mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 10:44:24 +00:00
719 lines
25 KiB
Python
719 lines
25 KiB
Python
"""
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Main File for Files API implementation
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https://platform.openai.com/docs/api-reference/files
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"""
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import asyncio
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import contextvars
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import os
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from functools import partial
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from typing import Any, Coroutine, Dict, Literal, Optional, Union
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import httpx
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import litellm
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from litellm import client, get_secret
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from litellm.llms.files_apis.azure import AzureOpenAIFilesAPI
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from litellm.llms.openai import FileDeleted, FileObject, OpenAIFilesAPI
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from litellm.types.llms.openai import (
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Batch,
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CreateFileRequest,
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FileContentRequest,
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FileTypes,
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HttpxBinaryResponseContent,
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)
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from litellm.types.router import *
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from litellm.utils import supports_httpx_timeout
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####### ENVIRONMENT VARIABLES ###################
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openai_files_instance = OpenAIFilesAPI()
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azure_files_instance = AzureOpenAIFilesAPI()
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#################################################
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async def afile_retrieve(
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file_id: str,
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custom_llm_provider: Literal["openai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> Coroutine[Any, Any, FileObject]:
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"""
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Async: Get file contents
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LiteLLM Equivalent of GET https://api.openai.com/v1/files
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"""
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try:
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loop = asyncio.get_event_loop()
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kwargs["is_async"] = True
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# Use a partial function to pass your keyword arguments
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func = partial(
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file_retrieve,
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file_id,
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custom_llm_provider,
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extra_headers,
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extra_body,
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**kwargs,
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)
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# Add the context to the function
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ctx = contextvars.copy_context()
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func_with_context = partial(ctx.run, func)
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init_response = await loop.run_in_executor(None, func_with_context)
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if asyncio.iscoroutine(init_response):
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response = await init_response
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else:
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response = init_response # type: ignore
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return response
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except Exception as e:
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raise e
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def file_retrieve(
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file_id: str,
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custom_llm_provider: Literal["openai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> FileObject:
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"""
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Returns the contents of the specified file.
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LiteLLM Equivalent of POST: POST https://api.openai.com/v1/files
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"""
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try:
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optional_params = GenericLiteLLMParams(**kwargs)
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if custom_llm_provider == "openai":
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# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
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api_base = (
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optional_params.api_base
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or litellm.api_base
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or os.getenv("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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)
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organization = (
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optional_params.organization
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or litellm.organization
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or os.getenv("OPENAI_ORGANIZATION", None)
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or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
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)
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# set API KEY
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api_key = (
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optional_params.api_key
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or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
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or litellm.openai_key
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or os.getenv("OPENAI_API_KEY")
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)
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### TIMEOUT LOGIC ###
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timeout = (
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optional_params.timeout or kwargs.get("request_timeout", 600) or 600
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)
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# set timeout for 10 minutes by default
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if (
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timeout is not None
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and isinstance(timeout, httpx.Timeout)
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and supports_httpx_timeout(custom_llm_provider) == False
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):
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read_timeout = timeout.read or 600
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timeout = read_timeout # default 10 min timeout
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elif timeout is not None and not isinstance(timeout, httpx.Timeout):
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timeout = float(timeout) # type: ignore
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elif timeout is None:
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timeout = 600.0
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_is_async = kwargs.pop("is_async", False) is True
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response = openai_files_instance.retrieve_file(
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file_id=file_id,
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_is_async=_is_async,
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api_base=api_base,
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api_key=api_key,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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organization=organization,
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)
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else:
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raise litellm.exceptions.BadRequestError(
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message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
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custom_llm_provider
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),
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model="n/a",
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llm_provider=custom_llm_provider,
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response=httpx.Response(
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status_code=400,
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content="Unsupported provider",
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request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
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),
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)
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return response
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except Exception as e:
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raise e
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# Delete file
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async def afile_delete(
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file_id: str,
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custom_llm_provider: Literal["openai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> Coroutine[Any, Any, FileObject]:
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"""
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Async: Delete file
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LiteLLM Equivalent of DELETE https://api.openai.com/v1/files
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"""
