This project includes a devcontainer configuration that allows you to open the project in a container with a fully configured development environment.
Both frontend and backend environments are initialized when the container is started.
## GitHub Codespaces
@@ -33,5 +33,5 @@ Performance Impact: While usually minimal, programs running inside a devcontaine
if you see such error message when you open this project in codespaces:
a simple workaround is change `/signin` endpoint into another one, then login with github account and close the tab, then change it back to `/signin` endpoint. Then all things will be fine.
a simple workaround is change `/signin` endpoint into another one, then login with GitHub account and close the tab, then change it back to `/signin` endpoint. Then all things will be fine.
The reason is `signin` endpoint is not allowed in codespaces, details can be found [here](https://github.com/orgs/community/discussions/5204)
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, caste, color, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Language Policy
To facilitate clear and effective communication, all discussions, comments, documentation, and pull requests in this project should be conducted in English. This ensures that all contributors can participate and collaborate effectively.
description:"To make sure we get to you in time, please check the following :)"
options:
- label:I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
required:true
- label:I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
required:true
- label:"[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:）"
required:true
- label:"Please do not modify this template :) and fill in all the required fields."
required:true
- type:textarea
attributes:
label:1. Is this request related to a challenge you're experiencing? Tell me about your story.
placeholder:Please describe the specific scenario or problem you're facing as clearly as possible. For instance "I was trying to use [feature] for [specific task], and [what happened]... It was frustrating because...."
validations:
required:true
- type:textarea
attributes:
label:2. Additional context or comments
placeholder:(Any other information, comments, documentations, links, or screenshots that would provide more clarity. This is the place to add anything else not covered above.)
description:"To make sure we get to you in time, please check the following :)"
options:
- label:I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
required:true
- label:I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
required:true
- label:"[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:）"
required:true
- label:"Please do not modify this template :) and fill in all the required fields."
required:true
- type:textarea
attributes:
label:1. Is this request related to a challenge you're experiencing? Tell me about your story.
placeholder:Please describe the specific scenario or problem you're facing as clearly as possible. For instance "I was trying to use [feature] for [specific task], and [what happened]... It was frustrating because...."
validations:
required:true
- type:textarea
attributes:
label:2. Additional context or comments
placeholder:(Any other information, comments, documentations, links, or screenshots that would provide more clarity. This is the place to add anything else not covered above.)
validations:
required:false
- type:checkboxes
attributes:
label:3. Can you help us with this feature?
description:Let us know! This is not a commitment, but a starting point for collaboration.
options:
- label:I am interested in contributing to this feature.
value:Please make sure to [search for existing issues](https://github.com/langgenius/dify/issues) before filing a new one!
- type:input
attributes:
label:Dify version
placeholder:0.3.21
description:See about section in Dify console
validations:
required:true
- type:checkboxes
attributes:
label:Self Checks
description:"To make sure we get to you in time, please check the following :)"
options:
- label:This is only for bug report, if you would like to ask a question, please head to [Discussions](https://github.com/langgenius/dify/discussions/categories/general).
required:true
- label:I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
required:true
- label:I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
required:true
- label:"[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:）"
required:true
- label:"Please do not modify this template :) and fill in all the required fields."
required:true
- type:dropdown
attributes:
label:Cloud or Self Hosted
description:How / Where was Dify installed from?
multiple:true
options:
- Cloud
- Self Hosted
- Other (please specify in "Steps to Reproduce")
validations:
required:true
- type:input
attributes:
label:Dify version
description:See about section in Dify console
validations:
required:true
- type:textarea
attributes:
label:Steps to reproduce
description:We highly suggest including screenshots and a bug report log.
placeholder:Having detailed steps helps us reproduce the bug.
validations:
required:true
- type:dropdown
attributes:
label:Cloud or Self Hosted
description:How / Where was Dify installed from?
multiple:true
options:
- Cloud
- Self Hosted (Docker)
- Self Hosted (Source)
validations:
required:true
- type:textarea
attributes:
label:✔️ Expected Behavior
placeholder:What were you expecting?
validations:
required:false
- type:textarea
attributes:
label:Steps to reproduce
description:We highly suggest including screenshots and a bug report log. Please use the right markdown syntax for code blocks.
placeholder:Having detailed steps helps us reproduce the bug.
label:Description of the new feature / enhancement
placeholder:What is the expected behavior of the proposed feature?
validations:
required:true
- type:textarea
attributes:
label:Scenario when this would be used?
placeholder:What is the scenario this would be used? Why is this important to your workflow as a dify user?
validations:
required:true
- type:textarea
attributes:
label:Supporting information
placeholder:"Having additional evidence, data, tweets, blog posts, research, ... anything is extremely helpful. This information provides context to the scenario that may otherwise be lost."
validations:
required:false
- type:markdown
attributes:
value:Please limit one request per issue.
- type:checkboxes
attributes:
label:Self Checks
description:"To make sure we get to you in time, please check the following :)"
options:
- label:I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
required:true
- label:I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
required:true
- label:"[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:）"
required:true
- label:"Please do not modify this template :) and fill in all the required fields."
required:true
- type:textarea
attributes:
label:1. Is this request related to a challenge you're experiencing? Tell me about your story.
placeholder:Please describe the specific scenario or problem you're facing as clearly as possible. For instance "I was trying to use [feature] for [specific task], and [what happened]... It was frustrating because...."
validations:
required:true
- type:textarea
attributes:
label:2. Additional context or comments
placeholder:(Any other information, comments, documentations, links, or screenshots that would provide more clarity. This is the place to add anything else not covered above.)
validations:
required:false
- type:checkboxes
attributes:
label:3. Can you help us with this feature?
description:Let us know! This is not a commitment, but a starting point for collaboration.
options:
- label:I am interested in contributing to this feature.
> Please review the checklist below before submitting your pull request.
- [ ] Please open an issue before creating a PR or link to an existing issue
- [ ] I have performed a self-review of my own code
- [ ] I have commented my code, particularly in hard-to-understand areas
- [ ] I ran `dev/reformat`(backend) and `cd web && npx lint-staged`(frontend) to appease the lint gods
# Description
Describe the big picture of your changes here to communicate to the maintainers why we should accept this pull request. If it fixes a bug or resolves a feature request, be sure to link to that issue. Close issue syntax: `Fixes #<issue number>`, see [documentation](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) for more details.
Fixes
## Type of Change
- [ ] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] This change requires a documentation update, included: [Dify Document](https://github.com/langgenius/dify-docs)
- [ ] Improvement, including but not limited to code refactoring, performance optimization, and UI/UX improvement
- [ ] Dependency upgrade
# Testing Instructions
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
So you're looking to contribute to Dify - that's awesome, we can't wait to see what you do. As a startup with limited headcount and funding, we have grand ambitions to design the most intuitive workflow for building and managing LLM applications. Any help from the community counts, truly.
Thanks for your interest in [Dify](https://dify.ai) and for wanting to contribute! Before you begin, read the
[code of conduct](https://github.com/langgenius/.github/blob/main/CODE_OF_CONDUCT.md) and check out the
This document describes how to set up your development environment to build and test [Dify](https://dify.ai).
We need to be nimble and ship fast given where we are, but we also want to make sure that contributors like you get as smooth an experience at contributing as possible. We've assembled this contribution guide for that purpose, aiming at getting you familiarized with the codebase & how we work with contributors, so you could quickly jump to the fun part.
### Install dependencies
This guide, like Dify itself, is a constant work in progress. We highly appreciate your understanding if at times it lags behind the actual project, and welcome any feedback for us to improve.
You need to install and configure the following dependencies on your machine to build [Dify](https://dify.ai):
In terms of licensing, please take a minute to read our short [License and Contributor Agreement](./LICENSE). The community also adheres to the [code of conduct](https://github.com/langgenius/.github/blob/main/CODE_OF_CONDUCT.md).
## Before you jump in
[Find](https://github.com/langgenius/dify/issues?q=is:issue+is:closed) an existing issue, or [open](https://github.com/langgenius/dify/issues/new/choose) a new one. We categorize issues into 2 types:
### Feature requests:
* If you're opening a new feature request, we'd like you to explain what the proposed feature achieves, and include as much context as possible. [@perzeusss](https://github.com/perzeuss) has made a solid [Feature Request Copilot](https://udify.app/chat/MK2kVSnw1gakVwMX) that helps you draft out your needs. Feel free to give it a try.
* If you want to pick one up from the existing issues, simply drop a comment below it saying so.
A team member working in the related direction will be looped in. If all looks good, they will give the go-ahead for you to start coding. We ask that you hold off working on the feature until then, so none of your work goes to waste should we propose changes.
Depending on whichever area the proposed feature falls under, you might talk to different team members. Here's rundown of the areas each our team members are working on at the moment:
| High-Priority Features as being labeled by a team member | High Priority |
| Popular feature requests from our [community feedback board](https://github.com/langgenius/dify/discussions/categories/feedbacks) | Medium Priority |
| Non-core features and minor enhancements | Low Priority |
- [npm](https://www.npmjs.com/) version 8.x.x or [Yarn](https://yarnpkg.com/)
- [Python](https://www.python.org/) version 3.10.x
## Local development
### 4. Installations
To set up a working developmentenvironment, just fork the project git repository and install the backend and frontend dependencies using the proper package manager and create run the docker-compose stack.
Dify is composed of a backend and a frontend. Navigate to the backend directory by `cd api/`, then follow the [Backend README](api/README.md) to install it. In a separate terminal, navigate to the frontend directory by `cd web/`, then follow the [Frontend README](web/README.md) to install.
### Fork the repository
Check the [installation FAQ](https://docs.dify.ai/learn-more/faq/self-host-faq) for a list of common issues and steps to troubleshoot.
you need to fork the [repository](https://github.com/langgenius/dify).
### 5. Visit dify in your browser
### Clone the repo
To validate your set up, head over to [http://localhost:3000](http://localhost:3000) (the default, or your self-configured URL and port) in your browser. You should now see Dify up and running.
Clone your GitHub forked repository:
## Developing
If you are adding a model provider, [this guide](https://github.com/langgenius/dify/blob/main/api/core/model_runtime/README.md) is for you.
If you are adding a tool provider to Agent or Workflow, [this guide](./api/core/tools/README.md) is for you.
To help you quickly navigate where your contribution fits, a brief, annotated outline of Dify's backend & frontend is as follows:
### Backend
Dify’s backend is written in Python using [Flask](https://flask.palletsprojects.com/en/3.0.x/). It uses [SQLAlchemy](https://www.sqlalchemy.org/) for ORM and [Celery](https://docs.celeryq.dev/en/stable/getting-started/introduction.html) for task queueing. Authorization logic goes via Flask-login.
├── tasks // Handling of async tasks and background jobs.
└── tests
```
### Install backend
### Frontend
To learn how to install the backend application, please refer to the [Backend README](api/README.md).
The website is bootstrapped on [Next.js](https://nextjs.org/) boilerplate in Typescript and uses [Tailwind CSS](https://tailwindcss.com/) for styling. [React-i18next](https://react.i18next.com/) is used for internationalization.
### Install frontend
```
[web/]
├── app // layouts, pages, and components
│ ├── (commonLayout) // common layout used throughout the app
│ ├── (shareLayout) // layouts specifically shared across token-specific sessions
│ ├── activate // activate page
│ ├── components // shared by pages and layouts
│ ├── install // install page
│ ├── signin // signin page
│ └── styles // globally shared styles
├── assets // Static assets
├── bin // scripts ran at build step
├── config // adjustable settings and options
├── context // shared contexts used by different portions of the app
├── models // describes data models & shapes of API responses
├── public // meta assets like favicon
├── service // specifies shapes of API actions
├── test
├── types // descriptions of function params and return values
└── utils // Shared utility functions
```
To learn how to install the frontend application, please refer to the [Frontend README](web/README.md).
## Submitting your PR
### Visit dify in your browser
At last, time to open a pull request (PR) to our repo. For major features, we first merge them into the `deploy/dev` branch for testing, before they go into the `main` branch. If you run into issues like merge conflicts or don't know how to open a pull request, check out [GitHub's pull request tutorial](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests).
Finally, you can now visit [http://localhost:3000](http://localhost:3000) to view the [Dify](https://dify.ai) in local environment.
And that's it! Once your PR is merged, you will be featured as a contributor in our [README](https://github.com/langgenius/dify/blob/main/README.md).
