import os
import gradio as gr
from groq import Groq

# Get API key from environment (will be set in Hugging Face Space secrets)
api_key = os.environ.get("GROQ_API_KEY")
if not api_key:
    raise ValueError("GROQ_API environment variable not set. Please add it to Space Secrets.")

client = Groq(api_key=api_key)

def translate_english_to_nepali(text):
    if not text or not text.strip():
        return "Please enter some English text to translate."
    
    try:
        response = client.chat.completions.create(
            model="llama-3.3-70b-versatile",
            messages=[
                {
                    "role": "system", 
                    "content": "You are a professional translator. Translate the given English text to Nepali (नेपाली) accurately. Provide only the translation without explanations, transliterations, or additional text."
                },
                {
                    "role": "user", 
                    "content": text
                }
            ],
            temperature=0.1,  # Lower temperature for more consistent translations
            max_tokens=1024
        )
        
        translation = response.choices[0].message.content.strip()
        return translation
        
    except Exception as e:
        return f"Error: {str(e)}"

# Custom CSS for better appearance
css = """
.container {max-width: 800px; margin: 0 auto;}
.input-text {font-size: 16px;}
.output-text {font-size: 18px; font-weight: 500;}
"""

with gr.Blocks(css=css, title="English to Nepali Translator") as demo:
    gr.Markdown(
        """
        # 🇬🇧 ➡️ 🇳🇵 English to Nepali Translator
        Made for Kucchi Mucchi | High-speed AI Translation
        """
    )
    
    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(
                label="English Text",
                placeholder="Enter English text here...",
                lines=6,
                elem_classes="input-text"
            )
            translate_btn = gr.Button("🔄 Translate", variant="primary", size="lg")
            clear_btn = gr.Button("Clear", size="sm")
        
        with gr.Column():
            output_text = gr.Textbox(
                label="Nepali Translation (नेपाली अनुवाद)",
                lines=6,
                elem_classes="output-text",
                interactive=False
            )
    
    gr.Markdown(
        """
        ### Tips:
        - Enter natural English sentences for best results
        - The model handles formal and informal Nepali contexts
        - Supports long paragraphs (up to 1024 tokens)
        """
    )
    
    # Event handlers
    translate_btn.click(
        fn=translate_english_to_nepali,
        inputs=input_text,
        outputs=output_text
    )
    
    clear_btn.click(
        fn=lambda: ("", ""),
        inputs=None,
        outputs=[input_text, output_text]
    )
    
    # Allow Enter key to submit
    input_text.submit(
        fn=translate_english_to_nepali,
        inputs=input_text,
        outputs=output_text
    )

# Launch configuration
if __name__ == "__main__":
    demo.launch()