From 6427c834dfd97b1f05c6659cdc7ccf010bf82fe1 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期一, 24 四月 2023 19:50:07 +0800
Subject: [PATCH] update

---
 funasr/runtime/python/grpc/grpc_server.py |   47 +++++++++++++++++++++++++++++++----------------
 1 files changed, 31 insertions(+), 16 deletions(-)

diff --git a/funasr/runtime/python/grpc/grpc_server.py b/funasr/runtime/python/grpc/grpc_server.py
index 9165c1f..4fd4f95 100644
--- a/funasr/runtime/python/grpc/grpc_server.py
+++ b/funasr/runtime/python/grpc/grpc_server.py
@@ -1,23 +1,33 @@
 from concurrent import futures
 import grpc
 import json
-import paraformer_pb2
-import paraformer_pb2_grpc
 import time
 
+import paraformer_pb2_grpc
 from paraformer_pb2 import Response
-from modelscope.pipelines import pipeline
-from modelscope.utils.constant import Tasks
 
 
 class ASRServicer(paraformer_pb2_grpc.ASRServicer):
-    def __init__(self, user_allowed, model, sample_rate):
+    def __init__(self, user_allowed, model, sample_rate, backend, onnx_dir, vad_model='', punc_model=''):
         print("ASRServicer init")
+        self.backend = backend
         self.init_flag = 0
         self.client_buffers = {}
         self.client_transcription = {}
         self.auth_user = user_allowed.split("|")
-        self.inference_16k_pipeline = pipeline(task=Tasks.auto_speech_recognition, model=model)
+        if self.backend == "pipeline":
+            try:
+                from modelscope.pipelines import pipeline
+                from modelscope.utils.constant import Tasks
+            except ImportError:
+                raise ImportError(f"Please install modelscope")
+            self.inference_16k_pipeline = pipeline(task=Tasks.auto_speech_recognition, model=model, vad_model=vad_model, punc_model=punc_model)
+        elif self.backend == "onnxruntime":
+            try:
+                from funasr_onnx import Paraformer
+            except ImportError:
+                raise ImportError(f"Please install onnxruntime environment")
+            self.inference_16k_pipeline = Paraformer(model_dir=onnx_dir)
         self.sample_rate = sample_rate
 
     def clear_states(self, user):
@@ -69,7 +79,7 @@
                 if req.user not in self.client_buffers:
                     result = {}
                     result["success"] = True
-                    result["detail"] = "waiting_for_voice"
+                    result["detail"] = "waiting_for_more_voice"
                     result["text"] = ""
                     yield Response(sentence=json.dumps(result), user=req.user, action="waiting", language=req.language)
                 else:
@@ -86,17 +96,22 @@
                         delay_str = str(end_time - begin_time)
                         result = {}
                         result["success"] = True
-                        result["detail"] = "finish_sentence_data_is_not_long_enough"
+                        result["detail"] = "waiting_for_more_voice"
                         result["server_delay_ms"] = delay_str
                         result["text"] = ""
-                        print ("user: %s , delay(ms): %s, error: %s " % (req.user, delay_str, "data_is_not_long_enough"))
-                        yield Response(sentence=json.dumps(result), user=req.user, action="finish", language=req.language)
-                    else:                           
-                        asr_result = self.inference_16k_pipeline(audio_in=tmp_data, audio_fs = self.sample_rate)
-                        if "text" in asr_result:
-                            asr_result = asr_result['text']
-                        else:
-                            asr_result = ""
+                        print ("user: %s , delay(ms): %s, info: %s " % (req.user, delay_str, "waiting_for_more_voice"))
+                        yield Response(sentence=json.dumps(result), user=req.user, action="waiting", language=req.language)
+                    else:
+                        if self.backend == "pipeline":
+                            asr_result = self.inference_16k_pipeline(audio_in=tmp_data, audio_fs = self.sample_rate)
+                            if "text" in asr_result:
+                                asr_result = asr_result['text']
+                            else:
+                                asr_result = ""
+                        elif self.backend == "onnxruntime":
+                            from funasr_onnx.utils.frontend import load_bytes
+                            array = load_bytes(tmp_data)
+                            asr_result = self.inference_16k_pipeline(array)[0]
                         end_time = int(round(time.time() * 1000))
                         delay_str = str(end_time - begin_time)
                         print ("user: %s , delay(ms): %s, text: %s " % (req.user, delay_str, asr_result))

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