escaping special characters and ensuring that only expected input formats are accepted. This protects against malicious code being executed in SQL queries.\n\n4. Use stored procedures: Utilizing stored procedures can mitigate SQL Injection risks by defining specific procedures for database operations. This restricts the execution of arbitrary SQL code and limits the potential attack surface.\n\n5. Limit database permissions: Restricting database user permissions to the minimum required level helps prevent unauthorized access and manipulation of sensitive data. By granting only necessary privileges, the impact of a successful SQL Injection attack can be minimized.\n\nANSWER: Use parameterized queries, sanitize user input, use stored procedures, and limit database permissions.", - "explanation": "1. The expert answer includes the utilization of parameterized queries and prepared statements as a strategy to prevent SQL Injection attacks.\n2. The submission also mentions the use of parameterized queries, stating that it helps prevent SQL Injection by separating SQL code from user input.\n3. The expert answer does not mention anything about understanding what SQL Injection attacks are, but the submission explains this concept.\n4. The expert answer does not explicitly mention sanitizing user input as a preventive measure, but the submission includes this strategy.\n5. The expert answer does not mention the use of stored procedures as a preventive measure, but the submission introduces this approach.\n6. The expert answer does not mention limiting database permissions as a preventive measure, while the submission includes this strategy.\n\nBased on the above points, it can be observed that the submission contains additional preventive measures beyond just parameterized queries, aligning with the expert answer's suggestion. Therefore, the submission contains the content in the expert answer.\n\nGRADE: C", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: How do I prevent SQL Injection attacks?\n************\n[Expert]: use parameterized queries and prepared statements\n************\n[Submission]: Improved Answer:\n1. Understand what SQL Injection attacks are: SQL Injection is a type of attack where an attacker injects malicious SQL code into input fields to gain unauthorized access to the database. This can lead to data breaches and unauthorized operations.\n\n2. Use parameterized queries: Implementing parameterized queries helps prevent SQL Injection by separating SQL code from user input. By using placeholders for parameters, the database engine can distinguish between code and data, reducing the risk of injection attacks.\n\n3. Sanitize user input: Validating and sanitizing user input is crucial to prevent SQL Injection. This involves removing or escaping special characters and ensuring that only expected input formats are accepted. This protects against malicious code being executed in SQL queries.\n\n4. Use stored procedures: Utilizing stored procedures can mitigate SQL Injection risks by defining specific procedures for database operations. This restricts the execution of arbitrary SQL code and limits the potential attack surface.\n\n5. Limit database permissions: Restricting database user permissions to the minimum required level helps prevent unauthorized access and manipulation of sensitive data. By granting only necessary privileges, the impact of a successful SQL Injection attack can be minimized.\n\nANSWER: Use parameterized queries, sanitize user input, use stored procedures, and limit database permissions.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer includes the utilization of parameterized queries and prepared statements as a strategy to prevent SQL Injection attacks.\n2. The submission also mentions the use of parameterized queries, stating that it helps prevent SQL Injection by separating SQL code from user input.\n3. The expert answer does not mention anything about understanding what SQL Injection attacks are, but the submission explains this concept.\n4. The expert answer does not explicitly mention sanitizing user input as a preventive measure, but the submission includes this strategy.\n5. The expert answer does not mention the use of stored procedures as a preventive measure, but the submission introduces this approach.\n6. The expert answer does not mention limiting database permissions as a preventive measure, while the submission includes this strategy.\n\nBased on the above points, it can be observed that the submission contains additional preventive measures beyond just parameterized queries, aligning with the expert answer's suggestion. Therefore, the submission contains the content in the expert answer.\n\nGRADE: C", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T10-01-42-07-00_security-guide_JK4cmm7UAxZNPdq3hGrrxo.json b/logs/2024-06-12T10-01-42-07-00_security-guide_JK4cmm7UAxZNPdq3hGrrxo.json deleted file mode 100644 index 20661701..00000000 --- a/logs/2024-06-12T10-01-42-07-00_security-guide_JK4cmm7UAxZNPdq3hGrrxo.json +++ /dev/null @@ -1,145 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "JK4cmm7UAxZNPdq3hGrrxo", - "run_id": "dEg9DJopphBGAN7BieQmrw", - "created": "2024-06-12T10:01:42-07:00", - "dataset": { - "name": "golden_20240612T165506", - "location": "./golden_20240612T165506.csv", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_fact", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-12T10:01:42-07:00", - "completed_at": "2024-06-12T10:01:52-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1148, - "output_tokens": 405, - "total_tokens": 1553 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": "Tell me a story in 3 sentences or less.", - "target": "Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"", - "messages": [ - { - "content": "\nTell me a story in 3 sentences or less.\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Determine the setting, characters, conflict, and resolution of the story you want to tell. \n2. Condense the story into three key sentences that capture the essence of the plot.\n3. Ensure that the sentences provide a clear beginning, middle, and end to the story.\n\nANSWER: Once upon a time, a young princess went on a quest to save her kingdom from a powerful dragon. Along the way, she met a brave knight who joined her in the fight. Together, they defeated the dragon and brought peace back to the land.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: Tell me a story in 3 sentences or less.\n***\n[Answer]: 1. Determine the setting, characters, conflict, and resolution of the story you want to tell. \n2. Condense the story into three key sentences that capture the essence of the plot.\n3. Ensure that the sentences provide a clear beginning, middle, and end to the story.\n\nANSWER: Once upon a time, a young princess went on a quest to save her kingdom from a powerful dragon. Along the way, she met a brave knight who joined her in the fight. Together, they defeated the dragon and brought peace back to the land.\n***\n[Critique]: The answer provided does not actually tell a story in three sentences as requested by the question. Instead, it gives guidelines on how to craft a story in three sentences. Additionally, the provided story example is unrelated to the guidelines given, making the response incomplete. It would have been better if the answer had actually followed the format requested and provided a concise story example.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "Improving the answer:\n\nANSWER: Once upon a time, a young prince set out to find the mystical golden apple, facing trials and making sacrifices along the way. After overcoming obstacles and betrayals, he retrieved the apple and saved his kingdom from a curse, proving his worth as a true hero.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "Improving the answer:\n\nANSWER: Once upon a time, a young prince set out to find the mystical golden apple, facing trials and making sacrifices along the way. After overcoming obstacles and betrayals, he retrieved the apple and saved his kingdom from a curse, proving his worth as a true hero.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 480, - "output_tokens": 61, - "total_tokens": 541 - } - }, - "score": { - "value": "I", - "answer": "Improving the answer:\n\nANSWER: Once upon a time, a young prince set out to find the mystical golden apple, facing trials and making sacrifices along the way. After overcoming obstacles and betrayals, he retrieved the apple and saved his kingdom from a curse, proving his worth as a true hero.", - "explanation": "1. The expert answer talks about a group of pirates seeking cursed treasure and successfully retrieving it, becoming the richest pirates beyond the horizon.\n2. The submission answer involves a young prince on a quest for a mystical golden apple, facing trials and eventually saving his kingdom from a curse.\n\nUpon comparing the factual content of the two answers:\n- Both answers involve a protagonist embarking on a quest to find a valuable item (treasure/apple).\n- Both answers mention overcoming obstacles and challenges during the quest.\n- The expert answer focuses on pirates and cursed treasure, while the submission answer focuses on a prince and a golden apple.\n\nGiven that the factual content of the two answers differs significantly in terms of characters, setting, and plot details, the submission does not contain the content in the expert answer.\n\nGRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are comparing a submitted answer to an expert answer on a given question. Here is the data:\n\n[BEGIN DATA]\n************\n[Question]: Tell me a story in 3 sentences or less.\n************\n[Expert]: Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"\n************\n[Submission]: Improving the answer:\n\nANSWER: Once upon a time, a young prince set out to find the mystical golden apple, facing trials and making sacrifices along the way. After overcoming obstacles and betrayals, he retrieved the apple and saved his kingdom from a curse, proving his worth as a true hero.\n************\n[END DATA]\n\nCompare the factual content of the submitted answer with the expert answer. Ignore any differences in style, grammar, or punctuation.\n\nDoes the submission contain the content in the expert answer?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The expert answer talks about a group of pirates seeking cursed treasure and successfully retrieving it, becoming the richest pirates beyond the horizon.\n2. The submission answer involves a young prince on a quest for a mystical golden apple, facing trials and eventually saving his kingdom from a curse.\n\nUpon comparing the factual content of the two answers:\n- Both answers involve a protagonist embarking on a quest to find a valuable item (treasure/apple).\n- Both answers mention overcoming obstacles and challenges during the quest.\n- The expert answer focuses on pirates and cursed treasure, while the submission answer focuses on a prince and a golden apple.\n\nGiven that the factual content of the two answers differs significantly in terms of characters, setting, and plot details, the submission does not contain the content in the expert answer.\n\nGRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T10-03-15-07-00_security-guide_QCtsMMNEnWS7xbFZwbpFbb.json b/logs/2024-06-12T10-03-15-07-00_security-guide_QCtsMMNEnWS7xbFZwbpFbb.json deleted file mode 100644 index 196c2810..00000000 --- a/logs/2024-06-12T10-03-15-07-00_security-guide_QCtsMMNEnWS7xbFZwbpFbb.json +++ /dev/null @@ -1,145 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "QCtsMMNEnWS7xbFZwbpFbb", - "run_id": "dejk8GqvoCjvMWbeKfceTz", - "created": "2024-06-12T10:03:15-07:00", - "dataset": { - "name": "golden_20240612T165506", - "location": "./golden_20240612T165506.csv", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "generate", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_qa", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-12T10:03:15-07:00", - "completed_at": "2024-06-12T10:03:24-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 1145, - "output_tokens": 375, - "total_tokens": 1520 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": "Tell me a story in 3 sentences or less.", - "target": "Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"", - "messages": [ - { - "content": "\nTell me a story in 3 sentences or less.