Raw output:\n",
- "Large language models are powerful artificial intelligence systems that can generate human-like text. \n",
- "They are trained on vast amounts of data to understand and generate language. \n",
- "These models have the ability to complete sentences, write stories, and even engage in conversations. \n",
+ "Large language models are advanced artificial intelligence systems that can generate human-like text. \n",
+ "They are trained on vast amounts of data to understand and mimic natural language patterns. \n",
+ "These models have the ability to generate coherent and contextually relevant responses to prompts. \n",
"\n",
"
\n"
],
"text/plain": [
"Raw output:\n",
- "Large language models are powerful artificial intelligence systems that can generate human-like text. \n",
- "They are trained on vast amounts of data to understand and generate language. \n",
- "These models have the ability to complete sentences, write stories, and even engage in conversations. \n",
+ "Large language models are advanced artificial intelligence systems that can generate human-like text. \n",
+ "They are trained on vast amounts of data to understand and mimic natural language patterns. \n",
+ "These models have the ability to generate coherent and contextually relevant responses to prompts. \n",
"\n"
]
},
@@ -882,12 +800,12 @@
"data": {
"text/html": [
"
Validated output:\n",
- "LARGE LANGUAGE MODELS ARE POWERFUL ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE HUMAN-LIKE TEXT. \n",
+ "LARGE LANGUAGE MODELS ARE ADVANCED ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE HUMAN-LIKE TEXT. \n",
"
\n"
],
"text/plain": [
"Validated output:\n",
- "LARGE LANGUAGE MODELS ARE POWERFUL ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE HUMAN-LIKE TEXT. \n"
+ "LARGE LANGUAGE MODELS ARE ADVANCED ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE HUMAN-LIKE TEXT. \n"
]
},
"metadata": {},
@@ -919,33 +837,33 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
ValidationOutcome(\n",
- " raw_llm_output='Large language models are advanced artificial intelligence systems that can generate human-like\n",
- "text. \\nThey are trained on vast amounts of data to understand and produce language. \\nThese models have the \n",
- "ability to complete sentences, write stories, and even engage in conversations. \\n',\n",
- " validated_output='LARGE LANGUAGE MODELS ARE ADVANCED ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE \n",
- "HUMAN-LIKE TEXT. ',\n",
+ " call_id='129880225974544',\n",
+ " raw_llm_output=' questions',\n",
+ " validation_summaries=None,\n",
+ " validated_output=' HEY HAVE THE ABILITY TO GENERATE COHERENT AND CONTEXTUALLY RELEVANT RESPONSES TO PROMPTS OR \n",
+ "QUESTIONS',\n",
" reask=None,\n",
- " validation_passed=True,\n",
+ " validation_passed=False,\n",
" error=None\n",
")\n",
"
\n"
],
"text/plain": [
"\u001b[1;35mValidationOutcome\u001b[0m\u001b[1m(\u001b[0m\n",
- " \u001b[33mraw_llm_output\u001b[0m=\u001b[32m'Large language models are advanced artificial intelligence systems that can generate human-like\u001b[0m\n",
- "\u001b[32mtext. \\nThey are trained on vast amounts of data to understand and produce language. \\nThese models have the \u001b[0m\n",
- "\u001b[32mability to complete sentences, write stories, and even engage in conversations. \\n'\u001b[0m,\n",
- " \u001b[33mvalidated_output\u001b[0m=\u001b[32m'LARGE LANGUAGE MODELS ARE ADVANCED ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE \u001b[0m\n",
- "\u001b[32mHUMAN-LIKE TEXT. '\u001b[0m,\n",
+ " \u001b[33mcall_id\u001b[0m=\u001b[32m'129880225974544'\u001b[0m,\n",
+ " \u001b[33mraw_llm_output\u001b[0m=\u001b[32m' questions'\u001b[0m,\n",
+ " \u001b[33mvalidation_summaries\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
+ " \u001b[33mvalidated_output\u001b[0m=\u001b[32m' HEY HAVE THE ABILITY TO GENERATE COHERENT AND CONTEXTUALLY RELEVANT RESPONSES TO PROMPTS OR \u001b[0m\n",
+ "\u001b[32mQUESTIONS'\u001b[0m,\n",
" \u001b[33mreask\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
- " \u001b[33mvalidation_passed\u001b[0m=\u001b[3;92mTrue\u001b[0m,\n",
+ " \u001b[33mvalidation_passed\u001b[0m=\u001b[3;91mFalse\u001b[0m,\n",
" \u001b[33merror\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
"\u001b[1m)\u001b[0m\n"
]
@@ -972,7 +890,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
@@ -980,26 +898,20 @@
"text/html": [
"
Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
" │ │ │ │\n",
" │ │ Generate a short description of large language models. Each new sentence should be on another line. │ │\n",
" │ │ │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭───────────────────────────────────────────── Instructions ──────────────────────────────────────────────╮ │\n",
- " │ │ You are a helpful assistant, expressing yourself through a string. │ │\n",
- " │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
" │ │ No message history. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
- " │ │ Large language models are advanced artificial intelligence systems that can generate human-like text. │ │\n",
- " │ │ They are trained on vast amounts of data to understand and produce language. │ │\n",
- " │ │ These models have the ability to complete sentences, write stories, and even engage in conversations. │ │\n",
+ " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
" │ │ │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
" │ │ 'LARGE LANGUAGE MODELS ARE ADVANCED ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE HUMAN-LIKE TEXT. │ │\n",
- " │ │ ' │ │\n",
+ " │ │ HEY HAVE THE ABILITY TO GENERATE COHERENT AND CONTEXTUALLY RELEVANT RESPONSES TO PROMPTS OR QUESTIONS' │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
"
\n"
@@ -1007,26 +919,20 @@
"text/plain": [
"Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m Prompt \u001b[0m\u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mGenerate a short description of large language models. Each new sentence should be on another line.\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;255;240;242m╭─\u001b[0m\u001b[48;2;255;240;242m────────────────────────────────────────────\u001b[0m\u001b[48;2;255;240;242m Instructions \u001b[0m\u001b[48;2;255;240;242m─────────────────────────────────────────────\u001b[0m\u001b[48;2;255;240;242m─╮\u001b[0m │\n",
- " │ \u001b[48;2;255;240;242m│\u001b[0m\u001b[48;2;255;240;242m \u001b[0m\u001b[48;2;255;240;242mYou are a helpful assistant, expressing yourself through a string.\u001b[0m\u001b[48;2;255;240;242m \u001b[0m\u001b[48;2;255;240;242m \u001b[0m\u001b[48;2;255;240;242m│\u001b[0m │\n",
- " │ \u001b[48;2;255;240;242m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m│\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235mNo message history.\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m│\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m Raw LLM Output \u001b[0m\u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mLarge language models are advanced artificial intelligence systems that can generate human-like text. \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mThey are trained on vast amounts of data to understand and produce language. \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mThese models have the ability to complete sentences, write stories, and even engage in conversations. \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
+ " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'LARGE LANGUAGE MODELS ARE ADVANCED ARTIFICIAL INTELLIGENCE SYSTEMS THAT CAN GENERATE HUMAN-LIKE TEXT. \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mHEY HAVE THE ABILITY TO GENERATE COHERENT AND CONTEXTUALLY RELEVANT RESPONSES TO PROMPTS OR QUESTIONS'\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n"
]
@@ -1064,7 +970,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.8"
+ "version": "3.11.7"
}
},
"nbformat": 4,
diff --git a/docs/concepts/validators.md b/docs/concepts/validators.md
index 9d0cb9ff6..eab1225c7 100644
--- a/docs/concepts/validators.md
+++ b/docs/concepts/validators.md
@@ -15,7 +15,7 @@ Occasionally, validators need additional metadata that is only available during
As an example, the `ExtractedSummarySentencesMatch` validator accepts a `filepaths` property in the metadata dictionary to specify what source files to compare the summary against to ensure similarity. Unlike arguments which are specified at validator initialization, metadata is specified when calling `guard.validate` or `guard.__call__` (this is the `guard()` function).
