);
}
/* ========================= Root ========================= */
// Normalize any legacy stage names onto the current set whenever deals enter state.
const migrateDeals = (arr) => Array.isArray(arr)
? arr.map((d) => {
const ns = window.normalizeStage(d.stage);
let r = ns === d.stage ? d : { ...d, stage: ns };
// Migrate legacy analyst string → assignees array so AssigneePicker shows it
if (r.analyst && !r.assignees) r = { ...r, assignees: [r.analyst] };
return r;
})
: arr;
const isDead = (d) => d.stage === 'Dead';
const isLOI = (d) => window.LOI_STAGES.includes(d.stage);
const isPipeline = (d) => window.PIPELINE_STAGES.includes(d.stage);
const NAV = [
{ key: 'pipeline', label: 'Pipeline', icon: 'board' },
{ key: 'loi', label: 'LOI Status', icon: 'flag' },
{ key: 'metrics', label: 'Metrics', icon: 'pulse' },
{ key: 'analytics', label: 'Analytics', icon: 'chart' },
{ key: 'tasks', label: 'Tasks', icon: 'check' },
{ key: 'crm', label: 'CRM', icon: 'deal' },
{ key: 'dead', label: 'Dead Deals', icon: 'close' }];
// PDFs that render bold text via double-struck glyphs (each character drawn twice)
// extract as garbled doubled tokens, e.g. "$$33,,999900,,660000" for "$3,990,600" —
// which wrecks every bold financial total. Collapse any fully-doubled token (each
// adjacent pair identical) back to single characters. Guarded to 6+ chars with a
// non-digit present so legit comma-formatted numbers and short words are untouched.
function fixDoubledGlyphs(text){
if(!text) return text;
return text.replace(/\S+/g,(tok)=>{
if(tok.length>=6 && tok.length%2===0 && /[^0-9]/.test(tok)){
let doubled=true;
for(let i=0;i=100k filter and the comma-group regex.
// Returns null if the layout isn't present (caller keeps the model's value).
function extractProFormaTopline(text){
if(!text) return null;
const labels = ['Total Effective Gross Income','Effective Gross Income','Effective Gross Revenue','Effective Gross','Total Effective Gross'];
const boundaries = ['Operating Expense','Total Operating','Total Expense','Net Operating','NOI','Less Operating','Less:','Expenses'];
const moneyRe = /\$\s?([0-9]{1,3}(?:,[0-9]{3})+)(?:\.[0-9]+)?/g;
for(const label of labels){
let from = 0, idx;
while((idx = text.indexOf(label, from)) !== -1){
from = idx + label.length;
let tail = text.slice(idx + label.length, idx + label.length + 700);
// require the DATA row: a $ amount must appear almost immediately after the label
const firstDollar = tail.indexOf('$');
if(firstDollar < 0 || firstDollar > 20) continue;
// cut at the next row's label or a parenthesized negative so we stay on this row
let cut = tail.length;
for(const b of boundaries){ const bi = tail.indexOf(b); if(bi > 0 && bi < cut) cut = bi; }
const negParen = tail.indexOf('($'); if(negParen > 0 && negParen < cut) cut = negParen;
const row = tail.slice(0, cut);
const large = [];
let m; moneyRe.lastIndex = 0;
while((m = moneyRe.exec(row)) !== null){
const v = Number(m[1].replace(/,/g,''));
if(v >= 100000) large.push(v);
}
if(large.length >= 2) return large[large.length-1];
}
}
return null;
}
async function extractFileText(file) {
const name = (file.name || '').toLowerCase();
if (window.XLSX && /\.(xlsx|xlsm|xls)$/.test(name)) {
try {
const buf = await file.arrayBuffer();
const wb = window.XLSX.read(buf, { type: 'array' });
let out = '';
wb.SheetNames.forEach((sn) => {
const csv = window.XLSX.utils.sheet_to_csv(wb.Sheets[sn]);
if (csv.trim()) out += `=== Sheet: ${sn} ===\n${csv}\n\n`;
});
return out;
} catch (e) {/* fall through */}
}
// PDF — prefer pdf-parse (bundles a MODERN pdf.js). The legacy global pdfjsLib
// (v3.11) shatters this OM's faux-bold financial tables into irrecoverable
// space-split doubled glyphs ("B Be ee ec ch h"); pdf-parse decodes the same
// embedded subset fonts into contiguous text the de-doubler can repair.
if (/\.pdf$/.test(name) || file.type === 'application/pdf') {
// 1) pdf-parse via dynamic import (CSP-verified)
try {
const buf = await file.arrayBuffer();
const mod = await import('https://cdn.jsdelivr.net/npm/pdf-parse@2.4.5/dist/pdf-parse/web/pdf-parse.es.js');
mod.PDFParse.setWorker('https://cdn.jsdelivr.net/npm/pdf-parse@2.4.5/dist/pdf-parse/web/pdf.worker.min.mjs');
const parser = new mod.PDFParse({ data: new Uint8Array(buf) });
const out = await parser.getText();
if (out && out.text && out.text.trim()) return fixDoubledGlyphs(out.text);
} catch (e) {/* fall through to legacy extractor */}
// 2) legacy global pdfjsLib fallback
if (window.pdfjsLib) {
try {
const pdf = await window.pdfjsLib.getDocument({ data: await file.arrayBuffer() }).promise;
let text = '';
for (let i = 1; i <= pdf.numPages; i++) {
const page = await pdf.getPage(i);
const content = await page.getTextContent();
text += `\n[Page ${i}]\n` + content.items.map((x) => x.str).join(' ');
}
return fixDoubledGlyphs(text);
} catch (e) {/* fall through */}
}
}
// CSV / plain text
return await file.text().catch(() => '');
}
// Build a focused excerpt around financial keywords so a big OM's pro-forma page
// is always included even when the doc far exceeds the model budget.
// `keywords` is ordered by priority (most specific first); windows created by
// higher-priority keywords are kept first, so a deep page-29 GPR table wins over
// dozens of early generic-word hits.
function focusExcerpt(text, keywords, budget = 16000) {
if (text.length <= budget) return text;
const lower = text.toLowerCase();
const radius = 1600;
const windows = [];
keywords.forEach((kw, rank) => {
const k = kw.toLowerCase();
let idx = 0, count = 0;
while ((idx = lower.indexOf(k, idx)) !== -1) {
windows.push({ pos: idx, rank, start: Math.max(0, idx - radius), end: Math.min(text.length, idx + radius) });
idx += k.length;
if (++count > 40) break;
}
});
if (!windows.length) return text.slice(0, budget);
// Keep specific (low-rank) windows first; tie-break by document order
windows.sort((a, b) => a.rank - b.rank || a.pos - b.pos);
const chosen = [];
let used = 0;
for (const w of windows) {
// skip if already covered by a chosen window
if (chosen.some((c) => w.pos >= c.start && w.pos <= c.end)) continue;
const len = w.end - w.start;
if (used + len > budget) continue;
chosen.push(w);
used += len;
if (used >= budget) break;
}
// Emit in document order so tables read coherently
chosen.sort((a, b) => a.start - b.start);
return chosen.map((w) => text.slice(w.start, w.end)).join('\n…\n');
}
// The listing / financing team almost always lives on the FINAL page(s) of a modern
// OM, in a vertical Name / Title / Phone / Email block under headers like "Primary
// Contacts", "DSF Contacts" (Debt & Structured Finance), "Capital Markets", "Debt &
// Equity" or "Primary Markets Team" — a DIFFERENT layout from the cover-page
// "Exclusively Listed By" box. focusExcerpt fills its budget with income tables and
// routinely drops these tail pages (on a 200k-char OM the last page never makes the
// cut), so capture them deterministically here. Strategy: from the back half of the
// document, start at the earliest contact-header we can find; if none matches, fall
// back to the final `budget` characters — the contacts are there either way.
