Vision

Models that support vision can accept images alongside text in messages[].content. Provide one or more image_url parts, optionally with a detail hint, and the model will describe, read, or reason about the visual content.

Endpoint: POST https://api.aifoundryhub.com/v1/chat/completions

---

Quick start — describe an image

curl

curl -X POST "https://api.aifoundryhub.com/v1/chat/completions" \
  -H "Authorization: Bearer $AI_FOUNDRY_HUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5",
    "max_tokens": 200,
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "Describe this room in two sentences." },
          { "type": "image_url", "image_url": { "url": "https://images.example.com/living-room.jpg", "detail": "auto" } }
        ]
      }
    ]
  }'

node.js

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.AI_FOUNDRY_HUB_API_KEY,
  baseURL: "https://api.aifoundryhub.com/v1",
});

const resp = await client.chat.completions.create({
  model: "gpt-5",
  max_tokens: 200,
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "Describe this room in two sentences." },
        { type: "image_url", image_url: { url: "https://images.example.com/living-room.jpg", detail: "auto" } }
      ]
    }
  ]
});

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

go

package main

import (
  "context"
  "fmt"
  "os"

  openai "github.com/openai/openai-go"
  "github.com/openai/openai-go/option"
)

func main() {
  client := openai.NewClient(
    option.WithAPIKey(os.Getenv("AI_FOUNDRY_HUB_API_KEY")),
    option.WithBaseURL("https://api.aifoundryhub.com/v1"),
  )

  ctx := context.Background()
  params := openai.ChatCompletionNewParams{
    Model: "gpt-5",
    Messages: []openai.ChatCompletionMessageParamUnion{{
      OfUser: &openai.ChatCompletionUserMessageParam{
        Content: openai.ChatCompletionUserMessageParamContentUnion{
          OfArrayOfContentParts: []openai.ChatCompletionContentPartUnionParam{
            {OfText: &openai.ChatCompletionContentPartTextParam{Type: "text", Text: "What's in this image?"}},
            {OfImageURL: &openai.ChatCompletionContentPartImageParam{
              Type: "image_url",
              ImageURL: openai.ChatCompletionContentPartImageImageURLParam{
                URL: "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
              },
            }},
          },
        },
      }},
  }
  resp, err := client.Chat.Completions.New(ctx, params)
  if err != nil {
    panic(err)
  }
  if len(resp.Choices) > 0 && len(resp.Choices[0].Message.Content) > 0 {
    fmt.Println(resp.Choices[0].Message.Content[0])
  }
}

python

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("AI_FOUNDRY_HUB_API_KEY"),
    base_url="https://api.aifoundryhub.com/v1",
)

resp = client.chat.completions.create(
    model="gpt-5",
    max_tokens=200,
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Describe this room in two sentences."},
            {"type": "image_url", "image_url": {"url": "https://images.example.com/living-room.jpg", "detail": "auto"}}
        ]
    }]
)

print(resp.choices[0].message.content[0].text)

Tip: detail: "high" is best for small text (fine print). Use detail: "low" when speed/cost matter more than precision.

---

Multi-image reasoning

Pass several image_url parts in a single message to compare or reason across images.

curl

curl -X POST "https://api.aifoundryhub.com/v1/chat/completions" \
  -H "Authorization: Bearer $AI_FOUNDRY_HUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5",
    "messages": [{
      "role": "user",
      "content": [
        {"type":"text","text":"Are these outfits the same color palette? Explain differences."},
        {"type":"image_url","image_url":{"url":"https://images.example.com/look1.jpg"}},
        {"type":"image_url","image_url":{"url":"https://images.example.com/look2.jpg"}}
      ]
    }]
  }'

node.js

const out = await client.chat.completions.create({
  model: "gpt-5",
  messages: [{
    role: "user",
    content: [
      { type: "text", text: "Are these outfits the same color palette? Explain differences." },
      { type: "image_url", image_url: { url: "https://images.example.com/look1.jpg" } },
      { type: "image_url", image_url: { url: "https://images.example.com/look2.jpg" } },
    ]
  }]
});
console.log(out.choices[0].message.content[0].text);

python

resp = client.chat.completions.create(
    model="gpt-5",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Are these outfits the same color palette? Explain differences."},
            {"type": "image_url", "image_url": {"url": "https://images.example.com/look1.jpg"}},
            {"type": "image_url", "image_url": {"url": "https://images.example.com/look2.jpg"}},
        ]
    }]
)
print(resp.choices[0].message.content[0].text)

go

package main

import (
  "context"
  "fmt"
  "os"

  openai "github.com/openai/openai-go"
  "github.com/openai/openai-go/option"
)

func main() {
  client := openai.NewClient(
    option.WithAPIKey(os.Getenv("AI_FOUNDRY_HUB_API_KEY")),
    option.WithBaseURL("https://api.aifoundryhub.com/v1"),
  )

