app.py

import pandas as pd
import gspread
import gradio as gr
from oauth2client.service_account import ServiceAccountCredentials
from datetime import datetime

# ------------------ 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")

# ------------------ 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"])

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

# ------------------ GRADIO APP ------------------
with gr.Blocks() as app:
    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()