The quickest way to deploy Dify locally is to run our [docker-compose.yml](https://github.com/langgenius/dify/blob/main/docker/docker-compose.yaml). Follow the instructions to start in 5 minutes.
> Before installing Dify, make sure your machine meets the following minimum system requirements:
>
>- CPU >= 2 Core
>- RAM >= 4 GiB
>- Docker and Docker Compose Installed
</br>
Run the following command in your terminal to clone the whole repo.
```bash
git clone https://github.com/langgenius/dify.git
```
After cloning,run the following command one by one.
```bash
cd dify
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. You will be asked to setup an admin account.
For more info of quick setup, check [here](https://docs.dify.ai/getting-started/install-self-hosted/docker-compose)
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:
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).
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.
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.
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.
## 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.
We provide additional enterprise-centric features. [Log your questions for us through this chatbot](https://udify.app/chat/22L1zSxg6yW1cWQg) or [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.
If you forget your admin account, you can refer to this [guide](https://docs.dify.ai/getting-started/install-self-hosted/faqs#id-4.-how-to-reset-the-password-of-the-admin-account) to reset the password.
> Use docker compose up without "-d" to enable logs printing out in your terminal. This might be useful if you have encountered unknow problems when using Dify.
If you encountered system error and would like to acquire help in Github issues, make sure you always paste logs of the error in the request to accerate the conversation. Go to [Community & contact](https://github.com/langgenius/dify?tab=readme-ov-file#community--contact) for more information.
> Please read the [Dify Documentation](https://docs.dify.ai/) for detailed how-to-use guidance. Most of the potential problems are explained in the doc.
> If you'd like to contribute to Dify or make additional development, refer to our [guide to deploying from source code](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
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.
> 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).
* [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).
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.
