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langflow-ui-clarity

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Mendon Kissling 2024-06-06 17:02:50 -04:00
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docs/docs/tutorials/rag-with-astradb.mdx
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@ -13,7 +13,7 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the
<Admonition type="tip">
This guide assumes that you have Langflow up and running. If you are new to
Langflow, you can check out the [Getting Started](/) guide.
Langflow, you can check out the [Getting Started](../getting-started/install-langflow.mdx) guide.
</Admonition>
TLDR;
@ -75,9 +75,11 @@ Now we are all set to start building our RAG application using Astra DB and Lang
If you haven't already, now is the time to launch Langflow. To make things easier, you can duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) which sets up a Langflow instance just for you.
## Open the Vector Store RAG Project
## Open the Vector Store RAG Project in Langflow
To get started, click on the **New Project** button and look for the **Vector Store RAG** project. This will open a starter project with the necessary components to run a RAG application using Astra DB.
Run Langflow and open the UI.
In the Langflow dashboard, click the **New Project** button and select the **Vector Store RAG** project. This will open a starter project with the necessary components to run a RAG application using Astra DB.
This project consists of two flows. The simpler one is the **Ingestion Flow** which is responsible for ingesting the documents into the Astra DB database.