import gradio as gr
import random

from llm.openai import Llm

# # mock for testing
# from llm.mock import Llm

llm = Llm()

def assistant_response(prompt):
    answer = llm.chatcompletion(prompt)
    return answer

def respond(message, chat_history):
    answer = llm.chatcompletion(message)
    print(answer)
    chat_history.append((message, answer))
    return "", chat_history

title = "OpenAPI Assistant API: " + llm.assistant.name

if llm.assistant.description is None:
    model = llm.assistant.model
    description = f"このデモはOpenAPI Assistant APIのデモです。テキストボックスにテキストを入力すると、{model}モデルが応答します。"
else:
    description = llm.assistant.description

# 実行例のリスト (現在使用してない)
import csv
examples = []
with open('flagged/log.csv', 'r', encoding='utf-8') as file:
    reader = csv.DictReader(file)
    examples = [row['prompt'] for row in reader]

with gr.Blocks() as demo:
    gr.Markdown(
    f"""
    # {title}
    {description}
    """)
    
    chatbot = gr.Chatbot()
    msg = gr.Textbox()
    clear = gr.ClearButton([msg, chatbot])
    examples=examples

    msg.submit(respond, [msg, chatbot], [msg, chatbot])

if __name__ == "__main__":
    demo.launch()