app.py

import streamlit as st
from transformers import pipeline 


###################################################
model_name = "sentence-transformers/all-MiniLM-L6-v2"
pipe = pipeline("text-generation", model=model_name)

    
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)