Update app.py

app.py

@@ -3,6 +3,7 @@ import gspread
 import gradio as gr
 from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime
+from math import radians, cos, sin, asin, sqrt
 
 # ------------------ AUTH ------------------
 VALID_USERS = {
@@ -25,47 +26,94 @@ def load_tab(sheet_name):
     except:
         return pd.DataFrame([["⚠️ Could not load sheet."]], columns=["Error"])
 
-def get_combined_orders(date_str):
-    df_field = load_tab("Field Sales")
-    df_ts = load_tab("TeleSales")
-
-    combined = []
-
-    if not df_field.empty:
-        df_field['Date'] = pd.to_datetime(df_field['Date'], errors='coerce')
-        df_field['DateStr'] = df_field['Date'].dt.date.astype(str)
-        df_field = df_field[df_field['DateStr'] == date_str.strip()]
-        df_field['Order Value'] = pd.to_numeric(df_field['Order Value'], errors='coerce').fillna(0)
-        df_field_orders = df_field.groupby("Rep").agg({
-            "Order Received": lambda x: (x == "Yes").sum(),
-            "Order Value": "sum"
-        }).reset_index().rename(columns={
-            "Order Received": "Orders Received",
-            "Order Value": "Total Order Value"
-        })
-        df_field_orders["Source"] = "Field Sales"
-        combined.append(df_field_orders)
-
-    if not df_ts.empty:
-        df_ts['Date'] = pd.to_datetime(df_ts['Date'], errors='coerce')
-        df_ts['DateStr'] = df_ts['Date'].dt.date.astype(str)
-        df_ts = df_ts[df_ts['DateStr'] == date_str.strip()]
-        df_ts['Order Value'] = pd.to_numeric(df_ts['Order Value'], errors='coerce').fillna(0)
-        df_ts_orders = df_ts.groupby("Rep").agg({
-            "Order Received": lambda x: (x == "Yes").sum(),
-            "Order Value": "sum"
-        }).reset_index().rename(columns={
-            "Order Received": "Orders Received",
-            "Order Value": "Total Order Value"
-        })
-        df_ts_orders["Source"] = "TeleSales"
-        combined.append(df_ts_orders)
-
-    if combined:
-        return pd.concat(combined, ignore_index=True)
-    else:
-        return pd.DataFrame([["No orders on this date"]], columns=["Message"])
+def haversine(coord1, coord2):
+    try:
+        lon1, lat1 = map(radians, map(float, coord1.split(',')[::-1]))
+        lon2, lat2 = map(radians, map(float, coord2.split(',')[::-1]))
+        dlon = lon2 - lon1
+        dlat = lat2 - lat1
+        a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
+        c = 2 * asin(sqrt(a))
+        return round(6371 * c, 2)
+    except:
+        return 0.0
+
+# ------------------ FIELD SALES ------------------
+def load_field_sales():
+    df = load_tab("Field Sales")
+    if df.empty:
+        return pd.DataFrame(columns=["Date", "Rep", "Order Value", "Order Received", "Location", "DateStr", "KM Travelled"])
+
+    df['Date'] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
+    df = df.dropna(subset=["Date"])
+    df['DateStr'] = df['Date'].dt.date.astype(str)
+    df["Order Value"] = pd.to_numeric(df.get("Order Value", 0), errors="coerce").fillna(0)
+    
+    df["KM Travelled"] = 0.0
+    for rep in df["Rep"].unique():
+        rep_df = df[df["Rep"] == rep].sort_values(by="Date")
+        prev_coord = None
+        for idx, row in rep_df.iterrows():
+            curr_coord = row.get("Location", "")
+            if prev_coord:
+                df.at[idx, "KM Travelled"] = haversine(prev_coord, curr_coord)
+            prev_coord = curr_coord
+
+    return df
+
+def get_field_summary():
+    df = load_field_sales()
+    if df.empty:
+        return pd.DataFrame([["No data available"]], columns=["Message"])
+    summary = df.groupby("Rep").agg({
+        "Order Value": "sum",
+        "Order Received": lambda x: (x == "Yes").sum(),
+        "KM Travelled": "sum"
+    }).reset_index().rename(columns={
+        "Order Value": "Total Order Value",
+        "Order Received": "Orders Received"
+    })
+    return summary
+
+# ------------------ TELESALES ------------------
+def get_telesales_summary():
+    df = load_tab("TeleSales")
+    if df.empty or "Rep" not in df.columns:
+        return pd.DataFrame([["No data available"]], columns=["Message"])
+    df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
+    df["DateStr"] = df["Date"].dt.date.astype(str)
+    df["Order Value"] = pd.to_numeric(df.get("Order Value", 0), errors="coerce").fillna(0)
+
+    summary = df.groupby("Rep").agg({
+        "Order Value": "sum",
+        "Order Received": lambda x: (x == "Yes").sum()
+    }).reset_index().rename(columns={
+        "Order Value": "Total Order Value",
+        "Order Received": "Orders Received"
+    })
+    return summary
+
+# ------------------ COMBINED ORDERS ------------------
+def get_combined_orders():
+    fs = get_field_summary()
+    ts = get_telesales_summary()
+
+    fs["Source"] = "Field Sales"
+    ts["Source"] = "TeleSales"
+
+    combined = pd.concat([fs, ts], ignore_index=True)
+    return combined[["Rep", "Orders Received", "Total Order Value", "Source"]].sort_values(by="Total Order Value", ascending=False)
+
+# ------------------ OEM VISITS ------------------
+def get_oem_summary():
+    df = load_tab("OEM Visit")
+    if df.empty or "Rep" not in df.columns:
+        return pd.DataFrame([["No data available"]], columns=["Message"])
+    df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
+    df["DateStr"] = df["Date"].dt.date.astype(str)
+    return df.groupby(["Rep", "DateStr"]).size().reset_index(name="OEM Visits")
 
