import os, requests, time
TW_SID = os.environ["TWILIO_ACCOUNT_SID"]
TW_TOKEN = os.environ["TWILIO_AUTH_TOKEN"]
TW_AUTH = (TW_SID, TW_TOKEN)
TW_BASE = f"https://api.twilio.com/2010-04-01/Accounts/{TW_SID}"
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 WhatsApp messages
r = requests.get(f"{TW_BASE}/Messages.json", auth=TW_AUTH, params={
"PageSize": 200, "To": "whatsapp:+14155238886",
})
r.raise_for_status()
all_msgs = r.json().get("messages", [])
wa_inbound = [m for m in all_msgs if m.get("direction") == "inbound"
and "whatsapp:" in m.get("from", "")]
wa_outbound = [m for m in all_msgs if m.get("direction") == "outbound-api"]
print(f"WhatsApp input: {len(wa_inbound)} inbound, {len(wa_outbound)} outbound")
# 2. Build conversation corpus
inbound_corpus = "\n".join(
f"- [{m.get('date_sent','')[:10]}] {m.get('body','')[:300]}"
for m in wa_inbound[:80]
)
# 3. Theme extraction via Mave
themes = requests.post(f"{MV_BASE}/mave/chat", headers=MV_H, json={
"message": f"Analyze {len(wa_inbound)} inbound WhatsApp business messages.\n\n"
f"MESSAGES:\n{inbound_corpus[:6000]}\n\n"
"Extract:\n"
"1. Top 5 conversation themes (with counts)\n"
"2. Common customer language patterns (phrases, tone, formality)\n"
"3. Sentiment distribution (positive/negative/neutral %)\n"
"4. Time-of-day patterns (if dates suggest)\n"
"5. Unmet needs (what customers ask for that we don't provide)"
}).json()
themes_text = themes.get("content", "")
print(f"\nThemes:\n{themes_text[:1000]}")
# 4. Create customer personas based on message patterns
CUSTOMER_TYPES = [
{"name": "Urgent Buyer", "desc": "Sends short, direct messages. Wants immediate answers. Price-focused. Uses WhatsApp because it's faster than email. Expects quick responses."},
{"name": "Relationship Builder", "desc": "Sends longer messages with context. Asks follow-up questions. Wants to feel valued. Uses emojis and greetings. Loyal when treated well."},
{"name": "Comparison Shopper", "desc": "Asks detailed product questions. Mentions competitors. Wants specs, pricing breakdowns, and guarantees. Analytical. Makes decisions slowly."},
]
persona_ids = []
for ct in CUSTOMER_TYPES:
p = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
"name": f"WhatsApp: {ct['name']}",
"description": ct["desc"],
}).json()
persona_ids.append({"id": p["id"], "name": ct["name"]})
time.sleep(0.3)
# 5. Speak sessions for persona insights
for persona in persona_ids:
speak = requests.post(f"{MV_BASE}/speak", headers=MV_H, json={
"persona_id": persona["id"],
"input": [
{"role": "system", "content": f"You are a {persona['name']} who communicates with businesses via WhatsApp. Based on these real customer conversation themes, share your perspective."},
{"role": "user", "content": f"Here's what customers are saying on WhatsApp:\n\n{themes_text[:1500]}\n\nAs a {persona['name']}, what resonates with you? What would make you buy? What turns you off?"},
{"role": "user", "content": "How should businesses message you on WhatsApp to earn your trust and get a response?"},
{"role": "user", "content": "What's the one thing most businesses get wrong when messaging you on WhatsApp?"},
],
"mode": "interview",
}).json()
print(f"\n{'='*60}\nPERSONA INSIGHT: {persona['name']}\n{'='*60}")
for ex in speak.get("exchanges", speak.get("messages", [])):
if ex.get("role") == "user":
print(f"\n Q: {ex['content'][:100]}")
elif ex.get("role") == "assistant":
print(f" A: {ex['content'][:400]}")
time.sleep(0.3)
# 6. Generate optimized WhatsApp templates
templates = requests.post(f"{MV_BASE}/generations", headers=MV_H, json={
"prompt": f"Based on these WhatsApp persona insights:\n\n{themes_text[:2000]}\n\n"
"Generate 5 optimized WhatsApp Business message templates:\n\n"
"1. Welcome / First Contact\n"
"2. Product Inquiry Response\n"
"3. Price Quote\n"
"4. Follow-up After No Response\n"
"5. Post-Purchase Check-in\n\n"
"Each template: max 160 chars for first message, conversational tone, "
"include a clear next step. Avoid sounding automated. Use WhatsApp formatting "
"(bold: *text*, italic: _text_).",
}).json()
print(f"\n{'='*60}\nOPTIMIZED WHATSAPP TEMPLATES\n{'='*60}")
print(templates.get("output", templates.get("content", ""))[:1500])
