> For the complete documentation index, see [llms.txt](https://docs.rememberizer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rememberizer.ai/es/recursos-para-desarrolladores/api-docs/vector-store/get-a-list-of-documents-in-a-vector-store.md).

# Obtener una lista de documentos en un Almacén de Vectores

{% openapi src="/files/5V7ybptH1vsfKadO6dio" path="/vector-stores/{vector-store-id}/documents" method="get" %}
[rememberizer\_openapi.yml](https://983989491-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FeFTiuIsKOMpUEE73g7bP%2Fuploads%2Fgit-blob-77b6137eeb641262ec8e531c78123c02b825b865%2Frememberizer_openapi.yml?alt=media\&token=03079f98-60fe-4914-9e1b-443e008fd108)
{% endopenapi %}

## Ejemplos de Solicitudes

{% tabs %}
{% tab title="cURL" %}

```bash
curl -X GET \
  https://api.rememberizer.ai/api/v1/vector-stores/vs_abc123/documents \
  -H "x-api-key: TU_API_KEY"
```

{% hint style="info" %}
Reemplaza `TU_API_KEY` con tu clave API real de Vector Store y `vs_abc123` con tu ID de Vector Store.
{% endhint %}
{% endtab %}

{% tab title="JavaScript" %}

```javascript
const getVectorStoreDocuments = async (vectorStoreId) => {
  const response = await fetch(`https://api.rememberizer.ai/api/v1/vector-stores/${vectorStoreId}/documents`, {
    method: 'GET',
    headers: {
      'x-api-key': 'TU_API_KEY'
    }
  });
  
  const data = await response.json();
  console.log(data);
};

getVectorStoreDocuments('vs_abc123');
```

{% hint style="info" %}
Reemplaza `TU_API_KEY` con tu clave API real de Vector Store y `vs_abc123` con tu ID de Vector Store.
{% endhint %}
{% endtab %}

{% tab title="Python" %}

```python
import requests

def get_vector_store_documents(vector_store_id):
    headers = {
        "x-api-key": "TU_API_KEY"
    }
    
    response = requests.get(
        f"https://api.rememberizer.ai/api/v1/vector-stores/{vector_store_id}/documents",
        headers=headers
    )
    
    data = response.json()
    print(data)

get_vector_store_documents('vs_abc123')
```

{% hint style="info" %}
Reemplaza `TU_API_KEY` con tu clave API real de Vector Store y `vs_abc123` con tu ID de Vector Store.
{% endhint %}
{% endtab %}
{% endtabs %}

## Parámetros de Ruta

| Parámetro       | Tipo   | Descripción                                                                |
| --------------- | ------ | -------------------------------------------------------------------------- |
| vector-store-id | string | **Requerido.** El ID de la tienda de vectores de la que listar documentos. |

## Formato de Respuesta

```json
[
  {
    "id": 1234,
    "name": "Manual del Producto.pdf",
    "type": "application/pdf",
    "vector_store": "vs_abc123",
    "size": 250000,
    "status": "indexed",
    "processing_status": "completed",
    "indexed_on": "2023-06-15T10:30:00Z",
    "status_error_message": null,
    "created": "2023-06-15T10:15:00Z",
    "modified": "2023-06-15T10:30:00Z"
  },
  {
    "id": 1235,
    "name": "Especificaciones Técnicas.docx",
    "type": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
    "vector_store": "vs_abc123",
    "size": 125000,
    "status": "indexed",
    "processing_status": "completed",
    "indexed_on": "2023-06-15T11:45:00Z",
    "status_error_message": null,
    "created": "2023-06-15T11:30:00Z",
    "modified": "2023-06-15T11:45:00Z"
  }
]
```

## Autenticación

Este endpoint requiere autenticación utilizando una clave API en el encabezado `x-api-key`.

## Respuestas de Error

| Código de Estado | Descripción                                       |
| ---------------- | ------------------------------------------------- |
| 401              | No autorizado - Clave API inválida o faltante     |
| 404              | No encontrado - Almacén de vectores no encontrado |
| 500              | Error interno del servidor                        |

Este endpoint recupera una lista de todos los documentos almacenados en el almacén de vectores especificado. Proporciona metadatos sobre cada documento, incluyendo el estado de procesamiento del documento, tamaño y marca de tiempo indexada. Esta información es útil para monitorear el contenido de su almacén de vectores y verificar el estado de procesamiento de los documentos.


---

# 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, and the optional `goal` query parameter:

```
GET https://docs.rememberizer.ai/es/recursos-para-desarrolladores/api-docs/vector-store/get-a-list-of-documents-in-a-vector-store.md?ask=<question>&goal=<endgoal>
```

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`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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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.