Summary

ChatLab is a free, open-source, desktop application designed for local chat history analysis. It targets privacy-conscious users, enabling deep insights via AI Agents and SQL queries without uploading sensitive data to the cloud. The tool aims to provide a unified interface for dissecting, querying, and reconstructing social data from various messaging platforms.

How It Works

Built with Electron, ChatLab features a main process for application lifecycle management and an IPC-isolated worker process for data handling. It employs streaming computation and multi-threading for high performance, capable of processing millions of messages smoothly. A data abstraction layer standardizes chat formats from different sources, while an integrated AI Agent leverages over 10 Function Calling tools for advanced data exploration. The user interface is rendered using Vue 3, Nuxt UI, and Tailwind CSS.

Quick Start & Requirements

Requires Node.js v20+. Installation involves running pnpm install to set up dependencies, followed by pnpm run dev to start the development server. An optional electron-fix tool is available for resolving startup issues. A preview of the interface can be accessed at chatlab.fun.

Highlighted Details

• Privacy-Centric: All chat data and configurations are stored locally; analysis occurs on-device, with AI functions being the primary exception.
• Performance: Leverages streaming computation and multi-threaded parallelism for a smooth user experience, even with millions of chat records.
• AI Integration: Features an intelligent AI Agent with over 10 Function Calling tools for dynamic data exploration and deeper insights.
• Data Standardization: A robust data abstraction layer unifies chat formats from supported platforms (WeChat, QQ, WhatsApp, with more planned).
• Visualization: Offers multi-dimensional charts for activity trends, temporal patterns, and member rankings.

Maintenance & Community

The project is explicitly stated to be in its early iteration phase, with known defects and incomplete features. Feedback is encouraged. No specific community channels (like Discord/Slack) or details on core maintainers are provided in the README.

Licensing & Compatibility

Licensed under AGPL-3.0. This strong copyleft license requires derivative works to also be open-sourced under AGPL-3.0, which may impose restrictions on commercial use or integration into proprietary software.

Limitations & Caveats

The project is in an early development stage, meaning users should expect potential bugs and missing functionalities. Specific performance benchmarks or detailed resource requirements for AI features are not provided.