import gradio as gr
import requests
import os 

##Bloom
API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
headers = {"Authorization": "Bearer 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"}

#def query(payload):
#	response = requests.post(API_URL, headers=headers, json=payload)
#	return response.json()
	
#output = query({
#	"inputs": "Can you please let us know more details about your ",
#})


# GPT-J-6B API
#API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B"
#HF_TOKEN = os.environ["HF_TOKEN"]
#headers = {"Authorization": f"Bearer {HF_TOKEN}"}
#word: bird
#poem using word: She sights a bird, she chuckles
#She flattens, then she crawls
#She runs without the look of feet
#Her eyes increase to Balls.

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: """

prompt = """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.
"""

examples = [["river"], ["night"], ["trees"],["table"],["laughs"]]


def poem_generate(word):

  #p = prompt + word.lower() + "\n" + "poem using word: "
  p = prompt #+ word.lower() 
  print(f"*****Inside poem_generate - Prompt is :{p}")
  json_ = {"inputs": p,
            "parameters":
            {
            "top_p": 0.9,
          "temperature": 1.1,
          "max_new_tokens": 500,
          "return_full_text": False
          }}
  response = requests.post(API_URL, headers=headers, json=json_)
  output = response.json()
  print(f"If there was an error? Reason is : {output}")
  output_tmp = output[0]['generated_text']
  print(f"GPTJ response without splits is: {output_tmp}")
  #poem = output[0]['generated_text'].split("\n\n")[0] # +"."
  if "\n\n" not in output_tmp:
    if output_tmp.find('.') != -1:
      idx = output_tmp.find('.')
      poem = output_tmp[:idx+1]
    else:
      idx = output_tmp.rfind('\n')
      poem = output_tmp[:idx]
  else:
    poem = output_tmp.split("\n\n")[0] # +"."
  poem = poem.replace('?','')
  #print(f"Poem being returned is: {poem}")
  return output_tmp #poem

def poem_to_image(poem):
  print("*****Inside Poem_to_image")
  poem = " ".join(poem.split('\n'))
  poem = poem + " oil on canvas."
  steps, width, height, images, diversity = '50','256','256','1',15
  img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(poem, steps, width, height, images, diversity)[0]
  return img

demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>Bloom</center></h1>")
  gr.Markdown(
        """Testing Bloom """
        )
  with gr.Row():
    input_word = gr.Textbox(placeholder="Enter a word here to generate text ...")
    poem_txt = gr.Textbox(lines=7)
    #output_image = gr.Image(type="filepath", shape=(256,256))
  
  b1 = gr.Button("Generate Text")
  #b2 = gr.Button("Generate Image") 

  b1.click(poem_generate, input_word, poem_txt)
  #b2.click(poem_to_image, poem_txt, output_image)
  #examples=examples

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