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65c78a31d3
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57a7ee11e6
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storage
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test*
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@ -1,174 +0,0 @@
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# UV
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# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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#uv.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
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.pdm.toml
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.pdm-python
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.pdm-build/
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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# Ruff stuff:
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.ruff_cache/
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# PyPI configuration file
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.pypirc
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@ -1,13 +0,0 @@
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import os
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from dotenv import load_dotenv
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def load_config():
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load_dotenv()
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return {
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"REDIS_HOST": os.getenv("REDIS_HOST", "localhost"),
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"REDIS_PORT": int(os.getenv("REDIS_PORT", "6379")),
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"WHISPER_MODEL": os.getenv("WHISPER_MODEL", "dvislobokov/whisper-large-v3-turbo-russian"),
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"DEVICE": os.getenv("DEVICE", "cuda"),
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"AUDIO_TASK_CHANNEL": os.getenv("AUDIO_TASK_CHANNEL", "audio_tasks"),
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"TEXT_RESULT_CHANNEL": os.getenv("TEXT_RESULT_CHANNEL", "texts"),
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}
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@ -1,53 +0,0 @@
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import asyncio
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import json
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from config import load_config
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from models import AudioTask
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from redis_client import RedisClient
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from transcriber import WhisperTranscriber
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async def process_audio_task(redis_client: RedisClient, transcriber: WhisperTranscriber, task_data: dict):
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try:
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task = AudioTask(**task_data)
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except Exception as e:
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print(f"Error creating AudioTask from data: {e}")
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return
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print(f"Processing task {task.uuid} ...")
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loop = asyncio.get_running_loop()
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text = await loop.run_in_executor(None, transcriber.transcribe, task.file_path)
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result = {
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"chat_id": task.chat_id,
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"user_id": task.user_id,
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"message_id": task.message_id,
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"text": text
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}
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await redis_client.publish_result(result)
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print(f"Published result for task {task.uuid}")
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async def main():
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config = load_config()
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redis_client = RedisClient(
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host=config["REDIS_HOST"],
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port=config["REDIS_PORT"],
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task_channel=config["AUDIO_TASK_CHANNEL"],
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result_channel=config["TEXT_RESULT_CHANNEL"]
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)
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transcriber = WhisperTranscriber(config["WHISPER_MODEL"], config["DEVICE"])
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pubsub = await redis_client.subscribe_tasks()
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print("Subscribed to audio_tasks channel. Waiting for tasks...")
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while True:
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message = await pubsub.get_message(ignore_subscribe_messages=True, timeout=1.0)
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if message:
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try:
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task_data = json.loads(message["data"])
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except Exception as e:
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print(f"Error parsing task message: {e}")
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continue
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asyncio.create_task(process_audio_task(redis_client, transcriber, task_data))
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await asyncio.sleep(0.1)
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if __name__ == "__main__":
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asyncio.run(main())
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@ -1,9 +0,0 @@
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from dataclasses import dataclass
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@dataclass
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class AudioTask:
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uuid: str
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file_path: str
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user_id: int
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chat_id: int
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message_id: int
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import json
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import redis.asyncio as redis
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class RedisClient:
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def __init__(self, host: str, port: int, task_channel: str, result_channel: str):
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self.client = redis.Redis(host=host, port=port, decode_responses=True)
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self.task_channel = task_channel
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self.result_channel = result_channel
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async def subscribe_tasks(self):
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pubsub = self.client.pubsub()
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await pubsub.subscribe(self.task_channel)
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return pubsub
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async def publish_result(self, result: dict):
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await self.client.publish(self.result_channel, json.dumps(result))
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--index-url https://download.pytorch.org/whl/cu121
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torch==2.5.1
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torchvision==0.20.1
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torchaudio==2.5.1
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--index-url https://pypi.org/simple
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transformers
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redis>=4.2.0
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python-dotenv
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from transformers import pipeline
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class WhisperTranscriber:
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def __init__(self, model_name: str, device: str = "cuda"):
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print("Loading Whisper model...")
