import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
import json
import base64
import time
import gradio as gr
from PIL import Image
from io import BytesIO
import os

host = "http://18.119.36.46:8888"

def image_prompt(prompt, image1, image2, image3, image4):
    source1 = open(image1, "rb").read()
    source2 = open(image2, "rb").read()
    source3 = open(image3, "rb").read()
    source4 = open(image4, "rb").read()
    
    params = {
        "prompt": prompt,
        "image_prompts": [
            {
                "cn_img": base64.b64encode(source1).decode('utf-8'),
                "cn_stop": 1,
                "cn_weight": 1,
                "cn_type": "ImagePrompt"
            },{
                "cn_img": base64.b64encode(source2).decode('utf-8'),
                "cn_stop": 1,
                "cn_weight": 1,
                "cn_type": "ImagePrompt"
            },{
                "cn_img": base64.b64encode(source3).decode('utf-8'),
                "cn_stop": 1,
                "cn_weight": 1,
                "cn_type": "ImagePrompt"
            },{
                "cn_img": base64.b64encode(source4).decode('utf-8'),
                "cn_stop": 1,
                "cn_weight": 1,
                "cn_type": "ImagePrompt"
            }
        ],
        "async_process": True
    }
    
    session = requests.Session()
    retries = Retry(total=5, backoff_factor=1, status_forcelist=[502, 503, 504])
    session.mount('http://', HTTPAdapter(max_retries=retries))

    response = session.post(
        url=f"{host}/v2/generation/text-to-image-with-ip",
        data=json.dumps(params),
        headers={"Content-Type": "application/json"},
        timeout=10  # Increase timeout as needed
    )
    result = response.json()
    
    job_id = result.get('job_id')
    if job_id:
        while True:
            query_url = f"http://18.119.36.46:8888/v1/generation/query-job?job_id={job_id}&require_step_preview=true"
            response = session.get(query_url, timeout=10)  # Increase timeout as needed
            job_data = response.json()
            
            job_stage = job_data.get("job_stage")
            
            if job_stage == "SUCCESS":
                final_image_url = job_data.get("job_result")[0].get("url")
                if final_image_url:
                    final_image_url = final_image_url.replace("127.0.0.1", "18.119.36.46")
                    image_response = session.get(final_image_url, timeout=10)  # Increase timeout as needed
                    image = Image.open(BytesIO(image_response.content))
                    return image, "Job completed successfully."
                else:
                    return None, "Final image URL not found in the job data."
            elif job_stage == "RUNNING":
                step_preview_base64 = job_data.get("job_step_preview")
                if step_preview_base64:
                    image = Image.open(BytesIO(base64.b64decode(step_preview_base64)))
                    return image, "Job is running, step preview available."
                time.sleep(5)
            elif job_stage == "FAILED":
                return None, "Job failed."
    else:
        return None, "Job ID not found."

def gradio_app():
    with gr.Blocks() as demo:
        prompt = gr.Textbox(label="Prompt", placeholder="Enter your text prompt here")
        with gr.Row():
            image1 = gr.Image(label="Image Prompt 1", type="filepath")
            image2 = gr.Image(label="Image Prompt 2", type="filepath")
            image3 = gr.Image(label="Image Prompt 3", type="filepath")
            image4 = gr.Image(label="Image Prompt 4", type="filepath")
        output_image = gr.Image(label="Generated Image")
        status = gr.Textbox(label="Status")
        
        generate_button = gr.Button("Generate Image")
        generate_button.click(image_prompt, inputs=[prompt, image1, image2, image3, image4], outputs=[output_image, status])
        
    demo.launch()

if __name__ == "__main__":
    gradio_app()