fix refactor - add batches endpoints proxy server.py

litellm/proxy/proxy_server.py

@@ -4563,6 +4563,230 @@ async def run_thread(
             )
 
 
+######################################################################
+
+#                          /v1/batches Endpoints
+
+
+######################################################################
+@router.post(
+    "/v1/batches",
+    dependencies=[Depends(user_api_key_auth)],
+    tags=["batch"],
+)
+@router.post(
+    "/batches",
+    dependencies=[Depends(user_api_key_auth)],
+    tags=["batch"],
+)
+async def create_batch(
+    request: Request,
+    fastapi_response: Response,
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+):
+    """
+    Create large batches of API requests for asynchronous processing.
+    This is the equivalent of POST https://api.openai.com/v1/batch
+    Supports Identical Params as: https://platform.openai.com/docs/api-reference/batch
+
+    Example Curl
+    ```
+    curl http://localhost:4000/v1/batches \
+        -H "Authorization: Bearer sk-1234" \
+        -H "Content-Type: application/json" \
+        -d '{
+            "input_file_id": "file-abc123",
+            "endpoint": "/v1/chat/completions",
+            "completion_window": "24h"
+    }'
+    ```
+    """
+    global proxy_logging_obj
+    data: Dict = {}
+    try:
+        # Use orjson to parse JSON data, orjson speeds up requests significantly
+        form_data = await request.form()
+        data = {key: value for key, value in form_data.items() if key != "file"}
+
+        # Include original request and headers in the data
+        data = await add_litellm_data_to_request(
+            data=data,
+            request=request,
+            general_settings=general_settings,
+            user_api_key_dict=user_api_key_dict,
+            version=version,
+            proxy_config=proxy_config,
+        )
+
+        _create_batch_data = CreateBatchRequest(**data)
+
+        # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
+        response = await litellm.acreate_batch(
+            custom_llm_provider="openai", **_create_batch_data
+        )
+
+        ### ALERTING ###
+        data["litellm_status"] = "success"  # used for alerting
+
+        ### RESPONSE HEADERS ###
+        hidden_params = getattr(response, "_hidden_params", {}) or {}
+        model_id = hidden_params.get("model_id", None) or ""
+        cache_key = hidden_params.get("cache_key", None) or ""
+        api_base = hidden_params.get("api_base", None) or ""
+
+        fastapi_response.headers.update(
+            get_custom_headers(
+                user_api_key_dict=user_api_key_dict,
+                model_id=model_id,
+                cache_key=cache_key,
+                api_base=api_base,
+                version=version,
+                model_region=getattr(user_api_key_dict, "allowed_model_region", ""),
+            )
+        )
+
+        return response
+    except Exception as e:
+        data["litellm_status"] = "fail"  # used for alerting
+        await proxy_logging_obj.post_call_failure_hook(
+            user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
+        )
+        verbose_proxy_logger.error(
+            "litellm.proxy.proxy_server.create_batch(): Exception occured - {}".format(
+                str(e)
+            )
+        )
+        verbose_proxy_logger.debug(traceback.format_exc())
+        if isinstance(e, HTTPException):
+            raise ProxyException(
+                message=getattr(e, "message", str(e.detail)),
+                type=getattr(e, "type", "None"),
+                param=getattr(e, "param", "None"),
+                code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
+            )
+        else:
+            error_msg = f"{str(e)}"
+            raise ProxyException(
+                message=getattr(e, "message", error_msg),
+                type=getattr(e, "type", "None"),
+                param=getattr(e, "param", "None"),
+                code=getattr(e, "status_code", 500),
+            )
+
+
+@router.get(
+    "/v1/batches{batch_id}",
+    dependencies=[Depends(user_api_key_auth)],
+    tags=["batch"],
+)
+@router.get(
+    "/batches{batch_id}",
+    dependencies=[Depends(user_api_key_auth)],
+    tags=["batch"],
+)
+async def retrieve_batch(
+    request: Request,
+    fastapi_response: Response,
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+    batch_id: str = Path(
+        title="Batch ID to retrieve", description="The ID of the batch to retrieve"
+    ),
+):
+    """
+    Retrieves a batch.
+    This is the equivalent of GET https://api.openai.com/v1/batches/{batch_id}
+    Supports Identical Params as: https://platform.openai.com/docs/api-reference/batch/retrieve
+
+    Example Curl
+    ```
+    curl http://localhost:4000/v1/batches/batch_abc123 \
+    -H "Authorization: Bearer sk-1234" \
+    -H "Content-Type: application/json" \
+
+    ```
+    """
+    global proxy_logging_obj
+    data: Dict = {}
+    try:
+        # Use orjson to parse JSON data, orjson speeds up requests significantly
+        form_data = await request.form()
+        data = {key: value for key, value in form_data.items() if key != "file"}
+
+        # Include original request and headers in the data
+        data = await add_litellm_data_to_request(
+            data=data,
+            request=request,
+            general_settings=general_settings,
+            user_api_key_dict=user_api_key_dict,
+            version=version,
+            proxy_config=proxy_config,
+        )
+
+        _retrieve_batch_request = RetrieveBatchRequest(
+            batch_id=batch_id,
+        )
+
+        # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
+        response = await litellm.aretrieve_batch(
+            custom_llm_provider="openai", **_retrieve_batch_request
+        )
+
+        ### ALERTING ###
+        data["litellm_status"] = "success"  # used for alerting
+
+        ### RESPONSE HEADERS ###
+        hidden_params = getattr(response, "_hidden_params", {}) or {}
+        model_id = hidden_params.get("model_id", None) or ""
+        cache_key = hidden_params.get("cache_key", None) or ""
+        api_base = hidden_params.get("api_base", None) or ""
+
+        fastapi_response.headers.update(
+            get_custom_headers(
+                user_api_key_dict=user_api_key_dict,
+                model_id=model_id,
+                cache_key=cache_key,
+                api_base=api_base,
+                version=version,
+                model_region=getattr(user_api_key_dict, "allowed_model_region", ""),
+            )
+        )
+
+        return response
+    except Exception as e:
+        data["litellm_status"] = "fail"  # used for alerting
+        await proxy_logging_obj.post_call_failure_hook(
+            user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
+        )
+        verbose_proxy_logger.error(
+            "litellm.proxy.proxy_server.retrieve_batch(): Exception occured - {}".format(
+                str(e)
+            )
+        )
+        verbose_proxy_logger.debug(traceback.format_exc())
+        if isinstance(e, HTTPException):
+            raise ProxyException(
+                message=getattr(e, "message", str(e.detail)),
+                type=getattr(e, "type", "None"),
+                param=getattr(e, "param", "None"),
+                code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
+            )
+        else:
+            error_traceback = traceback.format_exc()
+            error_msg = f"{str(e)}"
+            raise ProxyException(
+                message=getattr(e, "message", error_msg),
+                type=getattr(e, "type", "None"),
+                param=getattr(e, "param", "None"),
+                code=getattr(e, "status_code", 500),
+            )
+
+
+######################################################################
+
+#            END OF  /v1/batches Endpoints Implementation
+
+######################################################################
+
 ######################################################################
 
 #                          /v1/files Endpoints