🤖 MultiChat

Seamless Conversations Across Multiple LLMs

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🌍 The Problem

Ever started a chat with one LLM, but then realized another model (say Mistral, DeepSeek, or an open-source gem) would give you better answers? Right now, switching models means copy-pasting conversations, losing context, and wasting time.

That’s broken.

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⚡ The Solution: MultiChat

MultiChat is an AI orchestration layer that lets you:

• ✅ Start a chat with one model and seamlessly continue with another.
• ✅ Run parallel responses from multiple LLMs and compare answers.
• ✅ Build pipelines where different models handle different steps.
• ✅ Support both closed-source APIs and open-source LLMs.
• ✅ Keep your conversations synced, sessionized, and reusable.

Think of it as your “multi-agent switchboard” for the AI world.

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✨ Features

• 🔄 Continue Anywhere: Pick up your conversation in DeepSeek, Mistral, Qwen, or any LLM.
• 🧩 Extensible Connectors: Add new LLMs with a simple plug-and-play connector.
• ⚡ Parallel Mode: Ask multiple models the same thing, compare instantly.
• 📡 Pipelines: Chain models (e.g., Mistral for analysis → DeepSeek for summarization → Qwen for creativity).
• 🛠 Developer Friendly: Simple API endpoints to integrate into any app.

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🏗 Architecture

MultiChat is powered by:

• Backend: FastAPI (Python)
• Frontend: React (Next.js/Vite)
• LLM Connectors: DeepSeek, Mistral, Qwen, and more
• Middleware: Session tracking, orchestration logic

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🚀 Getting Started

Prerequisites

• Python 3.10+
• Node.js 18+
• API keys for your chosen LLMs (if using hosted ones)

Clone the Repo

git clone https://github.com/manitejagaddam/Multi-Chat.git
cd MultiChat

Backend Setup

cd server
pip install -r requirements.txt
uvicorn main:app --reload

Frontend Setup

cd client
npm install
npm run dev
# open another terminal
cd client
npm run start

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🧩 Usage

Once running:

• Visit http://localhost:3000 for the UI.
• Use /chat and /chatall endpoints for backend orchestration.

Example (parallel chat request):

{
  "session_id": "abc123",
  "message": "Explain quantum computing in simple terms",
  "models": ["deepseek", "mistral", "qwen"]
}

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🤝 Contributing

We welcome contributions from the community to make MultiChat even better!

Contribution Guidelines

1. Fork the repository and clone it locally.

2. Create a new branch for your feature or bugfix:

   git checkout -b feature/your-feature-name

3. Write clean, documented code and include tests if applicable.

4. Commit your changes with a descriptive message:

   git commit -m "Add feature: your feature description"

5. Push your branch to your forked repo:

   git push origin feature/your-feature-name

6. Open a Pull Request (PR) describing your changes clearly.

7. Ensure your PR passes all checks and reviews before merging.

Code of Conduct

We expect contributors to follow our Code of Conduct to ensure a welcoming environment for everyone.

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📜 License

This project is licensed under the Apache 2.0 License – see the LICENSE file for details.

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⭐ Vision

MultiChat is just the beginning. Our goal is to build a universal orchestration platform where multiple LLMs and agents collaborate — not compete — to give you the best possible intelligence layer for apps, research, and daily life.

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