Verified project record

langgenius/dify

Dify is an open-source platform that combines visual AI workflow building, RAG pipelines, agent capabilities, and model management into a single Backend-as-a-Service. It enables developers to build, test, and deploy LLM applications without requiring coding for basic configuration.

Project overview

The platform consolidates AI workflow orchestration, RAG, agent capabilities, and observability into a single system, allowing teams to move from prototype to production using a visual interface.

Project type: AI Agent · RAG · Workflow
Use cases: Knowledge Q&A · Coding & Development · Automation
Deployment: Docker / Docker Compose
License: License pending

Best for

Developers, AI engineers, and enterprise teams building production-ready agentic AI workflows and LLM applications.

Key capabilities

Build and test AI workflows on a visual canvas.
Integrates with hundreds of proprietary and open-source LLMs from dozens of inference providers and self-hosted solutions, covering models such as GPT, Mistral, and Llama3.
Interface for crafting prompts, comparing model performance, and adding features such as text-to-speech to chat-based apps.
Provides RAG capabilities from document ingestion to retrieval, with support for text extraction from PDFs, PPTs, and other common document formats.
Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools.
Monitor and analyze application logs and performance over time to improve prompts, datasets, and models based on production data and annotations.
Provides corresponding APIs for offerings, allowing integration into custom business logic.

Limitations and risks

Integration with external inference providers and APIs is optional for model capabilities, meaning external services and paid APIs may be involved depending on the chosen models.
Telemetry practices and GPU hardware requirements are not documented.

Getting started

To start locally, navigate to the dify/docker directory, copy the .env.example file to .env, and run docker compose up -d. Access the dashboard at http://localhost/install. Minimum system requirements are CPU >= 2 Core and RAM >= 4 GiB.

Evidence and sources

README: Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (incl…
GitHub project description: Production-ready platform for agentic workflow development.
Release: 1.15.0
README: Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.
README: 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 AP…

Reviewed at: 2026-07-15T15:12:13Z

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