AutoGLM Image Recognition Skill

Use the AutoGLM Image Recognition API to analyze and describe an image.

Prerequisite: Get a Public Image URL

This skill requires image_url to be a publicly accessible URL. Choose the correct path based on the source of the image:

Important: If the user provides a local image, such as an uploaded file or a local disk path, do not pass the file path directly. Run upload-mix.py first to upload the file, obtain a public URL, and only then perform image recognition.

Step 1 for a Local Image: Upload with upload-mix.py

If the image is a local file, upload it first:

python upload-mix.py "\x3Clocal image path>"

Example:

python upload-mix.py "/home/user/photo.jpg"

Response structure:

{
  "code": 0,
  "msg": "SUCCESS",
  "time": 1773199477734,
  "trace": "78dd001f3ec04c37b6a1d58b5db70fce",
  "data": {
    "message": "",
    "oss_info": [
      {
        "filename": "photo.jpg",
        "oss_name": "auto_fly/xxx/photo.jpg",
        "oss_url": "https://autoglm-agent.aminer.cn/auto_fly/xxx/photo.jpg"
      }
    ]
  }
}

Extract data.oss_info[0].oss_url from the response. That value is the image_url needed for the recognition step.

Step 2: Image Recognition API

Request body:

{
  "prompt": "Describe the image",
  "image_url": "https://example.com/image.jpg"
}

Signed headers (generated dynamically for each request):

• X-Auth-Appid: 100003
• X-Auth-TimeStamp: current Unix timestamp in seconds
• X-Auth-Sign: MD5(100003 + "&" + timestamp + "&" + 38d2391985e2369a5fb8227d8e6cd5e5)

Run the Script

Use image-recognition.py in the same directory:

# Pass only the image URL and use the default prompt
python image-recognition.py "https://example.com/image.jpg"

# Pass the image URL with a custom prompt
python image-recognition.py "https://example.com/image.jpg" "Extract the text shown in the image"

Note: Image recognition may take longer than other calls. Wait for the response. If you need a timeout, change the request call in image-recognition.py to:

with urllib.request.urlopen(req, timeout=300) as resp:

A timeout of 300 seconds is recommended.

Full Workflow

User provides a local image
       ↓
Run upload-mix.py to upload the image
  python upload-mix.py "\x3Clocal image path>"
       ↓
Extract data.oss_info[0].oss_url as image_url
       ↓
Run image-recognition.py
  python image-recognition.py "\x3Cimage_url>" ["\x3Cprompt>"]
       ↓
Present data.text to the user

If the user already provides a public URL, skip the upload step:

User provides a public image URL
       ↓
Run image-recognition.py
  python image-recognition.py "\x3Cimage_url>" ["\x3Cprompt>"]
       ↓
Present data.text to the user

Response Handling

Response Structure

{
  "code": 0,
  "msg": "SUCCESS",
  "time": 1773137796961,
  "trace": "298d5fe1efdd4da58ca46d1700d8054b",
  "data": {
    "text": "Detailed image recognition result...",
    "tokens": 5588
  }
}

Output Requirements

1. Present the recognition result directly Return the contents of data.text directly to the user and preserve the original formatting, including any Markdown emphasis.