5.2 добавлен Speech Recognition сервер, позволяющий упростить клиент - на клиенте не будет нужен даже VOSK.

- доки обновлены

vosk_asr_server.py

@@ -0,0 +1,132 @@
+# implementation of VOSK server voice recognition
+# origin: https://github.com/alphacep/vosk-server/blob/master/websocket/asr_server.py
+# license: Apache 2.0
+
+# Запускать после первого запуска WEBAPI!! - т.к. использует для настроек файл options/webapi.json
+# для размещения использует порт webapi+1 и тот же хост
+
+import json
+import os
+import sys
+import asyncio
+import pathlib
+import websockets
+import concurrent.futures
+import logging
+from vosk import Model, SpkModel, KaldiRecognizer
+
+version = "1.0"
+
+# main options
+with open('options/webapi.json', 'r', encoding="utf-8") as f:
+    s = f.read(10000000)
+    f.close()
+webapi_options = json.loads(s)
+
+def process_chunk(rec, message):
+    if message == '{"eof" : 1}':
+        return rec.FinalResult(), True
+    elif rec.AcceptWaveform(message):
+        return rec.Result(), False
+    else:
+        return rec.PartialResult(), False
+
+async def recognize(websocket, path):
+    global model
+    global spk_model
+    global args
+    global pool
+
+    loop = asyncio.get_running_loop()
+    rec = None
+    phrase_list = None
+    sample_rate = args.sample_rate
+    show_words = args.show_words
+    max_alternatives = args.max_alternatives
+
+    logging.info('Connection from %s', websocket.remote_address)
+
+    while True:
+
+        message = await websocket.recv()
+
+        # Load configuration if provided
+        if isinstance(message, str) and 'config' in message:
+            jobj = json.loads(message)['config']
+            logging.info("Config %s", jobj)
+            if 'phrase_list' in jobj:
+                phrase_list = jobj['phrase_list']
+            if 'sample_rate' in jobj:
+                sample_rate = float(jobj['sample_rate'])
+            if 'words' in jobj:
+                show_words = bool(jobj['words'])
+            if 'max_alternatives' in jobj:
+                max_alternatives = int(jobj['max_alternatives'])
+            continue
+
+        # Create the recognizer, word list is temporary disabled since not every model supports it
+        if not rec:
+            if phrase_list:
+                rec = KaldiRecognizer(model, sample_rate, json.dumps(phrase_list, ensure_ascii=False))
+            else:
+                rec = KaldiRecognizer(model, sample_rate)
+            rec.SetWords(show_words)
+            rec.SetMaxAlternatives(max_alternatives)
+            if spk_model:
+                rec.SetSpkModel(spk_model)
+
+        response, stop = await loop.run_in_executor(pool, process_chunk, rec, message)
+        await websocket.send(response)
+        if stop: break
+
+
+
+async def start():
+
+    global model
+    global spk_model
+    global args
+    global pool
+
+    # Enable loging if needed
+    #
+    # logger = logging.getLogger('websockets')
+    # logger.setLevel(logging.INFO)
+    # logger.addHandler(logging.StreamHandler())
+    logging.basicConfig(level=logging.INFO)
+
+    args = type('', (), {})()
+
+    # для размещения использует порт webapi+1 и тот же хост
+    args.interface = os.environ.get('VOSK_SERVER_INTERFACE', webapi_options["host"])
+    args.port = int(os.environ.get('VOSK_SERVER_PORT', int(webapi_options["port"])+1))
+    args.model_path = os.environ.get('VOSK_MODEL_PATH', 'model')
+    args.spk_model_path = os.environ.get('VOSK_SPK_MODEL_PATH')
+    args.sample_rate = float(os.environ.get('VOSK_SAMPLE_RATE', 8000))
+    args.max_alternatives = int(os.environ.get('VOSK_ALTERNATIVES', 0))
+    args.show_words = bool(os.environ.get('VOSK_SHOW_WORDS', True))
+
+    if len(sys.argv) > 1:
+        args.model_path = sys.argv[1]
+
+    # Gpu part, uncomment if vosk-api has gpu support
+    #
+    # from vosk import GpuInit, GpuInstantiate
+    # GpuInit()
+    # def thread_init():
+    #     GpuInstantiate()
+    # pool = concurrent.futures.ThreadPoolExecutor(initializer=thread_init)
+
+    model = Model(args.model_path)
+    spk_model = SpkModel(args.spk_model_path) if args.spk_model_path else None
+
+    pool = concurrent.futures.ThreadPoolExecutor((os.cpu_count() or 1))
+
+    print("VOSK Speech Recognition server v{0} started! host={1}, port={2}".format(version,args.interface,args.port))
+
+    async with websockets.serve(recognize, args.interface, args.port):
+        await asyncio.Future()
+
+
+if __name__ == '__main__':
+    asyncio.run(start())