Flowwise AI

Open-source drag-and-drop builder for creating custom LLM apps and agent workflows.

4.3 (4)

Перевірено Daniel Nikulshyn·Оновлено травень 2026 р.

RAG Agents Open Source Low-Code LLM Self-Hosted Visual Builder Developer Tools

Огляд

Flowise AI is an open-source low-code platform that lets developers and teams design LLM-powered applications through a visual node-based interface. Instead of writing extensive boilerplate, users connect components like models, prompts, memory, vector stores, and tools on a canvas to assemble chatbots, agents, and retrieval pipelines. Built on top of popular frameworks such as LangChain and LlamaIndex, Flowise supports a wide range of LLM providers, embeddings, and data sources. Finished flows can be deployed as APIs or embedded widgets, making it practical for prototyping internal tools as well as shipping production features. Because the project is self-hostable and community-driven, it appeals to teams that want flexibility, transparency, and control over their AI stack without being locked into a proprietary service.

Ключові функції

Node-based visual editor for LLM workflows
Support for LangChain and LlamaIndex components
Built-in agents, memory, and tool integrations
Connectors for vector databases and embeddings
API endpoints and chat widget deployment
Custom credentials and multi-model support

Кейси використання

Prototype custom AI chatbots visually

Drag and connect LLMs, prompts, and memory nodes on a canvas to quickly assemble and test conversational chatbots without writing extensive boilerplate code.

Build RAG pipelines over internal data

Connect embeddings and vector database nodes to create retrieval-augmented generation flows that answer questions grounded in your organization's documents.

Deploy LLM workflows as APIs

Expose finished flows as API endpoints or embeddable chat widgets to integrate AI features into existing web apps, internal tools, or production systems.

Design multi-tool AI agents

Use built-in agent and tool integrations to compose autonomous workflows that can call external services, query data sources, and complete multi-step tasks.

Плюси і мінуси

Плюси

Visual drag-and-drop flow builder
Open source and self-hostable
Integrates with many LLMs and vector stores
Exposes flows as APIs and embeds
Active community and frequent updates

Мінуси

Learning curve for non-developers
Self-hosting requires technical setup
Complex flows can become hard to manage
Documentation can lag new features

Відгуки

4.3

Середнє з 4 оцінок.

Увійди, щоб залишити відгук.

Ahmed Saleh

Years in this space

I've evaluated a lot of these over the years. What stands out here is custom credentials and multi-model support — handled better than most — and integrates with many LLMs and vector stores. Self-hosting requires technical setup is my one real gripe. Worth the time if this is your use case.

Tomáš Novák

Compared a few options

Evaluated this against two competitors. Where it wins: built-in agents, memory, and tool integrations and integrates with many LLMs and vector stores. Where it lags: complex flows can become hard to manage. On balance the feature set — especially connectors for vector databases and embeddings — justifies the 4 stars for our use case.

George Papadakis

Compared a few options

Evaluated this against two competitors. Where it wins: aPI endpoints and chat widget deployment and active community and frequent updates. Where it lags: self-hosting requires technical setup. On balance the feature set — especially aPI endpoints and chat widget deployment — justifies the 4 stars for our use case.

Diego Fernández

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on built-in agents, memory, and tool integrations, and exposes flows as APIs and embeds caught me off guard. Self-hosting requires technical setup is why this isn't a perfect score, still, I'd recommend giving it a real trial.