two version of R2R are here HEAD master

1 files changed, 97 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/vertex_ai/files/handler.py b/.venv/lib/python3.12/site-packages/litellm/llms/vertex_ai/files/handler.py
new file mode 100644
index 00000000..266169cd
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/llms/vertex_ai/files/handler.py
@@ -0,0 +1,97 @@
+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 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,
+        )
+
+    pass
+
+    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],
+    ):
+        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[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