Update src/streamlit_app.py

src/streamlit_app.py

@@ -9,9 +9,6 @@ import os
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 model = joblib.load(os.path.join(BASE_DIR, "breast_cancer_model.pkl"))
 
-# ======================
-# PAGE CONFIG
-# ======================
 st.set_page_config(
     page_title="Breast Cancer Prediction",
     page_icon="🎗️",
@@ -19,29 +16,27 @@ st.set_page_config(
 )
 
 st.title("🎗️ Breast Cancer Prediction")
-st.write("Predict whether a tumor is benign or malignant")
+st.write("Auto-generated inputs based on trained model features")
 
 # ======================
-# SIDEBAR INPUTS
+# GET FEATURE NAMES
 # ======================
-st.sidebar.header("Cell Nuclei Measurements")
-
-radius_mean = st.sidebar.slider("Radius Mean", 5.0, 30.0, 14.0)
-texture_mean = st.sidebar.slider("Texture Mean", 5.0, 40.0, 19.0)
-perimeter_mean = st.sidebar.slider("Perimeter Mean", 40.0, 200.0, 90.0)
-area_mean = st.sidebar.slider("Area Mean", 200.0, 2500.0, 650.0)
-smoothness_mean = st.sidebar.slider("Smoothness Mean", 0.05, 0.2, 0.1)
+feature_names = model.feature_names_in_
 
 # ======================
-# DATAFRAME
+# CREATE INPUTS
 # ======================
-input_df = pd.DataFrame({
-    "radius_mean": [radius_mean],
-    "texture_mean": [texture_mean],
-    "perimeter_mean": [perimeter_mean],
-    "area_mean": [area_mean],
-    "smoothness_mean": [smoothness_mean]
-})
+st.sidebar.header("Input Features")
+
+input_data = {}
+
+for feature in feature_names:
+    input_data[feature] = st.sidebar.number_input(
+        feature,
+        value=0.0
+    )
+
+input_df = pd.DataFrame([input_data])
 
 st.subheader("Input Data")
 st.write(input_df)