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self.pipe = pipeline(
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task="automatic-speech-recognition",
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model=model_name,
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tokenizer=model_name,
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device=0 if device == "cuda" else -1
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)
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print("Whisper model loaded.")
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def transcribe(self, audio_file: str) -> str:
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result = self.pipe(audio_file)
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return result.get("text", "").strip()
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@ -2,7 +2,6 @@ import os
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import uuid
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from functools import partial
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from aiogram import types, Dispatcher, F
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import ffmpeg
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async def handle_voice_and_video(message: types.Message, redis_service, storage_path: str):
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file_id = None
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file_path = file.file_path
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file_uuid = str(uuid.uuid4())
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original_filename = os.path.basename(file_path)
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temp_filename = f"{file_uuid}_{original_filename}"
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filename = f"{file_uuid}_{os.path.basename(file_path)}"
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os.makedirs(storage_path, exist_ok=True)
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temp_destination = os.path.join(storage_path, temp_filename)
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destination = os.path.join(storage_path, filename)
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await message.bot.download_file(file_path, temp_destination)
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wav_filename = f"{file_uuid}.wav"
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wav_destination = os.path.join(storage_path, wav_filename)
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convert_to_wav(temp_destination, wav_destination)
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os.remove(temp_destination)
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await message.bot.download_file(file_path, destination)
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task_data = {
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"uuid": file_uuid,
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"file_path": wav_destination,
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"file_local_path": destination,
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"user_id": message.from_user.id,
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"chat_id": message.chat.id,
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"message_id": message.message_id
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"chat_id": message.chat.id
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}
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await redis_service.publish_task(task_data)
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await message.reply("Your message has been received, converted to WAV, and queued for processing.\nWaiting for transcription...")
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text = await redis_service.wait_for_text(
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user_id=message.from_user.id,
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chat_id=message.chat.id,
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message_id=message.message_id
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)
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if text:
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await message.reply(f"Transcription result:\n{text}")
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else:
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await message.reply("Sorry, transcription result was not received within the timeout.")
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def convert_to_wav(input_file: str, output_file: str):
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"""
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Конвертирует любой аудио/видеофайл в .wav с частотой 16kHz, 1 канал (моно).
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"""
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try:
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ffmpeg.input(input_file).output(
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output_file,
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format="wav",
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acodec="pcm_s16le",
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ac=1,
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ar="16000"
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).run(overwrite_output=True)
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except Exception as e:
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print(f"Error converting {input_file} to WAV: {e}")
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redis_service.publish_task(task_data)
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await message.reply("Your message has been received and queued for processing.")
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def register_audio_handlers(dp: Dispatcher, redis_service, storage_path: str):
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# Оборачиваем callback для передачи дополнительных аргументов
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handler_callback = partial(handle_voice_and_video, redis_service=redis_service, storage_path=storage_path)
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# Регистрируем хэндлер с фильтром по content_type
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dp.message.register(handler_callback, F.content_type.in_({types.ContentType.VOICE, types.ContentType.VIDEO_NOTE}))
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dp.message.register(
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handler_callback,
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F.content_type.in_({types.ContentType.VOICE, types.ContentType.VIDEO_NOTE})
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)
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@ -1,29 +1,10 @@
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import json
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import redis.asyncio as redis
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import redis
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class RedisService:
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def __init__(self, host: str, port: int):
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self.client = redis.Redis(host=host, port=port, decode_responses=True)
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async def publish_task(self, task_data: dict):
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def publish_task(self, task_data: dict):
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channel = "audio_tasks"
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await self.client.publish(channel, json.dumps(task_data))
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async def wait_for_text(self, user_id: int, chat_id: int, message_id: int, timeout: int = 30):
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pubsub = self.client.pubsub()
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await pubsub.subscribe("texts")
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try:
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async for message in pubsub.listen():
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if message["type"] != "message":
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continue
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try:
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data = json.loads(message["data"])
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except Exception:
|
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continue
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if (data.get("user_id") == user_id and
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data.get("chat_id") == chat_id and
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data.get("message_id") == message_id):
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return data.get("text")
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finally:
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await pubsub.unsubscribe("texts")
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return None
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self.client.publish(channel, json.dumps(task_data))
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|
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