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:
Click the Fork button on GitHub to create your own copy of the repository.
Modify the URL by replacing github.com with github.dev.
Sign in using your GitHub account to proceed.
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.
The environment will open in Visual Studio Code, and Python installation will begin automatically.
Access the terminal from the VS Code interface.
Follow the instructions in the repository to set up your environment.
./setup.sh
source venv/bin/activate./run.sh- (Optional) Make the Server Public
If needed, you can expose the port to the public, allowing others to access your server.
We welcome contributions! Feel free to submit a Pull Request (PR) from your forked repository.