asynv

voice_recognition.py

@@ -5,7 +5,6 @@ import assemblyai as aai
 import discord
 from discord.ext import commands, voice_recv, tasks
 from discord.opus import Decoder as OpusDecoder
-from queue import Queue, Empty
 import time
 import threading
 # Replace with your API key
@@ -127,11 +126,10 @@ class SRBuffer(voice_recv.AudioSink):
 
 
 class Transcriber(commands.Cog):
-    def __init__(self, bot, worker,  queue):
+    def __init__(self, bot):
         self.bot = bot
         self.threads = []
-        self.comm_queue = queue
-        self.worker = worker
+        self.comm_queue = asyncio.Queue()
         self.wsink = SRBuffer(self.comm_queue)
 
     @commands.hybrid_command(name="transcribe")
@@ -151,7 +149,7 @@ class Transcriber(commands.Cog):
             logger.info(self.bot.voice_clients)
             self.check_data.start()
             logger.info("Start worker!~!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
-            self.worker.start()
+            asyncio.run(self.transcribe_output_queue())
             vc.listen(self.wsink)
 
 
@@ -196,35 +194,28 @@ class Transcriber(commands.Cog):
         self.comm_queue.put(stop_token)
         await ctx.voice_client.disconnect()
 
-
-#this needs to be async and transcript fun awaited
-def transcribe_output_queue(queue):
-    logger.info("Transcript worker start")
-    config = aai.TranscriptionConfig(speaker_labels=True, language_code="pl")
-    transcriber = aai.Transcriber()
-    while True:
-        item = queue.get()
-        if item.type == "STOP":
-            logger.info("Queue ended")
-            break
-        elif item.type == "send_file":
-            transcript = ""
-            for iter in item.data:
-                transcript = transcriber.transcribe(iter, config=config)
-            for utterance in transcript.utterances:
-                logger.info("%s : %s", item.user, utterance.text)
-        elif item.type == "user_cleanup":
-            logger.info("User %s disconnected - cleanup action")
-    logger.info("End transcript worker")
+    async def transcribe_output_queue(self):
+        logger.info("Transcript worker start")
+        config = aai.TranscriptionConfig(speaker_labels=True, language_code="pl")
+        transcriber = aai.Transcriber()
+        while True:
+            item = self.queue.get()
+            if item.type == "STOP":
+                logger.info("Queue ended")
+                break
+            elif item.type == "send_file":
+                transcript = ""
+                for iter in item.data:
+                    transcript = transcriber.transcribe(iter, config=config)
+                for utterance in transcript.utterances:
+                    logger.info("%s : %s", item.user, utterance.text)
+            elif item.type == "user_cleanup":
+                logger.info("User %s disconnected - cleanup action")
+        logger.info("End transcript worker")
 
 async def setup(bot):
     logger = logging.getLogger("discord")
-    logger.info("Loading voice transcribed module phase one")
-    worker = threading.Thread(target=transcribe_output_queue)
-    logger.info("Loading voice transcribed phasetwo")
-    queue = Queue()
-    logger.info("Loading voice transcribed module phase three")
-    await bot.add_cog(Transcriber(bot, worker, queue))
+    await bot.add_cog(Transcriber(bot))
     logger.info("Loading voice transcribed module done")
 
 # 1. zapisuj kwestie człowieka do pliku w którym będzie można stwierdzić kto co powiedział (callback z basicaudio + write z wavesinka). Zamykaj plik i wysyłaj do transkrypcji w momencie ciszy dłuższej niż 0.5s. Jeśli człowiek nadaje cały czas dawaj sygnał że nie można go transkrybować - i wyłaczaj zapis.