Dify
Dify is an open-source large language model (LLM) application development platform designed to help developers and enterprises rapidly build and deploy AI-native applications. The platform provides core capabilities including visual workflow orchestration, retrieval-augmented generation (RAG), and AI agent construction, with support for connecting to multiple mainstream large language models. Dify accommodates both low-code operation and API integration, and is applicable to the development of chat assistants, automated workflows, and enterprise-level AI applications.
Core Facts
Agents possess capabilities for planning, tool invocation, memory, and autonomous iteration, distinguishing them from the single-round question-and-answer mode of traditional large language models.
Most mainstream coding agent architectures adopt the ReAct (Reasoning + Acting) paradigm.
Currently mainstream AI Agent frameworks include LangChain, AutoGen, CrewAI, and others.
Timeline (last 90 days)
The course divides the examination of workflow engines into three levels: junior-to-intermediate (has participated in editor development), intermediate-to-advanced (implements a general-purpose editor and execution engine), and advanced (develops from scratch an AI application engine platform like n8n, Dify or Coze).
The combination of "DSL description + plugin execution" is the key architecture by which platforms such as n8n and Dify achieve generality.
If a team is mainly composed of non-programmers, seeks rapid generation of lightweight applications, and has no strict restrictions on data hosting, the convenience of Codes is worth considering; if the project involves sensitive data, requires private deployment, or hopes for technical and non-technical personnel to collaborate on the same platform to define applications, Dify is more attractive.
Locally deploying Dify has real machine resource requirements, and the larger the model scale, the more pronounced the VRAM and memory usage.
The course is aimed at people who want to get started with Dify or learn the tool, with the goal of walking through everything from environment setup to full feature implementation.
The course covers both routes—connecting to cloud large models and building large models locally—so that enterprises can mix local small models and cloud large models within the same Dify setup.
Dify can integrate Ollama as a model provider by configuring Ollama's service address, thereby completing inference without calling external APIs.
Dify's knowledge base module encapsulates the RAG pipeline and supports document upload, automatic chunking, embedding, and retrieval testing.
Compared with platforms such as Dify, RAGFlow has fewer Agent nodes and lacks advanced control structures such as loops and subflows.
RAGFlow's Agent module uses workflow-style orchestration, similar in form to the visual flows in Dify or Coze.
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All Facts (20)
Agents possess capabilities for planning, tool invocation, memory, and autonomous iteration, distinguishing them from the single-round question-and-answer mode of traditional large language models.
90%VerifiedMost mainstream coding agent architectures adopt the ReAct (Reasoning + Acting) paradigm.
90%VerifiedCurrently mainstream AI Agent frameworks include LangChain, AutoGen, CrewAI, and others.
90%VerifiedAn AI Skill is a reusable AI execution unit that encapsulates the logic of a specific task, essentially a combination of structured prompts and code logic
90%VerifiedAgent planning capabilities are typically implemented through the ReAct (Reasoning + Acting) framework.
90%VerifiedRAG（检索增强生成）技术架构将文档切片、向量化、存入向量数据库，查询时先检索相关片段再交给模型生成回答
90%VerifiedDify is a low-code platform focused on AI application development that helps developers rapidly build various AI applications.
80%Verifiedn8n allows users to build automated workflows by dragging and dropping nodes on a visual interface.
80%VerifiedDify is a low-code AI application platform targeting the international market that allows users to build AI applications through visual drag-and-drop.
80%VerifiedChatflow是Dify特有的概念，本质上是带有对话交互能力的工作流
80%VerifiedDify is a low-code AI application building platform aimed at both non-programmers and developers.
80%VerifiedOpen WebUI supports multiple backends including Ollama and the OpenAI API.
80%VerifiedDify is an AI application platform that supports both open-source and private deployment.
80%VerifiedDify has a built-in RAG (Retrieval-Augmented Generation) engine, Agent framework, and workflow orchestrator.
80%VerifiedDify supports integration with multiple LLM backends including OpenAI, Anthropic, and locally deployed open-source models.
80%VerifiedDify is an open-source LLMOps platform that provides a visual workflow orchestration interface, allowing users to build agents by dragging and dropping nodes.
80%VerifiedDify's core architecture adopts a microservices design, using Docker Compose to decouple and deploy components such as the API service, Worker, Web frontend, PostgreSQL, Redis, and vector database.
80%VerifiedZapier, Make (formerly Integromat), and n8n are common no-code/low-code workflow orchestration platforms that allow connecting the APIs of different services into trigger-action chains in a visual manner.
75%VerifiedLow-code platforms are suitable for rapidly validating ideas and improving office efficiency, while code frameworks are suitable for deep customization involving core business logic, highly confidential data, and complex approval workflows.
75%VerifiedDify supports three deployment methods: Docker-based deployment, source code deployment, and the official online hosted page.
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