diff --git a/litellm/integrations/gcs_bucket.py b/litellm/integrations/gcs_bucket.py index 2c9da5584..d58350621 100644 --- a/litellm/integrations/gcs_bucket.py +++ b/litellm/integrations/gcs_bucket.py @@ -83,11 +83,14 @@ class GCSBucketLogger(GCSBucketBase): # Modify the object_name to include the date-based folder object_name = f"{current_date}/{response_obj['id']}" - response = await self.async_httpx_client.post( - headers=headers, - url=f"https://storage.googleapis.com/upload/storage/v1/b/{bucket_name}/o?uploadType=media&name={object_name}", - data=json_logged_payload, - ) + try: + response = await self.async_httpx_client.post( + headers=headers, + url=f"https://storage.googleapis.com/upload/storage/v1/b/{bucket_name}/o?uploadType=media&name={object_name}", + data=json_logged_payload, + ) + except httpx.HTTPStatusError as e: + raise Exception(f"GCS Bucket logging error: {e.response.text}") if response.status_code != 200: verbose_logger.error("GCS Bucket logging error: %s", str(response.text)) diff --git a/litellm/proxy/_new_secret_config.yaml b/litellm/proxy/_new_secret_config.yaml index f08f15435..2c910865a 100644 --- a/litellm/proxy/_new_secret_config.yaml +++ b/litellm/proxy/_new_secret_config.yaml @@ -1,73 +1,9 @@ model_list: - - model_name: fake-claude-endpoint - litellm_params: - model: anthropic.claude-3-sonnet-20240229-v1:0 - api_base: https://exampleopenaiendpoint-production.up.railway.app - aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY - aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID - - model_name: gemini-vision - litellm_params: - model: vertex_ai/gemini-1.0-pro-vision-001 - api_base: https://exampleopenaiendpoint-production.up.railway.app/v1/projects/adroit-crow-413218/locations/us-central1/publishers/google/models/gemini-1.0-pro-vision-001 - vertex_project: "adroit-crow-413218" - vertex_location: "us-central1" - - model_name: fake-azure-endpoint - litellm_params: - model: openai/429 - api_key: fake-key - api_base: https://exampleopenaiendpoint-production.up.railway.app - model_name: fake-openai-endpoint litellm_params: - model: gpt-3.5-turbo - api_base: https://exampleopenaiendpoint-production.up.railway.app - - model_name: o1-preview - litellm_params: - model: o1-preview - - model_name: rerank-english-v3.0 - litellm_params: - model: cohere/rerank-english-v3.0 - api_key: os.environ/COHERE_API_KEY - - model_name: azure-rerank-english-v3.0 - litellm_params: - model: azure_ai/rerank-english-v3.0 - api_base: os.environ/AZURE_AI_COHERE_API_BASE - api_key: os.environ/AZURE_AI_COHERE_API_KEY - - model_name: "databricks/*" - litellm_params: - model: "databricks/*" - api_key: os.environ/DATABRICKS_API_KEY - api_base: os.environ/DATABRICKS_API_BASE - - model_name: "anthropic/*" - litellm_params: - model: "anthropic/*" - - model_name: "*" - litellm_params: - model: "openai/*" - - model_name: "fireworks_ai/*" - litellm_params: - model: "fireworks_ai/*" - configurable_clientside_auth_params: ["api_base"] - - model_name: "gemini-flash-experimental" - litellm_params: - model: "vertex_ai/gemini-flash-experimental" + model: openai/fake + api_key: fake-key + api_base: https://exampleopenaiendpoint-production.up.railway.app/ litellm_settings: - turn_off_message_logging: true - # callbacks: - # - prometheus - # - otel - failure_callback: - - sentry - - prometheus - success_callback: - - prometheus - - s3 - s3_callback_params: - s3_bucket_name: mytestbucketlitellm # AWS Bucket Name for S3 - s3_region_name: us-west-2 # AWS Region Name for S3 - s3_aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID # us os.environ/ to pass environment variables. This is AWS Access Key ID for S3 - s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY # AWS Secret Access Key for S3 - -general_settings: - db_url: os.environ/DATABASE_URL - # disable_prisma_schema_update: true \ No newline at end of file + callbacks: ["gcs_bucket"]