```python
-guard = Guard.from_rail("my_railspec.rail")
+guard = Guard.for_rail("my_railspec.rail")
outcome = guard(
llm_api=openai.chat.completions.create,
diff --git a/docs/examples/constrained_decoding.ipynb b/docs/examples/constrained_decoding.ipynb
index 12782c093..8805fae26 100644
--- a/docs/examples/constrained_decoding.ipynb
+++ b/docs/examples/constrained_decoding.ipynb
@@ -1,93 +1,93 @@
{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n",
- "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1\u001b[0m\n",
- "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
- "\n",
- "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1\u001b[0m\n",
- "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
- ]
- }
- ],
- "source": [
- "! pip install ipywidgets -q"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "81b91198c45249a2b0a7075d13ebf838",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "model.safetensors: 0%| | 10.5M/2.20G [00:00 \u001b[0m\u001b[32;49m24.1\u001b[0m\n",
+ "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
+ "\n",
+ "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1\u001b[0m\n",
+ "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
+ ]
+ }
+ ],
+ "source": [
+ "! pip install ipywidgets -q"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "81b91198c45249a2b0a7075d13ebf838",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "model.safetensors: 0%| | 10.5M/2.20G [00:00\n",
"\"\"\"\n",
"\n",
- "guard = Guard.from_rail_string(rail_spec)"
+ "guard = Guard.for_rail_string(rail_spec)"
]
},
{
@@ -123,7 +123,7 @@
" age: int\n",
"\n",
"\n",
- "guard = Guard.from_pydantic(Pet)\n",
+ "guard = Guard.for_pydantic(Pet)\n",
"guard.use(TwoWords(on_fail=\"exception\"), on=\"prompt\")\n",
"\n",
"try:\n",
diff --git a/docs/examples/json_function_calling_tools.ipynb b/docs/examples/json_function_calling_tools.ipynb
index 65ecb9d1c..ebb7a8bae 100644
--- a/docs/examples/json_function_calling_tools.ipynb
+++ b/docs/examples/json_function_calling_tools.ipynb
@@ -215,7 +215,7 @@
"class Schedule(BaseModel):\n",
" deliveries: List[Delivery]\n",
"\n",
- "pydantic_guard = Guard.from_pydantic(Schedule)\n",
+ "pydantic_guard = Guard.for_pydantic(Schedule)\n",
"\n",
"# Generate the function calling tool and add it to the list\n",
"pydantic_guard_tools = pydantic_guard.json_function_calling_tool([])\n",
@@ -246,7 +246,7 @@
"\n",
"\"\"\"\n",
"\n",
- "rail_guard = Guard.from_rail_string(rail)\n",
+ "rail_guard = Guard.for_rail_string(rail)\n",
"\n",
"\n",
"# Generate the function calling tool and add it to the list\n",
diff --git a/docs/examples/llamaindex-output-parsing.ipynb b/docs/examples/llamaindex-output-parsing.ipynb
index 80fbfd2aa..e69d30ecc 100644
--- a/docs/examples/llamaindex-output-parsing.ipynb
+++ b/docs/examples/llamaindex-output-parsing.ipynb
@@ -190,8 +190,8 @@
"metadata": {},
"outputs": [],
"source": [
- "# You can either define a RailSpec and initialise a Guard object from_rail_string()\n",
- "# OR define Pydantic classes and initialise a Guard object from_pydantic()\n",
+ "# You can either define a RailSpec and initialise a Guard object for_rail_string()\n",
+ "# OR define Pydantic classes and initialise a Guard object for_pydantic()\n",
"# For more info: https://docs.guardrailsai.com/defining_guards/pydantic/\n",
"# Guardrails recommends Pydantic\n",
"\n",
@@ -237,7 +237,7 @@
"outputs": [],
"source": [
"# Create a guard object\n",
- "guard = gd.Guard.from_pydantic(output_class=BulletPoints, prompt=prompt)\n",
+ "guard = gd.Guard.for_pydantic(output_class=BulletPoints, prompt=prompt)\n",
"\n",
"# Create output parse object\n",
"output_parser = GuardrailsOutputParser(guard, llm=llm_predictor.llm.complete)"
diff --git a/docs/examples/no_secrets_in_generated_text.ipynb b/docs/examples/no_secrets_in_generated_text.ipynb
index 8be7ef687..ec82302c0 100644
--- a/docs/examples/no_secrets_in_generated_text.ipynb
+++ b/docs/examples/no_secrets_in_generated_text.ipynb
@@ -175,7 +175,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -191,7 +191,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_pydantic(output_class=ScrubbedCode)"
+ "guard = gd.Guard.for_pydantic(output_class=ScrubbedCode)"
]
},
{
diff --git a/docs/examples/provenance.ipynb b/docs/examples/provenance.ipynb
index 3297601c0..4d0f8faca 100644
--- a/docs/examples/provenance.ipynb
+++ b/docs/examples/provenance.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
"metadata": {},
"outputs": [
{
@@ -10,13 +10,13 @@
"output_type": "stream",
"text": [
"Installing hub:\u001b[35m/\u001b[0m\u001b[35m/guardrails/\u001b[0m\u001b[95mprovenance_embeddings...\u001b[0m\n",
- "/Users/calebcourier/Projects/gr-mono/guardrails/docs/examples/.venv/lib/python3.12/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/transformers/tokenization_utils_base.py:1617: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be deprecated in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
" warnings.warn(\n",
"✅Successfully installed guardrails/provenance_embeddings!\n",
"\n",
"\n",
"Installing hub:\u001b[35m/\u001b[0m\u001b[35m/guardrails/\u001b[0m\u001b[95mprovenance_llm...\u001b[0m\n",
- "/Users/calebcourier/Projects/gr-mono/guardrails/docs/examples/.venv/lib/python3.12/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/transformers/tokenization_utils_base.py:1617: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be deprecated in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
" warnings.warn(\n",
"✅Successfully installed guardrails/provenance_llm!\n",
"\n",
@@ -76,7 +76,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -288,14 +288,14 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
- "/Users/calebcourier/Projects/gr-mono/guardrails/docs/examples/.venv/lib/python3.12/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py:11: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py:13: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
" from tqdm.autonotebook import tqdm, trange\n"
]
}
@@ -338,16 +338,13 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Initialize the guard object\n",
- "guard = Guard.from_string(\n",
- " validators=[\n",
- " ProvenanceEmbeddings(threshold=0.3, validation_method=\"sentence\", on_fail=\"fix\")\n",
- " ],\n",
- " description=\"testmeout\",\n",
+ "guard = Guard().use(\n",
+ " ProvenanceEmbeddings(threshold=0.3, validation_method=\"sentence\", on_fail=\"fix\")\n",
")"
]
},
@@ -360,28 +357,36 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 5,
"metadata": {},
"outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/guardrails/validator_service/__init__.py:85: UserWarning: Could not obtain an event loop. Falling back to synchronous validation.\n",
+ " warnings.warn(\n"
+ ]
+ },
{
"data": {
"text/html": [
"
Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
" │ │ No prompt │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
" │ │ No message history. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
" │ │ To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits │ │\n",
" │ │ so the cat doesn’t feel cornered. Find the right litterbox for your cat, as well as the right litter. │ │\n",
" │ │ Place the litterbox in a good spot, away from heavily trafficked and noisy areas. Keep the litterbox │ │\n",
" │ │ very clean, and do not punish the cat or confine her to just one room. Once training is complete, it is │ │\n",
