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.
"""
#Complete below sentence in fun way.
prompt4 = """Distracted from: hubble
by: james webb
Distracted from: homework
by: side project
Distracted from: goals
by: new goals
Distracted from: 
"""

prompt5 = """Distracted from: homework
by: side project
Distracted from: goals
by: new goals
Distracted from: working hard
by: hardly working
Distracted from: twitter
by: open in browser
Distracted from:
"""

"""Distracted from: homework
by: side project
Distracted from: goals
by: new goals
Distracted from: working hard
by: hardly working
Distracted from: twitter
by:  open in browser
Distracted from: code
by: blog post
Distracted from: code
by: blog post
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)
  
  prompt_list = final_solution.split('\n')
  girlfriend = prompt_list[8].split(':')[1].strip()
  new_girl = prompt_list[9].split(':')[1].strip()
  prompt_list.pop(0)
  prompt_list.pop(1)
  prompt_list = prompt_list[:7]
  prompt_list[8] = '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): #prompt, generated_txt): #, input_prompt_sql ): #, input_prompt_dalle2):

  print(f"*****Inside meme_generate - Prompt is :{prompt}")
  json_ = {"inputs": prompt,
            "parameters":
            {
          #"top_p": 0.95, 
          "top_p": 0.90,
          #"top_k":0,
          "max_new_tokens": 250,
          "temperature": 1.1,
          #"num_return_sequences": 3,
          "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
    
  meme_image, new_prompt = write_on_image(solution)  
  return meme_image, solution #final_solution #display_output, new_prompt  #generated_txt+prompt


demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>Testing</center></h1>")
  gr.Markdown(
        """Work In Progress"""
        )
  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", visible=False)
    in_image_display = gr.Image(value="./distracted00.jpg", visible=True)
    input_prompt = gr.Textbox(label="Write some prompt...", lines=5, 
                              value = """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:""", visible=False)  #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)

  with gr.Row():
    output_image = gr.Image() #type="filepath", shape=(256,256))
    #output_prompt = gr.Textbox(label="Text generated", lines=5)
    
  b1 = gr.Button("Generate")
  #b2 = gr.Button("Generate Image") 

  b1.click(meme_generate, inputs=[in_image, input_prompt], outputs=[output_image,input_prompt])  #output_prompt
  #b2.click(poem_to_image, poem_txt, output_image)
  #examples=examples 

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