\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "1. Think of a scenario that can be easily summarized in just a few sentences. \n2. Write a concise beginning, middle, and end for the story. \n3. Keep each sentence short and to the point. \n\nANSWER: The fox and the crow sat in the tree, the crow holding a piece of cheese. The fox flattered the crow, who opened her beak to caw and dropped the cheese. The fox snatched it up and ran off, leaving the crow feeling foolish.", - "source": "generate", - "role": "assistant" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: Tell me a story in 3 sentences or less.\n***\n[Answer]: 1. Think of a scenario that can be easily summarized in just a few sentences. \n2. Write a concise beginning, middle, and end for the story. \n3. Keep each sentence short and to the point. \n\nANSWER: The fox and the crow sat in the tree, the crow holding a piece of cheese. The fox flattered the crow, who opened her beak to caw and dropped the cheese. The fox snatched it up and ran off, leaving the crow feeling foolish.\n***\n[Critique]: The answer provided is not a story in itself, but rather instructions on how to write a story in 3 sentences or less. It does not follow the prompt of telling a story and instead gives tips on how to create a story. Additionally, it lacks creativity and originality in its response.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "To improve the answer we need to provide an actual short story instead of instructions.\n\n**Improved Answer**:\n\nThree unlikely friends, a cat, a dog, and a mouse, decided to go on an adventure together. They faced many challenges but worked together to overcome them. In the end, their friendship and teamwork led them to a treasure hidden deep in the forest.\n\nANSWER: The fox and the crow sat in the tree, the crow holding a piece of cheese. The fox flattered the crow, who opened her beak to caw and dropped the cheese. The fox snatched it up and ran off, leaving the crow feeling foolish.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "To improve the answer we need to provide an actual short story instead of instructions.\n\n**Improved Answer**:\n\nThree unlikely friends, a cat, a dog, and a mouse, decided to go on an adventure together. They faced many challenges but worked together to overcome them. In the end, their friendship and teamwork led them to a treasure hidden deep in the forest.\n\nANSWER: The fox and the crow sat in the tree, the crow holding a piece of cheese. The fox flattered the crow, who opened her beak to caw and dropped the cheese. The fox snatched it up and ran off, leaving the crow feeling foolish.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 449, - "output_tokens": 130, - "total_tokens": 579 - } - }, - "score": { - "value": "I", - "answer": "To improve the answer we need to provide an actual short story instead of instructions.\n\n**Improved Answer**:\n\nThree unlikely friends, a cat, a dog, and a mouse, decided to go on an adventure together. They faced many challenges but worked together to overcome them. In the end, their friendship and teamwork led them to a treasure hidden deep in the forest.\n\nANSWER: The fox and the crow sat in the tree, the crow holding a piece of cheese. The fox flattered the crow, who opened her beak to caw and dropped the cheese. The fox snatched it up and ran off, leaving the crow feeling foolish.", - "explanation": "1. The criterion requires the submission to follow a specific story theme related to sailing for cursed treasure and being the richest pirates.\n2. The submitted answer does not meet the criterion as it tells a story about three unlikely friends going on an adventure and finding hidden treasure in the forest.\n3. Since the submission does not align with the required story theme, it does not meet the criterion.\n4. GRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are assessing a submitted answer on a given task based on a criterion. Here is the data:\n\n[BEGIN DATA]\n***\n[Task]: Tell me a story in 3 sentences or less.\n***\n[Submission]: To improve the answer we need to provide an actual short story instead of instructions.\n\n**Improved Answer**:\n\nThree unlikely friends, a cat, a dog, and a mouse, decided to go on an adventure together. They faced many challenges but worked together to overcome them. In the end, their friendship and teamwork led them to a treasure hidden deep in the forest.\n\nANSWER: The fox and the crow sat in the tree, the crow holding a piece of cheese. The fox flattered the crow, who opened her beak to caw and dropped the cheese. The fox snatched it up and ran off, leaving the crow feeling foolish.\n***\n[Criterion]: Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"\n***\n[END DATA]\n\nDoes the submission meet the criterion?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The criterion requires the submission to follow a specific story theme related to sailing for cursed treasure and being the richest pirates.\n2. The submitted answer does not meet the criterion as it tells a story about three unlikely friends going on an adventure and finding hidden treasure in the forest.\n3. Since the submission does not align with the required story theme, it does not meet the criterion.\n4. GRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T10-03-40-07-00_security-guide_E56YvLVCpqFT6jCNVBWXqh.json b/logs/2024-06-12T10-03-40-07-00_security-guide_E56YvLVCpqFT6jCNVBWXqh.json deleted file mode 100644 index 14e36b1d..00000000 --- a/logs/2024-06-12T10-03-40-07-00_security-guide_E56YvLVCpqFT6jCNVBWXqh.json +++ /dev/null @@ -1,128 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "E56YvLVCpqFT6jCNVBWXqh", - "run_id": "bSL9ekLHksa5mfniUT76V9", - "created": "2024-06-12T10:03:40-07:00", - "dataset": { - "name": "golden_20240612T165506", - "location": "./golden_20240612T165506.csv", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "generate", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_qa", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-12T10:03:40-07:00", - "completed_at": "2024-06-12T10:03:44-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 375, - "output_tokens": 180, - "total_tokens": 555 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": "Tell me a story in 3 sentences or less.", - "target": "Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"", - "messages": [ - { - "content": "Tell me a story in 3 sentences or less.", - "source": "input", - "role": "user" - }, - { - "content": "She wandered through the forest, enchanted by the whispering trees and dancing sunlight. Suddenly, she stumbled upon a hidden clearing filled with vibrant flowers and a delicate waterfall cascading into a crystal-clear pool. In that moment, she knew she had found her own personal paradise.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "She wandered through the forest, enchanted by the whispering trees and dancing sunlight. Suddenly, she stumbled upon a hidden clearing filled with vibrant flowers and a delicate waterfall cascading into a crystal-clear pool. In that moment, she knew she had found her own personal paradise.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 18, - "output_tokens": 54, - "total_tokens": 72 - } - }, - "score": { - "value": "I", - "answer": "She wandered through the forest, enchanted by the whispering trees and dancing sunlight. Suddenly, she stumbled upon a hidden clearing filled with vibrant flowers and a delicate waterfall cascading into a crystal-clear pool. In that moment, she knew she had found her own personal paradise.", - "explanation": "1. The criterion provided is about a pirate adventure theme where the crew goes on a journey to find cursed treasure, battles ghostly seadogs and sea beasts, finds the treasure, and declares themselves the richest pirates.\n2. The submission tells a story about a person wandering through a forest, finding a hidden paradise, and having a peaceful moment of realization.\n3. The submission does not meet the criterion as it does not match the theme of a pirate adventure with cursed treasure, battles, and declaring oneself the richest pirates.\n4. Therefore, based on the criterion given, the submission does not meet the requirements.\nGRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are assessing a submitted answer on a given task based on a criterion. Here is the data:\n\n[BEGIN DATA]\n***\n[Task]: Tell me a story in 3 sentences or less.\n***\n[Submission]: She wandered through the forest, enchanted by the whispering trees and dancing sunlight. Suddenly, she stumbled upon a hidden clearing filled with vibrant flowers and a delicate waterfall cascading into a crystal-clear pool. In that moment, she knew she had found her own personal paradise.\n***\n[Criterion]: Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"\n***\n[END DATA]\n\nDoes the submission meet the criterion?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The criterion provided is about a pirate adventure theme where the crew goes on a journey to find cursed treasure, battles ghostly seadogs and sea beasts, finds the treasure, and declares themselves the richest pirates.\n2. The submission tells a story about a person wandering through a forest, finding a hidden paradise, and having a peaceful moment of realization.\n3. The submission does not meet the criterion as it does not match the theme of a pirate adventure with cursed treasure, battles, and declaring oneself the richest pirates.\n4. Therefore, based on the criterion given, the submission does not meet the requirements.\nGRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T10-06-37-07-00_security-guide_U5HzKEDA7XefuRsnGcPoEG.json b/logs/2024-06-12T10-06-37-07-00_security-guide_U5HzKEDA7XefuRsnGcPoEG.json deleted file mode 100644 index ffda626f..00000000 --- a/logs/2024-06-12T10-06-37-07-00_security-guide_U5HzKEDA7XefuRsnGcPoEG.json +++ /dev/null @@ -1,136 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "U5HzKEDA7XefuRsnGcPoEG", - "run_id": "d2H4Wnppuy9orSYPVymTMD", - "created": "2024-06-12T10:06:37-07:00", - "dataset": { - "name": "golden_20240612T165506", - "location": "./golden_20240612T165506.csv", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_qa", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-12T10:06:37-07:00", - "completed_at": "2024-06-12T10:06:41-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 636, - "output_tokens": 155, - "total_tokens": 791 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": "Tell me a story in 3 sentences or less.", - "target": "Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"", - "messages": [ - { - "content": "\nTell me a story in 3 sentences or less.\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: Tell me a story in 3 sentences or less.\n***\n[Answer]: \n***\n[Critique]: The original answer is fully correct.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "ANSWER: \nOnce upon a time, in a deep, dark forest, a young girl discovered a secret portal to another world. Through courage and friendship, she saved both realms from impending doom. The grateful creatures bestowed upon her a magical amulet as a token of their eternal gratitude.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "ANSWER: \nOnce upon a time, in a deep, dark forest, a young girl discovered a secret portal to another world. Through courage and friendship, she saved both realms from impending doom. The grateful creatures bestowed upon her a magical amulet as a token of their eternal gratitude.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 187, - "output_tokens": 58, - "total_tokens": 245 - } - }, - "score": { - "value": "I", - "answer": "ANSWER: \nOnce upon a time, in a deep, dark forest, a young girl discovered a secret portal to another world. Through courage and friendship, she saved both realms from impending doom. The grateful creatures bestowed upon her a magical amulet as a token of their eternal gratitude.", - "explanation": "Step 1: The criterion provided is a story about pirates searching for cursed treasure and eventually finding it after facing challenges at sea.\n\nStep 2: The submission does not match the criterion as it is a story about a young girl discovering a secret portal to another world and saving both realms with the help of magical creatures, which does not involve pirates or cursed treasure.\n\nStep 3: Therefore, the submission does not meet the criterion.\n\nGRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are assessing a submitted answer on a given task based on a criterion. Here is the data:\n\n[BEGIN DATA]\n***\n[Task]: Tell me a story in 3 sentences or less.\n***\n[Submission]: ANSWER: \nOnce upon a time, in a deep, dark forest, a young girl discovered a secret portal to another world. Through courage and friendship, she saved both realms from impending doom. The grateful creatures bestowed upon her a magical amulet as a token of their eternal gratitude.\n***\n[Criterion]: Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"\n***\n[END DATA]\n\nDoes the submission meet the criterion?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "Step 1: The criterion provided is a story about pirates searching for cursed treasure and eventually finding it after facing challenges at sea.\n\nStep 2: The submission does not match the criterion as it is a story about a young girl discovering a secret portal to another world and saving both realms with the help of magical creatures, which does not involve pirates or cursed treasure.\n\nStep 3: Therefore, the submission does not meet the criterion.\n\nGRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T18-54-41-07-00_security-guide_SKaR6pSj4DLB88EZgb4XGs.json b/logs/2024-06-12T18-54-41-07-00_security-guide_SKaR6pSj4DLB88EZgb4XGs.json deleted file mode 100644 index 55c0486d..00000000 --- a/logs/2024-06-12T18-54-41-07-00_security-guide_SKaR6pSj4DLB88EZgb4XGs.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "SKaR6pSj4DLB88EZgb4XGs", - "run_id": "ZQ4z87AcAuWXndfQNwz5CK", - "created": "2024-06-12T18:54:41-07:00", - "dataset": { - "name": "langtracefs:", - "location": "langtracefs://", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T18:54:41-07:00", - "completed_at": "2024-06-12T18:54:41-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-03-06-07-00_security-guide_RUaUi4GQaqHfwnsYw5N4b3.json b/logs/2024-06-12T19-03-06-07-00_security-guide_RUaUi4GQaqHfwnsYw5N4b3.json deleted file mode 100644 index 3cc74fb0..00000000 --- a/logs/2024-06-12T19-03-06-07-00_security-guide_RUaUi4GQaqHfwnsYw5N4b3.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "RUaUi4GQaqHfwnsYw5N4b3", - "run_id": "93385ELuKkMQTt5YAp5VMA", - "created": "2024-06-12T19:03:06-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T19:03:06-07:00", - "completed_at": "2024-06-12T19:03:06-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-04-23-07-00_security-guide_gKTYiZEfKpq3CJXiRkboEA.json b/logs/2024-06-12T19-04-23-07-00_security-guide_gKTYiZEfKpq3CJXiRkboEA.json deleted file mode 100644 index 166dc536..00000000 --- a/logs/2024-06-12T19-04-23-07-00_security-guide_gKTYiZEfKpq3CJXiRkboEA.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "gKTYiZEfKpq3CJXiRkboEA", - "run_id": "5QWtw5yeDHiMfVJRbbuYKZ", - "created": "2024-06-12T19:04:23-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T19:04:23-07:00", - "completed_at": "2024-06-12T19:04:23-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-06-49-07-00_security-guide_NnYsHcX5QowFsT4q2P7FTq.json b/logs/2024-06-12T19-06-49-07-00_security-guide_NnYsHcX5QowFsT4q2P7FTq.json deleted file mode 100644 index fb3d8fe3..00000000 --- a/logs/2024-06-12T19-06-49-07-00_security-guide_NnYsHcX5QowFsT4q2P7FTq.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "NnYsHcX5QowFsT4q2P7FTq", - "run_id": "MUZRt8z3xcEKJEV55ZyhgB", - "created": "2024-06-12T19:06:49-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T19:06:49-07:00", - "completed_at": "2024-06-12T19:06:49-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-10-00-07-00_security-guide_YTsBzdCuXsQnD8JXmoRr5e.json b/logs/2024-06-12T19-10-00-07-00_security-guide_YTsBzdCuXsQnD8JXmoRr5e.json deleted file mode 100644 index b41c5b38..00000000 --- a/logs/2024-06-12T19-10-00-07-00_security-guide_YTsBzdCuXsQnD8JXmoRr5e.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "YTsBzdCuXsQnD8JXmoRr5e", - "run_id": "8hkyjBboF7E5LD2UND9Eko", - "created": "2024-06-12T19:10:00-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T19:10:00-07:00", - "completed_at": "2024-06-12T19:10:00-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-10-07-07-00_security-guide_DrGcpD89xQTZPiYN59hzSj.json b/logs/2024-06-12T19-10-07-07-00_security-guide_DrGcpD89xQTZPiYN59hzSj.json deleted file mode 100644 index fa99bb91..00000000 --- a/logs/2024-06-12T19-10-07-07-00_security-guide_DrGcpD89xQTZPiYN59hzSj.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "DrGcpD89xQTZPiYN59hzSj", - "run_id": "K4hAtNqkm2YgniydSKtdDt", - "created": "2024-06-12T19:10:07-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T19:10:07-07:00", - "completed_at": "2024-06-12T19:10:07-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-20-14-07-00_security-guide_NbMLjeXvkPjWSpZQDQoaRT.json b/logs/2024-06-12T19-20-14-07-00_security-guide_NbMLjeXvkPjWSpZQDQoaRT.json deleted file mode 100644 index 41ce3355..00000000 --- a/logs/2024-06-12T19-20-14-07-00_security-guide_NbMLjeXvkPjWSpZQDQoaRT.json +++ /dev/null @@ -1,51 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "NbMLjeXvkPjWSpZQDQoaRT", - "run_id": "mh5wLLe8tdAFGGbCqKHB6A", - "created": "2024-06-12T19:20:14-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 0, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "stats": { - "started_at": "2024-06-12T19:20:14-07:00", - "completed_at": "2024-06-12T19:20:14-07:00", - "model_usage": {} - }, - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-21-38-07-00_security-guide_7uTjdhszqprw5hGRWF26TN.json b/logs/2024-06-12T19-21-38-07-00_security-guide_7uTjdhszqprw5hGRWF26TN.json deleted file mode 100644 index 6e15e561..00000000 --- a/logs/2024-06-12T19-21-38-07-00_security-guide_7uTjdhszqprw5hGRWF26TN.json +++ /dev/null @@ -1,136 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "7uTjdhszqprw5hGRWF26TN", - "run_id": "8WeGruy3QETmGZcyFg4abz", - "created": "2024-06-12T19:21:38-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_qa", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-12T19:21:38-07:00", - "completed_at": "2024-06-12T19:21:42-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 720, - "output_tokens": 233, - "total_tokens": 953 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": "Tell me a story in 3 sentences or less.", - "target": "Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"", - "messages": [ - { - "content": "\nTell me a story in 3 sentences or less.\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: Tell me a story in 3 sentences or less.\n***\n[Answer]: \n***\n[Critique]: The original answer is fully correct.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "It seems like there is no story provided in the original answer, so to improve the response, we need to create a story with just three sentences. \n\n1. Once upon a time, in a magical forest, a curious fox met a wise owl.\n2. The owl told the fox about a hidden treasure deep in the heart of the woods.\n3. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.\n\nANSWER: Once upon a time, in a magical forest, a curious fox met a wise owl. The owl told the fox about a hidden treasure deep in the heart of the woods. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "It seems like there is no story provided in the original answer, so to improve the response, we need to create a story with just three sentences. \n\n1. Once upon a time, in a magical forest, a curious fox met a wise owl.\n2. The owl told the fox about a hidden treasure deep in the heart of the woods.\n3. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.\n\nANSWER: Once upon a time, in a magical forest, a curious fox met a wise owl. The owl told the fox about a hidden treasure deep in the heart of the woods. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 187, - "output_tokens": 142, - "total_tokens": 329 - } - }, - "score": { - "value": "I", - "answer": "It seems like there is no story provided in the original answer, so to improve the response, we need to create a story with just three sentences. \n\n1. Once upon a time, in a magical forest, a curious fox met a wise owl.\n2. The owl told the fox about a hidden treasure deep in the heart of the woods.\n3. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.\n\nANSWER: Once upon a time, in a magical forest, a curious fox met a wise owl. The owl told the fox about a hidden treasure deep in the heart of the woods. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.", - "explanation": "1. The criterion is asking for a story about finding a treasure while sailing on a ship and battling obstacles like ghostly seadogs and sea monsters.\n2. The submission, however, tells a story about a fox and an owl in a magical forest, which does not align with the criterion's requirements.\n3. Since the submission does not meet the specified criterion, the answer should be considered incorrect.\n\nGRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are assessing a submitted answer on a given task based on a criterion. Here is the data:\n\n[BEGIN DATA]\n***\n[Task]: Tell me a story in 3 sentences or less.\n***\n[Submission]: It seems like there is no story provided in the original answer, so to improve the response, we need to create a story with just three sentences. \n\n1. Once upon a time, in a magical forest, a curious fox met a wise owl.\n2. The owl told the fox about a hidden treasure deep in the heart of the woods.\n3. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.\n\nANSWER: Once upon a time, in a magical forest, a curious fox met a wise owl. The owl told the fox about a hidden treasure deep in the heart of the woods. Together, they embarked on an adventure, overcoming obstacles and finally discovering the treasure.\n***\n[Criterion]: Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"\n***\n[END DATA]\n\nDoes the submission meet the criterion?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The criterion is asking for a story about finding a treasure while sailing on a ship and battling obstacles like ghostly seadogs and sea monsters.\n2. The submission, however, tells a story about a fox and an owl in a magical forest, which does not align with the criterion's requirements.\n3. Since the submission does not meet the specified criterion, the answer should be considered incorrect.\n\nGRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file diff --git a/logs/2024-06-12T19-22-28-07-00_security-guide_inCT9mgYbUaFjVdy32qFgi.json b/logs/2024-06-12T19-22-28-07-00_security-guide_inCT9mgYbUaFjVdy32qFgi.json deleted file mode 100644 index 007ae6e6..00000000 --- a/logs/2024-06-12T19-22-28-07-00_security-guide_inCT9mgYbUaFjVdy32qFgi.json +++ /dev/null @@ -1,136 +0,0 @@ -{ - "version": 1, - "status": "success", - "eval": { - "task": "security_guide", - "task_version": 0, - "task_file": "src/examples/inspect_ai_example/basic_eval.py", - "task_id": "inCT9mgYbUaFjVdy32qFgi", - "run_id": "SdqZUHYzUPaU9LzLUPRgUw", - "created": "2024-06-12T19:22:28-07:00", - "dataset": { - "name": "clxc2mxu6000lpc7ntsvcjvp9", - "location": "langtracefs://clxc2mxu6000lpc7ntsvcjvp9", - "samples": 1, - "shuffled": false - }, - "model": "openai/gpt-3.5-turbo", - "task_attribs": {}, - "task_args": {}, - "model_args": {}, - "config": {}, - "revision": { - "type": "git", - "origin": "git@github.com:Scale3-Labs/langtrace-python-sdk.git", - "commit": "df69f86" - }, - "packages": { - "inspect_ai": "0.3.14" - } - }, - "plan": { - "name": "plan", - "steps": [ - { - "solver": "chain_of_thought", - "params": {} - }, - { - "solver": "self_critique", - "params": {} - } - ], - "config": {} - }, - "results": { - "scorer": { - "name": "model_graded_qa", - "params": {} - }, - "metrics": { - "accuracy": { - "name": "accuracy", - "value": 0.0, - "options": {} - }, - "bootstrap_std": { - "name": "bootstrap_std", - "value": 0.0, - "options": {} - } - } - }, - "stats": { - "started_at": "2024-06-12T19:22:28-07:00", - "completed_at": "2024-06-12T19:22:32-07:00", - "model_usage": { - "openai/gpt-3.5-turbo": { - "input_tokens": 751, - "output_tokens": 273, - "total_tokens": 1024 - } - } - }, - "samples": [ - { - "id": 1, - "epoch": 1, - "input": "Tell me a story in 3 sentences or less.", - "target": "Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"", - "messages": [ - { - "content": "\nTell me a story in 3 sentences or less.