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📌Introducing Dify Workflow File Upload: Recreate Google NotebookLM Podcast

Dify Cloud ·Self-hosting ·Documentation ·Enterprise inquiry

Dify is an open-source LLM app development platform. Its intuitive interface combines agentic AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

Before installing Dify, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4 GiB

The easiest way to start the Dify server is throughdocker compose. Before running Dify with the following commands, make sure thatDocker andDocker Compose are installed on your machine:

cd difycd dockercp .env.example .envdocker compose up -d

After running, you can access the Dify dashboard in your browser athttp://localhost/install and start the initialization process.

Please refer to ourFAQ if you encounter problems setting up Dify. Reach out tothe community and us if you are still having issues.

If you'd like to contribute to Dify or do additional development, refer to ourguide to deploying from source code

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 foundhere.

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.

• Cloud
  We host aDify Cloud 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
  Quickly get Dify running in your environment with thisstarter guide.Use ourdocumentation for further references and more in-depth instructions.

• Dify for enterprise / organizations
  We provide additional enterprise-centric features.Log your questions for us through this chatbot orsend us an email to discuss enterprise needs.
  

  For startups and small businesses using AWS, check outDify Premium on AWS Marketplace 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.

Star Dify on GitHub and be instantly notified of new releases.

If you need to customize the configuration, please refer to the comments in our.env.example file and update the corresponding values in your.env file. Additionally, you might need to make adjustments to thedocker-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-rundocker-compose up -d. You can find the full list of available environment variableshere.

If you'd like to configure a highly-available setup, there are community-contributedHelm Charts and YAML files which allow Dify to be deployed on Kubernetes.

• Helm Chart by @LeoQuote
• Helm Chart by @BorisPolonsky
• YAML file by @Winson-030

Deploy Dify to Cloud Platform with a single click usingterraform

• Azure Terraform by @nikawang

• Google Cloud Terraform by @sotazum

Deploy Dify to AWS withCDK

• AWS CDK by @KevinZhao

For those who'd like to contribute code, see ourContribution Guide.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 thei18n README for more information, and leave us a comment in theglobal-users channel of ourDiscord Community Server.

• Github Discussion. Best for: sharing feedback and asking questions.
• GitHub Issues. Best for: bugs you encounter using Dify.AI, and feature proposals. See ourContribution Guide.
• Discord. Best for: sharing your applications and hanging out with the community.
• X(Twitter). Best for: sharing your applications and hanging out with the community.

Contributors

To protect your privacy, please avoid posting security issues on GitHub. Instead, send your questions tosecurity@dify.ai and we will provide you with a more detailed answer.

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