Flowise
Flowise is an open-source, low-code tool with a drag-and-drop visual interface for building LLM-powered applications and workflows, such as chatbots and retrieval-augmented generation pipelines.
Definition
Flowise is an open-source, low-code tool with a drag-and-drop visual interface for building LLM-powered applications and workflows, such as chatbots and retrieval-augmented generation pipelines.
Overview
Flowise lets developers assemble LLM applications by connecting visual nodes on a canvas rather than writing orchestration code by hand. Nodes represent building blocks familiar to anyone who has used a framework like LangChain — language models, prompt templates, vector databases, memory, and tools — and are wired together to define how data flows through an application, such as a RAG pipeline or conversational agent. Because it exposes these components visually, Flowise lowers the barrier to building and iterating on LLM application logic, making it accessible to people who understand the concepts of prompting and retrieval but prefer not to write Python or JavaScript orchestration code directly. Once built, flows can be deployed and exposed as APIs or embedded chat widgets for use in other applications. Flowise sits alongside other low-code and no-code LLM application builders such as Dify, with the common goal of making agentic and RAG-based application patterns accessible without requiring a full custom codebase, while still allowing developers to drop into code for more advanced customization when needed.
Key Features
- Drag-and-drop visual builder for LLM application workflows
- Pre-built nodes for language models, prompts, memory, and vector stores
- Support for building retrieval-augmented generation pipelines visually
- One-click deployment of flows as APIs or embeddable chat widgets
- Open-source and self-hostable
- Compatible with concepts and components familiar from LangChain