import base64
from openai import OpenAI
import os
from PIL import Image
import io

def resize_image(image, max_size=800):
    """Resize the image to ensure the max side length is `max_size` while maintaining aspect ratio."""
    # Open the image using Pillow
    img = Image.open(image)
    print(img.size)
    # Get the current width and height of the image
    width, height = img.size
    
    # Resize the image if necessary
    if width > height:
        new_width = max_size
        new_height = int((new_width / width) * height)
    else:
        new_height = max_size
        new_width = int((new_height / height) * width)
    
    # Resize the image using the LANCZOS filter for high-quality rescaling
    img = img.resize((new_width, new_height), Image.Resampling.LANCZOS)
    print('after resizing', img.size)
    # Save the resized image to a BytesIO object to later encode to base64
    img_byte_arr = io.BytesIO()
    img.save(img_byte_arr, format='PNG')
    img_byte_arr.seek(0)  # Rewind the BytesIO object to the beginning
    
    return img_byte_arr

# Function to encode the image
def encode_image(image_path):
    assert os.path.exists(image_path), "The image file does not exist."
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')
    
def encode_image_from_uploaded_file(image):
    # Convert image to bytes
    assert image is not None, "No image uploaded."
    resized_image = resize_image(image)
    image_bytes = resized_image.read()
    return base64.b64encode(image_bytes).decode('utf-8')

def transcribe_image(image_file):
    """Transcribe handwritten text from an image using OCR."""
    # Initialize the OpenAI client
    client = OpenAI()

    # Encoding the image
    base64_image = encode_image_from_uploaded_file(image_file)


    # Preparing the API call
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": "Please transcribe the handwritten text in this image. Return only the text content."},
                    {
                        "type": "image_url",
                        "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}
                    }
                ]
            }
        ],
        max_tokens=300
    )
    
    transcribed_text = response.choices[0].message.content

    return transcribed_text