copaw-ai-assistant

What This Skill Does

CoPaw is a robust personal AI assistant framework designed to act as a unified interface between you and various communication platforms. It serves as a central hub that aggregates chat channels—such as Discord, Telegram, Feishu, DingTalk, and Matrix—into a single, extensible environment. Unlike standard chatbots, CoPaw is built for developers and power users who need granular control over their AI, offering support for custom Python-based skills, automated cron scheduling, and flexible local or cloud LLM backend integration. With a dedicated web console accessible at http://127.0.0.1:8088/, users can manage their agent's configuration, monitor logs, and tweak settings in real-time without needing to constantly restart the underlying process.

Installation

To get started, ensure you have Python 3.10–3.13 installed. The recommended method is via pip: pip install copaw. Once installed, run copaw init --defaults to generate your workspace configuration. If you prefer a containerized or script-based approach, you can use the official installer script: curl -fsSL https://copaw.agentscope.io/install.sh | bash. This is especially useful for setting up extra dependencies like Ollama for local LLM support. After initialization, run copaw app to launch the dashboard. For those who want to contribute or modify the source, cloning the repository from GitHub and performing an editable pip install is the preferred method.

Use Cases

CoPaw is ideal for managing cross-platform notifications, creating custom automated responders, or maintaining a persistent AI persona across different messaging apps. For example, you can deploy a specific skill that monitors a Telegram channel for technical questions and automatically drafts responses using a local Llama 3 instance via Ollama. It is also excellent for personal productivity; by utilizing its cron job capabilities, you can have the agent summarize daily reminders or execute data-cleaning tasks at specific intervals, ensuring your digital workspace remains organized and responsive.

Example Prompts

1. "CoPaw, please summarize the last 10 messages from the #general Discord channel and highlight any action items."
2. "Schedule a cron job to check the weather and send a briefing to my Telegram account every morning at 7:00 AM."
3. "Execute my local 'system-stats' skill and report current CPU and memory usage to the admin group on DingTalk."

Tips & Limitations

To maximize the utility of CoPaw, focus on the config.yaml file to balance performance and privacy by switching between cloud-based LLMs like GPT-4o and local models via Ollama or LlamaCPP. Keep in mind that while the framework is highly extensible, custom skills require a basic understanding of Python to ensure safe and efficient execution. Always monitor the logs in ~/.copaw/workspace/logs/ if an agent behaves unexpectedly, as this is the most reliable way to debug integration issues. Remember that extensive background tasks or high-frequency cron jobs may impact your local system's responsiveness, so test your scripts thoroughly before deploying them in production environments.