" │ │ important to clean the litter box regularly and to provide a safe and healthy environment for the cat. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
" │ │ 'To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits │ │\n",
" │ │ so the cat doesn’t feel cornered.\\nFind the right litterbox for your cat, as well as the right │ │\n",
" │ │ litter.\\nKeep the litterbox very clean, and do not punish the cat or confine her to just one │ │\n",
@@ -394,20 +399,20 @@
"text/plain": [
"Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m Prompt \u001b[0m\u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mNo prompt\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m│\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235mNo message history.\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m│\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m Raw LLM Output \u001b[0m\u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mTo retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mso the cat doesn’t feel cornered. Find the right litterbox for your cat, as well as the right litter. \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mPlace the litterbox in a good spot, away from heavily trafficked and noisy areas. Keep the litterbox \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mvery clean, and do not punish the cat or confine her to just one room. Once training is complete, it is\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mimportant to clean the litter box regularly and to provide a safe and healthy environment for the cat.\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mso the cat doesn’t feel cornered.\\nFind the right litterbox for your cat, as well as the right \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mlitter.\\nKeep the litterbox very clean, and do not punish the cat or confine her to just one \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
@@ -417,7 +422,7 @@
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n"
]
},
- "execution_count": 7,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@@ -442,7 +447,7 @@
},
{
"cell_type": "code",
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+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -450,17 +455,17 @@
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Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
" │ │ No prompt │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
" │ │ No message history. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
" │ │ Cats love lollipops and other sweet and sour foods. Cats can be retrained to use a litter box. Reward │ │\n",
" │ │ them when they do with lots of candy. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
" │ │ 'Cats can be retrained to use a litter box.' │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
@@ -469,23 +474,23 @@
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+ " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
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- " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
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+ " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mCats love lollipops and other sweet and sour foods. Cats can be retrained to use a litter box. Reward \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mthem when they do with lots of candy.\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'Cats can be retrained to use a litter box.'\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n"
]
},
- "execution_count": 8,
+ "execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
@@ -524,14 +529,14 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Initialize the guard object\n",
"from guardrails.hub import ProvenanceLLM\n",
"\n",
- "guard_1 = Guard.from_string(\n",
+ "guard_1 = Guard.for_string(\n",
" validators=[\n",
" ProvenanceLLM(\n",
" validation_method=\"sentence\", # can be \"sentence\" or \"full\"\n",
@@ -546,7 +551,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -554,25 +559,25 @@
"text/html": [
"
Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
" │ │ No prompt │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
" │ │ No message history. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
" │ │ To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits │ │\n",
" │ │ so the cat doesn’t feel cornered. Find the right litterbox for your cat, as well as the right litter. │ │\n",
" │ │ Place the litterbox in a good spot, away from heavily trafficked and noisy areas. Keep the litterbox │ │\n",
" │ │ very clean, and do not punish the cat or confine her to just one room. Once training is complete, it is │ │\n",
" │ │ important to clean the litter box regularly and to provide a safe and healthy environment for the cat. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
- " │ │ To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits │ │\n",
- " │ │ so the cat doesn’t feel cornered. Find the right litterbox for your cat, as well as the right litter. │ │\n",
- " │ │ Place the litterbox in a good spot, away from heavily trafficked and noisy areas. Keep the litterbox │ │\n",
- " │ │ very clean, and do not punish the cat or confine her to just one room. Once training is complete, it is │ │\n",
- " │ │ important to clean the litter box regularly and to provide a safe and healthy environment for the cat. │ │\n",
+ " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ " │ │ 'To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits │ │\n",
+ " │ │ so the cat doesn’t feel cornered.\\nFind the right litterbox for your cat, as well as the right │ │\n",
+ " │ │ litter.\\nPlace the litterbox in a good spot, away from heavily trafficked and noisy areas.\\nOnce │ │\n",
+ " │ │ training is complete, it is important to clean the litter box regularly and to provide a safe and │ │\n",
+ " │ │ healthy environment for the cat.' │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
"
\n"
@@ -580,30 +585,30 @@
"text/plain": [
"Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m Prompt \u001b[0m\u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mNo prompt\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m│\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235mNo message history.\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m│\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m Raw LLM Output \u001b[0m\u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mTo retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mso the cat doesn’t feel cornered. Find the right litterbox for your cat, as well as the right litter. \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mPlace the litterbox in a good spot, away from heavily trafficked and noisy areas. Keep the litterbox \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mvery clean, and do not punish the cat or confine her to just one room. Once training is complete, it is\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mimportant to clean the litter box regularly and to provide a safe and healthy environment for the cat.