# Text Summary  (Deprecated)

The Text Summary API is a powerful tool designed to generate concise summaries from natural language text. This API utilizes pre-trained text summarization engines to extract essential information and condense lengthy passages into shorter, coherent summaries. The API allows developers to specify the minimum and maximum length of the generated summaries.

#### Pricing

Requests made to the Text Summary API are billed. Prices are based on the number of characters sent to the service to be summarized.

The pricing for API requests is as follows:

* **Per Request Cost**: 3 units base cost per request.

<mark style="color:green;">`POST`</mark> `https://api.autogon.ai/api/v1/services/text-summary/`

#### Headers

| Name                                           | Type   | Description      |
| ---------------------------------------------- | ------ | ---------------- |
| Content-Type<mark style="color:red;">\*</mark> | String | application/json |

#### Request Body

| Name                                   | Type    | Description                                                   |
| -------------------------------------- | ------- | ------------------------------------------------------------- |
| text<mark style="color:red;">\*</mark> | String  | The text to be summarized                                     |
| max\_length                            | Integer | Specifies the maximum length of the summary. Defaults to 130. |
| min\_length                            | Integer | Specifies the minimum length of the summary. Defaults to 30.  |

{% tabs %}
{% tab title="200: OK " %}

```json
```

{% endtab %}
{% endtabs %}


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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.autogon.ai/autogon-qore/natural-language-ai/text-summary-deprecated.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.
