version conflicts eh

Author: dmarticus

CHANGELOG.md

@@ -1,7 +1,19 @@
-## 3.15.2 - 2025-02-26
+## 3.18.1 – 2025-03-03
 
 1. Improve quota-limited feature flag logs
 
+## 3.18.0 - 2025-02-28
+
+1. Add support for Azure OpenAI.
+
+## 3.17.0 - 2025-02-27
+
+1. The LangChain handler now captures tools in `$ai_generation` events, in property `$ai_tools`. This allows for displaying tools provided to the LLM call in PostHog UI. Note that support for `$ai_tools` in OpenAI and Anthropic SDKs is coming soon.
+
+## 3.16.0 - 2025-02-26
+
+1. feat: add some platform info to events (#198)
+
 ## 3.15.1 - 2025-02-23
 
 1. Fix async client support for OpenAI.

README.md

@@ -10,8 +10,10 @@ Please see the [Python integration docs](https://posthog.com/docs/integrations/p
 ### Testing Locally
 
 1. Run `python3 -m venv env` (creates virtual environment called "env")
+    * or `uv venv env`
 2. Run `source env/bin/activate` (activates the virtual environment)
 3. Run `python3 -m pip install -e ".[test]"` (installs the package in develop mode, along with test dependencies)
+    * or `uv pip install -e ".[test]"`
 4. Run `make test`
   1. To run a specific test do `pytest -k test_no_api_key`
 

llm_observability_examples.py

@@ -33,11 +33,11 @@ def main_sync():
     groups = {"company": "test_company"}
 
     try:
-        # basic_openai_call(distinct_id, trace_id, properties, groups)
+        basic_openai_call(distinct_id, trace_id, properties, groups)
         # streaming_openai_call(distinct_id, trace_id, properties, groups)
         # embedding_openai_call(distinct_id, trace_id, properties, groups)
         # image_openai_call()
-        beta_openai_call(distinct_id, trace_id, properties, groups)
+        # beta_openai_call(distinct_id, trace_id, properties, groups)
     except Exception as e:
         print("Error during OpenAI call:", str(e))
 
@@ -216,6 +216,6 @@ def beta_openai_call(distinct_id, trace_id, properties, groups):
 # HOW TO RUN:
 # comment out one of these to run the other
 
-# if __name__ == "__main__":
-# main_sync()
-asyncio.run(main_async())
+if __name__ == "__main__":
+    main_sync()
+# asyncio.run(main_async())

posthog/ai/langchain/callbacks.py

@@ -60,6 +60,8 @@ class GenerationMetadata(SpanMetadata):
     """Model parameters of the run: temperature, max_tokens, etc."""
     base_url: Optional[str] = None
     """Base URL of the provider's API used in the run."""
+    tools: Optional[List[Dict[str, Any]]] = None
+    """Tools provided to the model."""
 
 
 RunMetadata = Union[SpanMetadata, GenerationMetadata]
@@ -377,6 +379,8 @@ def _set_llm_metadata(
         generation = GenerationMetadata(name=run_name, input=messages, start_time=time.time(), end_time=None)
         if isinstance(invocation_params, dict):
             generation.model_params = get_model_params(invocation_params)
+            if tools := invocation_params.get("tools"):
+                generation.tools = tools
         if isinstance(metadata, dict):
             if model := metadata.get("ls_model_name"):
                 generation.model = model
@@ -424,7 +428,11 @@ def _pop_run_and_capture_trace_or_span(self, run_id: UUID, parent_run_id: Option
             log.warning(f"Run {run_id} is a generation, but attempted to be captured as a trace or span.")
             return
         self._capture_trace_or_span(
-            trace_id, run_id, run, outputs, self._get_parent_run_id(trace_id, run_id, parent_run_id)
+            trace_id,
+            run_id,
+            run,
+            outputs,
+            self._get_parent_run_id(trace_id, run_id, parent_run_id),
         )
 