## Getting Help
## Create a pull request
After making your changes, open a pull request (PR). Once you submit your pull request, others from the Dify team/community will review it with you.
Did you have an issue, like a merge conflict, or don't know how to open a pull request? Check out [GitHub's pull request tutorial](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests) on how to resolve merge conflicts and other issues. Once your PR has been merged, you will be proudly listed as a contributor in the [contributor chart](https://github.com/langgenius/langgenius-gateway/graphs/contributors).
## Community channels
Stuck somewhere? Have any questions? Join the [Discord Community Server](https://discord.gg/j3XRWSPBf7). We are here to help!
### i18n (Internationalization) Support
We are looking for contributors to help with translations in other languages. If you are interested in helping, please join the [Discord Community Server](https://discord.gg/AhzKf7dNgk) and let us know.
Also check out the [Frontend i18n README]((web/i18n/README_EN.md)) for more information.
If you ever get stuck or got a burning question while contributing, simply shoot your queries our way via the related GitHub issue, or hop onto our [Discord](https://discord.gg/8Tpq4AcN9c) for a quick chat.
Thật tuyệt vời khi bạn muốn đóng góp cho Dify! Chúng tôi rất mong chờ được thấy những gì bạn sẽ làm. Là một startup với nguồn nhân lực và tài chính hạn chế, chúng tôi có tham vọng lớn là thiết kế quy trình trực quan nhất để xây dựng và quản lý các ứng dụng LLM. Mọi sự giúp đỡ từ cộng đồng đều rất quý giá đối với chúng tôi.
Chúng tôi cần linh hoạt và làm việc nhanh chóng, nhưng đồng thời cũng muốn đảm bảo các cộng tác viên như bạn có trải nghiệm đóng góp thuận lợi nhất có thể. Chúng tôi đã tạo ra hướng dẫn đóng góp này nhằm giúp bạn làm quen với codebase và cách chúng tôi làm việc với các cộng tác viên, để bạn có thể nhanh chóng bắt tay vào phần thú vị.
Hướng dẫn này, cũng như bản thân Dify, đang trong quá trình cải tiến liên tục. Chúng tôi rất cảm kích sự thông cảm của bạn nếu đôi khi nó không theo kịp dự án thực tế, và chúng tôi luôn hoan nghênh mọi phản hồi để cải thiện.
Về vấn đề cấp phép, xin vui lòng dành chút thời gian đọc qua [Thỏa thuận Cấp phép và Đóng góp](./LICENSE) ngắn gọn của chúng tôi. Cộng đồng cũng tuân thủ [quy tắc ứng xử](https://github.com/langgenius/.github/blob/main/CODE_OF_CONDUCT.md).
## Trước khi bắt đầu
[Tìm kiếm](https://github.com/langgenius/dify/issues?q=is:issue+is:closed) một vấn đề hiện có, hoặc [tạo mới](https://github.com/langgenius/dify/issues/new/choose) một vấn đề. Chúng tôi phân loại các vấn đề thành 2 loại:
### Yêu cầu tính năng:
* Nếu bạn đang tạo một yêu cầu tính năng mới, chúng tôi muốn bạn giải thích tính năng đề xuất sẽ đạt được điều gì và cung cấp càng nhiều thông tin chi tiết càng tốt. [@perzeusss](https://github.com/perzeuss) đã tạo một [Trợ lý Yêu cầu Tính năng](https://udify.app/chat/MK2kVSnw1gakVwMX) rất hữu ích để giúp bạn soạn thảo nhu cầu của mình. Hãy thử dùng nó nhé.
* Nếu bạn muốn chọn một vấn đề từ danh sách hiện có, chỉ cần để lại bình luận dưới vấn đề đó nói rằng bạn sẽ làm.
Một thành viên trong nhóm làm việc trong lĩnh vực liên quan sẽ được thông báo. Nếu mọi thứ ổn, họ sẽ cho phép bạn bắt đầu code. Chúng tôi yêu cầu bạn chờ đợi cho đến lúc đó trước khi bắt tay vào làm tính năng, để không lãng phí công sức của bạn nếu chúng tôi đề xuất thay đổi.
Tùy thuộc vào lĩnh vực mà tính năng đề xuất thuộc về, bạn có thể nói chuyện với các thành viên khác nhau trong nhóm. Dưới đây là danh sách các lĩnh vực mà các thành viên trong nhóm chúng tôi đang làm việc hiện tại:
| [@yeuoly](https://github.com/Yeuoly) | Thiết kế kiến trúc Agents |
| [@jyong](https://github.com/JohnJyong) | Thiết kế quy trình RAG |
| [@GarfieldDai](https://github.com/GarfieldDai) | Xây dựng quy trình làm việc |
| [@iamjoel](https://github.com/iamjoel) & [@zxhlyh](https://github.com/zxhlyh) | Làm cho giao diện người dùng dễ sử dụng |
| [@guchenhe](https://github.com/guchenhe) & [@crazywoola](https://github.com/crazywoola) | Trải nghiệm nhà phát triển, đầu mối liên hệ cho mọi vấn đề |
| [@takatost](https://github.com/takatost) | Định hướng và kiến trúc tổng thể sản phẩm |
| Tính năng ưu tiên cao được gắn nhãn bởi thành viên trong nhóm | Ưu tiên cao |
| Yêu cầu tính năng phổ biến từ [bảng phản hồi cộng đồng](https://github.com/langgenius/dify/discussions/categories/feedbacks) của chúng tôi | Ưu tiên trung bình |
| Tính năng không quan trọng và cải tiến nhỏ | Ưu tiên thấp |
| Có giá trị nhưng không cấp bách | Tính năng tương lai |
### Những vấn đề khác (ví dụ: báo cáo lỗi, tối ưu hiệu suất, sửa lỗi chính tả):
- [npm](https://www.npmjs.com/) phiên bản 8.x.x hoặc [Yarn](https://yarnpkg.com/)
- [Python](https://www.python.org/) phiên bản 3.10.x
### 4. Cài đặt
Dify bao gồm một backend và một frontend. Đi đến thư mục backend bằng lệnh `cd api/`, sau đó làm theo hướng dẫn trong [README của Backend](api/README.md) để cài đặt. Trong một terminal khác, đi đến thư mục frontend bằng lệnh `cd web/`, sau đó làm theo hướng dẫn trong [README của Frontend](web/README.md) để cài đặt.
Kiểm tra [FAQ về cài đặt](https://docs.dify.ai/learn-more/faq/self-host-faq) để xem danh sách các vấn đề thường gặp và các bước khắc phục.
### 5. Truy cập Dify trong trình duyệt của bạn
Để xác nhận cài đặt của bạn, hãy truy cập [http://localhost:3000](http://localhost:3000) (địa chỉ mặc định, hoặc URL và cổng bạn đã cấu hình) trong trình duyệt. Bạn sẽ thấy Dify đang chạy.
## Phát triển
Nếu bạn đang thêm một nhà cung cấp mô hình, [hướng dẫn này](https://github.com/langgenius/dify/blob/main/api/core/model_runtime/README.md) dành cho bạn.
Nếu bạn đang thêm một nhà cung cấp công cụ cho Agent hoặc Workflow, [hướng dẫn này](./api/core/tools/README.md) dành cho bạn.
Để giúp bạn nhanh chóng định hướng phần đóng góp của mình, dưới đây là một bản phác thảo ngắn gọn về cấu trúc backend & frontend của Dify:
### Backend
Backend của Dify được viết bằng Python sử dụng [Flask](https://flask.palletsprojects.com/en/3.0.x/). Nó sử dụng [SQLAlchemy](https://www.sqlalchemy.org/) cho ORM và [Celery](https://docs.celeryq.dev/en/stable/getting-started/introduction.html) cho hàng đợi tác vụ. Logic xác thực được thực hiện thông qua Flask-login.
```
[api/]
├── constants // Các cài đặt hằng số được sử dụng trong toàn bộ codebase.
├── controllers // Định nghĩa các route API và logic xử lý yêu cầu.
├── core // Điều phối ứng dụng cốt lõi, tích hợp mô hình và công cụ.
├── docker // Cấu hình liên quan đến Docker & containerization.
├── events // Xử lý và xử lý sự kiện
├── extensions // Mở rộng với các framework/nền tảng bên thứ 3.
├── fields // Định nghĩa trường cho serialization/marshalling.
├── libs // Thư viện và tiện ích có thể tái sử dụng.
├── migrations // Script cho việc di chuyển cơ sở dữ liệu.
├── models // Mô hình cơ sở dữ liệu & định nghĩa schema.
├── services // Xác định logic nghiệp vụ.
├── storage // Lưu trữ khóa riêng tư.
├── tasks // Xử lý các tác vụ bất đồng bộ và công việc nền.
└── tests
```
### Frontend
Website được khởi tạo trên boilerplate [Next.js](https://nextjs.org/) bằng Typescript và sử dụng [Tailwind CSS](https://tailwindcss.com/) cho styling. [React-i18next](https://react.i18next.com/) được sử dụng cho việc quốc tế hóa.
```
[web/]
├── app // layouts, pages và components
│ ├── (commonLayout) // layout chung được sử dụng trong toàn bộ ứng dụng
│ ├── (shareLayout) // layouts được chia sẻ cụ thể cho các phiên dựa trên token
│ ├── activate // trang kích hoạt
│ ├── components // được chia sẻ bởi các trang và layouts
│ ├── install // trang cài đặt
│ ├── signin // trang đăng nhập
│ └── styles // styles được chia sẻ toàn cục
├── assets // Tài nguyên tĩnh
├── bin // scripts chạy ở bước build
├── config // cài đặt và tùy chọn có thể điều chỉnh
├── context // contexts được chia sẻ bởi các phần khác nhau của ứng dụng
├── dictionaries // File dịch cho từng ngôn ngữ
├── docker // cấu hình container
├── hooks // Hooks có thể tái sử dụng
├── i18n // Cấu hình quốc tế hóa
├── models // mô tả các mô hình dữ liệu & hình dạng của phản hồi API
├── public // tài nguyên meta như favicon
├── service // xác định hình dạng của các hành động API
├── test
├── types // mô tả các tham số hàm và giá trị trả về
└── utils // Các hàm tiện ích được chia sẻ
```
## Gửi PR của bạn
Cuối cùng, đã đến lúc mở một pull request (PR) đến repository của chúng tôi. Đối với các tính năng lớn, chúng tôi sẽ merge chúng vào nhánh `deploy/dev` để kiểm tra trước khi đưa vào nhánh `main`. Nếu bạn gặp vấn đề như xung đột merge hoặc không biết cách mở pull request, hãy xem [hướng dẫn về pull request của GitHub](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests).
Và thế là xong! Khi PR của bạn được merge, bạn sẽ được giới thiệu là một người đóng góp trong [README](https://github.com/langgenius/dify/blob/main/README.md) của chúng tôi.
## Nhận trợ giúp
Nếu bạn gặp khó khăn hoặc có câu hỏi cấp bách trong quá trình đóng góp, hãy đặt câu hỏi của bạn trong vấn đề GitHub liên quan, hoặc tham gia [Discord](https://discord.gg/8Tpq4AcN9c) của chúng tôi để trò chuyện nhanh chóng.
The Dify project is licensed under the Apache License 2.0, with the following additional conditions:
Dify is licensed under the Apache License 2.0, with the following additional conditions:
1. Dify is permitted to be used for commercialization, such as using Dify as a "backend-as-a-service" for your other applications, or delivering it to enterprises as an application development platform. However, when the following conditions are met, you must contact the producer to obtain a commercial license:
1. Dify may be utilized commercially, including as a backendservice for other applications or as an application development platform for enterprises. Should the conditions below be met, a commercial license must be obtained from the producer:
a. Multi-tenant SaaS service: Unless explicitly authorized by Dify in writing, you may not use the Dify.AI source code to operate a multi-tenant SaaS service that is similar to the Dify.AI service edition.
b. LOGO and copyright information: In the process of using Dify, you may not remove or modify the LOGO or copyright information in the Dify console.
a. Multi-tenant SaaS service: Unless explicitly authorized by Dify in writing, you may not use the Dify source code to operate a multi-tenant environment.
- Tenant Definition: Within the context of Dify, one tenant corresponds to one workspace. The workspace provides a separated area for each tenant's data and configurations.
b. LOGO and copyright information: In the process of using Dify's frontend components, you may not remove or modify the LOGO or copyright information in the Dify console or applications. This restriction is inapplicable to uses of Dify that do not involve its frontend components.
