🎙️ Voice AI Agent (Streamlit + Groq API)

A simple Voice AI Agent built using Python and Streamlit, powered by the Groq API. This application allows users to ask questions about people, software, organizations, and weather through a conversational interface, with support for voice-style interaction logic.

---

🚀 Features

• 🧠 AI-powered question answering using Groq LLMs
• 🎤 Voice-style conversational agent interface
• 🌦️ Weather information queries
• 👤 General knowledge about people and organizations
• ⚡ Fast inference using Groq API
• 🖥️ Clean and interactive UI with Streamlit

---

🛠️ Tech Stack

• Python 3.9+
• Streamlit – Frontend & UI
• Groq API – Large Language Model inference
• Matplotlib / NumPy – (if used for visualizations)
• Tkinter (optional) – For additional UI logic (if applicable)

---

📸 Application Preview

---

📦 Installation

1️⃣ Clone the Repository

git clone https://github.com/your-username/voice-ai-agent.git
cd voice-ai-agent

2️⃣ Create a Virtual Environment (Recommended)

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3️⃣ Install Dependencies

pip install -r requirements.txt

---

🔑 Groq API Configuration

1. Create an account at Groq
2. Generate your Groq API Key
3. Enter the API key in the Streamlit sidebar when the app starts

⚠️ Keep your API key private. Do not hardcode it in public repositories.

---

▶️ Run the Application

streamlit run app.py

The app will open in your browser (usually at http://localhost:8501).

---

📂 Project Structure

voice-ai-agent/
│
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies
├── README.md              # Project documentation
├── assets/                # Images or icons (optional)
└── utils/                 # Helper functions (if any)

---

💬 Example Queries

• "Who is Donald Trump?"
• "What is the weather in New York?"
• "Explain what Streamlit is"
• "Tell me about Google"

---

🧠 How It Works

1. User enters a query (text/voice-style input)
2. Streamlit sends the query to the Groq API
3. Groq LLM processes the request
4. The AI-generated response is displayed in the chat interface

---

🔮 Future Improvements

• 🎧 Real-time speech-to-text (STT)
• 🔊 Text-to-speech (TTS) output
• 🌍 Live weather API integration
• 🧠 Memory-based conversations
• 🚀 Deployment on Streamlit Cloud

---

📜 License

This project is for educational and learning purposes. You may modify and use it freely.

---

👨‍💻 Author

Developed by: Shofi Ahmed Built with: Python, Streamlit & Groq API

---

⭐ If you like this project, consider giving it a star on GitHub!