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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, FileObject
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,
)
pass
async def async_create_file(
self,
create_file_data: CreateFileRequest,
api_base: Optional[str],
vertex_credentials: Optional[str],
vertex_project: Optional[str],
vertex_location: Optional[str],
timeout: Union[float, httpx.Timeout],
max_retries: Optional[int],
):
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[str],
vertex_project: Optional[str],
vertex_location: Optional[str],
timeout: Union[float, httpx.Timeout],
max_retries: Optional[int],
) -> Union[FileObject, Coroutine[Any, Any, FileObject]]:
"""
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
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