Skip to main content

FastClaw - AI Agent Framework with multi-channel support

Project description

FastClaw

A lightweight but powerful AI Agent framework in Python.

PyPI Installation (Recommended)

# Install
pip install fastclaw-ai

# Run
fastclaw start

# Persistent running (recommended for server)
nohup fastclaw start > /tmp/fastclaw.log 2>&1 &

Configure Agent

After starting, visit http://localhost:8765 , click Settings in the top right corner to configure main_agent, recommended: deepseek-chat.

Or edit the config file:

vim ~/.fastclaw/workspace/data/agents/main_agent/metadata.json

CLI Usage

# Interactive chat
fastclaw chat

# New session
fastclaw chat --new

# Check status
fastclaw status

Git Clone

git clone https://github.com/kandada/fastclaw.git
cd fastclaw
pip install -r requirements.txt
# Run
python main.py start

# Persistent running
nohup python main.py start > fastclaw.log 2>&1 &

Configure Agent

After starting, visit http://localhost:8765 , click Settings in the top right corner to configure main_agent, recommended: deepseek-chat.

Or edit the config file:

vim workspace/data/agents/main_agent/metadata.json

CLI Usage

# Interactive chat
python main.py chat

# New session
python main.py chat --new

# Check status
python main.py status

Design Philosophy

FastClaw is built on the core concept of event-driven agent orchestration. Key design principles:

  • Graph-based Agent: Uses a directed graph to orchestrate agent behavior, supporting conditional branching between nodes (e.g., tool execution, response generation)
  • Event Streaming: Real-time streaming output of LLM responses for better user experience
  • Tool System: Extensible tool framework supporting Shell commands, skills, and custom integrations
  • Session Management: Persistent conversation history with multi-session support
  • Cron Scheduling: Built-in cron-style task scheduling for automated workflows

Features

  • 🤖 LLM-powered - Built on FastMind framework with streaming support
  • 🔧 Tool Calling - Execute Shell commands, skills, and more
  • Cron Jobs - Schedule tasks with cron expressions
  • 💬 Multi-channel - Feishu, iMessage integrations
  • 🎨 Extensible - Easy to add custom skills and agents
  • 🐍 Python Ecosystem - Seamlessly call professional libraries like numpy and pandas, enabling AI to use Python ecosystem tools as skillfully as humans

License

GPL-3.0

Copyright (c) 2024-2026 xiefujin. All rights reserved.

Official Website

https://www.fastclaw.world/ | https://fastclaw-ai.com/

Acknowledgments

Inspired by OpenClaw. Special thanks to the open source community.


FastClaw is powerful, but its use depends entirely on the user - all responsibility lies with the user yourself.


Author:xiefujin email: 490021684@qq.com,welcome to contact me.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fastclaw_ai-1.1.4.tar.gz (625.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fastclaw_ai-1.1.4-py3-none-any.whl (636.2 kB view details)

Uploaded Python 3

File details

Details for the file fastclaw_ai-1.1.4.tar.gz.

File metadata

  • Download URL: fastclaw_ai-1.1.4.tar.gz
  • Upload date:
  • Size: 625.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.6

File hashes

Hashes for fastclaw_ai-1.1.4.tar.gz
Algorithm Hash digest
SHA256 6005f9b8bc55a5ec20ae12258447eda8fb90e176fe5e61ed9c5e64c4ae4feb01
MD5 51b3711f6aa71d3bc033421fdc6e07b7
BLAKE2b-256 0d2e4e9640b8489e3e852c2af0aa0e74b08f474539ebb4dcfb12928b4b4706ba

See more details on using hashes here.

File details

Details for the file fastclaw_ai-1.1.4-py3-none-any.whl.

File metadata

  • Download URL: fastclaw_ai-1.1.4-py3-none-any.whl
  • Upload date:
  • Size: 636.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.6

File hashes

Hashes for fastclaw_ai-1.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 56f3170b6dbfe897f8068164f087678fe887f200ed41ecfdcaa7efa9ffb32878
MD5 10be891e9512e883429e40a60522565e
BLAKE2b-256 bce80c4bf2e513ff157253771f6a684837d4dbb2b7ceb3200a26c39e68bb6572

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page