CoPaw
FreeAbout CoPaw
CoPaw (Co Personal Agent Workstation) is an open-source personal AI assistant workstation built on the AgentScope framework. It allows users to deploy a fully modular AI agent locally or in the cloud, connecting it to popular messaging platforms like DingTalk, Feishu, QQ, Discord, and iMessage. CoPaw distinguishes itself by offering full privacy control through local LLM execution (supporting llama.cpp and MLX), a proactive 'heartbeat' mechanism for autonomous tasks, and a long-term memory system that learns user preferences over time.
How to Use
Users can get started by installing CoPaw via 'pip install copaw' or a one-line curl script. After installation, run 'copaw init --defaults' and 'copaw app' to launch the web-based console. From the console, users can configure their preferred local or cloud models, connect chat channels, and manage automated skills.
Key Features
- Multi-Channel Chat Integration (DingTalk, Feishu, Discord, iMessage, etc.)
- Local LLM Execution (llama.cpp, MLX, and Ollama support)
- Modular Agent Architecture with decoupled Prompt, Hooks, and Tools
- Proactive Heartbeat Mechanism for scheduled autonomous tasks
- Long-Term Memory for tracking user decisions and preferences
- Extensible Skill System with built-in cron scheduling
Use Cases
- Automatically compiling daily news digests from social media and news sites
- Summarizing high-volume emails and generating weekly productivity reports
- Running private local AI models on Apple Silicon or standard hardware
- Automating desktop tasks like file organization and document summarization
- Setting up an AI assistant that proactively manages to-do lists and reminders
Key Features
Pros & Cons
- Completely free and open-source, no subscription costs
- Strong privacy through local LLM execution, no cloud data leakage
- Autonomous 'heartbeat' reduces need for manual prompting
- Adapts to users via long-term memory for personalized experience
- Broad messaging platform support for seamless integration
- Modular design allows easy customization and extension
- Requires technical knowledge for local setup and deployment
- Performance dependent on local hardware for LLM inference
- Limited to specific supported messaging platforms
- Autonomous features may need careful configuration to avoid unintended actions
- Ongoing maintenance as an open-source project
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