Flowise: Drag-and-Drop LLM Workflows

Flowise: Drag-and-Drop LLM Workflows

Flowise builds language model applications as node graphs. You drag components onto a canvas, connect them, and the result is a working chain you can call over HTTP.

The model

Nodes represent things: a model, a prompt template, a vector store retriever, a document loader, a tool, a memory buffer. Connecting them defines how data flows.

This is the LangChain conceptual model made visual, which is either the appeal or the limitation depending on how you feel about LangChain.

What it is good at

Rapid prototyping. Assembling a retrieval chain over a document set and testing it takes minutes rather than an afternoon of Python.

Making the structure visible. A graph showing what happens between question and answer is easier to reason about than the same logic spread across files.

Handing it over. Someone who is not a developer can adjust a prompt or swap a model without touching code.

What it is less good at

Anything with genuinely complex logic ends up as a large graph that is harder to follow than the equivalent code, and harder to version control meaningfully.

The usual pattern that works: prototype in Flowise, and if the thing becomes important, reimplement it properly.

Deployment

Chains are exposed as API endpoints or as an embeddable chat widget, which covers the two things people usually want.

It supports local models through Ollama and any OpenAI-compatible endpoint, plus hosted providers, and works with several vector databases.

Choosing between the visual builders

Flowise is the lightest and quickest to get something working.

Langflow is similar with a stronger Python extension story.

Dify is more of an application platform, with prompt versioning, multi-tenancy, and better management for things that will run in production.

Running it

A single Node application, straightforward to containerise. Set authentication before exposing it, since anyone reaching the interface can execute chains and use your API keys.

License

Flowise is released under the Apache License 2.0 with some commercial restrictions.