update the vector cli for server, test=doc

demos/streaming_asr_server/websocket_client.py

@@ -37,7 +37,7 @@ def main(args):
     if args.wavfile and os.path.exists(args.wavfile):
         logger.info(f"start to process the wavscp: {args.wavfile}")
         result = loop.run_until_complete(handler.run(args.wavfile))
-        # result = result["result"]
+        result = result["result"]
         logger.info(f"asr websocket client finished : {result}")
 
     # support to process batch audios from wav.scp 

paddlespeech/cli/vector/infer.py

@@ -285,8 +285,10 @@ class VectorExecutor(BaseExecutor):
                                                         Defaults to None.
             ckpt_path (Optional[os.PathLike], optional): the pretrained model path, which is stored in the disk. 
                                                          Defaults to None.
+            task (str, optional): the model task type
         """
         # stage 0: avoid to init the mode again
+        self.task = task
         if hasattr(self, "model"):
             logger.info("Model has been initialized")
             return
@@ -435,6 +437,7 @@ class VectorExecutor(BaseExecutor):
         if self.sample_rate != 16000 and self.sample_rate != 8000:
             logger.error(
                 "invalid sample rate, please input --sr 8000 or --sr 16000")
+            logger.error(f"The model sample rate: {self.sample_rate}, the external sample rate is: {sample_rate}")
             return False
 
         if isinstance(audio_file, (str, os.PathLike)):

paddlespeech/server/bin/paddlespeech_client.py

@@ -602,7 +602,11 @@ class VectorClientExecutor(BaseExecutor):
             default=None,
             help='sentence to be process by text server.')
         self.parser.add_argument(
-            '--task', type=str, default="spk", help="The vector service task")
+            '--task',
+            type=str,
+            default="spk",
+            choices=["spk", "score"],
+            help="The vector service task")
         self.parser.add_argument(
             "--enroll", type=str, default=None, help="The enroll audio")
         self.parser.add_argument(

paddlespeech/server/engine/vector/python/vector_engine.py

@@ -99,8 +99,8 @@ class PaddleVectorConnectionHandler:
         """extract the audio embedding
 
         Args:
-            audio (_type_): _description_
+            audio (str): the audio data
-            sample_rate (int, optional): _description_. Defaults to 16000.
+            sample_rate (int, optional): the audio sample rate. Defaults to 16000.
         """
         # we can not reuse the cache io.BytesIO(audio) data, 
         # because the soundfile will change the io.BytesIO(audio) to the end

paddlespeech/server/restful/request.py

@@ -115,7 +115,7 @@ class VectorScoreRequest(BaseModel):
     {
         "enroll_audio": "exSI6ICJlbiIsCgkgICAgInBvc2l0aW9uIjogImZhbHNlIgoJf...",
         "test_audio": "exSI6ICJlbiIsCgkgICAgInBvc2l0aW9uIjogImZhbHNlIgoJf...",
-        "task": "spk",
+        "task": "score",
         "audio_format": "wav",
         "sample_rate": 16000,
     }