Multi Truck Group — #1 Local Pack
in 11 Canadian Cities

# WebCoreLab — Multi Truck Review Generation Pipeline
import anthropic
import redis
from twilio.rest import Client as TwilioClient
from datetime import datetime, timedelta

GMB_REVIEW_URL = "https://g.page/r/CXxxx/review"
TWILIO_NUMBER = "+16475550199"

class ReviewSystem:
    def __init__(self):
        self.claude = anthropic.AsyncAnthropic()
        self.twilio = TwilioClient(SID, TOKEN)
        self.queue = redis.Redis(host='localhost', port=6379)

    async def send_review_request(self, delivery: dict):
        # Personalised SMS 24h after delivery.completed webhook
        msg = await self.claude.messages.create(
            model="claude-haiku-4-5",
            max_tokens=200,
            messages=[{"role": "user",
                "content": f"Write a friendly SMS asking for a Google review. "
                           f"Driver: {delivery['driver']}. "
                           f"Route: {delivery['origin']} → {delivery['dest']}. "
                           f"Under 160 chars. Conversational, not corporate."
            }]
        )
        self.twilio.messages.create(
            body=msg.content[0].text + f"\n{GMB_REVIEW_URL}",
            from_=TWILIO_NUMBER,
            to=delivery['customer_phone']
        )

    async def respond_to_review(self, review: dict):
        # Auto-draft response within 2h, human approves
        resp = await self.claude.messages.create(
            model="claude-sonnet-4-5",
            max_tokens=220,
            messages=[{"role": "user",
                "content": f"Review: \"{review['text']}\" "
                           f"Rating: {review['rating']}/5. "
                           f"Driver: {review.get('driver','N/A')}. "
                           f"Write a warm, specific, professional reply. "
                           f"If rating < 4, offer a resolution path."
            }]
        )
        return resp.content[0].text

# Q3 2022 baseline vs Q4 2022 after deploy:
# Reviews: 47 → 141 (+94 inbound at 4.7★ avg)
# Aggregate rating: 3.2★ → 4.8★
# Response rate: 12% → 100% within SLA
# Local Pack presence: 0/11 cities → TOP-3 in 11/11