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

# Search query expansion

## Overview

In this example, we will demonstrate how to leverage the enums and typed arrays
to segment a complex search prompt into multiple, better structured queries that
can be executed separately against specialized APIs or search engines.

## Why it matters

Extracting a list of tasks from text is a common use case for leveraging language
models. This pattern can be applied to various applications, such as virtual
assistants like Siri or Alexa, where understanding user intent and breaking down
requests into actionable tasks is crucial. In this example, we will demonstrate
how to use Instructor to segment search queries, so you can execute them separately
against specialized APIs or search engines.

## Structure of the data

The `SearchQuery` is a PHP class that defines the structure of an individual
search query.

It has three fields: `title`, `query`, and `type`. The `title` field is the title
of the request, the `query` field is the query to search for relevant content, and
the `type` field is the type of search. The `execute` method is used to execute the
search query.

## Example

```php theme={null}
<?php
require 'examples/boot.php';

use Cognesy\Instructor\StructuredOutput;

enum SearchType : string {
    case TEXT = "text";
    case IMAGE = "image";
    case VIDEO = "video";
}

class Search
{
    /** @var SearchQuery[] */
    public array $queries = [];
}

class SearchQuery
{
    public string $title;
    /**  Rewrite query for a search engine */
    public string $query;
    /** Type of search - image, video or text */
    public SearchType $type;

    public function execute() {
        // ... write actual search code here
        print("Searching for `{$this->title}` with query `{$this->query}` using `{$this->type->value}`\n");
    }
}
?>
```

## Segmenting the Search Prompt

The `segment` function takes a string `data` and segments it into multiple search queries.

It uses the `StructuredOutput::create()` method to extract the data into the target object.
The `responseModel` parameter specifies `Search::class` as the model to use for extraction.

```php theme={null}
<?php
function segment(string $data) : Search {
    return StructuredOutput::using('openai')
        ->withMessages("Consider the data below: '\n$data' and segment it into multiple search queries")
        ->withResponseClass(Search::class)
        ->get();
}

$search = segment("Find a picture of a cat and a video of a dog");
foreach ($search->queries as $query) {
    $query->execute();
}
// Results:
// Searching with query `picture of a cat` using `image`
// Searching with query `video of a dog` using `video`

assert(count($search->queries) === 2);
?>
```