Docsum Gateway Fix (opea-project#902)

* update gateway

Signed-off-by: Mustafa <[email protected]>

* update the gateway

Signed-off-by: Mustafa <[email protected]>

* update the gateway

Signed-off-by: Mustafa <[email protected]>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Signed-off-by: Mustafa <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: MSCetin37

comps/cores/mega/gateway.py

@@ -419,12 +419,62 @@ def __init__(self, megaservice, host="0.0.0.0", port=8888):
             output_datatype=ChatCompletionResponse,
         )
 
-    async def handle_request(self, request: Request):
-        data = await request.json()
-        stream_opt = data.get("stream", True)
-        chat_request = ChatCompletionRequest.model_validate(data)
+    async def handle_request(self, request: Request, files: List[UploadFile] = File(default=None)):
+
+        if "application/json" in request.headers.get("content-type"):
+            data = await request.json()
+            stream_opt = data.get("stream", True)
+            chat_request = ChatCompletionRequest.model_validate(data)
+            prompt = self._handle_message(chat_request.messages)
+
+            initial_inputs_data = {data["type"]: prompt}
+
+        elif "multipart/form-data" in request.headers.get("content-type"):
+            data = await request.form()
+            stream_opt = data.get("stream", True)
+            chat_request = ChatCompletionRequest.model_validate(data)
+
+            data_type = data.get("type")
+
+            file_summaries = []
+            if files:
+                for file in files:
+                    file_path = f"/tmp/{file.filename}"
+
+                    if data_type is not None and data_type in ["audio", "video"]:
+                        raise ValueError(
+                            "Audio and Video file uploads are not supported in docsum with curl request, please use the UI."
+                        )
+
+                    else:
+                        import aiofiles
+
+                        async with aiofiles.open(file_path, "wb") as f:
+                            await f.write(await file.read())
+
+                        docs = read_text_from_file(file, file_path)
+                        os.remove(file_path)
+
+                        if isinstance(docs, list):
+                            file_summaries.extend(docs)
+                        else:
+                            file_summaries.append(docs)
+
+            if file_summaries:
+                prompt = self._handle_message(chat_request.messages) + "\n".join(file_summaries)
+            else:
+                prompt = self._handle_message(chat_request.messages)
+
+            data_type = data.get("type")
+            if data_type is not None:
+                initial_inputs_data = {}
+                initial_inputs_data[data_type] = prompt
+            else:
+                initial_inputs_data = {"query": prompt}
+
+        else:
+            raise ValueError(f"Unknown request type: {request.headers.get('content-type')}")
 
-        prompt = self._handle_message(chat_request.messages)
         parameters = LLMParams(
             max_tokens=chat_request.max_tokens if chat_request.max_tokens else 1024,
             top_k=chat_request.top_k if chat_request.top_k else 10,
@@ -434,12 +484,14 @@ async def handle_request(self, request: Request):
             presence_penalty=chat_request.presence_penalty if chat_request.presence_penalty else 0.0,
             repetition_penalty=chat_request.repetition_penalty if chat_request.repetition_penalty else 1.03,
             streaming=stream_opt,
-            language=chat_request.language if chat_request.language else "auto",
             model=chat_request.model if chat_request.model else None,
+            language=chat_request.language if chat_request.language else "auto",
         )
+
         result_dict, runtime_graph = await self.megaservice.schedule(
-            initial_inputs={data["type"]: prompt}, llm_parameters=parameters
+            initial_inputs=initial_inputs_data, llm_parameters=parameters
         )
+
         for node, response in result_dict.items():
             # Here it suppose the last microservice in the megaservice is LLM.
             if (