mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 18:54:30 +00:00
053b0e741f
* test: fix import for test
* fix: fix bad error string
* docs: cleanup files docs
* fix(files/main.py): cleanup error string
* style: initial commit with a provider/config pattern for files api
google ai studio files api onboarding
* fix: test
* feat(gemini/files/transformation.py): support gemini files api response transformation
* fix(gemini/files/transformation.py): return file id as gemini uri
allows id to be passed in to chat completion request, just like openai
* feat(llm_http_handler.py): support async route for files api on llm_http_handler
* fix: fix linting errors
* fix: fix model info check
* fix: fix ruff errors
* fix: fix linting errors
* Revert "fix: fix linting errors"
This reverts commit 926a5a527f.
* fix: fix linting errors
* test: fix test
* test: fix tests
96 lines
3.2 KiB
Python
96 lines
3.2 KiB
Python
from typing import Any, Coroutine, Optional, Union
|
|
|
|
import httpx
|
|
|
|
from litellm import LlmProviders
|
|
from litellm.integrations.gcs_bucket.gcs_bucket_base import (
|
|
GCSBucketBase,
|
|
GCSLoggingConfig,
|
|
)
|
|
from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
|
|
from litellm.types.llms.openai import CreateFileRequest, OpenAIFileObject
|
|
from litellm.types.llms.vertex_ai import VERTEX_CREDENTIALS_TYPES
|
|
|
|
from .transformation import VertexAIFilesTransformation
|
|
|
|
vertex_ai_files_transformation = VertexAIFilesTransformation()
|
|
|
|
|
|
class VertexAIFilesHandler(GCSBucketBase):
|
|
"""
|
|
Handles Calling VertexAI in OpenAI Files API format v1/files/*
|
|
|
|
This implementation uploads files on GCS Buckets
|
|
"""
|
|
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.async_httpx_client = get_async_httpx_client(
|
|
llm_provider=LlmProviders.VERTEX_AI,
|
|
)
|
|
|
|
async def async_create_file(
|
|
self,
|
|
create_file_data: CreateFileRequest,
|
|
api_base: Optional[str],
|
|
vertex_credentials: Optional[VERTEX_CREDENTIALS_TYPES],
|
|
vertex_project: Optional[str],
|
|
vertex_location: Optional[str],
|
|
timeout: Union[float, httpx.Timeout],
|
|
max_retries: Optional[int],
|
|
) -> OpenAIFileObject:
|
|
gcs_logging_config: GCSLoggingConfig = await self.get_gcs_logging_config(
|
|
kwargs={}
|
|
)
|
|
headers = await self.construct_request_headers(
|
|
vertex_instance=gcs_logging_config["vertex_instance"],
|
|
service_account_json=gcs_logging_config["path_service_account"],
|
|
)
|
|
bucket_name = gcs_logging_config["bucket_name"]
|
|
(
|
|
logging_payload,
|
|
object_name,
|
|
) = vertex_ai_files_transformation.transform_openai_file_content_to_vertex_ai_file_content(
|
|
openai_file_content=create_file_data.get("file")
|
|
)
|
|
gcs_upload_response = await self._log_json_data_on_gcs(
|
|
headers=headers,
|
|
bucket_name=bucket_name,
|
|
object_name=object_name,
|
|
logging_payload=logging_payload,
|
|
)
|
|
|
|
return vertex_ai_files_transformation.transform_gcs_bucket_response_to_openai_file_object(
|
|
create_file_data=create_file_data,
|
|
gcs_upload_response=gcs_upload_response,
|
|
)
|
|
|
|
def create_file(
|
|
self,
|
|
_is_async: bool,
|
|
create_file_data: CreateFileRequest,
|
|
api_base: Optional[str],
|
|
vertex_credentials: Optional[VERTEX_CREDENTIALS_TYPES],
|
|
vertex_project: Optional[str],
|
|
vertex_location: Optional[str],
|
|
timeout: Union[float, httpx.Timeout],
|
|
max_retries: Optional[int],
|
|
) -> Union[OpenAIFileObject, Coroutine[Any, Any, OpenAIFileObject]]:
|
|
"""
|
|
Creates a file on VertexAI GCS Bucket
|
|
|
|
Only supported for Async litellm.acreate_file
|
|
"""
|
|
|
|
if _is_async:
|
|
return self.async_create_file(
|
|
create_file_data=create_file_data,
|
|
api_base=api_base,
|
|
vertex_credentials=vertex_credentials,
|
|
vertex_project=vertex_project,
|
|
vertex_location=vertex_location,
|
|
timeout=timeout,
|
|
max_retries=max_retries,
|
|
)
|
|
|
|
return None # type: ignore
|