import streamlit as st from transformers import pipeline ################################################### pipe = pipeline("text-generation", model='all-MiniLM-L6-v2') def main(): try: st.title("Which Resort is best for you?") weathers = ["Sunny", "Rainy", "Snowy"] activities = ["Skiing", "Hiking", "Swimming", "Relaxing"] weather = st.selectbox("What is the weather like?", weathers) activity = st.selectbox("What activity do you prefer?", activities) input_prompt = f"The weather is {weather.lower()} and I like {activity.lower()}." if st.button('Recommend a Resort'): with st.spinner('Generating recommendation...'): # Generate text based on the input prompt generated_texts = pipe(input_prompt, max_length=50, num_return_sequences=1) recommendation = generated_texts[0]['generated_text'] # Displaying the generated recommendation st.subheader("Recommended Resort:") st.write(recommendation) except Exception as e: st.error(e) ################################################### if __name__=="main": main()