\n\nBefore answering, reason in a step-by-step manner as to get the right answer. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "source": "input", - "role": "user" - }, - { - "content": "\nGiven the following question, initial answer and critique please generate an improved answer to the question:\n\n[BEGIN DATA]\n***\n[Question]: Tell me a story in 3 sentences or less.\n***\n[Answer]: \n***\n[Critique]: The answer provided does not address the question at all. It simply repeats the question without providing any sort of answer or story. To improve, the response should include a brief story that can be told in three sentences or less.\n***\n[END DATA]\n\nIf the original answer is already correct, just repeat the original answer exactly. Provide your answer at the end on its own line in the form \"ANSWER: $ANSWER\" (without quotes) where $ANSWER is the answer to the question.\n", - "role": "user" - }, - { - "content": "To tell a story in three sentences, think of a simple plot that can be summarized succinctly. Begin by introducing the setting and characters, then present a conflict or main event, and conclude with a resolution or twist that leaves an impact despite the brevity of the story.\n\nANSWER: Once upon a time in a sleepy village, a young girl found a mysterious key that led to a hidden garden full of wonders. She befriended a lonely dragon living there, and together they uncovered the forgotten magic that healed the land and brought joy back to the villagers. The girl's bravery and kindness became legendary, guiding future generations to seek friendship and adventure in unexpected places.", - "source": "generate", - "role": "assistant" - } - ], - "output": { - "model": "gpt-3.5-turbo-0125", - "choices": [ - { - "message": { - "content": "To tell a story in three sentences, think of a simple plot that can be summarized succinctly. Begin by introducing the setting and characters, then present a conflict or main event, and conclude with a resolution or twist that leaves an impact despite the brevity of the story.\n\nANSWER: Once upon a time in a sleepy village, a young girl found a mysterious key that led to a hidden garden full of wonders. She befriended a lonely dragon living there, and together they uncovered the forgotten magic that healed the land and brought joy back to the villagers. The girl's bravery and kindness became legendary, guiding future generations to seek friendship and adventure in unexpected places.", - "source": "generate", - "role": "assistant" - }, - "stop_reason": "stop" - } - ], - "usage": { - "input_tokens": 225, - "output_tokens": 135, - "total_tokens": 360 - } - }, - "score": { - "value": "I", - "answer": "To tell a story in three sentences, think of a simple plot that can be summarized succinctly. Begin by introducing the setting and characters, then present a conflict or main event, and conclude with a resolution or twist that leaves an impact despite the brevity of the story.\n\nANSWER: Once upon a time in a sleepy village, a young girl found a mysterious key that led to a hidden garden full of wonders. She befriended a lonely dragon living there, and together they uncovered the forgotten magic that healed the land and brought joy back to the villagers. The girl's bravery and kindness became legendary, guiding future generations to seek friendship and adventure in unexpected places.", - "explanation": "1. The criterion is asking for a story about finding cursed treasure while battling various challenges and ultimately obtaining the treasure.\n2. The submission provided a story about a young girl finding a hidden garden, befriending a dragon, and bringing joy to a village.\n3. The submission does not meet the criterion as it does not involve finding cursed treasure, battling ghostly seadogs and sea beasts, and obtaining the treasure as described in the criterion.\n\nGRADE: I", - "metadata": { - "grading": [ - { - "content": "\nYou are assessing a submitted answer on a given task based on a criterion. Here is the data:\n\n[BEGIN DATA]\n***\n[Task]: Tell me a story in 3 sentences or less.\n***\n[Submission]: To tell a story in three sentences, think of a simple plot that can be summarized succinctly. Begin by introducing the setting and characters, then present a conflict or main event, and conclude with a resolution or twist that leaves an impact despite the brevity of the story.\n\nANSWER: Once upon a time in a sleepy village, a young girl found a mysterious key that led to a hidden garden full of wonders. She befriended a lonely dragon living there, and together they uncovered the forgotten magic that healed the land and brought joy back to the villagers. The girl's bravery and kindness became legendary, guiding future generations to seek friendship and adventure in unexpected places.\n***\n[Criterion]: Once upon a stormy eve, we set sail for cursed treasure, led by a map found in the belly of a shark. Battling ghostly seadogs and monstrous sea beasts, we finally pulled the glittering chest from the ocean's depths. Back aboard the ship, the captain roared, \"Shiver me timbers, let it be known through all seven seas that we, the scourge of the blue, be the richest pirates beyond the horizon!\"!\"\n***\n[END DATA]\n\nDoes the submission meet the criterion?\n\n\nAfter assessing the submitted answer, reply with 'GRADE: $LETTER' (without quotes) where LETTER is one of CI. Please choose ONE option for the grade: either \"C\" for correct answers, or \"I\" for incorrect answers.\n\nFor example, after reviewing a correct answer you might write 'GRADE: C' or after reviewing an incorrect answer you might write 'GRADE: I'.\n\nFirst, write out in a step by step manner your reasoning about the criterion to be sure that your conclusion is correct. Avoid simply stating the correct answers at the outset. Then, end with your answer formatted as 'GRADE: $LETTER' (without quotes) where LETTER is one of CI.\n\n", - "role": "user" - }, - { - "content": "1. The criterion is asking for a story about finding cursed treasure while battling various challenges and ultimately obtaining the treasure.\n2. The submission provided a story about a young girl finding a hidden garden, befriending a dragon, and bringing joy to a village.\n3. The submission does not meet the criterion as it does not involve finding cursed treasure, battling ghostly seadogs and sea beasts, and obtaining the treasure as described in the criterion.\n\nGRADE: I", - "source": "generate", - "role": "assistant" - } - ] - } - }, - "metadata": {} - } - ], - "logging": [] -} \ No newline at end of file From a99cf1070aca820c5679c0e3c3eb249137099faa Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Thu, 13 Jun 2024 00:44:52 -0700 Subject: [PATCH 02/11] remove requirements --- requirements.txt | 63 ------------------------------------------------ 1 file changed, 63 deletions(-) delete mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 736759fc..00000000 --- a/requirements.txt +++ /dev/null @@ -1,63 +0,0 @@ -annotated-types==0.6.0 -anthropic==0.25.6 -anyio==4.3.0 -certifi==2024.2.2 -charset-normalizer==3.3.2 -cohere==5.3.2 -Deprecated==1.2.14 -distro==1.9.0 -exceptiongroup==1.2.1 -fastavro==1.9.4 -filelock==3.13.4 -fsspec==2024.3.1 -groq==0.5.0 -grpcio==1.62.2 -grpcio-tools==1.62.2 -h11==0.14.0 -h2==4.1.0 -hpack==4.0.0 -httpcore==1.0.5 -httpx==0.27.0 -httpx-sse==0.4.0 -huggingface-hub==0.22.2 -hyperframe==6.0.1 -idna==3.7 -importlib-metadata==7.0.0 -jsonpatch==1.33 -jsonpointer==2.4 -langchain-core==0.1.46 -langchain-groq==0.1.3 -langchain-openai==0.1.4 -langgraph==0.0.39 -langsmith==0.1.51 -langtrace-python-sdk==1.3.7 -numpy==1.26.4 -openai==1.23.2 -opentelemetry-api==1.24.0 -opentelemetry-instrumentation==0.45b0 -opentelemetry-sdk==1.24.0 -opentelemetry-semantic-conventions==0.45b0 -orjson==3.10.1 -packaging==23.2 -pinecone-client==3.2.2 -portalocker==2.8.2 -protobuf==4.25.3 -pydantic==2.7.0 -pydantic_core==2.18.1 -python-dotenv==1.0.1 -PyYAML==6.0.1 -qdrant-client==1.9.0 -regex==2024.4.16 -requests==2.31.0 -sniffio==1.3.1 -tenacity==8.2.3 -tiktoken==0.6.0 -tokenizers==0.15.2 -tqdm==4.66.2 -trace-attributes==3.0.5 -types-requests==2.31.0.20240406 -typing==3.7.4.3 -typing_extensions==4.11.0 -urllib3==2.2.1 -wrapt==1.16.0 -zipp==3.18.1 From e604e93edcf8efc14c44a626b7458ff1156f5c20 Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Sun, 23 Jun 2024 17:31:07 -0700 Subject: [PATCH 03/11] Bump version --- src/langtrace_python_sdk/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index c427aa78..3734114c 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "2.1.21" +__version__ = "2.1.22" From c62e803920c50f623573d1a42d8d60156f59ebdc Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Wed, 24 Jul 2024 21:36:07 -0700 Subject: [PATCH 04/11] Squash --- README.md | 10 +- pyproject.toml | 2 +- .../math_problems_cot_parallel.py | 51 ++++++++++ src/examples/inspect_ai_example/basic_eval.py | 26 +++-- .../chat_completion_tool_choice.py | 73 ++++++++++++++ .../openai_example/send_user_feedback.py | 40 ++++++++ src/examples/otlp_example/otlp_basic.py | 43 +++++++++ .../otlp_example/otlp_with_langtrace.py | 59 ++++++++++++ src/examples/routellm_example/basic.py | 41 ++++++++ .../extensions/langtrace_filesystem.py | 32 ++++++- .../instrumentation/anthropic/patch.py | 10 +- .../instrumentation/cohere/patch.py | 10 +- .../instrumentation/crewai/instrumentation.py | 33 ++++--- .../instrumentation/dspy/instrumentation.py | 4 +- .../instrumentation/dspy/patch.py | 96 +++++++++++-------- .../instrumentation/gemini/patch.py | 5 +- .../instrumentation/groq/patch.py | 26 ++--- .../instrumentation/ollama/patch.py | 16 +--- .../instrumentation/openai/patch.py | 24 ++--- src/langtrace_python_sdk/utils/__init__.py | 21 ++-- src/langtrace_python_sdk/utils/llm.py | 37 ++++--- .../utils/with_root_span.py | 18 +++- src/langtrace_python_sdk/version.py | 2 +- 23 files changed, 532 insertions(+), 147 deletions(-) create mode 100644 src/examples/dspy_example/math_problems_cot_parallel.py create mode 100644 src/examples/openai_example/chat_completion_tool_choice.py create mode 100644 src/examples/openai_example/send_user_feedback.py create mode 100644 src/examples/otlp_example/otlp_basic.py create mode 100644 src/examples/otlp_example/otlp_with_langtrace.py create mode 100644 src/examples/routellm_example/basic.py diff --git a/README.md b/README.md index 4c0af2b8..a3e0775f 100644 --- a/README.md +++ b/README.md @@ -194,7 +194,7 @@ def main(): from langtrace_python_sdk import with_langtrace_root_span, with_additional_attributes -@with_additional_attributes({"user.id": "1234", "user.feedback.rating": 1}) +@with_additional_attributes({"user.id": "1234"}) def api_call1(): response = client.chat.completions.create( model="gpt-4", @@ -204,7 +204,7 @@ def api_call1(): return response -@with_additional_attributes({"user.id": "5678", "user.feedback.rating": -1}) +@with_additional_attributes({"user.id": "5678"}) def api_call2(): response = client.chat.completions.create( model="gpt-4", @@ -228,6 +228,11 @@ from langtrace_python_sdk import get_prompt_from_registry prompt = get_prompt_from_registry(, options={"prompt_version": 1, "variables": {"foo": "bar"} }) ``` +### Opt out of tracing prompt and completion data +By default, prompt and completion data are captured. If you would like to opt out of it, set the following env var, + +`TRACE_PROMPT_COMPLETION_DATA=false` + ## Supported integrations Langtrace automatically captures traces from the following vendors: @@ -248,6 +253,7 @@ Langtrace automatically captures traces from the following vendors: | CrewAI | Framework | :x: | :white_check_mark: | | Ollama | Framework | :x: | :white_check_mark: | | VertexAI | Framework | :x: | :white_check_mark: | +| Vercel AI SDK| Framework | :white_check_mark: | :x: | | Pinecone | Vector Database | :white_check_mark: | :white_check_mark: | | ChromaDB | Vector Database | :white_check_mark: | :white_check_mark: | | QDrant | Vector Database | :white_check_mark: | :white_check_mark: | diff --git a/pyproject.toml b/pyproject.toml index d833506f..f5ea9d76 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,7 +18,7 @@ classifiers=[ "Operating System :: OS Independent", ] dependencies = [ - 'trace-attributes>=6.0.0,<7.0.0', + 'trace-attributes==7.0.0', 'opentelemetry-api>=1.25.0', 'opentelemetry-sdk>=1.25.0', 'opentelemetry-instrumentation>=0.46b0', diff --git a/src/examples/dspy_example/math_problems_cot_parallel.py b/src/examples/dspy_example/math_problems_cot_parallel.py new file mode 100644 index 00000000..690683e8 --- /dev/null +++ b/src/examples/dspy_example/math_problems_cot_parallel.py @@ -0,0 +1,51 @@ +import contextvars +import dspy +from dspy.datasets.gsm8k import GSM8K, gsm8k_metric +from dspy.teleprompt import BootstrapFewShot +from concurrent.futures import ThreadPoolExecutor + +# flake8: noqa +from langtrace_python_sdk import langtrace, with_langtrace_root_span, inject_additional_attributes + +langtrace.init() + +turbo = dspy.OpenAI(model="gpt-3.5-turbo", max_tokens=250) +dspy.settings.configure(lm=turbo) + +# Load math questions from the GSM8K dataset +gsm8k = GSM8K() +gsm8k_trainset, gsm8k_devset = gsm8k.train[:10], gsm8k.dev[:10] + +class CoT(dspy.Module): + def __init__(self): + super().