Langflow is a visual way to build, iterate, and deploy AI applications. Its intuitive interface allows for easy manipulation of AI building blocks, enabling developers to quickly prototype and turn their ideas into powerful, real-world solutions.

A single Langflow "flow" could contain multiple Langchain chat components, a Llama language model, an Astra vector store, and a Redis cache. You can build any AI flow you can think of with Langflow, but how can you be confident that these components are up-to-date and compatible with your project?

Using the ragstack-ai-langflow package solves this problem. It provides the intuitive flow building of Langflow, with components tested for compatibility, performance, and security with RAGStack.

Install Langflow

  1. Install the ragstack-ai-langflow package.

    pip install ragstack-ai-langflow
  2. Start Langflow.

    • Bash

    • Result

    langflow run
    │ Welcome to ⛓ Langflow                             │
    │                                                   │
    │ Access                      │
    │ Collaborate, and contribute at our GitHub Repo 🚀 │

    A browser window will open with the Langflow interface.

    You can now access Langflow at

  3. To create a new project, click New Project.

  4. Select Blank Flow to start with a blank canvas, or select one of the Starter Projects to try a pre-built flow. We recommend the Basic Prompting project to get started.

The ragstack-ai-langflow package

The ragstack-ai-langflow package contains a curated set of dependencies for using Langflow with Astra DB and all the supported integrations by ragstack-ai-langchain.

All the Langflow’s builtin integrations are included in the ragstack-ai-langflow package.

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