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72 lines
2.2 KiB
Python
72 lines
2.2 KiB
Python
# +-------------------------------------------------------------+
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#
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# Llama Guard
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# https://huggingface.co/meta-llama/LlamaGuard-7b/tree/main
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#
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# LLM for Content Moderation
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# +-------------------------------------------------------------+
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# Thank you users! We ❤️ you! - Krrish & Ishaan
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import sys, 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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from typing import Optional, Literal, Union
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import litellm, traceback, sys, uuid
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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_LlamaGuard(CustomLogger):
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# Class variables or attributes
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def __init__(self, model_name: Optional[str] = None):
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self.model = model_name or litellm.llamaguard_model_name
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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 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 Llama Guard Endpoint
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- Rejects request if it fails safety check
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The llama guard prompt template is applied automatically in factory.py
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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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response = await litellm.acompletion(
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model=self.model,
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messages=[safety_check_messages],
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hf_model_name="meta-llama/LlamaGuard-7b",
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)
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if "unsafe" in response.choices[0].message.content:
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raise HTTPException(
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status_code=400, detail={"error": "Violated content safety policy"}
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)
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return data
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