+# ------------------ OTHER TABS ------------------
 def get_requests():
     df = load_tab("Customer Requests")
     return df if not df.empty else pd.DataFrame([["No requests yet."]], columns=["Message"])
@@ -78,22 +126,8 @@ def get_users():
     df = load_tab("Users")
     return df if not df.empty else pd.DataFrame([["No users configured."]], columns=["Message"])
 
-def get_telesales_summary():
-    df = load_tab("TeleSales")
-    if df.empty or "Rep" not in df.columns:
-        return pd.DataFrame([["No Telesales data available"]], columns=["Message"])
-    return df.groupby("Rep").size().reset_index(name="Total Calls Made")
-
-def get_oem_summary():
-    df = load_tab("OEM Visit")
-    if df.empty or "Rep" not in df.columns:
-        return pd.DataFrame([["No OEM data available"]], columns=["Message"])
-    return df.groupby("Rep").size().reset_index(name="Total OEM Visits")
-
 def get_escalations():
-    df = load_tab("Field Sales")
-    if df.empty:
-        return pd.DataFrame([["No data in Field Sales"]], columns=["Message"])
+    df = load_field_sales()
     col = "Customer Type & Status"
     if col in df.columns:
         flagged = df[df[col].str.contains("Second", na=False)]
@@ -101,14 +135,6 @@ def get_escalations():
     else:
         return pd.DataFrame([["⚠️ Column 'Customer Type & Status' not found."]], columns=["Message"])
 
-def load_field_sales():
-    df = load_tab("Field Sales")
-    if df.empty:
-        return pd.DataFrame()
-    df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
-    df["DateStr"] = df["Date"].dt.date.astype(str)
-    return df
-
 # ------------------ GRADIO APP ------------------
 with gr.Blocks() as app:
     with gr.Row():
@@ -122,50 +148,50 @@ with gr.Blocks() as app:
         with gr.Column(visible=False) as main_ui:
             gr.Markdown("## 🗂️ CarMat Dashboard")
 
