AI Security for Developers and Practitioners (Full Day)

Building safe, trustworthy, and resilient AI systems

These instructions will guide you through configuring a GitHub Codespaces environment that you can use to run the course labs.

1. Change your codespace's default timeout from 30 minutes to longer. To do this, when logged in to GitHub, go to https://github.com/settings/codespaces and scroll down on that page until you see the Default idle timeout section. Adjust the value as desired.

2. Click on the button below to start a new codespace from this repository.

Click here ➡️

3. Then click on the option to create a new codespace.

This will run for several minutes while it gets everything ready. While this is running, you can do step 4.

4. Get a free API key for groq to enable use of more powerful models for some of the labs.

a. In a browser, go to https://console.groq.com and create an account. (If you have an email with a button to confirm, make sure the link is trying to open in the same browser where you were using groq before. If not, you can copy the link from the "click here" section and paste into the right browser.)

b. In the top right of the Groq screen, click on API Keys

c. Then click the Create API Key button.

d. Fill in the information, verify you're human if asked, and click Submit.

e. Copy the key (you can't view it again later).

5. Ensure the codespace is done setting up.

After the initial startup, it will run a script to setup the python environment, install needed python pieces, install Ollama, and then download the models we will use. This will take several more minutes to run. It will look like this while this is running.

The codespace is ready to use when you see a prompt like the one shown below in its terminal.

6. Setup your groq key in your codespace.

In the codespace TERMINAL, run the command below to set your key for all terminals. Paste your key when prompted and then hit Enter:

source scripts/setup-key.sh

Afterwards, you should see output that indicates two environment variables (AGENT_PROVIDER and GROQ_API_KEY) are set.

7. Run the warm-up script for faster LLM interactions.

python scripts/warmup_ollama.py 

8. Open up the labs.md file so you can follow along with the labs. You can either open it in a separate browser instance or open it in the codespace.

Now, you are ready for the labs!

NOTE: If your codespace times out and you need to reopen it

1. Go to https://github.com/your_github_userid/codespaces
2. Find the codespace in the list, right-click, and select Open in browser
3. Repeat steps 6 & 7 from the main section above to set the Groq env keys and run the warmup script again.
   
   

Troubleshooting

• A lab reports it cannot reach Ollama - the server isn't running. Run bash scripts/startOllama.sh from the repo root, then retry. Check /tmp/ollama.log if it persists.
• The first model call is slow (~30-60s) - run python3 scripts/warmup_ollama.py once, then retry. Later calls in the same session are fast.
• Groq returns 429 (rate limit) - you've exceeded the free tier's ~30 req/min. Wait a few seconds and retry, or export LLM_BACKEND=ollama to switch to the local model. Make sure each person uses their own key.
• Groq returns 401 / invalid key - GROQ_API_KEY is missing or wrong. Re-copy the key from console.groq.com, or unset it to fall back to Ollama.
• A python command "hangs" - the RAG and MCP labs use interactive prompts or run servers. Follow the lab's stop instruction (quit or Ctrl+C).
• Address already in use in Lab 4 - a previous server is still running. Stop it with Ctrl+C, or kill $(lsof -t -i:8000) / :9000.
• ModuleNotFoundError: yaml in Lab 7 - run pip install -r requirements.txt from the repo root.
• Skeleton file errors before merging - the skeleton files are meant to be completed via the code -d diff-merge step first. Each lab tells you when to merge.

License and attribution

For educational use only by the attendees of our workshops.

© 2026 Tech Skills Transformations and Brent C. Laster. All rights reserved.