import logging import wave 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 # Replace with your API key aai.settings.api_key = "aa9962f0088a449a9c4ab2361e96cc08" discord.opus._load_default() # VoiceState # self_mute=False # self_deaf=False # self_stream=False # suppress=False # requested_to_speak_at=None # channel= # user_limit=0 # category_id=1084451744496496753 # URL of the file to transcribe # You can also transcribe a local file by passing in a file path # FILE_URL = './path/to/file.mWp3 CHANNELS = OpusDecoder.CHANNELS SAMPLE_WIDTH = OpusDecoder.SAMPLE_SIZE // OpusDecoder.CHANNELS SAMPLING_RATE = OpusDecoder.SAMPLING_RATE #rotate file after there is 0.5s between last received pcm for user. #delete messsages after user disconnect logger = logging.getLogger("discord") location = "/home/pi/Conjurer/transcripts/" class WaveWriter: def __init__(self, user_id): self.username = str(user_id.id) logger.info("Creating Wavewriter %s", self.username) logger.info(user_id) self.present_file_id = 0 self.file_name_past = None self.file_name_present = location + self.username + "_" + str(self.present_file_id) + ".mp3" self.transcript_file_present : wave.Wave_write = wave.open( self.file_name_present, "wb" ) self.transcript_file_present.setnchannels(CHANNELS) self.transcript_file_present.setsampwidth(SAMPLE_WIDTH) self.transcript_file_present.setframerate(SAMPLING_RATE) self.file_name_future = location + self.username + "_" + str(self.present_file_id + 1) + ".mp3" self.transcript_file_future : wave.Wave_write = wave.open( self.file_name_future, "wb" ) self.transcript_file_future.setnchannels(CHANNELS) self.transcript_file_future.setsampwidth(SAMPLE_WIDTH) self.transcript_file_future.setframerate(SAMPLING_RATE) def rotate(self): self.transcript_file_present.close() self.name_file_past = self.file_name_present self.present_file_id += 1 self.file_name_present = self.file_name_future self.transcript_file_present = self.transcript_file_future self.file_name_future = location + self.username + "_" + str(self.present_file_id + 1) + ".mp3" self.transcript_file_future : wave.Wave_write = wave.open( self.file_name_future, "wb" ) self.transcript_file_future.setnchannels(CHANNELS) self.transcript_file_future.setsampwidth(SAMPLE_WIDTH) self.transcript_file_future.setframerate(SAMPLING_RATE) # send present to transcription def writeframes(self, pcmdata): logger.info(self.transcript_file_present) self.transcript_file_present.writeframes(pcmdata) def cleanup(self): logger.info("Cleanup for user %s", self.username) self.transcript_file_present.close() self.transcript_file_future.close() # send present to transcription class SRBuffer(voice_recv.AudioSink): """Endpoint AudioSink that generates a wav file. Best used in conjunction with a silence generating sink. (TBD) """ # on member join dodajemytypa do listy # on member disconnect - dropujemy go def __init__(self): super().__init__() self.wavewriter = {} def on_user_connect(self, username): self.wavewriter[str(username.id)] = [WaveWriter(username), time.time_ns(), False, False] def on_user_disconnect(self,username): self.wavewriter[str(username.id)].cleanup() self.wavewriter.pop(str(username.id)) def rotate_user(self,username): self.wavewriter[str(username.id)].rotate() def wants_opus(self) -> bool: return False def write(self, user, data) -> None: #logger.info("User %s", user) if user: self.wavewriter[str(user.id)][0].writeframes(data.pcm) self.wavewriter[str(user.id)][1] = time.time_ns() self.wavewriter[str(user.id)][2] = True def cleanup(self) -> None: try: logger.info("Cleanup for SRBuffer") for item in self.wavewriter.values(): item[0].cleanup() except Exception: logger.warning("WaveSink got error closing file on cleanup", exc_info=True) class Transcriber(commands.Cog): def __init__(self, bot): self.bot = bot self.wsink = SRBuffer() self.threads = [] self.comm_queue = Queue() async def transcribe(file_url): config = aai.TranscriptionConfig(speaker_labels=True, language_code="pl") transcriber = aai.Transcriber() transcript = transcriber.transcribe(file_url, config=config) for utterance in transcript.utterances: print(f"Speaker {utterance.speaker}: {utterance.text}") @commands.hybrid_command(name="transcribe") async def test(self, ctx): logger.info("Attempt transcribe") vc = None if self.bot.voice_clients: if isinstance(self.bot.voice_clients[0], voice_recv.VoiceRecvClient): logger.info("Already transcribing") else: logger.info("Already connected with other client") logger.info(self.bot.voice_clients) else: logger.info("Connected") vc = await ctx.author.voice.channel.connect(cls=voice_recv.VoiceRecvClient) logger.info(self.bot.voice_clients) vc.listen(self.wsink) self.check_data.start() @tasks.loop(seconds=0.5) async def check_data(self): for item in self.wsink.wavewriter.values(): logger.info(item[0]) logger.info(item[1]) logger.info(item[2]) logger.info(time.time_ns()) @commands.Cog.listener() async def on_voice_state_update(self, user, before, after): if before.channel is None: logger.info("User %s connected to channel %s", user, after.channel.name) self.wsink.on_user_connect(user) elif after.channel is None: logger.info("User %s disconnected from channel %s", user, before.channel.name) operation = { "type": "user_cleanup", user : user.id } self.comm_queue.put(operation) else: logger.info("User VC status changed %s", user.id) logger.info("Before %s", before) logger.info("After %s", after) @commands.command(name="stop_transcribe") async def stop(self, ctx): await ctx.voice_client.disconnect() async def setup(bot): await bot.add_cog(Transcriber(bot)) # 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. # 2. Transkrypcja to abstrakt - w zależności od tego która metoda jest włączona wysyła do odpowiedniego silnika, silniki offline odpalam na activcomie. Zaczynamy od assemblyai bo najlepiej wspiera polski. Potem zobaczymy co dalej.