feat: docs update

This commit is contained in:
zhayujie
2026-02-27 16:03:47 +08:00
parent d891312032
commit 6db22827f2
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---
title: Manual Install
description: Deploy CowAgent manually (source code / Docker)
---
## Source Code Deployment
### 1. Clone the project
```bash
git clone https://github.com/zhayujie/chatgpt-on-wechat
cd chatgpt-on-wechat/
```
<Tip>
For network issues, use the mirror: https://gitee.com/zhayujie/chatgpt-on-wechat
</Tip>
### 2. Install dependencies
Core dependencies (required):
```bash
pip3 install -r requirements.txt
```
Optional dependencies (recommended):
```bash
pip3 install -r requirements-optional.txt
```
### 3. Configure
Copy the config template and edit:
```bash
cp config-template.json config.json
```
Fill in model API keys, channel type, and other settings in `config.json`. See the [model docs](/en/models/index) for details.
### 4. Run
**Local run:**
```bash
python3 app.py
```
By default, the Web service starts. Access `http://localhost:9899/chat` to chat.
**Background run on server:**
```bash
nohup python3 app.py & tail -f nohup.out
```
## Docker Deployment
Docker deployment does not require cloning source code or installing dependencies. For Agent mode, source deployment is recommended for broader system access.
<Note>
Requires [Docker](https://docs.docker.com/engine/install/) and docker-compose.
</Note>
**1. Download config**
```bash
wget https://cdn.link-ai.tech/code/cow/docker-compose.yml
```
Edit `docker-compose.yml` with your configuration.
**2. Start container**
```bash
sudo docker compose up -d
```
**3. View logs**
```bash
sudo docker logs -f chatgpt-on-wechat
```
## Core Configuration
```json
{
"channel_type": "web",
"model": "MiniMax-M2.5",
"agent": true,
"agent_workspace": "~/cow",
"agent_max_context_tokens": 40000,
"agent_max_context_turns": 30,
"agent_max_steps": 15
}
```
| Parameter | Description | Default |
| --- | --- | --- |
| `channel_type` | Channel type | `web` |
| `model` | Model name | `MiniMax-M2.5` |
| `agent` | Enable Agent mode | `true` |
| `agent_workspace` | Agent workspace path | `~/cow` |
| `agent_max_context_tokens` | Max context tokens | `40000` |
| `agent_max_context_turns` | Max context turns | `30` |
| `agent_max_steps` | Max decision steps per task | `15` |
<Tip>
Full configuration options are in the project [`config.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/config.py).
</Tip>

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---
title: One-click Install
description: One-click install and manage CowAgent with scripts
---
The project provides scripts for one-click install, configuration, startup, and management. Script-based deployment is recommended for quick setup.
Supports Linux, macOS, and Windows. Requires Python 3.7-3.12 (3.9 recommended).
## Install Command
```bash
bash <(curl -sS https://cdn.link-ai.tech/code/cow/run.sh)
```
The script automatically performs these steps:
1. Check Python environment (requires Python 3.7+)
2. Install required tools (git, curl, etc.)
3. Clone project to `~/chatgpt-on-wechat`
4. Install Python dependencies
5. Guided configuration for AI model and channel
6. Start service
By default, the Web service starts after installation. Access `http://localhost:9899/chat` to begin chatting.
## Management Commands
After installation, use these commands to manage the service:
| Command | Description |
| --- | --- |
| `./run.sh start` | Start service |
| `./run.sh stop` | Stop service |
| `./run.sh restart` | Restart service |
| `./run.sh status` | Check run status |
| `./run.sh logs` | View real-time logs |
| `./run.sh config` | Reconfigure |
| `./run.sh update` | Update project code |