Project scaffolding tool for LeafMesh
Project description
create-leafmesh
Project scaffolding tool for LeafMesh — the YAML-native multi-agent orchestration platform.
Install
pip install create-leafmesh
Create a Project
create-leafmesh create my-project
cd my-project
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
python main.py
CLI Options
# Create in a specific directory
create-leafmesh create my-project -o /path/to/dir
# Skip git initialization
create-leafmesh create my-project --no-git
# Interactive mode (prompts for project name)
create-leafmesh create
Generated Project Structure
my-project/
configs/
config.yaml # Agent definitions, mesh wiring, HITL config
agency/
greeter_agent.py # LLM agent with @pre_compose
processor_agent.py # Programmatic agent with @conditional_chain
researcher_agent.py # LLM agent with @chain_with_results + smart memory
fallback_researcher_agent.py # Fast fallback (race pattern)
advisor_agent.py # LLM fan-in with @chain + @compose
scheduler_agent.py # Cron-scheduled agent
tools.py # Custom tools (@global_tool, @tool)
external_agents.py # Integration reference (CrewAI, LangGraph, etc.)
main.py # Entry point
hitl_stub_receiver.py # Webhook stub for testing HITL locally
requirements.txt
.env # API keys
Dockerfile
docker-compose.yml # Redis + app
What's Included
- 8 agents showcasing all 4 agent types (human, llm, programmatic, external)
- Human-in-the-Loop (HITL) with dual webhook mode and
from_agentrouting - Fan-in/fan-out with OR expressions (
processor AND (researcher OR fallback)) - Smart memory with hybrid recency/relevance scoring
- Scheduled agents with cron expressions
- Custom tools with access control and categories
- All 5 decorators:
@pre_compose,@chain,@chain_with_results,@conditional_chain,@compose - HITL test stub (
hitl_stub_receiver.py) for local webhook testing - Docker-ready with Redis included
- Full README with HITL walkthrough (2 scenarios, step-by-step)
Requirements
- Python 3.10+
- Redis server running (default: localhost:6379)
- At least one LLM API key (e.g.
OPENAI_API_KEYin.env)
Links
License
MIT
Project details
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