An exquisite asynchronous utility for the procurement of high-fidelity audiovisual recordings, leveraging a refined queue system for unmatched reliability.
Pray, allow me to introduce the new and improved architecture of this remarkable tool. To ensure that no request is lost to the whims of server timeouts, the bot now operates as a duo: a Webhook and a Worker.
The Webhook acts as a poised receptionist, accepting your requests and archiving them within a MongoDB vault. The Worker, a diligent archivist running upon your local machine, retrieves these requests and procures the media with surgical precision.
- Asynchronous Queueing: Requests are safely stored in MongoDB, ensuring that even the most substantial recordings are processed without interruption.
- Local Procurement: By running the worker locally, the bot avoids the uncouth bot-detection systems of the cloud, utilizing your own residential connection for a more seamless experience.
- Tiered Delivery: The bot notifies the user at every stage—from the initial archiving to the final delivery of both visual and auditory components.
- Fastidious Naming: Filenames are formatted with the utmost care:
video_name-channel_name(spaces to_, pipes to-), ensuring a tidy archive.
One must possess:
- A Telegram API Key (obtained via @BotFather).
- A MongoDB Connection String (a cluster on MongoDB Atlas is most recommended).
- The Repository: Deposit this codebase into a GitHub or GitLab repository.
- The Connection: Link said repository to your Vercel account.
- The Secrets: In the Vercel dashboard, introduce the following environment variables:
TELEGRAM_API_KEY: Your bot token.MONGODB_CONNECTION_STRING: Your MongoDB URI.
- The Activation: Inform Telegram of the webhook's residence:
npx sethook <YOUR_TELEGRAM_API_KEY> https://<YOUR_SITE_NAME>.vercel.app/api/webhook
The worker must be run on a local machine where yt-dlp can operate freely.
- Environment: Create a
.envfile in the root directory:TELEGRAM_API_KEY=your_token_here MONGODB_CONNECTION_STRING=your_mongodb_uri_here
- Dependencies: Install the required libraries:
pip install -r requirements.txt - Execution: Awaken the worker:
python worker.py
The Worker utilizes yt-dlp to download the finest available mp4 and m4a formats. By operating locally, it bypasses the "bot detection" issues common to serverless environments. The files are sent to the user as Documents to preserve their high-fidelity quality and correct filenames.
Developed with poise and precision. May your queue be short and your quality superlative.