https://github.com/moyangzhan/mango-desk

Search your files using nature language
https://github.com/moyangzhan/mango-desk

ai-search file-content-search sematic-search vector-search

Last synced: 4 months ago
JSON representation

Search your files using nature language

• Host: GitHub
• URL: https://github.com/moyangzhan/mango-desk
• Owner: moyangzhan
• License: other
• Created: 2025-12-25T11:42:14.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2026-02-03T12:10:08.000Z (4 months ago)
• Last Synced: 2026-02-04T02:24:24.206Z (4 months ago)
• Topics: ai-search, file-content-search, sematic-search, vector-search
• Language: Rust
• Homepage:
• Size: 80.6 MB
• Stars: 170
• Watchers: 1
• Forks: 9
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
[English](./README.md) | [中文](./README_CN.md)

# Mango Desk

**🥭 Awake your data**  

![image](./screenshots/work.png)

[![Download](./screenshots/download-ready.svg)](https://github.com/moyangzhan/mango-desk/releases)

## What is Mango Desk?

Mango Desk is a local-first desktop app for searching your local documents with natural language.

It helps you find information based on what you remember, not file names or folder structures.

![search](./screenshots/search.gif)

### 📌 Use Cases

Mango Desk is especially useful in scenarios where you have **a large amount of local documents** and want to retrieve information using natural language.

#### Typical Use Cases

- 📝 **Personal Document Libraries**

  - Years of accumulated notes, PDFs, Word files, Markdown files. etc

  - Example: *“That note where I summarized Rust ownership rules”*

- 📂 **SVN / Git Repositories**

  - Search through design docs, READMEs, technical proposals, and historical solutions

  - Example: *“Where is the document about the permission refactor?”*

- 🏢 **Team or Company Knowledge Base**

  - Internal documents, project docs, meeting notes, onboarding materials

  - Example: *"Find all Q4 meeting notes about budget planning"*

  - Example: *"What are the company policies regarding remote work?"*

- 📚 **Research and Study Materials**

  - Papers, experiment records, literature notes

  - Example: *“What is the latest research on AI?”*

- ⚖️ **Legal and Financial Documents**

  - Contracts, policy documents, reports

  - Example: *“What is the latest company policy on data privacy?”*

### ✨ Features

- 💭 **Search by meaning, not file names**

  - Find documents by describing what you remember, even if you don’t recall exact titles or locations

- 📍 **Search by path**

  - Find documents by multiple keywords if you remember some pecific parts of the file path

- 📂 **Works with your existing local files**

  - No need to reorganize folders or rename files — Mango Desk works with what you already have

- 👀 **Real-time file & directory watching**

  - Automatically detects file and folder changes (add / modify / delete) and keeps index and search results up to date

- ⚡ **Fast and lightweight**

  - Instant search results without slowing down your system

- 🔒 **Private by default**

  - All data stays on your device, ensuring your privacy

### 🏗️ Architecture

**Indexing**

![indexing](./screenshots/mango-desk-indexing.png)

`The self-hosted model part is under development and will be integrated according to the ollama interface.`

**Search**

![search](./screenshots/mango-desk-search.png)

### 🛠️ Technology Stack

* Frontend

  * WebView（Tauri）

  * PNPM

  * Node.js

* Backend

  * Rust

  * Tauri Core

## 🚀 Setting Up

### 1. Frontend

#### Node

`node` v20+ required

It is recommended to use [nvm](https://github.com/nvm-sh/nvm) to manage multiple `node` versions.

#### PNPM

`pnpm` v9+ required

If you haven't installed `pnpm`, you can install it with the following command:

```shell

npm install pnpm -g

```

#### Install dependencies

```sh

pnpm i

```

### 2. Backend(Rust)

`rust` v1.90.0+ required

Install tools: [https://www.rust-lang.org/tools/install](https://www.rust-lang.org/tools/install)

### 3. Tauri

Install Tauri Prerequisites: 

[https://tauri.app/start/prerequisites/](https://tauri.app/start/prerequisites/)

## ▶️ Development Run

A Tauri app has at least [two processes](https://tauri.app/concept/process-model/):

- the Core Process (`backend`)

- the WebView process (`frontend`)

Both backend and frontend start with a single command:

```sh

pnpm tauri dev

```

## 📦 Building

```sh

pnpm tauri build

```

After building, the executable file is usually located in `src-tauri/target/release/`.

windows: `src-tauri/target/release/bundle/msi/Mango Desk_0.1.0_x64_en-US.msi`

## ❓ FAQ

### Q: How does Mango Desk ensure data privacy?

A: Mango Desk follows a local-first architecture to ensure data privacy:

#### Local Data Processing

- All document indexing and search operations are performed locally on your device

- No data is transmitted to external servers during normal operation

#### Exception Cases

- Only when processing images or audio files, remote models may be used (if enabled)

- These remote models are disabled by default and must be manually enabled by users

#### Data storage

- All user data remains on the local device by default

#### Architecture Details

As shown in the architecture diagram above, the entire processing pipeline is designed to keep data local, ensuring maximum privacy and security.

### Q: Why are so many models used in the code?

A: The codebase includes multiple models serving different purposes:

#### 1. Active Local Models (Enabled by Default)

- `bge-base-*`

- These models run locally on users' computers for basic document processing

- Prioritized for privacy and performance

#### 2. Remote Models (Optional)

- `gpt-5-mini` and `gpt-4o-mini-transcribe`

- Designed for image and audio parsing

- Disabled by default, can be enabled if needed

- Note: We plan to replace these with local alternatives when available

- Kept as optional features for self-hosting scenarios

#### 3. Reserved Models (Future Features)

- `qwen-turbo`, `deepseek-chat`, and `deepseek-reasoner`

- Prepared for upcoming features like:

  - Knowledge graph generation

  - Advanced document analysis

- Also serves as a foundation for developers who want to customize with these models

- Maintains flexibility for future feature expansion

## 📝 License

see the [LICENSE](LICENSE) file for details.

## 🤝 Contributing

Contributions of all kinds are welcome, including but not limited to:

* 🐛 Reporting bugs

* 💡 Suggesting new features or improvements

* 📖 Improving documentation

* 🔧 Submitting code (pull requests)

Before submitting a pull request, please consider:

1. Fork this repository

1. Create a new branch (git checkout -b feature/xxx)

1. Ensure pnpm tauri dev runs successfully locally

1. Commit changes (git commit -m 'feat: xxx')

1. Push the branch (git push origin feature/xxx)

1. Submit a Pull Request

## ⭐ Support the Project

Support Mango Desk if you find it helpful:

- Starring the repository on GitHub

- Recommending it to others

- Sharing your experience