MCP ExplorerExplorer

Evo Chat

@evo-familyon 9 months ago
50 NOASSERTION
FreeCommunity
AI Systems
# Evo Chat Evo Chat (Evolution Chat) is a modern open-source AI dialogue platform dedicated to creating the most elegant entry point for large model interactions. It supports integration with mainstream large language model (LLM) service providers such as ChatGPT and Deepseak, and continuously evolves with enhanced knowledge bases, multimodal processing, and Model Control Protocol (MCP) capabilities, enriching AI functionalities. It supports deployment across all platforms (Web, App, Windows, Mac, Linux), providing users with ubiquitous access to AI capabilities.

Overview

What is Evo Chat

Evo Chat is a modern open-source AI conversation platform designed to create an elegant interface for large language models, supporting integration with major LLM providers and offering continuous enhancements through various features.

Use cases

Use cases include automated customer service chatbots, virtual teaching assistants, content generation tools, and interactive Q&A systems for quick information retrieval.

How to use

Users can access Evo Chat through its web interface or applications on multiple platforms. After setting up the integration with LLM providers, users can engage in intelligent conversations, manage knowledge bases, and handle files efficiently.

Key features

Key features include intelligent conversation capabilities, knowledge base management, file management, and cross-platform deployment, allowing for seamless user experiences across different devices.

Where to use

Evo Chat can be utilized in various fields such as customer support, educational platforms, content creation, and any domain requiring interactive AI-driven conversations.

Content

Welcome to Evo Chat 👋

English | 简体中文

Version Documentation Maintenance License: Apache 2.0

Evo Chat (Evolution Chat) is a modern open-source AI conversation platform dedicated to creating the most elegant interface for large model interactions. It supports integration with mainstream Large Language Model (LLM) providers such as ChatGPT, Deepseak, and more, while continuously evolving with enhanced capabilities like knowledge base augmentation, multimodal processing, and MCP (Model Control Protocol). Supporting cross-platform deployment (Web, App, Windows, Mac, Linux), it provides ubiquitous AI accessibility for users.

🖼️ Interface Display

  • Homepage
    Homepage

  • Assistant
    Assistant

  • Knowledge Base
    Knowledge Base

  • MCP
    MCP

  • MCP Session
    MCP Session

  • Model Management
    Model Management

  • Dark Mode
    Dark Mode

✨ Features

  • [x] 💬 Intelligent Conversation

    • [x] Support for multiple model integration, providing flexible conversation capabilities
    • [x] Context-aware conversations maintaining coherence
    • [x] Knowledge base Q&A for quick information retrieval
  • [x] 🚀 Knowledge Base Management

    • [x] Support for creating, editing, and deleting knowledge bases
    • [x] Document vectorization for improved retrieval efficiency
    • [x] Vector search for quick content location
  • [x] 📁 File Management

    • [x] Support for file upload, preview, and deletion
    • [x] File categorization management
    • [x] Batch operations for improved efficiency
  • [x] 💻 Cross-Platform Support

    • [x] Web access for anywhere, anytime use
    • [x] Desktop client support (Windows, Mac, Linux)
    • [x] Mobile app with smooth experience
  • [x] 🤖 Intelligent Assistants

    • [x] Pre-configured professional domain assistants (programming, writing, translation, etc.)
    • [x] Customizable assistant roles and domains
    • [x] Independent knowledge base management for assistants
    • [x] Quick switching between different assistant scenarios
  • [x] 🔮 Advanced Features

    • [x] MCP (Model Control Protocol) protocol support

📁 Project Structure

.
├── packages
│   ├── b-component            # Shared business component library
│   ├── data-store             # Data management
│   ├── knowledge-service      # Knowledge service (electron project only)
│   ├── pglite-manager         # pglite local PostgreSQL database
│   ├── platform-bridge        # Cross-platform capabilities
│   ├── types                  # Global type definitions
│   └── utils                  # Common utility functions
├── projects
│   ├── electron-app           # Desktop client
│   ├── h5                     # Mobile application
│   └── web                    # Web application
├── scripts
│   ├── build                 # Build-related scripts
│   └── utils                 # Utility scripts
└── docs                      # Project documentation

📦 Development

Requirements

  • Node.js >= 20.18.3
  • pnpm >= 9.15.5

Getting Started

# Clone the project
git clone https://github.com/evo-family/evo-chat.git

# Enter project directory
cd evo-chat

# Install dependencies
pnpm install

# Start web
pnpm run dev:web

# Start h5
pnpm run dev:h5

# Start h5
pnpm run dev:h5

# Start electron
pnpm run dev:client

Contact

Add WeChat evo-chat to contact us

👥 Contribution Guide

Welcome to the Evo Chat open source community! We appreciate all contributions, whether it’s submitting code, reporting issues, or improving documentation.

How to Contribute

  1. Fork this repository
  2. Create your feature branch ( git checkout -b feature/AmazingFeature )
  3. Commit your changes ( git commit -m ‘Add some AmazingFeature’ )
  4. Push to the branch ( git push origin feature/AmazingFeature )
  5. Submit a Pull Request

Contributors

Thanks to all contributors:

📄 开源协议

This project is licensed under the Apache 2.0 License.

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