Do I need to code with Flowise?

No, you can build many LLM apps visually, though custom logic can extend it.

How does Flowise differ from Dify?

Flowise stays close to the LangChain ecosystem and feels like a visual layer for developers, while Dify ships more product features out of the box — RAG engine, app publishing, team workspaces. Both self-host; pick by how much platform you want.

Can Flowise connect to my own models or APIs?

Yes — Flowise ships many prebuilt nodes for major providers and supports custom nodes or plain fetch calls, so you can wire in any LLM, vector store, or internal API. Self-hosting keeps those credentials under your control.

Open SourceBeginner

Flowise

Name: Flowise
Author: Flowise

Flowise is an open-source, drag-and-drop tool for visually building LLM applications and agent workflows with little to no code. It supports chaining prompts, integrating vector stores, and connecting multiple LLM providers — making it accessible for non-developers to prototype and deploy AI-powered solutions quickly.

Overview

"Flowise" is a "Open Source" resource curated by AI Resource Hub, filed under the Open-Source Tools category and suited to Beginner-level learners. It is provided by Flowise, was last updated on 2026-06-12, and holds an editorial score of 4.5/5 from our team. Click "Visit Resource" on the right to open the original page.

Our Verdict

Flowise is the fastest way to see an LLM idea working: drag nodes onto a canvas, wire up prompts, RAG, and agents, and have a prototype before your coffee cools. Its LangChain roots mean prebuilt nodes for most providers plus custom nodes and fetch calls for anything else. The limits: complex logic still wants code, self-hosting brings real infrastructure upkeep, and the community is smaller than LangChain's. For non-developers prototyping and developers sketching flows, it's a genuinely free head start.