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Flowise

Drag-and-drop UI for building LangChain chatbots and RAG pipelines

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Flowise is an open-source visual builder for creating LangChain-based chatbots, RAG pipelines, and AI agents. Connect LLMs, vector stores, prompts, and tools by dragging nodes on a canvas, then deploy as an API or embeddable chat widget. The go-to tool for visual LangChain prototyping.

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Key specs
55,569 GitHub stars source
as of 2026-11-12

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What we know

PricingFreefrom our original listing, not yet re-checked

Why it matters

  • 34,000+ GitHub stars — the most popular visual LangChain builder, with a large community of tutorials and templates.
  • Eliminates LangChain boilerplate: build a complete RAG chatbot in minutes without writing a single line of Python.
  • MIT license — no restrictions on commercial use; popular for internal tools and SaaS product features.
  • Embeddable chat widget means a Flowise app can be on your website in an afternoon.

Key capabilities

  • Visual node editor: Drag LangChain components onto a canvas — LLMs, vector stores, memory, chains, agents, tools.
  • Pre-built templates: Gallery of ready-made flows for common use cases (PDF chat, web scraping RAG, customer support).
  • Chatflows: Build and deploy conversational chatbots with persistent memory and tool use.
  • Agentflows: Create tool-using agents with web search, code execution, and API call capabilities.
  • Document loaders: Ingest PDFs, websites, Notion, Google Drive, GitHub, and more.
  • API endpoint: Every Flowise flow becomes a REST API automatically — call from any app.
  • Embeddable widget: One-line JavaScript snippet embeds the chat UI on any website.
  • Marketplace: Community-shared flows, templates, and tools.

Technical notes

  • License: MIT — fully open source, commercial use allowed
  • Deployment: Node.js; Docker; npm install -g flowise && flowise start; Flowise Cloud
  • Backend: Node.js + Express; LangChain.js under the hood
  • Database: SQLite (default); PostgreSQL supported
  • Auth: Basic HTTP auth; OAuth in Flowise Cloud
  • Pricing (cloud): Free (20 flows); Starter $35/mo; Enterprise custom
  • Founded: 2023 by Henry Heng and Alfred Tan; YC W23

Ideal for

  • LangChain users who want to build and demo RAG apps without writing Python code.
  • Developers building chatbot features for websites who need a quick embed-and-forget solution.
  • Teams prototyping AI workflows for stakeholder demos before committing to full engineering investment.

Not ideal for

  • Very complex production workflows requiring robust monitoring, dataset management, or advanced access control.
  • Organizations needing enterprise SLAs, audit logs, or SSO on self-hosted — look at Dify Enterprise.
  • Non-LangChain AI architectures — Flowise is tightly coupled to LangChain.js.

See also

  • Dify — More complete LLM app platform with production monitoring and dataset annotation.
  • n8n — Open-source workflow automation with AI nodes and 400+ integrations.
  • LangChain — The underlying Python/JS framework Flowise visualizes.

FAQ

What is Flowise?

Flowise is an open-source, visual drag-and-drop tool for building LangChain applications. You connect nodes (LLMs, vector stores, memory, prompts, tools) on a canvas to create chatbots, RAG apps, and AI agents — without writing Python code. Deploy as a REST API or embed the chat widget on any website.

Is Flowise free?

Flowise is fully open source under MIT license — free to self-host with all features. Flowise Cloud offers a hosted version with a free tier (20 flows) and paid plans from $35/mo. Self-hosting on a $5/month VPS is a common setup for teams that want to avoid cloud costs.

What is the difference between Flowise and Dify?

Both are visual LLM app builders. Flowise is more code-adjacent — it directly exposes LangChain components, giving power users fine control. Dify has a broader product focus with built-in production monitoring, dataset annotation, and a polished UI. Flowise is better for LangChain power users; Dify is better for shipping production apps.

What LLMs and vector stores does Flowise support?

Flowise supports OpenAI, Anthropic, HuggingFace, Ollama, Azure OpenAI, AWS Bedrock, Mistral, and Google Vertex. Vector stores: Pinecone, Chroma, Qdrant, Weaviate, Milvus, Redis, PostgreSQL (pgvector). It uses LangChain under the hood so anything LangChain supports, Flowise can connect to.

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Listed 2026-02-28 · updated 2026-09-11