import openai
from typing import List

def query_gpt4_vision(image_url, llmPrompt: List, max_tokens=150):
    if not image_url or image_url == "None":
        print("Image URL is empty or None.")
        return False

    # Initialize the messages list with system content from llmPrompt
    messages = [{
        "role": item["role"], 
        "content": item["content"]
    } for item in llmPrompt if item["role"] == "system"]

    # Assuming the last item in llmPrompt is always from the user and includes the prompt content
    if llmPrompt[-1]["role"] == "user":
        # Append a new user message that includes both the text and image URL
        messages.append({
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": llmPrompt[-1]["content"]
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": image_url
                    }
                }
            ]
        })

    print(f"Submitting to GPT-4-Vision with image URL: {image_url}")
    try:
        response = LLM_OAI.chat.completions.create(
            model="gpt-4-vision-preview",  # Ensure this matches your intended model
            messages=messages,
            max_tokens=max_tokens
        )
        # Assuming the response is structured as expected; adjust accordingly
        if response.choices:
            comment_content = response.choices[0].message['content']  # This path may need adjustment
            print(f"Generated comment: {comment_content}")
            return comment_content
        else:
            print("OpenAI API response did not contain expected data.")
            return "Failed to generate comment due to API response format."
    except Exception as e:
        print(f"Error during OpenAI API call: {e}")
        return "Failed to generate comment due to an error with the OpenAI API."