---
title: "Text search"
slug: "text-search"
updated: 2025-10-08T10:32:58Z
published: 2025-10-08T10:32:58Z
canonical: "docs.akridata.ai/text-search"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.akridata.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Text search

Vision Copilot provides various visual input-based search techniques, including full-image search, patch search, and full-object search. Text search augments these capabilities with support for free-form text inputs.

1. A dataset will get text search capability through a pre-registered pipeline named **'AkridataImageClipPipeline'**(for the Image data type) and **'AkridataVideoClipPipeline'**(for the Video data type). Read the [article](/data-explorer/docs/pipelines-and-dockers) to learn more about pipelines.
2. The corresponding pipeline must be attached to the dataset. Read the [article](/data-explorer/docs/pipeline-dataset-attachdetach-operations) to learn more about pipeline attachments to datasets.
3. The pipeline must be run to produce features that allow text search. Read the [article](/data-explorer/docs/dataset-pipeline-operations) to learn more about executing a pipeline.
4. The text feature pipeline will populate a catalog on the dataset catalog page. Read the [article](/data-explorer/docs/catalog) to learn more about catalog operations.

## Create a Visualization Job with Text Search

To create a job with text search capabilities, follow the steps below.

1. On the Dataset page, click the **Catalog** button to open the catalog page. Note that in the catalog page, the default pipeline is set to “all_pipeline_tables”. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/pascal-job.jpg)
2. Click **Visualize** to create a visualization job. Refer to the article [Create an explore job](https://docs.akridata.ai/docs/create-an-explore-job) for the detailed steps. Once the job is created, note that the job card indicates “Text search supported” by default. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/job-text-search-support.jpg)

## Create a View for Text Search

The **all_pipeline_tables**view described above supports text search and is created by default for every dataset. The below section describes creating a custom view with text search support.

1. Create a view that joins the catalog table from a pipeline that ingested image features and the text-search capable pipeline. The file_id and frame_idx_in_file fields must be used to join the catalog tables. Read the [article](/data-explorer/docs/catalog-views-1) to learn more about catalog views.
  - The screenshot below shows two pipeline tables that can be used to create a view that supports text search jobs.

![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/AkriData%20(12).png)
  - Create a view with file_id and frame_idx_in_file as the join columns. The 'frame_idx_in_file' column is not needed for the image type of the dataset. [Embedded content](https://akridata-ai.portal.trainn.co/share/RYFtYWKO1O7f8IwBcz5bBQ/embed)
2. Once the view is created, run the catalog query and create a visualize job.
  1. The icon highlighted below can identify a job with text search support.

![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/job-for-text-search.jpg)
  2. The job visualization shows a **'Text Search'** tab shown below.

![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/text-search-tab.jpg)

## Perform Text Search on the Job

1. On the job page, type text prompt search as per the following steps:
  1. Enter text prompt.
  2. Enter the required number of results.
  3. Optionally select the filters and tunables to further reduce the search space. Refer to the [article](/data-explorer/docs/search-space-reduction) for details about tunables and filters.
  4. Click the **'Search'** button. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/text-search-parameters.jpg)
2. Use the following controls on the text search results:
  1. Group Images: For Video datasets, successive images that are expected to be similar can be grouped together using this control to reduce redundancy in the results. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/group-images.jpg)
  2. Sim score settings: You can view the sim search match score and filter results above a threshold score. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/text-search-settings.jpg)
  3. Highlight points: View the results on a 2D plot that shows the relative position of the results in the content feature space. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/plot-image.jpg)