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}"}


prompt1 = """
word: risk
poem using word: And then the day came,
when the risk
to remain tight
in a bud
was more painful
than the risk
it took
to blossom.
word: """

prompt2 = """
Q: Joy has 5 balls. He buys 2 more cans of balls. Each can has 3 balls. How many balls he has now?
A: Joy had 5 balls. 2 cans of 3 balls each is 6 balls. 5 + 6 = 11. Answer is 11.
Q: Jane has 16 balls. Half balls are golf balls, and half golf balls are red. How many red golf balls are there?
A: """

prompt3 = """Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?
A: Let’s think step by step.
"""

prompt = """Distracted from hubble by james webb.
Distracted from homework by side projeect.
Distracted from goals by new goals.
Distracted from 
"""

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)
  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

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

  print(f"*****Inside meme_generate - Prompt is :{prompt}")
  #if input_prompt_sql != '':
  #  prompt = input_prompt_sql #"Instruction: Given an input question, respond with syntactically correct PostgreSQL\nInput: " +input_prompt_sql + "\nPostgreSQL query: "
  #elif input_prompt_dalle2 !='':
  #  prompt = "Dalle Prompt: " + input_prompt_dalle2 + "\nNew Dalle Prompt: "
    
  json_ = {"inputs": prompt,
            "parameters":
            {
            "top_p": 0.9,
          "temperature": 1.1,
          "max_new_tokens": 250,
          "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}")
  if '\nOutput:' in solution:
    final_solution = solution.split("\nOutput:")[0] 
    print(f"Response after removing output is: {final_solution}")
  elif '\n\n' in solution:
    final_solution = solution.split("\n\n")[0] 
    print(f"Response after removing new line entries is: {final_solution}")
  else:
    final_solution = solution
  
  
  if len(generated_txt) == 0 :
    display_output = final_solution
  else:
    display_output = generated_txt[:-len(prompt)] + final_solution
  new_prompt = final_solution[len(prompt):]
  print(f"new prompt for next cycle is : {new_prompt}")
  print(f"display_output for printing on screen is : {display_output}")
  if len(new_prompt) == 0:
    temp_text = display_output[::-1]
    print(f"What is the last character of sentence? : {temp_text[0]}")
    if temp_text[1] == '.':
      first_period_loc = temp_text[2:].find('.') + 1
      print(f"Location of last Period is: {first_period_loc}")
      new_prompt = display_output[-first_period_loc:-1]
      print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}")
    else:
      print("HERE")
      first_period_loc = temp_text.find('.')
      print(f"Location of last Period is : {first_period_loc}")
      new_prompt = display_output[-first_period_loc:-1]
      print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}")
    display_output = display_output[:-1]
  
  meme_image = write_on_image(final_solution)  
  return meme_image #final_solution #display_output, new_prompt  #generated_txt+prompt


demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>Bloom</center></h1>")
  gr.Markdown(
        """Testing Bloom. WIP"""
        )
  with gr.Row():
    #example_prompt = gr.Radio( ["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: Let’s think step by step.\n"], label= "Choose a sample Prompt")
    #example_prompt = gr.Radio( [
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL\nInput: How many users signed up in the past month?\nPostgreSQL query: ", 
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL\nInput: Create a query that displays empfname, emplname, deptid, deptname, location from employee table. Results should be in the ascending order based on the empfname and location.\nPostgreSQL query: ", 
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: What is the total salary paid to all the employees?\nPostgreSQL query: ",
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: List names of all the employees whose name end with 'r'.\nPostgreSQL query: ",
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: What are the number of employees in each department?\nPostgreSQL query: ",
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use table called 'employees'.\nInput: Select names of all theemployees who have third character in their name as 't'.\nPostgreSQL query: ",
    #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use table called 'employees'.\nInput: Select names of all the employees who are working under 'Peter'\nPostgreSQL query: ",  ], label= "Choose a sample Prompt")
    #"Dalle Prompt: Cyberwave vaporpunk art of a kneeling figure, looking up at a glowing neon book icon, smoke and mist, pink and blue lighting, cybernetic sci-fi render\nNew Dalle Prompt: " ], label= "Choose a sample Prompt")
    
  #with gr.Row():
    in_image = gr.Image(value="./distracted0.jpg")
    #input_prompt = gr.Textbox(label="Write some text to get started...", lines=3)  #input_prompt_sql
    #input_prompt_dalle2 = gr.Textbox(label="Or Write sample Dalle2 prompts to get more Prompt ideas...")
    #input_prompt2 = gr.Textbox(label="Write some text to get started...", lines=3, visible=False)  #input_prompt_sql
    
    #input_word = gr.Textbox(placeholder="Enter a word here to generate text ...")
  #with gr.Row():
    #generated_txt = gr.Textbox(lines=7, visible = True)
    output_image = gr.Image() #type="filepath", shape=(256,256))
  
  b1 = gr.Button("Generate MeMe")
  #b2 = gr.Button("Generate Image") 

  b1.click(text_generate, inputs=in_image, outputs=output_image) #input_word #input_prompt_dalle2 #input_prompt_sql #example_prompt
  #b2.click(poem_to_image, poem_txt, output_image)
  #examples=examples 

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