Sync app files

app/app.py

@@ -10,7 +10,7 @@ METRICS_DIR = os.path.join(ROOT, "metrics")
 MODEL_PATH = os.path.join(ROOT, "src", "model.pkl")
 
 model = joblib.load(MODEL_PATH)
-with open(os.path.join(METRICS_DIR, 'metrics.json')) as f:
+with open(os.path.join(METRICS_DIR, "metrics.json")) as f:
     metrics = json.load(f)
 
 cat_options = {
@@ -18,7 +18,7 @@ cat_options = {
     "device_type": ["Mobile", "Desktop", "Tablet"],
     "ad_position": ["Top", "Side", "Bottom"],
     "browsing_history": ["Sports", "News", "Shopping", "Other"],
-    "time_of_day": ["Morning", "Afternoon", "Evening", "Night"]
+    "time_of_day": ["Morning", "Afternoon", "Evening", "Night"],
 }
 
 st.title("Ad Click Predictor")
@@ -29,20 +29,24 @@ st.markdown(
 )
 
 age = st.slider("Wiek użytkownika", 18, 64, 30)
-gender = st.selectbox("Płeć", cat_options['gender'])
-device_type = st.selectbox("Typ urządzenia", cat_options['device_type'])
-ad_position = st.selectbox("Pozycja reklamy", cat_options['ad_position'])
-browsing_history = st.selectbox("Poprzednia aktywność", cat_options['browsing_history'])
-time_of_day = st.selectbox("Pora dnia", cat_options['time_of_day'])
-
-user_input = pd.DataFrame([{
-    "age": age,
-    "gender": gender,
-    "device_type": device_type,
-    "ad_position": ad_position,
-    "browsing_history": browsing_history,
-    "time_of_day": time_of_day
-}])
+gender = st.selectbox("Płeć", cat_options["gender"])
+device_type = st.selectbox("Typ urządzenia", cat_options["device_type"])
+ad_position = st.selectbox("Pozycja reklamy", cat_options["ad_position"])
+browsing_history = st.selectbox("Poprzednia aktywność", cat_options["browsing_history"])
+time_of_day = st.selectbox("Pora dnia", cat_options["time_of_day"])
+
+user_input = pd.DataFrame(
+    [
+        {
+            "age": age,
+            "gender": gender,
+            "device_type": device_type,
+            "ad_position": ad_position,
+            "browsing_history": browsing_history,
+            "time_of_day": time_of_day,
+        }
+    ]
+)
 
 if st.button("Sprawdź czy użytkownik kliknie w reklamę"):
     proba = model.predict_proba(user_input)[0][1]
@@ -59,4 +63,4 @@ st.write(f"- Accuracy: `{metrics['accuracy']:.2%}`")
 st.write(f"- F1-score: `{metrics['f1_score']:.2%}`")
 
 st.markdown("#### Macierz pomyłek (Confusion Matrix):")
-st.image(os.path.join(METRICS_DIR, 'confusion_matrix.png'))
+st.image(os.path.join(METRICS_DIR, "confusion_matrix.png"))