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feat: add skills and upgrade feishu/dingtalk channel
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297
skills/linkai-agent/README.md
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297
skills/linkai-agent/README.md
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@@ -0,0 +1,297 @@
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# LinkAI Agent Skill
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这个 skill 允许你调用 LinkAI 平台上的多个应用(App)和工作流(Workflow),通过简单的配置即可集成多个智能体能力。
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## 特性
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- ✅ **多应用支持** - 在一个配置文件中管理多个 LinkAI 应用/工作流
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- ✅ **动态加载** - skill 系统加载时自动从 `config.json` 读取应用列表
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- ✅ **自动技能描述** - 所有配置的应用会自动添加到技能描述中
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- ✅ **模型切换** - 可以为每个请求指定不同的模型
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- ✅ **知识库集成** - 支持应用绑定的知识库
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- ✅ **插件能力** - 支持应用启用的各类插件
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- ✅ **工作流执行** - 支持执行复杂的多步骤工作流
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## 快速开始
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### 1. 配置 API Key
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```bash
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env_config(action="set", key="LINKAI_API_KEY", value="your-linkai-api-key")
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```
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获取 API Key: https://link-ai.tech/console/interface
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### 2. 配置应用列表
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将 `config.json.template` 复制为 `config.json`:
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```bash
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cp config.json.template config.json
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```
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编辑 `config.json`,添加你的应用/工作流:
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```json
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{
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"apps": [
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{
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"app_code": "G7z6vKwp",
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"app_name": "通用助手",
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"app_description": "通用AI助手,可以回答各类问题"
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},
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{
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"app_code": "your_kb_app",
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"app_name": "产品文档助手",
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"app_description": "基于产品文档知识库的问答助手"
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},
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{
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"app_code": "your_workflow",
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"app_name": "数据分析工作流",
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"app_description": "执行数据清洗、分析和可视化的完整工作流"
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}
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]
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}
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```
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**注意:** 修改 `config.json` 后,Agent 在下次加载技能时会自动读取新配置。
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### 3. 调用应用
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```bash
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bash scripts/call.sh "G7z6vKwp" "What is artificial intelligence?"
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```
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## 使用示例
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### 基础调用
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```bash
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# 调用默认模型
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bash scripts/call.sh "G7z6vKwp" "解释一下量子计算"
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```
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### 指定模型
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```bash
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# 使用 GPT-4.1 模型
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bash scripts/call.sh "G7z6vKwp" "写一篇关于AI的文章" "LinkAI-4.1"
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# 使用 DeepSeek 模型
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bash scripts/call.sh "G7z6vKwp" "帮我写代码" "deepseek-chat"
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# 使用 Claude 模型
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bash scripts/call.sh "G7z6vKwp" "分析这段文本" "claude-4-sonnet"
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```
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### 调用工作流
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```bash
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# 工作流会按照配置的节点顺序执行
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bash scripts/call.sh "workflow_code" "输入数据或问题"
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```
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## ⚠️ 重要提示
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### 超时配置
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LinkAI 应用(特别是视频/图片生成、复杂工作流)可能需要较长时间处理。
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**脚本内置超时**:
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- 默认:120 秒(适合大多数场景)
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- 可通过第 5 个参数自定义:`bash scripts/call.sh <app_code> <question> "" "false" "180"`
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**推荐超时时间**:
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- **文本问答**:120 秒(默认)
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- **图片生成**:120-180 秒
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- **视频生成**:180-300 秒
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Agent 调用时会自动设置合适的超时时间。
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## 配置说明
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### config.json 字段
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| `app_code` | string | 应用或工作流的唯一标识码,从 LinkAI 控制台获取 |
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| `app_name` | string | 应用名称,会显示在技能描述中 |
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| `app_description` | string | 应用功能描述,帮助 Agent 理解何时使用该应用 |
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### 获取 app_code
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1. 登录 [LinkAI 控制台](https://link-ai.tech/console)
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2. 进入「应用管理」或「工作流管理」
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3. 选择要集成的应用/工作流
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4. 在应用详情页找到 `app_code`
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## 支持的模型
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LinkAI 支持多种主流 AI 模型:
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**OpenAI 系列:**
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- `LinkAI-4.1` - GPT-4.1 (1000K 上下文)
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- `LinkAI-4.1-mini` - GPT-4.1 mini (1000K)
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- `LinkAI-4.1-nano` - GPT-4.1 nano (1000K)
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- `LinkAI-4o` - GPT-4o (128K)
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- `LinkAI-4o-mini` - GPT-4o mini (128K)
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**DeepSeek 系列:**
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- `deepseek-chat` - DeepSeek-V3 对话模型 (64K)
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- `deepseek-reasoner` - DeepSeek-R1 推理模型 (64K)
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**Claude 系列:**
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- `claude-4-sonnet` - Claude 4 Sonnet (200K)
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- `claude-3-7-sonnet` - Claude 3.7 (200K)
