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📄 AI Document Digitizer (Qwen3-VL)

An intelligent document processing API & UI powered by the Qwen3-VL multimodal model. It extracts structured data from scanned forms, invoices, and documents, ignoring boilerplate text and focusing on business values.

🚀 Features

  • Strict Data Extraction: Ignores legal text and instructions, extracts only values.
  • Smart Formatting: Converts tables and forms into structured JSON.
  • Visual Verification: Interactive UI highlights extracted fields on the image.
  • Multiple Exports: Download results as JSON, CSV, or Excel.
  • Dual Mode: Works as a Web UI (Gradio) and a REST API (FastAPI) simultaneously.

🛠️ Installation

  1. Clone the repository:

    git clone https://github.com/ituvtu/qwen-doc-parser.git
cd qwen-doc-parser

  2. Сreate a virtual environment and install dependencies:

    python -m venv .venv
# Windows:
.venv\\Scripts\\activate
# Mac/Linux:
source .venv/bin/activate
pip install -r requirements.txt

  3. Set up environment variables: Copy .env.example to .env and add your Hugging Face Token:

    HF_TOKEN=your_token_here

  4. ▶️ Usage

    Run with Docker (Recommended)

    Option A: Using .env file (Best for security)

    docker build -t qwen-doc-parser .
docker run -p 7860:7860 --env-file .env qwen-doc-parser

    Option B: Passing token directly

    docker run -p 7860:7860 -e HF_TOKEN=hf_YourTokenHere qwen-doc-parser

    Run Locally

    uvicorn app.main:app --host 0.0.0.0 --port 7860 --reload

    Open your browser at http://localhost:7860.

📡 API Example

You can use the API to extract data programmatically:

curl -X POST "http://localhost:7860/api/v1/extract" \\
     -H "accept: application/json" \\
     -H "Content-Type: multipart/form-data" \\
     -F "file=@/path/to/invoice.jpg"

🧪 Quick Test Script

The project includes a Python script to verify the API functionality immediately.

  1. Open test_api.py and update the IMAGE_PATH variable to point to your test image.
  2. Run the script: 
    python test_api.py