# Search - [Text search](https://docs.searchagora.com/search/text-search.md) - [Query misspelling](https://docs.searchagora.com/search/query-misspelling.md) - [Query classification](https://docs.searchagora.com/search/query-classification.md) - [Query categorization](https://docs.searchagora.com/search/query-categorization.md) - [Deep search](https://docs.searchagora.com/search/deep-search.md) - [URL search](https://docs.searchagora.com/search/url-search.md): URL search is a 2 step process. First, you send the URL string to receive a slug id of the vectorized image on the page. Second, you use that id to get search results of similar products. - [Location search](https://docs.searchagora.com/search/location-search.md) - [Image search](https://docs.searchagora.com/search/image-search.md): Image search is a 2 step process. First, you send the image as a base64 encoded string to receive a slug id of the vectorized image. Second, you use that id to get search results of similar products. - [Detect objects](https://docs.searchagora.com/search/detect-objects.md) - [Store search](https://docs.searchagora.com/search/store-search.md) - [Brand search](https://docs.searchagora.com/search/brand-search.md) - [Product detail](https://docs.searchagora.com/search/product-detail.md) --- # 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://docs.searchagora.com/search.md?ask= ``` 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.