app.py

import streamlit as st
import pandas as pd
import numpy as np
import faiss

# Set page configuration
st.set_page_config(
    page_title="Crop Yield Predictor",
    page_icon="🌾",
    layout="wide",
    initial_sidebar_state="expanded"
)

# Header with title and local image
st.markdown("<h1 style='text-align: center; color: green;'>🌾 Crop Yield Prediction and Recommendations 🌱</h1>", unsafe_allow_html=True)

# Try loading the local image
try:
    st.image("./assets/agriculture_image.png", use_column_width=True)  # Ensure path is correct
except Exception:
    st.warning("Image not found. Please check if 'agriculture_image.png' exists in the 'assets/' folder.")

# Sidebar for uploading CSV
st.sidebar.header("Upload Crop Data CSV")
uploaded_file = st.sidebar.file_uploader("Upload your file here", type=["csv"])

# Check if file is uploaded
if uploaded_file is not None:
    data = pd.read_csv(uploaded_file)
    st.sidebar.success("File uploaded successfully!")

    # Display uploaded data
    st.write("### Uploaded Data")
    st.dataframe(data.head())

    # Select ID for prediction
    id_column = st.sidebar.selectbox("Select ID Column", options=data.columns)
    selected_id = st.sidebar.selectbox("Select ID", options=data[id_column].unique())

    # Dummy FAISS-based recommendation
    def dummy_recommendation(df, selected_id):
        # Filter data for selected ID (replace with actual FAISS logic)
        selected_data = df[df[id_column] == selected_id].iloc[0]
        recommendations = {
            "Crop Type": "Wheat",
            "Optimal pH": "6.0 - 7.0",
            "Soil Recommendation": "Loamy Soil",
            "Watering Schedule": "Twice a week"
        }
        return recommendations

    # Display prediction and recommendations
    if st.button("Get Recommendations"):
        st.write(f"### Recommendations for ID: {selected_id}")
        recommendations = dummy_recommendation(data, selected_id)
        for key, value in recommendations.items():
            st.markdown(f"<p style='font-size: 18px;'><strong>{key}:</strong> {value}</p>", unsafe_allow_html=True)
else:
    st.warning("Please upload a CSV file to proceed.")

# Footer
st.markdown("---")
st.markdown("<h3 style='text-align: center;'>Made with ❤️ for Sustainable Agriculture 🌱</h3>", unsafe_allow_html=True)
st.markdown("<p style='text-align: center;'>Powered by Streamlit</p>", unsafe_allow_html=True)