app.py

import gradio as gr
from gradio_client import Client as GrClient
import inspect
from gradio import routes
from typing import List, Type
from aiogoogletrans import Translator 

import requests, os, re, asyncio

loop = asyncio.get_event_loop()
gradio_client = GrClient(os.environ.get('GrClient_url'))
translator = Translator()
# Monkey patch
def get_types(cls_set: List[Type], component: str):
    docset = []
    types = []
    if component == "input":
        for cls in cls_set:
            doc = inspect.getdoc(cls)
            doc_lines = doc.split("\n")
            docset.append(doc_lines[1].split(":")[-1])
            types.append(doc_lines[1].split(")")[0].split("(")[-1])
    else:
        for cls in cls_set:
            doc = inspect.getdoc(cls)
            doc_lines = doc.split("\n")
            docset.append(doc_lines[-1].split(":")[-1])
            types.append(doc_lines[-1].split(")")[0].split("(")[-1])
    return docset, types
routes.get_types = get_types

# App code
def mbti(x):
    t = loop.run_until_complete(translator.translate(x, src='ko', dest='en'))
    str_trans = re.sub('[-=+,#/\?:^.@*\"※~ㆍ!』‘|\(\)\[\]`\'…》\”\“\’·]', '', t.text)
    result = gradio_client.predict(
				str_trans,	# str representing input in 'User input' Textbox component
				fn_index=2
    )

    r = sorted(result, key=lambda x : x['score'], reverse=True)
    
    return r
    
def chat(x):
    result = gradio_client.predict(
        x,# str representing input in 'User input' Textbox component
		0.9,	# float, representing input in 'Top-p (nucleus sampling)' Slider component
		50,	# int, representing input in 'Top-k (nucleus sampling)' Slider component
		0.9,	# float, representing input in 'Temperature' Slider component
		20,	# int, representing input in 'Max New Tokens' Slider component
		1.1,	# float, representing input in 'repetition_penalty' Slider component
		fn_index=0
    )
    return result

def yn(x):
    result = gradio_client.predict(
				x,	# str representing input in 'User input' Textbox component
				fn_index=1
    )
    return result

with gr.Blocks() as demo:
    aa = gr.Interface(
      fn=chat,
      inputs="text",
      outputs="text",
      description="chat"
    )
    
    bb = gr.Interface(
      fn=mbti,
      inputs="text",
      outputs="text",
      description="mbti"
    )
    
    cc = gr.Interface(
      fn=yn,
      inputs="text",
      outputs="text",
      description="yn"
    )
    demo.queue(max_size=32).launch(enable_queue=True)