The All File Converter service is designed as a scalable distributed SaaS system based on a modern asynchronous Python 3.12 stack. The architecture is divided into independent layers: network event intake, task orchestration, isolated execution of heavy binary processes, and the analytical loop.

1. General Technology Stack and System Architecture

The platform is built on the principles of high throughput, minimal memory consumption, and fault tolerance:

  • Telegram Bot Framework: Aiogram 3.13, operating in Webhook mode with secret token validation and custom message lifecycle filters.
  • Web Gateway and REST API: FastAPI based on the Uvicorn ASGI server with asynchronous binary file streaming (FileResponse) and background cleanup via BackgroundTasks.
  • Queue Broker and Cache: Redis 7 (Celery task management, race condition locks, brute-force protection, session caching).
  • Background Executor (Task Queue): Celery 5.4 with a dedicated worker pool in an isolated converter_worker container.
  • Database: PostgreSQL 16 with the SQLAlchemy 2.0 (asyncpg) ORM layer, a persistent connection pool (20+10 overflow), and auto-retry for failed transactions (@db_retry).
  • Network Perimeter: Tunneling via Cloudflare Zero Trust with direct IP access to the server blocked through Middleware.

2. Asynchronous Queues and Heavy Computation Isolation (Celery + Redis)

Media file and office suite conversion creates peak loads on CPU and RAM. To prevent incoming Telegram message processing from blocking during heavy operations, strict isolation is implemented:

  • Task Delegation to Redis: Upon format selection, the Telegram handler registers the task in the DB with the PROCESSING status and places the job in the tasks.execute_conversion queue via Celery.
  • Isolated Worker Container: Conversion utilities are executed within a separate Linux container with its own CPU time and memory limits.
  • Hang Control and Timeouts: External utility calls are wrapped in an asynchronous context with strict time control (conversion_timeout_sec = 180). If the limit is exceeded, the process is forcefully terminated via proc.kill(), freeing up resources.
  • Fault-Tolerant Fallback: In the event of temporary Redis broker unavailability, the task is automatically intercepted by the local asynchronous dispatcher and executed directly without disrupting the user.

3. Specialized Conversion Engine Pipeline

Highly specialized native utilities and libraries are used for each data type:

  • Documents and Spreadsheets (LibreOffice): Headless office suite (soffice --headless) for accurate rendering of DOCX, XLSX, PPTX, RTF, ODT into PDF or text formats.
  • Streaming Audio and Video (FFmpeg): Multithreaded transcoding of video codecs (H.264), audio codecs (MP3, OGG Opus), extraction of audio tracks, GIF generation (Lanczos filter), and square cropping (1:1) for Telegram video messages.
  • High-Speed PDF Processing (Poppler Utils): pdftotext utilities (instant extraction of formatted text in UTF-8) and pdftoppm (page-by-page PDF rendering to raster images without LibreOffice overhead).
  • Optical Character Recognition (Tesseract OCR): Neural network extraction of printed text from scans and photos across 40+ languages.
  • Raster and Vector Graphics: Pillow libraries (including HEIC and AVIF support), CairoSVG for vector images, and lottie for Telegram animated stickers (.TGS).
  • Books, Subtitles, and Fonts: Calibre engine (ebook-convert), pysubs2 subtitle parser (SRT, VTT, ASS, SSA), and fonttools font compiler (Brotli compression to WOFF2).

4. Preventive Resource Protection (System Guard)

To protect against server crashes due to insufficient memory (OOM Killer), the System Guard preventive diagnostics service has been introduced. Before accepting a file for processing, the system checks key host metrics:

  • Free RAM: Minimum 500 MB of free volume (guard_min_free_ram_mb).
  • Disk Space: Minimum 2 GB of free space in the /tmp directory (guard_min_free_disk_mb).
  • Task Queue: Limitation on the Celery queue length (no more than 20 pending tasks).

When limits are exceeded, the service temporarily enables protection (HTTP 503 / chat message), preventing server overload and sending an instant alert to administrators in Telegram.

5. File Lifecycle and Security (GDPR)

The architecture is designed around a Zero-Data-Footprint model:

  • User files are uploaded to a secure tmp/conversions/ volume with unique prefixes based on task IDs.
  • Files remain accessible strictly within the working session — no more than 15 minutes (900 seconds).
  • The automatic garbage collector erases source and ready files immediately after successful delivery confirmation to the chat or upon session timeout expiration.
  • The PostgreSQL database does not store binary files or personal document texts — tables record only anonymized technical metadata (formats, sizes in bytes, processing time, statuses).

6. Universal REST API for External Web Services

The service was initially designed as a multi-platform backend. Alongside the bot, a fully functional secure programmatic interface operates for websites (e.g., on Django) and third-party bots:

  • GET /api/v1/formats — a dynamic JSON matrix of available conversion directions, synchronized with Google Sheets settings.
  • POST /api/v1/convert — a universal endpoint that accepts multipart/form-data (file, target format, external client ID) and returns the ready byte stream as a direct download.
  • Authorization via Bearer tokens (WEBHOOK_REFRESH_TOKEN) with timing attack protection via secrets.compare_digest.

7. Control Panel and Observability (NiceGUI + AG Grid)

Business metric monitoring and system status have been brought into a native Single-Page control panel based on NiceGUI 2.x:

  • Interactive AG Grid (v32+) tables with custom Excel-style checkbox filters (aggrid_filters.js).
  • Real-time monitoring of queues, API provider latencies, and PostgreSQL / Redis pings.
  • End-to-end date filtering with seamless Metabase BI dashboard integration via signed JWT tokens.