AI Agent Workshop Setup Guide

Hands-on Session Requirements:

Today, we will utilize LLM via API by signing up for GROQ Inference (which offers a free trial) or XAI-Grok2 API (which provides a free tier in exchange for sharing content). Alternatively, you can run an LLM locally, but you'll also need to run the Colab Notebook locally. (Optional Tools: ollama, LLM Studio)

Colab is available here: https://gist.github.com/marscod/9e1cd2dfd07d8448d52214a63851a394

Follow these steps to set up your environment:

1. Fork the Repository

Click the Fork button on GitHub to create your own copy of the repository.

2. Get an API Key (XAI Grok2)

1. Visit the X.AI API Documentation to obtain your API key.
2. Use the provided .env_sample file as a template to create your own .env file at Agents/.env.
3. Add your API key(s) to the new .env file. You can leave the GROQ_API_KEY as is if you're using Grok2.

GROQ_API_KEY="YOUR GROQ KEY"
XAI_API_KEY="YOUR XAI KEY"

3. Open the Forked Repository in GitHub Codespaces

Modify the URL by replacing github.com with github.dev.

4. Sign in to GitHub

Sign in using your GitHub account to proceed.

5. Select a Deployment

A minimal resource allocation (e.g., 2 cores) is sufficient.

⚠️ Note: To avoid unnecessary charges, stop the server once you complete the task, even if it is idle.
Open GitHub Codespaces, select ... for the codespace, and choose Stop.

6. Wait for VS Code to Launch

The environment will open in Visual Studio Code, and Python installation will begin automatically.

7. Open the Terminal

Access the terminal from the VS Code interface.

8. Run the Required Commands

Follow the instructions in the repository to set up your environment.

./setup.sh 
source venv/bin/activate

Run Server

./run.sh

8. (Optional) Make the Server Public
   If needed, you can expose the port to the public, allowing others to access your AI Agent.

Contribution

We welcome contributions! Feel free to submit a Pull Request (PR) from your forked repository.