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Agent Workshop · Ollama + OpenAI Agents SDK

Four-stage curriculum (Stage 0–3) for teaching the OpenAI Agents SDK with a locally hosted qwen3-coder:30b model (Ollama) and a reproducible Docker + Python virtual environment.

Quickstart

Clone the repository:

git clone https://github.com/HKUGenAI/agent_workshop.git
cd agent_workshop

Set up the Docker environment:

docker compose up -d
docker compose exec ollama ollama pull qwen3-coder:30b   # first run only; downloads the model
docker compose exec workshop bash   # Get into the workshop container

Repository Layout

  • Dockerfile, docker-compose.yml — reproducible environment with Python + Ollama.
  • stages/stage0 — orientation demo that proves the SDK wiring.
  • stages/stage1 — custom bash function tool for repository exploration.
  • stages/stage2 — custom function tools for outfit recommendations blended with an external weather MCP server.
  • stages/stage3 — multi-agent workflows simulating a "Red Team vs. Blue Team" security audit of a code file.

Each stage directory contains:

  • README.md — teaching notes, concepts, and run instructions.
  • demo.py — runnable example referenced in the guide.
  • activity/ — starter code scaffolds for hands-on practice.

Stage 0 ships only with a README and demo; later stages introduce activities.

Running Examples

Use python -m from inside the workshop container so the repository root stays on sys.path:

python -m stages.stage0.demo
python -m stages.stage1.demo
python -m stages.stage2.demo
python -m stages.stage3.demo

Append --verbose to any demo/activity command (e.g. python -m stages.stage1.demo --verbose) to stream agent lifecycle events, including tool calls and handoffs. Activities are inside each stage's activity/ folder (python -m stages.stageX.activity.<script>). Follow the TODO markers in the starter scripts.

References

Happy building!

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