import gradio as gr
import subprocess
import openapi
import time

def translate(text_input, openapi_key):
    openai.api_key = openapi_key
    
    text_list = text_input.split('\n')[12:]

    reply = []
    
    for i in range(0,len(text_list)+9,10):
        content = """What do these sentences about Hugging Face Transformers (a machine learning library) mean in Korean? Please do not translate the word after a 🤗 emoji as it is a product name. Please ignore the video and image and translate only the sentences I provided. Ignore the contents of the iframe tag.
                ```md
                %s"""%'\n'.join(text_list[i:i+10])

        chat = openai.ChatCompletion.create(
        model = "gpt-3.5-turbo-0301", messages=[
            {"role": "system", 
             "content": content},])
            
        print("질문")
        print(content)
        print("응답")
        print(chat.choices[0].message.content)
        
        reply.append(chat.choices[0].message.content)

        time.sleep(20)
        
    return reply

inputs = [
    gr.inputs.Textbox(lines=2, label="Input Open API Key"),
    gr.inputs.File(label="Upload MDX File")
]

outputs = gr.outputs.Textbox(label="Translation")

def translate_with_upload(text, file):
    
    openapi_key = text
    
    if file is not None:
        # 파일 이름을 추출합니다.
        filename = os.path.basename(file.name)
        # 새로운 파일 이름을 생성합니다.
        new_filename = f"text_{filename}"
        # sed 명령어를 사용하여 파일을 변환합니다.
        subprocess.run(f"sed '/```/,/```/d' {filename} | sed '/^|.*|$/d' | sed '/^$/N;/^\n$/D' > {new_filename}", shell=True)
        # 새로운 파일을 열어서 내용을 읽어옵니다.
        with open(new_filename, 'r') as f:
            text_input = f.read()
    else:
        # 파일이 업로드되지 않은 경우, 빈 문자열로 초기화합니다.
        text_input = ""
        
    return translate(text_input, openapi_key)

prompt_translate = gr.Interface(
    fn=translate_with_upload,
    inputs=inputs,
    outputs=outputs,
    title="ChatGPT Korean Prompt Translation",
    description="Translate your text into Korean using the GPT-3 model.",
    theme="compact"
)

prompt_translate.launch()