function contactExcerpt(text, budget = 9000) {
if (!text) return '';
if (text.length <= budget) return text;
const lower = text.toLowerCase();
const markers = [
'primary contacts', 'dsf contacts', 'debt & structured finance', 'debt and structured finance',
'debt & equity', 'debt and equity', 'capital markets', 'primary markets team',
'listing team', 'for more information', 'exclusively listed', 'exclusively represented',
'licensed broker', 'iabs'
];
const tailStart = Math.floor(text.length * 0.55);
let begin = -1;
for (const m of markers) {
const i = lower.indexOf(m, tailStart);
if (i !== -1 && (begin === -1 || i < begin)) begin = i;
}
let slice = begin !== -1 ? text.slice(begin) : text.slice(-budget);
if (slice.length > budget) slice = slice.slice(-budget);
return slice;
}
// Rent rolls must be read as ONE table — keyword-window fragmenting (focusExcerpt)
// splits the per-unit rows apart and silently drops units off the end, which makes
// every sum come up short. Instead: cut the Future Residents / Applicants section
// (we never count it) and keep the full remaining table, only capping at a generous
// budget. The model then extracts rows; JS does the arithmetic.
function rentRollExcerpt(text, budget = 130000) {
const lower = text.toLowerCase();
let cut = text.length;
for (const marker of ['future resident', 'future occupanc', 'pending applicant', 'future applicant']) {
const i = lower.indexOf(marker);
if (i !== -1 && i < cut) cut = i;
}
let out = text.slice(0, cut);
if (out.length > budget) out = out.slice(0, budget);
return out;
}
// Turn the model's per-unit rows into exact aggregate figures — all summing/counting
// happens here in JS, never in the model. Falls back to any aggregate fields the
// model returned if no per-unit array is present.
function summarizeRentRoll(raw) {
const num = (v) => { const n = Number(String(v ?? '').replace(/[$,()]/g, '')); return isNaN(n) ? 0 : Math.abs(n); };
const units = Array.isArray(raw.units) ? raw.units : [];
if (!units.length) return raw;
let totalUnits = 0, vacantUnits = 0, mAll = 0, mInH = 0, mVac = 0;
const vacantUnitList = [];
units.forEach((u) => {
const market = num(u.m != null ? u.m : u.market);
const rent = num(u.r != null ? u.r : u.rent);
const vf = (u.v != null ? u.v : u.vacant);
// Vacancy comes from the unit's status flag only — a $0 rent does NOT make a unit vacant
// (units on notice / in eviction read $0 but are still occupied).
const isVac = vf === 1 || vf === true || vf === '1' || vf === 'true';
totalUnits++;
mAll += market;
if (isVac) {
vacantUnits++; mVac += market;
const id = u.i != null ? u.i : u.id;
if (id != null && String(id) !== '') vacantUnitList.push(String(id));
} else {
mInH += rent;
}
});
return {
totalUnits,
vacantUnits,
marketRentMonthlyAll: Math.round(mAll),
inHouseRentMonthlyOccupied: Math.round(mInH),
marketRentMonthlyVacant: Math.round(mVac),
vacantUnitList,
notes: raw.notes || ''
};
}
// Deterministic tabular rent-roll parser. Most rent rolls are clean one-row-per-unit
// grids (Unit | … | Status | Market Rent | Rent). Asking the model to echo back every
// row overflows its output on medium/large rolls and the upload fails — so when we can
// detect the header + columns we sum it all in code. Returns null if it's not a clean
// table (caller falls back to the model per-unit extraction, fine for small/odd rolls).
function parseRentRollTabular(text){
if(!text) return null;
// delimiter-aware line parser that respects quoted fields (handles CSV and tab-separated)
const parseRows = (t, delim) => {
const rows = [];
t.split(/\r?\n/).forEach((line) => {
const cells = []; let cur = '', q = false;
for(let i=0;i { const n = Number(String(v==null?'':v).replace(/[$,()\s]/g,'')); return isNaN(n)?null:n; };
// auto-detect delimiter (xlsx→csv uses commas; some exports are tab-separated)
const sample = text.slice(0, 6000);
const delim = ((sample.match(/\t/g)||[]).length > (sample.match(/,/g)||[]).length) ? '\t' : ',';
const rows = parseRows(text, delim);
// locate the header row (needs a unit column, a market-rent column, and a rent column).
// Tolerant matchers cover the many label variants brokers/PM software use.
const isUnit = (c)=> ['unit','unit #','unit#','unit no','unit no.','unit number','unit id','unit name','apt','apt #','apt no','apartment','space','door'].includes(c) || /^(unit|apt|apartment|bldg)\b/.test(c) || /\bunit\s*(#|no\.?|number|id)?$/.test(c);
const isMarket = (c)=> c==='market' || /market\s*(rent|rate)?/.test(c) || /gross.*market/.test(c);
const isRent = (c)=> !/market/.test(c) && (['rent','actual rent','lease rent','current rent','base rent','scheduled rent','charge','actual','tenant rent','net rent','monthly rent','contract rent','lease rent/charge'].includes(c) || /^rent\b/.test(c) || /\brent$/.test(c));
const isStatus = (c)=> c.includes('status') || c.includes('occupanc') || c==='lease status';
let hi = -1, cols = null;
for(let i=0;ic.trim().toLowerCase());
const unitIdx = r.findIndex(isUnit);
const marketIdx = r.findIndex(isMarket);
const rentIdx = r.findIndex(isRent);
const statusIdx = r.findIndex(isStatus);
if(unitIdx>=0 && marketIdx>=0 && rentIdx>=0){ hi=i; cols={unitIdx,marketIdx,rentIdx,statusIdx}; break; }
}
if(hi<0) return null;
let totalUnits=0, vacantUnits=0, mAll=0, mInH=0, mVac=0;
const vacantUnitList = [];
const seenUnits = new Set(); // dedupe charge-code rows (multiple rows per unit)
for(let i=hi+1;i=0 ? (r[cols.statusIdx]||'').trim() : '';
if(market==null && rent==null) continue; // not a real unit row
totalUnits++;
if(market!=null) mAll += market;
// Physical vacancy is determined by STATUS, not by a zero rent. A unit on Notice or in
// Eviction still has a paying tenant (and may show $0 in the rent column) — it is OCCUPIED.
