mirror of
https://github.com/BerriAI/litellm.git
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d57be47b0f
* ci(config.yml): add a 'check_code_quality' step Addresses https://github.com/BerriAI/litellm/issues/5991 * ci(config.yml): check why circle ci doesn't pick up this test * ci(config.yml): fix to run 'check_code_quality' tests * fix(__init__.py): fix unprotected import * fix(__init__.py): don't remove unused imports * build(ruff.toml): update ruff.toml to ignore unused imports * fix: fix: ruff + pyright - fix linting + type-checking errors * fix: fix linting errors * fix(lago.py): fix module init error * fix: fix linting errors * ci(config.yml): cd into correct dir for checks * fix(proxy_server.py): fix linting error * fix(utils.py): fix bare except causes ruff linting errors * fix: ruff - fix remaining linting errors * fix(clickhouse.py): use standard logging object * fix(__init__.py): fix unprotected import * fix: ruff - fix linting errors * fix: fix linting errors * ci(config.yml): cleanup code qa step (formatting handled in local_testing) * fix(_health_endpoints.py): fix ruff linting errors * ci(config.yml): just use ruff in check_code_quality pipeline for now * build(custom_guardrail.py): include missing file * style(embedding_handler.py): fix ruff check
318 lines
11 KiB
Python
318 lines
11 KiB
Python
from typing import Any, Coroutine, Dict, List, Optional, Union
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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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import litellm
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from litellm._logging import verbose_logger
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from litellm.llms.base import BaseLLM
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from litellm.types.llms.openai import *
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def get_azure_openai_client(
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api_key: Optional[str],
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api_base: 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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organization: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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_is_async: bool = False,
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) -> Optional[Union[AzureOpenAI, AsyncAzureOpenAI]]:
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received_args = locals()
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None
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if client is None:
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data = {}
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for k, v in received_args.items():
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if k == "self" or k == "client" or k == "_is_async":
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pass
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elif k == "api_base" and v is not None:
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data["azure_endpoint"] = v
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elif v is not None:
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data[k] = v
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if "api_version" not in data:
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data["api_version"] = litellm.AZURE_DEFAULT_API_VERSION
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if _is_async is True:
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openai_client = AsyncAzureOpenAI(**data)
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else:
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openai_client = AzureOpenAI(**data) # type: ignore
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else:
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openai_client = client
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return openai_client
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class AzureOpenAIFilesAPI(BaseLLM):
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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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) -> FileObject:
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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 response
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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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) -> Union[FileObject, Coroutine[Any, Any, FileObject]]:
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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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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timeout=timeout,
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max_retries=max_retries,
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client=client,
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_is_async=_is_async,
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)
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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( # type: ignore
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create_file_data=create_file_data, openai_client=openai_client
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)
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response = openai_client.files.create(**create_file_data)
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return response
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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 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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) -> Union[
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HttpxBinaryResponseContent, Coroutine[Any, Any, HttpxBinaryResponseContent]
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]:
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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api_version=api_version,
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max_retries=max_retries,
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organization=None,
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client=client,
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_is_async=_is_async,
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)
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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 = openai_client.files.content(**file_content_request)
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return 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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):
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=None,
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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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)
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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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):
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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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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)
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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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):
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=None, # openai param
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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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)
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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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