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try:
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loop = asyncio.get_event_loop()
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kwargs["is_async"] = True
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# Use a partial function to pass your keyword arguments
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func = partial(
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file_delete,
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file_id,
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custom_llm_provider,
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extra_headers,
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extra_body,
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**kwargs,
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)
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# Add the context to the function
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ctx = contextvars.copy_context()
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func_with_context = partial(ctx.run, func)
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init_response = await loop.run_in_executor(None, func_with_context)
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if asyncio.iscoroutine(init_response):
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response = await init_response
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else:
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response = init_response # type: ignore
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return response
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except Exception as e:
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raise e
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def file_delete(
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file_id: str,
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custom_llm_provider: Literal["openai", "azure"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> FileDeleted:
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"""
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Delete file
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LiteLLM Equivalent of DELETE https://api.openai.com/v1/files
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"""
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try:
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optional_params = GenericLiteLLMParams(**kwargs)
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### TIMEOUT LOGIC ###
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timeout = optional_params.timeout or kwargs.get("request_timeout", 600) or 600
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# set timeout for 10 minutes by default
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|
|
|
if (
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timeout is not None
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|
and isinstance(timeout, httpx.Timeout)
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|
and supports_httpx_timeout(custom_llm_provider) == False
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):
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read_timeout = timeout.read or 600
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timeout = read_timeout # default 10 min timeout
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elif timeout is not None and not isinstance(timeout, httpx.Timeout):
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timeout = float(timeout) # type: ignore
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elif timeout is None:
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timeout = 600.0
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_is_async = kwargs.pop("is_async", False) is True
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if custom_llm_provider == "openai":
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# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
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api_base = (
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optional_params.api_base
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or litellm.api_base
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or os.getenv("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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)
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organization = (
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optional_params.organization
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or litellm.organization
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or os.getenv("OPENAI_ORGANIZATION", None)
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or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
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)
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# set API KEY
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api_key = (
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optional_params.api_key
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or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
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or litellm.openai_key
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or os.getenv("OPENAI_API_KEY")
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)
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response = openai_files_instance.delete_file(
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file_id=file_id,
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_is_async=_is_async,
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api_base=api_base,
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api_key=api_key,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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organization=organization,
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)
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elif custom_llm_provider == "azure":
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api_base = optional_params.api_base or litellm.api_base or get_secret("AZURE_API_BASE") # type: ignore
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api_version = (
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optional_params.api_version
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or litellm.api_version
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or get_secret("AZURE_API_VERSION")
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) # type: ignore
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api_key = (
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optional_params.api_key
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or litellm.api_key
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or litellm.azure_key
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or get_secret("AZURE_OPENAI_API_KEY")
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or get_secret("AZURE_API_KEY")
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) # type: ignore
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extra_body = optional_params.get("extra_body", {})
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azure_ad_token: Optional[str] = None
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if extra_body is not None:
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azure_ad_token = extra_body.pop("azure_ad_token", None)
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else:
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azure_ad_token = get_secret("AZURE_AD_TOKEN") # type: ignore
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response = azure_files_instance.delete_file(
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_is_async=_is_async,
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api_base=api_base,
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api_key=api_key,
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api_version=api_version,
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|
timeout=timeout,
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max_retries=optional_params.max_retries,
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file_id=file_id,
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)
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else:
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|
raise litellm.exceptions.BadRequestError(
|
|
message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
|
|
custom_llm_provider
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|
),
|
|
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
|
|
),
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)
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return response
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except Exception as e:
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raise e
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|
|
|
|
|
# List files
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async def afile_list(
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custom_llm_provider: Literal["openai"] = "openai",
|
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purpose: Optional[str] = None,
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|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
):
|
|
"""
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|
Async: List files
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|
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|
LiteLLM Equivalent of GET https://api.openai.com/v1/files
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|
"""
|
|
try:
|
|
loop = asyncio.get_event_loop()
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|
kwargs["is_async"] = True
|
|
|
|
# Use a partial function to pass your keyword arguments
|
|
func = partial(
|
|
file_list,
|
|
custom_llm_provider,
|
|
purpose,
|
|
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_list(
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
purpose: Optional[str] = None,
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
):
|
|
"""
|
|
List files
|
|
|
|
LiteLLM Equivalent of GET 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.list_files(
|
|
purpose=purpose,
|
|
_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 'file_list'. 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="file_list", url="https://github.com/BerriAI/litellm"), # type: ignore
|
|
),
|
|
)
|
|
return response
|
|
except Exception as e:
|
|
raise e
|
|
|
|
|
|
async def acreate_file(
|
|
file: FileTypes,
|
|
purpose: Literal["assistants", "batch", "fine-tune"],
|
|
custom_llm_provider: Literal["openai", "azure"] = "openai",
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> FileObject:
|
|
"""
|
|
Async: Files are used to upload documents that can be used with features like Assistants, Fine-tuning, and Batch API.
