import json import os from datetime import datetime from typing import Any, Dict, List, Optional, Union import httpx from pydantic import BaseModel, Field import litellm from litellm._logging import verbose_logger from litellm.integrations.custom_logger import CustomLogger from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.proxy._types import SpendLogsPayload class GCSBucketPayload(SpendLogsPayload): messages: Optional[List] output: Optional[Union[Dict, str, List]] class GCSBucketLogger(CustomLogger): def __init__(self) -> None: self.async_httpx_client = AsyncHTTPHandler( timeout=httpx.Timeout(timeout=600.0, connect=5.0) ) self.path_service_account_json = os.getenv("GCS_PATH_SERVICE_ACCOUNT", None) self.BUCKET_NAME = os.getenv("GCS_BUCKET_NAME", None) if self.BUCKET_NAME is None: raise ValueError( "GCS_BUCKET_NAME is not set in the environment, but GCS Bucket is being used as a logging callback. Please set 'GCS_BUCKET_NAME' in the environment." ) if self.path_service_account_json is None: raise ValueError( "GCS_PATH_SERVICE_ACCOUNT is not set in the environment, but GCS Bucket is being used as a logging callback. Please set 'GCS_PATH_SERVICE_ACCOUNT' in the environment." ) pass #### ASYNC #### async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): try: verbose_logger.debug( "GCS Logger: async_log_success_event logging kwargs: %s, response_obj: %s", kwargs, response_obj, ) headers = await self.construct_request_headers() logging_payload: GCSBucketPayload = await self.get_gcs_payload( kwargs, response_obj, start_time, end_time ) object_name = logging_payload["request_id"] response = await self.async_httpx_client.post( headers=headers, url=f"https://storage.googleapis.com/upload/storage/v1/b/{self.BUCKET_NAME}/o?uploadType=media&name={object_name}", json=logging_payload, ) if response.status_code != 200: verbose_logger.error("GCS Bucket logging error: %s", str(response.text)) verbose_logger.debug("GCS Bucket response %s", response) verbose_logger.debug("GCS Bucket status code %s", response.status_code) verbose_logger.debug("GCS Bucket response.text %s", response.text) except Exception as e: verbose_logger.error("GCS Bucket logging error: %s", str(e)) async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): pass async def construct_request_headers(self) -> Dict[str, str]: from litellm import vertex_chat_completion auth_header, _ = vertex_chat_completion._get_token_and_url( model="gcs-bucket", vertex_credentials=self.path_service_account_json, vertex_project=None, vertex_location=None, gemini_api_key=None, stream=None, custom_llm_provider="vertex_ai", api_base=None, ) verbose_logger.debug("constructed auth_header %s", auth_header) headers = { "Authorization": f"Bearer {auth_header}", # auth_header "Content-Type": "application/json", } return headers async def get_gcs_payload( self, kwargs, response_obj, start_time, end_time ) -> GCSBucketPayload: from litellm.proxy.spend_tracking.spend_tracking_utils import ( get_logging_payload, ) spend_logs_payload: GCSBucketPayload = get_logging_payload( kwargs=kwargs, response_obj=response_obj, start_time=start_time, end_time=end_time, end_user_id=kwargs.get("user"), ) spend_logs_payload["startTime"] = start_time.isoformat() spend_logs_payload["endTime"] = end_time.isoformat() spend_logs_payload["completionStartTime"] = spend_logs_payload[ "completionStartTime" ].isoformat() object_name = spend_logs_payload["request_id"] output = None if response_obj is not None and ( kwargs.get("call_type", None) == "embedding" or isinstance(response_obj, litellm.EmbeddingResponse) ): output = None elif response_obj is not None and isinstance( response_obj, litellm.ModelResponse ): output_list = [] for choice in response_obj.choices: output_list.append(choice.json()) output = output_list elif response_obj is not None and isinstance( response_obj, litellm.TextCompletionResponse ): output_list = [] for choice in response_obj.choices: output_list.append(choice.json()) output = output_list elif response_obj is not None and isinstance( response_obj, litellm.ImageResponse ): output = response_obj["data"] elif response_obj is not None and isinstance( response_obj, litellm.TranscriptionResponse ): output = response_obj["text"] spend_logs_payload["output"] = output return spend_logs_payload async def download_gcs_object(self, object_name): """ Download an object from GCS. https://cloud.google.com/storage/docs/downloading-objects#download-object-json """ try: headers = await self.construct_request_headers() url = f"https://storage.googleapis.com/storage/v1/b/{self.BUCKET_NAME}/o/{object_name}?alt=media" # Send the GET request to download the object response = await self.async_httpx_client.get(url=url, headers=headers) if response.status_code != 200: verbose_logger.error( "GCS object download error: %s", str(response.text) ) return None verbose_logger.debug( "GCS object download response status code: %s", response.status_code ) # Return the content of the downloaded object return response.content except Exception as e: verbose_logger.error("GCS object download error: %s", str(e)) return None async def delete_gcs_object(self, object_name): """ Delete an object from GCS. """ try: headers = await self.construct_request_headers() url = f"https://storage.googleapis.com/storage/v1/b/{self.BUCKET_NAME}/o/{object_name}" # Send the DELETE request to delete the object response = await self.async_httpx_client.delete(url=url, headers=headers) if (response.status_code != 200) or (response.status_code != 204): verbose_logger.error( "GCS object delete error: %s, status code: %s", str(response.text), response.status_code, ) return None verbose_logger.debug( "GCS object delete response status code: %s, response: %s", response.status_code, response.text, ) # Return the content of the downloaded object return response.text except Exception as e: verbose_logger.error("GCS object download error: %s", str(e)) return None