  ctx := context.Background()
  params := openai.ChatCompletionNewParams{
    Model: "gpt-5",
    Messages: []openai.ChatCompletionMessageParamUnion{{
      OfUser: &openai.ChatCompletionUserMessageParam{
        Content: openai.ChatCompletionUserMessageParamContentUnion{
          OfArrayOfContentParts: []openai.ChatCompletionContentPartUnionParam{
            {OfText: &openai.ChatCompletionContentPartTextParam{Type: "text", Text: "Are these outfits the same color palette? Explain differences."}},
            {OfImageURL: &openai.ChatCompletionContentPartImageParam{Type: "image_url", ImageURL: openai.ChatCompletionContentPartImageImageURLParam{URL: "https://images.example.com/look1.jpg"}}},
            {OfImageURL: &openai.ChatCompletionContentPartImageParam{Type: "image_url", ImageURL: openai.ChatCompletionContentPartImageImageURLParam{URL: "https://images.example.com/look2.jpg"}}},
          },
        },
      },
    }},
  }
  resp, err := client.Chat.Completions.New(ctx, params)
  if err != nil {
    panic(err)
  }
  if len(resp.Choices) > 0 && len(resp.Choices[0].Message.Content) > 0 {
    fmt.Println(resp.Choices[0].Message.Content[0])
  }
}

---

Local images (base64 Data URL)

If you cannot host the image, send a Data URL as the image_url.url.

node.js

import fs from "node:fs";
const b64 = fs.readFileSync("./chart.png", "base64");
const dataUrl = `data:image/png;base64,${b64}`;

const out = await client.chat.completions.create({
  model: "gpt-5",
  messages: [{
    role: "user",
    content: [
      { type: "text", text: "Summarize the main trend in this chart." },
      { type: "image_url", image_url: { url: dataUrl, detail: "auto" } },
    ]
  }],
  max_tokens: 200,
});

python

import base64
b64 = base64.b64encode(open("chart.png", "rb").read()).decode("utf-8")

data_url = f"data:image/png;base64,{b64}"

out = client.chat.completions.create(
    model="gpt-5",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Summarize the main trend in this chart."},
            {"type": "image_url", "image_url": {"url": data_url, "detail": "auto"}},
        ]
    }],
    max_tokens=200,
)

curl

# Linux (GNU base64). On macOS use: b64=$(base64 chart.png | tr -d '\n')
b64=$(base64 -w 0 chart.png)

curl -X POST "https://api.aifoundryhub.com/v1/chat/completions" \
  -H "Authorization: Bearer $AI_FOUNDRY_HUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"gpt-5\",
    \"max_tokens\": 200,
    \"messages\": [{
      \"role\": \"user\",
      \"content\": [
        {\"type\": \"text\", \"text\": \"Summarize the main trend in this chart.\"},
        {\"type\": \"image_url\", \"image_url\": {\"url\": \"data:image/png;base64,$b64\", \"detail\": \"auto\"}}
      ]
    }]
  }"

go

package main

import (
  "context"
  "encoding/base64"
  "fmt"
  "os"

  openai "github.com/openai/openai-go"
  "github.com/openai/openai-go/option"
)

func main() {
  // Read and base64-encode the local file
  img, err := os.ReadFile("chart.png")
  if err != nil { panic(err) }
  b64 := base64.StdEncoding.EncodeToString(img)
  dataURL := "data:image/png;base64," + b64

  client := openai.NewClient(
    option.WithAPIKey(os.Getenv("AI_FOUNDRY_HUB_API_KEY")),
    option.WithBaseURL("https://api.aifoundryhub.com/v1"),
  )

  ctx := context.Background()
  params := openai.ChatCompletionNewParams{
    Model: "gpt-5",
    Messages: []openai.ChatCompletionMessageParamUnion{{
      OfUser: &openai.ChatCompletionUserMessageParam{
        Content: openai.ChatCompletionUserMessageParamContentUnion{
          OfArrayOfContentParts: []openai.ChatCompletionContentPartUnionParam{
            {OfText: &openai.ChatCompletionContentPartTextParam{Type: "text", Text: "Summarize the main trend in this chart."}},
            {OfImageURL: &openai.ChatCompletionContentPartImageParam{Type: "image_url", ImageURL: openai.ChatCompletionContentPartImageImageURLParam{URL: dataURL}}},
          },
        },
      },
    }},
  }

  resp, err := client.Chat.Completions.New(ctx, params)
  if err != nil { panic(err) }
  if len(resp.Choices) > 0 && len(resp.Choices[0].Message.Content) > 0 {
    fmt.Println(resp.Choices[0].Message.Content[0])
  }
}

---

Message content parts (vision)

Returns

A chat.completion object.

The same return shape as regular chat completions. Use message.content[0].text to read the model’s textual answer.