# Smart Search

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**Welcome to Our New API Docs!** This is the new home for all things API (previously at [Canvas LMS REST API Documentation](https://api.instructure.com)).
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## Smart Search API

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BETA: This API resource is not finalized, and there could be breaking changes before its final release.
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API for AI-powered course content search. NOTE: This feature has limited availability at present.

**A SearchResult object looks like:**

```js
// Reference to an object that matches a smart search
{
  // The ID of the matching object.
  "content_id": 2,
  // The type of the matching object.
  "content_type": "WikiPage",
  // The title of the matching object.
  "title": "Nicolaus Copernicus",
  // The body of the matching object.
  "body": "Nicolaus Copernicus was a Renaissance-era mathematician and astronomer who...",
  // The Canvas URL of the matching object.
  "html_url": "https://canvas.example.com/courses/123/pages/nicolaus-copernicus",
  // The distance between the search query and the result. Smaller numbers
  // indicate closer matches.
  "distance": 0.212
}
```

### [Search course content](#method.smart_search.search) <a href="#method.smart_search.search" id="method.smart_search.search"></a>

[SmartSearchController#search](https://github.com/instructure/canvas-lms/blob/master/app/controllers/smart_search_controller.rb)

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BETA: This API endpoint is not finalized, and there could be breaking changes before its final release.
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**`GET /api/v1/courses/:course_id/smartsearch`**

**Scope:** `url:GET|/api/v1/courses/:course_id/smartsearch`

Find course content using a meaning-based search

**Request Parameters:**

| Parameter   | Type              | Description                                                                                                                                                                                                                                                                                                                                            |
| ----------- | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `q`         | Required `string` | The search query                                                                                                                                                                                                                                                                                                                                       |
| `filter[]`  | `string`          | Types of objects to search. By default, all supported types are searched. Supported types include `pages`, `assignments`, `announcements`, and `discussion_topics`.                                                                                                                                                                                    |
| `include[]` | `string`          | <p>Optional information to include with each search result:</p><p><br></p><ul><li><p>modules</p><p>An array of module objects that the search result belongs to.</p></li><li><p>status</p><p>The published status for all results and the due\_date for all assignments.</p></li></ul><p>Allowed values: <code>status</code>, <code>modules</code></p> |

Returns a list of [SearchResult](#searchresult) objects.

***

This documentation is generated directly from the Canvas LMS source code, available [on Github](https://github.com/instructure/canvas-lms).


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://developerdocs.instructure.com/services/canvas/resources/smart_search.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.