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| """Price table and cost derivation. | |
| Claude rows are Anthropic first-party list prices (cached model table, 2026-10-06): input and | |
| output as listed, cache read as listed (0.1x input unless noted), 5-minute cache write 1.25x | |
| input. Haiku 5.5 matches Claude Code's own `total_cost_usd` (tests/test_prices.py). The Codex row | |
| is still a placeholder. Override any row with a JSON file whose path is in FLOCK_PRICES: | |
| {"claude-opus-5-5": {"input": 15, "output": 75, "cache_read": 1.5, "cache_write": 18.75}} | |
| All prices are USD per 1M tokens. Reasoning tokens are assumed to be included in the | |
| output count the harness reports, so they are not billed separately. | |
| """ | |
| from __future__ import annotations | |
| import json | |
| import os | |
| from dataclasses import dataclass | |
| from functools import lru_cache | |
| from flock.models import TokenUsage | |
| class Price: | |
| input: float | |
| output: float | |
| cache_read: float | |
| cache_write: float | |
| DEFAULT_MODEL = "default" | |
| # See module docstring. | |
| PRICES: dict[str, Price] = { | |
| "claude-opus-5-5": Price(4.0, 20.0, 0.2, 5.0), # cache read listed at $0.20 | |
| "claude-sonnet-5-5": Price(2.0, 10.0, 0.2, 2.5), | |
| "claude-haiku-5-5": Price(0.10, 0.50, 0.01, 0.125), | |
| "gpt-5.5-codex": Price(1.25, 10.0, 0.125, 0.0), | |
| DEFAULT_MODEL: Price(15.0, 75.0, 1.5, 18.75), # unknown models priced high, not free | |
| } | |
| def price_table() -> dict[str, Price]: | |
| table = dict(PRICES) | |
| path = os.environ.get("FLOCK_PRICES") | |
| if path: | |
| with open(path, encoding="utf-8") as f: | |
| for model, p in json.load(f).items(): | |
| table[model] = Price(**p) | |
| return table | |
| def price_for(model: str, table: dict[str, Price] | None = None) -> Price: | |
| """Exact match, else the longest table key that prefixes the model id, else default.""" | |
| table = table or price_table() | |
| if model in table: | |
| return table[model] | |
| prefixes = [k for k in table if k != DEFAULT_MODEL and model.startswith(k)] | |
| return table[max(prefixes, key=len)] if prefixes else table[DEFAULT_MODEL] | |
| def cost_usd(tokens: dict[str, TokenUsage], table: dict[str, Price] | None = None) -> float: | |
| total = 0.0 | |
| for model, u in tokens.items(): | |
| p = price_for(model, table) | |
| total += ( | |
| u.input * p.input | |
| + u.output * p.output | |
| + u.cache_read * p.cache_read | |
| + u.cache_write * p.cache_write | |
| ) / 1_000_000 | |
| return round(total, 6) | |