mirror of
https://github.com/tiennm99/litellm.git
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186 lines
6.2 KiB
Python
186 lines
6.2 KiB
Python
# 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.openai_moderation import (
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_ENTERPRISE_OpenAI_Moderation,
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)
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from litellm import Router, mock_completion
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from litellm.proxy.utils import ProxyLogging, hash_token
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.caching.caching import DualCache
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### UNIT TESTS FOR OpenAI Moderation ###
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@pytest.mark.asyncio
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async def test_openai_moderation_error_raising(monkeypatch):
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"""
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Tests to see OpenAI Moderation raises an error for a flagged response
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"""
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from unittest.mock import AsyncMock, MagicMock
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from litellm.types.llms.openai import OpenAIModerationResponse
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litellm.openai_moderations_model_name = "text-moderation-latest"
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openai_mod = _ENTERPRISE_OpenAI_Moderation()
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_api_key = "sk-12345"
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_api_key = hash_token("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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from litellm.proxy.proxy_server import llm_router
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llm_router = litellm.Router(
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model_list=[
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{
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"model_name": "text-moderation-latest",
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"litellm_params": {
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"model": "text-moderation-latest",
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"api_key": os.environ.get("OPENAI_API_KEY", "fake-key"),
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},
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}
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]
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)
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# Mock the amoderation call to return a flagged response
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mock_response = MagicMock(spec=OpenAIModerationResponse)
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mock_response.results = [MagicMock(flagged=True)]
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async def mock_amoderation(*args, **kwargs):
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return mock_response
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llm_router.amoderation = mock_amoderation
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setattr(litellm.proxy.proxy_server, "llm_router", llm_router)
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try:
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await openai_mod.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": "fuck off you're the worst",
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}
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]
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},
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user_api_key_dict=user_api_key_dict,
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call_type="completion",
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)
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pytest.fail(f"Should have failed")
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except Exception as e:
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print("Got exception: ", e)
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assert "Violated content safety policy" in str(e)
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pass
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@pytest.mark.asyncio
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async def test_openai_moderation_responses_api_input_field():
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"""
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Tests that OpenAI Moderation works with Responses API input field.
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This test verifies the fix for the issue where moderation was skipped
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for Responses API because it only checked for 'messages' field but
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Responses API uses 'input' field instead.
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"""
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from unittest.mock import AsyncMock, MagicMock, patch
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from litellm.types.llms.openai import (
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OpenAIModerationResponse,
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OpenAIModerationResult,
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)
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from litellm.proxy.guardrails.guardrail_hooks.openai.moderations import (
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OpenAIModerationGuardrail,
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)
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# Initialize the open-source OpenAI Moderation guardrail
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openai_mod = OpenAIModerationGuardrail(
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guardrail_name="openai-moderation-test",
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api_key="fake-key-for-testing",
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model="omni-moderation-latest",
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)
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_api_key = "sk-12345"
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_api_key = hash_token("sk-12345")
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user_api_key_dict = UserAPIKeyAuth(api_key=_api_key)
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# Mock the async_make_request to return a flagged response
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mock_moderation_response = OpenAIModerationResponse(
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id="modr-123",
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model="omni-moderation-latest",
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results=[
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OpenAIModerationResult(
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flagged=True,
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categories={"violence": True, "hate": False},
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category_scores={"violence": 0.95, "hate": 0.1},
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category_applied_input_types=None,
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)
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],
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)
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with patch.object(
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openai_mod, "async_make_request", return_value=mock_moderation_response
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):
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# Test 1: Responses API with input as string
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try:
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await openai_mod.async_moderation_hook(
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data={
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"model": "gpt-4o",
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"input": "I want to hurt people",
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},
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user_api_key_dict=user_api_key_dict,
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call_type="responses",
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)
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pytest.fail("Should have raised HTTPException for flagged content")
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except Exception as e:
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print("Got exception for string input: ", e)
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assert "Violated OpenAI moderation policy" in str(e)
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# Test 2: Responses API with input as list of messages
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try:
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await openai_mod.async_moderation_hook(
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data={
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"model": "gpt-4o",
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"input": [
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{"role": "user", "content": "I want to hurt people"}
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],
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},
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user_api_key_dict=user_api_key_dict,
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call_type="responses",
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)
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pytest.fail("Should have raised HTTPException for flagged content")
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except Exception as e:
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print("Got exception for list input: ", e)
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assert "Violated OpenAI moderation policy" in str(e)
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# Test 3: Verify it still works with messages field (Chat Completions)
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try:
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await openai_mod.async_moderation_hook(
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data={
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"model": "gpt-4o",
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"messages": [
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{"role": "user", "content": "I want to hurt people"}
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],
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},
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user_api_key_dict=user_api_key_dict,
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call_type="completion",
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)
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pytest.fail("Should have raised HTTPException for flagged content")
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except Exception as e:
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print("Got exception for messages field: ", e)
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assert "Violated OpenAI moderation policy" in str(e)
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print("✓ All Responses API moderation tests passed!")
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