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11 changed files with 14 additions and 364 deletions

2
.gitignore vendored
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storage
test*

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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# UV
# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
#uv.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
.pdm.toml
.pdm-python
.pdm-build/
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
# Ruff stuff:
.ruff_cache/
# PyPI configuration file
.pypirc

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import os
from dotenv import load_dotenv
def load_config():
load_dotenv()
return {
"REDIS_HOST": os.getenv("REDIS_HOST", "localhost"),
"REDIS_PORT": int(os.getenv("REDIS_PORT", "6379")),
"WHISPER_MODEL": os.getenv("WHISPER_MODEL", "dvislobokov/whisper-large-v3-turbo-russian"),
"DEVICE": os.getenv("DEVICE", "cuda"),
"AUDIO_TASK_CHANNEL": os.getenv("AUDIO_TASK_CHANNEL", "audio_tasks"),
"TEXT_RESULT_CHANNEL": os.getenv("TEXT_RESULT_CHANNEL", "texts"),
}

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import asyncio
import json
from config import load_config
from models import AudioTask
from redis_client import RedisClient
from transcriber import WhisperTranscriber
async def process_audio_task(redis_client: RedisClient, transcriber: WhisperTranscriber, task_data: dict):
try:
task = AudioTask(**task_data)
except Exception as e:
print(f"Error creating AudioTask from data: {e}")
return
print(f"Processing task {task.uuid} ...")
loop = asyncio.get_running_loop()
text = await loop.run_in_executor(None, transcriber.transcribe, task.file_path)
result = {
"chat_id": task.chat_id,
"user_id": task.user_id,
"message_id": task.message_id,
"text": text
}
await redis_client.publish_result(result)
print(f"Published result for task {task.uuid}")
async def main():
config = load_config()
redis_client = RedisClient(
host=config["REDIS_HOST"],
port=config["REDIS_PORT"],
task_channel=config["AUDIO_TASK_CHANNEL"],
result_channel=config["TEXT_RESULT_CHANNEL"]
)
transcriber = WhisperTranscriber(config["WHISPER_MODEL"], config["DEVICE"])
pubsub = await redis_client.subscribe_tasks()
print("Subscribed to audio_tasks channel. Waiting for tasks...")
while True:
message = await pubsub.get_message(ignore_subscribe_messages=True, timeout=1.0)
if message:
try:
task_data = json.loads(message["data"])
except Exception as e:
print(f"Error parsing task message: {e}")
continue
asyncio.create_task(process_audio_task(redis_client, transcriber, task_data))
await asyncio.sleep(0.1)
if __name__ == "__main__":
asyncio.run(main())

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from dataclasses import dataclass
@dataclass
class AudioTask:
uuid: str
file_path: str
user_id: int
chat_id: int
message_id: int

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import json
import redis.asyncio as redis
class RedisClient:
def __init__(self, host: str, port: int, task_channel: str, result_channel: str):
self.client = redis.Redis(host=host, port=port, decode_responses=True)
self.task_channel = task_channel
self.result_channel = result_channel
async def subscribe_tasks(self):
pubsub = self.client.pubsub()
await pubsub.subscribe(self.task_channel)
return pubsub
async def publish_result(self, result: dict):
await self.client.publish(self.result_channel, json.dumps(result))

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--index-url https://download.pytorch.org/whl/cu121
torch==2.5.1
torchvision==0.20.1
torchaudio==2.5.1
--index-url https://pypi.org/simple
transformers
redis>=4.2.0
python-dotenv

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from transformers import pipeline
class WhisperTranscriber:
def __init__(self, model_name: str, device: str = "cuda"):
print("Loading Whisper model...")
self.pipe = pipeline(
task="automatic-speech-recognition",
model=model_name,
tokenizer=model_name,
device=0 if device == "cuda" else -1
)
print("Whisper model loaded.")
def transcribe(self, audio_file: str) -> str:
result = self.pipe(audio_file)
return result.get("text", "").strip()

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import uuid
from functools import partial
from aiogram import types, Dispatcher, F
import ffmpeg
async def handle_voice_and_video(message: types.Message, redis_service, storage_path: str):
file_id = None
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file_path = file.file_path
file_uuid = str(uuid.uuid4())
original_filename = os.path.basename(file_path)
temp_filename = f"{file_uuid}_{original_filename}"
filename = f"{file_uuid}_{os.path.basename(file_path)}"
os.makedirs(storage_path, exist_ok=True)
temp_destination = os.path.join(storage_path, temp_filename)
destination = os.path.join(storage_path, filename)
await message.bot.download_file(file_path, temp_destination)
wav_filename = f"{file_uuid}.wav"
wav_destination = os.path.join(storage_path, wav_filename)
convert_to_wav(temp_destination, wav_destination)
os.remove(temp_destination)
await message.bot.download_file(file_path, destination)
task_data = {
"uuid": file_uuid,
"file_path": wav_destination,
"file_local_path": destination,
"user_id": message.from_user.id,
"chat_id": message.chat.id,
"message_id": message.message_id
"chat_id": message.chat.id
}
await redis_service.publish_task(task_data)
await message.reply("Your message has been received, converted to WAV, and queued for processing.\nWaiting for transcription...")
text = await redis_service.wait_for_text(
user_id=message.from_user.id,
chat_id=message.chat.id,
message_id=message.message_id
)
if text:
await message.reply(f"Transcription result:\n{text}")
else:
await message.reply("Sorry, transcription result was not received within the timeout.")
def convert_to_wav(input_file: str, output_file: str):
"""
Конвертирует любой аудио/видеофайл в .wav с частотой 16kHz, 1 канал (моно).
"""
try:
ffmpeg.input(input_file).output(
output_file,
format="wav",
acodec="pcm_s16le",
ac=1,
ar="16000"
).run(overwrite_output=True)
except Exception as e:
print(f"Error converting {input_file} to WAV: {e}")
redis_service.publish_task(task_data)
await message.reply("Your message has been received and queued for processing.")
def register_audio_handlers(dp: Dispatcher, redis_service, storage_path: str):
# Оборачиваем callback для передачи дополнительных аргументов
handler_callback = partial(handle_voice_and_video, redis_service=redis_service, storage_path=storage_path)
# Регистрируем хэндлер с фильтром по content_type
dp.message.register(handler_callback, F.content_type.in_({types.ContentType.VOICE, types.ContentType.VIDEO_NOTE}))
dp.message.register(
handler_callback,
F.content_type.in_({types.ContentType.VOICE, types.ContentType.VIDEO_NOTE})
)

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import json
import redis.asyncio as redis
import redis
class RedisService:
def __init__(self, host: str, port: int):
self.client = redis.Redis(host=host, port=port, decode_responses=True)
async def publish_task(self, task_data: dict):
def publish_task(self, task_data: dict):
channel = "audio_tasks"
await self.client.publish(channel, json.dumps(task_data))
async def wait_for_text(self, user_id: int, chat_id: int, message_id: int, timeout: int = 30):
pubsub = self.client.pubsub()
await pubsub.subscribe("texts")
try:
async for message in pubsub.listen():
if message["type"] != "message":
continue
try:
data = json.loads(message["data"])
except Exception:
continue
if (data.get("user_id") == user_id and
data.get("chat_id") == chat_id and
data.get("message_id") == message_id):
return data.get("text")
finally:
await pubsub.unsubscribe("texts")
return None
self.client.publish(channel, json.dumps(task_data))