Autonomous software generation system. Describe what you want, get working code with tests.
17 specialized AI agents coordinate via a ReAct (Reason-Act-Observe) loop to plan, research, architect, code, review, secure, and execute — producing complete project directories with source code, tests, and documentation.
User Goal
|
v
+------------------+
| Orchestrator | ReAct loop controller
+------------------+
|
v
+------------------+ +------------------+ +------------------+
| Planner | --> | Researcher | --> | Architect |
| (task breakdown) | | (web search) | | (file contracts) |
+------------------+ +------------------+ +------------------+
|
v (per task)
+------------------+ +------------------+ +------------------+
| Coder | --> | Critic | --> | Security |
| (code generation)| | (score 1-10) | | (static scan) |
+------------------+ +------------------+ +------------------+
| |
| score < 7 ? revise | score >= 7 ? approve
+<------------------------+
|
v
+------------------+ +------------------+ +------------------+
| Executor | --> | Tester | --> | Docs |
| (run & debug) | | (pytest runner) | | (README gen) |
+------------------+ +------------------+ +------------------+
|
v
workspace/projects/{slug}/
src/ tests/ docs/
main.py test_main.py README.md
- 17 agents: Planner, Researcher, Architect, Coder, Coder Fast, Critic, Executor, Security, Optimizer, Docs, Tester, Linter, Builder, UI Tester, Profiler, Analyzer, Orchestrator
- Hybrid LLM routing: Vertex AI (Gemini 2.5 Flash) for core pipeline, Blackbox (Claude Haiku, Qwen, Devstral) for auxiliary agents
- Quality gate: Critic scores code 1-10; < 7 triggers revision, < 4 triggers replan
- Auto-fix pipeline: Syntax checking, truncation repair, LLM-based error correction
- Security scanning: Regex-based static analysis for secrets, injection, unsafe APIs
- Web dashboard: FastAPI + WebSocket real-time monitoring
- Telegram bot: Send a goal, receive a ZIP with generated project
- Vector memory: ChromaDB semantic search across past projects
- Cost tracking: Per-project token and cost accounting ($0.00-$0.30/project)
# Clone
git clone https://github.com/your-username/Multi-Agent.git
cd Multi-Agent/multi_agent_system
# Install
pip install -r requirements.txt
# Configure
cp .env.example .env
# Edit .env: set VERTEX_PROJECT, VERTEX_LOCATION, BLACKBOX_API_KEY
# Authenticate GCP
gcloud auth application-default login
# Run
python main.py "Build a CLI todo app in Python"# Interactive mode
python main.py
# Single goal
python main.py "Flask REST API with SQLite"
# Demo project
python main.py --demo
# Web dashboard
python -m api.main_api # http://localhost:8000
# Telegram bot
python -m telegram_bot.botcd multi_agent_system
pytest # 126+ tests
pytest -v # verbose
pytest tests/test_api.py # API tests
pytest tests/test_auth.py # auth tests
pytest tests/test_routing.py # model routing
pytest tests/test_tools.py # tool testsmulti_agent_system/
agents/ # 17 specialized agents
api/ # FastAPI web dashboard + WebSocket
config/ # MODEL_ROUTING, pricing, settings
core/ # BaseAgent, Orchestrator, LLMClient, MessageBus, Memory
telegram_bot/ # Telegram interface
tools/ # Code runner, file manager, shell, web search, etc.
tests/ # 126+ unit and integration tests
workspace/ # Generated projects output
main.py # CLI entry point
| Variable | Required | Description |
|---|---|---|
VERTEX_PROJECT |
Yes | GCP project ID for Vertex AI |
VERTEX_LOCATION |
Yes | GCP region (e.g. us-central1) |
BLACKBOX_API_KEY |
Yes | Blackbox API key for auxiliary agents |
TELEGRAM_BOT_TOKEN |
No | Telegram bot token |
TELEGRAM_USER_ID |
No | Allowed Telegram user ID |
WEB_PASSWORD |
No | Web dashboard login password |
MAOS_USER_NAME |
No | User name for profiler agent |
MIT