app.py

import gradio as gr
from transformers import DistilGPT2LMHeadModel, DistilGPT2Tokenizer

# Load pre-trained DistilGPT-2 model and tokenizer
tokenizer = DistilGPT2Tokenizer.from_pretrained("distilgpt2")
model = DistilGPT2LMHeadModel.from_pretrained("distilgpt2")

# Function to generate keywords from input text
def generate_keywords(prompt):
    # Encode the input text
    inputs = tokenizer.encode(prompt, return_tensors="pt")

    # Generate output
    outputs = model.generate(inputs, max_length=50, num_return_sequences=1, no_repeat_ngram_size=2, top_k=50, top_p=0.95)

    # Decode and return the generated text (keywords)
    keywords = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return keywords.strip()

# Gradio interface
iface = gr.Interface(fn=generate_keywords, 
                     inputs=gr.Textbox(label="Enter Ad Prompt", placeholder="E.g., Generate ad keywords for wireless headphones"), 
                     outputs=gr.Textbox(label="Generated Keywords"),
                     live=True)

# Launch the Gradio interface
iface.launch()