app.py

import gradio as gr
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM

# Load the fine-tuned model
model_name = "gpt2"  # Replace with your fine-tuned model path if available
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
generator = pipeline("text-generation", model=model, tokenizer=tokenizer)

# Define chatbot function
def chatbot_response(input_text):
    response = generator(input_text, max_length=50, num_return_sequences=1)
    return response[0]['generated_text']

# Create Gradio interface
interface = gr.Interface(
    fn=chatbot_response,
    inputs="text",
    outputs="text",
    title="Love and Smile",
    description="An AI assistant for enhanced texting, flirting, and dating conversations.",
)

# Launch app
interface.launch()