Please contact business@dify.ai by email to inquire about licensing matters.
2. As a contributor, you should agree that your contributed code:
2. As a contributor, you should agree that:
a. The producer can adjust the open-source agreement to be more strict or relaxed.
b. Can be used for commercial purposes, such as Dify's cloud business.
a. The producer can adjust the open-source agreement to be more strict or relaxed as deemed necessary.
b. Your contributed code may be used for commercial purposes, including but not limited to its cloud business operations.
Apart from this, all other rights and restrictions follow the Apache License 2.0. If you need more detailed information, you can refer to the full version of Apache License 2.0.
Apart from the specific conditions mentioned above, all other rights and restrictions follow the Apache License 2.0. Detailed information about the Apache License 2.0 can be found at http://www.apache.org/licenses/LICENSE-2.0.
The interactive design of this product is protected by appearance patent.
**Dify** is an easy-to-use LLMOps platform designed to empower more people to create sustainable, AI-native applications. With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement.
Applications created with Dify include:
Out-of-the-box web sites supporting form mode and chat conversation mode
A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort
Visual data analysis, log review, and annotation for applications
<p align="center">
<a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production. Here's a list of the core features:
</br> </br>
**1. Workflow**:
Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.
## Highlighted Features
**1. LLMs support:** Choose capabilities based on different models when building your Dify AI apps. Dify is compatible with Langchain, meaning it will support various LLMs. Currently supported:
We provide the following free resources for registered Dify cloud users (sign up at [dify.ai](https://dify.ai)):
* 600,000 free Claude model tokens to build Claude-powered apps
* 200 free OpenAI queries to build OpenAI-based apps
**2. Visual orchestration:** Build an AI app in minutes by writing and debugging prompts visually.
**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).
**3. Text embedding:** Fully automated text preprocessing embeds your data as context without complex concepts. Supports PDF, TXT, and syncing data from Notion, webpages, APIs.
**4. API-based:** Backend-as-a-service. Access web apps directly or integrate via APIs without complex backend setup.
**5. Plugins:** Dify "Smart Chat" now supports first-party plugins like web browsing, Google search, Wikipedia to enable online lookup, analyzing web content, and explaining the AI's reasoning process conversationally.
**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.
**6. Team workspaces:** Team members can join workspaces to collaboratively edit, manage, and use team AI apps.
**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.
**7. Data labeling and improvement:** Visually inspect AI app logs and improve data via labeling. Observe the AI's reasoning process to continuously enhance performance. (Coming soon)
**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.
## Use cases
* [Create an AI ChatBot with Business Data in Minutes.](https://docs.dify.ai/use-cases/create-an-ai-chatbot-with-business-data-in-minutes)
* [How to Build an Notion AI Assistant Based on Your Own Notes?](https://docs.dify.ai/use-cases/build-an-notion-ai-assistant)
* [Create a Midjoureny Prompt Bot Without Code in Just a Few Minutes.](https://docs.dify.ai/use-cases/create-a-midjoureny-prompt-bot-with-dify)
**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.
## Use Cloud Services
**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.
Visit [Dify.ai](https://dify.ai)
## Install the Community Edition
## Feature comparison
<table style="width: 100%;">
<tr>
<th align="center">Feature</th>
<th align="center">Dify.AI</th>
<th align="center">LangChain</th>
<th align="center">Flowise</th>
<th align="center">OpenAI Assistants API</th>
</tr>
<tr>
<td align="center">Programming Approach</td>
<td align="center">API + App-oriented</td>
<td align="center">Python Code</td>
<td align="center">App-oriented</td>
<td align="center">API-oriented</td>
</tr>
<tr>
<td align="center">Supported LLMs</td>
<td align="center">Rich Variety</td>
<td align="center">Rich Variety</td>
<td align="center">Rich Variety</td>
<td align="center">OpenAI-only</td>
</tr>
<tr>
<td align="center">RAG Engine</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Agent</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Workflow</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Observability</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Enterprise Features (SSO/Access control)</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Local Deployment</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
</table>
### System Requirements
## Using Dify
Before installing Dify, make sure your machine meets the following minimum system requirements:
- **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.
-CPU >= 2 Core
- RAM >= 4GB
-**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.
### Quick Start
- **Dify for enterprise / organizations</br>**
We provide additional enterprise-centric features. [Log your questions for us through this chatbot](https://udify.app/chat/22L1zSxg6yW1cWQg) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
> For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) 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.
## Staying ahead
Star Dify on GitHub and be instantly notified of new releases.
> Before installing Dify, make sure your machine meets the following minimum system requirements:
>
>- CPU >= 2 Core
>- RAM >= 4GB
</br>
The easiest way to start the Dify server is to run our [docker-compose.yml](docker/docker-compose.yaml) file. Before running the installation command, 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 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 installation process.
After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization process.
### Helm Chart
> 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)
A big thanks to @BorisPolonsky for providing us with a [Helm Chart](https://helm.sh/) version, which allows Dify to be deployed on Kubernetes.
You can go to https://github.com/BorisPolonsky/dify-helm for deployment information.
## Next steps
### Configuration
If you need to customize the configuration, please refer to the comments in our [.env.example](docker/.env.example) file and update the corresponding values in your `.env` file. Additionally, you might need to make adjustments to the `docker-compose.yaml` file itself, such as changing image versions, port mappings, or volume mounts, based on your specific deployment environment and requirements. After making any changes, please re-run `docker-compose up -d`. You can find the full list of available environment variables [here](https://docs.dify.ai/getting-started/install-self-hosted/environments).
If you need to customize the configuration, please refer to the comments in our [docker-compose.yml](docker/docker-compose.yaml) file and manually set the environment configuration. After making the changes, please run 'docker-compose up -d' again.
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.
## Roadmap
- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
Features under development:
#### Using Terraform for Deployment
- **Datasets**, supporting more datasets, e.g. syncing content from Notion or webpages
We will support more datasets, including text, webpages, and even Notion content. Users can build AI applications based on their own data sources.
-**Plugins**, introducing ChatGPT Plugin-standard plugins for applications, or using Dify-produced plugins
We will release plugins complying with ChatGPT standard, or Dify's own plugins to enable more capabilities in applications.
##### Azure Global
Deploy Dify to Azure with a single click using [terraform](https://www.terraform.io/).
-[Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
## 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.
## Q&A
> We are looking for contributors to help with translating Dify to 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/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c).
**Q: What can I do with Dify?**
**Contributors**
A: Dify is a simple yet powerful LLM development and operations tool. You can use it to build commercial-grade applications, personal assistants. If you want to develop your own applications, LangDifyGenius can save you backend work in integrating with OpenAI and offer visual operations capabilities, allowing you to continuously improve and train your GPT model.
A: A valuable application consists of Prompt Engineering, context enhancement, and Fine-tuning. We've created a hybrid programming approach combining Prompts with programming languages (similar to a template engine), making it easy to accomplish long-text embedding or capturing subtitles from a user-input Youtube video - all of which will be submitted as context for LLMs to process. We place great emphasis on application operability, with data generated by users during App usage available for analysis, annotation, and continuous training. Without the right tools, these steps can be time-consuming.
* [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.
* [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
**Q: What do I need to prepare if I want to create my own application?**
A: We assume you already have an OpenAI API Key; if not, please register for one. If you already have some content that can serve as training context, that's great!
**Q: What interface languages are available?**
A: English and Chinese are currently supported, and you can contribute language packs to us.
## Star History
## Star history
[](https://star-history.com/#langgenius/dify&Date)
## Contributing
We welcome you to contribute to Dify to help make Dify better. We welcome contributions in various ways, submitting code, issues, new ideas, or sharing the interesting and useful AI applications you have created based on Dify. At the same time, we also welcome you to share Dify at different events, conferences, and social media.
### Submit a Pull Request
To ensure proper review, all code contributions, including from contributors with direct commit access, must be submitted as PR requests and approved by core developers before merging branches.
We welcome PRs from everyone! If you're willing to help out, you can learn more about how to contribute code to the project in the [Contribution Guide](CONTRIBUTING.md).
### Submit issues or ideas
You can submit your issues or ideas by adding issues to the Dify repository. If you encounter issues, please describe the steps you took to encounter the issue as much as possible so we can better discover it. If you have any new ideas for our product, we also welcome your feedback. Please share your insights as much as possible so we can get more feedback and further discussion in the community.
### Share your applications
We encourage all community members to share their AI applications built on Dify, which can be applied to different scenarios or different users. This will provide powerful inspiration for people who want to create AI capabilities! You can share your experience by [submitting an issue in the Dify-user-case repository](https://github.com/langgenius/dify-user-case/issues).
### Share Dify with others
We encourage community contributors to actively demonstrate different aspects of using Dify. You can talk or share any feature of using Dify at meetups and conferences, blogs or social media. We believe your unique sharing will be of great help to others! Mention @Dify.AI on Twitter and/or communicate on [Discord](https://discord.gg/FngNHpbcY7) so we can give pointers and tips and help you spread the word by promoting your content on the different Dify communication channels.
### Help others
You can also help people in need of help on Discord, GitHub issues or other social platforms, guide others to solve problems encountered during use and share usage experiences. This is also a great contribution! If you want to become a maintainer of the Dify community, please contact the official team via [Discord](https://discord.gg/FngNHpbcY7) or email us at support@dify.ai.
## Contact Us
If you have any questions, suggestions, or partnership inquiries, feel free to contact us through the following channels:
- Submit an Issue or PR on our GitHub Repo
- Join the discussion in our [Discord](https://discord.gg/FngNHpbcY7) Community
- Send an email to hello@dify.ai
We're eager to assist you and together create more fun and useful AI applications!
## Security
## Security disclosure
To protect your privacy, please avoid posting security issues on GitHub. Instead, send your questions to security@dify.ai and we will provide you with a more detailed answer.
## Citation
This software uses the following open-source software:
- Chase, H. (2022). LangChain [Computer software]. https://github.com/hwchase17/langchain
For more information, please refer to the official website or license text of the respective software.
## License
This repository is available under the [Dify Open Source License](LICENSE).
This repository is available under the [Dify Open Source License](LICENSE), which is essentially Apache 2.0 with a few additional restrictions.
<a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
</p>
<div style="text-align: right;">
مشروع Dify هو منصة تطوير تطبيقات الذكاء الصناعي مفتوحة المصدر. تجمع واجهته البديهية بين سير العمل الذكي بالذكاء الاصطناعي وخط أنابيب RAG وقدرات الوكيل وإدارة النماذج وميزات الملاحظة وأكثر من ذلك، مما يتيح لك الانتقال بسرعة من المرحلة التجريبية إلى الإنتاج. إليك قائمة بالميزات الأساسية:
</br> </br>
**1. سير العمل**: قم ببناء واختبار سير عمل الذكاء الاصطناعي القوي على قماش بصري، مستفيدًا من جميع الميزات التالية وأكثر.
**2. الدعم الشامل للنماذج**: تكامل سلس مع مئات من LLMs الخاصة / مفتوحة المصدر من عشرات من موفري التحليل والحلول المستضافة ذاتيًا، مما يغطي GPT و Mistral و Llama3 وأي نماذج متوافقة مع واجهة OpenAI API. يمكن العثور على قائمة كاملة بمزودي النموذج المدعومين [هنا](https://docs.dify.ai/getting-started/readme/model-providers).
**3. بيئة التطوير للأوامر**: واجهة بيئة التطوير المبتكرة لصياغة الأمر ومقارنة أداء النموذج، وإضافة ميزات إضافية مثل تحويل النص إلى كلام إلى تطبيق قائم على الدردشة.
**4. خط أنابيب RAG**: قدرات RAG الواسعة التي تغطي كل شيء من استيعاب الوثائق إلى الاسترجاع، مع الدعم الفوري لاستخراج النص من ملفات PDF و PPT وتنسيقات الوثائق الشائعة الأخرى.
**5. قدرات الوكيل**: يمكنك تعريف الوكلاء بناءً على أمر وظيفة LLM أو ReAct، وإضافة أدوات مدمجة أو مخصصة للوكيل. توفر Dify أكثر من 50 أداة مدمجة لوكلاء الذكاء الاصطناعي، مثل البحث في Google و DALL·E وStable Diffusion و WolframAlpha.