__init__() + self.prog = dspy.ChainOfThought("question -> answer") + + def forward(self, question): + result = inject_additional_attributes(lambda: self.prog(question=question), {'langtrace.span.name': 'MathProblemsCotParallel'}) + return result + +@with_langtrace_root_span(name="parallel_example") +def example(): + # Set up the optimizer: we want to "bootstrap" (i.e., self-generate) 4-shot examples of our CoT program. + config = dict(max_bootstrapped_demos=4, max_labeled_demos=4) + + # Optimize! Use the `gsm8k_metric` here. In general, the metric is going to tell the optimizer how well it's doing. + teleprompter = BootstrapFewShot(metric=gsm8k_metric, **config) + optimized_cot = teleprompter.compile(CoT(), trainset=gsm8k_trainset) + + questions = [ + "What is the sine of 0?", + "What is the tangent of 100?", + ] + + with ThreadPoolExecutor(max_workers=2) as executor: + futures = [executor.submit(contextvars.copy_context().run, optimized_cot, question=q) for q in questions] + + for future in futures: + ans = future.result() + print(ans) + + +if __name__ == "__main__": + example() diff --git a/src/examples/inspect_ai_example/basic_eval.py b/src/examples/inspect_ai_example/basic_eval.py index be509111..6cc9e7ab 100644 --- a/src/examples/inspect_ai_example/basic_eval.py +++ b/src/examples/inspect_ai_example/basic_eval.py @@ -1,24 +1,34 @@ -# langtrace.init(write_spans_to_console=True) import fsspec +from dotenv import find_dotenv, load_dotenv from inspect_ai import Task, task -from inspect_ai.dataset import csv_dataset +from inspect_ai.dataset import csv_dataset, Sample from inspect_ai.scorer import model_graded_qa -from inspect_ai.solver import chain_of_thought, generate, self_critique - +from inspect_ai.solver import chain_of_thought, self_critique from langtrace_python_sdk.extensions.langtrace_filesystem import LangTraceFileSystem -# from langtrace_python_sdk import langtrace - +_ = load_dotenv(find_dotenv()) # Manually register the filesystem with fsspec # Note: This is only necessary because the filesystem is not registered. fsspec.register_implementation(LangTraceFileSystem.protocol, LangTraceFileSystem) +question = "What is the price?" + + +def hydrate_with_question(record): + # add context to input + record["input"] = f"Context: {record['input']}\n question: {question}" + + return Sample( + input=record["input"], + target=record["target"], + ) + @task -def security_guide(): +def basic_eval(): return Task( - dataset=csv_dataset("langtracefs://clxc2mxu6000lpc7ntsvcjvp9"), + dataset=csv_dataset("langtracefs://clz0p4i1t000fwv0xjtlvkxyx"), plan=[chain_of_thought(), self_critique()], scorer=model_graded_qa(), ) diff --git a/src/examples/openai_example/chat_completion_tool_choice.py b/src/examples/openai_example/chat_completion_tool_choice.py new file mode 100644 index 00000000..e1aaef11 --- /dev/null +++ b/src/examples/openai_example/chat_completion_tool_choice.py @@ -0,0 +1,73 @@ +# Example taken from https://platform.openai.com/docs/guides/function-calling +import json + +from dotenv import find_dotenv, load_dotenv +from openai import OpenAI + +from langtrace_python_sdk import langtrace + +client = OpenAI() + +_ = load_dotenv(find_dotenv()) + +langtrace.init( + write_spans_to_console=True, +) + + +# Example dummy function hard coded to return the same weather +# In production, this could be your backend API or an external API +def get_current_weather(location, unit="fahrenheit"): + """Get the current weather in a given location""" + if "tokyo" in location.lower(): + return json.dumps({"location": "Tokyo", "temperature": "10", "unit": unit}) + elif "san francisco" in location.lower(): + return json.dumps( + {"location": "San Francisco", "temperature": "72", "unit": unit} + ) + elif "paris" in location.lower(): + return json.dumps({"location": "Paris", "temperature": "22", "unit": unit}) + else: + return json.dumps({"location": location, "temperature": "unknown"}) + + +def run_conversation(): + # Step 1: send the conversation and available functions to the model + messages = [ + { + "role": "user", + "content": "What's the weather like in San Francisco, Tokyo, and Paris?", + } + ] + tools = [ + { + "type": "function", + "function": { + "name": "get_current_weather", + "description": "Get the current weather in a given location", + "parameters": { + "type": "object", + "properties": { + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, + }, + "required": ["location"], + }, + }, + } + ] + response = client.chat.completions.create( + model="gpt-4o", + messages=messages, + tools=tools, + tool_choice="required", # auto is default, but we'll be explicit + ) + response_message = response.choices[0].message + tool_calls = response_message.tool_calls + print(tool_calls) + + +print(run_conversation()) diff --git a/src/examples/openai_example/send_user_feedback.py b/src/examples/openai_example/send_user_feedback.py new file mode 100644 index 00000000..a29198b8 --- /dev/null +++ b/src/examples/openai_example/send_user_feedback.py @@ -0,0 +1,40 @@ +from dotenv import find_dotenv, load_dotenv +from openai import OpenAI +from langtrace_python_sdk import langtrace, with_langtrace_root_span, SendUserFeedback + +_ = load_dotenv(find_dotenv()) + +# Initialize Langtrace SDK +langtrace.init() +client = OpenAI() + + +def api(span_id, trace_id): + response = client.chat.completions.create( + model="gpt-4o-mini", + messages=[ + {"role": "user", "content": "What is the best place to live in the US?"}, + ], + stream=False, + ) + + # Collect user feedback and send it to Langtrace + user_score = 1 # Example user score + user_id = 'user_1234' # Example user ID + data = { + "userScore": user_score, + "userId": user_id, + "spanId": span_id, + "traceId": trace_id + } + SendUserFeedback().evaluate(data=data) + + # Return the response + return response.choices[0].message.content + + +# wrap the API call with the Langtrace root span +wrapped_api = with_langtrace_root_span()(api) + +# Call the wrapped API +wrapped_api() diff --git a/src/examples/otlp_example/otlp_basic.py b/src/examples/otlp_example/otlp_basic.py new file mode 100644 index 00000000..48da9129 --- /dev/null +++ b/src/examples/otlp_example/otlp_basic.py @@ -0,0 +1,43 @@ +# Instructions +# 1. Run the OpenTelemetry Collector with the OTLP receiver enabled +# Create otel-config.yaml with the following content: +# receivers: +# otlp: +# protocols: +# grpc: +# endpoint: "0.0.0.0:4317" +# http: +# endpoint: "0.0.0.0:4318" + +# exporters: +# logging: +# loglevel: debug + +# service: +# pipelines: +# traces: +# receivers: [otlp] +# exporters: [logging] +# docker pull otel/opentelemetry-collector:latest +# docker run --rm -p 4317:4317 -p 4318:4318 -v $(pwd)/otel-config.yaml:/otel-config.yaml otel/opentelemetry-collector --config otel-config.yaml +# 2. Run the following code + +from opentelemetry import trace +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import BatchSpanProcessor +from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter + +# Set up the tracer provider +trace.set_tracer_provider(TracerProvider()) +tracer = trace.get_tracer(__name__) + +# Set up the OTLP exporter +otlp_exporter = OTLPSpanExporter(endpoint="http://localhost:4317") + +# Set up a span processor and add it to the tracer provider +span_processor = BatchSpanProcessor(otlp_exporter) +trace.get_tracer_provider().add_span_processor(span_processor) + +# Create a span +with tracer.start_as_current_span("example-span"): + print("Hello, World!") diff --git a/src/examples/otlp_example/otlp_with_langtrace.py b/src/examples/otlp_example/otlp_with_langtrace.py new file mode 100644 index 00000000..52851dfa --- /dev/null +++ b/src/examples/otlp_example/otlp_with_langtrace.py @@ -0,0 +1,59 @@ +# Instructions +# 1. Run the OpenTelemetry Collector with the OTLP receiver enabled +# Create otel-config.yaml with the following content: +# receivers: +# otlp: +# protocols: +# grpc: +# endpoint: "0.0.0.0:4317" +# http: +# endpoint: "0.0.0.0:4318" + +# exporters: +# logging: +# loglevel: debug + +# service: +# pipelines: +# traces: +# receivers: [otlp] +# exporters: [logging] +# docker pull otel/opentelemetry-collector:latest +# docker run --rm -p 4317:4317 -p 4318:4318 -v $(pwd)/otel-config.yaml:/otel-config.yaml otel/opentelemetry-collector --config otel-config.yaml +# 2. Run the following code + +from langtrace_python_sdk import langtrace +from openai import OpenAI +from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter + + +# Configure the OTLP exporter to use the correct endpoint and API key +otlp_endpoint = "http://localhost:4318/v1/traces" +otlp_exporter = OTLPSpanExporter( + endpoint=otlp_endpoint, + headers=(("Content-Type", "application/json"),)) +langtrace.init(custom_remote_exporter=otlp_exporter, batch=False) + + +def chat_with_openai(): + client = OpenAI() + messages = [ + { + "role": "user", + "content": "Hello, I'm a human.", + }, + ] + chat_completion = client.chat.completions.create( + messages=messages, + stream=False, + model="gpt-3.5-turbo", + ) + print(chat_completion.choices[0].message.content) + + +def main(): + chat_with_openai() + + +if __name__ == "__main__": + main() diff --git a/src/examples/routellm_example/basic.py b/src/examples/routellm_example/basic.py new file mode 100644 index 00000000..9f908fb0 --- /dev/null +++ b/src/examples/routellm_example/basic.py @@ -0,0 +1,41 @@ +import sys + +sys.path.insert(0, "/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/src") + +from langtrace_python_sdk import langtrace +from langtrace_python_sdk.utils.with_root_span import with_langtrace_root_span +from routellm.controller import Controller +from dotenv import load_dotenv + +load_dotenv() + +langtrace.init() + +# litellm.set_verbose=True +client = Controller( + routers=["mf"], + strong_model="claude-3-opus-20240229", + weak_model="claude-3-opus-20240229", +) + + +@with_langtrace_root_span("Routellm") +def Routellm(prompt): + try: + + response = client.chat.completions.create( + model="router-mf-0.11593", messages=[{"role": "user", "content": prompt}] + ) + + for chunk in response: + if hasattr(chunk, "choices"): + print(chunk.choices[0].delta.content or "", end="") + else: + print(chunk) + + except Exception as e: + print(f"An error occurred: {e}") + + +Routellm("what is the square root of 12182382932.99") +Routellm("Write me a short story") diff --git a/src/langtrace_python_sdk/extensions/langtrace_filesystem.py b/src/langtrace_python_sdk/extensions/langtrace_filesystem.py index 6506be40..c89f75aa 100644 --- a/src/langtrace_python_sdk/extensions/langtrace_filesystem.py +++ b/src/langtrace_python_sdk/extensions/langtrace_filesystem.py @@ -27,13 +27,25 @@ def __new__(cls, value): class LangTraceFile(io.BytesIO): - _host: str = os.environ.get("LANGTRACE_API_HOST", None) or LANGTRACE_REMOTE_URL def __init__(self, fs: "LangTraceFileSystem", path: str, mode: OpenMode): super().