import openai
import requests

# Use OpenAI Vision to compare a user-uploaded image to reference images
def compare_images(user_image_path, reference_image_urls):
    with open(user_image_path, "rb") as user_img:
        user_bytes = user_img.read()

    # Download the first reference image for comparison
    if not reference_image_urls:
        return {"confidence": 0.0, "reason": "No reference images available."}

    ref_response = requests.get(reference_image_urls[0])
    if ref_response.status_code != 200:
        return {"confidence": 0.0, "reason": "Failed to fetch reference image."}

    ref_bytes = ref_response.content

    # Use GPT-4 Vision to compare both images
    response = openai.chat.completions.create(
        model="gpt-4-vision-preview",
        messages=[
            {"role": "system", "content": "You are an expert in identifying error coins."},
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": "Do these images look like the same error coin?"},
                    {"type": "image", "image": user_bytes},
                    {"type": "image", "image": ref_bytes}
                ]
            }
        ],
        max_tokens=300
    )

    result_text = response.choices[0].message.content
    # Very simple scoring logic based on confidence language
    confidence = 0.8 if "yes" in result_text.lower() else 0.3
    return {"confidence": confidence, "summary": result_text}