Langflow is an open source visual environment for designing and prototyping AI workflows and agents. It provides a drag and drop canvas where users connect components such as models, prompts, memory, data loaders, and tools into working pipelines. Built around popular language model libraries, it lets builders experiment with retrieval, chaining, and agent logic while seeing the flow structure visually. Langflow can be run locally or self hosted, and completed flows can be exported or served as APIs for integration into applications and other systems.
The tool is designed for developers, data scientists, and technical teams who want a faster way to iterate on LLM pipelines than writing everything in raw code. It fits people building chat assistants, document question answering, and multi step agent flows who value being able to inspect and adjust each component. Because it is open source and Python based, it appeals to teams that want customization and the ability to extend components. Its visual approach also helps in prototyping and sharing designs across collaborators before committing to production code.
In practice, users place components on a canvas, connect their inputs and outputs, and run flows to test behavior interactively. Flows can incorporate vector stores, custom Python components, and multiple models. Finished designs are exported as code or exposed through an API for use elsewhere.
