promptdojo_
Checkpoint

One last thing before we move on. Same surface as a write step — but the lesson doesn't complete until this passes.

Final drill. Synthesize the model picker AND its cost into one function: cost_aware_routing(tasks).

Takes a list of task dicts (same shape as step 7: kind, volume_per_day, latency_ms_max, criticality).

Returns a dict:

  • routes: dict mapping each task's kind to the chosen model ("haiku", "sonnet", or "opus").
  • total_cost: float, total estimated daily cost across all tasks, rounded to 2 decimal places.

Use the same routing rules from step 7:

  1. volume_per_day >= 10000 → "haiku", unless criticality == "high" → "sonnet".
  2. volume_per_day < 100 AND criticality == "high" → "opus".
  3. Default → "sonnet".

Cost math: assume each call averages 1000 tokens. Blended prices per million tokens:

  • haiku: $3.00
  • sonnet: $9.00
  • opus: $15.00

Daily cost for one task = volume_per_day * 1000 * (rate / 1_000_000), which simplifies to volume_per_day * rate / 1000.

Five tasks run. Expected output:

ticket_tagger     -> haiku
support_summary   -> sonnet
contract_review   -> opus
fraud_alert       -> sonnet
architect_review  -> opus
total daily cost: $375.09

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