📦 langgenius/dify —— 面向智能体工作流开发的生产就绪平台

Dify Cloud · 自托管 · 文档 · Dify 版本概览

Dify 是一个开源的 LLM 应用开发平台。其直观的界面融合了 AI 工作流、RAG 管道、Agent 能力、模型管理、可观测性功能（包括 Opik、Langfuse 和 Arize Phoenix）等众多特性，让您能够快速从原型走向生产。以下是其核心功能列表：

在安装 Dify 之前，请确保您的机器满足以下最低系统要求：

• CPU >= 2 核
• 内存 >= 4 GiB

启动 Dify 服务的最简单方式是使用 Docker Compose。在使用以下命令运行 Dify 之前，请确保您的机器上已安装 Docker 和 Docker Compose：

cd dify
cd docker
cp .env.example .env
docker compose up -d

运行后，您可以在浏览器中访问 http://localhost/install 进入 Dify 面板并开始初始化流程。

如果您在设置 Dify 时遇到问题，请参考我们的 常见问题。如果仍有问题，请随时联系社区和我们。

如果您想为 Dify 做贡献或进行二次开发，请参考我们的 从源代码部署指南

1. 工作流：在可视化画布上构建并测试强大的 AI 工作流，充分利用以下所有功能以及更多。

2. 全面的模型支持：无缝集成来自数十个推理提供商和自托管方案的数百种专有/开源 LLM，涵盖 GPT、Mistral、Llama3 以及任何兼容 OpenAI API 的模型。完整的支持模型提供商列表请见 此处。

3. Prompt IDE：直观的界面，用于构思提示词、比较模型性能，并为基于聊天的应用添加文本转语音等附加功能。

4. RAG 管道：全面的 RAG 能力，涵盖从文档摄取到检索的各个环节，开箱即用地支持从 PDF、PPT 及其他常见文档格式中提取文本。

5. Agent 能力：您可以基于 LLM Function Calling 或 ReAct 定义 Agent，并为其添加预置或自定义工具。Dify 为 AI Agent 提供了 50 多个内置工具，例如 Google Search、DALL·E、Stable Diffusion 和 WolframAlpha。

6. LLMOps：监控和分析

Dify Cloud · Self-hosting · Documentation · Dify edition overview

Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features:

Before installing Dify, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4 GiB

The easiest way to start the Dify server is through Docker Compose. Before running Dify with the following commands, make sure that Docker and Docker Compose are installed on your machine:

cd dify
cd docker
cp .env.example .env
docker compose up -d

After running, you can access the Dify dashboard in your browser at http://localhost/install and start the initialization process.

Please refer to our FAQ if you encounter problems setting up Dify. Reach out to the community and us if you are still having issues.

If you'd like to contribute to Dify or do additional development, refer to our guide to deploying from source code

1. Workflow : Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.

2. Comprehensive model support : Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama3, and any OpenAI API-compatible models. A full list of supported model providers can be found here.

3. Prompt IDE : Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app.

4. RAG Pipeline : Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats.

5. Agent capabilities : You can define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools for the agent. Dify provides 50+ built-in tools for AI agents, such as Google Search, DALL·E, Stable Diffusion and WolframAlpha.

6. LLMOps : Monitor and analyze application logs and performance over time. You could continuously improve prompts, datasets, and models based on production data and annotations.

7. Backend-as-a-Service : All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.

• **Cloud
  ** We host a Dify Cloud service for anyone to try with zero setup. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls in the sandbox plan. If you run into issues with Dify Cloud, contact our Cloud support team.

• **Self-hosting Dify Community Edition
  ** Quickly get Dify running in your environment with this starter guide. Use our documentation for further references and more in-depth instructions.

• **Dify for enterprise / organizations
  ** We provide additional enterprise-centric features. Send us an email to discuss your enterprise needs.

For startups and small businesses using AWS, check out Dify Premium on AWS Marketplace and deploy it to your own AWS VPC with one click. It's an affordable AMI offering with the option to create apps with custom logo and branding.

Star Dify on GitHub and be instantly notified of new releases.

If you need to customize the configuration, edit docker/.env. The essential startup defaults live in docker/.env.example, and optional advanced variables are split under docker/envs/ by theme. After making any changes, re-run docker compose up -d from the docker directory. You can find the full list of available environment variables here.

Metrics Monitoring with Grafana

Import the dashboard to Grafana, using Dify's PostgreSQL database as data source, to monitor metrics in granularity of apps, tenants, messages, and more.

Deployment with Kubernetes

If you'd like to configure a highly available setup, there are community-contributed Helm Charts and YAML files which allow Dify to be deployed on Kubernetes.

Using Terraform for Deployment

Deploy Dify to Cloud Platform with a single click using terraform

Using AWS CDK for Deployment

Deploy Dify to AWS with CDK

Using Alibaba Cloud Computing Nest

Quickly deploy Dify to Alibaba cloud with Alibaba Cloud Computing Nest

Using Alibaba Cloud Data Management

One-Click deploy Dify to Alibaba Cloud with Alibaba Cloud Data Management

Deploy to AKS with Azure Devops Pipeline

One-Click deploy Dify to AKS with Azure Devops Pipeline Helm Chart by @LeoZhang

For those who'd like to contribute code, see our Contribution Guide. At the same time, please consider supporting Dify by sharing it on social media and at events and conferences.

We are looking for contributors to help translate Dify into languages other than Mandarin or English. If you are interested in helping, please see the i18n README for more information, and leave us a comment in the global-users channel of our Discord Community Server.

Community & contact

• GitHub Discussion. Best for: sharing feedback and asking questions.
• GitHub Issues. Best for: bugs you encounter using Dify.AI, and feature proposals. See our Contribution Guide.
• Discord. Best for: sharing your applications and hanging out with the community.
• X(Twitter). Best for: sharing your applications and hanging out with the community.

Contributors

To protect your privacy, please avoid posting security issues on GitHub. Instead, report issues to security@dify.ai, and our team will respond with detailed answer.

This repository is licensed under the Dify Open Source License, based on Apache 2.0 with additional conditions.