> ## Documentation Index
> Fetch the complete documentation index at: https://docs.llm7.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Image recognition

> Send images to chat models for captions, OCR, and visual Q&A.

Use the chat completions API to describe or reason about images. Add both the prompt and the image URL to the same user message so the model can reference the visual context.

<Note>
  Image recognition uses chat completions with image input. To create or edit image outputs, use the [Image generation and edits](/guides/image-generation) endpoints instead.
</Note>

## Streaming example

```python theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api.llm7.io/v1",
    api_key="unused",  # Use a https://dash.llm7.io/ token for higher limits.
)

image_url = "https://images.weserv.nl/?url=wsrv.nl/lichtenstein.jpg&w=600&output=webp"

messages = [
    {
        "role": "user",
        "content": [
            {"type": "text", "text": "Describe this image for alt text."},
            {"type": "image_url", "image_url": {"url": image_url}},
        ],
    }
]

stream = client.chat.completions.create(
    model="default",  # or a model ID with image input from /v1/models
    messages=messages,
    temperature=0.5,
    stream=True,
)

model_used = None
for chunk in stream:
    model_used = chunk.model
    delta = chunk.choices[0].delta.content or []
    if isinstance(delta, list):
        delta = "".join(
            part.get("text", "") for part in delta if part.get("type") == "text"
        )
    print(delta, end="", flush=True)

print(f"\nModel selected: {model_used}")
```

<Tip>
  Use a publicly reachable `https` image (or a signed URL) and keep text + image together in one `content` array. Use the [Models API](/guides/models-api) to find models with `image` in `modalities.input`.
</Tip>

## Non-streaming call

```python theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api.llm7.io/v1",
    api_key="unused",  # Use a https://dash.llm7.io/ token for higher limits.
)

image_url = "https://images.weserv.nl/?url=wsrv.nl/lichtenstein.jpg&w=600&output=webp"

result = client.chat.completions.create(
    model="pro",  # or a model ID with image input from /v1/models
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Summarize the scene in one sentence."},
                {"type": "image_url", "image_url": {"url": image_url}},
            ],
        }
    ],
    temperature=0.3,
)

print(result.choices[0].message.content)
print(f"Model selected: {result.model}")
```

## What to remember

* `messages[*].content` is an array: include both `text` and `image_url` parts in the same user message.
* Image URLs must be reachable over HTTPS; signed URLs work if they stay valid for the request duration.
* `response.model` (or `chunk.model` while streaming) tells you which underlying model handled the call.