How to use Dify (langgenius/dify): 3 use cases

3 use cases

Self-host Dify with Docker Compose

Copy the env file, start the stack, and finish setup in the browser.

View prompt

Self-host langgenius/dify with Docker Compose on this server, confirm all containers are healthy, and tell me which values in .env I should change before exposing it to my team.

Build a chatbot over your PDFs and slides

Upload documents to a knowledge base and wire a chat app that answers from them.
- REPO langgenius/dify
- Work and operations
- Intermediate
View prompt
```
In my langgenius/dify instance, create a knowledge base from <documents>, build a chat app that answers only from it and says when it does not know, and give me its API endpoint.
```
Give a Dify agent tools from MCP servers and the marketplace

Describe an agent, connect tools or MCP servers, and use it as a chat app or a step inside a workflow.
- REPO langgenius/dify
- Work and operations
- Intermediate
View prompt
```
Build a langgenius/dify agent that <task>, connect the <MCP server or tool>, test it in chat, then add it as a step in a workflow that <workflow>. List every tool it can call.
```

Quick start with Dify

Check you have what it needs: Docker and Docker Compose v2.24.0 or later for self-hosting; A machine with at least 2 CPU cores and 4 GiB RAM; API keys for the model providers you use.
Open langgenius/dify on GitHub and read the README and license.
Clone the repo, then cd dify and cd docker
Run cp .env.example .env
Start it with docker compose up -d
Open http://localhost/install and complete initialization

These steps come from our top use case, Self-host Dify with Docker Compose, which also has a copy-paste agent prompt.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for langgenius/dify

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

Cursor, ChatGPT, others

Dify alternatives · Best AI repos for Work and operations

About this repo

Who it is forTeams and builders who want to ship chatbots, internal assistants and AI workflows without hand-writing the whole stack.
Why it is hot159k stars, talked about in 2 AI sources we track
LanguagePython
Sourcegithub.com/langgenius/dify · Back to Hot repos

Requirements

Docker and Docker Compose v2.24.0 or later for self-hosting
A machine with at least 2 CPU cores and 4 GiB RAM
API keys for the model providers you use

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Questions about Dify

What is Dify?

Dify is an open-source platform for building LLM apps. It combines a visual workflow canvas, a RAG pipeline that ingests PDFs and slides, agents with their own sandbox, support for hundreds of models, a prompt IDE, observability and a backend-as-a-service API, so a team can go from prototype to production in one workspace. It runs in Dify Cloud or self-hosted with Docker Compose. It is an open-source project on GitHub: https://github.com/langgenius/dify.

How do I use Dify?

Clone the repo, then cd dify and cd docker; then run cp .env.example .env; start it with docker compose up -d. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is Dify for?

Teams and builders who want to ship chatbots, internal assistants and AI workflows without hand-writing the whole stack.

What can I do with Dify?

3 use cases so far, for example: Self-host Dify with Docker Compose; Build a chatbot over your PDFs and slides; Give a Dify agent tools from MCP servers and the marketplace. Each has steps and a copy-paste agent prompt.

What do I need to run Dify?

Docker and Docker Compose v2.24.0 or later for self-hosting; A machine with at least 2 CPU cores and 4 GiB RAM; API keys for the model providers you use.

What are alternatives to Dify?

Other hot AI repos in Work and operations: Solidcraft, OpenDots, Google Workspace CLI, n8n, Sprawling Agents.

Is Dify safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.