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import gradio as gr
import pandas as pd
import gspread
from gspread_dataframe import set_with_dataframe
from oauth2client.service_account import ServiceAccountCredentials
from datetime import datetime, timedelta
# -------------------- CONFIG --------------------
SHEET_URL = "https://docs.google.com/spreadsheets/d/1if4KoVQvw5ZbhknfdZbzMkcTiPfsD6bz9V3a1th-bwQ"
CREDS_JSON = "deep-mile-461309-t8-0e90103411e0.json"
# -------------------- AUTH --------------------
scope = [
"https://spreadsheets.google.com/feeds",
"https://www.googleapis.com/auth/drive"
]
creds = ServiceAccountCredentials.from_json_keyfile_name(CREDS_JSON, scope)
client = gspread.authorize(creds)
# -------------------- SHEET LOAD/UTILS --------------------
def normalize_columns(df):
df.columns = df.columns.str.strip().str.title()
return df
def load_sheet_df(sheet_name):
try:
ws = client.open_by_url(SHEET_URL).worksheet(sheet_name)
records= ws.get_all_records()
df = pd.DataFrame(records)
return normalize_columns(df)
except Exception as e:
# return a one-row DF with an Error column
return pd.DataFrame([{"Error": str(e)}])
# -------------------- DATE FILTERS --------------------
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()
out = df[(df[date_column] >= start) & (df[date_column] <= end)]
if rep and rep in out.columns:
out = out[out[rep_column] == rep]
return out
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"}])
df[date_column] = pd.to_datetime(df[date_column], errors="coerce").dt.date
out = df[df[date_column] == target]
if rep and rep in out.columns:
out = out[out[rep_column] == rep]
return out
# -------------------- REPORT DATA --------------------
def get_calls(rep=None):
df = load_sheet_df("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_calls_summary(rep=None):
df = get_calls(rep)
if "Error" in df.columns or df.empty:
return df
return (
df.groupby("Rep")
.size()
.reset_index(name="Count")
.sort_values("Count", ascending=False)
)
def search_calls_by_date(y,m,d, rep):
df = load_sheet_df("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 get_appointments(rep=None):
df = load_sheet_df("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 get_appointments_summary(rep=None):
df = get_appointments(rep)
if "Error" in df.columns or df.empty:
return df
return (
df.groupby("Rep")
.size()
.reset_index(name="Count")
.sort_values("Count", ascending=False)
)
def search_appointments_by_date(y,m,d, rep):
df = load_sheet_df("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_df("AllocatedLeads")
# rename if needed
df = df.rename(columns={"Assigned Rep":"Assigned Rep"})
if "Assigned Rep" not in df.columns:
return pd.DataFrame([{"Error":"Missing 'Assigned Rep' col"}])
return df
def get_leads_summary():
df = get_leads_detail()
if "Error" in df.columns:
return df
return df.groupby("Assigned Rep").size().reset_index(name="Leads Count")
# -------------------- INSIGHTS --------------------
def compute_insights():
calls = get_calls()
appts = get_appointments()
leads = get_leads_detail()
def top_rep(df, col):
if "Error" in df.columns or df.empty:
return "N/A"
counts = df.groupby(col).size()
if counts.empty:
return "N/A"
return counts.idxmax()
top_calls = top_rep(calls, "Rep")
top_appts = top_rep(appts, "Rep")
# unify column name for leads
leads = leads.rename(columns={"Assigned Rep":"Rep"})
top_leads = top_rep(leads, "Rep")
return 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},
])
# -------------------- USER MANAGEMENT --------------------
def load_users():
df = load_sheet_df("userAccess") # your actual tab name
# pick & title-case only the cols you want
wanted = [
"Id","Email","Name","Business","Role",
"Daily Phone Call Target","Daily Phone Appointment Target",
"Daily Quote Number Target","Daily Quote Revenue Target",
"Weekly Phone Call Target","Weekly Phone Appointment Target",
"Weekly Quote Number Target","Weekly Quote Revenue Target",
"Monthly Phone Call Target","Monthly Phone Appointment Target",
"Monthly Quote Number Target","Monthly Quote Revenue Target",
"Monthly Sales Revenue Target"
]
exist = [c for c in wanted if c in df.columns]
return df[exist]
def save_users(df):
ws = client.open_by_url(SHEET_URL).worksheet("userAccess")
ws.clear()
set_with_dataframe(ws, df)
return "β
Users saved!"
