🤖 Local GPT Playground

Welcome to the Local GPT Playground! This repository contains various implementations of running a local Large Language Model (LLM) using Ollama and Python.

Whether you prefer Streamlit for quick prototyping or Chainlit for a production-ready chat interface, you will find simple, boilerplate code here to get you started.

Why Local? 100% Privacy. Zero Cost. Offline Access.

📂 Repository Structure

The project is organized by the frontend framework used:

.
├── streamlit_app/      # Implementation using Streamlit (Web UI)
│   └── app.py
├── chainlit_app/       # Implementation using Chainlit (Chat UI)
│   └── app.py
├── requirements.txt    # Python dependencies
└── README.md

🛠️ Prerequisites

Before running the python scripts, you need the "Brain" of the operation.

1. Install Ollama: Download and install from ollama.com.
2. Pull a Model: Open your terminal and download a model (e.g., Llama3).

   ollama pull llama3

🚀 Installation

1. Clone this repository:

   git clone [https://github.com/your-username/local-gpt-playground.git](https://github.com/your-username/local-gpt-playground.git)
   cd local-gpt-playground

2. Install dependencies: It is recommended to use a virtual environment.

   pip install -r requirements.txt

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💻 Usage

Option 1: Streamlit Version

Simple, clean, and great for building dashboards around your AI.

streamlit run streamlit_app/app.py

Option 2: Chainlit Version

A more "ChatGPT-like" experience with built-in features for chat history and settings.

chainlit run chainlit_app/app.py -w

---

🔮 Roadmap & Updates

This repository is a living project! I am constantly experimenting with new ways to deploy local AI.

Come back soon to check out:

• Gradio Implementation: Another popular UI framework.
• RAG (Retrieval Augmented Generation): Chat with your own PDF files locally.
• FastAPI Backend: Turning this into a proper API service.

⭐ Star this repo to get notified when new implementations are added!

🤝 Contributing

Got a cool way to run Ollama? Feel free to open a Pull Request!

1. Fork the Project
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. Open a Pull Request