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#### [Website](https://dify.ai) • [Docs](https://docs.dify.ai) • [Deployment Docs](https://docs.dify.ai/getting-started/install-self-hosted) • [FAQ](https://docs.dify.ai/getting-started/faq) • [Twitter](https://twitter.com/dify_ai) • [Discord](https://discord.gg/FngNHpbcY7)
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#### [Website](https://dify.ai) • [Docs](https://docs.dify.ai) • [Deployment Docs](https://docs.dify.ai/getting-started/install-self-hosted) • [FAQ](https://docs.dify.ai/getting-started/faq) • [Twitter](https://twitter.com/dify_ai) • [Discord](https://discord.gg/FngNHpbcY7)
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**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.
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**Dify** is an LLM application development platform that has already seen over 100,000 applications built on Dify.AI. It integrates the concepts of Backend as a Service and LLMOps, covering the core tech stack required for building generative AI-native applications, including a built-in RAG engine. With Dify, **you can self-deploy capabilities similar to Assistants API and GPTs based on any LLMs.**
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Applications created with Dify include:
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Out-of-the-box web sites supporting form mode and chat conversation mode
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A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort
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Visual data analysis, log review, and annotation for applications
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https://github.com/langgenius/dify/assets/100913391/f6e658d5-31b3-4c16-a0af-9e191da4d0f6
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https://github.com/langgenius/dify/assets/100913391/f6e658d5-31b3-4c16-a0af-9e191da4d0f6
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## Highlighted Features
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**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:
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- [x] **OpenAI**: GPT4, GPT3.5-turbo, GPT3.5-turbo-16k, text-davinci-003
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- [x] **Azure OpenAI Service**
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- [x] **Anthropic**: Claude2, Claude-instant
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- [x] **Replicate**
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- [x] **Hugging Face Hub**
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- [x] **ChatGLM**
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- [x] **Llama2**
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- [x] **MiniMax**
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- [x] **Spark**
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- [x] **Wenxin**
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- [x] **Tongyi**
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We provide the following free resources for registered Dify cloud users (sign up at [dify.ai](https://dify.ai)):
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* 200 free OpenAI queries to build OpenAI-based apps
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**2. Visual orchestration:** Build an AI app in minutes by writing and debugging prompts visually.
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**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.
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**4. API-based:** Backend-as-a-service. Access web apps directly or integrate via APIs without complex backend setup.
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**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.
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**6. Team workspaces:** Team members can join workspaces to collaboratively edit, manage, and use team AI apps.
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**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)
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## Use cases
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* [Create an AI ChatBot with Business Data in Minutes.](https://docs.dify.ai/use-cases/create-an-ai-chatbot-with-business-data-in-minutes)
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* [How to Build an Notion AI Assistant Based on Your Own Notes?](https://docs.dify.ai/use-cases/build-an-notion-ai-assistant)
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* [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)
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## Use Cloud Services
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## Use Cloud Services
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Visit [Dify.ai](https://dify.ai)
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Using [Dify.AI Cloud](https://dify.ai) provides all the capabilities of the open-source version, and includes a complimentary 200 GPT trial credits.
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## Why Dify
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Dify features model neutrality and is a complete, engineered tech stack compared to hardcoded development libraries like LangChain. Unlike OpenAI's Assistants API, Dify allows for full local deployment of services.
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| Feature | Dify.AI | Assistants API | LangChain |
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|---------|---------|----------------|-----------|
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| **Programming Approach** | API-oriented | API-oriented | Python Code-oriented |
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| **Ecosystem Strategy** | Open Source | Closed and Commercial | Open Source |
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| **RAG Engine** | Supported | Supported | Not Supported |
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| **Prompt IDE** | Included | Included | None |
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| **Supported LLMs** | Rich Variety | Only GPT | Rich Variety |
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| **Local Deployment** | Supported | Not Supported | Not Applicable |
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## Features
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**1. LLM Support**: Integration with OpenAI's GPT family of models, or the open-source Llama2 family models. In fact, Dify supports mainstream commercial models and open-source models (locally deployed or based on MaaS).
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**2. Prompt IDE**: Visual orchestration of applications and services based on LLMs with your team.
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**3. RAG Engine**: Includes various RAG capabilities based on full-text indexing or vector database embeddings, allowing direct upload of PDFs, TXTs, and other text formats.
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**4. Agents**: A Function Calling based Agent framework that allows users to configure what they see is what they get. Dify includes basic plugin capabilities like Google Search.
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**5. Continuous Operations**: Monitor and analyze application logs and performance, continuously improving Prompts, datasets, or models using production data.
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## Install the Community Edition
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## Install the Community Edition
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@ -90,39 +70,11 @@ You can go to https://github.com/BorisPolonsky/dify-helm for deployment informat
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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.
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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.
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## Roadmap
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Features under development:
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- **Datasets**, supporting more datasets, e.g. syncing content from Notion or webpages
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We will support more datasets, including text, webpages, and even Notion content. Users can build AI applications based on their own data sources.
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- **Plugins**, introducing ChatGPT Plugin-standard plugins for applications, or using Dify-produced plugins
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We will release plugins complying with ChatGPT standard, or Dify's own plugins to enable more capabilities in applications.
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## Q&A
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**Q: What can I do with Dify?**
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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.
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**Q: How do I use Dify to "train" my own model?**
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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.
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**Q: What do I need to prepare if I want to create my own application?**
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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!
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**Q: What interface languages are available?**
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A: English and Chinese are currently supported, and you can contribute language packs to us.
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## Star History
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## Star History
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[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
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[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
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## Contributing
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## Contributing
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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.
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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.
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@ -162,14 +114,7 @@ We're eager to assist you and together create more fun and useful AI application
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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.
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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.
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## Citation
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This software uses the following open-source software:
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- Chase, H. (2022). LangChain [Computer software]. https://github.com/hwchase17/langchain
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For more information, please refer to the official website or license text of the respective software.
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## License
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## License
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This repository is available under the [Dify Open Source License](LICENSE).
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This repository is available under the [Dify Open Source License](LICENSE), which is essentially Apache 2.0 with a few additional restrictions.
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