Dify

Dify

An open-source LLM app development platform

Deploy Dify

Web

langgenius/dify-web

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Sandbox

langgenius/dify-sandbox

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/dependencies

Redis

redis:6-alpine

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/data

Storage console

railwayapp-templates/minio-console

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Api

langgenius/dify-api

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Weaviate

semitechnologies/weaviate

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/var/lib/weaviate

Worker

langgenius/dify-api

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postgres:15-alpine

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/var/lib/postgresql/data

Storage provision

minio/mc

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Storage

minio/minio

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/data

⚠️ After deploying for the first time, you'll need the auto-generated INIT_PASSWORD variable in the Api service to setup the admin account. Expect possible loading delays as a result of cache on fresh deployments.

cover-v5-optimized

Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production. Here's a list of the core features:

1. Workflow: Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.

https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa

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 found here.

providers-v5

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, DELL·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.

Feature comparison

FeatureDify.AILangChainFlowiseOpenAI Assistants API
Programming ApproachAPI + App-orientedPython CodeApp-orientedAPI-oriented
Supported LLMsRich VarietyRich VarietyRich VarietyOpenAI-only
RAG Engine
Agent
Workflow
Observability
Enterprise Features (SSO/Access control)
Local Deployment

Next steps

If you need to customize the configuration, please refer to the comments in our docker-compose.yml file and manually set the environment configuration. You can see the full list of environment variables here.

Community & contact

  • Github Discussion. Best for: sharing feedback and asking questions.
  • GitHub Issues. Best for: bugs you encounter using Dify.AI, and feature proposals. See our Contribution Guide.
  • Email. Best for: questions you have about using Dify.AI.
  • Discord. Best for: sharing your applications and hanging out with the community.
  • Twitter. Best for: sharing your applications and hanging out with the community.

License

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


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Details

Created on May 15, 2024

927 total projects

300 active projects

100% success on recent deploys

Dockerfile

AI/ML



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