""" Main File for Files API implementation https://platform.openai.com/docs/api-reference/files """ import asyncio import contextvars import os from functools import partial from typing import Any, Coroutine, Dict, Literal, Optional, Union import httpx from openai.types.file_object import FileObject import litellm from litellm import client from litellm.batches.main import openai_files_instance from litellm.types.llms.openai import ( Batch, CreateFileRequest, FileContentRequest, FileTypes, HttpxBinaryResponseContent, ) from litellm.types.router import * from litellm.utils import supports_httpx_timeout async def afile_retrieve( file_id: str, custom_llm_provider: Literal["openai"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, ) -> Coroutine[Any, Any, FileObject]: """ Async: Get file contents LiteLLM Equivalent of GET https://api.openai.com/v1/files """ try: loop = asyncio.get_event_loop() kwargs["is_async"] = True # Use a partial function to pass your keyword arguments func = partial( file_retrieve, file_id, custom_llm_provider, extra_headers, extra_body, **kwargs, ) # Add the context to the function ctx = contextvars.copy_context() func_with_context = partial(ctx.run, func) init_response = await loop.run_in_executor(None, func_with_context) if asyncio.iscoroutine(init_response): response = await init_response else: response = init_response # type: ignore return response except Exception as e: raise e def file_retrieve( file_id: str, custom_llm_provider: Literal["openai"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, ) -> FileObject: """ Returns the contents of the specified file. LiteLLM Equivalent of POST: POST https://api.openai.com/v1/files """ try: optional_params = GenericLiteLLMParams(**kwargs) if custom_llm_provider == "openai": # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there api_base = ( optional_params.api_base or litellm.api_base or os.getenv("OPENAI_API_BASE") or "https://api.openai.com/v1" ) organization = ( optional_params.organization or litellm.organization or os.getenv("OPENAI_ORGANIZATION", None) or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105 ) # set API KEY api_key = ( optional_params.api_key or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there or litellm.openai_key or os.getenv("OPENAI_API_KEY") ) ### TIMEOUT LOGIC ### timeout = ( optional_params.timeout or kwargs.get("request_timeout", 600) or 600 ) # set timeout for 10 minutes by default if ( timeout is not None and isinstance(timeout, httpx.Timeout) and supports_httpx_timeout(custom_llm_provider) == False ): read_timeout = timeout.read or 600 timeout = read_timeout # default 10 min timeout elif timeout is not None and not isinstance(timeout, httpx.Timeout): timeout = float(timeout) # type: ignore elif timeout is None: timeout = 600.0 _is_async = kwargs.pop("is_async", False) is True response = openai_files_instance.retrieve_file( file_id=file_id, _is_async=_is_async, api_base=api_base, api_key=api_key, timeout=timeout, max_retries=optional_params.max_retries, organization=organization, ) else: raise litellm.exceptions.BadRequestError( message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format( custom_llm_provider ), model="n/a", llm_provider=custom_llm_provider, response=httpx.Response( status_code=400, content="Unsupported provider", request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore ), ) return response except Exception as e: raise e