![cover-v5-optimized](./images/GitHub_README_if.png)

<p align="center">
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Self-hosting</a> ·
  <a href="https://docs.dify.ai">Documentation</a> ·
  <a href="https://dify.ai/pricing">Dify product editions</a>
</p>

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</p>

#

<p align="center">
  <a href="https://trendshift.io/repositories/2152" target="_blank"><img src="https://trendshift.io/api/badge/repositories/2152" alt="langgenius%2Fdify | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>
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.

**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, 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.


## 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 Feature (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>

## Using Dify

- **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.

- **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.

![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)



## Quick Start
> 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)
- [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
- [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)

#### Terraform atorlugu pilersitsineq

wa'logh nIqHom neH ghun deployment toy'wI' [terraform](https://www.terraform.io/) lo'laH.

##### Azure Global
- [Azure Terraform mung @nikawang](https://github.com/nikawang/dify-azure-terraform)

##### Google Cloud
- [Google Cloud Terraform qachlot @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)

#### AWS CDK atorlugh pilersitsineq

wa'logh nIqHom neH ghun deployment toy'wI' [CDK](https://aws.amazon.com/cdk/) lo'laH.

##### AWS 
- [AWS CDK qachlot @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws)

#### Alibaba Cloud

[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88)

#### Alibaba Cloud Data Management

[Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/)


## 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.


> 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).

**Contributors**

<a href="https://github.com/langgenius/dify/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=langgenius/dify" />
</a>

## 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).
* [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
* [X(Twitter)](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](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.
