Langflow

About

Langflow is an open-source visual framework for building multi-agent systems and RAG (Retrieval-Augmented Generation) applications through a drag-and-drop interface. Instead of writing code to wire together LLMs, vector databases, prompt templates, and tools, you visually connect components on a canvas — much like a node-based editor for AI workflows. Langflow supports all major LLM providers (OpenAI, Anthropic, Google, open-source models via Ollama), vector stores (Pinecone, Weaviate, Chroma, Qdrant), and LangChain components including chains, agents, and memory modules. You can build complex multi-agent systems where different AI agents handle different tasks: one agent retrieves information, another analyzes it, and a third formats the response. The drag-and-drop interface makes it accessible to non-coders for rapid prototyping, while the ability to export flows as API endpoints makes it production-ready for developers. Langflow supports custom Python functions within the visual flow using code nodes that let you add preprocessing, custom logic, or post-processing without leaving the visual environment. For AI application builders, Langflow dramatically reduces the time from concept to working prototype for RAG pipelines and agent systems. The project is open-source under the MIT license, can be self-hosted for privacy, and offers a cloud version for teams. Compared to Dify, Langflow offers a more flexible node-based interface with deeper LangChain integration.

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