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**Dify** is an open-source LLM app development platform. Dify's intuitive interface combines a RAG pipeline, AI workflow orchestration, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
![](./images/demo.png)
https://github.com/langgenius/dify/assets/13230914/979e7a68-f067-4bbc-b38e-2deb2cc2bbb5
## Using our Cloud Services
You can try out [Dify.AI Cloud](https://dify.ai) now. It provides all the capabilities of the self-deployed version, and includes 200 free requests to OpenAI GPT-3.5.
You can try out [Dify.AI Cloud](https://dify.ai) now. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls.
### Looking to purchase via AWS?
Check out [Dify Premium on AWS](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one-click.
## Features
![](./images/models.png)
**1. Workflow**: Create and test complex AI workflows on a visual canvas, with pre-built nodes taking advantage of the power of all the following features and beyond.
**2. Support**: Seamless integration with hundreds of proprietary / open-source LLMs and dozens of inference providers, including GPT, Mistral, Llama2, and OpenAI API-compatible models. A full list of supported model providers is kept [here](https://docs.dify.ai/getting-started/readme/model-providers).
**3. Prompt IDE**: Visual orchestration of applications and services based on any LLMs. Easily share with your team.
**4. 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.
**5. AI Agent**: Based on Function Calling and ReAct, the Agent inference framework allows users to customize tools, what you see is what you get. Dify provides more than a dozen built-in tools for AI agents, such as Google Search, DELL·E, Stable Diffusion, WolframAlpha, etc.
**6. LLMOps**: Monitor and analyze application logs and performance, continuously improving Prompts, datasets, or models based on production data.
## Dify vs. LangChain vs. Assistants API
| Feature | Dify.AI | Assistants API | LangChain |
@ -52,29 +69,10 @@ Check out [Dify Premium on AWS](https://aws.amazon.com/marketplace/pp/prodview-t
| **Local Deployment** | Supported | Not Supported | Not Applicable |
## Features
![](./images/models.png)
**1. Workflow**: Create and test complex AI workflows on a visual canvas, with pre-built nodes taking advantage of the power of all the following features and beyond.
**2. 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).
**3. Prompt IDE**: Visual orchestration of applications and services based on LLMs with your team.
**4. 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.
**5. AI Agent**: Based on Function Calling and ReAct, the Agent inference framework allows users to customize tools, what you see is what you get. Dify provides more than a dozen built-in tool calling capabilities, such as Google Search, DELL·E, Stable Diffusion, WolframAlpha, etc.
**5. Continuous Operations**: Monitor and analyze application logs and performance, continuously improving Prompts, datasets, or models using production data.
## Before You Start
**Star us on GitHub, and be instantly notified for new releases!**
![star-us](https://github.com/langgenius/dify/assets/100913391/95f37259-7370-4456-a9f0-0bc01ef8642f)
- [Website](https://dify.ai)
- [Docs](https://docs.dify.ai)
- [Deployment Docs](https://docs.dify.ai/getting-started/install-self-hosted)