paperless-gpt

_{💡 Maintained by Icereed. Proudly supported by BubbleTax.de – automated, BMF-compliant tax reports for Interactive Brokers traders in Germany.}

paperless-gpt seamlessly pairs with [paperless-ngx][paperless-ngx] to generate AI-powered document titles and tags, saving you hours of manual sorting. While other tools may offer AI chat features, paperless-gpt stands out by supercharging OCR with LLMs-ensuring high accuracy, even with tricky scans. It also connects documents that belong together: a reminder gets linked to the invoice it is about, an amendment to its contract, a letter to the case it cites. If you're craving next-level text extraction and effortless document organization, this is your solution.

https://github.com/user-attachments/assets/bd5d38b9-9309-40b9-93ca-918dfa4f3fd4

☁️ Self-host it or have it hosted
paperless-gpt is free, open source and fully self-hostable. If you're in Germany, Austria or Switzerland and would rather not run it yourself, server.camp offers managed paperless-ngx with paperless-gpt and shares part of that revenue with this project. → Managed hosting

❤️ Support This Project
If paperless-gpt is helping you organize your documents and saving you time, please consider sponsoring its development. Your support helps ensure continued improvements and maintenance!

Key Highlights

1. LLM-Enhanced OCR
   Harness Large Language Models (OpenAI or Ollama) for better-than-traditional OCR—turn messy or low-quality scans into context-aware, high-fidelity text.

2. Links related documents for you 🔗
   Reminders, credit notes, amendments, delivery notes and follow-up letters all cite a number: an invoice, contract, order or case number (Aktenzeichen). paperless-gpt reads that reference, finds the matching document in your archive and fills a paperless-ngx Document Link field, so both documents point at each other. Order, delivery note and invoice end up connected; a contract carries its amendments and termination; every letter citing the same file number lands in one case file, no matter who sent it.

Built to be conservative: the model only extracts the reference, paperless-gpt does an exact whole-word lookup, and anything ambiguous is left unlinked rather than guessed. → Use cases and setup

3. Use specialized AI OCR services

• LLM OCR: Use OpenAI or Ollama to extract text from images.
• Google Document AI: Leverage Google's powerful Document AI for OCR tasks.
• Azure Document Intelligence: Use Microsoft's enterprise OCR solution.
• Docling Server: Self-hosted OCR and document conversion service

4. Automatic Title, Tag & Created Date Generation
   No more guesswork. Let the AI do the naming and categorizing. You can easily review suggestions and refine them if needed.

5. Supports reasoning models in Ollama
   Greatly enhance accuracy by using a reasoning model like qwen3:8b. The perfect tradeoff between privacy and performance! Of course, if you got enough GPUs or NPUs, a bigger model will enhance the experience.

6. Automatic Correspondent Generation
   Automatically identify and generate correspondents from your documents, making it easier to track and organize your communications.

7. Automatic Custom Field Generation
   Extract and populate custom fields from your documents. Configure which fields to target and how they should be filled. This feature must be enabled in the settings, and you must select at least one custom field for it to function. Three write modes are available: - Append: This is the safest option: It only adds new fields that do not already exist on the document. It will never overwrite an existing field, even if it's empty. - Update: Adds new fields and overwrites existing fields with new suggestions. Fields on the document that don't have a new suggestion are left untouched. - Replace: Deletes all existing custom fields on the document and replaces them entirely with the suggested fields.

Fields of type Document Link are special: instead of filling in text, paperless-gpt resolves the references a document cites to the actual documents in your archive (see Links related documents above).

8. Searchable & Selectable PDFs
   Generate PDFs with transparent text layers positioned accurately over each word, making your documents both searchable and selectable while preserving the original appearance. With paperless-ngx 3.0, the searchable PDF can be added as a new version of the same document, so it keeps its ID, tags, custom fields and notes, and the original stays available as the previous version (PDF_UPLOAD_MODE=version, see PDF Upload to paperless-ngx).

9. Extensive Customization

• Customizable Prompts via Web UI: Tweak and manage all AI prompts for titles, tags, correspondents, and more directly within the web interface under the "Settings" menu. The application uses a safe default_prompts and prompts directory structure, ensuring your customizations are persistent.
• Tagging: Decide how documents get tagged—manually, automatically, or via OCR-based flows.
• AI Workflows: Give each kind of document its own trigger tag, prompts and processing steps: invoices get a title prompt tuned for invoice numbers, contracts get custom fields, private mail only gets a title. Test a workflow on a real document before saving it; workflows are plain files next to your prompts. → AI Workflows
• PDF Processing: Configure how OCR-enhanced PDFs are handled, with options to save locally or upload to paperless-ngx.

10. Simple Docker Deployment
    A few environment variables, and you're off! Compose it alongside paperless-ngx with minimal fuss.

11. Unified Web UI

• Manual Review: Approve or tweak AI's suggestions.
• Auto Processing: Focus only on edge cases while the rest is sorted for you.

12. Ad-hoc Document Analysis Perform ad-hoc analysis on a selection of documents using a custom prompt. Gain quick insights, summaries, or extract specific information from multiple documents at once.

Table of Contents

• paperless-gpt
• Key Highlights
• Table of Contents
• Managed Hosting for Germany, Austria and Switzerland
  • Fair Hosting
• Getting Started
  • Option 1: Managed Hosting
  • Option 2: Self-Hosting
  • Prerequisites
  • Security
  • Installation
  • Docker Compose
  • Manual Setup
• OCR Providers
  • 1. LLM-based OCR (Default)
  • 2. Azure Document Intelligence
  • 3. Google Document AI
  • 4. Docling Server
• OCR Processing Modes
  • Image Mode (Default)
  • PDF Mode
  • Whole PDF Mode
  • Provider Compatibility
  • Existing OCR Detection
• Enhanced OCR Features
  • PDF Text Layer Generation
  • Local File Saving
  • PDF Upload to paperless-ngx
  • Metadata Copying Limitations
  • Safety Features
  • Usage Recommendations
• Configuration
  • Environment Variables
  • Using a Different AI Provider
  • Custom Prompt Templates
  • Template Variables
• LLM-Based OCR: Compare for Yourself
  • Example 1
  • Example 2
  • How It Works
• Usage
• Troubleshooting
  • Working with Local LLMs
  • Token Management
  • PDF Processing Issues
  • Custom Field Generation Issues
• Contributing
• Support the Project
  • Support paperless-gpt through Fair Hosting
• License
• Star History
• Disclaimer

Managed Hosting for Germany, Austria and Switzerland

paperless-gpt is built to be self-hosted and remains free and open source.

If you'd rather use it without operating the infrastructure yourself, server.camp provides managed paperless-ngx hosting with paperless-gpt and the AI components it needs already set up:

• paperless-ngx and paperless-gpt ready to use
• hosting and updates managed for you
• no GPU of your