Economic Indicator → Focus Group

import os, requests, time

AV_KEY = os.environ["ALPHA_VANTAGE_KEY"]
AV_BASE = "https://www.alphavantage.co/query"
MV = os.environ["MAVERA_API_KEY"]
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

# 1. Fetch economic indicators
indicators = {}
for func, label in [("REAL_GDP", "GDP"), ("CPI", "CPI"), ("UNEMPLOYMENT", "Unemployment")]:
    r = requests.get(AV_BASE, params={"function": func, "interval": "quarterly" if func == "REAL_GDP" else "monthly", "apikey": AV_KEY})
    r.raise_for_status()
    data = r.json().get("data", [])
    recent = data[:4]
    indicators[label] = {
        "latest": recent[0] if recent else {},
        "trend": [{"date": d.get("date",""), "value": d.get("value","")} for d in recent],
    }
    latest = recent[0] if recent else {}
    print(f"{label}: {latest.get('value','N/A')} ({latest.get('date','N/A')})")
    time.sleep(15)

# 2. Build economic snapshot
snapshot = "\n".join(
    f"**{label}**: {d['latest'].get('value','N/A')} (as of {d['latest'].get('date','N/A')})\n"
    f"  Trend: {' → '.join(t['value'] for t in reversed(d['trend']))}"
    for label, d in indicators.items()
)

# 3. Create demographic personas
DEMOGRAPHICS = [
    {"name": "Retiree on Fixed Income", "desc": "Age 68. Pension + Social Security. $52K/year. Inflation directly erodes purchasing power. Risk-averse. Watches news daily."},
    {"name": "Recent College Graduate", "desc": "Age 23. First job, $55K salary. $38K student debt. Optimistic but financially stressed. Rents. No investments yet."},
    {"name": "Small Business Owner", "desc": "Age 42. Restaurant owner, 12 employees. Revenue $1.2M. Margins thin (8%). Labor costs and food costs top concerns."},
    {"name": "Dual-Income Suburban Family", "desc": "Ages 36/38. Combined $180K. Mortgage, two kids, saving for college. Feel upper-middle but stretched. Inflation hits grocery and childcare."},
]
persona_ids = []
for demo in DEMOGRAPHICS:
    p = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
        "name": f"Econ: {demo['name']}", "description": demo["desc"],
    }).json()
    persona_ids.append(p["id"])
    time.sleep(0.3)

# 4. Focus Group
fg = requests.post(f"{MV_BASE}/focus-groups", headers=MV_H, json={
    "name": "Economic Indicator Reactions",
    "persona_ids": persona_ids,
    "questions": [
        f"Here are the latest economic numbers:\n{snapshot}\n\nHow do these numbers make you feel about your financial situation?",
        "Based on these numbers, will you spend more, less, or the same in the next 3 months? On what?",
        "If a financial services company approached you right now, what message would resonate?",
        "What's the one economic indicator you personally watch most? Why?",
    ],
    "responses_per_persona": 2,
}).json()

for _ in range(25):
    time.sleep(5)
    data = requests.get(f"{MV_BASE}/focus-groups/{fg['id']}", headers=MV_H).json()
    if data.get("status") == "completed":
        break

# 5. Print responses
print(f"\n{'='*60}\nECONOMIC FOCUS GROUP RESULTS\n{'='*60}")
print(f"Indicators: {snapshot}\n")
for resp in data.get("responses", []):
    pid = resp.get("persona_id", "")
    idx = persona_ids.index(pid) if pid in persona_ids else -1
    name = DEMOGRAPHICS[idx]["name"] if 0 <= idx < len(DEMOGRAPHICS) else "Unknown"
    print(f"[{name}] Q: {resp.get('question','')[:80]}")
    print(f"  A: {resp.get('answer','')[:350]}\n")

const AV_KEY = process.env.ALPHA_VANTAGE_KEY;
const AV_BASE = "https://www.alphavantage.co/query";
const MV = process.env.MAVERA_API_KEY;
const MV_BASE = "https://app.mavera.io/api/v1";
const MV_H = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

// 1. Economic indicators
const indicators = {};
for (const [func, label, interval] of [
  ["REAL_GDP", "GDP", "quarterly"], ["CPI", "CPI", "monthly"], ["UNEMPLOYMENT", "Unemployment", "monthly"]
]) {
  const r = await fetch(`${AV_BASE}?function=${func}&interval=${interval}&apikey=${AV_KEY}`);
  const data = (await r.json()).data || [];
  const recent = data.slice(0, 4);
  indicators[label] = { latest: recent[0] || {}, trend: recent.map(d => ({ date: d.date, value: d.value })) };
  console.log(`${label}: ${recent[0]?.value || "N/A"} (${recent[0]?.date || "N/A"})`);
  await new Promise(r => setTimeout(r, 15000));
}

// 2. Snapshot
const snapshot = Object.entries(indicators).map(([label, d]) =>
  `**${label}**: ${d.latest.value||"N/A"} (${d.latest.date||"N/A"})\n  Trend: ${d.trend.map(t=>t.value).reverse().join(" → ")}`).join("\n");

// 3. Personas
const DEMOGRAPHICS = [
  { name: "Retiree on Fixed Income", desc: "Age 68. Pension + SS. $52K. Inflation erodes purchasing power." },
  { name: "Recent Graduate", desc: "Age 23. $55K salary. $38K debt. Optimistic but stressed. Rents." },
  { name: "Small Business Owner", desc: "Age 42. Restaurant, 12 employees. $1.2M revenue, 8% margins." },
  { name: "Dual-Income Family", desc: "Ages 36/38. $180K combined. Mortgage, 2 kids. Stretched." },
];
const personaIds = [];
for (const demo of DEMOGRAPHICS) {
  const p = await fetch(`${MV_BASE}/personas`, { method: "POST", headers: MV_H,
    body: JSON.stringify({ name: `Econ: ${demo.name}`, description: demo.desc }),
  }).then(r => r.json());
  personaIds.push(p.id);
  await new Promise(r => setTimeout(r, 300));
}

// 4. Focus Group
const fg = await fetch(`${MV_BASE}/focus-groups`, { method: "POST", headers: MV_H,
  body: JSON.stringify({ name: "Economic Indicator Reactions", persona_ids: personaIds,
    questions: [
      `Latest numbers:\n${snapshot}\n\nHow do these affect your financial situation?`,
      "Spend more, less, or same next 3 months? On what?",
      "What message from a financial company would resonate right now?",
      "Which indicator do you watch most? Why?",
    ], responses_per_persona: 2 }),
}).then(r => r.json());

let data;
for (let i = 0; i < 25; i++) {
  await new Promise(r => setTimeout(r, 5000));
  data = await fetch(`${MV_BASE}/focus-groups/${fg.id}`, { headers: MV_H }).then(r => r.json());
  if (data.status === "completed") break;
}

console.log(`\n${"=".repeat(60)}\nECONOMIC FOCUS GROUP RESULTS`);
for (const resp of data.responses || []) {
  const idx = personaIds.indexOf(resp.persona_id);
  const name = idx >= 0 ? DEMOGRAPHICS[idx].name : "Unknown";
  console.log(`[${name}] Q: ${(resp.question||"").slice(0,80)}`);
  console.log(`  A: ${(resp.answer||"").slice(0,350)}\n`);
}