**6. الـ LLMOps**: راقب وتحلل سجلات التطبيق والأداء على مر الزمن. يمكنك تحسين الأوامر والبيانات والنماذج باستمرار استنادًا إلى البيانات الإنتاجية والتعليقات.
**7.الواجهة الخلفية (Backend) كخدمة**: تأتي جميع عروض Dify مع APIs مطابقة، حتى يمكنك دمج Dify بسهولة في منطق أعمالك الخاص.
## مقارنة الميزات
<table style="width: 100%;">
<tr>
<th align="center">الميزة</th>
<th align="center">Dify.AI</th>
<th align="center">LangChain</th>
<th align="center">Flowise</th>
<th align="center">OpenAI Assistants API</th>
</tr>
<tr>
<td align="center">نهج البرمجة</td>
<td align="center">موجّه لـ تطبيق + واجهة برمجة تطبيق (API)</td>
<td align="center">برمجة Python</td>
<td align="center">موجه لتطبيق</td>
<td align="center">واجهة برمجة تطبيق (API)</td>
</tr>
<tr>
<td align="center">LLMs المدعومة</td>
<td align="center">تنوع غني</td>
<td align="center">تنوع غني</td>
<td align="center">تنوع غني</td>
<td align="center">فقط OpenAI</td>
</tr>
<tr>
<td align="center">محرك RAG</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">الوكيل</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">سير العمل</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">الملاحظة</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">ميزات الشركات (SSO / مراقبة الوصول)</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">نشر محلي</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
</table>
## استخدام Dify
- **سحابة </br>**
نحن نستضيف [خدمة Dify Cloud](https://dify.ai) لأي شخص لتجربتها بدون أي إعدادات. توفر كل قدرات النسخة التي تمت استضافتها ذاتيًا، وتتضمن 200 أمر GPT-4 مجانًا في خطة الصندوق الرملي.
- **استضافة ذاتية لنسخة المجتمع Dify</br>**
ابدأ سريعًا في تشغيل Dify في بيئتك باستخدام [دليل البدء السريع](#البدء السريع).
استخدم [توثيقنا](https://docs.dify.ai) للمزيد من المراجع والتعليمات الأعمق.
- **مشروع Dify للشركات / المؤسسات</br>**
نحن نوفر ميزات إضافية مركزة على الشركات. [جدول اجتماع معنا](https://cal.com/guchenhe/30min) أو [أرسل لنا بريدًا إلكترونيًا](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) لمناقشة احتياجات الشركات. </br>
> بالنسبة للشركات الناشئة والشركات الصغيرة التي تستخدم خدمات AWS، تحقق من [Dify Premium على AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) ونشرها في شبكتك الخاصة على AWS VPC بنقرة واحدة. إنها عرض AMI بأسعار معقولة مع خيار إنشاء تطبيقات بشعار وعلامة تجارية مخصصة.
## البقاء قدمًا
قم بإضافة نجمة إلى Dify على GitHub وتلق تنبيهًا فوريًا بالإصدارات الجديدة.
> قبل تثبيت Dify، تأكد من أن جهازك يلبي الحد الأدنى من متطلبات النظام التالية:
>
>- معالج >= 2 نواة
>- ذاكرة وصول عشوائي (RAM) >= 4 جيجابايت
</br>
أسهل طريقة لبدء تشغيل خادم Dify هي تشغيل ملف [docker-compose.yml](docker/docker-compose.yaml) الخاص بنا. قبل تشغيل أمر التثبيت، تأكد من تثبيت [Docker](https://docs.docker.com/get-docker/) و [Docker Compose](https://docs.docker.com/compose/install/) على جهازك:
```bash
cd docker
cp .env.example .env
docker compose up -d
```
بعد التشغيل، يمكنك الوصول إلى لوحة تحكم Dify في متصفحك على [http://localhost/install](http://localhost/install) وبدء عملية التهيئة.
> إذا كنت ترغب في المساهمة في Dify أو القيام بتطوير إضافي، فانظر إلى [دليلنا للنشر من الشفرة (code) المصدرية](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
## الخطوات التالية
إذا كنت بحاجة إلى تخصيص الإعدادات، فيرجى الرجوع إلى التعليقات في ملف [.env.example](docker/.env.example) وتحديث القيم المقابلة في ملف `.env`. بالإضافة إلى ذلك، قد تحتاج إلى إجراء تعديلات على ملف `docker-compose.yaml` نفسه، مثل تغيير إصدارات الصور أو تعيينات المنافذ أو نقاط تحميل وحدات التخزين، بناءً على بيئة النشر ومتطلباتك الخاصة. بعد إجراء أي تغييرات، يرجى إعادة تشغيل `docker-compose up -d`. يمكنك العثور على قائمة كاملة بمتغيرات البيئة المتاحة [هنا](https://docs.dify.ai/getting-started/install-self-hosted/environments).
يوجد مجتمع خاص بـ [Helm Charts](https://helm.sh/) وملفات YAML التي تسمح بتنفيذ Dify على Kubernetes للنظام من الإيجابيات العلوية.
- [رسم بياني Helm من قبل @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [رسم بياني Helm من قبل @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [ملف YAML من قبل @Winson-030](https://github.com/Winson-030/dify-kubernetes)
#### استخدام Terraform للتوزيع
##### Azure Global
استخدم [terraform](https://www.terraform.io/) لنشر Dify على Azure بنقرة واحدة.
- [Azure Terraform بواسطة @nikawang](https://github.com/nikawang/dify-azure-terraform)
## المساهمة
لأولئك الذين يرغبون في المساهمة، انظر إلى [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) لدينا.
في الوقت نفسه، يرجى النظر في دعم Dify عن طريق مشاركته على وسائل التواصل الاجتماعي وفي الفعاليات والمؤتمرات.
> نحن نبحث عن مساهمين لمساعدة في ترجمة Dify إلى لغات أخرى غير اللغة الصينية المندرين أو الإنجليزية. إذا كنت مهتمًا بالمساعدة، يرجى الاطلاع على [README للترجمة](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) لمزيد من المعلومات، واترك لنا تعليقًا في قناة `global-users` على [خادم المجتمع على Discord](https://discord.gg/8Tpq4AcN9c).
* [المشكلات على GitHub](https://github.com/langgenius/dify/issues). الأفضل لـ: الأخطاء التي تواجهها في استخدام Dify.AI، واقتراحات الميزات. انظر [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
* [Discord](https://discord.gg/FngNHpbcY7). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
* [تويتر](https://twitter.com/dify_ai). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
## تاريخ النجمة
[](https://star-history.com/#langgenius/dify&Date)
## الكشف عن الأمان
لحماية خصوصيتك، يرجى تجنب نشر مشكلات الأمان على GitHub. بدلاً من ذلك، أرسل أسئلتك إلى security@dify.ai وسنقدم لك إجابة أكثر تفصيلاً.
## الرخصة
هذا المستودع متاح تحت [رخصة البرنامج الحر Dify](LICENSE)، والتي تعتبر بشكل أساسي Apache 2.0 مع بعض القيود الإضافية.
<img alt="Actividad de Commits el último mes" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
<img alt="Publicaciones de discusión" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a>
</p>
**Dify** es una plataforma LLMOps fácil de usar diseñada para capacitar a más personas para que creen aplicaciones sostenibles basadas en IA. Con orquestación visual para varios tipos de aplicaciones, Dify ofrece aplicaciones listas para usar que también pueden funcionar como APIs de Backend-as-a-Service. Unifica tu proceso de desarrollo con una API para la integración de complementos y conjuntos de datos, y agiliza tus operaciones utilizando una interfaz única para la ingeniería de indicaciones, análisis visual y mejora continua.
<p align="center">
<a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
Dify es una plataforma de desarrollo de aplicaciones de LLM de código abierto. Su interfaz intuitiva combina flujo de trabajo de IA, pipeline RAG, capacidades de agente, gestión de modelos, características de observabilidad y más, lo que le permite pasar rápidamente de un prototipo a producción. Aquí hay una lista de las características principales:
</br> </br>
Dify es compatible con Langchain, lo que significa que gradualmente admitiremos múltiples LLMs, actualmente compatibles con:
**1. Flujo de trabajo**:
Construye y prueba potentes flujos de trabajo de IA en un lienzo visual, aprovechando todas las siguientes características y más.
Integración perfecta con cientos de LLMs propietarios / de código abierto de docenas de proveedores de inferencia y soluciones auto-alojadas, que cubren GPT, Mistral, Llama3 y cualquier modelo compatible con la API de OpenAI. Se puede encontrar una lista completa de proveedores de modelos admitidos [aquí](https://docs.dify.ai/getting-started/readme/model-providers).
Antes de instalar Dify, asegúrate de que tu máquina cumple con los siguientes requisitos mínimos del sistema:
Interfaz intuitiva para crear prompts, comparar el rendimiento del modelo y agregar características adicionales como texto a voz a una aplicación basada en chat.
La forma más sencilla de iniciar el servidor de Dify es ejecutar nuestro archivo [docker-compose.yml](docker/docker-compose.yaml). Antes de ejecutar el comando de instalación, asegúrate de que [Docker](https://docs.docker.com/get-docker/) y [Docker Compose](https://docs.docker.com/compose/install/) estén instalados en tu máquina:
**4. Pipeline RAG**:
Amplias capacidades de RAG que cubren todo, desde la ingestión de documentos hasta la recuperación, con soporte listo para usar para la extracción de texto de PDF, PPT y otros formatos de documento comunes.
**5. Capacidades de agente**:
Puedes definir agent
es basados en LLM Function Calling o ReAct, y agregar herramientas preconstruidas o personalizadas para el agente. Dify proporciona más de 50 herramientas integradas para agentes de IA, como Búsqueda de Google, DALL·E, Difusión Estable y WolframAlpha.
**6. LLMOps**:
Supervisa y analiza registros de aplicaciones y rendimiento a lo largo del tiempo. Podrías mejorar continuamente prompts, conjuntos de datos y modelos basados en datos de producción y anotaciones.
**7. Backend como servicio**:
Todas las ofertas de Dify vienen con APIs correspondientes, por lo que podrías integrar Dify sin esfuerzo en tu propia lógica empresarial.
## Comparación de características
<table style="width: 100%;">
<tr>
<th align="center">Característica</th>
<th align="center">Dify.AI</th>
<th align="center">LangChain</th>
<th align="center">Flowise</th>
<th align="center">API de Asistentes de OpenAI</th>
</tr>
<tr>
<td align="center">Enfoque de programación</td>
<td align="center">API + orientado a la aplicación</td>
<td align="center">Código Python</td>
<td align="center">Orientado a la aplicación</td>
<td align="center">Orientado a la API</td>
</tr>
<tr>
<td align="center">LLMs admitidos</td>
<td align="center">Gran variedad</td>
<td align="center">Gran variedad</td>
<td align="center">Gran variedad</td>
<td align="center">Solo OpenAI</td>
</tr>
<tr>
<td align="center">Motor RAG</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Agente</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Flujo de trabajo</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Observabilidad</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Característica empresarial (SSO/Control de acceso)</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Implementación local</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
</table>
## Usando Dify
- **Nube </br>**
Hospedamos un servicio [Dify Cloud](https://dify.ai) para que cualquiera lo pruebe sin configuración. Proporciona todas las capacidades de la versión autoimplementada e incluye 200 llamadas gratuitas a GPT-4 en el plan sandbox.
- **Auto-alojamiento de Dify Community Edition</br>**
Pon rápidamente Dify en funcionamiento en tu entorno con esta [guía de inicio rápido](#quick-start).
Usa nuestra [documentación](https://docs.dify.ai) para más referencias e instrucciones más detalladas.
- **Dify para Empresas / Organizaciones</br>**
Proporcionamos características adicionales centradas en la empresa. [Envíanos un correo electrónico](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) para discutir las necesidades empresariales. </br>
> Para startups y pequeñas empresas que utilizan AWS, echa un vistazo a [Dify Premium en AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) e impleméntalo en tu propio VPC de AWS con un clic. Es una AMI asequible que ofrece la opción de crear aplicaciones con logotipo y marca personalizados.
## Manteniéndote al tanto
Dale estrella a Dify en GitHub y serás notificado instantáneamente de las nuevas versiones.
