mirror of
https://github.com/BerriAI/litellm.git
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6dda1ba6dd
* Add date picker to usage tab + Add reasoning_content token tracking across all providers on streaming (#9722) * feat(new_usage.tsx): add date picker for new usage tab allow user to look back on their usage data * feat(anthropic/chat/transformation.py): report reasoning tokens in completion token details allows usage tracking on how many reasoning tokens are actually being used * feat(streaming_chunk_builder.py): return reasoning_tokens in anthropic/openai streaming response allows tracking reasoning_token usage across providers * Fix update team metadata + fix bulk adding models on Ui (#9721) * fix(handle_add_model_submit.tsx): fix bulk adding models * fix(team_info.tsx): fix team metadata update Fixes https://github.com/BerriAI/litellm/issues/9689 * (v0) Unified file id - allow calling multiple providers with same file id (#9718) * feat(files_endpoints.py): initial commit adding 'target_model_names' support allow developer to specify all the models they want to call with the file * feat(files_endpoints.py): return unified files endpoint * test(test_files_endpoints.py): add validation test - if invalid purpose submitted * feat: more updates * feat: initial working commit of unified file id translation * fix: additional fixes * fix(router.py): remove model replace logic in jsonl on acreate_file enables file upload to work for chat completion requests as well * fix(files_endpoints.py): remove whitespace around model name * fix(azure/handler.py): return acreate_file with correct response type * fix: fix linting errors * test: fix mock test to run on github actions * fix: fix ruff errors * fix: fix file too large error * fix(utils.py): remove redundant var * test: modify test to work on github actions * test: update tests * test: more debug logs to understand ci/cd issue * test: fix test for respx * test: skip mock respx test fails on ci/cd - not clear why * fix: fix ruff check * fix: fix test * fix(model_connection_test.tsx): fix linting error * test: update unit tests
283 lines
10 KiB
Python
283 lines
10 KiB
Python
from typing import Any, Coroutine, Optional, Union, cast
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import httpx
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from openai import AsyncAzureOpenAI, AzureOpenAI
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from openai.types.file_deleted import FileDeleted
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from litellm._logging import verbose_logger
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from litellm.types.llms.openai import *
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from ..common_utils import BaseAzureLLM
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class AzureOpenAIFilesAPI(BaseAzureLLM):
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"""
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AzureOpenAI methods to support for batches
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- create_file()
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- retrieve_file()
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- list_files()
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- delete_file()
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- file_content()
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- update_file()
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"""
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def __init__(self) -> None:
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super().__init__()
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async def acreate_file(
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self,
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create_file_data: CreateFileRequest,
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openai_client: AsyncAzureOpenAI,
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) -> OpenAIFileObject:
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verbose_logger.debug("create_file_data=%s", create_file_data)
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response = await openai_client.files.create(**create_file_data)
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verbose_logger.debug("create_file_response=%s", response)
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return OpenAIFileObject(**response.model_dump())
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def create_file(
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self,
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_is_async: bool,
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create_file_data: CreateFileRequest,
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api_base: Optional[str],
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api_key: Optional[str],
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api_version: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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litellm_params: Optional[dict] = None,
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) -> Union[OpenAIFileObject, Coroutine[Any, Any, OpenAIFileObject]]:
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openai_client: Optional[
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Union[AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_azure_openai_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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client=client,
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_is_async=_is_async,
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.acreate_file(
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create_file_data=create_file_data, openai_client=openai_client
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)
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response = cast(AzureOpenAI, openai_client).files.create(**create_file_data)
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return OpenAIFileObject(**response.model_dump())
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async def afile_content(
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self,
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file_content_request: FileContentRequest,
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openai_client: AsyncAzureOpenAI,
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) -> HttpxBinaryResponseContent:
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response = await openai_client.files.content(**file_content_request)
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return HttpxBinaryResponseContent(response=response.response)
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def file_content(
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self,
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_is_async: bool,
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file_content_request: FileContentRequest,
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api_base: Optional[str],
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api_key: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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api_version: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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litellm_params: Optional[dict] = None,
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) -> Union[
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HttpxBinaryResponseContent, Coroutine[Any, Any, HttpxBinaryResponseContent]
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]:
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openai_client: Optional[
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Union[AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_azure_openai_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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client=client,
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_is_async=_is_async,
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.afile_content( # type: ignore
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file_content_request=file_content_request,
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openai_client=openai_client,
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)
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response = cast(AzureOpenAI, openai_client).files.content(
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**file_content_request
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)
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return HttpxBinaryResponseContent(response=response.response)
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async def aretrieve_file(
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self,
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file_id: str,
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openai_client: AsyncAzureOpenAI,
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) -> FileObject:
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response = await openai_client.files.retrieve(file_id=file_id)
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return response
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def retrieve_file(
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self,
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_is_async: bool,
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file_id: str,
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api_base: Optional[str],
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api_key: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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api_version: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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litellm_params: Optional[dict] = None,
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):
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openai_client: Optional[
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Union[AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_azure_openai_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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client=client,
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_is_async=_is_async,
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.aretrieve_file( # type: ignore
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file_id=file_id,
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openai_client=openai_client,
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)
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response = openai_client.files.retrieve(file_id=file_id)
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return response
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async def adelete_file(
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self,
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file_id: str,
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openai_client: AsyncAzureOpenAI,
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) -> FileDeleted:
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response = await openai_client.files.delete(file_id=file_id)
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if not isinstance(response, FileDeleted): # azure returns an empty string
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return FileDeleted(id=file_id, deleted=True, object="file")
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return response
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def delete_file(
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self,
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_is_async: bool,
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file_id: str,
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api_base: Optional[str],
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api_key: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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organization: Optional[str] = None,
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api_version: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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litellm_params: Optional[dict] = None,
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):
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openai_client: Optional[
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Union[AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_azure_openai_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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client=client,
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_is_async=_is_async,
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.adelete_file( # type: ignore
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file_id=file_id,
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openai_client=openai_client,
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)
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response = openai_client.files.delete(file_id=file_id)
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if not isinstance(response, FileDeleted): # azure returns an empty string
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return FileDeleted(id=file_id, deleted=True, object="file")
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return response
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async def alist_files(
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self,
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openai_client: AsyncAzureOpenAI,
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purpose: Optional[str] = None,
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):
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if isinstance(purpose, str):
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response = await openai_client.files.list(purpose=purpose)
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else:
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response = await openai_client.files.list()
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return response
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def list_files(
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self,
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_is_async: bool,
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api_base: Optional[str],
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api_key: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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purpose: Optional[str] = None,
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api_version: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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litellm_params: Optional[dict] = None,
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):
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openai_client: Optional[
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Union[AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_azure_openai_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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client=client,
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_is_async=_is_async,
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.alist_files( # type: ignore
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purpose=purpose,
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openai_client=openai_client,
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)
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if isinstance(purpose, str):
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response = openai_client.files.list(purpose=purpose)
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else:
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response = openai_client.files.list()
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return response
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