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

# Multimodal Content

> Send text, images, files, and audio through the Chat Completions compatibility layer.

`Chat Completions API` accepts either plain string message content or arrays of typed content blocks.

Use this when you already depend on chat-style `messages[]` but still need images, PDFs, or audio in the same request.

## Supported Content Blocks

| Block type    | Shape                                                                          | Notes                                                                              |
| ------------- | ------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------- |
| `text`        | `{ "type": "text", "text": "..." }`                                            | Plain text                                                                         |
| `image_url`   | `{ "type": "image_url", "image_url": { "url": "...", "detail": "auto" } }`     | `url` accepts `http`, `https`, or `data`; `detail` can be `low`, `high`, or `auto` |
| `file`        | `{ "type": "file", "file": { "filename": "...", "file_data": "..." } }`        | `file_data` accepts `http`, `https`, or `data`                                     |
| `input_audio` | `{ "type": "input_audio", "input_audio": { "data": "...", "format": "wav" } }` | `data` must be raw base64, not a data URI; common formats include `wav` and `mp3`  |

## When to use this surface

* you already have chat-based client code and want to keep it
* you need multimodal inputs but do not want to migrate to Responses yet

If you are starting from scratch, `Responses API` is usually the cleaner multimodal path.

## Image Example

<CodeGroup>
  ```python Python theme={null}
  from openai import OpenAI

  client = OpenAI(
      base_url="https://api.naga.ac/v1",
      api_key="YOUR_API_KEY",
  )

  completion = client.chat.completions.create(
      model="gpt-4o-mini",
      messages=[
          {
              "role": "user",
              "content": [
                  {"type": "text", "text": "Describe this image briefly."},
                  {
                      "type": "image_url",
                      "image_url": {
                          "url": "https://example.com/receipt.png",
                          "detail": "auto",
                      },
                  },
              ],
          }
      ],
  )

  print(completion.choices[0].message.content)
  ```

  ```javascript Node.js theme={null}
  import OpenAI from 'openai';

  const client = new OpenAI({
    baseURL: 'https://api.naga.ac/v1',
    apiKey: 'YOUR_API_KEY',
  });

  const completion = await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Describe this image briefly.' },
          {
            type: 'image_url',
            image_url: {
              url: 'https://example.com/receipt.png',
              detail: 'auto',
            },
          },
        ],
      },
    ],
  });

  console.log(completion.choices[0].message.content);
  ```

  ```bash cURL theme={null}
  curl https://api.naga.ac/v1/chat/completions \
    -H "Authorization: Bearer YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "model": "gpt-4o-mini",
      "messages": [
        {
          "role": "user",
          "content": [
            { "type": "text", "text": "Describe this image briefly." },
            {
              "type": "image_url",
              "image_url": {
                "url": "https://example.com/receipt.png",
                "detail": "auto"
              }
            }
          ]
        }
      ]
    }'
  ```
</CodeGroup>

## File Example

<CodeGroup>
  ```python Python theme={null}
  from openai import OpenAI

  client = OpenAI(
      base_url="https://api.naga.ac/v1",
      api_key="YOUR_API_KEY",
  )

  completion = client.chat.completions.create(
      model="gpt-5",
      messages=[
          {
              "role": "user",
              "content": [
                  {"type": "text", "text": "Summarize this PDF."},
                  {
                      "type": "file",
                      "file": {
                          "filename": "report.pdf",
                          "file_data": "https://example.com/report.pdf",
                      },
                  },
              ],
          }
      ],
  )

  print(completion.choices[0].message.content)
  ```

  ```javascript Node.js theme={null}
  import OpenAI from 'openai';

  const client = new OpenAI({
    baseURL: 'https://api.naga.ac/v1',
    apiKey: 'YOUR_API_KEY',
  });

  const completion = await client.chat.completions.create({
    model: 'gpt-5',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Summarize this PDF.' },
          {
            type: 'file',
            file: {
              filename: 'report.pdf',
              file_data: 'https://example.com/report.pdf',
            },
          },
        ],
      },
    ],
  });

  console.log(completion.choices[0].message.content);
  ```

  ```bash cURL theme={null}
  curl https://api.naga.ac/v1/chat/completions \
    -H "Authorization: Bearer YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "model": "gpt-5",
      "messages": [
        {
          "role": "user",
          "content": [
            { "type": "text", "text": "Summarize this PDF." },
            {
              "type": "file",
              "file": {
                "filename": "report.pdf",
                "file_data": "https://example.com/report.pdf"
              }
            }
          ]
        }
      ]
    }'
  ```
</CodeGroup>

## Audio Example

<CodeGroup>
  ```python Python theme={null}
  from openai import OpenAI

  client = OpenAI(
      base_url="https://api.naga.ac/v1",
      api_key="YOUR_API_KEY",
  )

  completion = client.chat.completions.create(
      model="gemini-2.5-flash",
      messages=[
          {
              "role": "user",
              "content": [
                  {"type": "text", "text": "Tell me what is said in this audio."},
                  {
                      "type": "input_audio",
                      "input_audio": {
                          "data": "BASE64_AUDIO",
                          "format": "wav",
                      },
                  },
              ],
          }
      ],
  )

  print(completion.choices[0].message.content)
  ```

  ```javascript Node.js theme={null}
  import OpenAI from 'openai';

  const client = new OpenAI({
    baseURL: 'https://api.naga.ac/v1',
    apiKey: 'YOUR_API_KEY',
  });

  const completion = await client.chat.completions.create({
    model: 'gemini-2.5-flash',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Tell me what is said in this audio.' },
          {
            type: 'input_audio',
            input_audio: {
              data: 'BASE64_AUDIO',
              format: 'wav',
            },
          },
        ],
      },
    ],
  });

  console.log(completion.choices[0].message.content);
  ```

  ```bash cURL theme={null}
  curl https://api.naga.ac/v1/chat/completions \
    -H "Authorization: Bearer YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "model": "gemini-2.5-flash",
      "messages": [
        {
          "role": "user",
          "content": [
            { "type": "text", "text": "Tell me what is said in this audio." },
            {
              "type": "input_audio",
              "input_audio": {
                "data": "BASE64_AUDIO",
                "format": "wav"
              }
            }
          ]
        }
      ]
    }'
  ```
</CodeGroup>

## Caveats

* `input_audio.data` must be raw base64, not a `data:` URL
* multimodal support still depends on the selected model
* use the direct [Audio API](/api/audio) for transcription, translation, and text-to-speech
* use the direct [Images API](/api/images) for primary image generation and image edit workflows

## Common mistakes

* mixing chat content-block syntax with Responses input-part syntax
* assuming every model supports every multimodal block type
* using this surface for dedicated audio or image workflows that belong on the direct APIs

## Related Docs

* [Capability-level Multimodal Inputs](/build/multimodal-inputs)
* [Chat Completions API](/api/chat-completions)
* [Create chat completion](/api-reference/endpoints/chat/completions)