Qdrant Vector Database Integration
This guide walks you through configuring a Retrieval-Augmented Generation (RAG) pipeline in Vectorize using Qdrant as the vector database.
Before you Begin
Ensure you have:
- A Vectorize account (Create one free here ↗ )
- A Qdrant cluster.
Configure the integration
To configure a vector database integration to connect to your Qdrant instance:
-
Click Vector Databases from the main menu.
-
Click New Vector Database Integration from the Vector Databases page.
-
Select the Qdrant card.
-
Enter the parameters in the form using the Qdrant Parameters table below as a guide, then click Create Qdrant Integration.
Qdrant Parameters
| Field | Description | Required |
|---|---|---|
| Name | A descriptive name to identify the integration within Vectorize. | Yes |
| Host | The Qdrant cluster's endpoint. | Yes |
| API key | The Qdrant cluster's API key. | Yes |
Configuring the Qdrant integration in a RAG Pipeline
You can think of the Qdrant integration as having two parts to it. The first is authorization with your Qdrant cluster. This part is re-usable across pipelines and allows you to connect to this same application in different pipelines without providing the credentials every time.
The second part is the configuration that's specific to your RAG Pipeline. This is where you specify the name of the collection in your Qdrant database. If the collection does not already exist, Vectorize will create it for you.
Enter your collection name to complete configuration of your Qdrant integration for your RAG pipeline.
What's next?
-
If you haven't yet built a connector to your source database, go to configure a source connector and select your source data platform.
OR
-
If you're ready to start creating pipelines for vectorizing data, head to Pipeline Basics.