\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mTo retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mso the cat doesn’t feel cornered. Find the right litterbox for your cat, as well as the right litter. \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mPlace the litterbox in a good spot, away from heavily trafficked and noisy areas. Keep the litterbox \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mvery clean, and do not punish the cat or confine her to just one room. Once training is complete, it is\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mimportant to clean the litter box regularly and to provide a safe and healthy environment for the cat.\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'To retrain a cat to use the litter box, put its litter box in a low traffic area with at least 2 exits\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mso the cat doesn’t feel cornered.\\nFind the right litterbox for your cat, as well as the right \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mlitter.\\nPlace the litterbox in a good spot, away from heavily trafficked and noisy areas.\\nOnce \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mtraining is complete, it is important to clean the litter box regularly and to provide a safe and \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mhealthy environment for the cat.'\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n"
]
},
- "execution_count": 10,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -622,7 +627,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
@@ -630,17 +635,17 @@
"text/html": [
"
Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
" │ │ No prompt │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
" │ │ No message history. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
" │ │ Cats love lollipops and other sweet and sour foods. Cats can be retrained to use a litter box. Reward │ │\n",
" │ │ them when they do with lots of candy. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
" │ │ 'Cats can be retrained to use a litter box.' │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
@@ -649,23 +654,23 @@
"text/plain": [
"Logs\n",
"└── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m Prompt \u001b[0m\u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mNo prompt\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m│\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235mNo message history.\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m│\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m Raw LLM Output \u001b[0m\u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mCats love lollipops and other sweet and sour foods. Cats can be retrained to use a litter box. Reward \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220mthem when they do with lots of candy.\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'Cats can be retrained to use a litter box.'\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n"
]
},
- "execution_count": 11,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -705,7 +710,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.3"
+ "version": "3.11.7"
},
"orig_nbformat": 4
},
diff --git a/docs/examples/recipe_generation.ipynb b/docs/examples/recipe_generation.ipynb
index 1b62610bd..286888aba 100644
--- a/docs/examples/recipe_generation.ipynb
+++ b/docs/examples/recipe_generation.ipynb
@@ -201,7 +201,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -230,7 +230,7 @@
}
],
"source": [
- "guard = gd.Guard.from_pydantic(output_class=Recipe)"
+ "guard = gd.Guard.for_pydantic(output_class=Recipe)"
]
},
{
diff --git a/docs/examples/regex_validation.ipynb b/docs/examples/regex_validation.ipynb
index 4b5c598bb..6ab79b98d 100644
--- a/docs/examples/regex_validation.ipynb
+++ b/docs/examples/regex_validation.ipynb
@@ -58,7 +58,16 @@
"cell_type": "code",
"execution_count": 3,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py:13: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
+ " from tqdm.autonotebook import tqdm, trange\n"
+ ]
+ }
+ ],
"source": [
"from guardrails import Guard\n",
"from guardrails.hub import RegexMatch\n",
@@ -80,32 +89,40 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 4,
"metadata": {},
"outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/guardrails/validator_service/__init__.py:85: UserWarning: Could not obtain an event loop. Falling back to synchronous validation.\n",
+ " warnings.warn(\n"
+ ]
+ },
{
"data": {
"text/html": [
"
Logs\n",
"├── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- "│ │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ "│ │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
"│ │ │ I am writing a movie and need a fake phone number. Generate a fake phone number. Do not write anything │ │\n",
"│ │ │ other than the phone number. │ │\n",
"│ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- "│ │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ "│ │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
"│ │ │ No message history. │ │\n",
"│ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- "│ │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
+ "│ │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
"│ │ │ (555) 012-3456 │ │\n",
"│ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- "│ │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ "│ │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
"│ │ │ FieldReAsk( │ │\n",
"│ │ │ incorrect_value='(555) 012-3456', │ │\n",
"│ │ │ fail_results=[ │ │\n",
"│ │ │ FailResult( │ │\n",
"│ │ │ outcome='fail', │ │\n",
"│ │ │ error_message='Result must match \\\\d{3}-\\\\d{3}-\\\\d{4}', │ │\n",
- "│ │ │ fix_value='ah300-632-4603ah', │ │\n",
+ "│ │ │ fix_value='sh406-649-2143sh', │ │\n",
"│ │ │ error_spans=None, │ │\n",
"│ │ │ metadata=None, │ │\n",
"│ │ │ validated_chunk=None │ │\n",
@@ -117,7 +134,7 @@
"│ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
"│ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
"└── ╭────────────────────────────────────────────────── Step 1 ───────────────────────────────────────────────────╮\n",
- " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────────── Prompt ─────────────────────────────────────────────────╮ │\n",
" │ │ This was a previous response you generated: │ │\n",
" │ │ │ │\n",
" │ │ ====== │ │\n",
@@ -135,13 +152,13 @@
" │ │ Don't talk; just go. │ │\n",
" │ │ │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Message History ────────────────────────────────────────────╮ │\n",
" │ │ No message history. │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
+ " │ ╭──────────────────────────────────────────── Raw LLM Output ─────────────────────────────────────────────╮ │\n",
" │ │ 555-012-3456 │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
- " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
+ " │ ╭─────────────────────────────────────────── Validated Output ────────────────────────────────────────────╮ │\n",
" │ │ '555-012-3456' │ │\n",
" │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
@@ -150,24 +167,24 @@
"text/plain": [
"Logs\n",
"├── ╭────────────────────────────────────────────────── Step 0 ───────────────────────────────────────────────────╮\n",
- "│ │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m Prompt \u001b[0m\u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
+ "│ │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
