forked from phoenix/litellm-mirror
feat(llm_guard.py): support llm guard for content moderation
https://github.com/BerriAI/litellm/issues/2056
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122
enterprise/enterprise_hooks/llm_guard.py
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122
enterprise/enterprise_hooks/llm_guard.py
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# +------------------------+
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#
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# LLM Guard
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# https://llm-guard.com/
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#
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# +------------------------+
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# Thank you users! We ❤️ you! - Krrish & Ishaan
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## This provides an LLM Guard Integration for content moderation on the proxy
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from typing import Optional, Literal, Union
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import litellm, traceback, sys, uuid, os
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from litellm.caching import DualCache
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.integrations.custom_logger import CustomLogger
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from fastapi import HTTPException
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from litellm._logging import verbose_proxy_logger
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from litellm.utils import (
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ModelResponse,
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EmbeddingResponse,
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ImageResponse,
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StreamingChoices,
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)
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from datetime import datetime
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import aiohttp, asyncio
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litellm.set_verbose = True
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class _ENTERPRISE_LLMGuard(CustomLogger):
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# Class variables or attributes
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def __init__(
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self, mock_testing: bool = False, mock_redacted_text: Optional[dict] = None
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):
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self.mock_redacted_text = mock_redacted_text
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if mock_testing == True: # for testing purposes only
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return
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self.llm_guard_api_base = litellm.get_secret("LLM_GUARD_API_BASE", None)
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if self.llm_guard_api_base is None:
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raise Exception("Missing `LLM_GUARD_API_BASE` from environment")
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elif not self.llm_guard_api_base.endswith("/"):
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self.llm_guard_api_base += "/"
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def print_verbose(self, print_statement):
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try:
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verbose_proxy_logger.debug(print_statement)
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if litellm.set_verbose:
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print(print_statement) # noqa
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except:
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pass
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async def moderation_check(self, text: str):
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"""
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[TODO] make this more performant for high-throughput scenario
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"""
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try:
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async with aiohttp.ClientSession() as session:
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if self.mock_redacted_text is not None:
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redacted_text = self.mock_redacted_text
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else:
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# Make the first request to /analyze
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analyze_url = f"{self.llm_guard_api_base}analyze/prompt"
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verbose_proxy_logger.debug(f"Making request to: {analyze_url}")
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analyze_payload = {"prompt": text}
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redacted_text = None
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async with session.post(
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analyze_url, json=analyze_payload
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) as response:
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redacted_text = await response.json()
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if redacted_text is not None:
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if (
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redacted_text.get("is_valid", None) is not None
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and redacted_text["is_valid"] == "True"
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):
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raise HTTPException(
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status_code=400,
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detail={"error": "Violated content safety policy"},
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)
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else:
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pass
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else:
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raise HTTPException(
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status_code=500,
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detail={
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"error": f"Invalid content moderation response: {redacted_text}"
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},
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)
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except Exception as e:
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traceback.print_exc()
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raise e
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async def async_moderation_hook(
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self,
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data: dict,
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):
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"""
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- Calls the LLM Guard Endpoint
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- Rejects request if it fails safety check
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- Use the sanitized prompt returned
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- LLM Guard can handle things like PII Masking, etc.
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"""
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if "messages" in data:
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safety_check_messages = data["messages"][
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-1
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] # get the last response - llama guard has a 4k token limit
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if (
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isinstance(safety_check_messages, dict)
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and "content" in safety_check_messages
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and isinstance(safety_check_messages["content"], str)
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):
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await self.moderation_check(safety_check_messages["content"])
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return data
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# llm_guard = _ENTERPRISE_LLMGuard()
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# asyncio.run(
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# llm_guard.async_moderation_hook(
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# data={"messages": [{"role": "user", "content": "Hey how's it going?"}]}
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# )
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# )
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@ -1467,6 +1467,16 @@ class ProxyConfig:
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_ENTERPRISE_GoogleTextModeration()
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)
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imported_list.append(google_text_moderation_obj)
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elif (
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isinstance(callback, str)
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and callback == "llmguard_moderations"
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):
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from litellm.proxy.enterprise.enterprise_hooks.llm_guard import (
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_ENTERPRISE_LLMGuard,
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)
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llm_guard_moderation_obj = _ENTERPRISE_LLMGuard()
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imported_list.append(llm_guard_moderation_obj)
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else:
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imported_list.append(
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get_instance_fn(
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95
litellm/tests/test_llm_guard.py
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95
litellm/tests/test_llm_guard.py
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# What is this?
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## This tests the llm guard integration
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# What is this?
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## Unit test for presidio pii masking
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import sys, os, asyncio, time, random
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from datetime import datetime
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import os
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import pytest
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import litellm
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from litellm.proxy.enterprise.enterprise_hooks.llm_guard import _ENTERPRISE_LLMGuard
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from litellm import Router, mock_completion
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from litellm.proxy.utils import ProxyLogging
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.caching import DualCache
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### UNIT TESTS FOR LLM GUARD ###
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# Test if PII masking works with input A
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@pytest.mark.asyncio
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async def test_llm_guard_valid_response():
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"""
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Tests to see llm guard raises an error for a flagged response
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"""
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input_a_anonymizer_results = {
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"sanitized_prompt": "hello world",
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"is_valid": True,
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"scanners": {"Regex": 0.0},
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}
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llm_guard = _ENTERPRISE_LLMGuard(
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mock_testing=True, mock_redacted_text=input_a_anonymizer_results
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)
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_api_key = "sk-12345"
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user_api_key_dict = UserAPIKeyAuth(api_key=_api_key)
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local_cache = DualCache()
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try:
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await llm_guard.async_moderation_hook(
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data={
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"messages": [
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{
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"role": "user",
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"content": "hello world, my name is Jane Doe. My number is: 23r323r23r2wwkl",
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}
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]
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},
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)
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except Exception as e:
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pytest.fail(f"An exception occurred - {str(e)}")
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# Test if PII masking works with input B (also test if the response != A's response)
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@pytest.mark.asyncio
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async def test_llm_guard_error_raising():
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"""
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Tests to see llm guard raises an error for a flagged response
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"""
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input_b_anonymizer_results = {
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"sanitized_prompt": "hello world",
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"is_valid": False,
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"scanners": {"Regex": 0.0},
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}
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llm_guard = _ENTERPRISE_LLMGuard(
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mock_testing=True, mock_redacted_text=input_b_anonymizer_results
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)
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_api_key = "sk-12345"
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user_api_key_dict = UserAPIKeyAuth(api_key=_api_key)
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local_cache = DualCache()
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try:
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await llm_guard.async_moderation_hook(
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data={
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"messages": [
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{
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"role": "user",
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"content": "hello world, my name is Jane Doe. My number is: 23r323r23r2wwkl",
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}
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]
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},
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)
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pytest.fail(f"Should have failed - {str(e)}")
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except Exception as e:
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pass
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