# Query Engine

A query engine serves as an end-to-end pipeline enabling users to ask questions about their data. It receives a natural language query and furnishes a response, accompanied by relevant context information retrieved and passed to the LLM (Large Language Model).

<figure><img src="/files/rUSXRWqjJI3IEd664iRm" alt=""><figcaption></figcaption></figure>

## Inputs

* Vector Store Retriever
* [Response Synthesizer](/integrations/llamaindex/response-synthesizer.md)

## Parameters

| Name                    | Description                                                         |
| ----------------------- | ------------------------------------------------------------------- |
| Return Source Documents | To return citations/sources that were used to build up the response |

## Outputs

| Name        | Description                   |
| ----------- | ----------------------------- |
| QueryEngine | Final node to return response |


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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.flowiseai.com/integrations/llamaindex/engine/query-engine.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.