"│ │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mI am writing a movie and need a fake phone number. Generate a fake phone number. Do not write anything \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mother than the phone number.\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;248;255m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- "│ │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ "│ │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
"│ │ \u001b[48;2;231;223;235m│\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235mNo message history.\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m│\u001b[0m │\n",
"│ │ \u001b[48;2;231;223;235m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- "│ │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m Raw LLM Output \u001b[0m\u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
+ "│ │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
"│ │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m(555) 012-3456\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
"│ │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- "│ │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ "│ │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240mFieldReAsk(\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m incorrect_value='(555) 012-3456',\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m fail_results=[\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m FailResult(\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m outcome='fail',\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m error_message='Result must match \\\\d{3}-\\\\d{3}-\\\\d{4}',\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
- "│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m fix_value='ah300-632-4603ah',\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
+ "│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m fix_value='sh406-649-2143sh',\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m error_spans=None,\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m metadata=None,\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
"│ │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m validated_chunk=None\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
@@ -179,7 +196,7 @@
"│ │ \u001b[48;2;240;255;240m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
"│ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
"└── ╭────────────────────────────────────────────────── Step 1 ───────────────────────────────────────────────────╮\n",
- " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m Prompt \u001b[0m\u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;248;255m╭─\u001b[0m\u001b[48;2;240;248;255m───────────────────────────────────────────────\u001b[0m Prompt \u001b[48;2;240;248;255m────────────────────────────────────────────────\u001b[0m\u001b[48;2;240;248;255m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mThis was a previous response you generated:\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m======\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
@@ -197,13 +214,13 @@
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255mDon't talk; just go.\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m│\u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m \u001b[0m\u001b[48;2;240;248;255m│\u001b[0m │\n",
" │ \u001b[48;2;240;248;255m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m Message History \u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;231;223;235m╭─\u001b[0m\u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m Message History \u001b[48;2;231;223;235m───────────────────────────────────────────\u001b[0m\u001b[48;2;231;223;235m─╮\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m│\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235mNo message history.\u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m \u001b[0m\u001b[48;2;231;223;235m│\u001b[0m │\n",
" │ \u001b[48;2;231;223;235m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m Raw LLM Output \u001b[0m\u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;245;245;220m╭─\u001b[0m\u001b[48;2;245;245;220m───────────────────────────────────────────\u001b[0m Raw LLM Output \u001b[48;2;245;245;220m────────────────────────────────────────────\u001b[0m\u001b[48;2;245;245;220m─╮\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m│\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m555-012-3456\u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m \u001b[0m\u001b[48;2;245;245;220m│\u001b[0m │\n",
" │ \u001b[48;2;245;245;220m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
- " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m Validated Output \u001b[0m\u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
+ " │ \u001b[48;2;240;255;240m╭─\u001b[0m\u001b[48;2;240;255;240m──────────────────────────────────────────\u001b[0m Validated Output \u001b[48;2;240;255;240m───────────────────────────────────────────\u001b[0m\u001b[48;2;240;255;240m─╮\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m│\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m'555-012-3456'\u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m \u001b[0m\u001b[48;2;240;255;240m│\u001b[0m │\n",
" │ \u001b[48;2;240;255;240m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m │\n",
" ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n"
@@ -214,7 +231,7 @@
}
],
"source": [
- "guard = Guard.from_string(\n",
+ "guard = Guard.for_string(\n",
" validators=[RegexMatch(regex=regex, match_type='search', on_fail='reask')]\n",
")\n",
"\n",
@@ -243,7 +260,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.1"
+ "version": "3.11.7"
},
"orig_nbformat": 4
},
diff --git a/docs/examples/response_is_on_topic.ipynb b/docs/examples/response_is_on_topic.ipynb
index 2432c508d..627457f25 100644
--- a/docs/examples/response_is_on_topic.ipynb
+++ b/docs/examples/response_is_on_topic.ipynb
@@ -58,7 +58,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -136,14 +136,24 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 5,
"metadata": {},
"outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py:13: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
+ " from tqdm.autonotebook import tqdm, trange\n",
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/guardrails/validator_service/__init__.py:85: UserWarning: Could not obtain an event loop. Falling back to synchronous validation.\n",
+ " warnings.warn(\n"
+ ]
+ },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Validation failed for field with errors: Invalid topics found: ['tablet', 'phone', 'computer']\n"
+ "Validation failed for field with errors: Invalid topics found: ['tablet', 'computer', 'phone']\n"
]
}
],
@@ -153,7 +163,7 @@
"from guardrails.errors import ValidationError\n",
"\n",
"# Create the Guard with the OnTopic Validator\n",
- "guard = gd.Guard.from_string(\n",
+ "guard = gd.Guard.for_string(\n",
" validators=[\n",
" RestrictToTopic(\n",
" valid_topics=valid_topics,\n",
@@ -187,7 +197,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -233,7 +243,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
@@ -246,7 +256,7 @@
],
"source": [
"# Create the Guard with the OnTopic Validator\n",
- "guard = gd.Guard.from_string(\n",
+ "guard = gd.Guard.for_string(\n",
" validators=[\n",
" RestrictToTopic(\n",
" valid_topics=valid_topics,\n",
@@ -285,7 +295,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.1"
+ "version": "3.11.7"
}
},
"nbformat": 4,
