Flowise

Flowise is an open-source visual tool for building language model workflows. Written in LangchainJS, it lets you assemble a chain on a canvas: pick a model, add a prompt, connect a retriever, wire the output, and test the whole thing in the browser. The examples in the listing cover a basic LLM chain, a question-answer retrieval chain, and a language translation chain. Because it is open source, the component set is expandable, and the project is described as free for both commercial and personal use.

- Assemble an LLM chain visually instead of writing wiring code

- Build a retrieval chain over your own documents

- Wire a translation chain between languages

- Extend the tool with custom components

- Prototype a flow before committing to production code

- Developers prototyping language model applications quickly

- Teams that want a shared visual picture of how a chain fits together

- Anyone evaluating LLM patterns before writing real code

You run and maintain it yourself. That means hosting, updates, and security are your responsibility, not a vendor's. A canvas is excellent for a small chain and poor for a large one: once a flow has dozens of nodes it becomes harder to read than code. The tool also depends on external model providers, so you need your own keys and you inherit their outages and price changes. Debugging sits partly outside the visual layer, so expect to read logs when something fails. Behavior may vary across browsers and devices, so test before production use and consult the help docs if errors appear.