-            df_initial = load_field_sales()
-            unique_dates = sorted(df_initial["DateStr"].unique(), reverse=True) if not df_initial.empty else []
-
-            # --- Tabs ---
+            # --- Summary Tab ---
             with gr.Tab("📊 Summary"):
-                gr.Markdown("Summary content coming soon...")
+                summary_table = gr.Dataframe(label="Combined Orders", value=get_combined_orders)
 
-            with gr.Tab("📂 Field Sales"):
-                field_df = gr.Dataframe(value=load_field_sales, label="📂 Field Sales Records", interactive=False)
-                field_btn = gr.Button("🔄 Refresh Field Sales")
-                field_btn.click(fn=load_field_sales, outputs=field_df)
+            # --- Field Sales Tab ---
+            with gr.Tab("🛣️ Field Sales"):
+                fs_table = gr.Dataframe(label="Field Sales Summary", value=get_field_summary)
+                fs_raw = gr.Dataframe(label="Raw Field Sales", value=load_field_sales)
 
+            # --- Telesales Tab ---
             with gr.Tab("📞 TeleSales"):
-                ts_table = gr.Dataframe(value=get_telesales_summary, label="📞 TeleSales Summary")
-                ts_refresh = gr.Button("🔄 Refresh")
-                ts_refresh.click(fn=get_telesales_summary, outputs=ts_table)
+                ts_table = gr.Dataframe(label="TeleSales Summary", value=get_telesales_summary)
 
-            with gr.Tab("📦 Orders Summary"):
-                order_date = gr.Dropdown(label="Select Date", choices=unique_dates, interactive=True)
-                order_table = gr.Dataframe(label="🧾 Combined Order Summary")
-                order_date.change(fn=get_combined_orders, inputs=order_date, outputs=order_table)
+            # --- Orders Tab ---
+            with gr.Tab("📦 Orders"):
+                order_table = gr.Dataframe(label="All Orders Combined", value=get_combined_orders)
 
+            # --- Escalations ---
             with gr.Tab("🚨 Escalations"):
-                esc_table = gr.Dataframe(value=get_escalations, label="🚨 Used Dealership Escalations")
-                esc_btn = gr.Button("🔄 Refresh Escalations")
+                esc_table = gr.Dataframe(value=get_escalations, label="Second-hand Dealerships")
+                esc_btn = gr.Button("🔄 Refresh")
                 esc_btn.click(fn=get_escalations, outputs=esc_table)
 
+            # --- OEM Visits ---
             with gr.Tab("🏭 OEM Visits"):
-                oem_table = gr.Dataframe(value=get_oem_summary, label="🏭 OEM Visit Summary")
-                oem_refresh = gr.Button("🔄 Refresh")
+                oem_table = gr.Dataframe(value=get_oem_summary, label="OEM Visit Summary")
+                oem_refresh = gr.Button("🔄 Refresh OEM")
                 oem_refresh.click(fn=get_oem_summary, outputs=oem_table)
 
+            # --- Requests ---
             with gr.Tab("📬 Customer Requests"):
-                req_table = gr.Dataframe(value=get_requests, label="📬 Customer Requests", interactive=False)
+                req_table = gr.Dataframe(value=get_requests, label="Customer Requests", interactive=False)
                 req_refresh = gr.Button("🔄 Refresh Requests")
                 req_refresh.click(fn=get_requests, outputs=req_table)
 
+            # --- Dealership Listings ---
             with gr.Tab("📋 Dealership Directory"):
-                listings_table = gr.Dataframe(value=get_listings, label="📋 Customer Listings")
+                listings_table = gr.Dataframe(value=get_listings, label="Customer Listings")
                 listings_refresh = gr.Button("🔄 Refresh Listings")
                 listings_refresh.click(fn=get_listings, outputs=listings_table)
 
+            # --- Users ---
             with gr.Tab("👤 Users"):
-                users_table = gr.Dataframe(value=get_users, label="👥 Users")
+                users_table = gr.Dataframe(value=get_users, label="Users")
                 users_refresh = gr.Button("🔄 Refresh Users")
                 users_refresh.click(fn=get_users, outputs=users_table)