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Docling Studio

A visual document analysis studio powered by Docling.

Upload a PDF, configure the extraction pipeline, and visualize the results — text, tables, images, formulas, bounding boxes — all from your browser.

Docling Studio architecture{ width="600" }

Docling Studio — Execution Result

Features

  • 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
  • Chunking — split extracted content into semantic chunks (hierarchical, hybrid, or page-based) with configurable token limits
  • Markdown & HTML export of extracted content
  • Document management — upload, list, delete
  • Analysis history — re-visit and open past analyses
  • Feature flags — capabilities adapt to the conversion engine (local vs remote)
  • Upload limits — configurable max file size (MAX_FILE_SIZE_MB) and max page count (MAX_PAGE_COUNT) per document
  • Rate limiting — configurable requests per minute per IP (RATE_LIMIT_RPM)
  • Deployment modes — self-hosted (default) or HuggingFace Spaces (with disclaimer banner)
  • Health endpoint — /api/health reports engine type, deployment mode, and database status
  • Dark / Light theme and FR / EN localization

Tech Stack

Layer Stack
Frontend Vue 3, TypeScript, Vite, Pinia
Backend FastAPI, Docling 2.x, SQLite (aiosqlite)
CI GitHub Actions (lint, type-check, test, build)
Infra Docker Compose + Nginx

Quick Start

# Docker (fastest)
docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local

Open http://localhost:3000 and upload a PDF.

Note

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

See Getting Started for local development setup.

License

MIT — Pier-Jean Malandrino