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feat: add Clawdbot integration skills (#3428)
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.claude/skills/higress-clawdbot-integration/SKILL.md
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.claude/skills/higress-clawdbot-integration/SKILL.md
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# Higress Clawdbot Integration SKILL
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Deploy and configure Higress AI Gateway for Clawdbot integration.
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## Description
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This skill helps users deploy Higress AI Gateway and integrate it with Clawdbot. It provides:
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1. **One-click deployment**: Download and run the AI Gateway setup script
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2. **Model provider configuration**: Configure LLM providers via CLI parameters
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3. **Auto-routing setup**: Enable intelligent model routing based on message content
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4. **Session monitoring**: Track token usage and conversation history
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## When to Use
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Use this skill when:
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- User wants to deploy Higress AI Gateway
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- User wants to configure Clawdbot to use Higress as a model provider
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- User mentions "higress", "ai gateway", "model gateway", "统一网关"
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- User wants to set up model routing or auto-routing
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## Prerequisites
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- Docker installed and running
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- Internet access to download the setup script
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- LLM provider API keys (at least one)
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## Workflow
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### Step 1: Download Setup Script
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Download the official get-ai-gateway.sh script:
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```bash
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curl -fsSL https://raw.githubusercontent.com/higress-group/higress-standalone/main/all-in-one/get-ai-gateway.sh -o get-ai-gateway.sh
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chmod +x get-ai-gateway.sh
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```
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### Step 2: Gather Configuration
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Ask the user for:
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1. **LLM Provider API Keys**: At least one provider is required
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- Dashscope (Qwen): `--dashscope-key`
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- DeepSeek: `--deepseek-key`
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- OpenAI: `--openai-key`
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- OpenRouter: `--openrouter-key`
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- Claude: `--claude-key`
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- And more...
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2. **Port Configuration** (optional):
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- HTTP port: `--http-port` (default: 8080)
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- HTTPS port: `--https-port` (default: 8443)
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- Console port: `--console-port` (default: 8001)
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3. **Auto-routing** (optional):
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- Enable: `--auto-routing`
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- Default model: `--auto-routing-default-model`
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### Step 3: Run Setup Script
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Run the script in non-interactive mode with the gathered parameters:
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```bash
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./get-ai-gateway.sh start --non-interactive \
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--dashscope-key sk-xxx \
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--openai-key sk-xxx \
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--auto-routing \
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--auto-routing-default-model qwen-turbo
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```
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### Step 4: Verify Deployment
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After the script completes:
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1. Check container is running:
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```bash
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docker ps --filter "name=higress-ai-gateway"
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```
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2. Test the gateway endpoint:
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```bash
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curl http://localhost:8080/v1/models
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```
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3. Access the console (optional):
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```
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http://localhost:8001
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```
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### Step 5: Configure Clawdbot (if applicable)
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If the user wants to use Higress with Clawdbot:
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```bash
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clawdbot models auth login --provider higress
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```
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This will configure Clawdbot to use Higress AI Gateway as a model provider.
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## CLI Parameters Reference
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### Basic Options
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| Parameter | Description | Default |
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|-----------|-------------|---------|
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| `--non-interactive` | Run without prompts | - |
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| `--http-port` | Gateway HTTP port | 8080 |
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| `--https-port` | Gateway HTTPS port | 8443 |
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| `--console-port` | Console port | 8001 |
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| `--container-name` | Container name | higress-ai-gateway |
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| `--data-folder` | Data folder path | ./higress |
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### Auto-Routing Options
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| Parameter | Description |
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|-----------|-------------|
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| `--auto-routing` | Enable auto-routing feature |
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| `--auto-routing-default-model` | Default model when no rule matches |
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### LLM Provider API Keys
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| Parameter | Provider |
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|-----------|----------|
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| `--dashscope-key` | Aliyun Dashscope (Qwen) |
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| `--deepseek-key` | DeepSeek |
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| `--moonshot-key` | Moonshot (Kimi) |
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| `--zhipuai-key` | Zhipu AI |
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| `--openai-key` | OpenAI |
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| `--openrouter-key` | OpenRouter |
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| `--claude-key` | Claude |
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| `--gemini-key` | Google Gemini |
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| `--groq-key` | Groq |
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| `--doubao-key` | Doubao |
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| `--baichuan-key` | Baichuan AI |
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| `--yi-key` | 01.AI (Yi) |
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| `--stepfun-key` | Stepfun |
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| `--minimax-key` | Minimax |
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| `--cohere-key` | Cohere |
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| `--mistral-key` | Mistral AI |
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| `--github-key` | Github Models |
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| `--fireworks-key` | Fireworks AI |
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| `--togetherai-key` | Together AI |
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| `--grok-key` | Grok |
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## Access Logs
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After deployment, gateway access logs are available at:
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```
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$DATA_FOLDER/logs/access.log
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```
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These logs can be used with the **agent-session-monitor** skill for token tracking and conversation analysis.