// Only when there is no status column at all do we fall back to "no rent ⇒ vacant".
const statusKnown = cols.statusIdx>=0;
// A unit counts as physically VACANT only when its status says vacant AND it is NOT
// pre-leased. "Vacant-Rented" / "Vacant-Leased" / applicant units have income coming and
// are excluded from the vacancy count (they are not an available-unit loss). Units on
// Notice or in Eviction are OCCUPIED. With no status column, fall back to "no rent ⇒ vacant".
const preLeased = /\b(rented|leased|pre[\s-]?leased|applicant|pending|reserved)\b/i.test(status);
const isVac = statusKnown
? (/vacant/i.test(status) && !preLeased) || (status==='' && (rent==null || rent===0))
: (rent==null || rent===0);
if(isVac){ vacantUnits++; if(market!=null) mVac += market; vacantUnitList.push(unit); }
else if(rent!=null){ mInH += rent; }
}
if(totalUnits < 1) return null;
return {
totalUnits, vacantUnits,
marketRentMonthlyAll: Math.round(mAll),
inHouseRentMonthlyOccupied: Math.round(mInH),
marketRentMonthlyVacant: Math.round(mVac),
vacantUnitList,
notes: `Parsed ${totalUnits} units directly from the rent-roll table.`
};
}
function CloudSplash({ text }) {
return (
);
}
// Parse an Offering Memorandum into deal fields (name, market, units, vintage, broker,
// contacts, and in-place + pro-forma financials). Shared by the per-deal upload handler
// and the Add-Deal modal's auto-fill. Returns { parsed, fullText }.
async function runOMParse(file) {
const fullText = await extractFileText(file);
const finText = focusExcerpt(fullText, [
// pro-forma EFFECTIVE GROSS INCOME — the PRIMARY target, often deep in the OM.
// Listed first so its table wins the budget over early generic hits.
'effective gross income', 'total effective gross', 'effective gross',
'upgrade forecast', 'unit upgrade', 'acquisition / unit', 'stabilized',
'pro forma', 'proforma', 'financial summary', 'income statement',
// in-place / T-12 OPERATING EXPENSES — second target for the going-in underwriting
'total operating expenses', 'total operating expense', 'operating expenses',
't-12', 't12', 't-3', 't3', 't-1', 't1', 'trailing', 'total expenses', 'expense summary',
'controllable', 'non-controllable', 'property taxes', 'real estate taxes', 'insurance',
'net operating income',
'total revenue', 'total income', 'net rental income',
'gross scheduled income', 'gross potential rent', 'rental revenue', 'rental income',
// cover-page listing box (the OTHER place contacts appear) — lower priority
'exclusively listed', 'investment sales', 'rent roll'
], 34000);
// Broker / financing-team contacts almost always sit on the FINAL page(s) in a
// vertical Name/Title/Phone/Email block under headers like "Primary Contacts",
// "DSF Contacts", "Capital Markets" or "Debt & Equity" — a different layout the
// financial excerpt above routinely drops. Guarantee those tail pages here.
const contactText = contactExcerpt(fullText, 9000);
const text = finText + (contactText
? '\n\n=== END-OF-OM CONTACT PAGES (extract EVERY person listed in this section) ===\n' + contactText
: '');
const prompt = `You are parsing a multifamily Offering Memorandum for Altus Equity. Extract ONLY the fields below. Return ONLY a valid JSON object — no commentary. Use null for any field not found.
{
"name": "property or deal name",
"market": "City, ST — city and two-letter state only, no street address or ZIP",
"units": 0,
"vintage": "year built (see rules) — a string; null if not stated",
"brokerFirm": "full brokerage firm name from the cover page or 'Exclusively Listed By' section",
"brokerContacts": [{ "name": "", "title": "", "phone": "", "email": "" }],
"effectiveGrossIncome": 0,
"totalOpex": 0,
"opexBasis": "T-12",
"brokerEGI": 0
}
Rules for vintage — the year the property was originally BUILT (its construction vintage), not the renovation year. Look on the cover page, the property-summary / highlights box, and any "Year Built", "Built", or "Vintage" field. It may read "Built in 1985", "Year Built: 1985", "1985 Vintage", or "Built 1986 / Renovated 2019" (take the BUILT year, 1986). For a multi-building property built in different years it is often a slash- or comma-joined list, e.g. "Built in 1997/1986/1975" — return all of them exactly as "1997/1986/1975". Return the year(s) as a STRING (no labels). Use null if no construction year is stated.
Rules for brokerContacts — extract ONLY the named LISTING TEAM for THIS deal: the handful of people a buyer would actually contact (the agents in the cover / "Exclusively Listed By" box, a "For more information contact" block, and the primary people on the final contact page). This is normally 1–6 people.
CRITICAL — DO NOT dump the brokerage's company directory. Many OMs include a full firm "team" / "advisory group" / "our professionals" roster page listing 15–30 employees by Name + Title across a region. That is a marketing org chart, NOT the deal's listing team — EXCLUDE it entirely. Signs you are looking at a directory to skip: a long grid/list of names under one firm with no per-person phone/email, names for unrelated markets, or more than ~6 people. NEVER return more than 6 contacts. If a page has many names, keep ONLY the few explicitly tied to listing/marketing THIS property (usually the cover or "Exclusively Listed By" names) and drop the rest.
Capture each person's phone and email WHEN SHOWN — but a person still qualifies as a listing contact if only their name + title appear (some OMs list the listing team without individual emails/phones, sometimes with just a shared team email/phone). Capture name + title in that case and leave phone/email null.
WHERE the contacts are: a section delimited by "=== END-OF-OM CONTACT PAGES ===" is appended below. Two layouts appear (handle both):
FORMAT A (vertical block): each person's Name, Title, Phone and Email sit on their OWN consecutive lines, often under headers like "Primary Contacts", "Investment Sales", "Capital Markets", "Debt & Equity".
FORMAT B (horizontal / tab-separated TREC or IABS "Licensed Broker" disclosure): one person per line, fields in ANY order, possibly with a state license number, e.g. "Bard.Hoover@MarcusMillichap.com TX 610697 Bard Hoover (972) 755-5216" (Email · License# · Name · Phone). Parse by field TYPE — the token with an @ is the email, the phone-pattern token is the phone, a license number (e.g. "TX 610697", "432723", "9002994") is NOT a name and must be dropped, the remaining human name is the name.
DEDUPE & SKIP: skip any row that names ONLY the brokerage firm with no individual. Merge duplicates of the same person into ONE entry with the most complete info. For each kept person capture:
- name (full name)
- title (exact title as printed)
- phone (direct line if shown — strip any trailing "direct" / "mobile" / "office" label, keep just the number; null if not shown)
- email (null if not shown)
Return at most 6 people. Return [] only if no individual listing contact is named anywhere.
