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n8n-nodes-qiniu-ai

v1.0.0

Published

n8n nodes for Qiniu AI SDK - Chat, Image, Video, Audio, OCR, Agent and more

Readme

n8n-nodes-qiniu-ai

English | 中文


🇺🇸 English

npm version n8n License: MIT

n8n community node for Qiniu Cloud AI SDK - Integrate full-modal AI capabilities into your n8n workflows.

✨ Features

| Resource | Operations | Description | |----------|-----------|-------------| | Chat | Complete | Multi-model chat completion (Qwen, Claude, Gemini, GPT, DeepSeek, etc.) | | Image | Generate, Edit | AI image generation and editing with multiple models | | Video | Generate, Remix, Get Status | Video generation with Kling, Veo, Sora models | | Audio | Text-to-Speech, Speech-to-Text | TTS and ASR capabilities | | Agent | Execute | AI agent with built-in tools (Web Search, OCR, Image/Video Generation) and ReAct loop | | Tools | Web Search, OCR, Image Censor, Video Censor, VFrame | Utility tools with content safety and video processing |

🆕 What's New in v1.0.0

  • Cloud-Native State Persistence (KodoCheckpointer): Store agent conversation state in Qiniu Kodo object storage for production-grade persistence across workflow executions.
  • Content Safety Tools:
    • Image Censor: Synchronous content safety audit (pulp, terror, politician detection)
    • Video Censor: Asynchronous video content moderation with job polling
    • Video Frame Extract (VFrame): Extract frames from video at specific timestamps
  • SDK v0.27.3: Upgraded to the latest SDK with enhanced Agent capabilities.

📦 Installation

Community Node (Recommended)

  1. Go to Settings > Community Nodes
  2. Click Install
  3. Enter n8n-nodes-qiniu-ai and click Install

Manual Installation

# In your n8n custom nodes directory
npm install n8n-nodes-qiniu-ai

🔧 Configuration

  1. Create credentials in n8n:

    • Go to Credentials > New
    • Search for Qiniu AI API
    • Enter your API Key (obtain from Qiniu Cloud Console)
  2. (Optional) Custom Base URL for self-hosted deployments

📖 Usage Examples

Chat Completion

Resource: Chat
Operation: Complete
Model: claude-4.5-sonnet
Messages: [{"role": "user", "content": "Hello!"}]

Image Generation

Resource: Image
Operation: Generate
Model: kling-v2-1
Prompt: "A beautiful sunset over mountains"
Wait for Completion: true

Video Generation

Resource: Video
Operation: Generate
Model: kling-video-o1
Prompt: "A cat playing with a ball"
Aspect Ratio: 16:9

Image → Video Workflow

  1. Image Node: Generate an image
  2. Video Node:
    • Set First Frame Binary Property to data
    • The image from the previous node will be used as the first frame

🎯 Supported Models

  • Qwen: qwen3-235b-a22b, qwen3-max, qwen3-32b, qwen-turbo
  • Claude: claude-4.5-sonnet, claude-4.5-opus, claude-4.0-sonnet, claude-3.7-sonnet
  • Gemini: gemini-3.0-pro-preview, gemini-2.5-flash, gemini-2.5-pro
  • DeepSeek: deepseek-r1, deepseek-v3, deepseek-v3.1
  • GPT: openai/gpt-5, openai/gpt-5.2
  • Others: doubao-seed-1.6, glm-4.5, kimi-k2, minimax-m2
  • Kling: kling-v2-1, kling-v2, kling-v1-5
  • Gemini: gemini-3.0-pro-image-preview, gemini-2.5-flash-image
  • Others: doubao-1.5-vision-pro, qwen2.5-vl-72b-instruct
  • Kling: kling-video-o1, kling-v2-1, kling-v2-5-turbo
  • Veo: veo-3.1-generate-preview, veo-3.0-generate-preview, veo-2.0-generate-001
  • Others: sora-2, minimax-m2, mimo-v2-flash

💾 Persistent Memory (Multi-turn Conversations)

For conversation memory that persists across workflow executions, use n8n's built-in Memory nodes:

┌─────────────────────┐     ┌──────────────────┐
│ Redis/Postgres      │────▶│ Qiniu AI Agent   │
│ Chat Memory Node    │     │ (threadId link)  │
└─────────────────────┘     └──────────────────┘

Setup:

  1. Add Redis Chat Memory or Postgres Chat Memory node before the Agent
  2. Configure the Memory node with your database credentials
  3. In the Qiniu AI Agent node, set the Thread ID to match the Memory node's Session ID
  4. The agent will automatically resume from previous conversation context

Note: The built-in Memory checkpointer works within a single execution. For cross-execution persistence, use n8n's native Memory nodes.

