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langgenius/dify

▸ README 原文(同步于 2026-07-19 13:11)
![cover-v5-optimized](./images/GitHub_README_if.png) <p align="center"> <a href="https://cloud.dify.ai">Dify Cloud</a> · <a href="https://docs.dify.ai/getting-started/install-self-hosted">Self-hosting</a> · <a href="https://docs.dify.ai">Documentation</a> · <a href="https://dify.ai/pricing">Dify edition overview</a> </p> <p align="center"> <a href="https://dify.ai" target="_blank"> <img alt="Static Badge" src="https://img.shields.io/badge/Product-F04438"></a> <a href="https://dify.ai/pricing" target="_blank"> <img alt="Static Badge" src="https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff"></a> <a href="https://discord.gg/FngNHpbcY7" target="_blank"> <img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb" alt="chat on Discord"></a> <a href="https://reddit.com/r/difyai" target="_blank"> <img 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href="https://github.com/langgenius/dify/" target="_blank"> <img alt="Issues closed" src="https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98"></a> <a href="https://github.com/langgenius/dify/discussions/" target="_blank"> <img alt="Discussion posts" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a> <a href="https://insights.linuxfoundation.org/project/langgenius-dify" target="_blank"> <img alt="LFX Health Score" src="https://insights.linuxfoundation.org/api/badge/health-score?project=langgenius-dify"></a> <a href="https://insights.linuxfoundation.org/project/langgenius-dify" target="_blank"> <img alt="LFX Contributors" src="https://insights.linuxfoundation.org/api/badge/contributors?project=langgenius-dify"></a> <a href="https://insights.linuxfoundation.org/project/langgenius-dify" target="_blank"> <img alt="LFX Active Contributors" src="https://insights.linuxfoundation.org/api/badge/active-contributors?project=langgenius-dify"></a> </p> <p align="center"> <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a> <a href="./docs/zh-TW/README.md"><img alt="繁體中文文件" src="https://img.shields.io/badge/繁體中文-d9d9d9"></a> <a href="./docs/zh-CN/README.md"><img alt="简体中文文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a> <a href="./docs/ja-JP/README.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a> <a href="./docs/es-ES/README.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a> <a href="./docs/fr-FR/README.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a> <a href="./docs/tlh/README.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a> <a href="./docs/ko-KR/README.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a> <a href="./docs/ar-SA/README.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a> <a href="./docs/tr-TR/README.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a> <a href="./docs/vi-VN/README.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a> <a href="./docs/de-DE/README.md"><img alt="README in Deutsch" src="https://img.shields.io/badge/German-d9d9d9"></a> <a href="./docs/it-IT/README.md"><img alt="README in Italiano" src="https://img.shields.io/badge/Italiano-d9d9d9"></a> <a href="./docs/pt-BR/README.md"><img alt="README em Português do Brasil" src="https://img.shields.io/badge/Portugu%C3%AAs%20do%20Brasil-d9d9d9"></a> <a href="./docs/sl-SI/README.md"><img alt="README Slovenščina" src="https://img.shields.io/badge/Sloven%C5%A1%C4%8Dina-d9d9d9"></a> <a href="./docs/bn-BD/README.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a> <a href="./docs/hi-IN/README.md"><img alt="README in हिन्दी" src="https://img.shields.io/badge/Hindi-d9d9d9"></a> </p> 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](https://www.comet.com/docs/opik/integrations/dify), [Langfuse](https://docs.langfuse.com), and [Arize Phoenix](https://docs.arize.com/phoenix)) and more, letting you quickly go from prototype to production. Here's a list of the core features: ## Quick start > Before installing Dify, make sure your machine meets the following minimum system requirements: > > - CPU >= 2 Core > - RAM >= 4 GiB <br/> The easiest way to start the Dify server is through [Docker Compose](docker/docker-compose.yaml). Before running Dify with the following commands, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine: ```bash 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](http://localhost/install) and start the initialization process. #### Seeking help Please refer to our [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs) if you encounter problems setting up Dify. Reach out to [the community and us](#community--contact) 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](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code) ## Key features **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](https://docs.dify.ai/getting-started/readme/model-providers). ![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3) **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. ## Using Dify - **Cloud <br/>** We host a [Dify Cloud](https://dify.ai) 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](mailto:cloud@dify.ai?subject=%5BGitHub%5DDify%20Cloud%20Support). - **Self-hosting Dify Community Edition<br/>** Quickly get Dify running in your environment with this [starter guide](#quick-start). Use our [documentation](https://docs.dify.ai) for further references and more in-depth instructions. - **Dify for enterprise / organizations<br/>** We provide additional enterprise-centric features. [Send us an email](mailto:business@dify.ai?subject=%5BGitHub%5DBusiness%20License%20Inquiry) to discuss your enterprise needs. <br/> ## Staying ahead Star Dify on GitHub and be instantly notified of new releases. ![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4) ## Advanced Setup ### Custom configurations If you need to customize the configuration, edit `docker/.env`. The essential startup defaults live in [`docker/.env.example`](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](https://docs.dify.ai/getting-started/install-self-hosted/environments). ### 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. - [Grafana Dashboard by @bowenliang123](https://github.com/bowenliang123/dify-grafana-dashboard) ### Deployment with Kubernetes If you'd like to configure a highly available setup, there are community-contributed [Helm Charts](https://helm.sh/) and YAML files which allow Dify to be deployed on Kubernetes. - [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify) - [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm) - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts) - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes) - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s) - [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes) #### Using Terraform for Deployment Deploy Dify to Cloud Platform with a single click using [terraform](https://www.terraform.io/) ##### Azure Global - [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform) ##### Google Cloud - [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform) #### Using AWS CDK for Deployment Deploy Dify to AWS with [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK by @KevinZhao (EKS based)](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) - [AWS CDK by @tmokmss (ECS based)](https://github.com/aws-samples/dify-self-hosted-on-aws) #### Using Alibaba Cloud Computing Nest Quickly deploy Dify to Alibaba cloud with [Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) #### Using Alibaba Cloud Data Management One-Click deploy Dify to Alibaba Cloud with [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) #### Deploy to AKS with Azure Devops Pipeline One-Click deploy Dify to AKS with [Azure Devops Pipeline Helm Chart by @LeoZhang](https://github.com/Ruiruiz30/Dify-helm-chart-AKS) ## Contributing For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). 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](https://github.com/langgenius/dify/blob/main/web/i18n-config/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c). ## Community & contact - [GitHub Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions. - [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). - [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community. - [X(Twitter)](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community. **Contributors** <a href="https://github.com/langgenius/dify/graphs/contributors"> <img src="https://contrib.rocks/image?repo=langgenius/dify" /> </a> ## Star History <!-- GitHub token name: star-history --> <a href="https://www.star-history.com/?repos=langgenius%2Fdify&type=date&legend=top-left"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=langgenius/dify&type=date&theme=dark&legend=top-left&sealed_token=p-SWD-UXZEDc5a2d0EMfgMmyCwVyRlSof0Qox68v7k4PvQPKRlCx0jDIlNztw7mbA6DEn96R50DojO9pCi5LQUlDBAoIhRswt8-GuC8K3rZQ3naJUXbuHqR_oItIW2F0NNM-7npevzw5SXp7L5mwixgqJncAvAGzuGq5zmhQfiDRSW_Jd6y8TQCZMJbt" /> <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=langgenius/dify&type=date&legend=top-left&sealed_token=p-SWD-UXZEDc5a2d0EMfgMmyCwVyRlSof0Qox68v7k4PvQPKRlCx0jDIlNztw7mbA6DEn96R50DojO9pCi5LQUlDBAoIhRswt8-GuC8K3rZQ3naJUXbuHqR_oItIW2F0NNM-7npevzw5SXp7L5mwixgqJncAvAGzuGq5zmhQfiDRSW_Jd6y8TQCZMJbt" /> <img alt="Star History Chart" src="https://api.star-history.com/chart?repos=langgenius/dify&type=date&legend=top-left&sealed_token=p-SWD-UXZEDc5a2d0EMfgMmyCwVyRlSof0Qox68v7k4PvQPKRlCx0jDIlNztw7mbA6DEn96R50DojO9pCi5LQUlDBAoIhRswt8-GuC8K3rZQ3naJUXbuHqR_oItIW2F0NNM-7npevzw5SXp7L5mwixgqJncAvAGzuGq5zmhQfiDRSW_Jd6y8TQCZMJbt" /> </picture> </a> ## Security disclosure 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. ## License This repository is licensed under the [Dify Open Source License](LICENSE), based on Apache 2.0 with additional conditions.
▸ 中文总结(生成于 2026-07-19 13:11)

