app.py

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

# -------------------- AUTH --------------------
scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
creds = ServiceAccountCredentials.from_json_keyfile_name("deep-mile-461309-t8-0e90103411e0.json", scope)
client = gspread.authorize(creds)
sheet_url = "https://docs.google.com/spreadsheets/d/1if4KoVQvw5ZbhknfdZbzMkcTiPfsD6bz9V3a1th-bwQ"

# -------------------- UTILS --------------------
def normalize_columns(df):
    df.columns = df.columns.str.strip().str.title()  # e.g. “appointment date ” → “Appointment Date”
    return df

def load_sheet(sheet_name):
    try:
        sheet = client.open_by_url(sheet_url).worksheet(sheet_name)
        df = pd.DataFrame(sheet.get_all_records())
        df = normalize_columns(df)
        return df
    except Exception as e:
        return pd.DataFrame([{"Error": str(e)}])

def get_current_week_range():
    today = datetime.now()
    start = today - timedelta(days=today.weekday())
    end = start + timedelta(days=6)
    return start.date(), end.date()

def filter_week(df, date_column, rep_column=None, rep=None):
    df[date_column] = pd.to_datetime(df[date_column], errors='coerce').dt.date
    start, end = get_current_week_range()
    filtered = df[(df[date_column] >= start) & (df[date_column] <= end)]
    if rep:
        filtered = filtered[filtered[rep_column] == rep]
    return filtered

def filter_date(df, date_column, rep_column, y, m, d, rep):
    try:
        target = datetime(int(y), int(m), int(d)).date()
    except:
        return pd.DataFrame([{"Error": "Invalid date input"}])
    df[date_column] = pd.to_datetime(df[date_column], errors='coerce').dt.date
    filtered = df[df[date_column] == target]
    if rep:
        filtered = filtered[filtered[rep_column] == rep]
    return filtered

# -------------------- REPORT FUNCTIONS --------------------
def get_calls(rep=None):
    df = load_sheet("Calls")
    if "Call Date" not in df.columns:
        return pd.DataFrame([{"Error": "Missing 'Call Date' column"}])
    return filter_week(df, "Call Date", "Rep", rep)

def get_appointments(rep=None):
    df = load_sheet("Appointments")
    if "Appointment Date" not in df.columns:
        return pd.DataFrame([{"Error": "Missing 'Appointment Date' column"}])
    return filter_week(df, "Appointment Date", "Rep", rep)

def search_calls_by_date(y, m, d, rep):
    df = load_sheet("Calls")
    if "Call Date" not in df.columns:
        return pd.DataFrame([{"Error": "Missing 'Call Date' column"}])
    return filter_date(df, "Call Date", "Rep", y, m, d, rep)

def search_appointments_by_date(y, m, d, rep):
    df = load_sheet("Appointments")
    if "Appointment Date" not in df.columns:
        return pd.DataFrame([{"Error": "Missing 'Appointment Date' column"}])
    return filter_date(df, "Appointment Date", "Rep", y, m, d, rep)

def get_leads_detail():
    df = load_sheet("AllocatedLeads")
    # normalize expected names if necessary:
    df = df.rename(columns={"Assigned Rep": "Assigned Rep", "Company Name": "Company Name"})
    if "Assigned Rep" not in df.columns or "Company Name" not in df.columns:
        return pd.DataFrame([{"Error": "Missing 'Assigned Rep' or 'Company Name' column"}])
    return df

def get_leads_summary():
    df = get_leads_detail()
    if "Error" in df.columns:
        return df
    # count number of leads per rep
    summary = df.groupby("Assigned Rep").size().reset_index(name="Leads Count")
    return summary

# -------------------- INSIGHTS (Top Performers) --------------------
def compute_insights():
    calls = get_calls()
    appts = get_appointments()
    leads = get_leads_detail()

    top_calls = calls.groupby("Rep").size().idxmax() if not calls.empty else "N/A"
    top_appts = appts.groupby("Rep").size().idxmax() if not appts.empty else "N/A"
    top_leads = leads.groupby("Assigned Rep").size().idxmax() if "Assigned Rep" in leads.columns else "N/A"

    insights = pd.DataFrame([
        {"Metric": "Most Calls This Week",        "Rep": top_calls},
        {"Metric": "Most Appointments This Week", "Rep": top_appts},
        {"Metric": "Most Leads Allocated",        "Rep": top_leads},
    ])
    return insights

# -------------------- DROPDOWN OPTIONS --------------------
def rep_options(sheet_name, rep_col):
    df = load_sheet(sheet_name)
    if rep_col in df.columns:
        return sorted(df[rep_col].dropna().unique().tolist())
    return []

# -------------------- UI LAYOUT --------------------
with gr.Blocks(title="Graffiti Admin Dashboard") as app:
    gr.Markdown("# 📆 Graffiti Admin Dashboard")

    with gr.Tab("Calls Report"):
        rep_calls = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Calls", "Rep"), allow_custom_value=True)
        calls_btn = gr.Button("Load Current Week Calls")
        calls_table = gr.Dataframe()
        calls_btn.click(fn=get_calls, inputs=rep_calls, outputs=calls_table)

        gr.Markdown("### 🔍 Search Calls by Specific Date")
        y1, m1, d1 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
        rep1 = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Calls", "Rep"), allow_custom_value=True)
        calls_date_btn = gr.Button("Search Calls by Date")
        calls_date_table = gr.Dataframe()
        calls_date_btn.click(fn=search_calls_by_date, inputs=[y1, m1, d1, rep1], outputs=calls_date_table)

    with gr.Tab("Appointments Report"):
        rep_appt = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Appointments", "Rep"), allow_custom_value=True)
        appt_btn = gr.Button("Load Current Week Appointments")
        appt_summary = gr.Dataframe(label="📊 Weekly Appointments Summary by Rep")
        appt_table   = gr.Dataframe()
        appt_btn.click(
            fn=lambda rep: (get_appointments(rep).groupby("Rep").size().reset_index(name="Count"), 
                            get_appointments(rep)),
            inputs=rep_appt,
            outputs=[appt_summary, appt_table]
        )

        gr.Markdown("### 🔍 Search Appointments by Specific Date")
        y2, m2, d2 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
        rep2 = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Appointments", "Rep"), allow_custom_value=True)
        appt_date_btn = gr.Button("Search Appointments by Date")
        appt_date_summary = gr.Dataframe(label="📊 Appointments Summary for Date by Rep")
        appt_date_table   = gr.Dataframe()
        appt_date_btn.click(
            fn=lambda y,m,d,rep: (
                search_appointments_by_date(y,m,d,rep).groupby("Rep").size().reset_index(name="Count"),
                search_appointments_by_date(y,m,d,rep)
            ),
            inputs=[y2, m2, d2, rep2],
            outputs=[appt_date_summary, appt_date_table]
        )

    with gr.Tab("Appointed Leads"):
        leads_btn    = gr.Button("View Appointed Leads")
        leads_summary= gr.Dataframe(label="📊 Leads Count by Rep")
        leads_detail = gr.Dataframe(label="🔎 Detailed Leads")
        leads_btn.click(
            fn=lambda: (get_leads_summary(), get_leads_detail()),
            outputs=[leads_summary, leads_detail]
        )

    with gr.Tab("Insights"):
        insights_btn = gr.Button("Generate Insights")
        insights_tbl = gr.Dataframe()
        insights_btn.click(fn=compute_insights, outputs=insights_tbl)

app.launch()