"""
environments/trace_env/tools/dashboard_renderer.py
Dashboard Renderer for Trace.
Converts parsed transaction data → beautiful HTML dashboard.
Works for ALL transaction categories:
ride | food | shopping | payment | subscription | travel | banking | utility | education | healthcare
Usage:
from environments.trace_env.tools.dashboard_renderer import render_dashboard
html = render_dashboard(parsed_result)
# Save to file or return via a new FastAPI endpoint
"""
from __future__ import annotations
import json
import re
from datetime import datetime
def render_dashboard(parsed_result: dict) -> str:
"""
Render a full HTML dashboard from parse_transactions_bulk() output.
Args:
parsed_result: output of transaction_parser.parse_transactions_bulk()
Returns:
Complete HTML string ready to open in browser or serve via FastAPI.
"""
transactions = parsed_result.get("transactions", [])
summary = parsed_result.get("summary", {})
episode = parsed_result.get("episode", {})
cards_html = "\n".join(_render_card(t, i) for i, t in enumerate(transactions))
summary_html = _render_summary(summary)
episode_html = _render_episode_bar(episode)
chart_data = _build_chart_data(summary)
sheet_url = parsed_result.get("sheet_url")
sheets_html = ""
if sheet_url:
sheets_html = f"""
📊
Live Google Sheets Ledger Connected
The summary above includes all historical data synced from your spreadsheet.
Open Sheet ›
"""
prompt = parsed_result.get("prompt", "")
import html as html_lib
prompt_escaped = html_lib.escape(prompt)
prompt_html = f"""
"""
def _render_details(t: dict) -> str:
details = t.get("details", {})
category = t["category"]
rows = []
if category == "ride":
for k, v in [("Distance", details.get("distance")), ("Duration", details.get("duration")),
("Plate", details.get("license_plate")), ("From", details.get("from")),
("To", details.get("to"))]:
if v:
rows.append(f'
{k}{v}
')
elif category == "food":
if details.get("restaurant"):
rows.append(f'
Restaurant{details["restaurant"]}
')
if details.get("items"):
items_str = ", ".join(details["items"][:3])
rows.append(f'
Items{items_str}
')
if details.get("delivery_fee"):
rows.append(f'
Delivery{details["delivery_fee"]}
')
elif category == "payment":
for k, v in [("To", details.get("to")), ("From", details.get("from")),
("UPI Ref", details.get("upi_ref")), ("Status", details.get("status"))]:
if v:
rows.append(f'
{k}{v}
')
elif category == "shopping":
if details.get("items"):
for item in details["items"][:4]:
rows.append(f'
·{item}
')
if details.get("delivery_date"):
rows.append(f'
Delivery{details["delivery_date"]}
')
else:
# Generic: show snippet
snippet = t.get("snippet", "")[:150]
if snippet:
rows.append(f'
{snippet}
')
if not rows:
snippet = t.get("snippet", "")[:150]
rows.append(f'
{snippet or "No details extracted."}
')
return "\n".join(rows)
def _render_amounts(t: dict) -> str:
amounts = t.get("amounts", [])
if not amounts or len(amounts) <= 1:
return ""
items = "".join(f'{a}' for a in amounts[:6])
return f'
All Amounts
{items}
'
def _render_image_analysis(t: dict) -> str:
analyses = t.get("image_analyses", [])
if not analyses:
return ""
items = []
for a in analyses[:2]:
summary = a.get("summary", "")[:120]
doc_type = a.get("doc_type", "unknown")
items.append(f'
"""
# ── Insights panel ────────────────────────────────────────────────────────────
def _render_insights(transactions: list, summary: dict) -> str:
insights = []
total = summary.get("total_spend", 0)
if total > 0:
insights.append(("💡", "good", f"Total retrievable spend: ₹{total:,.2f} across {summary.get('count', 0)} transactions."))
reimb = [t for t in transactions if t.get("reimbursable")]
if reimb:
reimb_total = sum(
float(re.sub(r'[^\d.]', '', t["total"])) for t in reimb if t.get("total")
and re.sub(r'[^\d.]', '', t["total"]).replace('.', '').isdigit()
)
insights.append(("🧾", "good", f"{len(reimb)} reimbursable receipts found totaling ₹{reimb_total:,.2f}."))
by_cat = summary.get("by_category", {})
if by_cat:
top = list(by_cat.items())[0]
insights.append(("📊", "info", f"Highest spending category: {top[0].title()} at ₹{top[1]:,.2f}."))
cash_payments = [t for t in transactions if t.get("payment_method") == "Cash"]
if cash_payments:
insights.append(("⚠️", "warn", f"{len(cash_payments)} cash payment(s) detected — no digital trail for these transactions."))
rows = "".join(f'