Multimodal content

A user message can hold a list of content parts instead of a string. Check architecture.input_modalities of the model in /v1/models first: a part the model cannot read fails with 400 unsupported_modality.

Images

image_url.url takes an https URL or a data URI. detail is low, high or auto.

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.naga.ac/v1", api_key=os.environ["NAGAAI_API_KEY"])

completion = client.chat.completions.create(
    model="deepseek-v4.1-flash",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What is in this image? One sentence."},
            {"type": "image_url", "image_url": {"url": "https://media.naga.ac/outputs/6ab3444c-f19e-4944-80dc-d0b49c49c144.png"}},
        ],
    }],
)

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

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.naga.ac/v1", apiKey: process.env.NAGAAI_API_KEY });

const completion = await client.chat.completions.create({
  model: "deepseek-v4.1-flash",
  messages: [{
    role: "user",
    content: [
      { type: "text", text: "What is in this image? One sentence." },
      { type: "image_url", image_url: { url: "https://media.naga.ac/outputs/6ab3444c-f19e-4944-80dc-d0b49c49c144.png" } },
    ],
  }],
});

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

curl https://api.naga.ac/v1/chat/completions \
  -H "Authorization: Bearer $NAGAAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4.1-flash",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "What is in this image? One sentence."},
        {"type": "image_url", "image_url": {"url": "https://media.naga.ac/outputs/6ab3444c-f19e-4944-80dc-d0b49c49c144.png"}}
      ]
    }]
  }'

Files and PDFs

Send the file as a data URI in file_data, or as an https link in file_url, a NagaAI extension. NagaAI has no Files API, so a file_id fails with 400 file_id_unsupported.

Python

import base64

with open("report.pdf", "rb") as f:
    pdf = base64.b64encode(f.read()).decode()

completion = client.chat.completions.create(
    model="gpt-oss-120b",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Summarize this document in two sentences."},
            {"type": "file", "file": {"filename": "report.pdf", "file_data": f"data:application/pdf;base64,{pdf}"}},
        ],
    }],
)

Audio

input_audio.data is base64. A data: prefix fails with 400. format is wav, mp3, aiff, aac, ogg, flac, m4a, pcm16 or pcm24; the official API accepts only the first two.

Python

with open("question.mp3", "rb") as f:
    audio = base64.b64encode(f.read()).decode()

completion = client.chat.completions.create(
    model="gemini-3.7-flash",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Transcribe this and answer the question."},
            {"type": "input_audio", "input_audio": {"data": audio, "format": "mp3"}},
        ],
    }],
)

One inline part can be up to 20 MiB and the whole request up to 32 MiB.

Images in the answer

Models that draw return images in message.images, a list of {"type": "image_url", "image_url": {"url": "..."}} entries next to content. The url is a data: URI or an https link, so handle both. When you continue the conversation, send the assistant message back with its images so the model can edit the picture instead of drawing a new one.

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Images in the answer

​Images

​Files and PDFs

​Audio

​Images in the answer

Images

Files and PDFs

Audio

Images in the answer