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| import gradio as gr | |
| from transformers import pipeline | |
| import urllib.parse | |
| def extract_keywords(text: str, nlp_pipeline) -> list: | |
| """Extract relevant keywords from the input text""" | |
| prompt = f"Extract 3-4 most relevant gift-related keywords from: {text}\nKeywords:" | |
| response = nlp_pipeline(prompt, max_new_tokens=30, num_return_sequences=1) | |
| keywords = response[0]['generated_text'].split('Keywords:')[-1].strip() | |
| return [k.strip() for k in keywords.split(',') if k.strip()] | |
| def generate_search_urls(keywords: list) -> dict: | |
| """Generate search URLs for various e-commerce platforms""" | |
| # Encode queries properly for URLs | |
| query = urllib.parse.quote(" ".join(keywords)) | |
| return { | |
| "Amazon India": f'<a href="https://www.amazon.in/s?k={query}" target="_blank">Amazon</a>', | |
| "Flipkart": f'<a href="https://www.flipkart.com/search?q={query}" target="_blank">Flipkart</a>', | |
| "IGP Gifts": f'<a href="https://www.igp.com/search?q={query}" target="_blank">IGP</a>', | |
| "IndiaMart": f'<a href="https://www.indiamart.com/find?q={query}" target="_blank">IndiaMart</a>', | |
| } | |
| def recommend_gifts(text: str): | |
| """Main function to generate gift recommendations""" | |
| if not text: | |
| return "⚠️ Please provide a description." | |
| try: | |
| # Load GPT-2 as a text-generation model | |
| nlp = pipeline( | |
| "text-generation", | |
| model="gpt2", | |
| device_map="auto" | |
| ) | |
| # Extract relevant keywords | |
| keywords = extract_keywords(text, nlp) | |
| # Generate search URLs | |
| search_links = generate_search_urls(keywords) | |
| # Format the output as clickable links | |
| formatted_output = f""" | |
| <h3>🔍 Predicted Interests: {", ".join(keywords)}</h3> | |
| <h3>🛒 Gift Suggestions:</h3> | |
| <ul> | |
| <li>{search_links["Amazon India"]}</li> | |
| <li>{search_links["Flipkart"]}</li> | |
| <li>{search_links["IGP Gifts"]}</li> | |
| <li>{search_links["IndiaMart"]}</li> | |
| </ul> | |
| """ | |
| return formatted_output | |
| except Exception as e: | |
| return f"❌ Error: {str(e)}" | |
| # Create Gradio interface with HTML output | |
| demo = gr.Interface( | |
| fn=recommend_gifts, | |
| inputs=gr.Textbox( | |
| lines=3, | |
| placeholder="Describe who you're buying a gift for (age, interests, occasion, etc.)" | |
| ), | |
| outputs=gr.HTML(), # Change output type to HTML | |
| title="🎁 Smart Gift Recommender", | |
| description="Get personalized gift suggestions with direct shopping links!", | |
| examples=[ | |
| ["a small kid of age 3 want him to have something like a toy that teaches alphabets"], | |
| ["age is 25 and he loves puzzle and online FPS games"], | |
| ["Looking for a gift for my mom who enjoys gardening and cooking"] | |
| ] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |