# Documents

## Retrieving a Document

First, find the name of the knowledge that contains the document you wish to retrieve in the knowledge tab of Cortex.

<figure><img src="/files/TLq0tNyhDmETusOQLdk7" alt=""><figcaption></figcaption></figure>

Then, find the name of the documentID you want to retrieve.

<figure><img src="/files/eQFjVKW6bTqwZ9NMXDM5" alt=""><figcaption></figcaption></figure>

Use the knowledgeName and documentID with the `.getDocument` function of cortex to retrieve the document. See the Node.js Library for the exact .json return structure.

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

```javascript
try {
    const res = await cortex.getDocument('tigers','testing.txt')
    const document = res.data.document
    console.log(document.text);
} catch (error) {
    if (error.response) {
        console.log(error.response.status);
        console.log(error.response.data);
    } else {
        console.log(error.message);
    }
}
```

{% endtab %}

{% tab title="Python" %}

```python
CortexAPI.getDocument('tigers','testing.txt')
```

{% endtab %}
{% endtabs %}

## Uploading a Document

Find the knowledgeName of the desired location of the document.

Create an object that follows the createDocument interface to upload.

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

```javascript
interface createDocument {
  timestamp?: number;
  tags?: string[];
  text?: string | null;
  source_url?: string | null;
};
```

{% endtab %}

{% tab title="Python" %}

```python
class CreateDocument:
    def __init__(
        self,
        timestamp: Union[int, None] = None,
        tags:
        List[str] = None,
        text: Union[str, None] = None,
        source_url: Union[str, None] = None
    ):
        self.timestamp = timestamp
        self.tags = tags
        self.text = text
        self.source_url = source_url
```

{% endtab %}
{% endtabs %}

Use the documentID parameter to name the document you want to upload.

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

```javascript
const test = {
  "source_url": "https://www.test.com/",
  "text": "test"
  }

try {
  let output = await cortex.uploadDocument('tigers','test1',test);
  console.log(output.data.document);
} catch (error) {
  if (error.response) {
    console.log(error.response.status);
    console.log(error.response.data);
  } else {
    console.log(error.message);
  }
}
```

{% endtab %}

{% tab title="Python" %}

```python
test = cortex.CreateDocument()
test.source_url = "https://www.test.com/"
test.text = "test"

CortexAPI = cortex.CortexAPI("sk-...")
CortexAPI.uploadDocument('tigers','test1',test)
```

{% endtab %}
{% endtabs %}

## Deleting a Document

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

```javascript
try {
  let output = await cortex.deleteDocument('tigers','test1');
  console.log(output.data.document);
} catch (error:any) {
  if (error.response) {
    console.log(error.response.status);
    console.log(error.response.data);
  } else {
    console.log(error.message);
  }
}
```

{% endtab %}

{% tab title="Python" %}

```python
CortexAPI.deleteDocument('tigers','test1')
```

{% endtab %}
{% endtabs %}


---

# 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.trycortex.ai/guides/documents.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.