mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 18:54:30 +00:00
118 lines
3.4 KiB
Python
118 lines
3.4 KiB
Python
import asyncio
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import traceback
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from datetime import datetime, timedelta, timezone
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from typing import List, Optional
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import fastapi
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import httpx
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from fastapi import (
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APIRouter,
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Depends,
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File,
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Form,
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Header,
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HTTPException,
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Request,
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Response,
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UploadFile,
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status,
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)
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import litellm
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from litellm._logging import verbose_proxy_logger
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from litellm.batches.main import FileObject
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from litellm.fine_tuning.main import vertex_fine_tuning_apis_instance
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from litellm.proxy._types import *
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from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
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router = APIRouter()
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default_vertex_config = None
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def set_default_vertex_config(config):
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global default_vertex_config
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if config is None:
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return
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if not isinstance(config, dict):
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raise ValueError("invalid config, vertex default config must be a dictionary")
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if isinstance(config, dict):
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for key, value in config.items():
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if isinstance(value, str) and value.startswith("os.environ/"):
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config[key] = litellm.get_secret(value)
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default_vertex_config = config
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def exception_handler(e: Exception):
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verbose_proxy_logger.error(
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"litellm.proxy.proxy_server.v1/projects/tuningJobs(): Exception occurred - {}".format(
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str(e)
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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if isinstance(e, HTTPException):
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return ProxyException(
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message=getattr(e, "message", str(e.detail)),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
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)
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else:
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error_msg = f"{str(e)}"
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return ProxyException(
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message=getattr(e, "message", error_msg),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", 500),
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)
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async def execute_post_vertex_ai_request(
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request: Request,
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route: str,
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):
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from litellm.fine_tuning.main import vertex_fine_tuning_apis_instance
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vertex_project = default_vertex_config.get("vertex_project", None)
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vertex_location = default_vertex_config.get("vertex_location", None)
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vertex_credentials = default_vertex_config.get("vertex_credentials", None)
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request_data_json = await request.json()
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response = (
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await vertex_fine_tuning_apis_instance.pass_through_vertex_ai_POST_request(
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request_data=request_data_json,
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vertex_project=vertex_project,
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vertex_location=vertex_location,
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vertex_credentials=vertex_credentials,
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request_route=route,
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)
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)
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return response
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@router.post(
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"/vertex-ai/tuningJobs",
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dependencies=[Depends(user_api_key_auth)],
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tags=["Vertex AI endpoints"],
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)
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async def vertex_create_fine_tuning_job(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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this is a pass through endpoint for the Vertex AI API. /tuningJobs endpoint
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it uses the vertex ai credentials on the proxy and forwards to vertex ai api
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"""
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try:
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response = await execute_post_vertex_ai_request(
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request=request,
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route="/tuningJobs",
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)
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return response
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except Exception as e:
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raise exception_handler(e) from e
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