[BugFix] fix control signal release failed (#3390)

* [BugFix] fix control signal release failed

* [BugFix] fix control signal release failed

* update

* update

* update

fastdeploy/entrypoints/openai/api_server.py

@@ -175,10 +175,10 @@ async def connection_manager():
         await asyncio.wait_for(connection_semaphore.acquire(), timeout=0.001)
         yield
     except asyncio.TimeoutError:
-        api_server_logger.info(f"Reach max request release: {connection_semaphore.status()}")
+        api_server_logger.info(f"Reach max request concurrency, semaphore status: {connection_semaphore.status()}")
-        if connection_semaphore.locked():
+        raise HTTPException(
-            connection_semaphore.release()
+            status_code=429, detail=f"Too many requests,current max concurrency is {args.max_concurrency}"
-        raise HTTPException(status_code=429, detail="Too many requests")
+        )
 
 
 # TODO 传递真实引擎值 通过pid 获取状态
@@ -265,9 +265,11 @@ async def create_chat_completion(request: ChatCompletionRequest):
             inject_to_metadata(request)
             generator = await app.state.chat_handler.create_chat_completion(request)
             if isinstance(generator, ErrorResponse):
+                api_server_logger.debug(f"release: {connection_semaphore.status()}")
                 connection_semaphore.release()
                 return JSONResponse(content={"detail": generator.model_dump()}, status_code=generator.code)
             elif isinstance(generator, ChatCompletionResponse):
+                api_server_logger.debug(f"release: {connection_semaphore.status()}")
                 connection_semaphore.release()
                 return JSONResponse(content=generator.model_dump())
             else:

fastdeploy/entrypoints/openai/serving_chat.py

@@ -78,47 +78,47 @@ class OpenAIServingChat:
             err_msg = f"Only master node can accept completion request, please send request to master node: {self.pod_ips[0]}"
             api_server_logger.error(err_msg)
             return ErrorResponse(message=err_msg, code=400)
-
-        if request.user is not None:
-            request_id = f"chatcmpl-{request.user}-{uuid.uuid4()}"
-        else:
-            request_id = f"chatcmpl-{uuid.uuid4()}"
-        api_server_logger.info(f"create chat completion request: {request_id}")
-        text_after_process = None
         try:
-            current_req_dict = request.to_dict_for_infer(request_id)
-            if "chat_template" not in current_req_dict:
-                current_req_dict["chat_template"] = self.chat_template
-            current_req_dict["arrival_time"] = time.time()
-            prompt_token_ids = self.engine_client.format_and_add_data(current_req_dict)
-            text_after_process = current_req_dict.get("text_after_process")
-            if isinstance(prompt_token_ids, np.ndarray):
-                prompt_token_ids = prompt_token_ids.tolist()
-        except Exception as e:
-            return ErrorResponse(code=400, message=str(e))
-
-        del current_req_dict
-        try:
-            api_server_logger.debug(f"{self.engine_client.semaphore.status()}")
             if self.max_waiting_time < 0:
                 await self.engine_client.semaphore.acquire()
             else:
                 await asyncio.wait_for(self.engine_client.semaphore.acquire(), timeout=self.max_waiting_time)
-        except Exception:
+            api_server_logger.info(f"current {self.engine_client.semaphore.status()}")
-            return ErrorResponse(code=408, message=f"Request queued time exceed {self.max_waiting_time}")
 
-        if request.stream:
+            if request.user is not None:
-            return self.chat_completion_stream_generator(
+                request_id = f"chatcmpl-{request.user}-{uuid.uuid4()}"
-                request, request_id, request.model, prompt_token_ids, text_after_process
+            else:
-            )
+                request_id = f"chatcmpl-{uuid.uuid4()}"
-        else:
+            api_server_logger.info(f"create chat completion request: {request_id}")
+            text_after_process = None
             try:
-                return await self.chat_completion_full_generator(
+                current_req_dict = request.to_dict_for_infer(request_id)
-                    request, request_id, request.model, prompt_token_ids, text_after_process
+                if "chat_template" not in current_req_dict:
-                )
+                    current_req_dict["chat_template"] = self.chat_template
+                current_req_dict["arrival_time"] = time.time()
+                prompt_token_ids = self.engine_client.format_and_add_data(current_req_dict)
+                text_after_process = current_req_dict.get("text_after_process")
+                if isinstance(prompt_token_ids, np.ndarray):
+                    prompt_token_ids = prompt_token_ids.tolist()
             except Exception as e:
                 return ErrorResponse(code=400, message=str(e))
 