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- `claude-3-5-sonnet` - Claude 3.5 (200K)
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**Google 系列:**
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- `gemini-2.5-pro` - Gemini 2.5 Pro (1000K)
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- `gemini-2.0-flash` - Gemini 2.0 Flash (1000K)
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**国产模型:**
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- `qwen3` - 通义千问3 (128K)
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- `wenxin-4.5` - 文心一言4.5 (8K)
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- `doubao-1.5-pro-256k` - 豆包1.5 (256K)
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- `glm-4-plus` - 智谱GLM-4-Plus (4K)
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完整模型列表:https://link-ai.tech/console/models
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## 应用类型
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### 1. 普通应用
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配置了系统提示词和参数的标准对话应用,可以:
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- 设置角色和性格
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- 绑定知识库
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- 启用插件(图像识别、网页搜索、代码执行等)
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### 2. 知识库应用
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基于特定知识库的问答应用,适合:
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- 企业内部知识库
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- 产品文档问答
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- 客户支持
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### 3. 工作流
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多步骤的自动化流程,可以:
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- 串联多个处理节点
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- 条件分支
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- 循环处理
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- 调用外部 API
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## 响应格式
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### 成功响应
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```json
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{
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"app_code": "G7z6vKwp",
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"content": "人工智能(AI)是计算机科学的一个分支...",
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"usage": {
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"prompt_tokens": 10,
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"completion_tokens": 150,
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"total_tokens": 160
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}
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}
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```
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### 错误响应
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```json
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{
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"error": "LinkAI API error",
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"message": "应用不存在",
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"response": { ... }
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}
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```
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## 常见错误
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### LINKAI_API_KEY environment variable is not set
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**原因:** 未配置 API Key
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**解决:** 使用 `env_config` 工具设置 LINKAI_API_KEY
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### 应用不存在 (402)
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**原因:** app_code 不正确或应用已删除
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**解决:** 检查 app_code 是否正确,确认应用存在
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### 无访问权限 (403)
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**原因:** 尝试访问他人的私有应用
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**解决:** 确保应用是公开的或你是创建者
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### 账号积分额度不足 (406)
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**原因:** LinkAI 账户余额不足
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**解决:** 前往控制台充值
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### 内容审核不通过 (409)
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**原因:** 请求或响应包含敏感内容
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**解决:** 修改输入内容,避免敏感词
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## 技术实现
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### 自动技能描述生成
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当 skill 系统加载 `linkai-agent` 时,会自动:
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1. 读取 `config.json` 中的应用列表
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2. 将每个应用的 name 和 description 动态添加到技能描述中
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3. Agent 加载时会看到完整的应用列表
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这是在 `agent/skills/loader.py` 中实现的特殊处理。
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### 工作流程
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```
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用户配置 config.json
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↓
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Agent 启动/重新加载技能
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↓
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SkillLoader 检测到 linkai-agent
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↓
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动态读取 config.json
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↓
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生成包含所有应用描述的 description
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↓
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Agent 看到所有可用应用的完整信息
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↓
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用户请求触发
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↓
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Agent 根据描述选择合适的应用
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↓
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调用 call.sh <app_code> <question>
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↓
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LinkAI API 处理并返回结果
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```
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## 最佳实践
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1. **清晰的描述** - 为每个应用写清晰、具体的描述,帮助 Agent 理解应用用途
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2. **合理分工** - 不同应用负责不同领域,避免功能重叠
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3. **无需重启** - 修改 config.json 后,Agent 下次加载技能时会自动更新
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4. **模型选择** - 根据任务复杂度选择合适的模型
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5. **知识库优化** - 为专业领域的应用绑定相关知识库
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## 扩展用法
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### 在 Agent 系统中使用
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当 Agent 系统加载这个 skill 时,会自动从 `config.json` 读取应用列表并生成描述:
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```
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Call LinkAI apps/workflows. 通用助手(G7z6vKwp: 通用AI助手,可以回答各类问题); 产品文档助手(kb_app_001: 基于产品文档知识库的问答助手); 数据分析工作流(wf_002: 执行数据清洗、分析和可视化的完整工作流)
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```
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Agent 会根据用户问题自动选择最合适的应用进行调用。
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## 相关链接
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- LinkAI 平台: https://link-ai.tech
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- API 文档: https://docs.link-ai.tech
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- 控制台: https://link-ai.tech/console
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- 模型列表: https://link-ai.tech/console/models
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- 应用广场: https://link-ai.tech/square
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## License
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Part of the chatgpt-on-wechat project.