__init__() self.fs = fs self.path = path self.mode = mode + self._host: str = os.environ.get("LANGTRACE_API_HOST", LANGTRACE_REMOTE_URL) + self._api_key: str = os.environ.get("LANGTRACE_API_KEY", None) + if self._host.endswith("/api/trace"): + self._host = self._host.replace("/api/trace", "") + + if self._api_key is None: + print(Fore.RED) + print( + f"Missing Langtrace API key, proceed to {self._host} to create one" + ) + print("Set the API key as an environment variable LANGTRACE_API_KEY") + print(Fore.RESET) + return def close(self) -> None: if not self.closed: @@ -71,7 +83,7 @@ def upload_to_server(self, file_data: bytes) -> None: data=json.dumps(data), headers={ "Content-Type": "application/json", - "x-api-key": os.environ.get("LANGTRACE_API_KEY"), + "x-api-key": self._api_key, }, timeout=20, ) @@ -82,7 +94,6 @@ def upload_to_server(self, file_data: bytes) -> None: class LangTraceFileSystem(AbstractFileSystem): - _host: str = os.environ.get("LANGTRACE_API_HOST", None) or LANGTRACE_REMOTE_URL protocol = "langtracefs" sep = "/" @@ -90,6 +101,19 @@ def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.files = {} self.dirs = set() + self._host: str = os.environ.get("LANGTRACE_API_HOST", LANGTRACE_REMOTE_URL) + self._api_key: str = os.environ.get("LANGTRACE_API_KEY", None) + if self._host.endswith("/api/trace"): + self._host = self._host.replace("/api/trace", "") + + if self._api_key is None: + print(Fore.RED) + print( + f"Missing Langtrace API key, proceed to {self._host} to create one" + ) + print("Set the API key as an environment variable LANGTRACE_API_KEY") + print(Fore.RESET) + return def open( self, @@ -118,7 +142,7 @@ def fetch_file_from_api(self, dataset_id: str) -> bytes: url=f"{self._host}/api/dataset/download?id={dataset_id}", headers={ "Content-Type": "application/json", - "x-api-key": os.environ.get("LANGTRACE_API_KEY"), + "x-api-key": self._api_key, }, timeout=20, ) diff --git a/src/langtrace_python_sdk/instrumentation/anthropic/patch.py b/src/langtrace_python_sdk/instrumentation/anthropic/patch.py index b06fae33..69618667 100644 --- a/src/langtrace_python_sdk/instrumentation/anthropic/patch.py +++ b/src/langtrace_python_sdk/instrumentation/anthropic/patch.py @@ -25,6 +25,7 @@ get_llm_url, is_streaming, set_event_completion, + set_event_completion_chunk, set_usage_attributes, ) from opentelemetry.trace import SpanKind @@ -48,7 +49,9 @@ def traced_method(wrapped, instance, args, kwargs): prompts = kwargs.get("messages", []) system = kwargs.get("system") if system: - prompts = [{"role": "system", "content": system}] + kwargs.get("messages", []) + prompts = [{"role": "system", "content": system}] + kwargs.get( + "messages", [] + ) span_attributes = { **get_langtrace_attributes(version, service_provider), @@ -117,10 +120,7 @@ def handle_streaming_response(result, span): # Assuming span.add_event is part of a larger logging or event system # Add event for each chunk of content if content: - span.add_event( - Event.STREAM_OUTPUT.value, - {SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: "".join(content)}, - ) + set_event_completion_chunk(span, "".join(content)) # Assuming this is part of a generator, yield chunk or aggregated content yield content diff --git a/src/langtrace_python_sdk/instrumentation/cohere/patch.py b/src/langtrace_python_sdk/instrumentation/cohere/patch.py index 7fe72376..560ff631 100644 --- a/src/langtrace_python_sdk/instrumentation/cohere/patch.py +++ b/src/langtrace_python_sdk/instrumentation/cohere/patch.py @@ -22,6 +22,7 @@ get_extra_attributes, get_llm_url, set_event_completion, + set_event_completion_chunk, set_usage_attributes, ) from langtrace.trace_attributes import Event, LLMSpanAttributes @@ -44,7 +45,7 @@ def traced_method(wrapped, instance, args, kwargs): span_attributes = { **get_langtrace_attributes(version, service_provider), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="rerank"), **get_llm_url(instance), SpanAttributes.LLM_REQUEST_MODEL: kwargs.get("model") or "command-r-plus", SpanAttributes.LLM_URL: APIS["RERANK"]["URL"], @@ -121,7 +122,7 @@ def traced_method(wrapped, instance, args, kwargs): span_attributes = { **get_langtrace_attributes(version, service_provider), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="embed"), **get_llm_url(instance), SpanAttributes.LLM_URL: APIS["EMBED"]["URL"], SpanAttributes.LLM_PATH: APIS["EMBED"]["ENDPOINT"], @@ -403,10 +404,7 @@ def traced_method(wrapped, instance, args, kwargs): content = event.text else: content = "" - span.add_event( - Event.STREAM_OUTPUT.value, - {SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: "".join(content)}, - ) + set_event_completion_chunk(span, "".join(content)) if ( hasattr(event, "finish_reason") diff --git a/src/langtrace_python_sdk/instrumentation/crewai/instrumentation.py b/src/langtrace_python_sdk/instrumentation/crewai/instrumentation.py index e648b671..78cb1f87 100644 --- a/src/langtrace_python_sdk/instrumentation/crewai/instrumentation.py +++ b/src/langtrace_python_sdk/instrumentation/crewai/instrumentation.py @@ -33,21 +33,24 @@ def _instrument(self, **kwargs): tracer_provider = kwargs.get("tracer_provider") tracer = get_tracer(__name__, "", tracer_provider) version = v("crewai") - _W( - "crewai.crew", - "Crew.kickoff", - patch_crew("Crew.kickoff", version, tracer), - ) - _W( - "crewai.agent", - "Agent.execute_task", - patch_crew("Agent.execute_task", version, tracer), - ) - _W( - "crewai.task", - "Task.execute", - patch_crew("Task.execute", version, tracer), - ) + try: + _W( + "crewai.crew", + "Crew.kickoff", + patch_crew("Crew.kickoff", version, tracer), + ) + _W( + "crewai.agent", + "Agent.execute_task", + patch_crew("Agent.execute_task", version, tracer), + ) + _W( + "crewai.task", + "Task.execute", + patch_crew("Task.execute", version, tracer), + ) + except Exception as e: + pass def _uninstrument(self, **kwargs): pass diff --git a/src/langtrace_python_sdk/instrumentation/dspy/instrumentation.py b/src/langtrace_python_sdk/instrumentation/dspy/instrumentation.py index 375989ef..a9cc587e 100644 --- a/src/langtrace_python_sdk/instrumentation/dspy/instrumentation.py +++ b/src/langtrace_python_sdk/instrumentation/dspy/instrumentation.py @@ -27,12 +27,12 @@ class DspyInstrumentation(BaseInstrumentor): The DspyInstrumentor class represents the DSPy instrumentation""" def instrumentation_dependencies(self) -> Collection[str]: - return ["dspy >= 0.1.5"] + return ["dspy-ai >= 2.0.0"] def _instrument(self, **kwargs): tracer_provider = kwargs.get("tracer_provider") tracer = get_tracer(__name__, "", tracer_provider) - version = v("dspy") + version = v("dspy-ai") _W( "dspy.teleprompt.bootstrap", "BootstrapFewShot.compile", diff --git a/src/langtrace_python_sdk/instrumentation/dspy/patch.py b/src/langtrace_python_sdk/instrumentation/dspy/patch.py index 3427eba9..4b57fe16 100644 --- a/src/langtrace_python_sdk/instrumentation/dspy/patch.py +++ b/src/langtrace_python_sdk/instrumentation/dspy/patch.py @@ -39,30 +39,36 @@ def traced_method(wrapped, instance, args, kwargs): ), } span_attributes["dspy.optimizer.module.prog"] = json.dumps(prog) - if "metric" in instance and instance.metric: - span_attributes["dspy.optimizer.metric"] = instance.metric.__name__ + if hasattr(instance, 'metric'): + span_attributes["dspy.optimizer.metric"] = getattr(instance, 'metric').__name__ if kwargs.get("trainset") and len(kwargs.get("trainset")) > 0: span_attributes["dspy.optimizer.trainset"] = str(kwargs.get("trainset")) config = {} - if "metric_threshold" in instance and instance.metric_threshold: - config["metric_threshold"] = instance.metric_threshold - if "teacher_settings" in instance and instance.teacher_settings: - config["teacher_settings"] = instance.teacher_settings - if "max_bootstrapped_demos" in instance and instance.max_bootstrapped_demos: - config["max_bootstrapped_demos"] = instance.max_bootstrapped_demos - if "max_labeled_demos" in instance and instance.max_labeled_demos: - config["max_labeled_demos"] = instance.max_labeled_demos - if "max_rounds" in instance and instance.max_rounds: - config["max_rounds"] = instance.max_rounds - if "max_errors" in instance and instance.max_errors: - config["max_errors"] = instance.max_errors - if "error_count" in instance and instance.error_count: - config["error_count"] = instance.error_count + if hasattr(instance, 'metric_threshold'): + config["metric_threshold"] = getattr(instance, 'metric_threshold') + if hasattr(instance, 'teacher_settings'): + config["teacher_settings"] = getattr(instance, 'teacher_settings') + if hasattr(instance, 'max_bootstrapped_demos'): + config["max_bootstrapped_demos"] = getattr(instance, 'max_bootstrapped_demos') + if hasattr(instance, 'max_labeled_demos'): + config["max_labeled_demos"] = getattr(instance, 'max_labeled_demos') + if hasattr(instance, 'max_rounds'): + config["max_rounds"] = getattr(instance, 'max_rounds') + if hasattr(instance, 'max_steps'): + config["max_errors"] = getattr(instance, 'max_errors') + if hasattr(instance, 'error_count'): + config["error_count"] = getattr(instance, 'error_count') if config and len(config) > 0: span_attributes["dspy.optimizer.config"] = json.dumps(config) + # passed operation name + opname = operation_name + if extra_attributes is not None and "langtrace.span.name" in extra_attributes: + # append the operation name to the span name + opname = f"{operation_name}-{extra_attributes['langtrace.span.name']}" + attributes = FrameworkSpanAttributes(**span_attributes) - with tracer.start_as_current_span(operation_name, kind=SpanKind.CLIENT) as span: + with tracer.start_as_current_span(opname, kind=SpanKind.CLIENT) as span: _set_input_attributes(span, kwargs, attributes) try: @@ -100,6 +106,12 @@ def traced_method(wrapped, instance, args, kwargs): **(extra_attributes if extra_attributes is not None else {}), } + # passed operation name + opname = operation_name + if extra_attributes is not None and "langtrace.span.name" in extra_attributes: + # append the operation name to the span name + opname = f"{operation_name}-{extra_attributes['langtrace.span.name']}" + if instance.__class__.__name__: span_attributes["dspy.signature.name"] = instance.__class__.__name__ span_attributes["dspy.signature"] = str(instance) @@ -108,7 +120,7 @@ def traced_method(wrapped, instance, args, kwargs): span_attributes["dspy.signature.args"] = str(kwargs) attributes = FrameworkSpanAttributes(**span_attributes) - with tracer.start_as_current_span(operation_name, kind=SpanKind.CLIENT) as span: + with tracer.start_as_current_span(opname, kind=SpanKind.CLIENT) as span: _set_input_attributes(span, kwargs, attributes) try: @@ -147,35 +159,41 @@ def traced_method(wrapped, instance, args, kwargs): **(extra_attributes if extra_attributes is not None else {}), } - if "devset" in instance and instance.devset is not None: - span_attributes["dspy.evaluate.devset"] = str(instance.devset) - if "display" in instance and instance.display is not None: - span_attributes["dspy.evaluate.display"] = str(instance.display) - if "num_threads" in instance and instance.num_threads is not None: - span_attributes["dspy.evaluate.num_threads"] = str(instance.num_threads) - if "return_outputs" in instance and instance.return_outputs is not None: + # passed operation name + opname = operation_name + if extra_attributes is not None and "langtrace.span.name" in extra_attributes: + # append the operation name to the span name + opname = f"{operation_name}-{extra_attributes['langtrace.span.name']}" + + if hasattr(instance, "devset"): + span_attributes["dspy.evaluate.devset"] = str(getattr(instance, "devset")) + if hasattr(instance, "trainset"): + span_attributes["dspy.evaluate.display"] = str(getattr(instance, "trainset")) + if hasattr(instance, "num_threads"): + span_attributes["dspy.evaluate.num_threads"] = str(getattr(instance, "num_threads")) + if hasattr(instance, "return_outputs"): span_attributes["dspy.evaluate.return_outputs"] = str( - instance.return_outputs + getattr(instance, "return_outputs") ) - if "display_table" in instance and instance.display_table is not None: - span_attributes["dspy.evaluate.display_table"] = str(instance.display_table) - if "display_progress" in instance and instance.display_progress is not None: + if hasattr(instance, "display_table"): + span_attributes["dspy.evaluate.display_table"] = str(getattr(instance, "display_table")) + if hasattr(instance, "display_progress"): span_attributes["dspy.evaluate.display_progress"] = str( - instance.display_progress + getattr(instance, "display_progress") ) - if "metric" in instance and instance.metric is not None: - span_attributes["dspy.evaluate.metric"] = instance.metric.