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CoPaw

GitHub Repo PyPI Documentation Python Version Last Commit License Code Style GitHub Stars GitHub Forks DeepWiki Discord DingTalk

[Documentation] [中文 README] [日本語]

CoPaw Logo

Works for you, grows with you.

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

Core capabilities:

Every channel — DingTalk, Feishu, QQ, Discord, iMessage, and more. One assistant, connect as you need.

Under your control — Memory and personalization under your control. Deploy locally or in the cloud; scheduled reminders to any channel.

Skills — Built-in cron; custom skills in your workspace, auto-loaded. No lock-in.

What you can do
  • Social: daily digest of hot posts (Xiaohongshu, Zhihu, Reddit), Bilibili/YouTube summaries.
  • Productivity: newsletter digests to DingTalk/Feishu/QQ, contacts from email/calendar.
  • Creative: describe your goal, run overnight, get a draft next day.
  • Research: track tech/AI news, personal knowledge base.
  • Desktop: organize files, read/summarize docs, request files in chat.
  • Explore: combine Skills and cron into your own agentic app.

News

[2026-03-02] We released v0.0.4! See the v0.0.4 Release Notes for the full changelog.

  • [v0.0.4] FEAT: Telegram channel; OpenAI & Azure OpenAI providers; Ollama SDK; coding-plan provider; model connection testing; heartbeat monitoring panel; CORS configuration; audio file support for DingTalk & Feishu.
  • [v0.0.4] FEAT: Token-based memory compaction; file block processing; embedding configuration; normalized tool_choice behavior.
  • [v0.0.4] BUGFIX: Windows file paths; empty tool calls; console workspace UI; Ollama URL & connectivity; MCP transport; browser resource leak; static asset MIME types; API headers; Playwright Docker; heartbeat parsing; media message queuing.
  • [v0.0.4] RELS: Installation scripts with PowerShell; Docker guide; channel CLI docs; Feishu SOCKS proxy; MCP & runtime docs; FAQ (EN/ZH); skill-writing guide; CONTRIBUTING; console docs; website improvements.
  • [v0.0.4] COMM: Special thanks to all new contributors: @ekzhu, @fancyboi999, @zhaozhuang521, @hobostay, @dhbxs, @longway-code, @ydlstartx, @LudovicoYIN, @fenixc9, @dittotang, @forestxieCode, @yongtenglei, @kerwin612, @luixiao0, @gongpx20069.

Table of Contents

Recommended reading:

Quick Start

pip install (recommended)

If you prefer managing Python yourself:

pip install copaw
copaw init --defaults
copaw app

Then open http://127.0.0.1:8088/ in your browser for the Console (chat with CoPaw, configure the agent). To talk in DingTalk, Feishu, QQ, etc., add a channel in the docs.

Console

One-line install (beta, continuously improving)

No Python required — the installer handles everything:

macOS / Linux:

curl -fsSL https://copaw.agentscope.io/install.sh | bash

To install with Ollama support:

curl -fsSL https://copaw.agentscope.io/install.sh | bash -s -- --extras ollama

To install with multiple extras (e.g., Ollama + llama.cpp):

curl -fsSL https://copaw.agentscope.io/install.sh | bash -s -- --extras ollama,llamacpp

Windows (PowerShell):

irm https://copaw.agentscope.io/install.ps1 | iex

Then open a new terminal and run:

copaw init --defaults   # or: copaw init (interactive)
copaw app
Install options

macOS / Linux:

# Install a specific version
curl -fsSL ... | bash -s -- --version 0.0.2

# Install from source (dev/testing)
curl -fsSL ... | bash -s -- --from-source

# With local model support
bash install.sh --extras llamacpp    # llama.cpp (cross-platform)
bash install.sh --extras mlx         # MLX (Apple Silicon)
bash install.sh --extras llamacpp,mlx

# Upgrade — just re-run the installer
curl -fsSL ... | bash

# Uninstall
copaw uninstall          # keeps config and data
copaw uninstall --purge  # removes everything

Windows (PowerShell):

# Install a specific version
irm ... | iex; .\install.ps1 -Version 0.0.2

# Install from source (dev/testing)
.\install.ps1 -FromSource

# With local model support
.\install.ps1 -Extras llamacpp      # llama.cpp (cross-platform)
.\install.ps1 -Extras mlx           # MLX
.\install.ps1 -Extras llamacpp,mlx

# Upgrade — just re-run the installer
irm ... | iex

# Uninstall
copaw uninstall          # keeps config and data
copaw uninstall --purge  # removes everything

Using Docker

Images are on Docker Hub (agentscope/copaw). Image tags: latest (stable); pre (PyPI pre-release).

docker pull agentscope/copaw:latest
docker run -p 8088:8088 -v copaw-data:/app/working agentscope/copaw:latest

Also available on Alibaba Cloud Container Registry (ACR) for users in China: agentscope-registry.ap-southeast-1.cr.aliyuncs.com/agentscope/copaw (same tags).

Then open http://127.0.0.1:8088/ for the Console. Config, memory, and skills are stored in the copaw-data volume. To pass API keys (e.g. DASHSCOPE_API_KEY), add -e VAR=value or --env-file .env to docker run.

The image is built from scratch. To build the image yourself, please refer to the Build Docker image section in scripts/README.md, and then push to your registry.

Using ModelScope

No local install? ModelScope Studio one-click cloud setup. Set your Studio to non-public so others cannot control your CoPaw.

