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https://github.com/eclaire-labs/eclaire

Local-first, open-source AI assistant for your data. Unify tasks, notes, docs, photos, and bookmarks. Private, self-hosted, and extensible via APIs.
https://github.com/eclaire-labs/eclaire

ai ai-assistant automation bookmark-manager bookmarks data-extraction document-processing llm local-first note-taking ocr on-device-ai open-source personal-knowledge-management privacy rest-api self-hosted task-management web-archiving

Last synced: 5 months ago
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Local-first, open-source AI assistant for your data. Unify tasks, notes, docs, photos, and bookmarks. Private, self-hosted, and extensible via APIs.

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README 

          





  

    Eclaire Logo

  




ECLAIRE



Privacy-focused AI assistant for your data





  License

  Release

  Docs

  Watch demo






  

    Eclaire demo preview (click to watch on YouTube)

  

  


  Click to watch on YouTube






  Features •

  Installation •

  Selecting Models •

  Architecture •

  Development •

  Contributing •

  Docs •

  API




---



## ⚠️ Important Notices



> [!IMPORTANT]  

> **Pre-release / Development Status**  

> Eclaire is currently in pre-release and under active development.  

Expect frequent updates, breaking changes, and evolving APIs/configuration.  

> If you deploy it, please **backup your data regularly** and review release notes carefully before upgrading.



> [!WARNING]  

> **Security Warning**  

> Do **NOT** expose Eclaire directly to the public internet.  

> This project is designed to be self-hosted with privacy and security in mind, but it is **not hardened for direct exposure**.  

>  

> We strongly recommend placing it behind additional security layers such as:  

> - [Tailscale](https://tailscale.com/) or other private networks/VPNs  

> - [Cloudflare Tunnels](https://developers.cloudflare.com/cloudflare-one/connections/connect-apps/)  

> - A reverse proxy with authentication



---



## Description



**Eclaire** is a local-first, open-source AI that organizes, answers, and automates across tasks, notes, documents, photos, bookmarks and more.



There are are lot of existing frameworks and libraries enabling various AI capabilities; few deliver a complete product allowing users to get things done. Eclaire assembles proven building blocks into a cohesive, privacy-preserving solution you can run yourself.



With AI gaining rapid adoption, there is a growing need for alternatives to closed ecosystems and hosted models, especially for personal, private, or otherwise sensitive data.



- **Self-hosted**  - runs entirely on your hardware with local models and data storage

- **Unified data**  - one place where AI can see and connect everything

- **AI-powered**  - content understanding, search, classification, OCR, and automation

- **Open source**  - transparent, extensible, and community-driven



### What's New in v0.6.0



- **Unified deployment**: frontend + backend + workers can run in a single container

- **Simplified Self-Hosting**  - new one-command `setup.sh` flow, plus a streamlined `compose.yaml`

- **Better AI Support**  - New vision models (including Qwen3-VL), llama.cpp router, improved MLX support.

- **Modern Frontend**  - Migrated from Next.js to Vite + TanStack Router

- **SQLite Support**: Full SQLite database support alongside Postgres for simpler workloads

- **Database Queue Mode**: Support Postgres or SQLite for job processing instead of Redis/BullMQ

- **New Admin CLI**  - Manage your instance from the command line



See the [CHANGELOG](./CHANGELOG.md) for full details.

  

## Features

- **Cross-platform**: macOS, Linux and Windows. 

- **Private by default**: By default all AI models run locally, all data is stored locally.

- **Unified data**: Manage across tasks, notes, documents, photos, bookmarks and more.

- **AI conversations**: chat with context from your content; see sources for answers; supports streaming and thinking tokens.

- **AI tool calling**: The assistant has tools to search data, open content, resolve tasks, add comments, create notes, and more

- **Flexible deployment**: Run as a single unified container or separate services. SQLite or Postgres. Database queue or Redis. *(See [Architecture](#architecture) section below.)*

- **Full API**: OpenAI-compatible REST endpoints with session tokens or API keys. [API Docs](https://eclaire.co/docs/api)

- **Model backends**: works with llama.cpp, vLLM, mlx-lm/mlx-vlm, LM Studio, Ollama, and more via the standard OpenAI-compatible API. *(See [Selecting Models](#selecting-models).)*

- **Model support**: text and vision models from Qwen, Gemma, DeepSeek, Mistral, Kimi, and others. *(See [Selecting Models](#selecting-models).)*

- **Storage**: all assets (uploaded or generated) live in Postgres or file/object storage.

- **Integrations**: Telegram (more channels coming).

- **Documents**: PDF, DOC/DOCX, PPT/PPTX, XLS/XLSX, ODT/ODP/ODS, MD, TXT, RTF, Pages, Numbers, Keynote, HTML, CSV, and more.

- **Photos/Images**: JPG/JPEG, PNG, SVG, WebP, HEIC/HEIF, AVIF, GIF, BMP, TIFF, and more.

- **Tasks**: track user tasks or assign tasks for the AI assistant to complete; the assistant add comments to tasks or write to separate docs.

- **Notes**: plain text or Markdown format. Links to other assets.

- **Bookmarks**: Fetches bookmarks and creates PDF, Readable and LLM friendly versions. Special handling for Github and Reddit APIs and metadata.

- **Organization**: Tags, pin, flag, due dates, etc. across all asset types.

