📄 Paperless-AI

⚠️ IMPORTANT NOTICE:

This repo is currently not maintained. I appreciate all the efforts from the community pushing PRs and creating issues. I'm currently rewriting the entire codebase with a more stable, up-to-date architecture. But I'm limited to evenings, and doing support here while also working on the rewrite just isn't feasible for me. With the upcoming official AI integration in Paperless-ngx itself, I'm also not sure if I'll complete the rewrite or continue maintaining this repo at all.

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Paperless-AI is an AI-powered extension for Paperless-ngx that brings automatic document classification, smart tagging, and semantic search using OpenAI-compatible APIs and Ollama.

It enables fully automated document workflows, contextual chat, and powerful customization — all via an intuitive web interface.

💡 Just ask:
“When did I sign my rental agreement?”
“What was the amount of the last electricity bill?”
“Which documents mention my health insurance?”

Powered by Retrieval-Augmented Generation (RAG), you can now search semantically across your full archive and get precise, natural language answers.

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✨ Features

🔄 Automated Document Processing

• Detects new documents in Paperless-ngx automatically
• Analyzes content using OpenAI API, Ollama, and other compatible backends
• Assigns title, tags, document type, and correspondent
• Built-in support for:
  • Ollama (Mistral, Llama, Phi-3, Gemma-2)
  • OpenAI
  • DeepSeek.ai
  • OpenRouter.ai
  • Perplexity.ai
  • Together.ai
  • LiteLLM
  • VLLM
  • Fastchat
  • Gemini (Google)
  • ...and more!

🧠 RAG-Based AI Chat

• Natural language document search and Q&A
• Understands full document context (not just keywords)
• Semantic memory powered by your own data
• Fast, intelligent, privacy-friendly document queries
  

⚙️ Manual Processing

• Web interface for manual AI tagging
• Useful when reviewing sensitive documents
• Accessible via /manual

🧩 Smart Tagging & Rules

• Define rules to limit which documents are processed
• Disable prompts and apply tags automatically
• Set custom output tags for tracked classification
  

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🚀 Installation

⚠️ First-time install: Restart the container after completing setup (API keys, preferences) to build RAG index.
🔁 Not required for updates.

📘 Installation Wiki

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🐳 Docker Support

• Health monitoring and auto-restart
• Persistent volumes and graceful shutdown
• Works out of the box with minimal setup

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🔧 Local Development

# Install dependencies
npm install

# Start development/test mode
npm run test

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🧭 Roadmap Highlights

• ✅ Multi-AI model support
• ✅ Multilingual document analysis
• ✅ Tag rules and filters
• ✅ Integrated document chat with RAG
• ✅ Responsive web interface

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🤝 Contributing

We welcome PRs and contributions!

# Fork, clone, then:
git checkout -b feature/YourFeature
# After changes:
git commit -m "Add YourFeature"
git push origin feature/YourFeature

Then open a Pull Request via GitHub.

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🆘 Support & Community

• Issues
• Discord

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📄 License

This project is licensed under the MIT License. See LICENSE for details.

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🙏 Support Development