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165
skills/linkai-agent/SKILL.md
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165
skills/linkai-agent/SKILL.md
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---
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name: linkai-agent
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description: Call LinkAI applications and workflows. Use bash command to execute like 'bash <base_dir>/scripts/call.sh <app_code> <question>'.
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homepage: https://link-ai.tech
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metadata:
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emoji: 🤖
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requires:
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bins: ["curl"]
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env: ["LINKAI_API_KEY"]
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primaryEnv: "LINKAI_API_KEY"
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---
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# LinkAI Agent Caller
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Call LinkAI applications and workflows through API. Supports multiple apps/workflows configured in config.json.
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The available apps are dynamically loaded from `config.json` at skill loading time.
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## Setup
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This skill requires a LinkAI API key. If not configured:
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1. Get your API key from https://link-ai.tech/console/api-keys
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2. Set the key using: `env_config(action="set", key="LINKAI_API_KEY", value="your-key")`
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## Configuration
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1. Copy `config.json.template` to `config.json`
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2. Configure your apps/workflows:
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```json
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{
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"apps": [
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{
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"app_code": "your_app_code",
|
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"app_name": "App Name",
|
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"app_description": "What this app does"
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}
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]
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}
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```
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3. The skill description will be automatically updated when the agent loads this skill
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## Usage
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**Important**: Scripts are located relative to this skill's base directory.
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When you see this skill in `<available_skills>`, note the `<base_dir>` path.
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**CRITICAL**: Always use `bash` command to execute the script:
|
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|
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```bash
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# General pattern (MUST start with bash):
|
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bash "<base_dir>/scripts/call.sh" "<app_code>" "<question>" [model] [stream] [timeout]
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# DO NOT execute the script directly like this (WRONG):
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# "<base_dir>/scripts/call.sh" ...
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|
||||
# Parameters:
|
||||
# - app_code: LinkAI app or workflow code (required)
|
||||
# - question: User question (required)
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||||
# - model: Override model (optional, uses app default if not specified)
|
||||
# - stream: Enable streaming (true/false, default: false)
|
||||
# - timeout: curl timeout in seconds (default: 120, recommended for video/image generation)
|
||||
```
|
||||
|
||||
**IMPORTANT - Timeout Configuration**:
|
||||
- The script has a **default timeout of 120 seconds** (suitable for most cases)
|
||||
- For complex tasks (video generation, large workflows), pass a longer timeout as the 5th parameter
|
||||
- The bash tool also needs sufficient timeout - set its `timeout` parameter accordingly
|
||||
- Example: `bash(command="bash <script> <app_code> <question> '' 'false' 180", timeout=200)`
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||||
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||||
## Examples
|
||||
|
||||
### Call an app (uses default 60s timeout)
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```bash
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bash(command='bash "<base_dir>/scripts/call.sh" "G7z6vKwp" "What is AI?"', timeout=60)
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||||
```
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||||
|
||||
### Call an app with specific model
|
||||
```bash
|
||||
bash(command='bash "<base_dir>/scripts/call.sh" "G7z6vKwp" "Explain machine learning" "LinkAI-4.1"', timeout=60)
|
||||
```
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||||
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||||
### Call a workflow with custom timeout (video generation)
|
||||
```bash
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||||
# Pass timeout as 5th parameter to script, and set bash timeout slightly longer
|
||||
bash(command='bash "<base_dir>/scripts/call.sh" "workflow_code" "Generate a sunset video" "" "false" "180"', timeout=180)
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||||
```
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||||
```bash
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||||
bash "<base_dir>/scripts/call.sh" "workflow_code" "Analyze this data: ..."
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||||
```
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||||
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||||
## Supported Models
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||||
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||||
You can specify any LinkAI supported model:
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||||
- `LinkAI-4.1` - Latest GPT-4.1 model (1000K context)
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||||
- `LinkAI-4.1-mini` - GPT-4.1 mini (1000K context)
|
||||
- `LinkAI-4o` - GPT-4o model (128K context)
|
||||
- `LinkAI-4o-mini` - GPT-4o mini (128K context)
|
||||
- `deepseek-chat` - DeepSeek-V3 (64K context)
|
||||
- `deepseek-reasoner` - DeepSeek-R1 reasoning model
|
||||
- `claude-4-sonnet` - Claude 4 Sonnet (200K context)
|
||||
- `gemini-2.5-pro` - Gemini 2.5 Pro (1000K context)
|
||||
- And many more...
