feat: add synchronous file writing method and enhance async file savi… (#101)

* feat: add synchronous file writing method and enhance async file saving in API server

* refactor: clean up image file handling in API server and improve error message in service

lightx2v/server/api.py

@@ -45,6 +45,11 @@ class ApiServer:
         self.app.include_router(self.files_router)
         self.app.include_router(self.service_router)
 
+    def _write_file_sync(self, file_path: Path, content: bytes) -> None:
+        """同步写入文件到指定路径"""
+        with open(file_path, "wb") as buffer:
+            buffer.write(content)
+
     def _stream_file_response(self, file_path: Path, filename: str | None = None) -> StreamingResponse:
         """Common file streaming response method"""
         assert self.file_service is not None, "File service is not initialized"
@@ -130,32 +135,30 @@ class ApiServer:
             video_duration: int = Form(default=5),
         ):
             """Create video generation task via form"""
-            # Process uploaded image file
-            image_path = ""
             assert self.file_service is not None, "File service is not initialized"
 
-            if image_file and image_file.filename:
-                file_extension = Path(image_file.filename).suffix
+            async def save_file_async(file: UploadFile, target_dir: Path) -> str:
+                """异步保存文件到指定目录"""
+                if not file or not file.filename:
+                    return ""
+
+                file_extension = Path(file.filename).suffix
                 unique_filename = f"{uuid.uuid4()}{file_extension}"
-                image_path = self.file_service.input_image_dir / unique_filename
+                file_path = target_dir / unique_filename
 
-                with open(image_path, "wb") as buffer:
-                    content = await image_file.read()
-                    buffer.write(content)
+                content = await file.read()
 
-                image_path = str(image_path)
+                await asyncio.to_thread(self._write_file_sync, file_path, content)
 
-            audio_path = ""
-            if audio_file and audio_file.filename:
-                file_extension = Path(audio_file.filename).suffix
-                unique_filename = f"{uuid.uuid4()}{file_extension}"
-                audio_path = self.file_service.input_audio_dir / unique_filename
+                return str(file_path)
 
-                with open(audio_path, "wb") as buffer:
-                    content = await audio_file.read()
-                    buffer.write(content)
+            image_path = ""
+            if image_file and image_file.filename:
+                image_path = await save_file_async(image_file, self.file_service.input_image_dir)
 
-                audio_path = str(audio_path)
+            audio_path = ""
+            if audio_file and audio_file.filename:
+                audio_path = await save_file_async(audio_file, self.file_service.input_audio_dir)
 
             message = TaskRequest(
                 prompt=prompt,
@@ -276,6 +279,12 @@ class ApiServer:
             """Get service status"""
             return ServiceStatus.get_status_service()
 
+        @self.service_router.get("/metadata", response_model=dict)
+        async def get_service_metadata():
+            """Get service metadata"""
+            assert self.inference_service is not None, "Inference service is not initialized"
+            return self.inference_service.server_metadata()
+
     def _process_video_generation(self, message: TaskRequest, stop_event: threading.Event):
         assert self.video_service is not None, "Video service is not initialized"
         try:

lightx2v/server/service.py

@@ -186,6 +186,7 @@ class DistributedInferenceService:
         self.is_running = False
 
     def start_distributed_inference(self, args) -> bool:
+        self.args = args
         if self.is_running:
             logger.warning("Distributed inference service is already running")
             return True
@@ -311,6 +312,10 @@ class DistributedInferenceService:
 
         return None
 
+    def server_metadata(self):
+        assert hasattr(self, "args"), "Distributed inference service has not been started. Call start_distributed_inference() first."
+        return {"nproc_per_node": self.args.nproc_per_node, "model_cls": self.args.model_cls, "model_path": self.args.model_path}
+
 
 class VideoGenerationService:
     def __init__(self, file_service: FileService, inference_service: DistributedInferenceService):