An AI-powered engineering crew that turns natural language requirements into a designed backend module, implementation, Gradio UI, and unit tests. It is a multi-agent pipeline that automates software development from requirements to delivery. You provide high-level requirements (what the system should do), a target module name, and a class name. The crew designs the solution, implements it in Python, builds a Gradio demo UI, and writes unit tests — all in one run.
The pipeline uses CrewAI with four specialized agents that collaborate sequentially. Code execution runs inside Docker for safety and isolation. Built with CrewAI and orchestrated as a sequential, multi-agent pipeline. Agents that execute code run inside Docker for isolation.
- Python 3.10–3.12
- uv (recommended) or
pip - Docker Desktop (required for agents that execute code)
- An LLM API key in your environment (for example
OPENAI_API_KEY)
From the CrewAI project root:
cd src/engineering_team
uv syncSet your API key (shell) or put it in a .env file.
export OPENAI_API_KEY="..."cd src/engineering_team
crewai runEdit src/engineering_team/src/engineering_team/main.py:
requirements: natural language specmodule_name: e.g.accounts.pyclass_name: e.g.Account
- Agents:
src/engineering_team/src/engineering_team/config/agents.yaml - Tasks:
src/engineering_team/src/engineering_team/config/tasks.yaml - Crew assembly:
src/engineering_team/src/engineering_team/crew.py
After a successful run, generated artifacts are written to:
src/engineering_team/output/
Typical files:
- Design:
{module_name}_design.md - Backend module:
{module_name} - Gradio UI:
app.py - Unit tests:
test_{module_name}
Run the app:
cd src/engineering_team/output
uv run app.pyRun tests:
cd src/engineering_team/output
uv run pytest test_accounts.py -vai_engineering_team/
├── src/engineering_team/
│ ├── src/engineering_team/
│ │ ├── config/ # agents.yaml, tasks.yaml
│ │ ├── crew.py # Crew definition
│ │ └── main.py # Entry point & inputs
│ └── output/ # Generated design, module, app, tests
└── docs/
├── architecture.md # More detailed diagrams/notes
└── developers_guide.md # How to extend the crew
- Docker errors / code execution fails: ensure Docker Desktop is installed and running. The Backend and Test agents execute code in Docker for isolation.
- Missing API key: set
OPENAI_API_KEY(or the provider key you configured inagents.yaml). - Run fails from repo root: run from
src/engineering_team/(this is the CrewAI project root).