IRIS AI

A high-performance, fully customizable AI assistant interface built on Streamlit.

---

IRIS AI is an open-source AI assistant. I built this project to push the boundaries of what a Streamlit interface can look and feel like. It completely overrides the default Streamlit styling with a custom-built, modern UI, while packing serious functionality under the hood.

If you find the code useful or want to adapt the custom CSS framework for your own Streamlit projects, dropping a Star and a Fork is highly appreciated.

Features

• Blazing Fast Output: Runs on the Groq API (using Llama 3) for near-instant inference.
• Voice I/O: Native browser microphone input and seamless gTTS audio output.
• Custom UI System: 5 built-in premium CSS themes (Black, Pink, Blue, Green, White) featuring customized chat bubbles, glassmorphism sidebars, and fluid animations.
• Dynamic Integrations:
  • Live weather tracking via Open-Meteo (No API key needed).
  • Image and Web Search via Google Custom Search API integration.
  • Interactive YouTube search with embedded thumbnail cards.
• State Management: Local JSON-based memory for user profiles and chat session history.

Quick Start

1. Clone the repository

git clone https://github.com/Satharva2004/IRIS-AI-Chatbot.git
cd IRIS-AI-Chatbot
python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate
pip install -r requirements.txt

2. Set up Environment Variables
   Create a .env file in the root directory.

# Core LLM 
GEMINI_API_KEY=your_groq_api_key

# Integrations
GOOGLE_API_KEY=your_google_api_key
GOOGLE_CSE_ID=your_google_cse_id
YOUTUBE_API_KEY=your_youtube_api_key

3. Run the App

streamlit run app.py

Deployment

Deploying to Streamlit Community Cloud takes minutes:

1. Push your clone to a GitHub repository.
2. Go to share.streamlit.io and deploy a new app pointing to app.py.
3. Add your .env variables in the Streamlit Dashboard under Settings > Secrets.

Contributing

Contributions are welcome. If you want to add new tool integrations, optimize the code, or design a new CSS theme, feel free to open a PR.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/NewFeature)
3. Commit your Changes (git commit -m 'Add NewFeature')
4. Push to the Branch (git push origin feature/NewFeature)
5. Open a Pull Request