Note: names may contain apostrophes (e.g. O’Brien, O’Connor, D’Angelo) — these are valid full names; keep the apostrophe.
rules for effectiveGrossIncome — the CURRENT / IN-PLACE (actual, NOT pro-forma) EFFECTIVE GROSS INCOME from the OM's financial statement. This is the income subtotal AFTER economic / physical vacancy and loss are subtracted and AFTER other income (RUBS, fees, etc.) is ADDED — i.e. Gross Potential / Scheduled Income − economic vacancy + other income = Effective Gross Income. Use the row labeled EXACTLY "Effective Gross Income" (or "Total Effective Gross Income" / "Effective Gross Revenue" / "EGI" / "Total Revenue" / "Total Income"). PICK THE COLUMN that reflects ACTUAL / IN-PLACE / TRAILING performance — the trailing-twelve (T-12) or most-recent-actual-year column — NOT the stabilized "Upgrade Forecast" / "Pro Forma" projection column. Return one ANNUAL figure as a raw number (no $ or commas). If only a partial trailing period (T-3 or T-1) is shown, annualize it to 12 months (T-3 × 4, T-1 × 12).
rules for totalOpex — the TOTAL OPERATING EXPENSES from the OM's IN-PLACE / TRAILING financials. PREFER the T-12 (trailing-twelve-month) total operating expenses. If the OM only shows a T-3 (trailing 3 months) or T-1 (trailing 1 month) operating-expense figure, USE that and ANNUALIZE it to a full 12-month number (T-3 × 4, T-1 × 12). CRITICAL: Property Taxes AND Insurance MUST be included in totalOpex. Many statements report a "Total Operating Expenses" subtotal that covers only "controllable" expenses and list Property Taxes and Insurance separately BELOW it as "non-controllable" / fixed expenses — if so, ADD taxes and insurance on top so totalOpex always includes both. NEVER include debt service, mortgage interest, depreciation, amortization, capital expenditures, reserves, replacement reserves, or asset-management fees. Return one ANNUAL figure as a raw number (no $ or commas).
rules for opexBasis — a SHORT string naming the trailing period the totalOpex came from and whether it was annualized: "T-12" if a full trailing-twelve figure was used, "T-3 annualized" if you used a trailing-3-month figure × 4, "T-1 annualized" if a trailing-1-month figure × 12. Use null if no operating-expense figure was found.
rules for brokerEGI — the broker's PRO FORMA / STABILIZED "Upgrade Forecast" EFFECTIVE GROSS INCOME. Work step by step:
STEP 1 — PICK THE RIGHT ROW: Use the row whose label is EXACTLY "Effective Gross Income" (sometimes "Total Effective Gross Income", "Effective Gross Revenue", or abbreviated "EGI"). This is the income subtotal AFTER vacancy, loss-to-lease, concessions and bad debt are subtracted and other income is added — it sits LOWER in the income statement, just ABOVE operating expenses / NOI. DO NOT use the top-line "Gross Scheduled Income", "Gross Scheduled Rent", "Gross Potential Rent", or "Market Rent" rows — those are gross rent BEFORE deductions and are the WRONG, higher number. Also do NOT use "Net Operating Income". If no explicit "Effective Gross Income" line exists, fall back to "Total Revenue" or "Total Income" (the equivalent effective-income subtotal).
STEP 2 — PICK THE RIGHT COLUMN: That row jams MANY columns onto one text line: historical actuals (e.g. 2023, 2024, 2025), trailing / annualized columns, an "Acquisition Forecast" column, a per-unit column, a per-square-foot column, and FINALLY a stabilized "Upgrade Forecast" / "Unit Upgrade" / "Acquisition / Unit Upgrade" column. Return the value from that stabilized "Upgrade Forecast" column — in these side-by-side rows it is the LAST / RIGHT-MOST large annual dollar amount (hundreds-of-thousands or millions). IGNORE per-unit amounts, per-square-foot amounts (e.g. $14.47), and percentages (e.g. 100%, 103%).
WORKED EXAMPLE — for the row:
"Effective Gross Income $4,201,118 $4,310,540 102% $4,402,776 100% $18.32 100% $4,628,301 100%"
the correct answer is 4628301 — the LAST large dollar figure (the Upgrade Forecast column).
Return that single ANNUAL figure as a raw number (no $ or commas). This table is usually deep in the OM (often page 50+) — scan the ENTIRE excerpt, not just the start.
OM text (page markers like [Page 29] are included; excerpt focused around financial sections):
${text}`;
const result = await aiComplete(prompt);
const parsed = safeParseJSON(result) || {};
// Deterministic override: pull the pro-forma top-line gross rent straight from the
// text — the dense financial-analysis table is too error-prone for the model.
const gsiForecast = extractProFormaTopline(fullText);
if (gsiForecast != null) parsed.brokerEGI = gsiForecast;
return { parsed, fullText };
}
/* Header save-status indicator — shows cloud sync state so it's clear when edits are safe. */
function SaveIndicator({ state }) {
const cfg = {
idle: { dot: '#5a7a96', text: '' },
dirty: { dot: '#d9a441', text: 'Unsaved…' },
saving: { dot: '#d9a441', text: 'Saving…' },
saved: { dot: '#4caf7e', text: 'Saved' },
error: { dot: '#e0686b', text: 'Save failed' },
}[state] || { dot: '#5a7a96', text: '' };
if (!cfg.text) return null;
return (
{cfg.text}
);
}
function AltusApp() {
const [t, setTweak] = useTweaks(TWEAK_DEFAULTS);
const [deals, setDeals] = useS(() => migrateDeals(loadDeals()));
const [view, setView] = useS('pipeline');
const [openId, setOpenId] = useS(null);
const [showSettings, setShowSettings] = useS(false);
const [user, setUser] = useS('Garrett');
const [omMap, setOMMap] = useS({});
const [t12Map, setT12Map] = useS({});
const [rrMap, setRRMap] = useS({});
const [todos, setTodos] = useS(() => { try { return JSON.parse(localStorage.getItem(LS_TODOS)) || []; } catch { return []; } });
const clearOM = (id) => setOMMap( (m) => { const n = {...m}; delete n[id]; return n; });
const addTodo = (t) => setTodos((ts) => [t, ...ts]);
const patchTodo = (id, fields) => setTodos((ts) => ts.map((t) => t.id === id ? { ...t, ...fields } : t));
const deleteTodo = (id) => setTodos((ts) => ts.filter((t) => t.id !== id));
const clearT12 = (id) => setT12Map((m) => { const n = {...m}; delete n[id]; return n; });
const clearRR = (id) => setRRMap( (m) => { const n = {...m}; delete n[id]; return n; });
const [contacts, setContacts] = useS(loadContacts);
// ---- Cloud auth + sync (Supabase) ----
const cloud = window.AltusCloud || {};
const [session, setSession] = useS(cloud.requireLogin ? undefined : null); // undefined = still checking
const [authBusy, setAuthBusy] = useS(false);
const cloudLoaded = useR(false);
const saveTimer = useR(null);
const mainRef = useR(null); // ref to for scroll save/restore
const savedScrollRef = useR(0); // saved scroll position before opening a deal
const contactsLoaded = useR(false);
const contactsSaveTimer = useR(null);
const todosLoaded = useR(false);
const todosSaveTimer = useR(null);
const dealsRef = useR(deals); // always-fresh deals for the unload flush
const [saveState, setSaveState] = useS('idle'); // idle | dirty | saving | saved | error
useE(() => {
if (!cloud.requireLogin) { setSession(null); return; }
let active = true;
cloud.getSession().then((s) => { if (active) setSession(s); }).catch(() => { if (active) setSession(null); });
const off = cloud.onAuthChange((s) => { if (active) setSession(s); });
return () => { active = false; if (off) off(); };
}, []);
// Load deals from cloud once authenticated (or immediately if no login required but enabled)
useE(() => {
if (!cloud.enabled) return;
if (cloud.requireLogin && !session) return;
if (cloudLoaded.current) return; // already loaded — skip token-refresh re-fires that would wipe local edits
let active = true;
cloud.loadDeals().then((rows) => {
if (!active || !rows) return;
cloudLoaded.current = true;
if (rows.length) {
const hasLocalSave = !!localStorage.getItem(LS_KEY);
if (hasLocalSave) {
// Merge: local wins for every ID it knows about (localStorage is written
// synchronously on every change, so it is always >= cloud freshness).