diff --git a/docs/examples/secrets_detection.ipynb b/docs/examples/secrets_detection.ipynb
index 738ea8a18..fe2467ee6 100644
--- a/docs/examples/secrets_detection.ipynb
+++ b/docs/examples/secrets_detection.ipynb
@@ -41,7 +41,7 @@
"output_type": "stream",
"text": [
"\n",
- "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1.1\u001b[0m\n",
+ "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.2\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
]
}
@@ -55,7 +55,16 @@
"cell_type": "code",
"execution_count": 3,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py:13: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
+ " from tqdm.autonotebook import tqdm, trange\n"
+ ]
+ }
+ ],
"source": [
"# Import the guardrails package\n",
"# and import the SecretsPresent validator\n",
@@ -75,7 +84,7 @@
"# Here, we'll specify that we want to fix\n",
"# if the validator detects secrets\n",
"\n",
- "guard = gd.Guard.from_string(\n",
+ "guard = gd.Guard.for_string(\n",
" validators=[SecretsPresent(on_fail=\"fix\")],\n",
" description=\"testmeout\",\n",
")"
@@ -86,6 +95,14 @@
"execution_count": 5,
"metadata": {},
"outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/zayd/workspace/guardrails/docs/.venv/lib/python3.11/site-packages/guardrails/validator_service/__init__.py:85: UserWarning: Could not obtain an event loop. Falling back to synchronous validation.\n",
+ " warnings.warn(\n"
+ ]
+ },
{
"data": {
"text/html": [
@@ -239,7 +256,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.1"
+ "version": "3.11.7"
}
},
"nbformat": 4,
diff --git a/docs/examples/select_choice_based_on_action.ipynb b/docs/examples/select_choice_based_on_action.ipynb
index 17a106318..b77107ecf 100644
--- a/docs/examples/select_choice_based_on_action.ipynb
+++ b/docs/examples/select_choice_based_on_action.ipynb
@@ -171,7 +171,7 @@
"\n",
"from rich import print\n",
"\n",
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -191,7 +191,7 @@
"\n",
"from rich import print\n",
"\n",
- "guard = gd.Guard.from_pydantic(output_class=FightOrFlight)"
+ "guard = gd.Guard.for_pydantic(output_class=FightOrFlight)"
]
},
{
diff --git a/docs/examples/summarizer.ipynb b/docs/examples/summarizer.ipynb
index 24c40eb17..d71565f9a 100644
--- a/docs/examples/summarizer.ipynb
+++ b/docs/examples/summarizer.ipynb
@@ -132,7 +132,7 @@
"import guardrails as gd\n",
"from guardrails.errors import ValidationError\n",
"\n",
- "guard = gd.Guard().from_pydantic(TextSummary)"
+ "guard = gd.Guard().for_pydantic(TextSummary)"
]
},
{
diff --git a/docs/examples/syntax_error_free_sql.ipynb b/docs/examples/syntax_error_free_sql.ipynb
index b8a944a79..4cf763b78 100644
--- a/docs/examples/syntax_error_free_sql.ipynb
+++ b/docs/examples/syntax_error_free_sql.ipynb
@@ -199,7 +199,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -215,7 +215,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_pydantic(output_class=ValidSql)"
+ "guard = gd.Guard.for_pydantic(output_class=ValidSql)"
]
},
{
diff --git a/docs/examples/text_summarization_quality.ipynb b/docs/examples/text_summarization_quality.ipynb
index 0daf1f509..38b4bd8f4 100644
--- a/docs/examples/text_summarization_quality.ipynb
+++ b/docs/examples/text_summarization_quality.ipynb
@@ -197,7 +197,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -213,7 +213,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_pydantic(output_class=DocumentSummary)"
+ "guard = gd.Guard.for_pydantic(output_class=DocumentSummary)"
]
},
{
diff --git a/docs/examples/translation_to_specific_language.ipynb b/docs/examples/translation_to_specific_language.ipynb
index 26f3a345d..6847296ed 100644
--- a/docs/examples/translation_to_specific_language.ipynb
+++ b/docs/examples/translation_to_specific_language.ipynb
@@ -214,7 +214,7 @@
},
"outputs": [],
"source": [
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -230,7 +230,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_pydantic(output_class=Translation)"
+ "guard = gd.Guard.for_pydantic(output_class=Translation)"
]
},
{
diff --git a/docs/examples/valid_chess_moves.ipynb b/docs/examples/valid_chess_moves.ipynb
index 40a7880b5..194f8c0e8 100644
--- a/docs/examples/valid_chess_moves.ipynb
+++ b/docs/examples/valid_chess_moves.ipynb
@@ -184,7 +184,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_rail_string(rail_str)"
+ "guard = gd.Guard.for_rail_string(rail_str)"
]
},
{
@@ -200,7 +200,7 @@
"metadata": {},
"outputs": [],
"source": [
- "guard = gd.Guard.from_pydantic(output_class=ChessMove)"
+ "guard = gd.Guard.for_pydantic(output_class=ChessMove)"
]
},
{
diff --git a/docs/examples/value_within_distribution.ipynb b/docs/examples/value_within_distribution.ipynb
index 8f3730e7c..58ab87f6b 100644
--- a/docs/examples/value_within_distribution.ipynb
+++ b/docs/examples/value_within_distribution.ipynb
@@ -62,7 +62,7 @@
"class MyModel(BaseModel):\n",
" value: int = Field(validators=[SimilarToPreviousValues(standard_deviations=2, threshold=0.8, on_fail=\"fix\")])\n",
"\n",
- "guard = Guard.from_pydantic(MyModel)"
+ "guard = Guard.for_pydantic(MyModel)"
]
},
{
diff --git a/docs/getting_started/quickstart.md b/docs/getting_started/quickstart.md
index 359bb4958..c29a5ed49 100644
--- a/docs/getting_started/quickstart.md
+++ b/docs/getting_started/quickstart.md
@@ -106,7 +106,7 @@ prompt = """
${gr.complete_json_suffix_v2}
"""
-guard = Guard.from_pydantic(output_class=Pet)
+guard = Guard.for_pydantic(output_class=Pet)
res = guard(
model="gpt-3.5-turbo",
diff --git a/docs/guardrails_ai/getting_started.md b/docs/guardrails_ai/getting_started.md
index 4c6cbb621..cdfa53f7c 100644
--- a/docs/guardrails_ai/getting_started.md
+++ b/docs/guardrails_ai/getting_started.md
@@ -84,7 +84,7 @@ prompt = """
${gr.complete_xml_suffix_v2}
"""
-guard = Guard.from_pydantic(output_class=Pet)
+guard = Guard.for_pydantic(output_class=Pet)
res = guard(
messages=[{"role": "user", "content": prompt}],
diff --git a/docs/how_to_guides/custom_validators.md b/docs/how_to_guides/custom_validators.md
index 5c5446605..141d530d8 100644
--- a/docs/how_to_guides/custom_validators.md
+++ b/docs/how_to_guides/custom_validators.md
@@ -286,7 +286,7 @@ class MyModel(BaseModel):
a_string: Field(validators=[toxic_words()])
custom_string: Field(validators=[ToxicLanguage(threshold=0.8)])
-guard = Guard.from_pydantic(MyModel)
+guard = Guard.for_pydantic(MyModel)
```
### RAIL Example
diff --git a/docs/how_to_guides/generate_structured_data.md b/docs/how_to_guides/generate_structured_data.md
index a3447f239..38147189e 100644
--- a/docs/how_to_guides/generate_structured_data.md
+++ b/docs/how_to_guides/generate_structured_data.md
@@ -29,7 +29,7 @@ class Delivery(BaseModel):
class Schedule(BaseModel):
deliveries: List[Delivery]
-guard = Guard.from_pydantic(Schedule)
+guard = Guard.for_pydantic(Schedule)
chat_history="""
nelson and murdock: i need a pickup 797 9th Avenue, manila envelope, June 3 10:00am with dropoff 10:30am Courthouse, 61 Center Street C/O frank james
operator: quote - $23.00
@@ -101,7 +101,7 @@ response = guard(
For Hugging Face models structured JSON output maybe returned utilizing constrained decoding. Constrained decoding is a technique that allows you to guide the model to generate a specific type of output, a little bit like JSON ad-libs. Learn more about constrained decoding [here](https://www.guardrailsai.com/blog/json-with-open-source-models).
