Overview of Large Model Application Development Platforms: LangChain, Dify, Flowise, and Coze

The article introduces several open‑source and commercial platforms for building large‑model‑based AI applications, focusing on LangChain, Dify, Flowise, and Coze.

LangChain adopts a modular, plug‑in architecture with core components such as Schema, Models, Prompts, Memory, Chain and Agent. It provides reusable abstractions for LLMs, prompt templates, chaining, agents and memory, enabling developers to assemble complex AI systems while preserving extensibility.

Dify builds on LangChain’s ideas and offers a one‑stop, low‑code development platform. It supports dozens of model providers (OpenAI, Tongyi Qianwen, Wenxin Yiyan, Xunfei Xinghuo, etc.), visual workflow orchestration, private‑data knowledge bases, variable‑driven prompts, one‑click deployment as frontend components or APIs, and built‑in logging, annotation and analytics for operations.

Flowise is a third‑party visual orchestration tool also based on LangChain. It is quick to run locally with Node.js and Docker, but offers fewer extensibility features and a lower overall product maturity compared with Dify.

Coze provides a low‑cost alternative with open APIs and domestic/international access (www.coze.cn / www.coze.com). Its functionality roughly matches the other platforms while aiming to reduce user‑side costs.

The article further describes derivative products that extend the basic platforms with capabilities such as permission control, flexible model access (self‑trained or fine‑tuned LLMs, embedding models), backend SDKs, vector‑database integration (e.g., Chroma), and business‑specific process customization.

A practical walkthrough shows how to use Dify to create a 'form development assistant': creating an app, importing a private knowledge base (e.g., Fromily v2.x Linkage docs), configuring prompts, testing retrieval, previewing and publishing the workflow as a frontend component or API, integrating via a simple script tag, and monitoring usage through logs, conversation records and token‑output metrics.

In conclusion, as AI technology advances, platforms like LangChain, Dify, Flowise and Coze are becoming essential infrastructure for efficient, flexible large‑model application development, accelerating AI adoption across industries.