from asyncio import constants
import gradio as gr
import requests
import os 
import re
import random

# 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}"}

prompt = """
Bilbo is a hobbit rogue who wears a brown cloak and carries a ring.

Bremen is a human wizard, he wears a blue robe and carries a wand.
"""

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


def npc_randomize():
    #name is a random combination of syllables
    vowels = list("aeiou")
    constants = list("bcdfghjklmnpqrstvwxyz")
    seperators=list("-'")
    name =""
    for i in range(random.randint(2,4)):
        name += random.choice(constants)
        name += random.choice(vowels)
        if random.random()<0.5:
            name += random.choice(constants)
        if random.random()<0.1:
            name += random.choice(seperators)

    #capitalize first letter
    name = name[0].upper() + name[1:]
    
    races="""Dwarf
    Elf
    Halfling
    Human
    Dragonborn
    Gnome
    Half-elf
    Half-orc
    Tiefling
    Aarakocra
    Genasi
    Goliath""".split("\n")

    races=[x.strip() for x in races]

    race=random.choice(races)

    print("foo",races,race)


    classes="""Barbarian
    Bard
    Cleric
    Druid
    Fighter
    Monk
    Paladin
    Ranger
    Rogue
    Sorcerer
    Warlock
    Wizard""".split("\n")
    
    classes=[x.strip() for x in classes]

    characterClass=random.choice(classes)

    pronoun=random.choices(["he","she","they"],weights=[0.45,0.45,0.1],k=1)[0]

    return name,race,characterClass,pronoun


    




def npc_generate(name,race,characterClass,pronoun):

  desc="{name} is a {race} {characterClass}, {pronoun}".format(name=name,race=race,characterClass=characterClass,pronoun=pronoun)

  p = prompt + "\n"+desc
  print(f"*****Inside poem_generate - Prompt is :{p}")
  json_ = {"inputs": p,
            "parameters":
            {
            "top_p": 0.9,
          "temperature": 1.1,
          "max_new_tokens": 50,
          "return_full_text": False,
          }}
  #response = requests.post(API_URL, headers=headers, json=json_)
  response = requests.post(API_URL, 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 desc+poem

def poem_to_image(poem):
  print("*****Inside Poem_to_image")
  poem = " ".join(poem.split('\n'))
  poem = poem + ", character art, concept art, artstation"
  steps, width, height, images, diversity = '50','256','256','1',15
  iface = gr.Interface.load("spaces/multimodalart/latentdiffusion")
  print("about to die",iface,dir(iface))

  prompt = re.sub(r'[^a-zA-Z0-9 .]', '', poem)
  print("about to die",prompt)


  img=iface(poem, steps, width, height, images, diversity)[0]
  return img

demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>NPC Generator</center></h1>")
  gr.Markdown(
        "based on <a href=https://huggingface.co/spaces/Gradio-Blocks/GPTJ6B_Poetry_LatentDiff_Illustration> Gradio poetry generator</a>."
        "<div>first input name, race and class (or generate them randomly)</div>"
        "<div>Next, use GPT-J to generate a short description</div>"
        "<div>Finally, Generate an illustration 🎨 provided by Latent Diffusion model.</div>"
    )
  
  with gr.Row():
    b0 = gr.Button("Randomize name,race and class")
    b1 = gr.Button("Generate NPC")
    b2 = gr.Button("Generate Image")
  
  with gr.Row():  
    input_name = gr.Textbox(label="name",placeholder="Drizzt")
    input_race = gr.Textbox(label="race",placeholder="dark elf")
    input_class = gr.Textbox(label="class",placeholder="ranger")
    input_pronoun = gr.Textbox(label="pronoun",placeholder="he")

  with gr.Row():
    poem_txt = gr.Textbox(label="description",lines=7)
    output_image = gr.Image(label="portrait",type="filepath", shape=(256,256))
  
  b0.click(npc_randomize,inputs=[],outputs=[input_name,input_race,input_class,input_pronoun])
  b1.click(npc_generate, inputs=[ input_name,input_race,input_class,input_pronoun], outputs=poem_txt)
  b2.click(poem_to_image, poem_txt, output_image)
  #examples=examples

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