🔗 Resources

📄 License

MIT License - see LICENSE for details.


🇨🇳 中文

npm version n8n License: MIT

n8n 社区节点 - 集成 七牛云 AI SDK 的全模态 AI 能力到 n8n 工作流中。

✨ 功能特性

| 资源 | 操作 | 描述 | |------|-----|------| | Chat(聊天) | 文本生成 | 多模型聊天补全(通义千问、Claude、Gemini、GPT、DeepSeek 等) | | Image(图像) | 生成、编辑 | AI 图像生成和编辑 | | Video(视频) | 生成、混剪、查询状态 | 视频生成(可灵、Veo、Sora) | | Audio(音频) | 文本转语音、语音转文本 | TTS 和 ASR 能力 | | Agent(智能体) | 执行 | 支持内置工具(搜索、OCR、图像/视频生成)和 ReAct 循环的 AI 智能体 | | Tools(工具) | 网络搜索、OCR、图片审核视频审核视频帧提取 | 内容安全与视频处理工具 |

🆕 v1.0.0 新功能

  • 云原生状态持久化 (KodoCheckpointer):将 Agent 对话状态存储在七牛 Kodo 对象存储中,实现跨工作流执行的生产级持久化。
  • 内容安全工具
    • 图片审核 (Image Censor):同步内容安全审核(涉黄、暴力、政治敏感检测)
    • 视频审核 (Video Censor):异步视频内容审核,支持任务轮询
    • 视频帧提取 (VFrame):从视频中提取指定时间戳的帧
  • SDK v0.27.3:升级至最新 SDK,增强 Agent 能力。

📦 安装

社区节点安装(推荐)

  1. 进入 设置 > 社区节点
  2. 点击 安装
  3. 输入 n8n-nodes-qiniu-ai 并点击 安装

手动安装

# 在 n8n 自定义节点目录
npm install n8n-nodes-qiniu-ai

🔧 配置

  1. 在 n8n 中创建凭证:

  2. (可选)自定义 Base URL 用于私有化部署

📖 使用示例

聊天补全

资源: Chat
操作: Complete
模型: claude-4.5-sonnet
消息: [{"role": "user", "content": "你好!"}]

图像生成

资源: Image
操作: Generate
模型: kling-v2-1
提示词: "山间美丽的日落"
等待完成: true

视频生成

资源: Video
操作: Generate
模型: kling-video-o1
提示词: "一只猫在玩球"
宽高比: 16:9

图像 → 视频工作流

  1. 图像节点:生成图像
  2. 视频节点
    • 设置 首帧图片二进制属性data
    • 上一节点生成的图像将作为视频首帧

🎯 支持的模型

  • 通义千问: qwen3-235b-a22b, qwen3-max, qwen3-32b, qwen-turbo
  • Claude: claude-4.5-sonnet, claude-4.5-opus, claude-4.0-sonnet, claude-3.7-sonnet
  • Gemini: gemini-3.0-pro-preview, gemini-2.5-flash, gemini-2.5-pro
  • DeepSeek: deepseek-r1, deepseek-v3, deepseek-v3.1
  • GPT: openai/gpt-5, openai/gpt-5.2
  • 其他: doubao-seed-1.6, glm-4.5, kimi-k2, minimax-m2
  • 可灵: kling-v2-1, kling-v2, kling-v1-5
  • Gemini: gemini-3.0-pro-image-preview, gemini-2.5-flash-image
  • 其他: doubao-1.5-vision-pro, qwen2.5-vl-72b-instruct
  • 可灵: kling-video-o1, kling-v2-1, kling-v2-5-turbo
  • Veo: veo-3.1-generate-preview, veo-3.0-generate-preview, veo-2.0-generate-001
  • 其他: sora-2, minimax-m2, mimo-v2-flash

💾 持久化对话历史(多轮对话)

如需跨工作流执行保持对话记忆,请使用 n8n 内置的 Memory 节点:

┌─────────────────────┐     ┌──────────────────┐
│ Redis/Postgres      │────▶│ Qiniu AI Agent   │
│ Chat Memory 节点    │     │ (threadId 关联)  │
└─────────────────────┘     └──────────────────┘

配置步骤:

  1. 在 Agent 节点前添加 Redis Chat MemoryPostgres Chat Memory 节点
  2. 配置 Memory 节点的数据库连接
  3. 在 Qiniu AI Agent 节点中,将 Thread ID 设置为与 Memory 节点的 Session ID 一致
  4. Agent 将自动接续之前的对话上下文

注意: 内置的 Memory checkpointer 仅在单次执行内有效。跨执行的持久化请使用 n8n 原生 Memory 节点。

🔗 相关链接

📄 许可证

MIT License - 详见 LICENSE


🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📞 Support


Made with ❤️ by bowenQT