Deploy on Alibaba Cloud ECS

To run CoPaw on Alibaba Cloud (ECS), use the one-click deployment: open the CoPaw on Alibaba Cloud (ECS) deployment link and follow the prompts. For step-by-step instructions, see Alibaba Cloud Developer: Deploy your AI assistant in 3 minutes.

API Key

If you use a cloud LLM (e.g. DashScope, ModelScope), you must set an API key before chatting. CoPaw will not work until a valid key is configured.

Where to set it:

  1. copaw init — When you run copaw init, the command has a step to configure the LLM provider and API key. Follow the prompts to choose a provider and enter your key.
  2. Console — After copaw app, open http://127.0.0.1:8088/ → Settings → Models. Select a provider, fill in the API Key field, then activate that provider and model.
  3. Environment variable — For DashScope you can set DASHSCOPE_API_KEY in your shell or in a .env file in the working directory.

Tools that need extra keys (e.g. TAVILY_API_KEY for web search) can be set in Console Settings → Environment variables, or see Config for details.

Using local models only? If you use Local Models (llama.cpp or MLX), you do not need any API key.

Local Models

CoPaw can run LLMs entirely on your machine — no API keys or cloud services required.

Backend Best for Install
llama.cpp Cross-platform (macOS / Linux / Windows) pip install 'copaw[llamacpp]' or bash install.sh --extras llamacpp
MLX Apple Silicon Macs (M1/M2/M3/M4) pip install 'copaw[mlx]' or bash install.sh --extras mlx
Ollama Cross-platform (requires Ollama service) pip install 'copaw[ollama]' or bash install.sh --extras ollama

After installing, download a model and start chatting:

copaw models download Qwen/Qwen3-4B-GGUF
copaw models # select the downloaded model
copaw app # start the server

You can also download and manage local models from the Console UI.

Documentation

Topic Description
Introduction What CoPaw is and how you use it
Quick start Install and run (local or ModelScope Studio)
Console Web UI for chat and agent config
Channels DingTalk, Feishu, QQ, Discord, iMessage, and more
Heartbeat Scheduled check-in or digest
Local Models Run models locally with llama.cpp or MLX
CLI Init, cron jobs, skills, clean
Skills Extend and customize capabilities
FAQ Common questions and troubleshooting tips
Memory Context management and long-term memory
Config Working directory and config file

Full docs in this repo: website/public/docs/.

Roadmap

Area Item Status
Horizontal Expansion More channels, models, skills, MCPs — community contributions welcome Seeking Contributors
Existing Feature Extension Display optimization, download hints, Windows path compatibility, etc. — community contributions welcome Seeking Contributors
Compatibility & Ease of Use App-level packaging (DMG, EXE) In Progress
One-click deployment: built-in deps, dev extras, install/upgrade tutorials In Progress
Release & Contributing Contributing docs and test framework In Progress
Responsive handling of community contributions In Progress
Contributing guidance for vibe coding agents Planned
Bugfixes & Enhancements Message collapse/hide in UI Planned
Skills and MCP runtime install, hot-reload improvements Planned
Context management and compression (long tool outputs, lower token usage) Planned
Multimodal support In Progress
Security Shell execution confirmation Planned
Tool/skills security Planned
Configurable security levels (user-configurable) Planned
Multimodal Voice/video calls and real-time interaction Long-term Planning
Multi-agent Built on AgentScope, native multi-agent workflows Long-term Planning
Sandbox Deeper integration with AgentScope Runtime sandboxes Long-term Planning
Self-healing Daemon agent for automated recovery and health monitoring Long-term Planning
CoPaw-optimized local models LLMs tuned for CoPaw's native skills and common tasks; better local personal-assistant usability Long-term Planning
Small + large model collaboration Local LLMs for sensitive data; cloud LLMs for planning and coding; balance of privacy, performance, and capability Long-term Planning
Cloud-native Deeper integration with AgentScope Runtime; leverage cloud compute, storage, and tooling Long-term Planning
Skills Hub Enrich the AgentScope Skills repository and improve discoverability of high-quality skills Long-term Planning

Status: In Progress — actively being worked on; Planned — queued or under design, also welcome contributions; Seeking Contributors — we strongly encourage community contributions; Long-term Planning — longer-horizon roadmap.

Get involved

We are building CoPaw in the open and welcome contributions of all kinds! Check the Roadmap above (especially items marked Seeking Contributors) to find areas that interest you, and read CONTRIBUTING to get started. We particularly welcome:

  • Horizontal expansion — new channels, model providers, skills, MCPs.
  • Existing feature extension — display and UX improvements, download hints, Windows path compatibility, and the like.

Join the conversation on GitHub Discussions to suggest or pick up work.

Install from source

git clone https://github.com/agentscope-ai/CoPaw.git
cd CoPaw
pip install -e .
  • Dev (tests, formatting): pip install -e ".[dev]"
  • Console (build frontend): cd console && npm ci && npm run build, then copaw app from project root.

Why CoPaw?

CoPaw represents both a Co Personal Agent Workstation and a "co-paw"—a partner always by your side. More than just a cold tool, CoPaw is a warm "little paw" always ready to lend a hand (or a paw!). It is the ultimate teammate for your digital life.

Built by

AgentScope team · AgentScope · AgentScope Runtime · ReMe

Contact us

Discord DingTalk
Discord DingTalk

License

CoPaw is released under the Apache License 2.0.

About

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

copaw.agentscope.io/

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