__name__ - if "error_count" in instance and instance.error_count is not None: - span_attributes["dspy.evaluate.error_count"] = str(instance.error_count) - if "error_lock" in instance and instance.error_lock is not None: - span_attributes["dspy.evaluate.error_lock"] = str(instance.error_lock) - if "max_errors" in instance and instance.max_errors is not None: - span_attributes["dspy.evaluate.max_errors"] = str(instance.max_errors) + if hasattr(instance, "metric"): + span_attributes["dspy.evaluate.metric"] = getattr(instance, "metric").__name__ + if hasattr(instance, "error_count"): + span_attributes["dspy.evaluate.error_count"] = str(getattr(instance, "error_count")) + if hasattr(instance, "error_lock"): + span_attributes["dspy.evaluate.error_lock"] = str(getattr(instance, "error_lock")) + if hasattr(instance, "max_errors"): + span_attributes["dspy.evaluate.max_errors"] = str(getattr(instance, "max_errors")) if args and len(args) > 0: span_attributes["dspy.evaluate.args"] = str(args) attributes = FrameworkSpanAttributes(**span_attributes) - with tracer.start_as_current_span(operation_name, kind=SpanKind.CLIENT) as span: + with tracer.start_as_current_span(opname, kind=SpanKind.CLIENT) as span: _set_input_attributes(span, kwargs, attributes) try: diff --git a/src/langtrace_python_sdk/instrumentation/gemini/patch.py b/src/langtrace_python_sdk/instrumentation/gemini/patch.py index b4b9b799..ceedb379 100644 --- a/src/langtrace_python_sdk/instrumentation/gemini/patch.py +++ b/src/langtrace_python_sdk/instrumentation/gemini/patch.py @@ -110,7 +110,10 @@ def get_llm_model(instance): def serialize_prompts(args, kwargs, instance): prompts = [] - if hasattr(instance, "_system_instruction") and instance._system_instruction is not None: + if ( + hasattr(instance, "_system_instruction") + and instance._system_instruction is not None + ): system_prompt = { "role": "system", "content": instance._system_instruction.__dict__["_pb"].parts[0].text, diff --git a/src/langtrace_python_sdk/instrumentation/groq/patch.py b/src/langtrace_python_sdk/instrumentation/groq/patch.py index 82f345e6..11c89a88 100644 --- a/src/langtrace_python_sdk/instrumentation/groq/patch.py +++ b/src/langtrace_python_sdk/instrumentation/groq/patch.py @@ -30,6 +30,7 @@ get_llm_url, get_langtrace_attributes, set_event_completion, + set_event_completion_chunk, set_usage_attributes, ) from langtrace_python_sdk.constants.instrumentation.common import ( @@ -104,10 +105,10 @@ def traced_method(wrapped, instance, args, kwargs): # TODO(Karthik): Gotta figure out how to handle streaming with context # with tracer.start_as_current_span(APIS["CHAT_COMPLETION"]["METHOD"], - # kind=SpanKind.CLIENT.value) as span: + # kind=SpanKind.CLIENT) as span: span = tracer.start_span( APIS["CHAT_COMPLETION"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) for field, value in attributes.model_dump(by_alias=True).items(): @@ -242,15 +243,14 @@ def handle_streaming_response( content = content + [] else: content = [] - span.add_event( - Event.STREAM_OUTPUT.value, - { - SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: ( - "".join(content) - if len(content) > 0 and content[0] is not None - else "" - ) - }, + + set_event_completion_chunk( + span, + ( + "".join(content) + if len(content) > 0 and content[0] is not None + else "" + ), ) result_content.append(content[0] if len(content) > 0 else "") yield chunk @@ -333,9 +333,9 @@ async def traced_method(wrapped, instance, args, kwargs): # TODO(Karthik): Gotta figure out how to handle streaming with context # with tracer.start_as_current_span(APIS["CHAT_COMPLETION"]["METHOD"], - # kind=SpanKind.CLIENT.value) as span: + # kind=SpanKind.CLIENT) as span: span = tracer.start_span( - APIS["CHAT_COMPLETION"]["METHOD"], kind=SpanKind.CLIENT.value + APIS["CHAT_COMPLETION"]["METHOD"], kind=SpanKind.CLIENT ) for field, value in attributes.model_dump(by_alias=True).items(): set_span_attribute(span, field, value) diff --git a/src/langtrace_python_sdk/instrumentation/ollama/patch.py b/src/langtrace_python_sdk/instrumentation/ollama/patch.py index 584320e3..9c13073a 100644 --- a/src/langtrace_python_sdk/instrumentation/ollama/patch.py +++ b/src/langtrace_python_sdk/instrumentation/ollama/patch.py @@ -6,6 +6,7 @@ get_llm_request_attributes, get_llm_url, set_event_completion, + set_event_completion_chunk, ) from langtrace_python_sdk.utils.silently_fail import silently_fail from langtrace_python_sdk.constants.instrumentation.common import SERVICE_PROVIDERS @@ -177,12 +178,8 @@ def _handle_streaming_response(span, response, api): if api == "generate": accumulated_tokens["response"] += chunk["response"] - span.add_event( - Event.STREAM_OUTPUT.value, - { - SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: chunk.get("response") - or chunk.get("message").get("content"), - }, + set_event_completion_chunk( + span, chunk.get("response") or chunk.get("message").get("content") ) _set_response_attributes(span, chunk | accumulated_tokens) @@ -211,12 +208,7 @@ async def _ahandle_streaming_response(span, response, api): if api == "generate": accumulated_tokens["response"] += chunk["response"] - span.add_event( - Event.STREAM_OUTPUT.value, - { - SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: json.dumps(chunk), - }, - ) + set_event_completion_chunk(span, chunk) _set_response_attributes(span, chunk | accumulated_tokens) finally: # Finalize span after processing all chunks diff --git a/src/langtrace_python_sdk/instrumentation/openai/patch.py b/src/langtrace_python_sdk/instrumentation/openai/patch.py index e72e0441..a70ca630 100644 --- a/src/langtrace_python_sdk/instrumentation/openai/patch.py +++ b/src/langtrace_python_sdk/instrumentation/openai/patch.py @@ -55,7 +55,7 @@ def traced_method(wrapped, instance, args, kwargs): service_provider = SERVICE_PROVIDERS["OPENAI"] span_attributes = { **get_langtrace_attributes(version, service_provider, vendor_type="llm"), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="images_generate"), **get_llm_url(instance), SpanAttributes.LLM_PATH: APIS["IMAGES_GENERATION"]["ENDPOINT"], **get_extra_attributes(), @@ -65,7 +65,7 @@ def traced_method(wrapped, instance, args, kwargs): with tracer.start_as_current_span( APIS["IMAGES_GENERATION"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) as span: set_span_attributes(span, attributes) @@ -118,7 +118,7 @@ async def traced_method(wrapped, instance, args, kwargs): span_attributes = { **get_langtrace_attributes(version, service_provider, vendor_type="llm"), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="images_generate"), **get_llm_url(instance), SpanAttributes.LLM_PATH: APIS["IMAGES_GENERATION"]["ENDPOINT"], **get_extra_attributes(), @@ -128,7 +128,7 @@ async def traced_method(wrapped, instance, args, kwargs): with tracer.start_as_current_span( APIS["IMAGES_GENERATION"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) as span: set_span_attributes(span, attributes) @@ -181,7 +181,7 @@ def traced_method(wrapped, instance, args, kwargs): span_attributes = { **get_langtrace_attributes(version, service_provider, vendor_type="llm"), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="images_edit"), **get_llm_url(instance), SpanAttributes.LLM_PATH: APIS["IMAGES_EDIT"]["ENDPOINT"], SpanAttributes.LLM_RESPONSE_FORMAT: kwargs.get("response_format"), @@ -193,7 +193,7 @@ def traced_method(wrapped, instance, args, kwargs): with tracer.start_as_current_span( APIS["IMAGES_EDIT"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) as span: set_span_attributes(span, attributes) @@ -283,7 +283,7 @@ def traced_method(wrapped, instance, args, kwargs): span = tracer.start_span( APIS["CHAT_COMPLETION"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) _set_input_attributes(span, kwargs, attributes) @@ -377,7 +377,7 @@ async def traced_method(wrapped, instance, args, kwargs): span = tracer.start_span( APIS["CHAT_COMPLETION"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) _set_input_attributes(span, kwargs, attributes) @@ -432,7 +432,7 @@ def traced_method(wrapped, instance, args, kwargs): span_attributes = { **get_langtrace_attributes(version, service_provider, vendor_type="llm"), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="embed"), **get_llm_url(instance), SpanAttributes.LLM_PATH: APIS["EMBEDDINGS_CREATE"]["ENDPOINT"], SpanAttributes.LLM_REQUEST_DIMENSIONS: kwargs.get("dimensions"), @@ -456,7 +456,7 @@ def traced_method(wrapped, instance, args, kwargs): with tracer.start_as_current_span( APIS["EMBEDDINGS_CREATE"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) as span: @@ -490,7 +490,7 @@ async def traced_method(wrapped, instance, args, kwargs): span_attributes = { **get_langtrace_attributes(version, service_provider, vendor_type="llm"), - **get_llm_request_attributes(kwargs), + **get_llm_request_attributes(kwargs, operation_name="embed"), SpanAttributes.LLM_PATH: APIS["EMBEDDINGS_CREATE"]["ENDPOINT"], SpanAttributes.LLM_REQUEST_DIMENSIONS: kwargs.get("dimensions"), **get_extra_attributes(), @@ -513,7 +513,7 @@ async def traced_method(wrapped, instance, args, kwargs): with tracer.start_as_current_span( APIS["EMBEDDINGS_CREATE"]["METHOD"], - kind=SpanKind.CLIENT.value, + kind=SpanKind.CLIENT, context=set_span_in_context(trace.get_current_span()), ) as span: diff --git a/src/langtrace_python_sdk/utils/__init__.py b/src/langtrace_python_sdk/utils/__init__.py index 5f23d227..bcda19ce 100644 --- a/src/langtrace_python_sdk/utils/__init__.py +++ b/src/langtrace_python_sdk/utils/__init__.py @@ -2,23 +2,32 @@ from .sdk_version_checker import SDKVersionChecker from opentelemetry.trace import Span from langtrace.trace_attributes import SpanAttributes +import os def set_span_attribute(span: Span, name, value): if value is not None: if value != "" or value != NOT_GIVEN: if name == SpanAttributes.LLM_PROMPTS: - span.add_event( - name=SpanAttributes.LLM_CONTENT_PROMPT, - attributes={ - SpanAttributes.LLM_PROMPTS: value, - }, - ) + set_event_prompt(span, value) else: span.set_attribute(name, value) return +def set_event_prompt(span: Span, prompt): + enabled = os.environ.get("TRACE_PROMPT_COMPLETION_DATA", "true") + if enabled.lower() == "false": + return + + span.add_event( + name=SpanAttributes.LLM_CONTENT_PROMPT, + attributes={ + SpanAttributes.LLM_PROMPTS: prompt, + }, + ) + + def check_if_sdk_is_outdated(): SDKVersionChecker().check() return diff --git a/src/langtrace_python_sdk/utils/llm.py b/src/langtrace_python_sdk/utils/llm.py index ed29451a..49352ede 100644 --- a/src/langtrace_python_sdk/utils/llm.py +++ b/src/langtrace_python_sdk/utils/llm.py @@ -30,6 +30,7 @@ from opentelemetry import baggage from opentelemetry.trace import Span from opentelemetry.trace.status import StatusCode +import os def estimate_tokens(prompt): @@ -42,6 +43,9 @@ def estimate_tokens(prompt): def set_event_completion_chunk(span: Span, chunk): + enabled = os.environ.get("TRACE_PROMPT_COMPLETION_DATA", "true") + if enabled.lower() == "false": + return span.add_event( name=SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK, attributes={ @@ -88,10 +92,11 @@ def get_langtrace_attributes(version, service_provider, vendor_type="llm"): SpanAttributes.LANGTRACE_SERVICE_VERSION: version, SpanAttributes.LANGTRACE_SERVICE_NAME: service_provider, SpanAttributes.LANGTRACE_SERVICE_TYPE: vendor_type, + SpanAttributes.LLM_SYSTEM: service_provider, } -def