Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,98 @@
-import altair as alt
-import numpy as np
+import requests
 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])),
-    ))
+# 🚀 Your deployed Flask backend URL
+BACKEND_URL = "https://Pushpak21-EngineeringGeneral.hf.space/predict"
+
+st.title("🎯 Engineering College Predictor")
+st.write("Enter your details below:")
+
+# 📋 Input controls
+category = st.selectbox("Category", ['GOPEN', 'GSC', 'GSEBC', 'LOPEN', 'LST', 'LOBC', 'EWS', 'GST',
+       'GOBC', 'LSEBC', 'LSC', 'GNTA', 'LNTB', 'GNTB', 'GNTC', 'LNTA',
+       'GNTD', 'LNTC', 'LNTD', 'ORP'])
+
+course = st.selectbox("Category", ['Civil Engineering', 'Computer Science and Engineering',
+       'Information Technology', 'Electrical Engineering',
+       'Electronics and Telecommunication Engg',
+       'Instrumentation Engineering', 'Mechanical Engineering',
+       'Computer Engineering', 'Electrical Engg[Electronics and Power]',
+       'Artificial Intelligence (AI) and Data Science', 'Industrial IoT',
+       'Artificial Intelligence and Data Science', 'Chemical Engineering',
+       'Computer Science and Engineering(Data Science)',
+       'Production Engineering', 'Textile Technology',
+       'Electronics and Computer Engineering',
+       'Computer Science and Engineering(Artificial Intelligence and Machine Learning)',
+       'Agricultural Engineering', 'Computer Science and Design',
+       'Plastic and Polymer Engineering', 'Electronics Engineering',
+       'Electrical and Electronics Engineering',
+       'Artificial Intelligence and Machine Learning',
+       'Electronics Engineering ( VLSI Design and Technology)',
+       'Electronics and Communication(Advanced Communication Technology)',
+       'Artificial Intelligence', 'Production Engineering[Sandwich]',
+       'Electronics and Telecommunication Engg[Direct Second Year Second Shift]',
+       'Petro Chemical Engineering', 'Computer Science and Technology',
+       'Electronics and Communication Engineering', 'Data Science',
+       'Mechatronics Engineering', 'Civil and infrastructure Engineering',
+       'Bio Medical Engineering', 'Electronics and Computer Science',
+       'Computer Science and Engineering (Internet of Things and Cyber Security Including Block Chain Technology)',
+       'Cyber Security', 'Mechanical & Automation Engineering',
+       'Food Technology', 'Paper and Pulp Technology',
+       'Computer Technology', 'Aeronautical Engineering',
+       'Mining Engineering', 'Computer Science and Engineering (IoT)',
+       'Oil Fats and Waxes Technology', 'Paints Technology',
+       'Instrumentation and Control Engineering',
+       'Automation and Robotics', 'Robotics and Automation',
+       'Structural Engineering', 'Civil and Environmental Engineering',
+       'Automobile Engineering', 'Robotics and Artificial Intelligence',
+       'Manufacturing Science and Engineering',
+       'Metallurgy and Material Technology',
+       'Computer Science and Business Systems',
+       'Computer Engineering (Software Engineering)',
+       'Computer Engineering[Direct Second Year Second Shift]',
+       'Computer Science and Information Technology',
+       'Fashion Technology', 'Textile Plant Engineering',
+       'Computer Science and Engineering (Artificial Intelligence and Data Science)',
+       'Electrical and Computer Engineering', 'Printing Technology',
+       'Mechanical Engineering[Sandwich]',
+       'Computer Science and Engineering (Artificial Intelligence)'])
+
+rank = st.number_input("Rank", min_value=1, value=1500)
+percentage = st.number_input("Percentage", min_value=0.0, max_value=100.0, value=75.0)
+
+if st.button("Predict Top 20 Choices"):
+    payload = {
+        "Category": category,
+        "Rank": rank,
+        "Percentage": percentage,
+        "Course Name": course
+    }
+
+    # 🔷 Call your backend API
+    resp = requests.post(BACKEND_URL, json=payload)
+    if resp.status_code != 200:
+        st.error(f"Backend error: {resp.status_code}")
+        st.write(resp.text)
+    else:
+        data = resp.json().get("top_20_predictions", [])
+        if not data:
+            st.warning("No predictions returned.")
+        else:
+            df = pd.DataFrame(data)
+
+            # Reorder & rename columns
+            df = df[["rank", "choice_code", "college_name", "probability_percent"]]
+            df.rename(columns={
+                "rank": "Rank",
+                "choice_code": "Choice Code",
+                "college_name": "College Name",
+                "probability_percent": "Probability (%)"
+            }, inplace=True)
+
+            # 🎯 Display table without index and full width
+            st.write("### 🎯 Top‑20 Predicted Choices")
+            st.dataframe(
+                df.style.hide(axis="index"),
+                use_container_width=True
+            )