Update app.py

app.py

@@ -3,109 +3,178 @@ import gspread
 import gradio as gr
 from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime
-from geopy.distance import geodesic
-import folium
-from io import BytesIO
 
-# Google Sheets Auth
+# ------------------ AUTH ------------------
+VALID_USERS = {
+    "[email protected]": "Pass.123",
+    "[email protected]": "Pass.123",
+    "[email protected]": "Pass.123"
+}
+
+# ------------------ GOOGLE SHEET SETUP ------------------
 scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
 creds = ServiceAccountCredentials.from_json_keyfile_name("credentials.json", scope)
 client = gspread.authorize(creds)
 sheet_file = client.open("userAccess")
 
-# Load Data
+# ------------------ HELPERS ------------------
 def load_tab(sheet_name):
     try:
         df = pd.DataFrame(sheet_file.worksheet(sheet_name).get_all_records())
         return df
     except:
-        return pd.DataFrame(["⚠️ Could not load sheet."], columns=["Error"])
-
-# GPS calculations
-def calculate_gps_data(df):
-    df = df.sort_values(['Date', 'Time']).reset_index(drop=True)
-    df[['Latitude', 'Longitude']] = df['Location'].str.split(', ', expand=True).astype(float)
-
-    df['Kms Travelled'] = 0.0
-    df['Duration Between Calls (min)'] = 0.0
-
-    for i in range(1, len(df)):
-        prev_coords = (df.at[i-1, 'Latitude'], df.at[i-1, 'Longitude'])
-        current_coords = (df.at[i, 'Latitude'], df.at[i, 'Longitude'])
-        df.at[i, 'Kms Travelled'] = geodesic(prev_coords, current_coords).km
-
-        prev_time = pd.to_datetime(df.at[i-1, 'Date'] + ' ' + df.at[i-1, 'Time'])
-        current_time = pd.to_datetime(df.at[i, 'Date'] + ' ' + df.at[i, 'Time'])
-        df.at[i, 'Duration Between Calls (min)'] = (current_time - prev_time).total_seconds() / 60.0
-
+        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 get_requests():
+    df = load_tab("Customer Requests")
+    return df if not df.empty else pd.DataFrame([["No requests yet."]], columns=["Message"])
+
+def get_listings():
+    df = load_tab("CustomerListings")
+    return df if not df.empty else pd.DataFrame([["No listings found."]], columns=["Message"])
+
+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"])
+    col = "Customer Type & Status"
+    if col in df.columns:
+        flagged = df[df[col].str.contains("Second", na=False)]
+        return flagged if not flagged.empty else pd.DataFrame([["No second-hand dealerships flagged."]], columns=["Message"])
+    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
 
-# Load and process Field Sales data
-field_sales_df = calculate_gps_data(load_tab("Field Sales"))
-
-# Map generation
-def generate_map(df):
-    if df.empty or df[['Latitude', 'Longitude']].isna().all().all():
-        return None
-
-    coords = df[['Latitude', 'Longitude']].dropna().values
-    map_center = coords[0]
-    m = folium.Map(location=map_center, zoom_start=12)
-
-    for idx, coord in enumerate(coords):
-        folium.Marker(location=coord, popup=f"Visit {idx+1}").add_to(m)
-
-    folium.PolyLine(coords, color='blue').add_to(m)
-
-    buf = BytesIO()
-    m.save(buf, close_file=False)
-    return buf.getvalue().decode()
-
-# Gradio Interface
+# ------------------ GRADIO APP ------------------
 with gr.Blocks() as app:
-    gr.Markdown("## 🚗 CarMat Dashboard")
-
-    unique_dates = sorted(field_sales_df['Date'].unique(), reverse=True)
-
-    # Field Sales Tab
-    with gr.Tab("🗺️ Field Sales"):
-        date_selector = gr.Dropdown(label="Select Date", choices=unique_dates)
-        data_output = gr.DataFrame()
-        map_html = gr.HTML()
-
-        def update_field_sales(date):
-            day_df = field_sales_df[field_sales_df['Date'] == date]
-            map_render = generate_map(day_df)
-            return day_df, map_render
-
-        date_selector.change(fn=update_field_sales, inputs=date_selector, outputs=[data_output, map_html])
-
-    # Summary Tab
-    with gr.Tab("📊 Summary"):
-        date_summary = gr.Dropdown(label="Select Date", choices=unique_dates)
-        summary_visits = gr.DataFrame()
-
-        def update_summary(date):
-            day_df = field_sales_df[field_sales_df['Date'] == date]
-            visits = day_df.groupby("Rep").size().reset_index(name="Total Visits")
-            return visits
-
-        date_summary.change(fn=update_summary, inputs=date_summary, outputs=summary_visits)
-
-    # Orders Tab
-    with gr.Tab("📦 Orders"):
-        order_date = gr.Dropdown(label="Select Date", choices=unique_dates)
-        orders_output = gr.DataFrame()
-
-        def orders_summary(date):
-            day_df = field_sales_df[field_sales_df['Date'] == date]
-            orders_df = day_df[day_df["Order Received"] == "Yes"]
-            summary = orders_df.groupby("Rep").agg({
-                "Order Value": "sum",
-                "Order Received": "count"
-            }).rename(columns={"Order Received": "Orders Count"}).reset_index()
-            return summary
-
-        order_date.change(fn=orders_summary, inputs=order_date, outputs=orders_output)
+    with gr.Row():
+        with gr.Column(visible=True) as login_ui:
+            gr.Markdown("## 🔐 Login Required")
+            email = gr.Textbox(label="Email")
+            password = gr.Textbox(label="Password", type="password")
+            login_btn = gr.Button("Login")
+            login_msg = gr.Markdown("")
+
+        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 ---
+            with gr.Tab("📊 Summary"):
+                gr.Markdown("Summary content coming soon...")
+
+            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)
+
+            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)
+
+            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)
+
+            with gr.Tab("🚨 Escalations"):
+                esc_table = gr.Dataframe(value=get_escalations, label="🚨 Used Dealership Escalations")
+                esc_btn = gr.Button("🔄 Refresh Escalations")
+                esc_btn.click(fn=get_escalations, outputs=esc_table)
+
+            with gr.Tab("🏭 OEM Visits"):
+                oem_table = gr.Dataframe(value=get_oem_summary, label="🏭 OEM Visit Summary")
+                oem_refresh = gr.Button("🔄 Refresh")
+                oem_refresh.click(fn=get_oem_summary, outputs=oem_table)
+
+            with gr.Tab("📬 Customer Requests"):
+                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)
+
+            with gr.Tab("📋 Dealership Directory"):
+                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)
+
+            with gr.Tab("👤 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)
+
+    def do_login(user, pw):
+        if VALID_USERS.get(user) == pw:
+            return gr.update(visible=False), gr.update(visible=True), ""
+        else:
+            return gr.update(visible=True), gr.update(visible=False), "❌ Invalid login."
+
+    login_btn.click(fn=do_login, inputs=[email, password], outputs=[login_ui, main_ui, login_msg])
 
 app.launch()