|
|
|
|
LiteLLM Equivalent of POST: POST https://api.openai.com/v1/files
|
|
"""
|
|
try:
|
|
loop = asyncio.get_event_loop()
|
|
kwargs["acreate_file"] = True
|
|
|
|
# Use a partial function to pass your keyword arguments
|
|
func = partial(
|
|
create_file,
|
|
file,
|
|
purpose,
|
|
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 create_file(
|
|
file: FileTypes,
|
|
purpose: Literal["assistants", "batch", "fine-tune"],
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> Union[FileObject, Coroutine[Any, Any, FileObject]]:
|
|
"""
|
|
Files are used to upload documents that can be used with features like Assistants, Fine-tuning, and Batch API.
|
|
|
|
LiteLLM Equivalent of POST: POST https://api.openai.com/v1/files
|
|
"""
|
|
try:
|
|
_is_async = kwargs.pop("acreate_file", False) is True
|
|
optional_params = GenericLiteLLMParams(**kwargs)
|
|
|
|
### 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
|
|
|
|
_create_file_request = CreateFileRequest(
|
|
file=file,
|
|
purpose=purpose,
|
|
extra_headers=extra_headers,
|
|
extra_body=extra_body,
|
|
)
|
|
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")
|
|
)
|
|
|
|
response = openai_files_instance.create_file(
|
|
_is_async=_is_async,
|
|
api_base=api_base,
|
|
api_key=api_key,
|
|
timeout=timeout,
|
|
max_retries=optional_params.max_retries,
|
|
organization=organization,
|
|
create_file_data=_create_file_request,
|
|
)
|
|
elif custom_llm_provider == "azure":
|
|
api_base = optional_params.api_base or litellm.api_base or get_secret("AZURE_API_BASE") # type: ignore
|
|
api_version = (
|
|
optional_params.api_version
|
|
or litellm.api_version
|
|
or get_secret("AZURE_API_VERSION")
|
|
) # type: ignore
|
|
|
|
api_key = (
|
|
optional_params.api_key
|
|
or litellm.api_key
|
|
or litellm.azure_key
|
|
or get_secret("AZURE_OPENAI_API_KEY")
|
|
or get_secret("AZURE_API_KEY")
|
|
) # type: ignore
|
|
|
|
extra_body = optional_params.get("extra_body", {})
|
|
azure_ad_token: Optional[str] = None
|
|
if extra_body is not None:
|
|
azure_ad_token = extra_body.pop("azure_ad_token", None)
|
|
else:
|
|
azure_ad_token = get_secret("AZURE_AD_TOKEN") # type: ignore
|
|
|
|
response = azure_files_instance.create_file(
|
|
_is_async=_is_async,
|
|
api_base=api_base,
|
|
api_key=api_key,
|
|
api_version=api_version,
|
|
timeout=timeout,
|
|
max_retries=optional_params.max_retries,
|
|
create_file_data=_create_file_request,
|
|
)
|
|
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
|
|
|
|
|
|
async def afile_content(
|
|
file_id: str,
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> HttpxBinaryResponseContent:
|
|
"""
|
|
Async: Get file contents
|
|
|
|
LiteLLM Equivalent of GET https://api.openai.com/v1/files
|
|
"""
|
|
try:
|
|
loop = asyncio.get_event_loop()
|
|
kwargs["afile_content"] = True
|
|
|
|
# Use a partial function to pass your keyword arguments
|
|
func = partial(
|
|
file_content,
|
|
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_content(
|
|
file_id: str,
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> Union[HttpxBinaryResponseContent, Coroutine[Any, Any, HttpxBinaryResponseContent]]:
|
|
"""
|
|
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
|
|
|
|
_file_content_request = FileContentRequest(
|
|
file_id=file_id,
|
|
extra_headers=extra_headers,
|
|
extra_body=extra_body,
|
|
)
|
|
|
|
_is_async = kwargs.pop("afile_content", False) is True
|
|
|
|
response = openai_files_instance.file_content(
|
|
_is_async=_is_async,
|
|
file_content_request=_file_content_request,
|
|
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
|