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_agent routing
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_KEY in .env)

License

MIT

Metadata

Release files for create-leafmesh 2.7.4

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Source distribution (sdist)

Source distribution for create-leafmesh 2.7.4
File	Size	Uploaded	Provenance
create_leafmesh-2.7.4.tar.gz	1.4 MB	Oct 5, 2026	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for create-leafmesh 2.7.4
File	Interpreter	ABI	Platform	Reset
create_leafmesh-2.7.4-py3-none-any.whl 1.7 MB Oct 5, 2026 Without provenance	Python 3	none	any	Details

Total release size: 3.1 MB

Release files / create_leafmesh-2.7.4.tar.gz

Download URL	create_leafmesh-2.7.4.tar.gz
Size	1.4 MB
Tags	Source
SHA-256 checksum How to use checksums	`869cb6290619edc552d344f23dca86177bbb647a1b93e19098a4037741a111c4`
BLAKE2b-256 checksum How to use checksums	`6cbb4f19af9263301c705377c4cc748a95639c9bc352bf0e8ed030d1fc1ebef6`
Upload date	Oct 5, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.14.2`

Release files / create_leafmesh-2.7.4-py3-none-any.whl

Download URL	create_leafmesh-2.7.4-py3-none-any.whl
Size	1.7 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`ad2e696bed7f59e6ae6bac1ca9f8ff61e5f83aa98775ca10e96a954603b459ea`
BLAKE2b-256 checksum How to use checksums	`0b31155401502be0b2b48aebfc054955aff0770e7cdc07087bc6159666eaef81`
Upload date	Oct 5, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.14.2`

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