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---
title: Docling Studio
emoji: 📄
colorFrom: yellow
colorTo: blue
sdk: docker
app_port: 3000
pinned: false
---
# Docling Studio
![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
![Python](https://img.shields.io/badge/python-3.12+-blue)
![Node](https://img.shields.io/badge/node-20+-green)
![Docling](https://img.shields.io/badge/powered%20by-Docling-orange)
![CI](https://github.com/scub-france/Docling-Studio/actions/workflows/ci.yml/badge.svg)
[![GitHub Stars](https://img.shields.io/github/stars/scub-france/Docling-Studio?style=flat-square&logo=github&label=Stars)](https://github.com/scub-france/Docling-Studio)
A visual document analysis studio powered by [Docling](https://github.com/DS4SD/docling).
Upload a PDF, configure the extraction pipeline, and visualize the results — text, tables, images, formulas, bounding boxes — all from your browser.
![Docling Studio — Presentation](docs/screenshots/presentation.gif)
## Features
- **Home page** with quick upload and recent documents
- **PDF viewer** with page navigation, bounding box overlay, and resizable results panel
- **Configurable Docling pipeline** — OCR, table extraction, code/formula enrichment, picture classification & description, image generation
- **Bounding box visualization** — color-coded element overlay directly on the PDF
- **Per-page results** — right panel syncs with the current PDF page
- **Markdown & HTML export** of extracted content
- **Document management** — upload, list, delete
- **Analysis history** — re-visit and open past analyses
- **Dark / Light theme** and **FR / EN** localization
## Architecture
```
┌────────────┐ ┌──────────────────────┐
│ Frontend │────────▶│ Document Parser │
│ Vue 3 │ /api/* │ FastAPI + Docling │
│ port 3000 │ │ SQLite + file storage│
└────────────┘ │ port 8000 │
└──────────────────────┘
```
| Service | Stack | Role |
|---------|-------|------|
| **frontend** | Vue 3, TypeScript, Vite, Pinia | UI, PDF viewer, results display |
| **document-parser** | FastAPI, Docling, SQLite, pdf2image | REST API, document parsing, storage |
### Backend structure (clean architecture)
```
document-parser/
├── main.py # FastAPI app, CORS, lifespan
├── domain/ # Pure domain — no HTTP, no DB
│ ├── models.py # Document, AnalysisJob dataclasses
│ ├── ports.py # Abstract protocols (converter, chunker)
│ └── value_objects.py # ConversionResult, PageDetail, ChunkResult
├── api/ # HTTP layer (FastAPI routers)
│ ├── schemas.py # Pydantic DTOs (camelCase serialization)
│ ├── documents.py # /api/documents endpoints
│ └── analyses.py # /api/analyses endpoints
├── persistence/ # Data layer (SQLite via aiosqlite)
│ ├── database.py # Connection management, schema init
│ ├── document_repo.py # Document CRUD
│ └── analysis_repo.py # AnalysisJob CRUD
├── services/ # Use case orchestration
│ ├── document_service.py # Upload, delete, preview
│ └── analysis_service.py # Async Docling processing
└── tests/ # 199 tests (pytest)
```
### Frontend structure (feature-based)
```
frontend/src/
├── app/ # App shell, router, global styles
├── pages/ # Route-level pages
│ ├── HomePage.vue # Landing page with upload & stats
│ ├── StudioPage.vue # PDF viewer + config + results
│ ├── DocumentsPage.vue # Document management
│ ├── HistoryPage.vue # Past analyses
│ └── SettingsPage.vue # Theme, language, API URL
├── features/ # Feature modules
│ ├── analysis/ # Analysis store, API, bbox, UI components
│ ├── document/ # Document store, API, upload, list
│ ├── history/ # History store, API, navigation
│ └── settings/ # Settings store
└── shared/ # Shared utilities (types, i18n, http, format)
```
## Quick Start
Docling Studio ships two Docker image variants:
| Variant | Image tag | Size | Description |
|---------|-----------|------|-------------|
| **remote** | `latest-remote` | ~270 MB | Lightweight — delegates to an external [Docling Serve](https://github.com/DS4SD/docling-serve) instance |
| **local** | `latest-local` | ~1.9 GB | Full — runs Docling in-process, CPU-only (downloads ML models on first run) |
### Docker — remote mode (fastest)
```bash
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)
```bash
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](http://localhost:3000)
### Docker Compose (for development)
```bash
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
```
### Running Tests
```bash
# Backend (199 tests)
cd document-parser
pip install pytest pytest-asyncio httpx
pytest tests/ -v
# Frontend (129 tests)
cd frontend
npm run test:run
```
## Pipeline Options
These options map directly to Docling's [`PdfPipelineOptions`](https://docling-project.github.io/docling/usage/). See the [Docling documentation](https://docling-project.github.io/docling/) for details on each feature.
| 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 (chart, photo, diagram…) |
| `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. See [`.env.example`](.env.example).
| 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 (comma-separated) |
| `UPLOAD_DIR` | `./uploads` | File storage directory |
| `DB_PATH` | `./data/docling_studio.db` | SQLite database path |
| `CONVERSION_TIMEOUT` | `600` | Max seconds for a single Docling conversion |
## CI / Release
GitHub Actions pipelines (see [`.github/workflows/`](.github/workflows/)):
| Workflow | Trigger | What it does |
|----------|---------|--------------|
| **CI** | push to `main`, pull requests | Lint + type check + Backend tests + Frontend tests + build |
| **Release** | push tag `v*` | Build & push **two** multi-arch Docker images (`remote` + `local`) to `ghcr.io` |
| **Docs** | push to `main` (docs changes) | Build & deploy MkDocs to GitHub Pages |
We follow [Semantic Versioning](https://semver.org/) with a simplified Git Flow. See [CONTRIBUTING.md](CONTRIBUTING.md) for the full release process.
## Performance & System Requirements
| Document type | Pages | Approx. time (CPU) |
|---------------|-------|---------------------|
| Simple report | 5–10 | ~30s–1 min |
| Research paper | 10–30 | ~1–2 min |
| Large document | 100+ | ~2–5 min |
### Docker Desktop settings
| | Remote image | Local image |
|---|---|---|
| **Image size** | ~270 MB | ~1.9 GB |
| **Memory** | 2 GB | 6 GB (recommended 8 GB+) |
| **CPUs** | 2 | 4 (recommended 8+) |
### Platform support
All Docker images are multi-arch (linux/amd64 + linux/arm64). No GPU required.
## Tech Stack
- **Frontend**: Vue 3, TypeScript, Vite, Pinia, DOMPurify
- **Backend**: FastAPI, Docling 2.x, SQLite (aiosqlite), pdf2image
- **CI**: GitHub Actions
- **Infra**: Docker Compose + Nginx
## Contributing
Contributions are welcome! Please open an issue first to discuss what you'd like to change.
## License
[MIT](LICENSE) — Pier-Jean Malandrino