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146 lines
3.1 KiB
Plaintext
146 lines
3.1 KiB
Plaintext
---
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title: Manual Install
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description: Deploy CowAgent manually (source code / Docker)
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---
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## Source Code Deployment
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### 1. Clone the project
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```bash
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git clone https://github.com/zhayujie/CowAgent
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cd CowAgent/
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```
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<Tip>
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For network issues, use the mirror: https://gitee.com/zhayujie/CowAgent
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</Tip>
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### 2. Install dependencies
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Core dependencies (required):
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```bash
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pip3 install -r requirements.txt
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```
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Optional dependencies (recommended):
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```bash
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pip3 install -r requirements-optional.txt
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```
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### 3. Install Cow CLI
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Install the command-line tool for managing services and skills:
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```bash
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pip3 install -e .
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```
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Then use the `cow` command:
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```bash
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cow help
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```
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<Note>
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This step is recommended. After installation you can use `cow start`, `cow stop`, `cow update` to manage the service, and `cow skill` to manage skills. Without the CLI, you can use `./run.sh` or `python3 app.py` to run.
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</Note>
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### 4. Configure
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Copy the config template and edit:
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```bash
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cp config-template.json config.json
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```
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Fill in model API keys, channel type, and other settings in `config.json`. See the [model docs](/en/models/index) for details.
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### 5. Run
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**Using Cow CLI (recommended):**
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```bash
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cow start
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```
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**Or run locally in foreground:**
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```bash
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python3 app.py
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```
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By default, the Web console starts. Access `http://localhost:9899` to chat.
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**Background run on server (without CLI):**
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```bash
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nohup python3 app.py & tail -f nohup.out
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```
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<Tip>
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If deploying on a server, open port `9899` in your firewall or security group to access the Web console. It's recommended to restrict access to specific IPs for security.
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</Tip>
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## Docker Deployment
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Docker deployment does not require cloning source code or installing dependencies. For Agent mode, source deployment is recommended for broader system access.
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<Note>
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Requires [Docker](https://docs.docker.com/engine/install/) and docker-compose.
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</Note>
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**1. Download config**
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```bash
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curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
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```
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Edit `docker-compose.yml` with your configuration.
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**2. Start container**
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```bash
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sudo docker compose up -d
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```
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**3. View logs**
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```bash
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sudo docker logs -f chatgpt-on-wechat
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```
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<Tip>
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If deploying on a server, open port `9899` in your firewall or security group to access the Web console. It's recommended to restrict access to specific IPs for security.
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</Tip>
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## Core Configuration
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```json
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{
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"channel_type": "web",
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"model": "MiniMax-M2.5",
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"agent": true,
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"agent_workspace": "~/cow",
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"agent_max_context_tokens": 40000,
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"agent_max_context_turns": 30,
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"agent_max_steps": 15
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}
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```
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| Parameter | Description | Default |
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| --- | --- | --- |
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| `channel_type` | Channel type | `web` |
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| `model` | Model name | `MiniMax-M2.5` |
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| `agent` | Enable Agent mode | `true` |
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| `agent_workspace` | Agent workspace path | `~/cow` |
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| `agent_max_context_tokens` | Max context tokens | `40000` |
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| `agent_max_context_turns` | Max context turns | `30` |
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| `agent_max_steps` | Max decision steps per task | `15` |
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<Tip>
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Full configuration options are in the project [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py).
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</Tip>
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