     def _capture_trace_or_span(
@@ -465,7 +473,10 @@ def _capture_trace_or_span(
         )
 
     def _pop_run_and_capture_generation(
-        self, run_id: UUID, parent_run_id: Optional[UUID], response: Union[LLMResult, BaseException]
+        self,
+        run_id: UUID,
+        parent_run_id: Optional[UUID],
+        response: Union[LLMResult, BaseException],
     ):
         trace_id = self._get_trace_id(run_id)
         self._pop_parent_of_run(run_id)
@@ -476,7 +487,11 @@ def _pop_run_and_capture_generation(
             log.warning(f"Run {run_id} is not a generation, but attempted to be captured as a generation.")
             return
         self._capture_generation(
-            trace_id, run_id, run, response, self._get_parent_run_id(trace_id, run_id, parent_run_id)
+            trace_id,
+            run_id,
+            run,
+            response,
+            self._get_parent_run_id(trace_id, run_id, parent_run_id),
         )
 
     def _capture_generation(
@@ -500,6 +515,8 @@ def _capture_generation(
             "$ai_latency": run.latency,
             "$ai_base_url": run.base_url,
         }
+        if run.tools:
+            event_properties["$ai_tools"] = run.tools
 
         if isinstance(output, BaseException):
             event_properties["$ai_http_status"] = _get_http_status(output)

posthog/ai/openai/__init__.py

@@ -1,4 +1,5 @@
 from .openai import OpenAI
 from .openai_async import AsyncOpenAI
+from .openai_providers import AsyncAzureOpenAI, AzureOpenAI
 
-__all__ = ["OpenAI", "AsyncOpenAI"]
+__all__ = ["OpenAI", "AsyncOpenAI", "AzureOpenAI", "AsyncAzureOpenAI"]

posthog/ai/openai/openai_providers.py

@@ -0,0 +1,41 @@
+try:
+    import openai
+    import openai.resources
+except ImportError:
+    raise ModuleNotFoundError("Please install the Open AI SDK to use this feature: 'pip install openai'")
+
+from posthog.ai.openai.openai import WrappedBeta, WrappedChat, WrappedEmbeddings
+from posthog.ai.openai.openai_async import WrappedBeta as AsyncWrappedBeta
+from posthog.ai.openai.openai_async import WrappedChat as AsyncWrappedChat
+from posthog.ai.openai.openai_async import WrappedEmbeddings as AsyncWrappedEmbeddings
+from posthog.client import Client as PostHogClient
+
+
+class AzureOpenAI(openai.AzureOpenAI):
+    """
+    A wrapper around the Azure OpenAI SDK that automatically sends LLM usage events to PostHog.
+    """
+
+    _ph_client: PostHogClient
+
+    def __init__(self, posthog_client: PostHogClient, **kwargs):
+        super().__init__(**kwargs)
+        self._ph_client = posthog_client
+        self.chat = WrappedChat(self)
+        self.embeddings = WrappedEmbeddings(self)
+        self.beta = WrappedBeta(self)
+
+
+class AsyncAzureOpenAI(openai.AsyncAzureOpenAI):
+    """
+    A wrapper around the Azure OpenAI SDK that automatically sends LLM usage events to PostHog.
+    """
+
+    _ph_client: PostHogClient
+
+    def __init__(self, posthog_client: PostHogClient, **kwargs):
+        super().__init__(**kwargs)
+        self._ph_client = posthog_client
+        self.chat = AsyncWrappedChat(self)
+        self.embeddings = AsyncWrappedEmbeddings(self)
+        self.beta = AsyncWrappedBeta(self)

posthog/client.py

@@ -2,11 +2,14 @@
 import logging
 import numbers
 import os
+import platform
 import sys
 import warnings
 from datetime import datetime, timedelta
+from typing import Any
 from uuid import UUID, uuid4
 
+import distro  # For Linux OS detection
 from dateutil.tz import tzutc
 from six import string_types
 
