import gradio as gr
import openai
import os
import requests

# Load the OpenAI API key from environment variables
openai.api_key = os.getenv("OPENAI_API_KEY")

def translate_and_speak(text):
    try:
        # Translate text using OpenAI's ChatGPT-3.5 Turbo
        response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=[{"role": "system", "content": "try translate every prompt of word  with Skibidi, rizz, ohio, edging, yapping, fanum tax, glazing, dogwater, girlboss, alpha, andrew tate, beta, baby gronk, musty, crook, quandale dingle, kai cenat, grimace, ice spice, turbulence, 3 am, lovvy dunne, mewing, mouthbreather, beta, level 1000 gyatt, caseoh, food taxer, looksmaxxing, gooner, gooning, goon"}, 
                      {"role": "user", "content": text}],
            max_tokens=150
        )
        translated_text = response['choices'][0]['message']['content']

        # Generate speech from translated text using Whisper
        whisper_response = openai.Audio.create(
            model="whisper-1",
            input=translated_text,
            output_format="mp3"
        )
        audio_url = whisper_response['url']

        # Download the MP3 file from the URL
        response = requests.get(audio_url)
        if response.status_code == 200:
            # Save the MP3 file to a temporary path
            mp3_path = "/tmp/translated_audio.mp3"  # Ensure this path is writable
            with open(mp3_path, "wb") as f:
                f.write(response.content)
            return translated_text, mp3_path
        else:
            return translated_text, "Error downloading file"
    except Exception as e:
        return f"Error: {str(e)}", ""

# Create the Gradio interface
interface = gr.Interface(
    fn=translate_and_speak,
    inputs=gr.Textbox(label="Enter text to translate"),
    outputs=[gr.Textbox(label="Translated Text"), gr.Audio(label="Listen to Translation")],
    title="Skibidi Translator",
    description="Type any phrase to translate it into a specific set of keywords and hear it spoken back."
)

# Launch the interface
interface.launch(share=True)