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## Managing Routing Rules
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After deployment, use the `route` subcommand to manage auto-routing rules:
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```bash
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# Add a routing rule
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./get-ai-gateway.sh route add --model claude-opus-4.5 --trigger "深入思考|deep thinking"
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# List all rules
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./get-ai-gateway.sh route list
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# Remove a rule
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./get-ai-gateway.sh route remove --rule-id 0
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```
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See [higress-auto-router](../higress-auto-router/SKILL.md) for detailed documentation.
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## Related Skills
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This skill works with:
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### higress-auto-router
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Configure automatic model routing using CLI commands. Example:
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```bash
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./get-ai-gateway.sh route add --model claude-opus-4.5 --trigger "深入思考|deep thinking"
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```
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See: [higress-auto-router](../higress-auto-router/SKILL.md)
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### agent-session-monitor
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Monitor and track token usage across sessions. Example:
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- View session statistics in web UI
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- Export FinOps reports
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- Parse logs from `$DATA_FOLDER/logs/access.log`
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See: [agent-session-monitor](../agent-session-monitor/SKILL.md)
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## Examples
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### Example 1: Basic Deployment with Dashscope
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**User:** 帮我部署一个Higress AI网关，使用阿里云的通义千问
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**Steps:**
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1. Download script
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2. Get Dashscope API key from user
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3. Run:
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```bash
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./get-ai-gateway.sh start --non-interactive \
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--dashscope-key sk-xxx
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```
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**Response:**
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```
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✅ Higress AI Gateway 部署完成！
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网关地址: http://localhost:8080/v1/chat/completions
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控制台: http://localhost:8001
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日志目录: ./higress/logs
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已配置的模型提供商:
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- Aliyun Dashscope (Qwen)
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测试命令:
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curl 'http://localhost:8080/v1/chat/completions' \
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-H 'Content-Type: application/json' \
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-d '{"model": "qwen-turbo", "messages": [{"role": "user", "content": "Hello!"}]}'
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```
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### Example 2: Deployment with Auto-Routing
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**User:** 部署Higress网关，启用自动路由，默认使用qwen-turbo
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**Steps:**
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1. Download script
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2. Get API keys
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3. Run:
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```bash
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./get-ai-gateway.sh start --non-interactive \
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--dashscope-key sk-xxx \
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--auto-routing \
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--auto-routing-default-model qwen-turbo
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```
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**Response:**
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```
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✅ Higress AI Gateway 部署完成！
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网关地址: http://localhost:8080/v1/chat/completions
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控制台: http://localhost:8001
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🔀 自动路由已启用:
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- 默认模型: qwen-turbo
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- 使用 model="higress/auto" 触发自动路由
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添加路由规则:
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./get-ai-gateway.sh route add --model claude-opus-4.5 --trigger "深入思考|deep thinking"
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```
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### Example 3: Add Routing Rules
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**User:** 我希望在解决困难问题时路由到claude-opus-4.5
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**Steps:**
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```bash
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./get-ai-gateway.sh route add \
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--model claude-opus-4.5 \
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--trigger "深入思考|deep thinking"
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```
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**Response:**
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```
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✅ 路由规则添加成功！
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触发方式：以 "深入思考" 或 "deep thinking" 开头
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目标模型：claude-opus-4.5
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使用示例：
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- 深入思考 这道算法题应该怎么解？
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- deep thinking What's the best architecture for this system?
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```
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### Example 4: Full Integration with Clawdbot
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**User:** 完整配置Higress和Clawdbot的集成
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**Steps:**
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1. Deploy Higress AI Gateway
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2. Configure Clawdbot provider
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3. Enable auto-routing
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4. Set up session monitoring
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**Response:**
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```
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✅ Higress AI Gateway 集成完成！
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1. 网关已部署:
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- HTTP: http://localhost:8080
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- Console: http://localhost:8001
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2. Clawdbot 配置:
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运行 `clawdbot models auth login --provider higress`
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3. 自动路由:
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已启用，使用 model="higress/auto"
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4. 会话监控:
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日志路径: ./higress/logs/access.log
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启动 Web UI: python3 agent-session-monitor/scripts/webserver.py --data-dir ./sessions
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需要我帮你配置自动路由规则吗？
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```
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## Troubleshooting
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### Container fails to start
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- Check Docker is running: `docker info`
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- Check port availability: `netstat -tlnp | grep 8080`
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- View container logs: `docker logs higress-ai-gateway`
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### Gateway not responding
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- Check container status: `docker ps -a`
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- Verify port mapping: `docker port higress-ai-gateway`
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- Test locally: `curl http://localhost:8080/v1/models`
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### API key errors
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- Verify the API key is correct
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- Check provider documentation for key format
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- Some providers require additional configuration (e.g., Azure, Bedrock)
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