> Antes de instalar Dify, asegúrate de que tu máquina cumpla con los siguientes requisitos mínimos del sistema:
>
>- CPU >= 2 núcleos
>- RAM >= 4GB
</br>
La forma más fácil de iniciar el servidor de Dify es ejecutar nuestro archivo [docker-compose.yml](docker/docker-compose.yaml). Antes de ejecutar el comando de instalación, asegúrate de que [Docker](https://docs.docker.com/get-docker/) y [Docker Compose](https://docs.docker.com/compose/install/) estén instalados en tu máquina:
```bash
cd docker
cp .env.example .env
docker compose up -d
```
Después de ejecutarlo, puedes acceder al panel de control de Dify en tu navegador desde [http://localhost/install](http://localhost/install) y comenzar el proceso de instalación de inicialización.
Después de ejecutarlo, puedes acceder al panel de control de Dify en tu navegador en [http://localhost/install](http://localhost/install) y comenzar el proceso de inicialización.
### Helm Chart
> Si deseas contribuir a Dify o realizar desarrollo adicional, consulta nuestra [guía para implementar desde el código fuente](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
Un gran agradecimiento a @BorisPolonsky por proporcionarnos una versión de [Helm Chart](https://helm.sh/), que permite desplegar Dify en Kubernetes.
Puede ir a https://github.com/BorisPolonsky/dify-helm para obtener información de despliegue.
## Próximos pasos
### Configuración
Si necesita personalizar la configuración, consulte los comentarios en nuestro archivo [.env.example](docker/.env.example) y actualice los valores correspondientes en su archivo `.env`. Además, es posible que deba realizar ajustes en el propio archivo `docker-compose.yaml`, como cambiar las versiones de las imágenes, las asignaciones de puertos o los montajes de volúmenes, según su entorno de implementación y requisitos específicos. Después de realizar cualquier cambio, vuelva a ejecutar `docker-compose up -d`. Puede encontrar la lista completa de variables de entorno disponibles [aquí](https://docs.dify.ai/getting-started/install-self-hosted/environments).
Si necesitas personalizar la configuración, consulta los comentarios en nuestro archivo [docker-compose.yml](docker/docker-compose.yaml) y configura manualmente la configuración del entorno. Después de realizar los cambios, ejecuta nuevamente 'docker-compose up -d'.
. Después de realizar los cambios, ejecuta `docker-compose up -d` nuevamente. Puedes ver la lista completa de variables de entorno [aquí](https://docs.dify.ai/getting-started/install-self-hosted/environments).
## Hoja de ruta
Si desea configurar una configuración de alta disponibilidad, la comunidad proporciona [Gráficos Helm](https://helm.sh/) y archivos YAML, a través de los cuales puede desplegar Dify en Kubernetes.
Funciones en desarrollo:
- [Gráfico Helm por @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [Gráfico Helm por @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [Ficheros YAML por @Winson-030](https://github.com/Winson-030/dify-kubernetes)
- **Conjuntos de datos**, admitiendo más conjuntos de datos, por ejemplo, sincronización de contenido desde Notion o páginas web.
Admitiremos más conjuntos de datos, incluidos texto, páginas web e incluso contenido de Notion. Los usuarios pueden construir aplicaciones de IA basadas en sus propias fuentes de datos
- **Complementos**, introduciendo complementos estándar de ChatGPT para aplicaciones, o utilizando complementos producidos por Dify.
Lanzaremos complementos que cumplan con el estándar de ChatGPT, o nuestros propios complementos de Dify para habilitar más capacidades en las aplicaciones.
- **Modelos de código abierto**, por ejemplo, adoptar Llama como proveedor de modelos o para un ajuste adicional.
Trabajaremos con excelentes modelos de código abierto como Llama, proporcionándolos como opciones de modelos en nuestra plataforma o utilizándolos para un ajuste adicional.
#### Uso de Terraform para el despliegue
## Preguntas y respuestas
##### Azure Global
Utiliza [terraform](https://www.terraform.io/) para desplegar Dify en Azure con un solo clic.
- [Azure Terraform por @nikawang](https://github.com/nikawang/dify-azure-terraform)
**P: ¿Qué puedo hacer con Dify?**
R: Dify es una herramienta de desarrollo y operaciones de LLM, simple pero poderosa. Puedes usarla para construir aplicaciones de calidad comercial y asistentes personales. Si deseas desarrollar tus propias aplicaciones, LangDifyGenius puede ahorrarte trabajo en el backend al integrar con OpenAI y ofrecer capacidades de operaciones visuales, lo que te permite mejorar y entrenar continuamente tu modelo GPT.
## Contribuir
**P: ¿Cómo uso Dify para "entrenar" mi propio modelo?**
Para aquellos que deseen contribuir con código, consulten nuestra [Guía de contribución](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
Al mismo tiempo, considera apoyar a Dify compartiéndolo en redes sociales y en eventos y conferencias.
R: Una aplicación valiosa consta de Ingeniería de indicaciones, mejora de contexto y ajuste fino. Hemos creado un enfoque de programación híbrida que combina las indicaciones con lenguajes de programación (similar a un motor de plantillas), lo que facilita la incorporación de texto largo o la captura de subtítulos de un video de YouTube ingresado por el usuario, todo lo cual se enviará como contexto para que los LLM lo procesen. Damos gran importancia a la operabilidad de la aplicación, con los datos generados por los usuarios durante el uso de la aplicación disponibles para análisis, anotación y entrenamiento continuo. Sin las herramientas adecuadas, estos pasos pueden llevar mucho tiempo.
**P: ¿Qué necesito preparar si quiero crear mi propia aplicación?**
> Estamos buscando colaboradores para ayudar con la traducción de Dify a idiomas que no sean el mandarín o el inglés. Si estás interesado en ayudar, consulta el [README de i18n](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) para obtener más información y déjanos un comentario en el canal `global-users` de nuestro [Servidor de Comunidad en Discord](https://discord.gg/8Tpq4AcN9c).
R: Suponemos que ya tienes una clave de API de OpenAI; si no la tienes, por favor regístrate. ¡Si ya tienes contenido que pueda servir como contexto de entrenamiento, eso es genial!
**Contribuidores**
**P: ¿Qué idiomas de interfaz están disponibles?**
R: Actualmente se admiten inglés y chino, y puedes contribuir con paquetes de idiomas.
## Comunidad y Contacto
## Historial de estrellas
* [Discusión en GitHub](https://github.com/langgenius/dify/discussions). Lo mejor para: compartir comentarios y hacer preguntas.
* [Reporte de problemas en GitHub](https://github.com/langgenius/dify/issues). Lo mejor para: errores que encuentres usando Dify.AI y propuestas de características. Consulta nuestra [Guía de contribución](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
* [Discord](https://discord.gg/FngNHpbcY7). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.
* [Twitter](https://twitter.com/dify_ai). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.
[](https://star-history.com/#langgenius/dify&Date)
## Historial de Estrellas
## Contáctanos
[](https://star-history.com/#langgenius/dify&Date)
Si tienes alguna pregunta, sugerencia o consulta sobre asociación, no dudes en contactarnos a través de los siguientes canales:
- Presentar un problema o una solicitud de extracción en nuestro repositorio de GitHub.
- Únete a la discusión en nuestra comunidad de [Discord](https://discord.gg/FngNHpbcY7).
- Envía un correo electrónico a hello@dify.ai.
¡Estamos ansiosos por ayudarte y crear juntos aplicaciones de IA más divertidas y útiles!
## Contribuciones
Para garantizar una revisión adecuada, todas las contribuciones de código, incluidas las de los colaboradores con acceso directo a los compromisos, deben enviarse mediante solicitudes de extracción y ser aprobadas por el equipo principal de
desarrollo antes de fusionarse.
¡Agradecemos todas las solicitudes de extracción! Si deseas ayudar, consulta la [Guía de Contribución](CONTRIBUTING.md) para obtener más información sobre cómo comenzar.
## Seguridad
## Divulgación de Seguridad
Para proteger tu privacidad, evita publicar problemas de seguridad en GitHub. En su lugar, envía tus preguntas a security@dify.ai y te proporcionaremos una respuesta más detallada.
## Citación
Este software utiliza el siguiente software de código abierto:
- Chase, H. (2022). LangChain [Software de computadora]. https://github.com/hwchase17/langchain
Para obtener más información, consulta el sitio web oficial o el texto de la licencia del software correspondiente.
## Licencia
Este repositorio está disponible bajo la [Licencia de código abierto de Dify](LICENSE).
Este repositorio está disponible bajo la [Licencia de Código Abierto de Dify](LICENSE), que es esencialmente Apache 2.0 con algunas restricciones adicionales.
<img alt="Commits le mois dernier" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
Dify est une plateforme de développement d'applications LLM open source. Son interface intuitive combine un flux de travail d'IA, un pipeline RAG, des capacités d'agent, une gestion de modèles, des fonctionnalités d'observabilité, et plus encore, vous permettant de passer rapidement du prototype à la production. Voici une liste des fonctionnalités principales:
</br> </br>
**1. Flux de travail**:
Construisez et testez des flux de travail d'IA puissants sur un canevas visuel, en utilisant toutes les fonctionnalités suivantes et plus encore.
Intégration transparente avec des centaines de LLM propriétaires / open source provenant de dizaines de fournisseurs d'inférence et de solutions auto-hébergées, couvrant GPT, Mistral, Llama3, et tous les modèles compatibles avec l'API OpenAI. Une liste complète des fournisseurs de modèles pris en charge se trouve [ici](https://docs.dify.ai/getting-started/readme/model-providers).
Interface intuitive pour créer des prompts, comparer les performances des modèles et ajouter des fonctionnalités supplémentaires telles que la synthèse vocale à une application basée sur des chats.
**4. Pipeline RAG**:
Des capacités RAG étendues qui couvrent tout, de l'ingestion de documents à la récupération, avec un support prêt à l'emploi pour l'extraction de texte à partir de PDF, PPT et autres formats de document courants.
**5. Capac
ités d'agent**:
Vous pouvez définir des agents basés sur l'appel de fonction LLM ou ReAct, et ajouter des outils pré-construits ou personnalisés pour l'agent. Dify fournit plus de 50 outils intégrés pour les agents d'IA, tels que la recherche Google, DALL·E, Stable Diffusion et WolframAlpha.
**6. LLMOps**:
Surveillez et analysez les journaux d'application et les performances au fil du temps. Vous pouvez continuellement améliorer les prompts, les ensembles de données et les modèles en fonction des données de production et des annotations.
**7. Backend-as-a-Service**:
Toutes les offres de Dify sont accompagnées d'API correspondantes, vous permettant d'intégrer facilement Dify dans votre propre logique métier.
Nous hébergeons un service [Dify Cloud](https://dify.ai) pour que tout le monde puisse l'essayer sans aucune configuration. Il fournit toutes les capacités de la version auto-hébergée et comprend 200 appels GPT-4 gratuits dans le plan bac à sable.
- **Auto-hébergement Dify Community Edition</br>**
Lancez rapidement Dify dans votre environnement avec ce [guide de démarrage](#quick-start).
Utilisez notre [documentation](https://docs.dify.ai) pour plus de références et des instructions plus détaillées.
- **Dify pour les entreprises / organisations</br>**
Nous proposons des fonctionnalités supplémentaires adaptées aux entreprises. [Envoyez-nous un e-mail](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) pour discuter des besoins de l'entreprise. </br>
> Pour les startups et les petites entreprises utilisant AWS, consultez [Dify Premium sur AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) et déployez-le dans votre propre VPC AWS en un clic. C'est une offre AMI abordable avec la possibilité de créer des applications avec un logo et une marque personnalisés.
## Rester en avance
Mettez une étoile à Dify sur GitHub et soyez instantanément informé des nouvelles versions.
> Avant d'installer Dify, assurez-vous que votre machine répond aux exigences système minimales suivantes:
>
>- CPU >= 2 cœurs
>- RAM >= 4 Go
</br>
La manière la plus simple de démarrer le serveur Dify est d'exécuter notre fichier [docker-compose.yml](docker/docker-compose.yaml). Avant d'exécuter la commande d'installation, assurez-vous que [Docker](https://docs.docker.com/get-docker/) et [Docker Compose](https://docs.docker.com/compose/install/) sont installés sur votre machine:
```bash
cd docker
cp .env.example .env
docker compose up -d
```
Après l'exécution, vous pouvez accéder au tableau de bord Dify dans votre navigateur à [http://localhost/install](http://localhost/install) et commencer le processus d'initialisation.
