Voice of Customer → Brand Voice

import os, requests, time

DG = os.environ["DEEPGRAM_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

INTERVIEWS = [{"file": "interviews/sarah-vp-marketing.wav", "name": "Sarah, VP Marketing"},
    {"file": "interviews/marcus-ops-lead.wav", "name": "Marcus, Ops Lead"},
    {"file": "interviews/priya-cmo.wav", "name": "Priya, CMO"},
    {"file": "interviews/james-founder.wav", "name": "James, Founder"},
    {"file": "interviews/elena-director.wav", "name": "Elena, Director"}]
params = {"model": "nova-3", "smart_format": "true", "punctuate": "true",
    "diarize": "true", "utterances": "true", "paragraphs": "true", "language": "en"}

all_text = []
for iv in INTERVIEWS:
    with open(iv["file"], "rb") as f:
        resp = requests.post("https://api.deepgram.com/v1/listen", params=params,
            headers={"Authorization": f"Token {DG}", "Content-Type": "audio/wav"},
            data=f, timeout=120)
    resp.raise_for_status()
    r = resp.json()
    utts = r.get("results",{}).get("utterances",[])
    dur = r.get("metadata",{}).get("duration",0)
    spk_wc = {}
    for u in utts:
        sp = u.get("speaker",0); spk_wc[sp] = spk_wc.get(sp,0) + len(u.get("transcript","").split())
    cust_sp = max(spk_wc, key=spk_wc.get) if spk_wc else 0
    text = " ".join(u["transcript"] for u in utts if u.get("speaker") == cust_sp)
    all_text.append({"name": iv["name"], "min": round(dur/60,1), "words": len(text.split()), "text": text})
    print(f"{iv['name']} — {round(dur/60,1)}min | {len(text.split())} customer words")
    time.sleep(2)

total = sum(c["words"] for c in all_text)
corpus = "\n\n".join(f"### {c['name']} ({c['min']}min, {c['words']} words)\n{c['text'][:2000]}"
    for c in all_text)

time.sleep(1)
voice = requests.post(f"{MV_BASE}/mave/chat", headers=MV_H, json={
    "message": f"Voice pattern analyst. {len(all_text)} customer interviews.\n\n{corpus[:10000]}\n\n"
        "Extract consistent patterns:\n"
        "1. **VOCABULARY DNA** — Words/phrases used by 3+ customers\n"
        "2. **SENTENCE PATTERNS** — How they structure descriptions\n"
        "3. **METAPHOR INVENTORY** — Analogies they reach for\n"
        "4. **EMOTIONAL REGISTER** — Where animated, where matter-of-fact\n"
        "5. **JARGON USAGE** — Industry terms used vs. avoided\n"
        "6. **STORYTELLING ARC** — How they narrate before/after\n"
        "7. **VOICE SUMMARY** — 200-word brand voice description\n"
}).json()

bv = requests.post(f"{MV_BASE}/brand-voices", headers=MV_H, json={
    "name": "Customer Voice — Interviews Q1 2026",
    "description": f"From {len(INTERVIEWS)} interviews ({total:,} words). "
        f"Customers: {', '.join(c['name'] for c in all_text)}.\n\n"
        f"{voice.get('content','')[:4000]}",
}).json()
print(f"\nBrand Voice created: {bv.get('id')}")
print(voice.get("content","")[:3000])

import fs from "fs";
const DG = process.env.DEEPGRAM_API_KEY, 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" };

const INTERVIEWS = [
  { file: "interviews/sarah-vp-marketing.wav", name: "Sarah, VP Marketing" },
  { file: "interviews/marcus-ops-lead.wav", name: "Marcus, Ops Lead" },
  { file: "interviews/priya-cmo.wav", name: "Priya, CMO" },
  { file: "interviews/james-founder.wav", name: "James, Founder" },
  { file: "interviews/elena-director.wav", name: "Elena, Director" }];
const params = new URLSearchParams({ model: "nova-3", smart_format: "true", punctuate: "true",
  diarize: "true", utterances: "true", paragraphs: "true", language: "en" });

const allText = [];
for (const iv of INTERVIEWS) {
  const r = await fetch(`https://api.deepgram.com/v1/listen?${params}`, { method: "POST",
    headers: { Authorization: `Token ${DG}`, "Content-Type": "audio/wav" },
    body: fs.readFileSync(iv.file) }).then(r => r.json());
  const utts = r.results?.utterances || [];
  const spkW = {};
  for (const u of utts) spkW[u.speaker??0] = (spkW[u.speaker??0]||0) + (u.transcript||"").split(/\s+/).length;
  const custSp = Object.entries(spkW).sort((a,b) => b[1]-a[1])[0]?.[0];
  const text = utts.filter(u => String(u.speaker)===custSp).map(u => u.transcript||"").join(" ");
  allText.push({ name: iv.name, min: Math.round((r.metadata?.duration||0)/60*10)/10,
    words: text.split(/\s+/).length, text });
  await new Promise(r => setTimeout(r, 2000));
}

const total = allText.reduce((s,c) => s+c.words, 0);
let corpus = allText.map(c => `### ${c.name} (${c.min}min)\n${c.text.slice(0,2000)}`).join("\n\n");
const voice = await fetch(`${MV_BASE}/mave/chat`, { method: "POST", headers: MV_H,
  body: JSON.stringify({ message: `Voice analyst. ${allText.length} interviews.\n\n${corpus.slice(0,10000)}\n\n`
    + "Extract: VOCABULARY DNA, SENTENCE PATTERNS, METAPHOR INVENTORY, "
    + "EMOTIONAL REGISTER, JARGON USAGE, STORYTELLING ARC, VOICE SUMMARY (200 words)" }),
}).then(r => r.json());

const bv = await fetch(`${MV_BASE}/brand-voices`, { method: "POST", headers: MV_H,
  body: JSON.stringify({ name: "Customer Voice — Interviews Q1 2026",
    description: `From ${INTERVIEWS.length} interviews (${total.toLocaleString()} words).\n\n`
      + (voice.content||"").slice(0,4000) }),
}).then(r => r.json());
console.log(`Brand Voice: ${bv.id}\n\n${(voice.content||"").slice(0,3000)}`);