@@ -29,6 +32,60 @@
 MAX_DICT_SIZE = 50_000
 
 
+def get_os_info():
+    """
+    Returns standardized OS name and version information.
+    Similar to how user agent parsing works in JS.
+    """
+    os_name = ""
+    os_version = ""
+
+    platform_name = sys.platform
+
+    if platform_name.startswith("win"):
+        os_name = "Windows"
+        if hasattr(platform, "win32_ver"):
+            win_version = platform.win32_ver()[0]
+            if win_version:
+                os_version = win_version
+
+    elif platform_name == "darwin":
+        os_name = "Mac OS X"
+        if hasattr(platform, "mac_ver"):
+            mac_version = platform.mac_ver()[0]
+            if mac_version:
+                os_version = mac_version
+
+    elif platform_name.startswith("linux"):
+        os_name = "Linux"
+        linux_info = distro.info()
+        if linux_info["version"]:
+            os_version = linux_info["version"]
+
+    elif platform_name.startswith("freebsd"):
+        os_name = "FreeBSD"
+        if hasattr(platform, "release"):
+            os_version = platform.release()
+
+    else:
+        os_name = platform_name
+        if hasattr(platform, "release"):
+            os_version = platform.release()
+
+    return os_name, os_version
+
+
+def system_context() -> dict[str, Any]:
+    os_name, os_version = get_os_info()
+
+    return {
+        "$python_runtime": platform.python_implementation(),
+        "$python_version": "%s.%s.%s" % (sys.version_info[:3]),
+        "$os": os_name,
+        "$os_version": os_version,
+    }
+
+
 class Client(object):
     """Create a new PostHog client."""
 
@@ -231,7 +288,8 @@ def capture(
                 stacklevel=2,
             )
 
-        properties = properties or {}
+        properties = {**(properties or {}), **system_context()}
+
         require("distinct_id", distinct_id, ID_TYPES)
         require("properties", properties, dict)
         require("event", event, string_types)

posthog/test/ai/langchain/test_callbacks.py

@@ -1168,6 +1168,61 @@ async def test_async_anthropic_streaming(mock_client):
     assert isinstance(trace_props["$ai_output_state"], AIMessage)
 
 
+def test_metadata_tools(mock_client):
+    callbacks = CallbackHandler(mock_client)
+    run_id = uuid.uuid4()
+    tools = [
+        [
+            {
+                "type": "function",
+                "function": {
+                    "name": "foo",
+                    "description": "The foo.",
+                    "parameters": {
+                        "properties": {
+                            "bar": {
+                                "description": "The bar of foo.",
+                                "type": "string",
+                            },
+                        },
+                        "required": ["query_description", "query_kind"],
+                        "type": "object",
+                        "additionalProperties": False,
+                    },
+                    "strict": True,
+                },
+            }
+        ]
+    ]
+
+    with patch("time.time", return_value=1234567890):
+        callbacks._set_llm_metadata(
+            {"kwargs": {"openai_api_base": "https://us.posthog.com"}},
+            run_id,
+            messages=[{"role": "user", "content": "What's the weather like in SF?"}],
+            invocation_params={"temperature": 0.5, "tools": tools},
+            metadata={"ls_model_name": "hog-mini", "ls_provider": "posthog"},
+            name="test",
+        )
+    expected = GenerationMetadata(
+        model="hog-mini",
+        input=[{"role": "user", "content": "What's the weather like in SF?"}],
+        start_time=1234567890,
+        model_params={"temperature": 0.5},
+        provider="posthog",
+        base_url="https://us.posthog.com",
+        name="test",
+        tools=tools,
+        end_time=None,
+    )
+    assert callbacks._runs[run_id] == expected
+    with patch("time.time", return_value=1234567891):
+        run = callbacks._pop_run_metadata(run_id)
+    expected.end_time = 1234567891
+    assert run == expected
+    assert callbacks._runs == {}
+
+
 def test_tool_calls(mock_client):
     prompt = ChatPromptTemplate.from_messages([("user", "Foo")])
     model = FakeMessagesListChatModel(