app.py

import gradio as gr
import requests 
import os 
import PIL
from PIL import Image
from PIL import ImageDraw
from PIL import ImageFont

##Bloom
API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
HF_TOKEN = os.environ["HF_TOKEN"]
headers = {"Authorization": f"Bearer {HF_TOKEN}"}


def write_on_image(final_solution):
  print("************ Inside write_on_image ***********")
  image_path0 = "./distracted0.jpg"
  image0 = Image.open(image_path0)
  I1 = ImageDraw.Draw(image0)
  myfont = ImageFont.truetype('./font1.ttf', 30)
  
  prompt_list = final_solution.split('\n')
  girlfriend = prompt_list[8].split(':')[1].strip()
  girlfriend_list = girlfriend.split()
  if len(girlfriend_list) >= 2:
    girlfriend = '\n'.join(girlfriend_list)
  print(f"girlfriend  is : {girlfriend }")
  new_girl = prompt_list[9].split(':')[1].strip()
  new_girl_list = new_girl.split()
  if len(new_girl_list) > 2:
    new_girl = '\n'.join(new_girl_list)  
  print(f"new_girl is : {new_girl}")
  prompt_list.pop(0)
  prompt_list.pop(0)
  prompt_list = prompt_list[:8]
  prompt_list.append('Distracted from:')
  print(f"prompt list is : {prompt_list}")
  new_prompt = '\n'.join(prompt_list)
  print(f"final_solution is : {new_prompt}")
  
  I1.text((613, 89), girlfriend,font=myfont, fill =(255, 255, 255))
  I1.text((371, 223), "ME", font=myfont, fill =(255, 255, 255))
  I1.text((142, 336), new_girl,font=myfont, fill =(255, 255, 255))
  
  return image0, new_prompt

def meme_generate(img, prompt, temp, top_p): #prompt, generated_txt): #, input_prompt_sql ): #, input_prompt_dalle2):

  print(f"*****Inside meme_generate - Prompt is :{prompt}")
  if len(prompt) == 0:
    prompt = """Distracted from: homework\nby: side project\nDistracted from: goals\nby: new goals\nDistracted from: working hard\nby: hardly working\nDistracted from: twitter\nby: open in browser\nDistracted from:"""
  
  json_ = {"inputs": prompt,
            "parameters":
            {
          "top_p": top_p, #0.90 default
          "max_new_tokens": 250,
          "temperature": temp, #1.1 default
          "return_full_text": True,
          "do_sample": True,
          }, 
          "options": 
          {"use_cache": True,
          "wait_for_model": True, 
          },}
  response = requests.post(API_URL, headers=headers, json=json_)
  print(f"Response  is : {response}")
  output = response.json()
  print(f"output is : {output}") 
  output_tmp = output[0]['generated_text']
  print(f"output_tmp is: {output_tmp}")
  solution = output_tmp.split("\nQ:")[0]   
  print(f"Final response after splits is: {solution}")
    
  meme_image, new_prompt = write_on_image(solution)  
  return meme_image, new_prompt 


demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>Distracted Boyfriend Meme😄- Brought to you by Bloom 🌸 </center></h1>")
  gr.Markdown(
        """Bloom is a model made by research teams from [HuggingFace](https://huggingface.co/bigscience/bloom) and world over (more than 1000 researchers coming together and working as [BigScienceW Bloom](https://twitter.com/BigscienceW)).\n\nLarge language models can produce coherent sentences but can they produce **Humor** too? Yes, they can, given the correct prompt (Yes, Prompt Engineering 🤖 has definitely become a thing).\n\n**How to Use this App**: Just Fire Away the Generate Meme button below!!\n\n**How this App works**: Figuring out the right set of Prompting + Writing on an Image + Bit of engineering. Currently, Bloom's Public API has size-limits on Token-Generation, yo can get only very few tokens generated in one go.\n\n<pre>Bloom generating very few tokens                    When Few words are Enough</pre>\n\n<pre>                                               🤝</pre>\n\n\nIt is a fun little App which you can play with for a while.\n\nThis Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma)"""
        )
  with gr.Row():

    in_image = gr.Image(value="./distracted0.jpg", visible=False)
    in_image_display = gr.Image(value="./distracted00.jpg", visible=True)
    input_prompt = gr.Textbox(label="Write some prompt...", lines=5, visible=False)

    output_image = gr.Image() 
    
  with gr.Row():
    in_slider_temp = gr.Slider(minimum=0.0, maximum=1.4, value=1.1, step=0.1, label='Temperature')
    in_slider_top_p = gr.Slider(minimum=0.50, maximum=0.99, value=0.90, step=0.01, label='Top_p')
  
    
  b1 = gr.Button("Generate")

  b1.click(meme_generate, inputs=[in_image, input_prompt, in_slider_temp, in_slider_top_p] , outputs=[output_image,input_prompt])    

demo.launch(enable_queue=True, debug=True)