app.py

import pandas as pd
import gspread
from oauth2client.service_account import ServiceAccountCredentials
import gradio as gr
import plotly.express as px

# === Google Sheets Auth ===
scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
creds = ServiceAccountCredentials.from_json_keyfile_name("tough-star.json", scope)
client = gspread.authorize(creds)

# === Load sheet data ===
sheet_url = "https://docs.google.com/spreadsheets/d/1bpeFS6yihb6niCavpwjWmVEypaSkGxONGg2jZfKX_sA"
sheet = client.open_by_url(sheet_url).worksheet("Calls")
data = sheet.get_all_records()
df = pd.DataFrame(data)

# === Parse and clean ===
df['Timestamp'] = pd.to_datetime(df['Timestamp'], dayfirst=True, errors='coerce')
df['Date'] = df['Timestamp'].dt.date.astype(str)
df['Time'] = df['Timestamp'].dt.time

location_split = df['Location'].str.split(',', expand=True)
df['Latitude'] = pd.to_numeric(location_split[0], errors='coerce')
df['Longitude'] = pd.to_numeric(location_split[1], errors='coerce')
df = df.dropna(subset=['Date', 'Rep Name', 'Latitude', 'Longitude'])
df = df[(df['Latitude'] != 0) & (df['Longitude'] != 0)]
df = df.sort_values(by=['Rep Name', 'Timestamp'])
df['Time Diff (min)'] = df.groupby(['Rep Name', 'Date'])['Timestamp'].diff().dt.total_seconds().div(60).fillna(0)

# Add Visit Order
df['Visit Order'] = df.groupby(['Rep Name', 'Date']).cumcount() + 1

# Construct image thumbnail URLs from Google Drive folder
drive_folder_url = "https://drive.google.com/uc?id="
df['Image ID'] = df['Image'].str.extract(r'Calls_Images/([^.]+)')
df['Image URL'] = df['Image ID'].apply(lambda x: f"{drive_folder_url}{x}" if pd.notna(x) else "")

# === Functions ===
def get_reps(date_str):
    reps = df[df['Date'] == date_str]['Rep Name'].dropna().unique()
    return sorted(reps)

def show_map(date_str, rep):
    subset = df[(df['Date'] == date_str) & (df['Rep Name'] == rep)]
    if subset.empty:
        return "No valid data", None

    subset = subset.sort_values(by='Timestamp').copy()
    subset['Visit Order'] = range(1, len(subset) + 1)

    # Center and zoom
    center_lat = subset['Latitude'].mean()
    center_lon = subset['Longitude'].mean()

    fig = px.line_mapbox(
        subset,
        lat="Latitude", lon="Longitude",
        hover_name="Dealership Name",
        hover_data={"Time": True, "Time Diff (min)": True, "Visit Order": True},
        height=700,
        zoom=13,
        center={"lat": center_lat, "lon": center_lon}
    )

    scatter = px.scatter_mapbox(
        subset,
        lat="Latitude", lon="Longitude",
        color="Visit Order",
        hover_name="Dealership Name",
        hover_data=["Time", "Time Diff (min)"],
        color_continuous_scale="Bluered"
    )
    for trace in scatter.data:
        fig.add_trace(trace)

    fig.add_trace(px.scatter_mapbox(
        pd.DataFrame([subset.iloc[0]]),
        lat="Latitude", lon="Longitude",
        text=["Start"], color_discrete_sequence=["green"]).data[0])
    fig.add_trace(px.scatter_mapbox(
        pd.DataFrame([subset.iloc[-1]]),
        lat="Latitude", lon="Longitude",
        text=["End"], color_discrete_sequence=["red"]).data[0])

    fig.update_layout(mapbox_style="open-street-map", title=f"📍 {rep}'s Route on {date_str}")

    # === Build display table
    table = subset[[
        'Visit Order', 'Dealership Name', 'Time', 'Time Diff (min)',
        'Type of call', 'Sales or service', 'Image URL'
    ]]
    table = table.rename(columns={
        'Dealership Name': '🧭 Dealer',
        'Time': '🕒 Time',
        'Time Diff (min)': '⏱️ Time Spent',
        'Type of call': '📞 Call Type',
        'Sales or service': '💼 Category',
        'Image URL': '📸 Photo'
    })

    # Add time summary
    total_time = round(table['⏱️ Time Spent'].sum(), 2)
    summary_row = pd.DataFrame([{
        '🧭 Dealer': f"🧮 Total Time: {total_time} min",
        'Visit Order': '',
        '🕒 Time': '',
        '⏱️ Time Spent': '',
        '📞 Call Type': '',
        '💼 Category': '',
        '📸 Photo': ''
    }])
    table = pd.concat([table, summary_row], ignore_index=True)

    return table, fig

# === Gradio UI ===
def update(date_str):
    return gr.Dropdown(choices=get_reps(date_str), label="Select Rep")

with gr.Blocks() as app:
    gr.Markdown("## 🗺️ Rep Route & Visit Visualizer")

    date_picker = gr.Dropdown(
        label="Select Date", 
        choices=sorted(df['Date'].unique(), reverse=True)
    )
    rep_picker = gr.Dropdown(label="Select Rep")

    btn = gr.Button("Show Route")

    table = gr.Dataframe(label="Call Table")
    map_plot = gr.Plot(label="Map")

    date_picker.change(fn=update, inputs=date_picker, outputs=rep_picker)
    btn.click(fn=show_map, inputs=[date_picker, rep_picker], outputs=[table, map_plot])

app.launch()