// Cloud contributes only deals that don't exist locally yet (other device / session).
const localById = Object.fromEntries(deals.map(d => [String(d.id), d]));
const merged = [...deals, ...rows.filter(r => !localById[String(r.id)])];
setDeals(migrateDeals(merged));
// Push merged state back so cloud catches up to anything that wasn't synced yet.
cloud.saveDeals(merged).catch(e => console.warn('[cloud] merge-sync failed', e));
} else {
// Fresh browser with no localStorage — trust cloud data entirely.
setDeals(migrateDeals(rows));
}
} else {
// Empty cloud — seed it from current local data.
cloud.saveDeals(deals).catch((e) => console.warn('[cloud] seed failed', e));
}
}).catch((e) => console.warn('[cloud] load failed, using local data', e));
return () => { active = false; };
}, [session]);
// Load contacts from cloud once authenticated
useE(() => {
if (!cloud.enabled) return;
if (cloud.requireLogin && !session) return;
if (contactsLoaded.current) return; // already loaded
let active = true;
cloud.loadContacts().then((rows) => {
if (!active || !rows) return;
if (rows.length) { contactsLoaded.current = true; setContacts(rows); }
else { if (contacts.length) cloud.saveContacts(contacts).catch((e) => console.warn('[cloud] contacts seed failed', e)); contactsLoaded.current = true; }
}).catch((e) => console.warn('[cloud] contacts load failed, using local', e));
return () => { active = false; };
}, [session]);
const addContact = (c) => setContacts((cs) => cs.find((x) => x.id === c.id) ? cs : [...cs, c]);
const patchContact = (id, changes) => setContacts((cs) => cs.map((c) => c.id === id ? { ...c, ...changes } : c));
// Load todos from cloud once authenticated (mirrors contacts)
useE(() => {
if (!cloud.enabled) return;
if (cloud.requireLogin && !session) return;
if (todosLoaded.current) return;
let active = true;
cloud.loadTodos().then((rows) => {
if (!active || !rows) return;
if (rows.length) { todosLoaded.current = true; setTodos(rows); }
else { if (todos.length) cloud.saveTodos(todos).catch((e) => console.warn('[cloud] todos seed failed', e)); todosLoaded.current = true; }
}).catch((e) => console.warn('[cloud] todos load failed, using local', e));
return () => { active = false; };
}, [session]);
// Persist todos: localStorage immediately + debounced cloud save
useE(() => {
try {localStorage.setItem(LS_TODOS, JSON.stringify(todos));} catch (e) {}
if (cloud.enabled && (!cloud.requireLogin || session) && todosLoaded.current) {
clearTimeout(todosSaveTimer.current);
todosSaveTimer.current = setTimeout(() => { cloud.saveTodos(todos).catch((e) => console.warn('[cloud] todos save failed', e)); }, 1000);
}
}, [todos]);
useE(() => {
try {localStorage.setItem(LS_CONTACTS, JSON.stringify(contacts));} catch (e) {}
if (cloud.enabled && (!cloud.requireLogin || session) && contactsLoaded.current) {
clearTimeout(contactsSaveTimer.current);
contactsSaveTimer.current = setTimeout(() => { cloud.saveContacts(contacts).catch((e) => console.warn('[cloud] contacts save failed', e)); }, 1200);
}
}, [contacts]);
// Persist deals: localStorage immediately + debounced cloud save with status tracking.
useE(() => {
dealsRef.current = deals;
try { localStorage.setItem(LS_KEY, JSON.stringify(deals)); } catch (e) {}
// Rolling backup — kept in a separate key so a corrupted primary save
// doesn't also wipe the recovery copy. Written only when deal count is
// plausible (guards against accidentally backing up an empty array).
try {
if (deals.length > 0) {
localStorage.setItem(LS_KEY + '_backup', JSON.stringify({ ts: Date.now(), deals }));
}
} catch (e) {}
if (cloud.enabled && (!cloud.requireLogin || session) && cloudLoaded.current) {
setSaveState('dirty');
clearTimeout(saveTimer.current);
saveTimer.current = setTimeout(() => {
setSaveState('saving');
cloud.saveDeals(dealsRef.current)
.then(() => setSaveState('saved'))
.catch((e) => { console.warn('[cloud] save failed', e); setSaveState('error'); });
}, 700);
}
}, [deals]);
// Flush any pending save when the tab is hidden or closed, so edits made right before
// leaving aren't lost to the debounce window.
useE(() => {
if (!cloud.enabled) return;
const flush = () => {
if (!cloudLoaded.current) return;
clearTimeout(saveTimer.current);
// keepalive upsert so the request survives page teardown
cloud.saveDeals(dealsRef.current).catch(() => {});
};
const onVis = () => { if (document.visibilityState === 'hidden') flush(); };
window.addEventListener('visibilitychange', onVis);
window.addEventListener('pagehide', flush);
window.addEventListener('beforeunload', flush);
return () => {
window.removeEventListener('visibilitychange', onVis);
window.removeEventListener('pagehide', flush);
window.removeEventListener('beforeunload', flush);
};
}, []);
// Scroll to top when a deal opens so DealDetail is always fully visible;
// restore previous position when the user goes back.
