import gradio as gr
from openai import OpenAI
import pandas as pd
import io
import tempfile
import shutil
import google.generativeai as genai
import os

api_key = os.getenv("OPENAI_API_KEY")
gemni_api_key = os.getenv("GEMNI_API_KEY")


supported_languages = ['English', 'Brazilian Portuguese', 'Latin American Spanish', 'French', 'European Portuguese', 'Castilian Spanish', 'German', 'Italian', 'Czech', 'Danish', 'Dutch', 'Finnish', 'Norwegian', 'Swedish', 'Hungarian', 'Greek', 'Romanian', 'Polish', 'Arabic', 'Urdu']




# OPENAI
client = OpenAI(api_key  = api_key)

def translate_text_openai(source_language, target_language, TEXT, max_characters):

    response = client.chat.completions.create(
      model="gpt-3.5-turbo-0125",
      temperature = 0.1,
      messages=[
        {"role": "system", "content": "You are a multilingual translator for movies subtitles."},
        {"role": "system", "content": "The number of input characters and output characters should be the same despite the change in language."},
         {"role": "system", "content": f"In response, maximum characters allowed are {max_characters}"},
        {"role": "system", "content": "You SHOULD NOT SKIP ANY LINE OR ANY INFORMATION"},
        {"role": "system", "content": "The Tranlation should be error proof"},


        {"role": "user", "content": f"""Translate the text from {source_language} language to {target_language} language.:
        \nTEXT: {TEXT}
        NOTE: THE OUTPUT SHOULD BE IN  {target_language} language.
        \nREMEMBER: MAXIMUM output chaeracters should be {max_characters}

        END NOTE: THE OUTPUT SHOULD BE IN  {target_language} language.
        REMEMBER: THE OUTPUT SHOULD BE IN  {target_language} language.
        Hey on some instances you give response in languages other than {target_language}, which is wrong
        """},
      ]
    )
    return response.choices[0].message.content

def translate_text_correct_openai(source_language, target_language, TEXT, max_characters):

    response = client.chat.completions.create(
      model="gpt-3.5-turbo-0125",
      temperature = 0.1,
      messages=[
        {"role": "system", "content": "You reduce the size of the sentences."},
        {"role": "system", "content": f"The maximuim output should not be more than {max_characters} characters."},
        {"role": "user", "content": f"""
        DO NOT CHANGE THE LANGUAGE
         Reduce the size of the text to less than {max_characters} characters even if there is a change in meaning.
         REMEMBER LLM, THE INPUT AND THE OUTPUT SHOULD BE IN THE SAME LANGUAGE
         \nWrite the sentence in shortest possible manner
        \nTEXT: {TEXT}\
        REMEMBER LLM, THE INPUT AND THE OUTPUT SHOULD BE IN THE SAME LANGUAGE
     
        """},
      ]
    )
    return response.choices[0].message.content

# GEMNI


genai.configure(api_key=gemni_api_key)

model = genai.GenerativeModel('gemini-1.5-flash')


def translate_text_gemni(source_language, target_language, TEXT, max_characters):

    response = model.generate_content(f'''You are a multilingual translator for movies subtitles.
        The number of input characters and output characters should be the same despite the change in language.
        In response, maximum characters allowed are {max_characters}.
        You SHOULD NOT SKIP ANY LINE OR ANY INFORMATION.
        The Tranlation should be error proof.
        Translate the text from {source_language} language to {target_language} language.:
        \nTEXT: {TEXT}
        NOTE: THE OUTPUT SHOULD BE IN  {target_language} language.
        \nREMEMBER: MAXIMUM output chaeracters should be {max_characters}

        END NOTE: THE OUTPUT SHOULD BE IN  {target_language} language.
        REMEMBER: THE OUTPUT SHOULD BE IN  {target_language} language.
        Hey on some instances you give response in languages other than {target_language}, which is wrong
        '''

    )
    return response.text

def translate_text_correct_gemni(source_language, target_language, TEXT, max_characters):

    response = model.generate_content(f"""
        You reduce the size of the sentences.
        The maximuim output should not be more than {max_characters} characters.
        DO NOT CHANGE THE LANGUAGE
        Reduce the size of the text to less than {max_characters} characters even if there is a change in meaning.
        REMEMBER LLM, THE INPUT AND THE OUTPUT SHOULD BE IN THE SAME LANGUAGE
         \nWrite the sentence in shortest possible manner
        \nTEXT: {TEXT}\
        REMEMBER LLM, THE INPUT AND THE OUTPUT SHOULD BE IN THE SAME LANGUAGE
        """
    )
    return response.text










def check_conditon_openai(source_language, target_language, response, max_characters):
  length = len(response)
  
  if length > int(max_characters):
    response = translate_text_correct_openai(source_language, target_language, response, max_characters)
    return check_conditon_openai(source_language, target_language, response, max_characters)
  return response


def check_conditon_gemni(source_language, target_language, response, max_characters):
  length = len(response)
  
  if length > int(max_characters):
    response = translate_text_correct_gemni(source_language, target_language, response, max_characters)
    return check_conditon_gemni(source_language, target_language, response, max_characters)
  return response




def get_translation(source_language, target_language, TEXT, max_characters):
    
    response_openai = translate_text_openai(source_language, target_language, TEXT, max_characters)
    response_openai = check_conditon_openai(source_language, target_language, response_openai, max_characters)

    response_gemni = translate_text_gemni(source_language, target_language, TEXT, max_characters)
    response_gemni = check_conditon_gemni(source_language, target_language, response_gemni, max_characters)


    excel_data_path = create_excel(TEXT, response_openai, response_gemni)

    
    return excel_data_path


def create_excel(TEXT, response_openai, response_gemni):
    # Create a DataFrame from the input data
    df = pd.DataFrame({"Original Text": TEXT, "OpenAI Translated": response_openai, "Gemni Translated": response_gemni}, index = [1])
    
    # Create a temporary file to store the Excel data
    with tempfile.NamedTemporaryFile(delete=False, suffix='.xlsx') as temp_file:
        # Write the DataFrame to the temporary file as an Excel file
        with pd.ExcelWriter(temp_file, engine='xlsxwriter') as writer:
            df.to_excel(writer, index=False, sheet_name='Sheet1')
        
        # Return the path to the temporary file
        temp_file_path = temp_file.name
    
    return temp_file_path


iface = gr.Interface(
    fn=get_translation,
    inputs=[
        gr.Dropdown(choices= supported_languages, label="Source Language"),  # Add more languages as needed
        gr.Dropdown(choices= supported_languages, label="Target Language"),
        gr.Textbox(lines=2, label="Input Text"),
        gr.Textbox(lines=1, label="Difine number of output characters"),
    ],
    outputs=gr.File(label="Download Excel File"),
    title="MVP Multilingual Translation",
    description="MVP Multilingual Translation by Farhan",
)

iface.launch(share=True, debug=True)