Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without reb
Dify Cloud ·
Self-hosting ·
Documentation ·
Dify edition overview
Dify is an LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including
Opik,
Langfuse, and
Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features:
Key features
**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 / 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, 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.
Using Dify
- **Cloud
**
We host a
Dify 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. If you run into issues with Dify Cloud,
contact our Cloud support team.
- **Self-hosting Dify Community Edition
**
Quickly get Dify running in your environment with this
starter guide.
Use our
documentation for further references and more in-depth instructions.
- **Dify for enterprise / organizations
**
We provide additional enterprise-centric features.
Send us an email to discuss your enterprise needs.
Staying ahead
Star Dify on and be instantly notified of new releases.
Advanced Setup
Custom configurations
If you need to customize the configuration, edit `docker/.env`. The essential startup defaults live in
`docker/.env.example`, and optional advanced variables are split under `docker/envs/` by theme. After making any changes, re-run `docker compose up -d` from the `docker` directory. You can find the full list of available environment variables
here.
Metrics Monitoring with Grafana
Import the dashboard to Grafana, using Dify's PostgreSQL database as data source, to monitor metrics in granularity of apps, tenants, messages, and more.
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Deployment with Kubernetes
If you'd like to configure a highly available setup, there are community-
Helm Charts and YAML files which allow Dify to be deployed on Kubernetes.
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Using Terraform for Deployment
Deploy Dify to Cloud Platform with a single click using
terraform
Azure Global
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Google Cloud
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Using AWS CDK for Deployment
Deploy Dify to AWS with
CDK
AWS
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Using Alibaba Cloud Computing Nest
Quickly deploy Dify to Alibaba cloud with
Alibaba Cloud Computing Nest
Using Alibaba Cloud Data Management
One-Click deploy Dify to Alibaba Cloud with
Alibaba Cloud Data Management
Deploy to AKS with Azure Devops Pipeline
One-Click deploy Dify to AKS with
Security disclosure
To protect your privacy, please avoid posting security issues on . Instead, report issues to security@dify.ai, and our team will respond with detailed answer.