> For the complete documentation index, see [llms.txt](https://docs.flowiseai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.flowiseai.com/espanol/documentacion-oficial/integraciones/llamaindex/engine/query-engine.md).

# Query Engine

Un query engine sirve como un pipeline de extremo a extremo que permite a los usuarios hacer preguntas sobre sus datos. Recibe una consulta en lenguaje natural y proporciona una respuesta, acompañada de información contextual relevante recuperada y enviada al LLM (Large Language Model).

<figure><img src="/files/I8ize4QZUpMUPd7AviiQ" alt=""><figcaption></figcaption></figure>

## Entradas

* Vector Store Retriever
* [Response Synthesizer](/espanol/documentacion-oficial/integraciones/llamaindex/response-synthesizer.md)

## Parámetros

| Nombre                  | Descripción                                                           |
| ----------------------- | --------------------------------------------------------------------- |
| Return Source Documents | Para devolver citas/fuentes que se usaron para construir la respuesta |

## Salidas

| Nombre      | Descripción                           |
| ----------- | ------------------------------------- |
| QueryEngine | Nodo final para devolver la respuesta |


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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/espanol/documentacion-oficial/integraciones/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.