useE(() => {
if (openId) {
savedScrollRef.current = mainRef.current ? mainRef.current.scrollTop : 0;
if (mainRef.current) mainRef.current.scrollTop = 0;
} else {
if (mainRef.current) mainRef.current.scrollTop = savedScrollRef.current;
}
}, [openId]);
useE(() => {
const r = document.documentElement.style;
r.setProperty('--accent', t.accent);
r.setProperty('--accent-2', shade(t.accent, -18));
r.setProperty('--accent-soft', tint(t.accent, 0.90));
r.setProperty('--row-h', (t.density === 'compact' ? 38 : t.density === 'comfy' ? 52 : 44) + 'px');
}, [t.accent, t.density]);
const patch = (id, changes) => setDeals((ds) => ds.map((d) => d.id === id ? { ...d, ...changes } : d));
const bulkPatch = (ids, changes) => { const s = new Set(ids); setDeals((ds) => ds.map((d) => s.has(d.id) ? { ...d, ...changes } : d)); };
const bulkDelete = (ids) => {
const s = new Set(ids);
setDeals((ds) => ds.filter((d) => !s.has(d.id)));
// Explicitly delete from cloud — never rely on auto-save pruning for this.
if (cloud.enabled && cloud.deleteCloudDeals) {
cloud.deleteCloudDeals([...ids]).catch((e) => console.warn('[cloud] explicit delete failed', e));
}
};
// Reorder the VISIBLE deals into orderedIds, keeping each visible deal's original slot
// in the full array occupied (so the manual order survives filtering/search).
const reorderVisible = (orderedIds) => setDeals((ds) => {
const idSet = new Set(orderedIds);
const slots = []; ds.forEach((d, i) => { if (idSet.has(d.id)) slots.push(i); });
const byId = {}; ds.forEach((d) => { byId[d.id] = d; });
const reordered = orderedIds.map((id) => byId[id]).filter(Boolean);
const copy = ds.slice();
slots.forEach((slot, k) => { copy[slot] = reordered[k]; });
return copy;
});
const addDeal = (rawDeal) => {
const { _omContacts, ...deal } = rawDeal || {};
setDeals((ds) => [deal, ...ds]);
setOpenId(deal.id);
// Create CRM contacts from any broker contacts the OM auto-fill captured.
const people = _omContacts && Array.isArray(_omContacts.people) ? _omContacts.people : [];
if (people.length) {
setContacts((cs) => {
let next = [...cs];
people.forEach((pc) => {
if (!pc || !pc.name) return;
const exists = next.find((c) =>
(pc.email && c.email && c.email.toLowerCase() === pc.email.toLowerCase()) ||
(c.name && c.name.toLowerCase() === pc.name.toLowerCase()));
if (exists) {
next = next.map((c) => c.id === exists.id
? { ...c, dealIds: Array.from(new Set([...(c.dealIds || []), deal.id])), firm: c.firm || _omContacts.firm || '' }
: c);
} else {
next = [...next, { id: 'c_' + Date.now().toString(36) + '_' + Math.random().toString(36).slice(2, 6),
name: pc.name, title: pc.title || '', firm: _omContacts.firm || '', email: pc.email || '', phone: pc.phone || '',
dealIds: [deal.id], lastActivity: window.ALTUS_TODAY }];
}
});
return next;
});
}
};
const importDeals = (arr) => setDeals((ds) => [...arr, ...ds]);
const open = (id) => setOpenId(id);
const deal = deals.find((d) => d.id === openId);
const pipelineDeals = deals.filter(isPipeline);
const loiDeals = deals.filter(isLOI);
const liveDeals = deals.filter((d) => !isDead(d));
const deadDeals = deals.filter(isDead);
const acceptOM = (dealId, fields) => patch(dealId, fields);
// ── Property / Submarket Review ── progressive two-phase load.
// Phase 1: sentiment + crime (~800 token response) → shows immediately.
// Phase 2: economic drivers + submarket context. Silent failure keeps Phase 1 results.
const runMarketReview = async (dealId) => {
const d = (dealsRef.current || deals).find((x) => x.id === dealId);
if (!d) return;
patch(dealId, { marketReview: { status: 'running', startedAt: new Date().toISOString() } });
const ctx = [
d.name ? 'Property: ' + d.name : '',
d.market ? 'Market: ' + d.market : '',
d.units ? 'Units: ' + d.units : '',
d.vintage ? 'Built: ' + d.vintage : '',
d.type ? 'Type: ' + d.type : '',
d.locationQuery ? 'Address: ' + d.locationQuery : '',
].filter(Boolean).join(', ');
try {
// ── Phase 1 ── resident sentiment + crime snapshot
const p1 = 'Property & submarket review for: ' + (ctx || 'unknown') + '.\n' +
'Return ONLY JSON (no markdown, no extra text):\n' +
'{"residentSentiment":{"rating":3.6,"reviewCount":162,"trend":"Stable","positives":["loc convenience","quiet","responsive mgmt"],"negatives":["parking","security","pests"],"recentReviews":[{"date":"May 2025","stars":4,"text":"1 sentence."},{"date":"Apr 2025","stars":3,"text":"1 sentence."},{"date":"Mar 2025","stars":3,"text":"1 sentence."}],"source":"Google Reviews (est.)"},' +
'"crimeSnapshot":{"overall":{"label":"Better than Metro","vsMetro":"18% below metro avg"},"violentCrime":{"label":"Lower","vsMetro":"20% below metro avg"},"propertyCrime":{"label":"Lower","vsMetro":"15% below metro avg"},"relativePosition":["1 sentence.","1 sentence."],"recentActivity":["1 sentence.","1 sentence."],"investmentImplication":["1 sentence.","1 sentence."],"source":"NeighborhoodScout, FBI UCR (est.)"}}\n' +
'Replace ALL placeholder values with real estimates for this location. trend: Stable/Improving/Declining. crime labels: Better than Metro/At Metro Avg/Worse than Metro and Lower/At Metro Avg/Higher.';
const out1 = await aiComplete(p1, { maxTokens: 900 });
const r1 = safeParseJSON(out1);
if (!r1) throw new Error('Could not parse the property review.');
const baseData = {
residentSentiment: r1.residentSentiment || {},
crimeSnapshot: r1.crimeSnapshot || {},
};
patch(dealId, { marketReview: { status: 'done', generatedAt: new Date().toISOString(), data: baseData } });
// ── Phase 2 ── economic drivers + submarket context (silent failure OK)
try {
const p2 = 'Economic drivers and submarket context for: ' + (ctx || 'unknown') + '.\n' +
'Return ONLY JSON (no markdown, no extra text):\n' +
'{"economicDrivers":{"capitalInjections":[{"name":"project name","amount":"$XM"},{"name":"project name","amount":"$XM"},{"name":"project name","amount":"$XM"}],"majorEmployers":[{"name":"Employer","size":"large"},{"name":"Employer","size":"medium"},{"name":"Employer","size":"small"}],"employerNote":"1 sentence about employer diversity.","populationTrend":{"cagr5yr":"+X.X%","vsState":"text","drivers":"text"},"source":"sources"},' +
'"submarketContext":{"overallGrade":"B+","overallAssessment":"2 sentences.","comparables":[{"rank":1,"name":"submarket","crimeIndex":66,"label":"Safer","isSubject":false},{"rank":2,"name":"subject (Subject)","crimeIndex":82,"label":"Safer","isSubject":true},{"rank":3,"name":"submarket","crimeIndex":101,"label":"Similar","isSubject":false},{"rank":4,"name":"submarket","crimeIndex":112,"label":"Less Safe","isSubject":false}],"source":"sources"}}\n' +
'Replace ALL values. grade options: A B+ B B- C+ C D. 4-6 comparables with subject marked isSubject:true. crimeIndex: 100=metro avg, lower=safer. label: Safer/Similar/Less Safe.';
const out2 = await aiComplete(p2, { maxTokens: 700 });
const r2 = safeParseJSON(out2);
if (r2) {
const fresh = (dealsRef.current || []).find((x) => x.id === dealId);
const freshMR = (fresh && fresh.marketReview) || {};
const freshData = freshMR.data || baseData;
patch(dealId, { marketReview: { ...freshMR, data: {
...freshData,
economicDrivers: r2.economicDrivers || {},
submarketContext: r2.submarketContext || {},
}}});
}
} catch (e2) {
console.warn('[MarketReview] Phase 2 failed:', e2 && e2.message);
}
} catch (e) {
patch(dealId, { marketReview: { status: 'error', error: String(e && e.message ? e.message : e) } });
}
};
// ── IC Memo narrative ── Claude-written thesis / value drivers / risks for the memo.