> Si vous souhaitez contribuer à Dify ou effectuer un développement supplémentaire, consultez notre [guide de déploiement à partir du code source](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
## Prochaines étapes
Si vous devez personnaliser la configuration, veuillez vous référer aux commentaires dans notre fichier [.env.example](docker/.env.example) et mettre à jour les valeurs correspondantes dans votre fichier `.env`. De plus, vous devrez peut-être apporter des modifications au fichier `docker-compose.yaml` lui-même, comme changer les versions d'image, les mappages de ports ou les montages de volumes, en fonction de votre environnement de déploiement et de vos exigences spécifiques. Après avoir effectué des modifications, veuillez réexécuter `docker-compose up -d`. Vous pouvez trouver la liste complète des variables d'environnement disponibles [ici](https://docs.dify.ai/getting-started/install-self-hosted/environments).
Si vous souhaitez configurer une configuration haute disponibilité, la communauté fournit des [Helm Charts](https://helm.sh/) et des fichiers YAML, à travers lesquels vous pouvez déployer Dify sur Kubernetes.
- [Helm Chart par @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [Helm Chart par @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [Fichier YAML par @Winson-030](https://github.com/Winson-030/dify-kubernetes)
#### Utilisation de Terraform pour le déploiement
##### Azure Global
Utilisez [terraform](https://www.terraform.io/) pour déployer Dify sur Azure en un clic.
- [Azure Terraform par @nikawang](https://github.com/nikawang/dify-azure-terraform)
## Contribuer
Pour ceux qui souhaitent contribuer du code, consultez notre [Guide de contribution](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
Dans le même temps, veuillez envisager de soutenir Dify en le partageant sur les réseaux sociaux et lors d'événements et de conférences.
> Nous recherchons des contributeurs pour aider à traduire Dify dans des langues autres que le mandarin ou l'anglais. Si vous êtes intéressé à aider, veuillez consulter le [README i18n](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) pour plus d'informations, et laissez-nous un commentaire dans le canal `global-users` de notre [Serveur communautaire Discord](https://discord.gg/8Tpq4AcN9c).
* [Discussion GitHub](https://github.com/langgenius/dify/discussions). Meilleur pour: partager des commentaires et poser des questions.
* [Problèmes GitHub](https://github.com/langgenius/dify/issues). Meilleur pour: les bogues que vous rencontrez en utilisant Dify.AI et les propositions de fonctionnalités. Consultez notre [Guide de contribution](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
* [Discord](https://discord.gg/FngNHpbcY7). Meilleur pour: partager vos applications et passer du temps avec la communauté.
* [Twitter](https://twitter.com/dify_ai). Meilleur pour: partager vos applications et passer du temps avec la communauté.
## Historique des étoiles
[](https://star-history.com/#langgenius/dify&Date)
## Divulgation de sécurité
Pour protéger votre vie privée, veuillez éviter de publier des problèmes de sécurité sur GitHub. Au lieu de cela, envoyez vos questions à security@dify.ai et nous vous fournirons une réponse plus détaillée.
## Licence
Ce référentiel est disponible sous la [Licence open source Dify](LICENSE), qui est essentiellement l'Apache 2.0 avec quelques restrictions supplémentaires.
**Dify** は、より多くの人々が持続可能な AI ネイティブアプリケーションを作成できるように設計された、使いやすい LLMOps プラットフォームです。様々なアプリケーションタイプに対応したビジュアルオーケストレーションにより Dify は Backend-as-a-Service API としても機能する、すぐに使えるアプリケーションを提供します。プラグインやデータセットを統合するための1つの API で開発プロセスを統一し、プロンプトエンジニアリング、ビジュアル分析、継続的な改善のための1つのインターフェイスを使って業務を合理化します。
LLM Function CallingやReActに基づくエージェントの定義が可能で、AIエージェント用のプリビルトまたはカスタムツールを追加できます。Difyには、Google検索、DALL·E、Stable Diffusion、WolframAlphaなどのAIエージェント用の50以上の組み込みツールが提供します。
Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production. Here's a list of the core features:
</br> </br>
**1. Workflow**:
Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.
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).
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.
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.
- **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=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
> For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) 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.
## Staying ahead
Star Dify on GitHub and be instantly notified of new releases.
> Before installing Dify, make sure your machine meets the following minimum system requirements:
>
>- CPU >= 2 Core
>- RAM >= 4GB
</br>
The easiest way to start the Dify server is to run our [docker-compose.yml](docker/docker-compose.yaml) file. Before running the installation command, 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 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.
> 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)
## Next steps
If you need to customize the configuration, please refer to the comments in our [.env.example](docker/.env.example) file and update the corresponding values in your `.env` file. Additionally, you might need to make adjustments to the `docker-compose.yaml` file itself, such as changing image versions, port mappings, or volume mounts, based on your specific deployment environment and requirements. After making any changes, please re-run `docker-compose up -d`. You can find the full list of available environment variables [here](https://docs.dify.ai/getting-started/install-self-hosted/environments).
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)
- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
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 with translating Dify to 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/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c).
). 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.
* [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
## Star History
[](https://star-history.com/#langgenius/dify&Date)
## Security Disclosure
To protect your privacy, please avoid posting security issues on GitHub. Instead, send your questions to security@dify.ai and we will provide you with a more detailed answer.
## License
This repository is available under the [Dify Open Source License](LICENSE), which is essentially Apache 2.0 with a few additional restrictions.
<a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
</p>
Dify는 오픈 소스 LLM 앱 개발 플랫폼입니다. 직관적인 인터페이스를 통해 AI 워크플로우, RAG 파이프라인, 에이전트 기능, 모델 관리, 관찰 기능 등을 결합하여 프로토타입에서 프로덕션까지 빠르게 전환할 수 있습니다. 주요 기능 목록은 다음과 같습니다:</br> </br>
**1. 워크플로우**:
다음 기능들을 비롯한 다양한 기능을 활용하여 시각적 캔버스에서 강력한 AI 워크플로우를 구축하고 테스트하세요.
수십 개의 추론 제공업체와 자체 호스팅 솔루션에서 제공하는 수백 개의 독점 및 오픈 소스 LLM과 원활하게 통합되며, GPT, Mistral, Llama3 및 모든 OpenAI API 호환 모델을 포함합니다. 지원되는 모델 제공업체의 전체 목록은 [여기](https://docs.dify.ai/getting-started/readme/model-providers)에서 확인할 수 있습니다.
프롬프트를 작성하고, 모델 성능을 비교하며, 텍스트-음성 변환과 같은 추가 기능을 채팅 기반 앱에 추가할 수 있는 직관적인 인터페이스를 제공합니다.
**4. RAG 파이프라인**:
문서 수집부터 검색까지 모든 것을 다루며, PDF, PPT 및 기타 일반적인 문서 형식에서 텍스트 추출을 위한 기본 지원이 포함되어 있는 광범위한 RAG 기능을 제공합니다.
**5. 에이전트 기능**:
LLM 함수 호출 또는 ReAct를 기반으로 에이전트를 정의하고 에이전트에 대해 사전 구축된 도구나 사용자 정의 도구를 추가할 수 있습니다. Dify는 Google Search, DALL·E, Stable Diffusion, WolframAlpha 등 AI 에이전트를 위한 50개 이상의 내장 도구를 제공합니다.
**6. LLMOps**:
시간 경과에 따른 애플리케이션 로그와 성능을 모니터링하고 분석합니다. 생산 데이터와 주석을 기반으로 프롬프트, 데이터세트, 모델을 지속적으로 개선할 수 있습니다.
**7. Backend-as-a-Service**:
Dify의 모든 제품에는 해당 API가 함께 제공되므로 Dify를 자신의 비즈니스 로직에 쉽게 통합할 수 있습니다.
## 기능 비교
<table style="width: 100%;">
<tr>
<th align="center">기능</th>
<th align="center">Dify.AI</th>
<th align="center">LangChain</th>
<th align="center">Flowise</th>
<th align="center">OpenAI Assistants API</th>
</tr>
<tr>
<td align="center">프로그래밍 접근 방식</td>
<td align="center">API + 앱 중심</td>
<td align="center">Python 코드</td>
<td align="center">앱 중심</td>
<td align="center">API 중심</td>
</tr>
<tr>
<td align="center">지원되는 LLMs</td>
<td align="center">다양한 종류</td>
<td align="center">다양한 종류</td>
<td align="center">다양한 종류</td>
<td align="center">OpenAI 전용</td>
</tr>
<tr>
<td align="center">RAG 엔진</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">에이전트</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">워크플로우</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">가시성</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">기업용 기능 (SSO/접근 제어)</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">로컬 배포</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
</table>
## Dify 사용하기
- **클라우드 </br>**
우리는 누구나 설정이 필요 없이 사용해 볼 수 있도록 [Dify 클라우드](https://dify.ai) 서비스를 호스팅합니다. 이는 자체 배포 버전의 모든 기능을 제공하며, 샌드박스 플랜에서 무료로 200회의 GPT-4 호출을 포함합니다.
- **셀프-호스팅 Dify 커뮤니티 에디션</br>**
환경에서 Dify를 빠르게 실행하려면 이 [스타터 가이드를](#quick-start) 참조하세요.
추가 참조 및 더 심층적인 지침은 [문서](https://docs.dify.ai)를 사용하세요.
- **기업 / 조직을 위한 Dify</br>**
우리는 추가적인 기업 중심 기능을 제공합니다. 잡거나 [이메일 보내기](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)를 통해 기업 요구 사항을 논의하십시오. </br>
> AWS를 사용하는 스타트업 및 중소기업의 경우 [AWS Marketplace에서 Dify Premium](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6)을 확인하고 한 번의 클릭으로 자체 AWS VPC에 배포하십시오. 맞춤형 로고와 브랜딩이 포함된 앱을 생성할 수 있는 옵션이 포함된 저렴한 AMI 제품입니다.
>Dify를 설치하기 전에 컴퓨터가 다음과 같은 최소 시스템 요구 사항을 충족하는지 확인하세요 :
>- CPU >= 2 Core
>- RAM >= 4GB
</br>
Dify 서버를 시작하는 가장 쉬운 방법은 [docker-compose.yml](docker/docker-compose.yaml) 파일을 실행하는 것입니다. 설치 명령을 실행하기 전에 [Docker](https://docs.docker.com/get-docker/) 및 [Docker Compose](https://docs.docker.com/compose/install/)가 머신에 설치되어 있는지 확인하세요.
```bash
cd docker
cp .env.example .env
docker compose up -d
```
실행 후 브라우저의 [http://localhost/install](http://localhost/install) 에서 Dify 대시보드에 액세스하고 초기화 프로세스를 시작할 수 있습니다.
> Dify에 기여하거나 추가 개발을 하고 싶다면 소스 코드에서 [배포에 대한 가이드](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)를 참조하세요.
## 다음 단계
구성을 사용자 정의해야 하는 경우 [.env.example](docker/.env.example) 파일의 주석을 참조하고 `.env` 파일에서 해당 값을 업데이트하십시오. 또한 특정 배포 환경 및 요구 사항에 따라 `docker-compose.yaml` 파일 자체를 조정해야 할 수도 있습니다. 예를 들어 이미지 버전, 포트 매핑 또는 볼륨 마운트를 변경합니다. 변경 한 후 `docker-compose up -d`를 다시 실행하십시오. 사용 가능한 환경 변수의 전체 목록은 [여기](https://docs.dify.ai/getting-started/install-self-hosted/environments)에서 찾을 수 있습니다.
Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했다는 커뮤니티가 제공하는 [Helm Charts](https://helm.sh/)와 YAML 파일이 존재합니다.
- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
#### Terraform을 사용한 배포
##### Azure Global
[terraform](https://www.terraform.io/)을 사용하여 Azure에 Dify를 원클릭으로 배포하세요.
코드에 기여하고 싶은 분들은 [기여 가이드](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)를 참조하세요.
동시에 Dify를 소셜 미디어와 행사 및 컨퍼런스에 공유하여 지원하는 것을 고려해 주시기 바랍니다.
> 우리는 Dify를 중국어나 영어 이외의 언어로 번역하는 데 도움을 줄 수 있는 기여자를 찾고 있습니다. 도움을 주고 싶으시다면 [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md)에서 더 많은 정보를 확인하시고 [Discord 커뮤니티 서버](https://discord.gg/8Tpq4AcN9c)의 `global-users` 채널에 댓글을 남겨주세요.
