app.py

import streamlit as st
from utils import validate_sequence, predict
from model import model

def main():
    st.title("AA Property Inference Demo")
    
    # User input: Text and CSV
    sequence = st.text_input("Enter your amino acid sequence:")
    uploaded_file = st.file_uploader("Or upload a CSV file with amino acid sequences", type="csv")

    if st.button("Analyze Sequence"):
        sequences = [sequence] if sequence else []
        if uploaded_file:
            df = pd.read_csv(uploaded_file)
            sequences.extend(df['sequence'].tolist())

        results = []
        for seq in sequences:
            if validate_sequence(seq):
                model_results = {}
                for model_name, model in models.items():
                    prediction, confidence = predict(model, seq)
                    model_results[model_name] = {"Prediction": prediction, "Confidence": confidence}
                results.append({"Sequence": seq, **model_results})
            else:
                st.error(f"Invalid sequence: {seq}")
        
        if results:
            st.write("### Results")
            st.table(results)

if __name__ == "__main__":
    main()