import openai
import os
import gradio as gr
import requests
import json

openai.api_key = "your_openai_api_key"

def translate_code(code, from_language, to_language):
    context = f"Translate the following {from_language} code snippet to {to_language}:\n\n{code}\n\nKeep the translation accurate and idiomatic, considering language-specific best practices."

    data = {
        "model": "gpt-3.5-turbo",
        "messages": [{"role": "system", "content": "You are a code translator assistant that translates code snippets between programming languages."}, {"role": "user", "content": context}],
        "max_tokens": 300,
        "temperature": 0.6,
        "top_p": 1,
        "frequency_penalty": 0,
        "presence_penalty": 0,
    }

    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {openai.api_key}",
    }

    try:
        response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, data=json.dumps(data))
        response.raise_for_status()
        result = response.json()

        return result["choices"][0]["message"]["content"].strip()

    except requests.exceptions.HTTPError as e:
        return f"Error: {str(e)}\nResponse: {response.text}"

inputs = [
    gr.inputs.Textarea(placeholder="Enter your code here...", label="Code"),
    gr.inputs.Dropdown(choices=["Python", "JavaScript", "Java", "C++", "C#", "Ruby", "Go", "PHP"], label="From Language"),
    gr.inputs.Dropdown(choices=["Python", "JavaScript", "Java", "C++", "C#", "Ruby", "Go", "PHP"], label="To Language"),
]

outputs = gr.outputs.Textarea(label="Translated Code")

gr.Interface(fn=translate_code, inputs=inputs, outputs=outputs, title="Code Translator", description="Translate code between different programming languages. Note that the translations might not always be perfect and may require some manual adjustments.", theme="compact").launch()