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app1.py

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+import streamlit as st
+import pandas as pd
+import joblib
+
+# Load the saved models and encoders
+ensemble_clf = joblib.load('ensemble_clf.pkl')
+encoder = joblib.load('encoder.pkl')
+label_encoder = joblib.load('label_encoder.pkl')
+
+# Define custom CSS for light and dark modes
+def set_page_styles(dark_mode):
+    if dark_mode:
+        st.markdown(
+            """<style>
+            body {
+                background-color: #ffffff;
+                color: #ffffff;
+            }
+            .stButton > button {
+                background-color: #333333;
+                color: #ffffff;
+                border: 1px solid #444444;
+            }
+            .stTextInput > div > input, .stSelectbox > div > div > div {
+                background-color: #333333;
+                color: #ffffff;
+                border: 1px solid #444444;
+            }
+            .stSidebar {
+                background-color: #1e1e1e;
+                color: #ffffff;
+            }
+            .css-1aumxhk {
+                background-color: #1e1e1e;
+                color: #ffffff;
+            }
+            </style>""",
+            unsafe_allow_html=True,
+        )
+    else:
+        st.markdown(
+            """<style>
+            body {
+                background-color: #ffffff;
+                color: #000000;
+            }
+            .stButton > button {
+                background-color: #f0f0f0;
+                color: #000000;
+                border: 1px solid #cccccc;
+            }
+            .stTextInput > div > input, .stSelectbox > div > div > div {
+                background-color: #ffffff;
+                color: #000000;
+                border: 1px solid #cccccc;
+            }
+            .stSidebar {
+                background-color: #f8f9fa;
+                color: #000000;
+            }
+            .css-1aumxhk {
+                background-color: #f8f9fa;
+                color: #000000;
+            }
+            </style>""",
+            unsafe_allow_html=True,
+        )
+
+# Page configuration
+st.set_page_config(page_title="Laptop Recommendation System", layout="centered")
+
+# Sidebar for theme toggle
+dark_mode = st.sidebar.checkbox("Dark Mode")
+set_page_styles(dark_mode)
+
+# Streamlit app title
+st.title("Laptop Recommendation System")
+
+# Input fields for user preferences
+st.header("Enter Your Preferences")
+with st.form("user_preferences_form"):
+    persona = st.selectbox(
+        "Select Persona", ["Student", "Gamer", "Professional", "Creative", "Engineering", "Business"]
+    )
+    usage = st.text_input(
+        "Describe Usage (e.g., Studying, Gaming, Video Editing)", "Studying, assignments, research"
+    )
+    processor = st.selectbox(
+        "Preferred Processor", ["Intel Core i5 / AMD Ryzen 5", "Intel Core i7 / AMD Ryzen 7"]
+    )
+    ram = st.selectbox("Preferred RAM", ["8GB DDR4", "16GB DDR4"])
+    graphics = st.selectbox(
+        "Preferred Graphics", [
+            "Integrated (Intel Iris Xe)",
+            "NVIDIA RTX 3060 / AMD Radeon RX 6600XT",
+            "NVIDIA RTX 3070 / AMD Radeon RX 6700M",
+            "NVIDIA RTX 3080 / AMD Radeon RX 6800M",
+            "NVIDIA RTX 3090 / AMD Radeon RX 6900M",
+            "Integrated (Intel UHD / AMD Vega)",
+            "Integrated (Intel Iris Xe) or NVIDIA MX550",
+        ]
+    )
+    storage = st.selectbox(
+        "Preferred Storage", [
+            "256GB SSD",
+            "512GB SSD",
+            "1TB HDD",
+            "512GB SSD + 1TB HDD",
+            "1TB SSD + 1TB HDD",
+            "1TB SSD + 2TB HDD",
+        ]
+    )
+    display = st.selectbox("Preferred Display", ["13-15\" Full HD", "15-17\" QHD/4K"])
+    battery = st.selectbox(
+        "Battery Life Expectation", ["6-8 hours", "7-9 hours", "8-12 hours", "12+ hours"]
+    )
+    submit_button = st.form_submit_button(label="Get Recommendation")
+
+# If form is submitted
+if submit_button:
+    # Create a DataFrame from user inputs
+    new_user = pd.DataFrame({
+        'Persona': [persona],
+        'Usage': [usage],
+        'Processor': [processor],
+        'RAM': [ram],
+        'Graphics': [graphics],
+        'Storage': [storage],
+        'Display': [display],
+        'Battery Life': [battery]
+    })
+
+    # Encode the user input
+    new_user_encoded = encoder.transform(new_user)
+
+    # Predict the laptop specification label
+    predicted_label = label_encoder.inverse_transform(ensemble_clf.predict(new_user_encoded))
+
+    # Display the prediction
+    st.subheader("Recommended Laptop Specification")
+    st.success(f"**{predicted_label[0]}**")

encoder.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:87d7246e07a7fdcc61233b1b6d4ccf9f1c605b118e7d1d9111b806ac75ecb6c1
+size 4299

ensemble_clf.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:806acaa9cd16f648e510d8d606af500adc9daf6296c3fc1ec0f775b743074648
+size 415937

label_encoder.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:33074751a1ba25e5b54e3558448cc37188fde2e65c370bf6c095576f8fde0d98
+size 1106

requirements.txt

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+Flask
+pandas
+joblib
+scikit-learn
+# Add any additional dependencies here