
Langflow is a low-code platform for building, configuring, and deploying agentic and retrieval-augmented generation applications using Python with various large language models and vector databases.
Langflow is a low-code platform for designing, building, and deploying agentic and retrieval-augmented generation (RAG) applications. It provides a visual interface for composing complex AI workflows while allowing developers to integrate custom Python code where needed. The primary purpose of Langflow is to help teams rapidly prototype and operationalize AI agents and RAG pipelines using any large language model (LLM) or vector database of their choice.
The tool offers a drag-and-drop flow editor for chaining together LLMs, vector stores, tools, prompts, and data sources into reusable components. Developers can extend flows with Python nodes, enabling fine-grained control over logic, data transformations, and integrations with external APIs or services. Langflow supports multiple LLM providers and vector databases, making it suitable for heterogeneous infrastructure and avoiding lock-in. Versioning, configuration management, and environment support help move from experimentation to production with greater reliability and traceability.
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