7514bb4740
Greptile P2 follow-ups on _content_utils.py: - Drop unreachable ``_resolve_messages``. The new ``_iter_inspection_messages`` walks ``messages`` AND ``input`` independently; leaving the old fallback-only variant around invited a future maintainer to wire it back up and silently narrow coverage. - Rename ``iter_user_text`` → ``iter_message_text``. The helper walks every role (user, assistant, system); the old name implied user-turn content only. Callers and tests updated. - Close mixed-list coverage gap. When ``data["input"]`` was a list mixing content-part dicts and bare strings, ``iter_message_text`` and ``build_inspection_messages`` only saw the dict parts while ``walk_user_text`` already inspected both. ``_iter_text_parts_in_content`` now treats bare strings inside a content list as text fragments, so read and write helpers agree on coverage. Adds two regression tests for the mixed-list shape. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
136 lines
4.7 KiB
Python
136 lines
4.7 KiB
Python
# +-----------------------------------------------+
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#
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# Google Text Moderation
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# https://cloud.google.com/natural-language/docs/moderating-text
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#
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# +-----------------------------------------------+
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# Thank you users! We ❤️ you! - Krrish & Ishaan
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from fastapi import HTTPException
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import litellm
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from litellm._logging import verbose_proxy_logger
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from litellm.integrations.custom_logger import CustomLogger
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.proxy.guardrails._content_utils import iter_message_text
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from litellm.types.utils import CallTypesLiteral
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class _ENTERPRISE_GoogleTextModeration(CustomLogger):
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user_api_key_cache = None
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confidence_categories = [
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"toxic",
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"insult",
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"profanity",
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"derogatory",
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"sexual",
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"death_harm_and_tragedy",
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"violent",
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"firearms_and_weapons",
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"public_safety",
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"health",
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"religion_and_belief",
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"illicit_drugs",
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"war_and_conflict",
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"politics",
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"finance",
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"legal",
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] # https://cloud.google.com/natural-language/docs/moderating-text#safety_attribute_confidence_scores
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# Class variables or attributes
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def __init__(self):
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try:
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from google.cloud import language_v1 # type: ignore
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except Exception:
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raise Exception(
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"Missing google.cloud package. Run `pip install --upgrade google-cloud-language`"
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)
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# Instantiates a client
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self.client = language_v1.LanguageServiceClient()
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self.moderate_text_request = language_v1.ModerateTextRequest
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self.language_document = language_v1.types.Document # type: ignore
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self.document_type = language_v1.types.Document.Type.PLAIN_TEXT # type: ignore
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default_confidence_threshold = (
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litellm.google_moderation_confidence_threshold or 0.8
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) # by default require a high confidence (80%) to fail
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for category in self.confidence_categories:
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if hasattr(litellm, f"{category}_confidence_threshold"):
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setattr(
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self,
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f"{category}_confidence_threshold",
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getattr(litellm, f"{category}_confidence_threshold"),
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)
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else:
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setattr(
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self,
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f"{category}_confidence_threshold",
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default_confidence_threshold,
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)
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set_confidence_value = getattr(
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self,
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f"{category}_confidence_threshold",
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)
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verbose_proxy_logger.info(
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f"Google Text Moderation: {category}_confidence_threshold: {set_confidence_value}"
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)
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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 Exception:
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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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user_api_key_dict: UserAPIKeyAuth,
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call_type: CallTypesLiteral,
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):
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"""
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- Calls Google's Text Moderation API
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- Rejects request if it fails safety check
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"""
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# Covers multimodal list content + Responses-API input.
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text = "".join(iter_message_text(data))
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if text:
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document = self.language_document(content=text, type_=self.document_type)
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request = self.moderate_text_request(
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document=document,
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)
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# Make the request
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response = self.client.moderate_text(request=request)
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for category in response.moderation_categories:
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category_name = category.name
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category_name = category_name.lower()
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category_name = category_name.replace("&", "and")
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category_name = category_name.replace(",", "")
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category_name = category_name.replace(
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" ", "_"
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) # e.g. go from 'Firearms & Weapons' to 'firearms_and_weapons'
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if category.confidence > getattr(
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self, f"{category_name}_confidence_threshold"
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):
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raise HTTPException(
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status_code=400,
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detail={
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"error": f"Violated content safety policy. Category={category}"
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},
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)
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# Handle the response
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return data
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# google_text_moderation_obj = _ENTERPRISE_GoogleTextModeration()
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# asyncio.run(
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# google_text_moderation_obj.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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