Update app.py

app.py

@@ -19,9 +19,8 @@ except:
 # 🔹 Load Dataset (REAL or DUMMY)
 # =========================
 try:
-    data = pd.read_csv("churn_data.csv")  # 🔥 Replace with your dataset
+    data = pd.read_csv("churn_data.csv")
 except:
-    # fallback dummy dataset
     np.random.seed(42)
     data = pd.DataFrame({
         "gender": np.random.choice(["Male","Female"], 300),
@@ -53,13 +52,10 @@ def get_kpis(df):
 # =========================
 def apply_filters(gender, contract):
     df = data.copy()
-
     if gender != "All":
         df = df[df["gender"] == gender]
-
     if contract != "All":
         df = df[df["Contract"] == contract]
-
     return df
 
 # =========================
@@ -125,6 +121,15 @@ def predict_churn(age, gender, tenure, usage, support, delay,
         if model is None:
             return "Model not loaded ❌", "", "", None, ""
 
+        # 🔹 Convert inputs safely
+        age = float(age)
+        tenure = float(tenure)
+        usage = float(usage)
+        support = float(support)
+        delay = float(delay)
+        spend = float(spend)
+        interaction = float(interaction)
+
         gender_val = 1 if gender == "Female" else 0
 
         sub_premium = 1 if subscription == "Premium" else 0
@@ -156,14 +161,14 @@ def predict_churn(age, gender, tenure, usage, support, delay,
         else:
             risk = "🟢 Low Risk"
 
-        # probability chart
+        # 📊 Probability Chart
         fig, ax = plt.subplots()
         ax.bar(["No Churn","Churn"], [1-prob, prob])
         ax.set_ylim(0,1)
         ax.set_title("Prediction Probability")
         plt.close(fig)
 
-        # explanation
+        # 🧠 Explanation
         reasons = []
         if delay > 15: reasons.append("High payment delay")
         if tenure < 6: reasons.append("Low tenure")
@@ -188,8 +193,8 @@ with gr.Blocks() as demo:
     # ---------------------
     with gr.Tab("📊 Dashboard"):
 
-        gender_filter = gr.Dropdown(["All","Male","Female"], value="All", label="Filter by Gender")
-        contract_filter = gr.Dropdown(["All","Monthly","Quarterly","Yearly"], value="All", label="Filter by Contract")
+        gender_filter = gr.Dropdown(["All","Male","Female"], value="All")
+        contract_filter = gr.Dropdown(["All","Monthly","Quarterly","Yearly"], value="All")
 
         kpi_text = gr.Markdown()
         chart1 = gr.Plot()
@@ -207,35 +212,34 @@ with gr.Blocks() as demo:
                 risk_pie(df)
             )
 
+        demo.load(update_dashboard, [gender_filter, contract_filter],
+                  [kpi_text, chart1, chart2, chart3, chart4])
+
         gender_filter.change(update_dashboard, [gender_filter, contract_filter],
                              [kpi_text, chart1, chart2, chart3, chart4])
 
         contract_filter.change(update_dashboard, [gender_filter, contract_filter],
                                [kpi_text, chart1, chart2, chart3, chart4])
 
-        # initial load
-        demo.load(update_dashboard, [gender_filter, contract_filter],
-                  [kpi_text, chart1, chart2, chart3, chart4])
-
     # ---------------------
-    # 🔍 PREDICTION TAB
+    # 🔍 PREDICTION TAB (UPDATED)
     # ---------------------
     with gr.Tab("🔍 Prediction"):
 
         with gr.Row():
-            age = gr.Slider(18,80,value=30)
-            gender = gr.Radio(["Male","Female"], value="Male")
-            tenure = gr.Slider(0,60,value=12)
-            usage = gr.Slider(0,50,value=10)
+            age = gr.Number(value=30, label="Age")
+            gender = gr.Dropdown(["Male","Female"], value="Male", label="Gender")
+            tenure = gr.Number(value=12, label="Tenure")
+            usage = gr.Number(value=10, label="Usage")
 
         with gr.Row():
-            support = gr.Slider(0,20,value=2)
-            delay = gr.Slider(0,30,value=5)
-            subscription = gr.Radio(["Basic","Standard","Premium"], value="Basic")
-            contract = gr.Radio(["Monthly","Quarterly","Yearly"], value="Monthly")
+            support = gr.Number(value=2, label="Support Calls")
+            delay = gr.Number(value=5, label="Payment Delay")
+            subscription = gr.Dropdown(["Basic","Standard","Premium"], value="Basic")
+            contract = gr.Dropdown(["Monthly","Quarterly","Yearly"], value="Monthly")
 
-        spend = gr.Slider(0,10000,value=2000)
-        interaction = gr.Slider(0,100,value=20)
+        spend = gr.Number(value=2000, label="Total Spend")
+        interaction = gr.Number(value=20, label="Last Interaction")
 
         btn = gr.Button("Predict")