import gradio as gr 
import os
import requests
import time
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import paddlehub as hub

#HF_TOKEN = os.environ["HF_TOKEN"]
HF_TOKEN = os.environ.get("HF_TOKEN") or True
model = hub.Module(name='ernie_vilg')

def get_ernie_vilg(text_prompts): 
  results = model.generate_image(text_prompts=text_prompts, style="油画", visualization=False)
  return results[0]
  
sd_inf = gr.Interface.load(name="spaces/stabilityai/stable-diffusion", use_auth_token=HF_TOKEN) 
 
nllb_model_name = 'facebook/nllb-200-distilled-600M'
nllb_model = AutoModelForSeq2SeqLM.from_pretrained(nllb_model_name)
nllb_tokenizer = AutoTokenizer.from_pretrained(nllb_model_name)

def get_chinese_translation(in_language_first, in_language_second, text):
  print("********Inside get_chinese_translation ********")
  print(f"text is :{text}, source language is : {in_language_first}, target language is : {in_language_second} ") 
  
  translator = pipeline('translation', model=nllb_model, tokenizer=nllb_tokenizer, src_lang=in_language_first, tgt_lang=in_language_second)
  output = translator(text, max_length=400)
  print(f"initial output is:{output}")
  output = output[0]['translation_text']
  print(f"output is:{output}")
  
  return output 
  
  
def get_sd(translated_txt, samples, steps, scale, seed):
  print("******** Inside get_SD ********")
  print(f"translated_txt is : {translated_txt}")
  print(f"sd_inf is: {sd_inf}")
  sd_img_gallery = sd_inf(translated_txt, samples, steps, scale, seed, fn_index=1)[0]  #(fn_index=1)
  
  return sd_img_gallery #[0]

demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>ERNIE-ViLG, NLLB-Facebook-600Million, Stable Diffusion Pipeline </center></h1>")
  
  with gr.Row():
    in_text_prompt = gr.Textbox(label="Enter English text here")
    out_text_chinese = gr.Textbox(label="Your Chinese language output")
    b1 = gr.Button("English to Chinese")
    
    s1 = gr.Slider(label='samples', value=4, visible=False)
    s2 = gr.Slider(label='steps', value=45, visible=False)
    s3 = gr.Slider(label='scale', value=7.5, visible=False)
    s4 = gr.Slider(label='seed', value=1024, visible=False)
    
    in_language_first = gr.Dropdown(visible=False, value= 'eng_Latn') #'English') 
    in_language_second = gr.Dropdown(visible=False, value= 'zho_Hans') #'Chinese (Simplified)') 
    
  with gr.Row():
    out_ernie = gr.Image(type="pil", label="Ernie output for the given prompt")
    #out_gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery") #.style(grid=[2, 3], height="auto")
    b2 = gr.Button("Generate Images from Ernie")
    
    out_sd = gr.Image(type="pil", label="SD output for the given prompt")
    b3 = gr.Button("Generate Images from SD")
    
    b1.click(get_chinese_translation, [in_language_first, in_language_second, in_text_prompt], out_text_chinese )  
    b2.click(get_ernie_vilg, out_text_chinese, out_ernie) #out_gallery )  
    b3.click(get_sd, [in_text_prompt,s1,s2,s3,s4], out_sd) #out_gallery )  
    
demo.launch(enable_queue=True, debug=True)