import gradio as gr
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")

# setting=heroic pose, wearing a sleek, high-tech suit and holding a futuristic gadget.The background should be dark and dramatic, with explosions and other action-packed elements
def generate(celebrity, movie,setting):
  prompt=f" Create a movie poster featuring {celebrity} in a {movie} inspired role.The poster should include the title of the movie {movie},and feature {celebrity} in a {setting}"
  image = pipe(prompt).images[0]  
  return image

import os

HF_TOKEN = os.getenv('sai')
hf_writer =  gr.HuggingFaceDatasetSaver(HF_TOKEN, "movie-poster")

gr.Interface(
  fn = generate,  
    inputs=[
        gr.inputs.Textbox(label="celebrity"),
        gr.inputs.Dropdown(label="Movies", choices=["Mission Impossible", "Avengers", "Batman","Baahubali","Transporter","Rocky"]),
        gr.inputs.Textbox(label="Setting")               
    ],
    outputs= gr.outputs.Image(label="Generated movie poster",type='pil'),
    title="Movie Poster Generator"  ,
    allow_flagging="manual",
    flagging_options=["Good", "Better", "Worst"],
    flagging_callback=hf_writer
).launch(share=True)