|
||||
|
||||
Full model list: https://link-ai.tech/console/models
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||||
|
||||
## Response Format
|
||||
|
||||
Success response:
|
||||
```json
|
||||
{
|
||||
"app_code": "G7z6vKwp",
|
||||
"content": "AI stands for Artificial Intelligence...",
|
||||
"usage": {
|
||||
"prompt_tokens": 10,
|
||||
"completion_tokens": 50,
|
||||
"total_tokens": 60
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Error response:
|
||||
```json
|
||||
{
|
||||
"error": "Error description",
|
||||
"message": "Detailed error message"
|
||||
}
|
||||
```
|
||||
|
||||
## Features
|
||||
|
||||
- ✅ **Multiple Apps**: Configure and call multiple LinkAI apps/workflows
|
||||
- ✅ **Dynamic Loading**: Apps are loaded from config.json at runtime
|
||||
- ✅ **Model Override**: Optionally specify model per request
|
||||
- ✅ **Streaming Support**: Enable streaming output
|
||||
- ✅ **Knowledge Base**: Apps can use configured knowledge bases
|
||||
- ✅ **Plugins**: Apps can use enabled plugins (image recognition, web search, etc.)
|
||||
- ✅ **Workflows**: Execute complex multi-step workflows
|
||||
|
||||
## Notes
|
||||
|
||||
- Each app/workflow maintains its own configuration (prompt, model, temperature, etc.)
|
||||
- Apps can have knowledge bases attached for domain-specific Q&A
|
||||
- Workflows execute from start node to end node and return final output
|
||||
- Token usage and costs depend on the model used
|
||||
- See LinkAI documentation for pricing: https://link-ai.tech/console/funds
|
||||
- The skill description is automatically generated from config.json when loaded
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
**"LINKAI_API_KEY environment variable is not set"**
|
||||
- Use env_config tool to set the API key
|
||||
|
||||
**"app_code is required"**
|
||||
- Make sure you're passing the app_code as the first parameter
|
||||
|
||||
**"应用不存在" (App not found)**
|
||||
- Check that the app_code is correct
|
||||
- Ensure you have access to the app
|
||||
|
||||
**"账号积分额度不足" (Insufficient credits)**
|
||||
- Top up your LinkAI account credits
|
||||
14
skills/linkai-agent/config.json.template
Normal file
14
skills/linkai-agent/config.json.template
Normal file
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"apps": [
|
||||
{
|
||||
"app_code": "your_app_code_2",
|
||||
"app_name": "知识库助手",
|
||||
"app_description": "基于特定领域知识库提供智能问答的知识助手"
|
||||
},
|
||||
{
|
||||
"app_code": "your_workflow_code",
|
||||
"app_name": "数据分析工作流",
|
||||
"app_description": "用于数据分析任务的工作流程"
|
||||
}
|
||||
]
|
||||
}
|
||||
138
skills/linkai-agent/scripts/call.sh
Executable file
138
skills/linkai-agent/scripts/call.sh
Executable file
@@ -0,0 +1,138 @@
|
||||
#!/usr/bin/env bash
|
||||
# LinkAI Agent Caller
|
||||
# API Docs: https://api.link-ai.tech/v1/chat/completions
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
app_code="${1:-}"
|
||||
question="${2:-}"
|
||||
model="${3:-}"
|
||||
stream="${4:-false}"
|
||||
timeout="${5:-120}" # Default 120 seconds for video/image generation
|
||||
|
||||
if [ -z "$app_code" ]; then
|
||||
echo '{"error": "app_code is required", "usage": "bash call.sh <app_code> <question> [model] [stream] [timeout]"}'
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [ -z "$question" ]; then
|
||||
echo '{"error": "question is required", "usage": "bash call.sh <app_code> <question> [model] [stream] [timeout]"}'
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [ -z "${LINKAI_API_KEY:-}" ]; then
|
||||
echo '{"error": "LINKAI_API_KEY environment variable is not set", "help": "Use env_config to set LINKAI_API_KEY"}'
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# API endpoint
|
||||
api_url="https://api.link-ai.tech/v1/chat/completions"
|
||||
|
||||
# Build JSON request body
|
||||
if [ -n "$model" ]; then
|
||||
request_body=$(cat <<EOF
|
||||
{
|
||||
"app_code": "$app_code",
|
||||
"model": "$model",
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "$question"
|
||||
}
|
||||
],
|
||||
"stream": $stream
|
||||
}
|
||||
EOF
|
||||
)
|
||||
else
|
||||
request_body=$(cat <<EOF
|
||||
{
|
||||
"app_code": "$app_code",
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "$question"
|
||||
}
|
||||
],
|
||||
"stream": $stream
|
||||
}
|
||||
EOF
|
||||
)
|
||||
fi
|
||||
|
||||
# Call LinkAI API
|
||||
response=$(curl -sS --max-time "$timeout" \
|
||||
-X POST \
|
||||
-H "Authorization: Bearer $LINKAI_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d "$request_body" \
|
||||
"$api_url" 2>&1)
|
||||
|
||||
curl_exit_code=$?
