> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nodesms.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Text Completions

> Create a text completion based on a given prompt. This is the legacy Completions endpoint, suitable for scenarios where you need the model to continue or complete text.

## Headers

**Authorization** `string` *required*

Bearer token authentication. Format: `Authorization: Bearer sk-xxxxxx`

## Body

Format: `application/json`

**model** `string` *required*

Model ID

**prompt** `string | string[]` *required*

Prompt text, can be a string or an array of strings

**max\_tokens** `integer`

Maximum number of tokens to generate

**temperature** `number`

Sampling temperature

**top\_p** `number`

Nucleus sampling parameter

**n** `integer`

Number of completions to generate

**stream** `boolean`

Whether to stream the response

**stop** `string | string[]`

Stop sequence(s)

**suffix** `string`

Suffix text for insertion

**echo** `boolean`

Whether to echo the prompt text in the output

## Response

### 200 Successfully created response

Format: `application/json`

> **TypeScript type definitions**
>
> ```ts theme={"dark"}
> interface CompletionResponse {
>   id?: string;
>   object?: string;
>   created?: number;
>   model?: string;
>   choices?: {
>     text?: string;
>     index?: number;
>     finish_reason?: string;
>   }[];
>   usage?: {
>     prompt_tokens?: number;
>     completion_tokens?: number;
>     total_tokens?: number;
>     prompt_tokens_details?: {
>       cached_tokens?: number;
>       text_tokens?: number;
>       audio_tokens?: number;
>       image_tokens?: number;
>     };
>     completion_tokens_details?: {
>       text_tokens?: number;
>       audio_tokens?: number;
>       reasoning_tokens?: number;
>     };
>   };
> }
> ```

**id** `string`

Completion ID

**object** `string`

Object type, value is `text_completion`

**created** `integer`

Creation timestamp

**model** `string`

Model ID

**choices** `object[]`

List of generated results

**Properties**

**text** `string`

Generated text

**index** `integer`

Result index

**finish\_reason** `string`

Finish reason

**usage** `object`

Token usage information

**Properties**

**prompt\_tokens** `integer`

Prompt token count

**completion\_tokens** `integer`

Completion token count

**total\_tokens** `integer`

Total token count

**prompt\_tokens\_details** `object`

Prompt token details

**Properties**

**cached\_tokens** `integer`

Cached token count

**text\_tokens** `integer`

Text token count

**audio\_tokens** `integer`

Audio token count

**image\_tokens** `integer`

Image token count

**completion\_tokens\_details** `object`

Completion token details

**Properties**

**text\_tokens** `integer`

Text token count

**audio\_tokens** `integer`

Audio token count

**reasoning\_tokens** `integer`

Reasoning token count

```bash cURL theme={"dark"}
curl -X POST "https://t.ato2.nodesms.com/v1/completions" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "string",
    "prompt": "string"
  }'
```

```python Python theme={"dark"}
import openai

client = openai.OpenAI(
    api_key="sk-xxxxxx",
    base_url="https://t.ato2.nodesms.com/v1"
)

response = client.completions.create(
    model="string",
    prompt="string"
)
print(response.choices[0].text)
```

```json 200 theme={"dark"}
{
  "id": "string",
  "object": "text_completion",
  "created": 0,
  "model": "string",
  "choices": [
    {
      "text": "string",
      "index": 0,
      "finish_reason": "string"
    }
  ],
  "usage": {
    "prompt_tokens": 0,
    "completion_tokens": 0,
    "total_tokens": 0,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "text_tokens": 0,
      "audio_tokens": 0,
      "image_tokens": 0
    },
    "completion_tokens_details": {
      "text_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0
    }
  }
}
```


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