langgenius/dify 项目介绍

一句话概括

Dify 是一个面向生产环境的、用于开发 AI 智能体工作流的低代码/无代码平台。

项目核心内容

  • 项目定位:Dify 是一个开源的、生产就绪的 AI 应用开发平台,专注于帮助开发者和非技术人员快速构建、部署和管理基于大语言模型(LLM)的智能体应用和工作流。

  • 解决的核心问题:

    • 降低 AI 应用开发的门槛,让不擅长编码的用户也能通过可视化方式编排复杂的 AI 工作流
    • 提供从原型到生产的一站式解决方案,包括数据管理、提示词工程、模型调用、应用监控等
    • 解决多模型(如 GPT-4、Gemini、开源模型)统一管理和切换的问题
    • 支持 RAG(检索增强生成)和 MCP(模型上下文协议)等高级 AI 架构的快速集成
  • 技术架构与实现思路:

    • 基于 TypeScript(前端)和 Python(后端)构建,使用 Next.js 作为前端框架
    • 采用模块化架构,核心组件包括:工作流引擎、RAG 引擎、模型适配层、应用运行时
    • 提供可视化拖拽式工作流编辑器,支持 agentic workflow(智能体工作流)的编排
    • 内置 RAG 管道,支持文档导入、分块、向量化、检索等完整流程
    • 通过插件机制支持多种 LLM 提供商(OpenAI、Gemini 等)和向量数据库
  • 技术亮点:

    • 低代码/无代码:提供可视化界面,无需编写代码即可构建复杂的 AI 工作流
    • 生产就绪:包含监控、日志、调试、版本管理等生产环境所需的基础设施
    • 多模型支持:统一抽象层,可无缝切换或组合使用不同 LLM 模型
    • RAG 原生支持:内置完整的检索增强生成流程,无需额外配置
    • MCP 支持:遵循模型上下文协议,便于与外部工具和系统集成
    • 开源且活跃:拥有超过 14 万 Star,社区活跃度高,持续迭代

Release 历史(5 条)

1.17.1 langgenius/dify 1.17.1 已完成 2026-09-10 1.17.0 langgenius/dify 1.17.0 已完成 2026-08-25 1.16.1 langgenius/dify 1.16.1 已完成 2026-07-28 1.16.0 langgenius/dify 1.16.0 已完成 2026-07-17 1.16.0 langgenius/dify 1.16.0 已完成 2026-07-17