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107 lines
4.6 KiB
Markdown
107 lines
4.6 KiB
Markdown
<div align="center">
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<img src="./public/images/chatlab.svg" alt="ChatLab" title="ChatLab" width="300" />
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Local-first chat analysis tool: Relive your social memories powered by SQL and AI Agents.
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English | [简体中文](./README.zh-CN.md)
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[Project Website](https://chatlab.fun/) ·
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[Documentation](https://chatlab.fun/usage/) ·
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[Roadmap](https://chatlabfun.featurebase.app/roadmap) ·
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[Issue Submission](https://github.com/hellodigua/ChatLab/issues)
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</div>
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ChatLab is a free, open-source, and local-first application dedicated to analyzing chat records. Through an AI Agent and a flexible SQL engine, you can freely dissect, query, and even reconstruct your social data.
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We refuse to upload your privacy to the cloud; instead, we bring powerful analytics directly to your computer.
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Currently supported: Chat record analysis for **LINE, WeChat, QQ, WhatsApp, Instagram and Discord**. Upcoming support: **Messenger, iMessage**.
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The project is still in early iteration, so there are many bugs and unfinished features. If you encounter any issues, feel free to provide feedback.
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## Core Features
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- 🚀 **Ultimate Performance**: Utilizing stream computing and multi-threaded parallel architecture, it maintains fluid interaction and response even with millions of chat records.
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- 🔒 **Privacy Protection**: Chat records and configurations are stored in your local database, and all analysis is performed locally (with the exception of AI features).
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- 🤖 **Intelligent AI Agent**: Integrated with 10+ Function Calling tools and supporting dynamic scheduling to deeply excavate interesting insights from chat records.
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- 📊 **Multi-dimensional Data Visualization**: Provides intuitive analysis charts for activity trends, time distribution patterns, member rankings, and more.
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- 🧩 **Format Standardization**: Through a powerful data abstraction layer, it bridges the format differences between various chat applications, allowing any chat records to be analyzed.
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## Usage Guides
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- [Chat Record Export Guide](https://chatlab.fun/usage/how-to-export.html)
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- [Standardized Format Specification](https://chatlab.fun/usage/chatlab-format.html)
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- [Troubleshooting Guide](https://chatlab.fun/usage/troubleshooting.html)
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## Preview Interface
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For more previews, please visit the official website: [chatlab.fun](https://chatlab.fun/)
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## System Architecture
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### Electron Main Process
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- `electron/main/index.ts` handles the application lifecycle, window management, and custom protocol registration.
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- `electron/main/ipc/` splits IPC modules by function (Window, Chat, Merge, AI, Cache) to ensure secure and controllable data exchange.
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- `electron/main/ai/` integrates multiple LLMs, featuring built-in Agent pipelines, prompt assembly, and Function Calling tool registration.
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### Worker and Data Pipeline
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- The `workerManager` in `electron/main/worker/` coordinates Worker threads, while `dbWorker` handles message routing.
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- `worker/query/*` handles activity, AI search, advanced analysis, and SQL Lab queries.
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- `worker/import/streamImport.ts` provides stream importing.
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- The `parser/` directory adopts a three-layer "sniff + parse" architecture capable of processing GB-level log files with constant memory usage.
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### Rendering Process
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- Vue 3 + Nuxt UI + Tailwind CSS manages the visualization pages.
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- `src/pages` contains business pages, while `src/components/analysis` and `src/components/charts` provide reusable components.
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- `src/stores` manages states like sessions, layout, and AI prompts via Pinia.
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- `src/composables/useAIChat.ts` encapsulates the AI conversation workflow.
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- The preload script `electron/preload/index.ts` exposes `window.chatApi/mergeApi/aiApi/llmApi`, ensuring secure isolation between the renderer and main processes.
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---
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## Local Development
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### Setup Steps
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Node.js environment requirement: v20+
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```bash
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# Install dependencies
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pnpm install
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# Start development server
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pnpm run dev
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```
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If Electron encounters exceptions during startup, you can try using `electron-fix`:
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```bash
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npm install electron-fix -g
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electron-fix start
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```
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## Contribution Guide
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Please follow these principles before submitting a Pull Request:
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- Obvious bug fixes can be submitted directly.
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- For new features, please submit an Issue for discussion first; **PRs submitted without prior discussion will be closed**.
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- Keep one PR focused on one task; if changes are extensive, consider splitting them into multiple independent PRs.
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## Privacy Policy & User Agreement
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Before using this software, please read the [Privacy Policy & User Agreement](./src/assets/docs/agreement_en.md).
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## License
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AGPL-3.0 License
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