# Query a Vector Search Index

> Query a Vector Search Index activity in the Databricks connector.

## Project compatibility

Windows | Cross-platform

## Overview

| Description | API Method | API Path |
| --- | --- | --- |
| Run a similarity search against a Databricks Vector Search index and return the matching rows. | POST | `/vector-search/indexes/{index_name}/query` |

## Input

| Parameter | Description | Data Type |
| --- | --- | --- |
| Index Name \* | Full three-level name of the Vector Search index, for example `catalog.schema.index`. | string |
| Columns \* | Columns to return for each match. For example, `["id", "title", "url"]`. | array |
| Query Text | Text query; for indexes with a Databricks-computed embedding. For example, `How do I reset my password?`. | string |
| Query Vector | Raw embedding vector; for self-managed embeddings. For example, `[0.12, 0.84, -0.33]`. | array |
| Number of Results | Number of matches to return. For example, `10`. Default: `10`. | integer |
| Filters JSON | JSON filter expression applied before the search. For example, `{"category": "support"}`. | string |
| Query Type | Type of search to run against the index, for example `ANN` or `HYBRID`. Allowed values: `ANN`, `HYBRID`. | string |
| Score Threshold | Minimum similarity score a match must reach to be returned. For example, `0.7`. | number |

\* Required parameter.

## Output

| Parameter | Description | Data Type |
| --- | --- | --- |
| Result | Matches under result.data_array, ordered by score. | object |
| Manifest | Column schema of the result set. | object |

:::note
You might see variations in the output depending on where you run the activity. In API workflows and Maestro Flow, a single response object containing all the fields is returned. In RPA workflows, not all fields are exposed, but you can still retrieve them from the exposed response object.
:::