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ZGI - All-in-One AI Chat Interface

ZGI is an intuitive llm platform that supports multiple LLM providers, integrates various plugins, and provides a personalized AI assistant experience.

🌟 Key Features

🌟 Key Features of ZGI

  • 🧠 Multi-Model Integration: Seamlessly connect with a variety of language models, including cloud-based options like OpenAI and local models such as LLaMA.
  • 🔌 Plugin Ecosystem: Enhance platform capabilities with a wide range of third-party plugins, including function calling for advanced interactions.
  • 📄 RAG-Enhanced Retrieval: Interact with various file formats like PDF, Markdown, JSON, Word, Excel, and images to build a powerful information retrieval system.
  • 🤖 Custom AI Agents: Create and tailor AI agents for specific tasks, providing solutions perfectly suited to your needs.
  • 🗣️ Text-to-Speech: Convert AI-generated text into speech for a hands-free experience.
  • 🎙️ Speech-to-Text (Coming Soon): Use voice input to interact with AI naturally and efficiently.
  • 💾 Local Storage: Securely store data locally using in-browser IndexedDB, ensuring privacy and faster access.
  • 📤📥 Easy Import/Export: Effortlessly move documents with robust data portability for smooth migration and backups.
  • 📚 Knowledge Spaces (Coming Soon): Build custom knowledge bases to store and access information tailored to your interests.
  • 👤 Personalization: Utilize the memory plugin for more contextual, personalized AI responses that adapt to your unique workflow.

🗺 Roadmap

  • 🎙️ Chat with PDF: Coming soon.
  • 📚 Knowledge Spaces: Coming soon.

🚀 Quick Start

Prerequisites

  • Ensure you have yarn or bun installed.

Installation

  1. Clone the repository:
    git clone https://github.com/zgiai/zgi.git
    cd zgi
  2. Install dependencies:
    yarn install
    # or
    bun install
  3. Start the development server:
    yarn dev
    # or
    bun dev
  4. Open your browser and navigate to: http://localhost:3000.

📦 Deployment

  • Detailed instructions for deployment will be added soon. For now, you can use popular platforms like Vercel or Netlify to deploy the app.

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  • TypeScript 49.2%
  • Python 44.3%
  • JavaScript 2.9%
  • Shell 1.6%
  • CSS 1.6%
  • Dockerfile 0.4%