del create_background_tasks

Author: shell-nlp

gpt_server/model_worker/base/model_worker_base.py

@@ -318,8 +318,8 @@ async def api_generate_stream(request: Request):
     params.pop("prompt")
     logger.debug(f"params {params}")
     generator = worker.generate_stream_gate(params)
-    background_tasks = create_background_tasks(request_id)
-    return StreamingResponse(generator, background=background_tasks)
+    # background_tasks = create_background_tasks(request_id)
+    return StreamingResponse(generator, background=None)
 
 
 @app.post("/worker_generate_voice_stream")
@@ -331,7 +331,7 @@ async def api_generate_stream(request: Request):
     params["request"] = request
     logger.debug(f"params {params}")
     generator = worker.generate_voice_stream(params)
-    background_tasks = create_background_tasks(request_id)
+    # background_tasks = create_background_tasks(request_id)
     response_format = params["response_format"]
     content_type = {
         "mp3": "audio/mpeg",
@@ -343,7 +343,7 @@ async def api_generate_stream(request: Request):
     }.get(response_format, f"audio/{response_format}")
     return StreamingResponse(
         generator,
-        background=background_tasks,
+        background=None,
         media_type=content_type,
         headers={
             "Content-Disposition": f"attachment; filename=speech.{response_format}",
@@ -365,8 +365,8 @@ async def api_generate(request: Request):
     logger.debug(f"params {params}")
     output = await worker.generate_gate(params)
     release_worker_semaphore()
-    if os.getenv("backend") == "vllm":
-        await worker.backend.engine.abort(request_id)
+    # if os.getenv("backend") == "vllm":
+    #     await worker.backend.engine.abort(request_id)
     return JSONResponse(output)
 
 

gpt_server/model_worker/spark_tts.py

@@ -131,7 +131,9 @@ async def stream_async(self, params):
         async for chunk_data in generator:
             audio = audio_writer.write_chunk(chunk_data, finalize=False)
             yield audio
-        yield audio_writer.write_chunk(finalize=True)
+        end_chunk_data = audio_writer.write_chunk(finalize=True)
+        yield end_chunk_data
+        logger.debug(f"end_chunk_data 长度：{len(end_chunk_data)}")
 
 
 if __name__ == "__main__":