feat(log):add_request_and_response_log (#3392)

fastdeploy/entrypoints/openai/api_server.py

@@ -244,6 +244,7 @@ async def create_chat_completion(request: ChatCompletionRequest):
     """
     Create a chat completion for the provided prompt and parameters.
     """
+    api_server_logger.info(f"Chat Received request: {request.model_dump_json()}")
     if app.state.dynamic_load_weight:
         status, msg = app.state.engine_client.is_workers_alive()
         if not status:
@@ -272,6 +273,7 @@ async def create_completion(request: CompletionRequest):
     """
     Create a completion for the provided prompt and parameters.
     """
+    api_server_logger.info(f"Completion Received request: {request.model_dump_json()}")
     if app.state.dynamic_load_weight:
         status, msg = app.state.engine_client.is_workers_alive()
         if not status:

fastdeploy/entrypoints/openai/serving_chat.py

@@ -239,6 +239,7 @@ class OpenAIServingChat:
                                     prompt_tokens_details=PromptTokenUsageInfo(cached_tokens=num_cached_tokens),
                                 )
                             yield f"data: {chunk.model_dump_json(exclude_unset=True)} \n\n"
+                            api_server_logger.info(f"Chat Streaming response send_idx 0: {chunk.model_dump_json()}")
                         first_iteration = False
 
                     output = res["outputs"]
@@ -265,6 +266,7 @@ class OpenAIServingChat:
                         logprobs=logprobs_res,
                         arrival_time=arrival_time,
                     )
+
                     if res["finished"]:
                         num_choices -= 1
                         work_process_metrics.e2e_request_latency.observe(
@@ -299,6 +301,9 @@ 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 = []
 
                 if choices:
@@ -452,13 +457,15 @@ class OpenAIServingChat:
             prompt_tokens_details=PromptTokenUsageInfo(cached_tokens=final_res.get("num_cached_tokens", 0)),
         )
         work_process_metrics.e2e_request_latency.observe(time.time() - final_res["metrics"]["request_start_time"])
-        return ChatCompletionResponse(
+        res = ChatCompletionResponse(
             id=request_id,
             created=created_time,
             model=model_name,
             choices=choices,
             usage=usage,
         )
+        api_server_logger.info(f"Chat response: {res.model_dump_json()}")
+        return res
 
     def _create_chat_logprobs(
         self,

fastdeploy/entrypoints/openai/serving_completion.py

@@ -221,8 +221,7 @@ class OpenAIServingCompletion:
                         valid_results[rid] = data
                         num_choices -= 1
                         break
-
-            return self.request_output_to_completion_response(
+            res = self.request_output_to_completion_response(
                 final_res_batch=valid_results,
                 request=request,
                 request_id=request_id,
@@ -232,6 +231,8 @@ class OpenAIServingCompletion:
                 completion_batched_token_ids=completion_batched_token_ids,
                 text_after_process_list=text_after_process_list,
             )
+            api_server_logger.info(f"Completion response: {res.model_dump_json()}")
+            return res
         except Exception as e:
             api_server_logger.error(f"Error in completion_full_generator: {e}", exc_info=True)
             raise
@@ -322,6 +323,9 @@ class OpenAIServingCompletion:
                                 ],
                             )
                             yield f"data: {chunk.model_dump_json(exclude_unset=True)}\n\n"
+                            api_server_logger.info(
+                                f"Completion Streaming response send_idx 0: {chunk.model_dump_json()}"
+                            )
                         first_iteration[idx] = False
 
                     self.engine_client.data_processor.process_response_dict(
@@ -358,6 +362,15 @@ class OpenAIServingCompletion:
                         choices[-1].finish_reason = self.calc_finish_reason(
                             request.max_tokens, output_tokens[idx], output
                         )
+                    send_idx = output.get("send_idx")
+                    # 只有当 send_idx 明确为 0 时才记录日志
+                    if send_idx == 0 and not request.return_token_ids:
+                        chunk_temp = chunk
+                        chunk_temp.choices = choices
+                        api_server_logger.info(
+                            f"Completion Streaming response send_idx 0: {chunk_temp.model_dump_json()}"
+                        )
+                        del chunk_temp
 
                     if len(choices) == max_streaming_response_tokens or res["finished"]:
                         chunk = CompletionStreamResponse(
@@ -383,6 +396,7 @@ class OpenAIServingCompletion:
                                 ),
                             )
                             yield f"data: {usage_chunk.model_dump_json(exclude_unset=True)}\n\n"
+                        api_server_logger.info(f"Completion Streaming response last send: {chunk.model_dump_json()}")
                 if choices:
                     chunk.choices = choices
                     yield f"data: {chunk.model_dump_json(exclude_unset=True)}\n\n"