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,):
    request = str(request)
    results = []
    for i in range(iterations):
        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
        )
        rescount = f'Result {i+1}:\n'
        respond = chat_completion.choices[0].message.content
        nline = '\n_______________________________________\n'
        results.append(f'{rescount}{respond}{nline}')
    
    return ''.join(results)

with gr.Blocks(theme='snehilsanyal/scikit-learn') as app:
    gr.Interface(
    fn=ask,
    inputs=[
        gr.Textbox(valu='Panjenengan saged nerangaken menapa LLM saged gadhah peranan wigatos babagan pelestarian basa?', label="Pitakenan Jawa Krama"),
    gr.Slider(label="Temperature",minimum=0,maximum=1,value=.9,step=.05),
    gr.Slider(label="Top p",minimum=0,maximum=1,value=.1,step=.05),
    gr.Checkbox(label="Generate 3 at once")
    ],
    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)