langgenius/dify

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 rebuilding the stack.

 Dify Cloud · Self-hosting · Documentation · Dify edition overview Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including [Opik](https://www.comet.com/docs/opik/integrations/dify), [Langfuse](https://docs.langfuse.com), and [Arize Phoenix](https://docs.arize.com/phoenix)) and more, letting you quickly go from prototype to production. Here's a list of the core features: ## Quick start > 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 through [Docker Compose](docker/docker-compose.yaml). Install [Docker](https://docs.docker.com/get-docker/) with a running daemon, Docker Compose v2.35.0 or later, and OpenSSL. For a new deployment, run the following commands from the repository root. For an existing deployment, preserve your `.env` and follow the [upgrade guidance](docker/README.md#review-configuration-after-an-upgrade). ```bash cd docker cp .env.example .env openssl rand -hex 32 ``` Open `.env` and set `DIFY_AGENT_LOCAL_SANDBOX_AUTH_TOKEN` to the generated value. Keep the default `COMPOSE_PROFILES` value for the bundled services. Service defaults load automatically; no additional configuration files are required. From the same `docker` directory, start the services: ```bash docker compose up -d docker compose ps --all ``` Once the services are running, open [http://localhost/install](http://localhost/install) to complete the initial setup. The one-time `init_permi