litellm/enterprise/enterprise_hooks/llm_guard.py
Ishaan Jaff 4d1b4beb3d
(refactor) caching use LLMCachingHandler for async_get_cache and set_cache (#6208)
* use folder for caching

* fix importing caching

* fix clickhouse pyright

* fix linting

* fix correctly pass kwargs and args

* fix test case for embedding

* fix linting

* fix embedding caching logic

* fix refactor handle utils.py

* fix test_embedding_caching_azure_individual_items_reordered
2024-10-14 16:34:01 +05:30

192 lines
6.7 KiB
Python

# +------------------------+
#
# LLM Guard
# https://llm-guard.com/
#
# +------------------------+
# Thank you users! We ❤️ you! - Krrish & Ishaan
## This provides an LLM Guard Integration for content moderation on the proxy
from typing import Optional, Literal, Union
import litellm
import traceback
import sys
import uuid
import os
from litellm.caching.caching import DualCache
from litellm.proxy._types import UserAPIKeyAuth
from litellm.integrations.custom_logger import CustomLogger
from fastapi import HTTPException
from litellm._logging import verbose_proxy_logger
from litellm.utils import (
ModelResponse,
EmbeddingResponse,
ImageResponse,
StreamingChoices,
)
from datetime import datetime
import aiohttp
import asyncio
from litellm.utils import get_formatted_prompt
from litellm.secret_managers.main import get_secret_str
litellm.set_verbose = True
class _ENTERPRISE_LLMGuard(CustomLogger):
# Class variables or attributes
def __init__(
self,
mock_testing: bool = False,
mock_redacted_text: Optional[dict] = None,
):
self.mock_redacted_text = mock_redacted_text
self.llm_guard_mode = litellm.llm_guard_mode
if mock_testing == True: # for testing purposes only
return
self.llm_guard_api_base = get_secret_str("LLM_GUARD_API_BASE", None)
if self.llm_guard_api_base is None:
raise Exception("Missing `LLM_GUARD_API_BASE` from environment")
elif not self.llm_guard_api_base.endswith("/"):
self.llm_guard_api_base += "/"
def print_verbose(self, print_statement):
try:
verbose_proxy_logger.debug(print_statement)
if litellm.set_verbose:
print(print_statement) # noqa
except Exception:
pass
async def moderation_check(self, text: str):
"""
[TODO] make this more performant for high-throughput scenario
"""
try:
async with aiohttp.ClientSession() as session:
if self.mock_redacted_text is not None:
redacted_text = self.mock_redacted_text
else:
# Make the first request to /analyze
analyze_url = f"{self.llm_guard_api_base}analyze/prompt"
verbose_proxy_logger.debug("Making request to: %s", analyze_url)
analyze_payload = {"prompt": text}
redacted_text = None
async with session.post(
analyze_url, json=analyze_payload
) as response:
redacted_text = await response.json()
verbose_proxy_logger.info(
f"LLM Guard: Received response - {redacted_text}"
)
if redacted_text is not None:
if (
redacted_text.get("is_valid", None) is not None
and redacted_text["is_valid"] != True
):
raise HTTPException(
status_code=400,
detail={"error": "Violated content safety policy"},
)
else:
pass
else:
raise HTTPException(
status_code=500,
detail={
"error": f"Invalid content moderation response: {redacted_text}"
},
)
except Exception as e:
verbose_proxy_logger.exception(
"litellm.enterprise.enterprise_hooks.llm_guard::moderation_check - Exception occurred - {}".format(
str(e)
)
)
raise e
def should_proceed(self, user_api_key_dict: UserAPIKeyAuth, data: dict) -> bool:
if self.llm_guard_mode == "key-specific":
# check if llm guard enabled for specific keys only
self.print_verbose(
f"user_api_key_dict.permissions: {user_api_key_dict.permissions}"
)
if (
user_api_key_dict.permissions.get("enable_llm_guard_check", False)
== True
):
return True
elif self.llm_guard_mode == "all":
return True
elif self.llm_guard_mode == "request-specific":
self.print_verbose(f"received metadata: {data.get('metadata', {})}")
metadata = data.get("metadata", {})
permissions = metadata.get("permissions", {})
if (
"enable_llm_guard_check" in permissions
and permissions["enable_llm_guard_check"] == True
):
return True
return False
async def async_moderation_hook(
self,
data: dict,
user_api_key_dict: UserAPIKeyAuth,
call_type: Literal[
"completion",
"embeddings",
"image_generation",
"moderation",
"audio_transcription",
],
):
"""
- Calls the LLM Guard Endpoint
- Rejects request if it fails safety check
- Use the sanitized prompt returned
- LLM Guard can handle things like PII Masking, etc.
"""
self.print_verbose(
f"Inside LLM Guard Pre-Call Hook - llm_guard_mode={self.llm_guard_mode}"
)
_proceed = self.should_proceed(user_api_key_dict=user_api_key_dict, data=data)
if _proceed == False:
return
self.print_verbose("Makes LLM Guard Check")
try:
assert call_type in [
"completion",
"embeddings",
"image_generation",
"moderation",
"audio_transcription",
]
except Exception as e:
self.print_verbose(
f"Call Type - {call_type}, not in accepted list - ['completion','embeddings','image_generation','moderation','audio_transcription']"
)
return data
formatted_prompt = get_formatted_prompt(data=data, call_type=call_type) # type: ignore
self.print_verbose(f"LLM Guard, formatted_prompt: {formatted_prompt}")
return await self.moderation_check(text=formatted_prompt)
async def async_post_call_streaming_hook(
self, user_api_key_dict: UserAPIKeyAuth, response: str
):
if response is not None:
await self.moderation_check(text=response)
return response
# llm_guard = _ENTERPRISE_LLMGuard()
# asyncio.run(
# llm_guard.async_moderation_hook(
# data={"messages": [{"role": "user", "content": "Hey how's it going?"}]}
# )
# )