app.py

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 genericDescription():
    colors="""red

    blue

    green

    yellow

    orange

    purple

    pink

    brown

    black

    white""".split("\n")
    colors=[x.strip() for x in colors]
    outfits="""shirt

    pair of pants

    pair of shoes

    hat

    pair of glasses

    backpack

    belt

    tie

    cloak

    robe

    chain mail vest

    suit of plate armor

    suit of leather armor

    suit of studded leather armor

    suit of scale armor

    suit of chain mail armor

    suit of ring mail armor

    """.split("\n")
    outfits=[x.strip() for x in outfits]
    weapons="""sword

    dagger

    mace

    axe

    polearm

    bow

    crossbow

    sling

    club

    flail

    warhammer

    morningstar

    halberd

    war pick

    war sickle

    war hammer""".split("\n")
    weapons=[x.strip() for x in weapons]

    objects="""shield

    lantern

    sack

    severed head

    crystal""".split("\n")
    objects=[x.strip() for x in objects]
    
    desc="wears a {color} {outfit}".format(color=random.choice(colors),outfit=random.choice(outfits))
    if random.random()<0.5:
        desc+="and a {color} {outfit}".format(color=random.choice(colors),outfit=random.choice(outfits))
    
    if random.random()<0.5:
        desc+="and carries a {weapon}".format(weapon=random.choice(weapons))
    elif random.random()<0.5:
        desc+="and carries a {weapon} and a {object}".format(weapon=random.choice(weapons),object=random.choice(objects))
    else:
        desc+="and carries two {weapon}s".format(weapon=random.choice(weapons))
        
    return desc


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 desc_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}")


  #error handling
  if "error" in output:
    #fallback method
    longDescription=genericDescription()
  else:
    output_tmp = output[0]['generated_text']
    print(f"GPTJ response without splits is: {output_tmp}")
    if "\n\n" not in output_tmp:
        if output_tmp.find('.') != -1:
        idx = output_tmp.find('.')
        longDescription = output_tmp[:idx+1]
        else:
        idx = output_tmp.rfind('\n')
        longDescription = output_tmp[:idx]
    else:
        longDescription = output_tmp.split("\n\n")[0] # +"."
    longDescription = longDescription.replace('?','')
    print(f"longDescription being returned is: {longDescription}")
  return desc+longDescription

def desc_to_image(desc):
  print("*****Inside desc_to_image")
  desc = " ".join(desc.split('\n'))
  desc = desc + ", 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 ,.]', '', desc)
  print("about to die",prompt)


  img=iface(desc, 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 Description")
    b2 = gr.Button("Generate Portrait")
  
  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():
    desc_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=desc_txt)
  b2.click(desc_to_image, desc_txt, output_image)
  #examples=examples

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