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import gradio as gr
import openai
from openai import OpenAI
import os
api_secret = os.getenv('openaikey')
model = os.getenv('model')
client = OpenAI(api_key=api_secret)
sysint ='Sampean asisten ingkang mangsuli ngangge basa Jawa Krama, sanes Ngoko.'
def ask(request, temp, topp,):
chat_completion = client.chat.completions.create(
messages=[
{"role": 'system', "content": sysint},
{"role": 'user', "content": request}],
temperature=temp,
top_p=topp,
max_tokens=700,
model=model
)
response = chat_completion.choices[0].message.content
return response
with gr.Blocks(theme='snehilsanyal/scikit-learn') as app:
gr.Interface(
fn=ask,
inputs=[
gr.Textbox(value='Panjenengan saged nerangaken menapa kacerdhasan gaweyan saged gadhah peranan wigatos babagan pelestarian basa?', label="Pitakenan Jawa Krama"),
gr.Slider(label="Temperature",minimum=0,maximum=1,value=.5,step=.05),
gr.Slider(label="Top p",minimum=0,maximum=1,value=.5,step=.05)
],
outputs=gr.Textbox(label="Mangsulan"),
title="Jawa Krama Chatbot Demo",
allow_flagging="never",
description='This is a fine-tuned version of GPT-3.5 Turbo, trained to speak Krama Javanese. The model is optimized to respond to educational questions.')
app.launch(debug=True, share=True) |