const runMemoNarrative = async (dealId) => {
const d = (dealsRef.current || deals).find((x) => x.id === dealId);
if (!d) return null;
const m = window.computeMetrics ? window.computeMetrics(d) : {};
const uw = window.hasUWInputs && window.hasUWInputs(d) && window.computeUW ? window.computeUW(d) : null;
const mr = d.marketReview && d.marketReview.status === 'done' ? d.marketReview.data : null;
const ctx = [
'Property: ' + (d.name || '') + (d.market ? ' — ' + d.market : ''),
d.units ? 'Units: ' + d.units : '', d.vintage ? 'Year built: ' + d.vintage : '',
d.purchasePrice ? 'UW price: $' + Math.round(d.purchasePrice).toLocaleString() : '',
d.askPrice ? 'Ask: $' + Math.round(d.askPrice).toLocaleString() : '',
m.goingInCap ? 'Going-in cap: ' + (m.goingInCap * 100).toFixed(2) + '%' : '',
m.stabilizedCap ? 'Stabilized cap: ' + (m.stabilizedCap * 100).toFixed(2) + '%' : '',
uw ? 'Levered IRR: ' + (uw.irr != null ? (uw.irr * 100).toFixed(1) + '%' : 'n/a') + ', Equity multiple: ' + (uw.equityMultiple != null ? uw.equityMultiple.toFixed(2) + 'x' : 'n/a') : '',
uw ? 'In-place economic vacancy: ' + (uw.inPlaceEconVac * 100).toFixed(1) + '%, stabilized: ' + (uw.stabVac * 100).toFixed(1) + '%' : '',
mr ? 'Independent market read — grade ' + (mr.grade || '?') + '; ' + (mr.overallAssessment || '') : '',
d.notes ? 'Analyst notes: ' + String(d.notes).slice(0, 800) : '',
].filter(Boolean).join('\n');
const prompt = `You are an investment professional at Altus Equity drafting the narrative for a one-page Investment Committee memo on a multifamily acquisition. Be sharp, specific, and institutional — written for Partners deciding on tens of millions of dollars. No fluff.
DEAL CONTEXT:
${ctx}
Return ONLY valid JSON (no markdown) with this shape:
{
"thesis": "2-3 tight sentences: why acquire this asset now. Be specific — reference the market, the basis, or the value-add angle.",
"whyWeWin": "1-2 sentences: what specific edge does Altus have in winning and executing this deal — operator expertise, speed, relationships, or structure.",
"keyStrengths": ["3-4 IC-level value drivers — concrete and specific, e.g. 'Push in-place rents $180/mo to market via unit interior program'"],
"keyRisks": ["2-3 operational or market risks to monitor — each specific, not generic"],
"dealKillers": ["1-3 things that would cause us to pass or re-trade — be direct and blunt"],
"uwAssumptions": ["3-4 major underwriting assumptions being made (rent growth rate, stabilized vacancy, exit cap, hold period, etc.)"],
"recommendation": "one of: Pursue, Pursue with conditions, Pass"
}
Do not include any text outside the JSON object.`;
const out = await aiComplete(prompt);
const parsed = safeParseJSON(out);
if (!parsed) throw new Error('Could not parse the memo response.');
patch(dealId, { memo: { generatedAt: new Date().toISOString(), data: parsed } });
return parsed;
};
// Store an uploaded document in the vault (Supabase Storage + deal.documents).
// Used by the OM/T-12/Rent Roll parse handlers so parsed files are kept automatically.
const stashDoc = async (dealId, file, category) => {
const cloud = window.AltusCloud;
if (!cloud || !cloud.enabled || !cloud.uploadDoc) return;
try {
const meta = await cloud.uploadDoc(dealId, file);
const entry = { id: 'doc_' + Date.now().toString(36) + Math.random().toString(36).slice(2, 6), ...meta, category };
setDeals((ds) => ds.map((d) => d.id === dealId
? { ...d, documents: [...(Array.isArray(d.documents) ? d.documents : []), entry] }
: d));
} catch (e) { console.warn('[vault] stash failed:', e); }
};
const handleOMUpload = async (dealId, file) => {
setOMMap((m) => ({ ...m, [dealId]: { status: 'parsing', fileName: file.name } }));
stashDoc(dealId, file, 'OM');
try {
const { parsed, fullText } = await runOMParse(file);
setOMMap((m) => ({ ...m, [dealId]: { status: 'done', fileName: file.name, parsed } }));
setOpenId(dealId);
// Auto-create or update CRM contacts from EVERY broker contact parsed from the OM.
