⚠️ 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.

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.

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

Next steps

If you need to customize the configuration, please refer to the comments in our docker-compose.yml file and manually set the environment configuration. You can see the full list of environment variables here.

Community & contact

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

License

This repository is available under the Dify Open Source License, which is essentially Apache 2.0 with a few additional restrictions.