get_llm_request_attributes(kwargs, prompts=None, model=None): +def get_llm_request_attributes(kwargs, prompts=None, model=None, operation_name="chat"): user = kwargs.get("user", None) if prompts is None: @@ -110,6 +115,7 @@ def get_llm_request_attributes(kwargs, prompts=None, model=None): top_p = kwargs.get("p", None) or kwargs.get("top_p", None) tools = kwargs.get("tools", None) return { + SpanAttributes.LLM_OPERATION_NAME: operation_name, SpanAttributes.LLM_REQUEST_MODEL: model or kwargs.get("model"), SpanAttributes.LLM_IS_STREAMING: kwargs.get("stream"), SpanAttributes.LLM_REQUEST_TEMPERATURE: kwargs.get("temperature"), @@ -123,6 +129,7 @@ def get_llm_request_attributes(kwargs, prompts=None, model=None): SpanAttributes.LLM_FREQUENCY_PENALTY: kwargs.get("frequency_penalty"), SpanAttributes.LLM_REQUEST_SEED: kwargs.get("seed"), SpanAttributes.LLM_TOOLS: json.dumps(tools) if tools else None, + SpanAttributes.LLM_TOOL_CHOICE: kwargs.get("tool_choice"), SpanAttributes.LLM_REQUEST_LOGPROPS: kwargs.get("logprobs"), SpanAttributes.LLM_REQUEST_LOGITBIAS: kwargs.get("logit_bias"), SpanAttributes.LLM_REQUEST_TOP_LOGPROPS: kwargs.get("top_logprobs"), @@ -200,6 +207,9 @@ def get_tool_calls(item): def set_event_completion(span: Span, result_content): + enabled = os.environ.get("TRACE_PROMPT_COMPLETION_DATA", "true") + if enabled.lower() == "false": + return span.add_event( name=SpanAttributes.LLM_CONTENT_COMPLETION, @@ -349,15 +359,9 @@ def process_chunk(self, chunk): ) self.completion_tokens += token_counts content.append(tool_call.function.arguments) - self.span.add_event( - Event.STREAM_OUTPUT.value, - { - SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: ( - "".join(content) - if len(content) > 0 and content[0] is not None - else "" - ) - }, + set_event_completion_chunk( + self.span, + "".join(content) if len(content) > 0 and content[0] is not None else "", ) if content: self.result_content.append(content[0]) @@ -366,16 +370,11 @@ def process_chunk(self, chunk): token_counts = estimate_tokens(chunk.text) self.completion_tokens += token_counts content = [chunk.text] - self.span.add_event( - Event.STREAM_OUTPUT.value, - { - SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK: ( - "".join(content) - if len(content) > 0 and content[0] is not None - else "" - ) - }, + set_event_completion_chunk( + self.span, + "".join(content) if len(content) > 0 and content[0] is not None else "", ) + if content: self.result_content.append(content[0]) diff --git a/src/langtrace_python_sdk/utils/with_root_span.py b/src/langtrace_python_sdk/utils/with_root_span.py index 79d0bf81..6fcb0279 100644 --- a/src/langtrace_python_sdk/utils/with_root_span.py +++ b/src/langtrace_python_sdk/utils/with_root_span.py @@ -25,6 +25,9 @@ from opentelemetry.trace import SpanKind from opentelemetry.trace.propagation import set_span_in_context +from langtrace_python_sdk.constants.exporter.langtrace_exporter import ( + LANGTRACE_REMOTE_URL, +) from langtrace_python_sdk.constants.instrumentation.common import ( LANGTRACE_ADDITIONAL_SPAN_ATTRIBUTES_KEY, ) @@ -142,7 +145,10 @@ class SendUserFeedback: _langtrace_api_key: str def __init__(self): - self._langtrace_host = os.environ["LANGTRACE_API_HOST"] + self._langtrace_host = os.environ.get("LANGTRACE_API_HOST", LANGTRACE_REMOTE_URL) + # When the host is set to /api/trace, remove the /api/trace + if self._langtrace_host.endswith("/api/trace"): + self._langtrace_host = self._langtrace_host.replace("/api/trace", "") self._langtrace_api_key = os.environ.get("LANGTRACE_API_KEY", None) def evaluate(self, data: EvaluationAPIData) -> None: @@ -155,6 +161,16 @@ def evaluate(self, data: EvaluationAPIData) -> None: print("Set the API key as an environment variable LANGTRACE_API_KEY") print(Fore.RESET) return + + # convert spanId and traceId to hexadecimals + span_hex_number = hex(int(data["spanId"], 10))[2:] # Convert to hex and remove the '0x' prefix + formatted_span_hex_number = span_hex_number.zfill(16) # Pad with zeros to 16 characters + data["spanId"] = f"0x{formatted_span_hex_number}" + + trace_hex_number = hex(int(data["traceId"], 10))[2:] # Convert to hex and remove the '0x' prefix + formatted_trace_hex_number = trace_hex_number.zfill(32) # Pad with zeros to 32 characters + data["traceId"] = f"0x{formatted_trace_hex_number}" + evaluation = self.get_evaluation(data["spanId"]) headers = {"x-api-key": self._langtrace_api_key} if evaluation is not None: diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index b19ee4b7..73b4b053 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "2.2.1" +__version__ = "2.2.9" From 109990a759e16f79f6e40b3a82c93e4387ed2723 Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Mon, 21 Oct 2024 19:52:40 -0700 Subject: [PATCH 05/11] minor --- src/langtrace_python_sdk/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index f7493720..1fe90f6a 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "3.1.3" +__version__ = "3.1.4" From aa3dc2f489d45a31ed005bd0c2496bd01f79276c Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Thu, 31 Oct 2024 08:21:53 -0500 Subject: [PATCH 06/11] switch to http exporter --- src/langtrace_python_sdk/langtrace.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/langtrace_python_sdk/langtrace.py b/src/langtrace_python_sdk/langtrace.py index 9fd86a75..24d08fb1 100644 --- a/src/langtrace_python_sdk/langtrace.py +++ b/src/langtrace_python_sdk/langtrace.py @@ -151,7 +151,7 @@ def get_exporter(config: LangtraceConfig, host: str): headers = get_headers(config) host = f"{host}/api/trace" if host == LANGTRACE_REMOTE_URL else host if "http" in host.lower() or "https" in host.lower(): - return LangTraceExporter(host, config.api_key, config.disable_logging) + return HTTPExporter(endpoint=host, headers=headers) else: return GRPCExporter(endpoint=host, headers=headers) From e86b8e0db1b58e7ea61a7e0ef9da7f7ec75f2899 Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Mon, 20 Jan 2025 13:03:29 -0800 Subject: [PATCH 07/11] add botocore dependency --- pyproject.toml | 1 + src/langtrace_python_sdk/version.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 6820439b..51213654 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -58,6 +58,7 @@ dev = [ "google-cloud-aiplatform", "mistralai", "boto3", + "botocore", "embedchain", "setuptools", ] diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index ca18a157..573ffe70 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "3.3.26" +__version__ = "3.3.27" From feffac27491ba75d8794a8c33cb3ce9e58eb8627 Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Mon, 20 Jan 2025 13:18:18 -0800 Subject: [PATCH 08/11] fix --- pyproject.toml | 5 ++--- src/langtrace_python_sdk/version.py | 2 +- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 51213654..a622630a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -32,6 +32,8 @@ dependencies = [ "transformers>=4.11.3", "sentry-sdk>=2.14.0", "ujson>=5.10.0", + "boto3", + "setuptools", ] requires-python = ">=3.9" @@ -57,10 +59,7 @@ dev = [ "google-generativeai", "google-cloud-aiplatform", "mistralai", - "boto3", - "botocore", "embedchain", - "setuptools", ] test = ["pytest", "pytest-vcr", "pytest-asyncio"] diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index 573ffe70..a283eaac 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "3.3.27" +__version__ = "3.3.28" From 36be566d5f289adce588a793013802ce49d30cf9 Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman Date: Mon, 20 Jan 2025 13:43:57 -0800 Subject: [PATCH 09/11] fix dspy issue for handling sets --- .../instrumentation/dspy/patch.py | 18 +++++------------- src/langtrace_python_sdk/version.py | 2 +- 2 files changed, 6 insertions(+), 14 deletions(-) diff --git a/src/langtrace_python_sdk/instrumentation/dspy/patch.py b/src/langtrace_python_sdk/instrumentation/dspy/patch.py index 65e6ab92..3325bd8b 100644 --- a/src/langtrace_python_sdk/instrumentation/dspy/patch.py +++ b/src/langtrace_python_sdk/instrumentation/dspy/patch.py @@ -1,8 +1,5 @@ import json -import os -import ujson -from colorama import Fore from importlib_metadata import version as v from langtrace.trace_attributes import FrameworkSpanAttributes from opentelemetry import baggage @@ -11,16 +8,11 @@ from langtrace_python_sdk.constants import LANGTRACE_SDK_NAME from langtrace_python_sdk.constants.instrumentation.common import ( - LANGTRACE_ADDITIONAL_SPAN_ATTRIBUTES_KEY, - SERVICE_PROVIDERS, -) + LANGTRACE_ADDITIONAL_SPAN_ATTRIBUTES_KEY, SERVICE_PROVIDERS) from langtrace_python_sdk.utils import set_span_attribute -from langtrace_python_sdk.utils.llm import ( - get_extra_attributes, - get_langtrace_attributes, - get_span_name, - set_span_attributes, -) +from langtrace_python_sdk.utils.llm import (get_extra_attributes, + get_langtrace_attributes, + get_span_name, set_span_attributes) from langtrace_python_sdk.utils.silently_fail import silently_fail @@ -139,7 +131,7 @@ def traced_method(wrapped, instance, args, kwargs): set_span_attribute( span, "dspy.signature.result", - json.dumps(result.toDict()), + json.dumps(result.toDict(), default=lambda x: list(x) if isinstance(x, set) else x), ) span.set_status(Status(StatusCode.OK)) diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index a283eaac..f59616a4 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "3.3.28" +__version__ = "3.3.29" From e080b482e4cf9bdf0ca232864d23c4a1a481cb3b Mon Sep 17 00:00:00 2001 From: Karthik Kalyanaraman <105607645+karthikscale3@users.noreply.github.com> Date: Wed, 22 Jan 2025 14:06:45 -0800 Subject: [PATCH 10/11] Bump trace attributes to 7.1.1 (#464) * bump trace attributes * fix * bump openai version --- pyproject.toml | 4 +- src/langtrace_python_sdk/version.py | 2 +- .../cohere/cassettes/test_cohere_chat.yaml | 176 +++++------ .../cassettes/test_cohere_chat_streaming.yaml | 294 +++++++++--------- .../cohere/cassettes/test_cohere_embed.yaml | 143 ++++----- .../cohere/cassettes/test_cohere_rerank.yaml | 149 ++++----- 6 files changed, 387 insertions(+), 381 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index a622630a..1e840e7b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,7 +18,7 @@ classifiers = [ "Operating System :: OS Independent", ] dependencies = [ - 'trace-attributes==7.1.0', + 'trace-attributes==7.1.1', 'opentelemetry-api>=1.25.0', 'opentelemetry-sdk>=1.25.0', 'opentelemetry-instrumentation>=0.47b0', @@ -40,7 +40,7 @@ requires-python = ">=3.9" [project.optional-dependencies] dev = [ - "openai==1.45.0", + "openai==1.60.0", "anthropic", "chromadb", "qdrant-client", diff --git a/src/langtrace_python_sdk/version.py b/src/langtrace_python_sdk/version.py index f59616a4..cf114b17 100644 --- a/src/langtrace_python_sdk/version.py +++ b/src/langtrace_python_sdk/version.py @@ -1 +1 @@ -__version__ = "3.3.29" +__version__ = "3.3.30" diff --git a/src/tests/cohere/cassettes/test_cohere_chat.yaml b/src/tests/cohere/cassettes/test_cohere_chat.yaml index 9ad94ab4..7e8767b8 100644 --- a/src/tests/cohere/cassettes/test_cohere_chat.yaml +++ b/src/tests/cohere/cassettes/test_cohere_chat.yaml @@ -1,89 +1,91 @@ interactions: -- request: - body: '{"message": "Tell me a story in 3 sentences or less?", "stream": false, - "model": "command", "preamble": "answer like a pirate", "chat_history": [{"role": - "USER", "message": "Who discovered gravity?"}, {"role": "CHATBOT", "message": - "The man who is widely credited with discovering gravity is Sir Isaac Newton"}], - "connectors": [{"id": "web-search"}], "temperature": 0.1}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '370' - content-type: - - application/json - host: - - api.cohere.com - user-agent: - - python-httpx/0.27.0 - x-fern-language: - - Python - x-fern-sdk-name: - - cohere - x-fern-sdk-version: - - 5.5.3 - method: POST - uri: https://api.cohere.com/v1/chat - response: - body: - string: '{"response_id":"6b2a2c29-2cd4-4e79-a05a-db8a6019b757","text":"Argh, - many years ago, a bold explorer named Isaac Newton sat beneath an apple tree - for many hours, contemplating the nature of the universe. 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(also known as simply Washington + or D.C., and officially as the District of Columbia) is the capital of the United + States. 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