According to AlphaMoat, as of 2026-09, Dify has 2,357 downloads and 5 stars — ranked #4,209 of 5,078 AI skills overall, and #850 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 46 | 1.6K | 2 | 1 |
| SkillHub ↗ | 131 | 2.4K | 5 | — |
Platforms count differently and update at different times.
It covers chat and workflow apps, RAG, model and tool configuration, nodes, APIs, and self-hosting. Verify platform versions, credentials, and permissions; review inputs and side effects before code-node or API execution. Review remote installers before execution; protect API keys, avoid unintended sensitive uploads, and confirm deletions.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 2.4K | — | 5 |
| 2026-08 | 1.8K | +19.8% | 5 |
| 2026-07 | 1.5K | +21.5% | 5 |
| 2026-06 | 1.2K | +12.5% | 4 |
| 2026-05 | 1.1K | — | 3 |
| 2026-03 | 670 | — | 2 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: dify description: Dify AI应用开发平台指南。用于构建LLM应用、工作流、Agent和知识库。当用户需要(1)使用Dify创建AI应用 (2)设计LLM工作流 (3)配置知识库RAG (4)开发AI Agent (5)调用Dify API (6)自托管部署Dify时激活此技能。 --- # Dify AI应用开发平台 Dify是开源的LLM应用开发平台,支持快速构建AI应用、工作流和Agent。 ## 核心概念
### 应用类型
- **Chat App** - 对话型应用,支持会话持久化,适合聊天机器人、客服AI
- **Workflow App** - 工作流应用,无状态执行,适合翻译、写作、摘要
- **Agent** - 智能体应用,支持工具调用和自主规划
- **Completion App** - 文本补全应用,单次请求响应
### 核心组件
- **Studio** - 应用构建工作台
- **Knowledge Base** - 知识库,支持RAG检索增强
- **Model Providers** - 模型提供商配置
- **Tools** - 工具集成
## 工作流节点
### 输入输出
- **User Input** - 用户输入,定义输入变量
- **Output** - 输出结果
### 逻辑控制
- **IF/ELSE** - 条件分支
- **Iteration** - 迭代循环
- **Parallel** - 并行执行
### 数据处理
- **Parameter Extractor** - 参数提取,用LLM从自然语言提取结构化数据
- **List Operator** - 列表操作,过滤和转换数组
- **Variable Aggregator** - 变量聚合
- **Template** - 模板渲染
### LLM节点
- **LLM** - 大语言模型调用
- **Question Classifier** - 问题分类
- **Knowledge Retrieval** - 知识检索
### 工具节点
- **HTTP Request** - HTTP请求
- **Code** - 代码执行(Python/JavaScript)
- **Tool** - 工具调用
## 快速开始
### 部署Dify (Docker)
```bash
# 克隆最新版本
git clone --branch "$(curl -s https://api.github.com/repos/langgenius/dify/releases/latest | jq -r .tag_name)" https://github.com/langgenius/dify.git
# 启动
cd dify/docker
cp .env.example .env
docker compose up -d
```
访问 `http://localhost/install` 初始化管理员账户。
### 系统要求
- CPU >= 2 Core
- RAM >= 4 GiB
- Docker 19.03+
- Docker Compose 1.28+
## API调用
### 认证
所有API请求需要在Header中携带API Key:
```
Authorization: Bearer {api_key}
```
### 执行工作流
```bash
POST /v1/workflows/run
Content-Type: application/json
{
"inputs": {
"query": "翻译这段文字..."
},
"response_mode": "blocking", # 或 "streaming"
"user": "user-123"
}
```
### 发送聊天消息
```bash
POST /v1/chat-messages
Content-Type: application/json
{
"query": "你好",
"response_mode": "streaming",
"user": "user-123",
"conversation_id": "" # 首次为空,后续传入返回的conversation_id
}
```
### 响应模式
- **blocking** - 同步等待完整响应
- **streaming** - SSE流式响应
## 知识库
### 创建知识库
1. Studio → Knowledge → Create Knowledge
2. 上传文档 (支持txt, markdown, pdf, docx, html等)
3. 选择索引模式:
- **High Quality** - 高质量索引,需要Embedding模型
- **Economy** - 经济模式,关键词检索
### 检索设置
- **Vector Search** - 向量检索
- **Full Text Search** - 全文检索
- **Hybrid Search** - 混合检索
### 在应用中使用
工作流中添加 Knowledge Retrieval 节点,选择知识库。
## 详细参考
- [API文档](references/api.md) - 完整API接口说明
- [工作流节点](references/workflow-nodes.md) - 所有节点详细配置
- [知识库配置](references/knowledge-base.md) - 知识库高级设置
- [模型配置](references/model-providers.md) - 支持的模型提供商
## 资源链接
- 官方文档: https://docs.dify.ai
- GitHub: https://github.com/langgenius/dify
- 社区: https://github.com/langgenius/dify/discussions
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
Stores agent memory and cross-skill state as a typed, constraint-checked knowledge graph.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.