* [Github 토론](https://github.com/langgenius/dify/discussions). 피드백 공유 및 질문하기에 적합합니다.
* [GitHub 이슈](https://github.com/langgenius/dify/issues). Dify.AI 사용 중 발견한 버그와 기능 제안에 적합합니다. [기여 가이드](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)를 참조하세요.
* [디스코드](https://discord.gg/FngNHpbcY7). 애플리케이션 공유 및 커뮤니티와 소통하기에 적합합니다.
* [트위터](https://twitter.com/dify_ai). 애플리케이션 공유 및 커뮤니티와 소통하기에 적합합니다.
## Star 히스토리
[](https://star-history.com/#langgenius/dify&Date)
## 보안 공개
개인정보 보호를 위해 보안 문제를 GitHub에 게시하지 마십시오. 대신 security@dify.ai로 질문을 보내주시면 더 자세한 답변을 드리겠습니다.
## 라이선스
이 저장소는 기본적으로 몇 가지 추가 제한 사항이 있는 Apache 2.0인 [Dify 오픈 소스 라이선스](LICENSE)에 따라 사용할 수 있습니다.
<img alt="Geçen ay yapılan commitler" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
<a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
</p>
Dify, açık kaynaklı bir LLM uygulama geliştirme platformudur. Sezgisel arayüzü, AI iş akışı, RAG pipeline'ı, ajan yetenekleri, model yönetimi, gözlemlenebilirlik özellikleri ve daha fazlasını birleştirerek, prototipten üretime hızlıca geçmenizi sağlar. İşte temel özelliklerin bir listesi:
</br> </br>
**1. Workflow**:
Görsel bir arayüz üzerinde güçlü AI iş akışları oluşturun ve test edin, aşağıdaki tüm özellikleri ve daha fazlasını kullanarak.
Çok sayıda çıkarım sağlayıcısı ve kendi kendine barındırılan çözümlerden yüzlerce özel / açık kaynaklı LLM ile sorunsuz entegrasyon sağlar. GPT, Mistral, Llama3 ve OpenAI API uyumlu tüm modelleri kapsar. Desteklenen model sağlayıcılarının tam listesine [buradan](https://docs.dify.ai/getting-started/readme/model-providers) ulaşabilirsiniz.
Özür dilerim, haklısınız. Daha anlamlı ve akıcı bir çeviri yapmaya çalışayım. İşte güncellenmiş çeviri:
**3. Prompt IDE**:
Komut istemlerini oluşturmak, model performansını karşılaştırmak ve sohbet tabanlı uygulamalara metin-konuşma gibi ek özellikler eklemek için kullanıcı dostu bir arayüz.
**4. RAG Pipeline**:
Belge alımından bilgi çekmeye kadar geniş kapsamlı RAG yetenekleri. PDF'ler, PPT'ler ve diğer yaygın belge formatlarından metin çıkarma için hazır destek sunar.
**5. Ajan yetenekleri**:
LLM Fonksiyon Çağırma veya ReAct'a dayalı ajanlar tanımlayabilir ve bu ajanlara önceden hazırlanmış veya özel araçlar ekleyebilirsiniz. Dify, AI ajanları için Google Arama, DALL·E, Stable Diffusion ve WolframAlpha gibi 50'den fazla yerleşik araç sağlar.
**6. LLMOps**:
Uygulama loglarını ve performans metriklerini zaman içinde izleme ve analiz etme imkanı. Üretim ortamından elde edilen verilere ve kullanıcı geri bildirimlerine dayanarak, prompt'ları, veri setlerini ve modelleri sürekli olarak optimize edebilirsiniz. Bu sayede, AI uygulamanızın performansını ve doğruluğunu sürekli olarak artırabilirsiniz.
**7. Hizmet Olarak Backend**:
Dify'ın tüm özellikleri ilgili API'lerle birlikte gelir, böylece Dify'ı kendi iş mantığınıza kolayca entegre edebilirsiniz.
## Özellik karşılaştırması
<table style="width: 100%;">
<tr>
<th align="center">Özellik</th>
<th align="center">Dify.AI</th>
<th align="center">LangChain</th>
<th align="center">Flowise</th>
<th align="center">OpenAI Assistants API</th>
</tr>
<tr>
<td align="center">Programlama Yaklaşımı</td>
<td align="center">API + Uygulama odaklı</td>
<td align="center">Python Kodu</td>
<td align="center">Uygulama odaklı</td>
<td align="center">API odaklı</td>
</tr>
<tr>
<td align="center">Desteklenen LLM'ler</td>
<td align="center">Zengin Çeşitlilik</td>
<td align="center">Zengin Çeşitlilik</td>
<td align="center">Zengin Çeşitlilik</td>
<td align="center">Yalnızca OpenAI</td>
</tr>
<tr>
<td align="center">RAG Motoru</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Ajan</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">İş Akışı</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Gözlemlenebilirlik</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Kurumsal Özellikler (SSO/Erişim kontrolü)</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Yerel Dağıtım</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
</table>
## Dify'ı Kullanma
- **Cloud </br>**
İşte verdiğiniz metnin Türkçe çevirisi, kod bloğu içinde:
-
Herkesin sıfır kurulumla denemesi için bir [Dify Cloud](https://dify.ai) hizmeti sunuyoruz. Bu hizmet, kendi kendine dağıtılan versiyonun tüm yeteneklerini sağlar ve sandbox planında 200 ücretsiz GPT-4 çağrısı içerir.
- **Dify Topluluk Sürümünü Kendi Sunucunuzda Barındırma</br>**
Bu [başlangıç kılavuzu](#quick-start) ile Dify'ı kendi ortamınızda hızlıca çalıştırın.
Daha fazla referans ve detaylı talimatlar için [dokümantasyonumuzu](https://docs.dify.ai) kullanın.
- **Kurumlar / organizasyonlar için Dify</br>**
Ek kurumsal odaklı özellikler sunuyoruz. Kurumsal ihtiyaçları görüşmek için [bize bir e-posta gönderin](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry). </br>
> AWS kullanan startuplar ve küçük işletmeler için, [AWS Marketplace'deki Dify Premium'a](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) göz atın ve tek tıklamayla kendi AWS VPC'nize dağıtın. Bu, özel logo ve marka ile uygulamalar oluşturma seçeneğine sahip uygun fiyatlı bir AMI teklifdir.
## Güncel Kalma
GitHub'da Dify'a yıldız verin ve yeni sürümlerden anında haberdar olun.
> Dify'ı kurmadan önce, makinenizin aşağıdaki minimum sistem gereksinimlerini karşıladığından emin olun:
>
>- CPU >= 2 Çekirdek
>- RAM >= 4GB
</br>
İşte verdiğiniz metnin Türkçe çevirisi, kod bloğu içinde:
Dify sunucusunu başlatmanın en kolay yolu, [docker-compose.yml](docker/docker-compose.yaml) dosyamızı çalıştırmaktır. Kurulum komutunu çalıştırmadan önce, makinenizde [Docker](https://docs.docker.com/get-docker/) ve [Docker Compose](https://docs.docker.com/compose/install/)'un kurulu olduğundan emin olun:
```bash
cd docker
cp .env.example .env
docker compose up -d
```
Çalıştırdıktan sonra, tarayıcınızda [http://localhost/install](http://localhost/install) adresinden Dify kontrol paneline erişebilir ve başlangıç ayarları sürecini başlatabilirsiniz.
> Eğer Dify'a katkıda bulunmak veya ek geliştirmeler yapmak isterseniz, [kaynak koddan dağıtım kılavuzumuza](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code) başvurun.
## Sonraki adımlar
Yapılandırmayı özelleştirmeniz gerekiyorsa, lütfen [.env.example](docker/.env.example) dosyamızdaki yorumlara bakın ve `.env` dosyanızdaki ilgili değerleri güncelleyin. Ayrıca, spesifik dağıtım ortamınıza ve gereksinimlerinize bağlı olarak `docker-compose.yaml` dosyasının kendisinde de, imaj sürümlerini, port eşlemelerini veya hacim bağlantılarını değiştirmek gibi ayarlamalar yapmanız gerekebilir. Herhangi bir değişiklik yaptıktan sonra, lütfen `docker-compose up -d` komutunu tekrar çalıştırın. Kullanılabilir tüm ortam değişkenlerinin tam listesini [burada](https://docs.dify.ai/getting-started/install-self-hosted/environments) bulabilirsiniz.
Yüksek kullanılabilirliğe sahip bir kurulum yapılandırmak isterseniz, Dify'ın Kubernetes üzerine dağıtılmasına olanak tanıyan topluluk katkılı [Helm Charts](https://helm.sh/) ve YAML dosyaları mevcuttur.
- [@LeoQuote tarafından Helm Chart](https://github.com/douban/charts/tree/master/charts/dify)
- [@BorisPolonsky tarafından Helm Chart](https://github.com/BorisPolonsky/dify-helm)
- [@Winson-030 tarafından YAML dosyası](https://github.com/Winson-030/dify-kubernetes)
#### Dağıtım için Terraform Kullanımı
##### Azure Global
[Terraform](https://www.terraform.io/) kullanarak Dify'ı Azure'a tek tıklamayla dağıtın.
- [@nikawang tarafından Azure Terraform](https://github.com/nikawang/dify-azure-terraform)
## Katkıda Bulunma
Kod katkısında bulunmak isteyenler için [Katkı Kılavuzumuza](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) bakabilirsiniz.
Aynı zamanda, lütfen Dify'ı sosyal medyada, etkinliklerde ve konferanslarda paylaşarak desteklemeyi düşünün.
> Dify'ı Mandarin veya İngilizce dışındaki dillere çevirmemize yardımcı olacak katkıda bulunanlara ihtiyacımız var. Yardımcı olmakla ilgileniyorsanız, lütfen daha fazla bilgi için [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) dosyasına bakın ve [Discord Topluluk Sunucumuzdaki](https://discord.gg/8Tpq4AcN9c) `global-users` kanalında bize bir yorum bırakın.
* [Github Tartışmaları](https://github.com/langgenius/dify/discussions). En uygun: geri bildirim paylaşmak ve soru sormak için.
* [GitHub Sorunları](https://github.com/langgenius/dify/issues). En uygun: Dify.AI kullanırken karşılaştığınız hatalar ve özellik önerileri için. [Katkı Kılavuzumuza](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) bakın.
* [Discord](https://discord.gg/FngNHpbcY7). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
* [Twitter](https://twitter.com/dify_ai). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
## Star history
[](https://star-history.com/#langgenius/dify&Date)
## Güvenlik açıklaması
Gizliliğinizi korumak için, lütfen güvenlik sorunlarını GitHub'da paylaşmaktan kaçının. Bunun yerine, sorularınızı security@dify.ai adresine gönderin ve size daha detaylı bir cevap vereceğiz.
## Lisans
Bu depo, temel olarak Apache 2.0 lisansı ve birkaç ek kısıtlama içeren [Dify Açık Kaynak Lisansı](LICENSE) altında kullanıma sunulmuştur.
<img alt="Vấn đề đã đóng" 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="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
</p>
Dify là một nền tảng phát triển ứng dụng LLM mã nguồn mở. Giao diện trực quan kết hợp quy trình làm việc AI, mô hình RAG, khả năng tác nhân, quản lý mô hình, tính năng quan sát và hơn thế nữa, cho phép bạn nhanh chóng chuyển từ nguyên mẫu sang sản phẩm. Đây là danh sách các tính năng cốt lõi:
</br> </br>
**1. Quy trình làm việc**:
Xây dựng và kiểm tra các quy trình làm việc AI mạnh mẽ trên một canvas trực quan, tận dụng tất cả các tính năng sau đây và hơn thế nữa.
Tích hợp liền mạch với hàng trăm mô hình LLM độc quyền / mã nguồn mở từ hàng chục nhà cung cấp suy luận và giải pháp tự lưu trữ, bao gồm GPT, Mistral, Llama3, và bất kỳ mô hình tương thích API OpenAI nào. Danh sách đầy đủ các nhà cung cấp mô hình được hỗ trợ có thể được tìm thấy [tại đây](https://docs.dify.ai/getting-started/readme/model-providers).
Giao diện trực quan để tạo prompt, so sánh hiệu suất mô hình và thêm các tính năng bổ sung như chuyển văn bản thành giọng nói cho một ứng dụng dựa trên trò chuyện.