```python
-g = Guard.from_pydantic(NewFriends, output_formatter="jsonformer")
+g = Guard.for_pydantic(NewFriends, output_formatter="jsonformer")
# JSONFormer is only compatible with HF Pipelines and HF Models:
from transformers import pipeline
diff --git a/docs/how_to_guides/rail.md b/docs/how_to_guides/rail.md
index 3024a211c..68d4db21f 100644
--- a/docs/how_to_guides/rail.md
+++ b/docs/how_to_guides/rail.md
@@ -97,7 +97,7 @@ After creating a `RAIL` specification, you can use it to get corrected output fr
import guardrails as gd
# Create a Guard object
-guard = gd.Guard.from_rail('path/to/rail/spec.xml') # (1)!
+guard = gd.Guard.for_rail('path/to/rail/spec.xml') # (1)!
_, validated_output, *rest = guard(
openai.Completion.create, # (2)!
**prompt_args,
diff --git a/docs/how_to_guides/structured_data_with_guardrails.mdx b/docs/how_to_guides/structured_data_with_guardrails.mdx
index f7559deb6..3be84bc6c 100644
--- a/docs/how_to_guides/structured_data_with_guardrails.mdx
+++ b/docs/how_to_guides/structured_data_with_guardrails.mdx
@@ -33,7 +33,7 @@ Below is the syntax for generating structured data with Guardrails AI using `Pyd
```python
from guardrails import Guard
- guard = Guard.from_pydantic(Person)
+ guard = Guard.for_pydantic(Person)
```
Finally, call the LLM of your choice with the `guard` object to generate structured data.
@@ -62,7 +62,7 @@ Below is the syntax for generating structured data with Guardrails AI using `Pyd
```python
from guardrails import Guard
- guard = Guard.from_rail_string("""
+ guard = Guard.for_rail_string("""
"""
- guard = Guard.from_rail_string(rail_spec)
+ guard = Guard.for_rail_string(rail_spec)
# If raises is True, then the test should raise an exception.
# For our existing test cases this will always be a ValidationError
@@ -117,7 +117,7 @@ class Flight(BaseModel):
class Choice(BaseModel):
choice: Union[Fight, Flight] = Field(..., discriminator="action")
- guard = Guard.from_pydantic(output_class=Choice, prompt="Dummy prompt.")
+ guard = Guard.for_pydantic(output_class=Choice, prompt="Dummy prompt.")
# If raises is True, then the test should raise an exception.
# For our existing test cases this will always be a ValidationError
diff --git a/tests/integration_tests/test_datatypes.py b/tests/integration_tests/test_datatypes.py
index 05a842ca0..2be91e67b 100644
--- a/tests/integration_tests/test_datatypes.py
+++ b/tests/integration_tests/test_datatypes.py
@@ -21,7 +21,7 @@ def test_passed_date_format():
"""
- guard = Guard.from_rail_string(rail_spec)
+ guard = Guard.for_rail_string(rail_spec)
guard.parse(llm_output='{"name": "John Doe", "dob": "2021-01-01"}', num_reasks=0)
@@ -50,7 +50,7 @@ def test_defaulted_date_parser(date_string: str):
"""
- guard = Guard.from_rail_string(rail_spec)
+ guard = Guard.for_rail_string(rail_spec)
# This should not raise an exception
guard.parse(
llm_output='{"name": "John Doe", "dob": "' + date_string + '"}', num_reasks=0
@@ -86,7 +86,7 @@ def test_defaulted_date_parser_unsupported_values(
"""
- guard = Guard.from_rail_string(rail_spec)
+ guard = Guard.for_rail_string(rail_spec)
with pytest.raises(Exception) as excinfo:
guard.parse(
llm_output='{"name": "John Doe", "dob": "' + date_string + '"}',
diff --git a/tests/integration_tests/test_formatters.py b/tests/integration_tests/test_formatters.py
index 48f9628b8..90cb3009a 100644
--- a/tests/integration_tests/test_formatters.py
+++ b/tests/integration_tests/test_formatters.py
@@ -24,7 +24,7 @@ class Foo(BaseModel):
bar: str
bez: List[str]
- g = Guard.from_pydantic(Foo, output_formatter="jsonformer")
+ g = Guard.for_pydantic(Foo, output_formatter="jsonformer")
response = g(model.generate, tokenizer=tokenizer, prompt="test")
validated_output = response.validated_output
assert isinstance(validated_output, dict)
@@ -44,7 +44,7 @@ class Foo(BaseModel):
bar: str
bez: List[str]
- g = Guard.from_pydantic(Foo, output_formatter="jsonformer")
+ g = Guard.for_pydantic(Foo, output_formatter="jsonformer")
response = g(model, prompt="Sample:")
validated_output = response.validated_output
assert isinstance(validated_output, dict)
@@ -68,7 +68,7 @@ class MultiNum(BaseModel):
class Tricky(BaseModel):
foo: MultiNum
- g = Guard.from_pydantic(Tricky, output_formatter="jsonformer")
+ g = Guard.for_pydantic(Tricky, output_formatter="jsonformer")
response = g(model, prompt="Sample:")
out = response.validated_output
assert isinstance(out, dict)
diff --git a/tests/integration_tests/test_guard.py b/tests/integration_tests/test_guard.py
index 4038ae18d..86a258cdb 100644
--- a/tests/integration_tests/test_guard.py
+++ b/tests/integration_tests/test_guard.py
@@ -110,14 +110,14 @@ def guard_initializer(
"""Helper function to initialize a Guard using the correct method."""
if isinstance(rail, str):
- return Guard.from_rail_string(rail)
+ return Guard.for_rail_string(rail)
else:
- return Guard.from_pydantic(rail, prompt=prompt, instructions=instructions)
+ return Guard.for_pydantic(rail, prompt=prompt, instructions=instructions)
'''def test_rail_spec_output_parse(rail_spec, llm_output, validated_output):
"""Test that the rail_spec fixture is working."""
