import gradio as gr
import requests
import json
from transformers import pipeline

API_URL = "https://api.openai.com/v1/chat/completions"

# 번역 파이프라인 초기화
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")

def translate_text(text):
    # 입력된 텍스트를 영어로 번역
    translation = translator(text, max_length=512)
    translated_text = translation[0]['translation_text']
    return translated_text

def predict(inputs, top_p, temperature, openai_api_key):
    narration_prompt = f"아동용 애니메이션 동영상에 사용할 스크립트를 작성하라. 반드시 한글로 작성할것. 입력: '{inputs}'"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {openai_api_key}"
    }
    payload = {
        "model": "gpt-4-1106-preview",
        "messages": [{"role": "system", "content": narration_prompt}],
        "temperature": temperature,
        "top_p": top_p,
        "n": 1,
        "max_tokens": 1000
    }
    response = requests.post(API_URL, headers=headers, json=payload)
    if response.status_code == 200:
        response_data = response.json()
        generated_text = response_data['choices'][0]['message']['content']
        return generated_text
    else:
        return "Error: Unable to generate response."

def generate_prompts(script):
    # 스크립트의 각 줄을 영어로 번역하여 프롬프트 생성
    lines = script.split('\n')
    translated_prompts = [translate_text(line) for line in lines if line.strip() != '']
    return "\n".join(translated_prompts)

with gr.Blocks() as demo:
    gr.Markdown("<h1 align='center'>토리의 모험: 3D 애니메이션 생성기</h1>")
    with gr.Row():
        openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here")
        inputs = gr.Textbox(placeholder="여기에 입력하세요.", label="아동용 애니메이션 스크립트를 생성하고 싶은 주제어나 문장을 입력하세요.")
        top_p = gr.Slider(minimum=0, maximum=1.0, value=1.0, step=0.05, label="Top-p (nucleus sampling)")
        temperature = gr.Slider(minimum=0, maximum=5.0, value=1.0, step=0.1, label="Temperature")
    output = gr.Textbox(label="Generated Script", readonly=True)
    prompts_output = gr.TextArea(label="Translated Image Generation Prompts", readonly=True)
    submit_button = gr.Button("Generate Script")
    prompts_button = gr.Button("Translate Prompts")

    submit_button.click(fn=predict, inputs=[inputs, top_p, temperature, openai_api_key], outputs=output)
    prompts_button.click(fn=generate_prompts, inputs=[output], outputs=prompts_output)

demo.launch()