FastClaw - AI Agent Framework with multi-channel support
Project description
FastClaw
a python-based light but strong lobster
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
Quick Start
Installation
git clone https://github.com/kandada/fastclaw.git
cd fastclaw
pip install -r requirements.txt
Start Server
python main.py start
# or want it remaining in background:
nohup python main.py start > fastclaw.log 2>&1 &
Agent Configuration
vim workspace/data/agents/main_agent/metadata.json
# Edit the file to configure your LLM provider and API key
# Currently supports OpenAI gateway models (DeepSeek, OpenAI, etc.), recommended: deepseek-chat
# Default agent is main_agent. To switch, modify workspace/data/settings.json
Access at http://localhost:8765 You can also select agents and enter API keys in the Settings page. API key must be provided for the agent to work properly.
CLI Usage
# Interactive chat
python main.py chat
# New session
python main.py chat --new
# Check status
python main.py status
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
License
GPL-3.0
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file fastclaw_ai-1.1.0.tar.gz.
File metadata
- Download URL: fastclaw_ai-1.1.0.tar.gz
- Upload date:
- Size: 546.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
44084f8fb6151d7865dcc8216e85c67fc7b8acd1fabae5912cfcb3604c803240
|
|
| MD5 |
598b4da35ef6f678b6eb9f6a08fdff37
|
|
| BLAKE2b-256 |
f90d701cc752ec0d26518369023f92d6d5b10b0882b271ac2164e471c820c7e7
|
File details
Details for the file fastclaw_ai-1.1.0-py3-none-any.whl.
File metadata
- Download URL: fastclaw_ai-1.1.0-py3-none-any.whl
- Upload date:
- Size: 557.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f55a9301a51c854cab5f626c6bb426f0d337e00dbb92757d7e8051eff9810372
|
|
| MD5 |
5a267bc4ba47fef93a9c06f25a7fd258
|
|
| BLAKE2b-256 |
02c38ae7d5fff2bb790b8c3ebc571f96d6bbd95caa953df605e8fe47783b4632
|