import gradio as gr
from gradio.inputs import Textbox

import torch
from diffusers import StableDiffusionPipeline
import boto3
from io import BytesIO
import os
import botocore
from time import sleep

AWS_ACCESS_KEY_ID = os.getenv("AWS_ACCESS_KEY_ID")
AWS_SECRET_ACCESS_KEY = os.getenv("AWS_SECRET_ACCESS_KEY")
S3_BUCKET_NAME = 'pineblogs101145-dev'

model_id = "CompVis/stable-diffusion-v1-4"
device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = StableDiffusionPipeline.from_pretrained(
    model_id, torch_dtype=torch.float32)

pipe = pipe.to(device)

s3 = boto3.resource('s3',
                    aws_access_key_id=AWS_ACCESS_KEY_ID,
                    aws_secret_access_key=AWS_SECRET_ACCESS_KEY)

s3_client = boto3.client('s3',
                    aws_access_key_id=AWS_ACCESS_KEY_ID,
                    aws_secret_access_key=AWS_SECRET_ACCESS_KEY)

bucket_name = 'pineblogs101145-dev'
folder = 'public/mdx/'


def text_to_image(prompt, save_as, key_id):

    if AWS_ACCESS_KEY_ID != key_id:
        return "not permition"

    # Create an instance of the S3 client
    s3 = boto3.client('s3',
                      aws_access_key_id=AWS_ACCESS_KEY_ID,
                      aws_secret_access_key=AWS_SECRET_ACCESS_KEY)

    image_name = '-'.join(save_as.split()) + ".webp"

    def save_image_to_s3(image):
        # Create a BytesIO object to store the image.
        image_buffer = BytesIO()
        image.save(image_buffer, format='WEBP')
        image_buffer.seek(0)

        # Full path of the file in the bucket
        s3_key = "public/" + image_name
        print('Saving image to s3')

        # Upload the image to the S3 bucket
        s3.upload_fileobj(image_buffer, S3_BUCKET_NAME, s3_key)
        print('Image saved to s3')

    def generator_image(prompt):
        prompt = prompt
        print('Starting to generate the image ...')
        try:
            image = pipe(prompt).images[0]
        except Exception as e:
            print('Error: ', e)

        print('Image generation completed')

        # Save the image in S3
        save_image_to_s3(image)

    generator_image(prompt)
    return image_name


def check_if_exist(bucket_name, key):

    try:
        s3.Object(bucket_name, key).load()
    except botocore.exceptions.ClientError as e:
        if e.response['Error']['Code'] == "404":
            # The object does not exist.
            return False
        else:
            # Something else has gone wrong.
            raise
    else:
        return True


def list_s3_files(bucket_name, folder):

    my_bucket = s3.Bucket(bucket_name)

    for objects in my_bucket.objects.filter(Prefix=folder):
        print(objects.key)

        filename_ext = '%s' % os.path.basename(objects.key)
        filename = os.path.splitext(filename_ext)[0]
        s3image = 'public/%s.webp' % filename

        if check_if_exist(bucket_name, s3image):
            print('Image %s already exists!' % s3image)
        else:
            response = s3_client.head_object(Bucket=bucket_name, Key=objects.key)
            metadata = response['Metadata']
            print(metadata)
            if 'resumen' in metadata:
                print('Has resume, ready to create image!')
                print('Start creating image.. %s ' % s3image)
                resumen = metadata['resumen']
            else:
                print('There is NOT resume, skipping..')

        sleep(500/1000)
    text_to_image(resumen, filename, AWS_ACCESS_KEY_ID)


list_s3_files(bucket_name, folder)

iface = gr.Interface(fn=list_s3_files, inputs=[Textbox(label="bucket_name"), Textbox(label="folder")], outputs="text")
iface.launch()