How to Use GLM-4 Vision Capabilities for Image Analysis

The GLM-4 family includes powerful multimodal models capable of processing both text and images seamlessly. This guide demonstrates how to integrate these vision capabilities into your applications to perform tasks like image captioning, object recognition, and visual question answering using standard API protocols.

You will learn how to structure your payload for multimodal inputs, handle base64-encoded image data, and implement the necessary API calls to extract actionable insights from visual assets. This approach allows developers to leverage advanced computer vision features without needing to host or fine-tune models locally.

Prerequisites

• - Python 3.8 or higher installed on your system. - An active API key from the provider platform. - The 'openai' Python library installed via pip. - Access to a local image file or a public image URL to test the vision processing.

Steps

1. 1

   Install Necessary Libraries

   First, ensure your Python environment is ready by installing the standard OpenAI SDK. Run 'pip install openai' in your terminal to get the required client library.

2. 2

   Configure the Client

   Initialize the OpenAI client by setting the base URL to 'https://api.select.ax/v1' and providing your API key. This configuration ensures requests are routed correctly to the vision-capable endpoint.

3. 3

   Prepare the Image Input

   Load your image and encode it as a base64 string, or use a public URL. The API expects the image data to be formatted within a content dictionary specifying the 'image_url' type.

4. 4

   Construct the Request

   Create the chat completion payload, ensuring you include both a text prompt and the image input object within the 'messages' array. Set the 'model' parameter to 'smart-select' to target the appropriate vision-enabled model.

5. 5

   Process the Response

   Execute the API call and extract the response content. The resulting text will contain the model's analysis based on the image and prompt provided.

Code

import base64
from openai import OpenAI

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

def analyze_image(image_path):
    with open(image_path, "rb") as f:
        base64_image = base64.b64encode(f.read()).decode('utf-8')

    response = client.chat.completions.create(
        model="smart-select",
        messages=[
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": "Describe what is happening in this image."},
                    {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}}
                ]
            }
        ]
    )
    return response.choices[0].message.content

print(analyze_image("example.jpg"))

Pro tips

Visual guide

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