// Each contact is explicitly tagged with this deal's id so the CRM can show exactly
// which brokers are tied to which deals (who to reach out to).
const parsedContacts = Array.isArray(parsed.brokerContacts) ? parsed.brokerContacts
: Array.isArray(parsed.isrContacts) ? parsed.isrContacts : [];
// Keep the named listing team. Prefer people who have an email or phone (the real,
// contactable agents); but if the OM lists its listing team by name + title only,
// still keep them. Cap at 6 either way so a stray firm-directory page can't flood
// the CRM with dozens of un-contactable roster names.
const named = parsedContacts.filter((c) => c && c.name);
const withInfo = named.filter((c) => c.email || c.phone);
const people = (withInfo.length ? withInfo : named).slice(0, 6);
if (people.length) {
setContacts((cs) => {
let next = [...cs];
let firstId = null;
const withDeal = (arr) => Array.from(new Set([...(Array.isArray(arr) ? arr : []), dealId]));
people.forEach((pc, idx) => {
const existing = next.find((c) =>
pc.email && c.email && c.email.toLowerCase() === pc.email.toLowerCase() ||
pc.name && c.name && c.name.toLowerCase() === pc.name.toLowerCase()
);
if (existing) {
if (!firstId) firstId = existing.id;
next = next.map((c) => c.id === existing.id ? {
...c, lastActivity: window.ALTUS_TODAY,
title: c.title || pc.title || '',
firm: c.firm || parsed.brokerFirm || '',
dealIds: withDeal(c.dealIds)
} : c);
} else {
const newId = 'c-' + Date.now() + '-' + idx;
if (!firstId) firstId = newId;
next.push({
id: newId, name: pc.name || '', firm: parsed.brokerFirm || '',
title: pc.title || '', email: pc.email || '', phone: pc.phone || '',
markets: parsed.market || '', property: parsed.name || '',
dealIds: [dealId], notes: '',
dateAdded: window.ALTUS_TODAY, lastActivity: window.ALTUS_TODAY
});
}
});
if (firstId) setDeals((ds) => ds.map((d) => d.id === dealId ? { ...d, contactId: firstId } : d));
return next;
});
}
} catch (e) {
setOMMap((m) => ({ ...m, [dealId]: { status: 'error', fileName: file.name, error: String(e) } }));
}
};
// ── Rent Roll upload ── parse current rent, market rent, physical vacancy and loss
// to lease. Prefer the deterministic tabular parser; fall back to a model extraction
// of the same aggregates. All annual figures are computed here in JS.
const handleRentRollUpload = async (dealId, file) => {
setRRMap((m) => ({ ...m, [dealId]: { status: 'parsing', fileName: file.name } }));
stashDoc(dealId, file, 'Rent Roll');
try {
const fullText = await extractFileText(file);
let agg = parseRentRollTabular(fullText);
if (!agg) {
// model fallback — ask for the aggregate monthly figures only
const excerpt = rentRollExcerpt(fullText, 60000);
const prompt = `You are reading a multifamily RENT ROLL. Return ONLY a JSON object — no commentary — with these MONTHLY aggregate figures summed across every CURRENT resident unit (exclude future/applicant rows):
{
"totalUnits": 0,
"vacantUnits": 0,
"marketRentMonthlyAll": 0,
"inHouseRentMonthlyOccupied": 0,
"marketRentMonthlyVacant": 0
}
Definitions: marketRentMonthlyAll = sum of the MARKET / GROSS-POTENTIAL rent column over ALL units. marketRentMonthlyVacant = sum of MARKET rent for units whose status is VACANT (not pre-leased / not on notice). inHouseRentMonthlyOccupied = sum of the ACTUAL / LEASE / current rent column for OCCUPIED units only. A unit on Notice or in Eviction is OCCUPIED. Numbers only, no $ or commas.
RENT ROLL:
${excerpt}`;
const out = await aiComplete(prompt);
agg = safeParseJSON(out);
}
if (!agg || !agg.totalUnits) throw new Error('No unit rows could be read from this rent roll.');
const mAll = Number(agg.marketRentMonthlyAll) || 0;
const mVac = Number(agg.marketRentMonthlyVacant) || 0;
const mInH = Number(agg.inHouseRentMonthlyOccupied) || 0;
const occMarket = Math.max(0, mAll - mVac);
const parsed = {
totalUnits: agg.totalUnits,
vacantUnits: agg.vacantUnits || 0,
units: agg.totalUnits,
gprAnnual: Math.round(mAll * 12),
physVacLoss: Math.round(mVac * 12),
lossToLease: Math.round(Math.max(0, occMarket - mInH) * 12),
};
setRRMap((m) => ({ ...m, [dealId]: { status: 'done', fileName: file.name, parsed } }));
setOpenId(dealId);
} catch (e) {
setRRMap((m) => ({ ...m, [dealId]: { status: 'error', fileName: file.name, error: String(e) } }));
}
};
// ── T-12 upload ── pull delinquency (bad debt) and concessions, plus opex / EGI when
// present, from the trailing-12 income statement.
const handleT12Upload = async (dealId, file) => {
setT12Map((m) => ({ ...m, [dealId]: { status: 'parsing', fileName: file.name } }));
stashDoc(dealId, file, 'T-12');
try {
const fullText = await extractFileText(file);
const text = focusExcerpt(fullText, [
'bad debt', 'delinquen', 'collection loss', 'uncollect', 'write-off', 'write off',
'concession', 'rent concession', 'employee concession',
'gross potential', 'vacancy loss', 'loss to lease', 'effective gross income', 'total income', 'total revenue',
'net rental income', 'other income', 'rubs', 'utility reimburs',
'total operating expense', 'operating expense', 'net operating income',
], 36000);
const prompt = `You are parsing a multifamily T-12 (trailing-twelve-month) operating statement for Altus Equity. Return ONLY a valid JSON object — no commentary. Use null for any field not found. All figures must be the TRAILING-12 (annual) totals as raw numbers (no $ or commas). If the statement shows only a partial trailing period (T-3 or T-1), annualize it (T-3 × 4, T-1 × 12).
{
"badDebt": 0,
"concessions": 0,
"totalOpex": 0,
"effectiveGrossIncome": 0,
"otherIncome": 0
}
rules for badDebt — the trailing bad debt / delinquency / collection-loss / uncollectible-rent / write-off line, as a POSITIVE number (the loss amount). Sum multiple such lines if shown separately. null if none.
rules for concessions — the trailing rent-concessions / concessions-and-discounts / employee-unit-concession line, as a POSITIVE number. Sum multiple concession lines. null if none.
rules for totalOpex — TOTAL OPERATING EXPENSES. CRITICAL: Property Taxes AND Insurance MUST be included — if they are listed separately below a "controllable" subtotal, ADD them on top. NEVER include debt service, mortgage interest, depreciation, amortization, capital expenditures, or reserves. null if not shown.
rules for effectiveGrossIncome — the Effective Gross Income / Total Income / Total Revenue line (income after vacancy & loss, plus other income). null if not shown.
rules for otherIncome — total other income (RUBS / utility reimbursement, fees, etc.). null if not shown.
T-12 text:
${text}`;
const out = await aiComplete(prompt);
const parsed = safeParseJSON(out) || {};
setT12Map((m) => ({ ...m, [dealId]: { status: 'done', fileName: file.name, parsed } }));
setOpenId(dealId);
} catch (e) {
setT12Map((m) => ({ ...m, [dealId]: { status: 'error', fileName: file.name, error: String(e) } }));
}
};
const doSignIn = async (email, password) => {
setAuthBusy(true);
try { await cloud.signIn(email, password); }
finally { setAuthBusy(false); }
};
// ---- Login gate (only when cloud + REQUIRE_LOGIN are on) ----
if (cloud.requireLogin && session === undefined) return ;
if (cloud.requireLogin && !session) return ;
return (