ba54427445
- Conditionally mount ingestion router only when OpenSearch + embedding are configured - Add `ingestionAvailable` field to /api/health response - Add `ingestion` feature flag to frontend (hides Search nav, Ingest button, OpenSearch badge, indexed badges/filters when disabled) - Skip ingestion polling when flag is off - Make OpenSearch + embedding optional in docker-compose via profiles - Add docker-compose.ingestion.yml override for full-stack ingestion - Set BATCH_PAGE_SIZE=5 default in Docker local image - Lead Quick Start with one-liner docker run command - Document ingestion as opt-in with dedicated section - Add BATCH_PAGE_SIZE, MAX_FILE_SIZE_MB, MAX_PAGE_COUNT, RATE_LIMIT_RPM to config tables - Update test counts (380 backend, 159 frontend) - Date CHANGELOG 0.4.0, bump frontend version to 0.4.0 - Sync CONTRIBUTING.md with E2E Karate test sections Closes #180
52 lines
2.3 KiB
Markdown
52 lines
2.3 KiB
Markdown
# Docling Studio
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A visual document analysis studio powered by [Docling](https://github.com/DS4SD/docling).
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Upload a PDF, configure the extraction pipeline, and visualize the results — text, tables, images, formulas, bounding boxes — all from your browser.
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{ width="600" }
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## Features
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- **PDF viewer** with page navigation, bounding box overlay, and resizable results panel
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- **Configurable Docling pipeline** — OCR, table extraction, code/formula enrichment, picture classification & description, image generation
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- **Bounding box visualization** — color-coded element overlay directly on the PDF
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- **Chunking** — split extracted content into semantic chunks (hierarchical, hybrid, or page-based) with configurable token limits
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- **Markdown & HTML export** of extracted content
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- **Document management** — upload, list, delete
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- **Analysis history** — re-visit and open past analyses
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- **Feature flags** — capabilities adapt to the conversion engine (local vs remote)
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- **Upload limits** — configurable max file size (`MAX_FILE_SIZE_MB`) and max page count (`MAX_PAGE_COUNT`) per document
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- **Rate limiting** — configurable requests per minute per IP (`RATE_LIMIT_RPM`)
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- **Deployment modes** — self-hosted (default) or HuggingFace Spaces (with disclaimer banner)
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- **Health endpoint** — `/api/health` reports engine type, deployment mode, and database status
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- **Dark / Light theme** and **FR / EN** localization
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## Tech Stack
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| Layer | Stack |
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| **Frontend** | Vue 3, TypeScript, Vite, Pinia |
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| **Backend** | FastAPI, Docling 2.x, SQLite (aiosqlite) |
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| **CI** | GitHub Actions (lint, type-check, test, build) |
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| **Infra** | Docker Compose + Nginx |
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## Quick Start
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```bash
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# Docker (fastest)
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docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local
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```
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Open [http://localhost:3000](http://localhost:3000) and upload a PDF.
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!!! note
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The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.
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See [Getting Started](getting-started.md) for local development setup.
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## License
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[MIT](https://github.com/scub-france/Docling-Studio/blob/main/LICENSE) — Pier-Jean Malandrino
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