All Templates / AI/ML
Dify
An open-source LLM app development platform
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
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.
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.
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 | Dify.AI | LangChain | Flowise | OpenAI Assistants API |
---|---|---|---|---|
Programming Approach | API + App-oriented | Python Code | App-oriented | API-oriented |
Supported LLMs | Rich Variety | Rich Variety | Rich Variety | OpenAI-only |
RAG Engine | ✅ | ✅ | ✅ | ✅ |
Agent | ✅ | ✅ | ❌ | ✅ |
Workflow | ✅ | ❌ | ✅ | ❌ |
Observability | ✅ | ✅ | ❌ | ❌ |
Enterprise Features (SSO/Access control) | ✅ | ❌ | ❌ | ❌ |
Local Deployment | ✅ | ✅ | ✅ | ❌ |
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.
This repository is available under the Dify Open Source License, which is essentially Apache 2.0 with a few additional restrictions.
Template Content
Sandbox
langgenius/dify-sandboxRedis
redis:6-alpineStorage console
railwayapp-templates/minio-consoleWeaviate
semitechnologies/weaviateWorker
langgenius/dify-apiPostgres
postgres:15-alpineStorage provision
minio/mcStorage
minio/minioDetails
Created on May 15, 2024
945 total projects
303 active projects
84% success on recent deploys
Dockerfile
AI/ML
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