# -------------------- GRADIO UI --------------------
with gr.Blocks(title="π Graffiti Field App Admin Dashboard") as app:
gr.Markdown("# π Graffiti Field App Admin Dashboard")
# βββ Calls Report βββββββββββββββββββββββββββββ
with gr.Tab("Calls Report"):
rep_calls = gr.Dropdown(
label="Optional Rep Filter",
choices=load_sheet_df("Calls")["Rep"].dropna().unique().tolist(),
allow_custom_value=True
)
calls_btn = gr.Button("Load Current Week Calls")
calls_summary = gr.Dataframe(label="π Calls by Rep")
calls_table = gr.Dataframe(label="π Detailed Calls")
calls_btn.click(
fn=lambda r: (get_calls_summary(r), get_calls(r)),
inputs=rep_calls,
outputs=[calls_summary, calls_table]
)
gr.Markdown("### π 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=load_sheet_df("Calls")["Rep"].dropna().unique().tolist(),
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
)
# βββ Appointments Report βββββββββββββββββββββ
with gr.Tab("Appointments Report"):
rep_appt = gr.Dropdown(
label="Optional Rep Filter",
choices=load_sheet_df("Appointments")["Rep"].dropna().unique().tolist(),
allow_custom_value=True
)
appt_btn = gr.Button("Load Current Week Appointments")
appt_summary = gr.Dataframe(label="π Appts by Rep")
appt_table = gr.Dataframe(label="π Detailed Appointments")
appt_btn.click(
fn=lambda r: (get_appointments_summary(r), get_appointments(r)),
inputs=rep_appt,
outputs=[appt_summary, appt_table]
)
gr.Markdown("### π 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=load_sheet_df("Appointments")["Rep"].dropna().unique().tolist(),
allow_custom_value=True
)
appt_date_btn = gr.Button("Search Appts by Date")
appt_date_summary = gr.Dataframe(label="π Appts Summary by Rep")
appt_date_table = gr.Dataframe()
appt_date_btn.click(
fn=lambda y,m,d,r: (
(lambda df: df.groupby("Rep").size().reset_index(name="Count"))(search_appointments_by_date(y,m,d,r)),
search_appointments_by_date(y,m,d,r)
),
inputs=[y2,m2,d2,rep2],
outputs=[appt_date_summary, appt_date_table]
)
# βββ Appointed Leads ββββββββββββββββββββββββββ
with gr.Tab("Appointed Leads"):
leads_btn = gr.Button("View Appointed Leads")
leads_summary = gr.Dataframe(label="π Leads Count by Rep")
leads_detail = gr.Dataframe(label="π Detailed Leads")
leads_btn.click(
fn=lambda: (get_leads_summary(), get_leads_detail()),
outputs=[leads_summary, leads_detail]
)
# βββ Insights βββββββββββββββββββββββββββββββββ
with gr.Tab("Insights"):
insights_btn = gr.Button("Generate Insights")
insights_tbl = gr.Dataframe()
insights_btn.click(fn=compute_insights, outputs=insights_tbl)
# βββ User Management ββββββββββββββββββββββββββ
with gr.Tab("User Management"):
gr.Markdown("## π€ Manage Users\nEdit/add/remove rows below, then click **Save Users**.")
users_tbl = gr.Dataframe(value=load_users(), interactive=True)
save_btn = gr.Button("Save Users")
status = gr.Textbox()
save_btn.click(fn=save_users, inputs=users_tbl, outputs=status)
# end Blocks
app.launch()
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