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.

[2026-03-06] We released v0.0.5! See the v0.0.5 Release Notes for the full changelog.

• [v0.0.5] Added: Daemon mode; Twilio voice channel; DeepSeek Reasoner support; agent interruption API; version update notifications; optional display of thinking and tool calls.
• [v0.0.5] Improved: Memory system upgrade; console UI improvements; optional channel lazy loading; Windows one-click installation script.
• [v0.0.5] Fixed: Docker configuration persistence; Ollama base URL; channel fixes; Windows compatibility; MCP client stability.
• [v0.0.5] Docs: Release notes; improved model and channel configuration guides; Docker + Ollama connection guide.
• [v0.0.5] Contributors: Thanks to new contributors: @qoli, @qbc2016, @yunlzheng, @BlueSkyXN, @sidonsoft, @lishengzxc, @pikaxinge, @linshengli, @eltociear, @liuxiaopai-ai, @Leirunlin, @pan-x-c, @garyzhang99, @celestialhorse51D, @wwx814, @nszhsl, @DavdGao, @zhangckcup.

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

Recommended reading:

• I want to run CoPaw in 3 commands: Quick Start → open Console in browser.
• I want to chat in DingTalk / Feishu / QQ: Configure channels in the Console.
• I don’t want to install Python: One-line install handles Python automatically, or use ModelScope one-click for cloud deployment.

• News
• Quick Start
• API Key
• Local Models
• Documentation
• FAQ
• Roadmap
• Contributing
• Install from source
• Why CoPaw?
• Built by
• License

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.

No Python required — the installer handles everything for you:

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 (CMD):

curl -fsSL https://copaw.agentscope.io/install.bat -o install.bat && install.bat

Windows (PowerShell):

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

Note: The installer will automatically check the status of uv. If it is not installed, it will attempt to download and configure it automatically. If the automatic installation fails, please follow the on-screen prompts or execute python -m pip install -U uv, then rerun the installer.

⚠️ Special Notice for Windows Enterprise LTSC Users

If you are using Windows LTSC or an enterprise environment governed by strict security policies, PowerShell may run in Constrained Language Mode, potentially causing the following issue:

1. If using CMD (.bat): Script executes successfully but fails to write to Path

   The script completes file installation. Due to Constrained Language Mode, it cannot automatically update environment variables. Manually configure as follows:

   • Locate the installation directory:
     • Check if uv is available: Enter uv --version in CMD. If a version number appears, only configure the CoPaw path. If you receive the prompt 'uv' is not recognized as an internal or external command, operable program or batch file, configure both paths.
     • uv path (choose one based on installation location; use if uv fails): Typically %USERPROFILE%\.local\bin, %USERPROFILE%\AppData\Local\uv, or the Scripts folder within your Python installation directory
     • CoPaw path: Typically located at %USERPROFILE%\.copaw\bin.
   • Manually add to the system's Path environment variable:
     • Press Win + R, type sysdm.cpl and press Enter to open System Properties.
     • Click “Advanced” -> “Environment Variables”.
     • Under “System variables”, locate and select Path, then click “Edit”.
     • Click “New”, enter both directory paths sequentially, then click OK to save.

2. If using PowerShell (.ps1): Script execution interrupted

Due to Constrained Language Mode, the script may fail to automatically download uv.

• Manually install uv: Refer to the GitHub Release to download uv.exe and place it in %USERPROFILE%\.local\bin or %USERPROFILE%\AppData\Local\uv; or ensure Python is installed and run python -m pip install -U uv.
• Configure uv environment variables: Add the uv directory and %USERPROFILE%\.copaw\bin to your system's Path variable.
• Re-run the installation: Open a new terminal and execute the installation script again to complete the CoPaw installation.
• Configure the CoPaw environment variable: Add %USERPROFILE%\.copaw\bin to your system's Path variable.

Once installed, open a new terminal and run:

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

# 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

# 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

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

docker pull agentscope/copaw:latest
docker run -p 127.0.0.1:8088:8088 -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.

Connecting to Ollama or other services on the host machine

Inside a Docker container, localhost refers to the container itself, not your host machine. If you run Ollama (or other model services) on the host and want CoPaw in Docker to reach them, use one of these approaches:

Option A — Explicit host binding (all platforms):

docker run -p 127.0.0.1:8088:8088 \
  --add-host=host.docker.internal:host-gateway \
  -v copaw-data:/app/working agentscope/copaw:latest

Then in CoPaw Settings → Models → Ollama, change the Base URL to http://host.docker.internal:11434/v1 or your corresponding port.

Option B — Host networking (Linux only):

docker run --network=host -v copaw-data:/app/working agentscope/copaw:latest

No port mapping (-p) is needed; the container shares the host network directly. Note that all container ports are exposed on the host, which may cause conflicts if the port is already in use.

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.

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

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.

If you use a cloud LLM (e.g. DashScope, ModelScope), you must configure an API key before chatting. CoPaw will not work until a valid key is set. See the official docs for details.

How to configure:

1. Console (recommended) — After running copaw app, open http://127.0.0.1:8088/ → Settings → Models. Choose a provider, enter the API Key, and enable that provider and model.
2. copaw init — When you run copaw init, it will guide you through configuring the LLM provider and API key. Follow the prompts to choose a provider and enter your key.
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.

CoPaw can run LLMs entirely on your machine — no API keys or cloud services required. See the official docs for details.

After installing, you can download and manage local models in the Console UI. You can also use the command line:

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

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

For common questions, troubleshooting tips, and known issues, please visit the FAQ page.

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.

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.

git clone https://github.com/agentscope-ai/CoPaw.git
cd CoPaw

# Build console frontend first (required for web UI)
cd console && npm ci && npm run build
cd ..

# Copy console build output to package directory
mkdir -p src/copaw/console
cp -R console/dist/. src/copaw/console/

# Install Python package
pip install -e .

• Dev (tests, formatting): pip install -e ".[dev]"
• Then: Run copaw init --defaults, then copaw app.

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.

AgentScope team · AgentScope · AgentScope Runtime · ReMe

Discord	X (Twitter)	DingTalk

CoPaw is released under the Apache License 2.0.

All thanks to our contributors: