README.md

metadata

title: D365stuff Chat
emoji: 🦀
colorFrom: yellow
colorTo: red
sdk: docker
pinned: false

D365Stuff Chat

A conversational AI interface for the D365Stuff blog, built by TheDataGuy.pro using the Let's Talk framework. This application allows users to interact with the blog's content in a natural, conversational way.

Features

• 🤖 AI-powered chat interface for D365Stuff blog content
• 🔍 Smart search and retrieval of relevant blog posts
• 💻 Code examples with syntax highlighting
• 🌐 Multi-language support
• 🎨 Dark/Light theme support
• 📤 File upload capabilities
• 🔒 Privacy-focused (no permanent conversation storage)

Prerequisites

• Python 3.13 or higher
• Docker (optional, for containerized deployment)
• UV package manager

Installation

1. Clone the repository:

git clone https://github.com/mafzaal/d365stuff-chat.git
cd d365stuff-chat

2. Install dependencies using UV:

uv sync

3. Set up environment variables:

cp .env.example .env
# Edit .env with your configuration

Running the Application

Local Development

uv run chainlit run app.py --port 8000

Docker Deployment

docker build -t d365stuff-chat .
docker run -p 7860:7860 d365stuff-chat

Project Structure

.
├── app.py              # Main application entry point
├── prompt.py           # Chat prompt configuration
├── pipeline.py        # Blog data processing pipeline
├── data/             # Blog post data
├── stats/            # Processing statistics
└── .chainlit/        # Chainlit configuration

Configuration

The application can be configured through:

• .env file for environment variables
• .chainlit/config.toml for UI settings

Blog Data Processing

The application includes a pipeline for processing blog posts:

python pipeline.py [--force-recreate] [--data-dir DATA_DIR] [--output-dir OUTPUT_DIR]

Options:

• --force-recreate: Force recreation of the vector store
• --data-dir: Directory containing blog posts
• --output-dir: Directory for stats and artifacts
• --no-chunking: Process whole documents without chunking
• --no-save-stats: Skip saving document statistics

Contributing

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

Built With

• Chainlit - Chat UI framework
• LangChain - AI agent framework
• Let's Talk - Conversational AI framework by TheDataGuy.pro
• Docker - Containerization

Acknowledgments

• Built by TheDataGuy.pro using the Let's Talk framework
• Blog content from D365Stuff

License

This project is licensed under the MIT License - see the LICENSE file for details.