- guard = gd.Guard.from_rail_string(rail_spec)
+ guard = gd.Guard.for_rail_string(rail_spec)
assert guard.parse(llm_output) == validated_output'''
@@ -455,7 +455,7 @@ def test_entity_extraction_with_fix_chat_models(mocker, rail, prompt, instructio
"guardrails.llm_providers.openai_wrapper", new=openai_completion_create
)
- guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_LIST)
+ guard = gd.Guard.for_rail_string(string.RAIL_SPEC_FOR_LIST)
_, final_output, *rest = guard(
llm_api=openai.completions.create,
num_reasks=1,
@@ -566,7 +566,7 @@ def test_entity_extraction_with_reask_with_optional_prompts(
mock_openai_invoke_llm.side_effect = llm_return_values
content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
- guard = Guard.from_rail_string(rail)
+ guard = Guard.for_rail_string(rail)
final_output = guard(
llm_api=llm_api,
@@ -662,7 +662,7 @@ def test_skeleton_reask(mocker):
)
content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
- guard = gd.Guard.from_rail_string(
+ guard = gd.Guard.for_rail_string(
entity_extraction.RAIL_SPEC_WITH_SKELETON_REASK
)
final_output = guard(
@@ -708,7 +708,7 @@ def test_string_with_message_history_reask(mocker):
new=MockOpenAIChatCallable,
)
- guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_MSG_HISTORY)
+ guard = gd.Guard.for_rail_string(string.RAIL_SPEC_FOR_MSG_HISTORY)
final_output = guard(
llm_api=openai.chat.completions.create,
msg_history=string.MOVIE_MSG_HISTORY,
@@ -764,7 +764,7 @@ def test_pydantic_with_message_history_reask(mocker):
},
)
- guard = gd.Guard.from_pydantic(output_class=pydantic.WITH_MSG_HISTORY)
+ guard = gd.Guard.for_pydantic(output_class=pydantic.WITH_MSG_HISTORY)
final_output = guard(
llm_api=openai.chat.completions.create,
msg_history=string.MOVIE_MSG_HISTORY,
@@ -898,7 +898,7 @@ def custom_llm(
nonlocal return_value
return return_value
- guard = gd.Guard.from_pydantic(Task)
+ guard = gd.Guard.for_pydantic(Task)
_, dict_o, *rest = guard(
custom_llm,
prompt="What is the status of this task?",
@@ -906,7 +906,7 @@ def custom_llm(
assert dict_o == {"status": "not started"}
return_value = pydantic.LLM_OUTPUT_ENUM_2
- guard = gd.Guard.from_pydantic(Task)
+ guard = gd.Guard.for_pydantic(Task)
result = guard(
custom_llm,
prompt="What is the status of this task REALLY?",
@@ -970,7 +970,7 @@ def test_pydantic_with_lite_llm(mocker):
response_token_count=1234,
),
]
- guard = gd.Guard.from_pydantic(output_class=pydantic.WITH_MSG_HISTORY)
+ guard = gd.Guard.for_pydantic(output_class=pydantic.WITH_MSG_HISTORY)
final_output = guard(
messages=string.MOVIE_MSG_HISTORY, model="gpt-3.5-turbo", max_tokens=10
)
@@ -997,7 +997,7 @@ def test_string_output(mocker):
)
]
- guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_STRING)
+ guard = gd.Guard.for_rail_string(string.RAIL_SPEC_FOR_STRING)
final_output = guard(
llm_api=openai.completions.create,
prompt_params={"ingredients": "tomato, cheese, sour cream"},
@@ -1058,7 +1058,7 @@ class Task(BaseModel):
class Tasks(BaseModel):
list: List[Task]
- guard = Guard.from_pydantic(Tasks)
+ guard = Guard.for_pydantic(Tasks)
tools = [
{
"type": "function",
@@ -1133,7 +1133,7 @@ def test_string_reask(mocker):
),
]
- guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_STRING_REASK)
+ guard = gd.Guard.for_rail_string(string.RAIL_SPEC_FOR_STRING_REASK)
final_output = guard(
llm_api=openai.completions.create,
prompt_params={"ingredients": "tomato, cheese, sour cream"},
@@ -1248,7 +1248,7 @@ def test_ser_deser(self):
and not importlib.util.find_spec("torch"),
reason="transformers or torch is not installed",
)
-def test_guard_from_pydantic_with_mock_hf_pipeline():
+def test_guard_for_pydantic_with_mock_hf_pipeline():
from tests.unit_tests.mocks.mock_hf_models import make_mock_pipeline
pipe = make_mock_pipeline()
@@ -1261,7 +1261,7 @@ def test_guard_from_pydantic_with_mock_hf_pipeline():
and not importlib.util.find_spec("torch"),
reason="transformers or torch is not installed",
)
-def test_guard_from_pydantic_with_mock_hf_model():
+def test_guard_for_pydantic_with_mock_hf_model():
from tests.unit_tests.mocks.mock_hf_models import make_mock_model_and_tokenizer
model, tokenizer = make_mock_model_and_tokenizer()
@@ -1291,10 +1291,10 @@ def test_guard_init(self, mocker):
assert init_spy.call_count == 1
- def test_from_rail(self, mocker):
+ def test_for_rail(self, mocker):
init_spy = mocker.spy(LowerCase, "__init__")
- guard = Guard.from_rail_string(
+ guard = Guard.for_rail_string(
"""