⚠️ After deploying for the first time, you'll need the auto-generated `INIT_PASSWORD` variable in the `Api` service to setup the admin account. Expect possible loading delays as a result of cache on fresh deployments. ![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab) 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: **1. Workflow**: Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond. https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa **2. Comprehensive model support**: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama3, and any OpenAI API-compatible models. A full list of supported model providers can be found [here](https://docs.dify.ai/getting-started/readme/model-providers). ![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3) **3. Prompt IDE**: Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app. **4. RAG Pipeline**: Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats. **5. Agent capabilities**: You can define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools for the agent. Dify provides 50+ built-in tools for AI agents, such as Google Search, DELL·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. ## Feature comparison

Feature	Dify.AI	LangChain	Flowise	OpenAI Assistants API
Programming Approach	API + App-oriented	Python Code	App-oriented	API-oriented
Supported LLMs	Rich Variety	Rich Variety	Rich Variety	OpenAI-only
RAG Engine	✅	✅	✅	✅
Agent	✅	✅	❌	✅
Workflow	✅	❌	✅	❌
Observability	✅	✅	❌	❌
Enterprise Features (SSO/Access control)	✅	❌	❌	❌
Local Deployment	✅	✅	✅	❌

## Next steps 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. You can see the full list of environment variables [here](https://docs.dify.ai/getting-started/install-self-hosted/environments). ## Community & contact * [Github Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions. * [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). * [Email](mailto:support@dify.ai?subject=[GitHub]Questions%20About%20Dify). Best for: questions you have about using Dify.AI. * [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. ## License This repository is available under the [Dify Open Source License](LICENSE), which is essentially Apache 2.0 with a few additional restrictions.