**4. Mô hình RAG**:
Khả năng RAG mở rộng bao gồm mọi thứ từ nhập tài liệu đến truy xuất, với hỗ trợ sẵn có cho việc trích xuất văn bản từ PDF, PPT và các định dạng tài liệu phổ biến khác.
**5. Khả năng tác nhân**:
Bạn có thể định nghĩa các tác nhân dựa trên LLM Function Calling hoặc ReAct, và thêm các công cụ được xây dựng sẵn hoặc tùy chỉnh cho tác nhân. Dify cung cấp hơn 50 công cụ tích hợp sẵn cho các tác nhân AI, như Google Search, DALL·E, Stable Diffusion và WolframAlpha.
**6. LLMOps**:
Giám sát và phân tích nhật ký và hiệu suất ứng dụng theo thời gian. Bạn có thể liên tục cải thiện prompt, bộ dữ liệu và mô hình dựa trên dữ liệu sản xuất và chú thích.
**7. Backend-as-a-Service**:
Tất cả các dịch vụ của Dify đều đi kèm với các API tương ứng, vì vậy bạn có thể dễ dàng tích hợp Dify vào logic kinh doanh của riêng mình.
## So sánh tính năng
<table style="width: 100%;">
<tr>
<th align="center">Tính năng</th>
<th align="center">Dify.AI</th>
<th align="center">LangChain</th>
<th align="center">Flowise</th>
<th align="center">OpenAI Assistants API</th>
</tr>
<tr>
<td align="center">Phương pháp lập trình</td>
<td align="center">Hướng API + Ứng dụng</td>
<td align="center">Mã Python</td>
<td align="center">Hướng ứng dụng</td>
<td align="center">Hướng API</td>
</tr>
<tr>
<td align="center">LLMs được hỗ trợ</td>
<td align="center">Đa dạng phong phú</td>
<td align="center">Đa dạng phong phú</td>
<td align="center">Đa dạng phong phú</td>
<td align="center">Chỉ OpenAI</td>
</tr>
<tr>
<td align="center">RAG Engine</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Agent</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
</tr>
<tr>
<td align="center">Quy trình làm việc</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Khả năng quan sát</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Tính năng doanh nghiệp (SSO/Kiểm soát truy cập)</td>
<td align="center">✅</td>
<td align="center">❌</td>
<td align="center">❌</td>
<td align="center">❌</td>
</tr>
<tr>
<td align="center">Triển khai cục bộ</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">❌</td>
</tr>
</table>
## Sử dụng Dify
- **Cloud </br>**
Chúng tôi lưu trữ dịch vụ [Dify Cloud](https://dify.ai) cho bất kỳ ai muốn thử mà không cần cài đặt. Nó cung cấp tất cả các khả năng của phiên bản tự triển khai và bao gồm 200 lượt gọi GPT-4 miễn phí trong gói sandbox.
- **Tự triển khai Dify Community Edition</br>**
Nhanh chóng chạy Dify trong môi trường của bạn với [hướng dẫn bắt đầu](#quick-start) này.
Sử dụng [tài liệu](https://docs.dify.ai) của chúng tôi để tham khảo thêm và nhận hướng dẫn chi tiết hơn.
- **Dify cho doanh nghiệp / tổ chức</br>**
Chúng tôi cung cấp các tính năng bổ sung tập trung vào doanh nghiệp. [Ghi lại câu hỏi của bạn cho chúng tôi thông qua chatbot này](https://udify.app/chat/22L1zSxg6yW1cWQg) hoặc [gửi email cho chúng tôi](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) để thảo luận về nhu cầu doanh nghiệp. </br>
> Đối với các công ty khởi nghiệp và doanh nghiệp nhỏ sử dụng AWS, hãy xem [Dify Premium trên AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) và triển khai nó vào AWS VPC của riêng bạn chỉ với một cú nhấp chuột. Đây là một AMI giá cả phải chăng với tùy chọn tạo ứng dụng với logo và thương hiệu tùy chỉnh.
## Luôn cập nhật
Yêu thích Dify trên GitHub và được thông báo ngay lập tức về các bản phát hành mới.
> Trước khi cài đặt Dify, hãy đảm bảo máy của bạn đáp ứng các yêu cầu hệ thống tối thiểu sau:
>
>- CPU >= 2 Core
>- RAM >= 4GB
</br>
Cách dễ nhất để khởi động máy chủ Dify là chạy tệp [docker-compose.yml](docker/docker-compose.yaml) của chúng tôi. Trước khi chạy lệnh cài đặt, hãy đảm bảo rằng [Docker](https://docs.docker.com/get-docker/) và [Docker Compose](https://docs.docker.com/compose/install/) đã được cài đặt trên máy của bạn:
```bash
cd docker
cp .env.example .env
docker compose up -d
```
Sau khi chạy, bạn có thể truy cập bảng điều khiển Dify trong trình duyệt của bạn tại [http://localhost/install](http://localhost/install) và bắt đầu quá trình khởi tạo.
> Nếu bạn muốn đóng góp cho Dify hoặc phát triển thêm, hãy tham khảo [hướng dẫn triển khai từ mã nguồn](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code) của chúng tôi
## Các bước tiếp theo
Nếu bạn cần tùy chỉnh cấu hình, vui lòng tham khảo các nhận xét trong tệp [.env.example](docker/.env.example) của chúng tôi và cập nhật các giá trị tương ứng trong tệp `.env` của bạn. Ngoài ra, bạn có thể cần điều chỉnh tệp `docker-compose.yaml`, chẳng hạn như thay đổi phiên bản hình ảnh, ánh xạ cổng hoặc gắn kết khối lượng, dựa trên môi trường triển khai cụ thể và yêu cầu của bạn. Sau khi thực hiện bất kỳ thay đổi nào, vui lòng chạy lại `docker-compose up -d`. Bạn có thể tìm thấy danh sách đầy đủ các biến môi trường có sẵn [tại đây](https://docs.dify.ai/getting-started/install-self-hosted/environments).
Nếu bạn muốn cấu hình một cài đặt có độ sẵn sàng cao, có các [Helm Charts](https://helm.sh/) và tệp YAML do cộng đồng đóng góp cho phép Dify được triển khai trên Kubernetes.
- [Helm Chart bởi @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [Helm Chart bởi @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [Tệp YAML bởi @Winson-030](https://github.com/Winson-030/dify-kubernetes)
#### Sử dụng Terraform để Triển khai
##### Azure Global
Triển khai Dify lên Azure chỉ với một cú nhấp chuột bằng cách sử dụng [terraform](https://www.terraform.io/).
- [Azure Terraform bởi @nikawang](https://github.com/nikawang/dify-azure-terraform)
## Đóng góp
Đối với những người muốn đóng góp mã, xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi.
Đồng thời, vui lòng xem xét hỗ trợ Dify bằng cách chia sẻ nó trên mạng xã hội và tại các sự kiện và hội nghị.
> Chúng tôi đang tìm kiếm người đóng góp để giúp dịch Dify sang các ngôn ngữ khác ngoài tiếng Trung hoặc tiếng Anh. Nếu bạn quan tâm đến việc giúp đỡ, vui lòng xem [README i18n](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) để biết thêm thông tin và để lại bình luận cho chúng tôi trong kênh `global-users` của [Máy chủ Cộng đồng Discord](https://discord.gg/8Tpq4AcN9c) của chúng tôi.
* [Thảo luận GitHub](https://github.com/langgenius/dify/discussions). Tốt nhất cho: chia sẻ phản hồi và đặt câu hỏi.
* [Vấn đề GitHub](https://github.com/langgenius/dify/issues). Tốt nhất cho: lỗi bạn gặp phải khi sử dụng Dify.AI và đề xuất tính năng. Xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi.
* [Discord](https://discord.gg/FngNHpbcY7). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
* [Twitter](https://twitter.com/dify_ai). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
## Lịch sử Yêu thích
[](https://star-history.com/#langgenius/dify&Date)
## Tiết lộ bảo mật
Để bảo vệ quyền riêng tư của bạn, vui lòng tránh đăng các vấn đề bảo mật trên GitHub. Thay vào đó, hãy gửi câu hỏi của bạn đến security@dify.ai và chúng tôi sẽ cung cấp cho bạn câu trả lời chi tiết hơn.
## Giấy phép
Kho lưu trữ này có sẵn theo [Giấy phép Mã nguồn Mở Dify](LICENSE), về cơ bản là Apache 2.0 với một vài hạn chế bổ sung.
poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
```
7. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
8. If you need to debug local async processing, you can run `celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail`, celery can do dataset importing and other async tasks.
8. Start frontend
You can start the frontend by running `npm install && npm run dev` in web/ folder, or you can use docker to start the frontend, for example:
8. Start Dify [web](../web) service.
9. Setup your application by visiting `http://localhost:3000`...
10. If you need to debug local async processing, please start the worker service.
```bash
poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion
'description':'A multilingual translator that provides translation capabilities in multiple languages, translating user input into the language they need.',
'mode':'completion',
'model_config':AppModelConfig(
provider='openai',
model_id='gpt-3.5-turbo-instruct',
configs={
'prompt_template':"Please translate the following text into {{target_language}}:\n",
'prompt_variables':[
{
"key":"target_language",
"name":"Target Language",
"description":"The language you want to translate into.",
"type":"select",
"default":"Chinese",
'options':[
'Chinese',
'English',
'Japanese',
'French',
'Russian',
'German',
'Spanish',
'Korean',
'Italian',
]
}
],
'completion_params':{
'max_token':1000,
'temperature':0,
'top_p':0,
'presence_penalty':0.1,
'frequency_penalty':0.1,
}
},
opening_statement='',
suggested_questions=None,
pre_prompt="Please translate the following text into {{target_language}}:\n{{query}}\ntranslate:",
model=json.dumps({
"provider":"openai",
"name":"gpt-3.5-turbo-instruct",
"mode":"completion",
"completion_params":{
"max_tokens":1000,
"temperature":0,
"top_p":0,
"presence_penalty":0.1,
"frequency_penalty":0.1
}
}),
user_input_form=json.dumps([
"completion_params":{},
},
"user_input_form":json.dumps(
[
{
"select":{
"label":"Target Language",
"variable":"target_language",
"description":"The language you want to translate into.",
"default":"Chinese",
"required":True,
'options':[
'Chinese',
'English',
'Japanese',
'French',
'Russian',
'German',
'Spanish',
'Korean',
'Italian',
]
}
},{
"paragraph":{
"label":"Query",
"variable":"query",
"required":True,
"default":""
}
}
])
)
"default":"",
},
},
]
),
"pre_prompt":"{{query}}",
},
{
'name':'AI Front-end Interviewer',
'icon':'',
'icon_background':'',
'description':'A simulated front-end interviewer that tests the skill level of front-end development through questioning.',
'mode':'chat',
'model_config':AppModelConfig(
provider='openai',
model_id='gpt-3.5-turbo',
configs={
'introduction':'Hi, welcome to our interview. I am the interviewer for this technology company, and I will test your web front-end development skills. Next, I will ask you some technical questions. Please answer them as thoroughly as possible. ',
'prompt_template':"You will play the role of an interviewer for a technology company, examining the user's web front-end development skills and posing 5-10 sharp technical questions.\n\nPlease note:\n- Only ask one question at a time.\n- After the user answers a question, ask the next question directly, without trying to correct any mistakes made by the candidate.\n- If you think the user has not answered correctly for several consecutive questions, ask fewer questions.\n- After asking the last question, you can ask this question: Why did you leave your last job? After the user answers this question, please express your understanding and support.\n",
'prompt_variables':[],
'completion_params':{
'max_token':300,
'temperature':0.8,
'top_p':0.9,
'presence_penalty':0.1,
'frequency_penalty':0.1,
}
},
opening_statement='Hi, welcome to our interview. I am the interviewer for this technology company, and I will test your web front-end development skills. Next, I will ask you some technical questions. Please answer them as thoroughly as possible. ',
suggested_questions=None,
pre_prompt="You will play the role of an interviewer for a technology company, examining the user's web front-end development skills and posing 5-10 sharp technical questions.\n\nPlease note:\n- Only ask one question at a time.\n- After the user answers a question, ask the next question directly, without trying to correct any mistakes made by the candidate.\n- If you think the user has not answered correctly for several consecutive questions, ask fewer questions.\n- After asking the last question, you can ask this question: Why did you leave your last job? After the user answers this question, please express your understanding and support.\n",
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