Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,33 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+from model.predictor import predict_footprint
+from utils.reducer import suggest_reduction
+
+st.set_page_config(page_title="GreenPrint AI 🌱", layout="centered")
+
+st.title("🌿 GreenPrint AI: Carbon Footprint Detector")
+st.markdown("Estimate your carbon footprint and get eco-friendly suggestions.")
+
+# User Input
+with st.form("activity_form"):
+    car_km = st.number_input("🚗 Car travel per week (km)", 0, 1000, 50)
+    electricity = st.number_input("💡 Electricity usage per month (units)", 0, 1000, 200)
+    meat = st.number_input("🍖 Meat meals per week", 0, 21, 7)
+    flights = st.number_input("✈️ Flights per year", 0, 20, 1)
+
+    submitted = st.form_submit_button("Calculate")
+
+if submitted:
+    user_input = {
+        "car_km_per_week": car_km,
+        "electricity_units_per_month": electricity,
+        "meat_meals_per_week": meat,
+        "flights_per_year": flights
+    }
+
+    result = predict_footprint(user_input)
+    st.success(f"Estimated Annual Carbon Footprint: **{result:.2f} kg CO₂**")
+
+    st.markdown("---")
+    st.subheader("♻️ Suggestions to Reduce Your Footprint")
+    for tip in suggest_reduction(user_input):
+        st.markdown(f"- {tip}")