# Vector Search

## What is Vector Search?

Vector search is a search method which returns the result which are close to your search query in multi dimensional space.

## Difference between Full Text Search (FTS) and Vector Search

The basic difference between Full Text search and Vector Search is that it in FTS it returns only data based on the text-matches, whereas in Vector Search you get the result which are close to the vectors in multi-dimensional field. 

## Concepts

### Vector

A vector is a 1-D numerical array that represents data across multiple dimensions. Vectors can encapsulate various types of data, including text, images, audio, and unstructured data. Semantic similarity between vectors is assessed by calculating the distance between them.

### Vector Embedding

Vector Embedding also known as vectorization is the process of converting the data into vectors.

### Embedding Model

The LLM Models which convert normal data to Vector Embedding, for example OpenAI GPT model, AWS Bedrock, Google Gemini AI, etc.

## Useful links

* [Create a Vector Search Index on Cosmocloud](/resources/vector-search/create-a-vector-search-index.md)
* [Edit a Vector Search Index](/resources/vector-search/edit-a-vector-search-index.md)
* [Delete a Vector Search Index](/resources/vector-search/delete-a-vector-search-index.md)


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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://docs.cosmocloud.io/resources/vector-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.