add retrive file to litellm SDK

litellm/__init__.py

@@ -364,7 +364,7 @@ for key, value in model_cost.items():
     elif value.get("litellm_provider") == "mistral":
         mistral_chat_models.append(key)
     elif value.get("litellm_provider") == "anthropic":
-        anthropic_models.append(key)    
+        anthropic_models.append(key)
     elif value.get("litellm_provider") == "empower":
         empower_models.append(key)
     elif value.get("litellm_provider") == "openrouter":
@@ -879,5 +879,6 @@ from .proxy.proxy_cli import run_server
 from .router import Router
 from .assistants.main import *
 from .batches.main import *
+from .files.main import *
 from .scheduler import *
 from .cost_calculator import response_cost_calculator, cost_per_token

litellm/files/main.py

@@ -0,0 +1,150 @@
+"""
+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

litellm/llms/openai.py

@@ -2064,6 +2064,52 @@ class OpenAIFilesAPI(BaseLLM):
 
         return response
 
+    async def aretrieve_file(
+        self,
+        file_id: str,
+        openai_client: AsyncOpenAI,
+    ) -> FileObject:
+        response = await openai_client.files.retrieve(file_id=file_id)
+        return response
+
+    def retrieve_file(
+        self,
+        _is_async: bool,
+        file_id: str,
+        api_base: str,
+        api_key: Optional[str],
+        timeout: Union[float, httpx.Timeout],
+        max_retries: Optional[int],
+        organization: Optional[str],
+        client: Optional[Union[OpenAI, AsyncOpenAI]] = None,
+    ):
+        openai_client: Optional[Union[OpenAI, AsyncOpenAI]] = self.get_openai_client(
+            api_key=api_key,
+            api_base=api_base,
+            timeout=timeout,
+            max_retries=max_retries,
+            organization=organization,
+            client=client,
+            _is_async=_is_async,
+        )
+        if openai_client is None:
+            raise ValueError(
+                "OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
+            )
+
+        if _is_async is True:
+            if not isinstance(openai_client, AsyncOpenAI):
+                raise ValueError(
+                    "OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
+                )
+            return self.aretrieve_file(  # type: ignore
+                file_id=file_id,
+                openai_client=openai_client,
+            )
+        response = openai_client.files.retrieve(file_id=file_id)
+
+        return response
+
 
 class OpenAIBatchesAPI(BaseLLM):
     """