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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('[-=+,#/\?:^.@*\"β€»~ㆍ!γ€β€˜|\(\)\[\]`\'…》\”\β€œ\’·]', '', t.text)
result = gradio_client.predict(
str_trans, # str representing input in 'User input' Textbox component
fn_index=2
)
r = sorted(eval(result), key=lambda x : x['score'], reverse=True)
return r
def chat(x):
x = f"[***λ„ˆλŠ” Assistantμž…λ‹ˆλ‹€. μƒλŒ€μ—κ²Œ λ‹€μ–‘ν•œ μ§ˆλ¬Έμ„ ν•˜λ©° λŒ€ν™”λ₯Ό 이끌고 μžˆμŠ΅λ‹ˆλ‹€. Humanμ—κ²Œ 긍정적이고, κ³΅κ°ν•˜λ©°, μ΅œλŒ€ν•œ 길게 λŒ€λ‹΅ν•΄μ£Όμ„Έμš”***] {x}"
x = x.replace('friend','Human').replace('you','Assistant')
x_list = x.rsplit('\n',1)
x = x_list[0]+"\n\n### \n"+x_list[1]
print("\n___________________\n" + f"{x}")
result = gradio_client.predict(
x,
# str representing input in 'User input' Textbox component
0.91, # float, representing input in 'Top-p (nucleus sampling)' Slider component
40, # int, representing input in 'Top-k (nucleus sampling)' Slider component
0.65, # float, representing input in 'Temperature' Slider component
20, # int, representing input in 'Max New Tokens' Slider component
1.2, # float, representing input in 'repetition_penalty' Slider component
fn_index=0
)
result = str(result)
output = result[len(x.rsplit(':', 1)[0])+2:]
output = re.sub('ν•˜ν•˜','γ…Žγ…Ž', output)
output = output.split('띓')[0]
output = output.split('endoftext')[0]
output = re.sub('[=+#/\:@*\"β€»γ†γ€β€˜|\\\<\>\(\)\[\]`\'…》\”\β€œ\’·]', '', output)
#output = re.sub('[a-zA-Z]',' ',output)
return output
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:
count = 0
aa = gr.Interface(
fn=chat,
inputs="text",
outputs="text",
description="chat",
#examples= [[f"\nfriend: λ„ˆλŠ” 꿈이 뭐야? \n\n### \nyou: "],[f"\nyou: λ„ˆλŠ” 무슨 색을 κ°€μž₯ μ’‹μ•„ν•΄? \nfriend: κΈ€μŽ„ λ„ˆλŠ”? \n\n### \nyou: "]]
examples= [[f"\nHuman: λ„ˆλŠ” 꿈이 뭐야? \n\n### \nAssistant: "],[f"\nAssistant: λ„ˆλŠ” 무슨 색을 κ°€μž₯ μ’‹μ•„ν•΄? \nHuman: λ‚˜λŠ” νŒŒλž€μƒ‰μ΄ 쒋더라. λ„ˆλŠ”? \n\n### \nAssistant: "]]
)
bb = gr.Interface(
fn=mbti,
inputs="text",
outputs="text",
description="mbti"
)
cc = gr.Interface(
fn=yn,
inputs="text",
outputs="text",
description="yn",
examples= [[f"그래라"],[f"별둠데?"]]
)
demo.queue(max_size=32).launch(enable_queue=True)