docling-studio/docs/getting-started.md

Getting Started

Docling Studio ships two Docker image variants:

Variant	Image tag	Size	Description
remote	latest-remote	~300 MB	Lightweight — delegates to an external Docling Serve instance
local	latest-local	~2–3 GB	Full — runs Docling in-process (downloads ML models on first run)

Docker — remote mode (fastest)

docker run -p 3000:3000 \
  -e DOCLING_SERVE_URL=http://your-docling-serve:5001 \
  ghcr.io/scub-france/docling-studio:latest-remote

Docker — local mode (self-contained)

docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local

Note: The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.

Open http://localhost:3000.

Docker Compose (recommended for development)

git clone https://github.com/scub-france/Docling-Studio.git
cd Docling-Studio

# Local mode (default)
docker compose up --build

# Remote mode
CONVERSION_MODE=remote DOCLING_SERVE_URL=http://your-docling-serve:5001 docker compose up --build

Local Development

=== "Backend (Python 3.12+)"

```bash
cd document-parser
python -m venv .venv && source .venv/bin/activate

# Remote mode (lightweight)
pip install -r requirements.txt

# Local mode (with Docling)
pip install -r requirements-local.txt

uvicorn main:app --reload --port 8000
```

=== "Frontend (Node 20+)"

```bash
cd frontend
npm install
npm run dev
```

The frontend runs on http://localhost:3000 and proxies API calls to http://localhost:8000.

Running Tests

=== "Backend"

```bash
cd document-parser
pip install pytest pytest-asyncio httpx
pytest tests/ -v
```

=== "Frontend"

```bash
cd frontend
npm run test:run
```

Pipeline Options

These options map directly to Docling's PdfPipelineOptions.

Option	Default	Description
do_ocr	true	OCR for scanned pages and embedded images
do_table_structure	true	Table detection and row/column reconstruction
table_mode	accurate	accurate (TableFormer) or fast
do_code_enrichment	false	Specialized OCR for code blocks
do_formula_enrichment	false	Math formula recognition (LaTeX output)
do_picture_classification	false	Classify images by type
do_picture_description	false	Generate image descriptions via VLM
generate_picture_images	false	Extract detected images as separate files
generate_page_images	false	Rasterize each page as an image
images_scale	1.0	Scale factor for generated images (0.1–10)

Configuration

All configuration is done via environment variables:

Variable	Default	Description
CONVERSION_ENGINE	local	local (in-process Docling) or remote (Docling Serve)
DOCLING_SERVE_URL	http://localhost:5001	Docling Serve endpoint (remote mode only)
DOCLING_SERVE_API_KEY	—	API key for Docling Serve (optional)
CORS_ORIGINS	http://localhost:3000,...	CORS allowed origins
UPLOAD_DIR	./uploads	File storage directory
DB_PATH	./data/docling_studio.db	SQLite database path
CONVERSION_TIMEOUT	600	Max seconds per Docling conversion

System Requirements

	Remote image	Local image
Image size	~300 MB	~2–3 GB
Memory	2 GB	6 GB (recommended 8 GB+)
CPUs	2	4 (recommended 8+)

All Docker images are multi-arch (linux/amd64 + linux/arm64). No GPU required.