- Open VS Code
- Open backend project as DevContainer:
Reopen in Container -> Backend Container

- Wait until VS Code has configured DevContainer – this can take a while

- Add a
.envfiles (root: env.example, langgraphstudio: env.example) - Open new terminal in VS Code
- Activate python environment in the terminal via
source .venv/bin/activateand check viawhich python - Run tests via
./manage.py test . - Start development server via
./manage.py runserver 0.0.0.0:8000and openhttp://127.0.0.1:8000/api/v1/docs/openapi/v3/orhttp://127.0.0.1:8000/api/v1/docs/asyncapi/v3/

- Not able to load
.env: Close the terminal and open it again. Make shure you are in the right environmentwhich python(source .venv/bin/activate).
- Open LangGraph Studio app
- Select
/backend/agents, which contains the langgraph project - To make the studio work, you have to comment out the lines 57-58 in
agents/workflows/tools_markdown_chatbot.py
Here are the basics commands for handling the dev database:
- Run
./manage.py makemigrations - Run
./manage.py migrate - Run
./manage.py createsuperuser:{username: cleon, password: thp.F26zeJ} - Run
./manage.py runscript seed_database