+            del current_req_dict
+
+            if request.stream:
+                return self.chat_completion_stream_generator(
+                    request, request_id, request.model, prompt_token_ids, text_after_process
+                )
+            else:
+                try:
+                    return await self.chat_completion_full_generator(
+                        request, request_id, request.model, prompt_token_ids, text_after_process
+                    )
+                except Exception as e:
+                    return ErrorResponse(code=400, message=str(e))
+        except Exception:
+            return ErrorResponse(code=408, message=f"Request queued time exceed {self.max_waiting_time}")
+
     def _create_streaming_error_response(self, message: str) -> str:
         error_response = ErrorResponse(
             code=400,
@@ -254,6 +254,7 @@ class OpenAIServingChat:
                         logprobs_res = self._create_chat_logprobs(
                             output_top_logprobs, request.logprobs, request.top_logprobs
                         )
+
                     if self.engine_client.data_processor.tool_parser_obj and not res["finished"]:
                         tool_delta_message = output["tool_delta_message"]
                         if tool_delta_message is None:
@@ -277,7 +278,6 @@ class OpenAIServingChat:
                         logprobs=logprobs_res,
                         arrival_time=arrival_time,
                     )
-
                     if res["finished"]:
                         num_choices -= 1
                         work_process_metrics.e2e_request_latency.observe(
@@ -309,7 +309,6 @@ class OpenAIServingChat:
                     if len(choices) == max_streaming_response_tokens or res["finished"]:
                         chunk.choices = choices
                         yield f"data: {chunk.model_dump_json(exclude_unset=True)}\n\n"
-                        # 打印尾包
                         if res["finished"]:
                             api_server_logger.info(f"Chat Streaming response last send: {chunk.model_dump_json()}")
                         choices = []
@@ -417,8 +416,9 @@ class OpenAIServingChat:
                 if task_is_finished:
                     break
         finally:
-            self.engine_client.semaphore.release()
             dealer.close()
+            self.engine_client.semaphore.release()
+            api_server_logger.info(f"release {self.engine_client.semaphore.status()}")
 
         choices = []
         output = final_res["outputs"]

fastdeploy/entrypoints/openai/serving_completion.py

@@ -101,6 +101,14 @@ class OpenAIServingCompletion:
         api_server_logger.info(f"start inference for request {num_choices}")
         prompt_batched_token_ids = []
         text_after_process_list = []
+        try:
+            if self.max_waiting_time < 0:
+                await self.engine_client.semaphore.acquire()
+            else:
+                await asyncio.wait_for(self.engine_client.semaphore.acquire(), timeout=self.max_waiting_time)
+        except Exception:
+            return ErrorResponse(code=408, message=f"Request queued time exceed {self.max_waiting_time}")
+
         try:
             for idx, prompt in enumerate(request_prompts):
                 request_id_idx = f"{request_id}-{idx}"
@@ -117,14 +125,6 @@ class OpenAIServingCompletion:
 
                 del current_req_dict
 
-            try:
-                if self.max_waiting_time < 0:
-                    await self.engine_client.semaphore.acquire()
-                else:
-                    await asyncio.wait_for(self.engine_client.semaphore.acquire(), timeout=self.max_waiting_time)
-            except Exception:
-                return ErrorResponse(code=408, message=f"Request queued time exceed {self.max_waiting_time}")
-
             if request.stream:
                 return self.completion_stream_generator(
                     request=request,

fastdeploy/inter_communicator/zmq_client.py

@@ -31,7 +31,7 @@ class ZmqClient:
     """
 
     def __init__(self, name, mode):
-        self.context = zmq.Context()
+        self.context = zmq.Context(4)
         self.socket = self.context.socket(mode)
         self.file_name = f"/dev/shm/{name}.socket"
         self.router_path = f"/dev/shm/router_{name}.ipc"
@@ -67,6 +67,7 @@ class ZmqClient:
         """
         self.router = self.context.socket(zmq.ROUTER)
         self.router.setsockopt(zmq.SNDHWM, self.ZMQ_SNDHWM)
+        self.router.setsockopt(zmq.ROUTER_MANDATORY, 1)
         self.router.setsockopt(zmq.SNDTIMEO, -1)
         self.router.bind(f"ipc://{self.router_path}")
 
@@ -125,6 +126,11 @@ class ZmqClient:
                 else:
                     break
 
+        if self.req_dict[req_id] == -1:
+            if data[-1].finished:
+                with self.mutex:
+                    self.req_dict.pop(req_id, None)
+            return
         try:
             start_send = time.time()
             if self.aggregate_send:
@@ -133,7 +139,9 @@ class ZmqClient:
                 result = msgpack.packb([response.to_dict() for response in data])
             self.router.send_multipart([self.req_dict[req_id], b"", result])
             llm_logger.debug(f"send_multipart result: {req_id} len {len(data)} elapse: {time.time()-start_send}")
-
+        except zmq.ZMQError as e:
+            llm_logger.error(f"[{req_id}] zmq error: {e}")
+            self.req_dict[req_id] = -1
         except Exception as e:
             llm_logger.error(f"Send result to zmq client failed: {e}")