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The Local UI is available at http://localhost:6575 once the VectorAI DB Docker container is running. No login is required for local deployments. See Docker setup if you need to start the container first. Screen shot showing VectorAI DB dashboard

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Dashboard sections

SectionDescription
ConsoleExecute REST API calls and inspect raw responses.
CollectionsBrowse, manage, and search your vector collections.

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Console

The Console lets you run ad-hoc REST API requests, test queries, and inspect JSON responses alongside HTTP status codes — all from the browser.

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Collections

The Collections section gives you a visual overview of all collections in VectorAI DB.
  • View all existing collections and their configuration.
  • Inspect vector count, dimension size, and distance metric for each collection.
  • Browse individual vectors and their associated payloads.
  • Run similarity searches against a collection using a vector or an existing record’s ID.
  • Delete collections you no longer need.

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Browsing vectors

Select any collection to open its detail view: a paginated table of stored vectors with their payload fields. Filter by payload values to locate specific entries.
1

Open a collection

Select the collection you want to search from the Collections list.
2

Go to the Search tab

Click the Search tab within the collection detail view.
3

Enter a query vector

Enter a JSON array representing your query vector in the input field.
4

Set search parameters

Configure top_k to control how many results to return. Optionally apply payload filters to narrow results.
5

Run the search

Click Search to execute. Results appear ranked by similarity score, with each result showing its ID, score, and payload.

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Next steps

Python SDK

Install and configure the Python SDK.

REST API

Explore the full REST API reference.

Core concepts

Understand the data model, architecture, and how search works.

Troubleshooting

Resolve common issues with VectorAI DB.