- **Hardware acceleration**: takes advantage of Apple MLX, NVIDIA CUDA, and other platform-specific optimizations.

- **Mobile & PWA**: installable PWA; iOS & Apple Watch via Shortcuts; Android via Tasker/MacroDroid.



## Sample use cases

- Dictate notes using Apple Watch (or other smartwatch).

- Save bookmarks to read later; generate clean “readable” and PDF versions.

- Create readable and PDF versions of websites

- Extract text from photos and document images (OCR).

- Bulk-convert photos from HEIC to JPG.

- Analyze, categorize, and search documents and photos with AI.

- Create LLM-friendly text/Markdown versions of documents and bookmarks.

- Save interesting content (web pages, photos, documents) from phone, tablet, or desktop.

- Ask AI to find or summarize information across your data.

- Schedule automations (e.g., “Every Monday morning, summarize my tasks for the week.”).

- Chat with AI from web, mobile, Telegram, and other channels.

- Process sensitive information (bank, health, etc.) privately on local models.

- De-clutter your desktop by bulk-uploading and letting AI sort and tag.

- Migrate data from Google/Apple and other vendors into an open, self-hosted platform under your control.



## Screenshots



  

    Dashboard View

    Photo OCR

  

  

    Main Dashboard

    AI Assistant

  



## Installation



### Prerequisites



- **Docker** and **Docker Compose**

- **A local LLM server**  - [llama.cpp](https://github.com/ggml-org/llama.cpp) recommended



### Quick Start



```bash

mkdir eclaire && cd eclaire

curl -fsSL https://raw.githubusercontent.com/eclaire-labs/eclaire/main/setup.sh | sh

```



The script will:

1. Download configuration files

2. Generate secrets automatically

3. Initialize the database (PostgreSQL)



After setup completes:



```bash

# 1. Start your LLM servers (in separate terminals)

#    Models download automatically on first run if not already cached

llama-server -hf unsloth/Qwen3-14B-GGUF:Q4_K_XL --ctx-size 16384 --port 11500

llama-server -hf unsloth/gemma-3-4b-it-qat-GGUF:Q4_K_XL --ctx-size 16384 --port 11501



# 2. Start Eclaire

docker compose up -d

```

Open http://localhost:3000 and click "Sign up" to create your account.



See [AI Model Configuration](docs/ai-models.md) to use other AI providers and models.



### Configuration



Configuration lives in two places:

- **`.env`**  - secrets, database settings, ports

- **`config/ai/`**  - LLM provider URLs and model definitions



### Stopping



```bash

docker compose down

```



## Selecting Models



Eclaire uses AI models for two purposes:

- **Backend**: Powers the chat assistant (requires good tool calling)

- **Workers**: Processes documents and images (requires vision capability)



> **Apple Silicon**: Mac users can leverage MLX for optimized local inference. See the [configuration guide](docs/ai-models.md#mlx-on-apple-silicon) for details.



Use the CLI to manage models:



```bash

docker compose run --rm eclaire model list

```



See [AI Model Configuration](docs/ai-models.md) for detailed setup and model recommendations. 



## Architecture



Eclaire follows a modular architecture with clear separation between the frontend, backend API, background workers, and data layers.



**📋 [View detailed architecture diagram →](docs/architecture.md)**



### Key Components

- **Frontend**: Vite web application with React 19, TanStack Router, and Radix UI

- **Backend API**: Node.js/Hono server with REST APIs

- **Background Workers**: Job processing and scheduling (runs unified with backend by default)

- **Data Layer**: PostgreSQL (recommended) or SQLite for persistence; database or Redis for job queue

- **AI Services**: Local LLM backends (llama.cpp, MLX, LM Studio, etc.) for inference; Docling for document processing

- **External Integrations**: GitHub and Reddit APIs for bookmark fetching



## Roadmap

- Support for more data sources and integrations

- More robust full text indexing and search

- Better extensibility and plugin system

- Improved AI capabilities and model support

- Evals for models and content pipelines

- More hardening and security

- Top requests from the community



## Development



For contributors who want to build from source.



### Additional Prerequisites



Beyond Docker and an LLM server, you'll need:



- **Node.js ≥ 24** with corepack enabled

- **pnpm** (managed via corepack)



**Document/image processing tools:**



**macOS:**

```bash

brew install --cask libreoffice

brew install poppler graphicsmagick imagemagick ghostscript libheif

```



**Ubuntu/Debian:**

```bash

sudo apt-get install libreoffice poppler-utils graphicsmagick imagemagick ghostscript libheif-examples

```



### Setup



```bash

git clone https://github.com/eclaire-labs/eclaire.git

cd eclaire

corepack enable

pnpm setup:dev

pnpm dev

```



Access the application:

- Frontend: http://localhost:3000

- Backend: http://localhost:3001/health



### Building Docker Locally



To build and test custom Docker images:



```bash

./scripts/build.sh

docker compose -f compose.yaml -f compose.dev.yaml -f compose.local.yaml up -d

```



## Contributing

We 💙 contributions! Please read the Contributing Guide.



## Security

See [SECURITY.md](./SECURITY.md) for our policy.



## Telemetry

There should be no telemetry in the Eclaire code although 3rd party dependencies may have. If you find an instance where that is the case, let us know.



## Community & Support

Issues: [GitHub Issues](https://github.com/eclaire-labs/eclaire/issues)