File format conversion, document OCR, and audio-to-text — I’ve collected a bunch of different tools, but finding the right one is a hassle.

FileWizard bundles these tools into a self-hosted web page; just drag in a file to convert, with only a few clicks in your browser.

Under the hood, it wraps mature tools like FFmpeg, LibreOffice, and Pandoc, covering a broad set of format conversions.

You can run OCR on images and PDFs, use Whisper to transcribe audio into text, and it includes background tasks and real-time progress.

GitHub: http://github.com/LoredCast/filewizard…

It provides a one-click local deployment via Docker — the project runs on your own machine, so files don’t go to any third party.

If you frequently juggle various file formats, set one up yourself as an online toolbox.

LoredCast/filewizard

Source: https://github.com/LoredCast/filewizard

File Wizard

PayPal (https://www.paypal.me/unterrikermanu) Docker Pulls (https://hub.docker.com/r/loredcast/filewizard) Docker Image Version (https://hub.docker.com/r/loredcast/filewizard)

A self-hosted, browser-based utility for file conversion, OCR and audio transcription. It wraps common CLI and Python converters (FFmpeg, LibreOffice, Pandoc, ImageMagick, etc.), plus faster-whisper and Tesseract OCR.

Screenshot

Features

• Convert between many file formats; extendable via settings.yml to add any CLI tool.
• OCR for PDFs and images (tesseract / ocrmypdf).
• Audio transcription using Whisper models.
• Simple, responsive dark UI with drag-and-drop and file picker.
• Background job processing with real-time status updates and persistent history.
• /settings page for configuring conversion tools and OAuth (runs without auth in local mode).
• CPU-only by default; a -cuda image is available for GPU use.

Security

Warning: exposing this app publicly without authentication risks arbitrary code execution. Intended for local use or behind a properly configured OAuth/OIDC provider.

Tech stack

FastAPI, vanilla HTML/JS/CSS frontend.

Installation

Recommended — Docker (pull from Docker Hub)

Images available:

• loredcast/filewizard:latest (newest full release without cuda)
• loredcast/filewizard:0.3-small (omits TeX and other large tools)
• loredcast/filewizard:0.3-cuda (CUDA-enabled)

``

docker-compose.yml

version: “3.9” services: web: image: loredcast/filewizard:latest environment: - LOCAL_ONLY=True # False for Auth - SECRET_KEY= # set if using auth - UPLOADS_DIR=/app/uploads # inside the container - PROCESSED_DIR=/app/processed # inside the container - OMP_NUM_THREADS=1 - DOWNLOAD_KOKORO_ON_STARTUP=true ports: - “6969:8000” volumes: - ./config:/app/config # settings.yml will be here - ./uploads_data:/app/uploads - ./processed_data:/app/processed volumes: uploads_data: {} processed_data: {} ``

Copy docker-compose.yml from the repo or the above, adjust as needed, then:

bash docker compose up -d FileWizard will be available at localhost:6969

Build locally with Docker (new build types)

For different build configurations, use the BUILD_TYPE argument:

``bash

Full build (includes all dependencies but no CUDA)

docker build –build-arg BUILD_TYPE=full -t filewizard:full .

Small build (excludes TeX and markitdown dependencies for smaller image)

docker build –build-arg BUILD_TYPE=small -t filewizard:small .

CUDA build (includes CUDA support for GPU acceleration)

docker build –build-arg BUILD_TYPE=cuda -t filewizard:cuda . ``

Or with docker-compose:

``bash

For full build

docker compose build –build-arg BUILD_TYPE=full

For small build

docker compose build –build-arg BUILD_TYPE=small

For CUDA build

docker compose build –build-arg BUILD_TYPE=cuda ``

For CUDA builds, ensure you have:

• NVIDIA Docker runtime installed (nvidia-docker2 package)
• Compatible GPU with appropriate drivers
• Add the GPU configuration to docker-compose.yml if building with compose: yaml deploy: resources: reservations: devices: - driver: nvidia count: all capabilities: [gpu]

For troubleshooting GPU issues, make sure:

1. Your GPU drivers support the CUDA version (12.1)
2. cuDNN libraries are properly installed in the container
3. The nvidia-container-toolkit is properly configured
4. Test NVIDIA setup with: docker run --rm --gpus all nvidia/cuda:12.1-base-ubuntu22.04 nvidia-smi

bash git clone https://github.com/LoredCast/filewizard.git cd filewizard docker compose up --build Note: building can be slow (TeX and other dependencies).

Manual (no Docker)

bash git clone https://github.com/LoredCast/filewizard.git cd filewizard python -m venv venv source venv/bin/activate # Windows: venv\\Scripts\\activate pip install -r requirements.txt chmod +x run.sh ./run.sh

Dependencies include fastapi, uvicorn, sqlalchemy, huey, faster-whisper, ocrmypdf, pytesseract, python-multipart, pyyaml, etc.

Configuration & docs

See the project Wiki for details and examples:
https://github.com/LoredCast/filewizard/wiki

Usage

1. Open http://127.0.0.1:8000.
2. Drag & drop or choose files.
3. Select action: Convert, OCR, or Transcribe.
4. Track job progress in the History table (updates automatically).

Tools Table

Consider spending 30 seconds on the » usage survey « (https://app.youform.com/forms/sdlb6mto) to help improve the app and suggest changes!

ko-fi (https://ko-fi.com/loredcast)