app.py

import gradio as gr
from transformers import pipeline

# Load grammar correction & dictionary models
corrector = pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
dictionary = pipeline("text2text-generation", model="google/flan-t5-small")

def smart_gpt(input_text):
    input_text = input_text.strip()

    # Single word check
    if " " not in input_text:
        meaning = dictionary(f"define {input_text}")[0]['generated_text']
        return f"""
🧠 **SmartGPT Word Check**

✅ **Word:** {input_text}
📖 **Meaning:** {meaning}

💬 **Gen Z Vibe:** Bro that word lowkey slaps 😎
        """

    # Sentence check
    correction = corrector(input_text)[0]['generated_text'].strip()
    
    if correction.lower() == input_text.lower():
        return f"""
🧠 **SmartGPT Sentence Check**

✅ **Sentence:** Looks perfect, chief 🔥  
✨ **Better Version:** {correction}  
💭 **Gen Z Vibe:** You cooked, no cap 😎
        """
    else:
        return f"""
🧠 **SmartGPT Grammar Fix**

❌ **Found issues in:** {input_text}  
✅ **Fixed Version:** {correction}  
✨ **Better Version:** {correction}  
💭 **Gen Z Vibe:** Bro we fixed it fr 😭🔥
        """

# Interface UI setup
demo = gr.Interface(
    fn=smart_gpt,
    inputs=gr.Textbox(lines=2, placeholder="Type a word or sentence here...", label="Enter text 💬"),
    outputs=gr.Markdown(label="SmartGPT Response 💡"),
    title="SmartGPT 🔥",
    description="Your AI homie for spelling, grammar & Gen Z style chats 😎",
    theme="soft",  # clean pastel theme
)

demo.launch()