🦙 Build Your First AI Chatbot with LLaMA 3.3

Workshop Duration: 6:00 PM – 7:30 PM Format: Hybrid (In-Person & Remote) Hosted by: Versent

Welcome to our hands-on workshop! In this session, you'll learn how to build a simple command-line chatbot using Python, powered by the open-source LLaMA 3.3 model hosted on Azure AI Foundry.

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🧠 Workshop Objectives

By the end of this workshop, you will:

• Understand the basics of Large Language Models (LLMs) and LLaMA 3.3.
• Set up and configure a Python environment for API interactions.
• Build a CLI-based chatbot that communicates with the LLaMA 3.3 model.
• Learn how to structure prompts and handle responses effectively.

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🛠️ Prerequisites

Before we begin, ensure you have the following:

• Python 3.7+ installed on your machine.
• A code editor (e.g., VS Code, PyCharm) or access to an online IDE like Replit.
• Internet connectivity to access the hosted LLaMA 3.3 model.
• Your unique API Key and Endpoint URL provided by the instructor.

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📁 Project Structure

llama_chatbot/
├── chatbot.py
├── .env
└── requirements.txt

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📦 Setup Instructions

1. Clone the Repository

   If using Git:

   git clone hhttps://github.com/dylan-mccarthy/llama-hackathon

   Or download the ZIP file and extract it.

2. Create and Activate a Virtual Environment (Optional but Recommended)

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

3. Install Dependencies

   cd llama_chatbot
   pip install -r requirements.txt

4. Configure Environment Variables

   Create a .env file in the project root directory:

   LLAMA_API_URL=https://your-endpoint-url.com/v1/chat/completions
   LLAMA_API_KEY=your-api-key-here

   Replace https://your-endpoint-url.com/v1/chat/completions and your-api-key-here with the credentials provided.

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💬 Running the Chatbot

Execute the chatbot script:

python chatbot.py

You should see:

🤖 Welcome to the LLaMA 3.3 Chatbot! Type 'exit' to quit.
You:

Start typing your messages, and the chatbot will respond accordingly.

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🧪 Customization Ideas

• System Prompt: Modify the initial behavior of the chatbot by changing the system prompt in the code.

  messages = [{"role": "system", "content": "You are a helpful assistant."}]

• Adjust Parameters: Tweak temperature and max_tokens in the payload to control response creativity and length.

• Enhance CLI: Add features like command history, colored text, or even integrate with speech-to-text libraries for voice input.

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🧰 Troubleshooting

• No Response / Errors:

  • Ensure your API URL and Key are correctly set in the .env file.
  • Check your internet connection.
  • Verify that the LLaMA 3.3 model is deployed and accessible.

• Module Not Found:

  • Ensure all dependencies are installed:

    pip install -r requirements.txt

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📚 Additional Resources

• LLaMA GitHub Repository
• Azure AI Foundry Documentation
• Prompt Engineering Guide

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🙌 Acknowledgments

This workshop is proudly presented by Versent, aiming to inspire and empower the next generation of engineers and technologists.

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Feel free to reach out if you have any questions or need further assistance during the workshop. Happy coding! 🚀