|
||||
|
||||
if [ $curl_exit_code -ne 0 ]; then
|
||||
echo "{\"error\": \"Failed to call LinkAI API\", \"details\": \"$response\"}"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Simple JSON validation
|
||||
if [[ ! "$response" =~ ^[[:space:]]*[\{\[] ]]; then
|
||||
echo "{\"error\": \"Invalid JSON response from API\", \"response\": \"$response\"}"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Check for API error (top-level error only, not content_filter_result)
|
||||
if echo "$response" | grep -q '^[[:space:]]*{[[:space:]]*"error"[[:space:]]*:' || echo "$response" | grep -q '"error"[[:space:]]*:[[:space:]]*{[^}]*"code"[[:space:]]*:[[:space:]]*"[^"]*"[^}]*"message"'; then
|
||||
# Make sure it's not just content_filter_result inside choices
|
||||
if ! echo "$response" | grep -q '"choices"[[:space:]]*:[[:space:]]*\['; then
|
||||
# Extract error message
|
||||
error_msg=$(echo "$response" | grep -o '"message"[[:space:]]*:[[:space:]]*"[^"]*"' | sed 's/"message"[[:space:]]*:[[:space:]]*"\(.*\)"/\1/' | head -1)
|
||||
error_code=$(echo "$response" | grep -o '"code"[[:space:]]*:[[:space:]]*"[^"]*"' | sed 's/"code"[[:space:]]*:[[:space:]]*"\(.*\)"/\1/' | head -1)
|
||||
|
||||
if [ -z "$error_msg" ]; then
|
||||
error_msg="Unknown API error"
|
||||
fi
|
||||
|
||||
# Provide friendly error message for content filter
|
||||
if [ "$error_code" = "content_filter_error" ] || echo "$error_msg" | grep -qi "content.*filter"; then
|
||||
echo "{\"error\": \"内容安全审核\", \"message\": \"您的问题或应用返回的内容触发了LinkAI的安全审核机制,请换一种方式提问或检查应用配置\", \"details\": \"$error_msg\"}"
|
||||
else
|
||||
echo "{\"error\": \"LinkAI API error\", \"message\": \"$error_msg\", \"code\": \"$error_code\"}"
|
||||
fi
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
# For non-stream mode, extract and format the response
|
||||
if [ "$stream" = "false" ]; then
|
||||
# Extract content from response
|
||||
content=$(echo "$response" | grep -o '"content"[[:space:]]*:[[:space:]]*"[^"]*"' | sed 's/"content"[[:space:]]*:[[:space:]]*"\(.*\)"/\1/' | head -1)
|
||||
|
||||
# Extract usage information
|
||||
prompt_tokens=$(echo "$response" | grep -o '"prompt_tokens"[[:space:]]*:[[:space:]]*[0-9]*' | grep -o '[0-9]*' | head -1)
|
||||
completion_tokens=$(echo "$response" | grep -o '"completion_tokens"[[:space:]]*:[[:space:]]*[0-9]*' | grep -o '[0-9]*' | head -1)
|
||||
total_tokens=$(echo "$response" | grep -o '"total_tokens"[[:space:]]*:[[:space:]]*[0-9]*' | grep -o '[0-9]*' | head -1)
|
||||
|
||||
if [ -n "$content" ]; then
|
||||
# Unescape JSON content
|
||||
content=$(echo "$content" | sed 's/\\n/\n/g' | sed 's/\\"/"/g')
|
||||
|
||||
cat <<EOF
|
||||
{
|
||||
"app_code": "$app_code",
|
||||
"content": "$content",
|
||||
"usage": {
|
||||
"prompt_tokens": ${prompt_tokens:-0},
|
||||
"completion_tokens": ${completion_tokens:-0},
|
||||
"total_tokens": ${total_tokens:-0}
|
||||
}
|
||||
}
|
||||
EOF
|
||||
else
|
||||
# Return full response if we can't extract content
|
||||
echo "$response"
|
||||
fi
|
||||
else
|
||||
# For stream mode, return raw response (caller needs to handle streaming)
|
||||
echo "$response"
|
||||
fi
|
||||
Reference in New Issue
Block a user