Is this a simple classification, routing, or yes/no decision?
  YES → Use Haiku
  NO ↓

Does this task require deep multi-step reasoning or extended thinking?
  YES → Use Opus
  NO ↓

Is this high-stakes? (customer-facing, security, legal, or visible to many people)
  YES → Run with Sonnet first. Compare quality with Opus on 5 samples.
         If Opus is measurably better → Use Opus
         If quality is similar → Stay with Sonnet
  NO ↓

Use Sonnet (default for everything else)

# shopmate/router.py -- Right model for each ShopMate task
from enum import Enum

class Task(Enum):
    CLASSIFY    = "classify"    # sentiment check, category label
    WRITE       = "write"       # product descriptions, email replies
    CAMPAIGN    = "campaign"    # seasonal campaign copy, Maya reviews

# Model choice + max tokens per task
ROUTING = {
    Task.CLASSIFY: ("claude-haiku-4-5-20251001",  30),   # fastest, cheapest
    Task.WRITE:    ("claude-haiku-4-5-20251001",  250),  # good quality, low cost
    Task.CAMPAIGN: ("claude-sonnet-4-6",          800),  # best quality for Maya
}

# Cost per 1 million tokens (input / output) — verify at anthropic.com/pricing
PRICES = {
    "claude-haiku-4-5-20251001": (0.80,  4.00),   # $0.80 input / $4.00 output per 1M tokens
    "claude-sonnet-4-6":        (3.00, 15.00),  # $3.00 input / $15.00 output per 1M tokens
}

def route(task: Task) -> tuple[str, int]:
    return ROUTING[task]

def monthly_cost_estimate() -> None:
    volumes = {Task.CLASSIFY: 2000, Task.WRITE: 500, Task.CAMPAIGN: 8}
    total = 0
    print(f"{'Task':<15} {'Model':<35} {'Vol':>5} {'Cost':>8}")
    print("-" * 68)
    for task, vol in volumes.items():
        model, max_out = ROUTING[task]
        cin, cout = PRICES[model]
        cost = ((400/1e6)*cin + (max_out/1e6)*cout) * vol
        total += cost
        print(f"{task.value:<15} {model:<35} {vol:>5} ${cost:>7.2f}")
    print(f"
Estimated monthly total: ${total:.2f}")

monthly_cost_estimate()

# shopmate/dynamic_router.py -- Haiku classifies, then routes to the right model
import anthropic
client = anthropic.Anthropic()

def classify_complexity(user_message: str) -> str:
    """Use Haiku to classify whether a request needs Haiku, Sonnet, or Opus."""
    resp = client.messages.create(
        model="claude-haiku-4-5-20251001", max_tokens=10,
        system="""Classify the complexity of this user request.
Reply with ONLY one word: haiku, sonnet, or opus.
- haiku: simple lookup, yes/no, classification
- sonnet: writing, coding, analysis, most tasks
- opus: complex reasoning, architecture, security, multi-step logic""",
        messages=[{"role":"user", "content": user_message}]
    )
    return resp.content[0].text.strip().lower()

MODEL_MAP = {
    "haiku":  "claude-haiku-4-5-20251001",
    "sonnet": "claude-sonnet-4-6",
    "opus":   "claude-opus-4-6",
}

def smart_route(user_message: str) -> str:
    """Route a message to the appropriate model based on complexity."""
    complexity = classify_complexity(user_message)
    model = MODEL_MAP.get(complexity, "claude-sonnet-4-6")  # default to Sonnet
    print(f"Routing to {model} (classified as: {complexity})")
    resp = client.messages.create(
        model=model, max_tokens=1000,
        messages=[{"role":"user", "content": user_message}]
    )
    return resp.content[0].text

# The Haiku classification call costs fractions of a cent
# but saves dollars when it routes simple requests away from Opus