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Author SHA1 Message Date
Daniel Han
2201fd687b
Studio: per-session cost calculator + /api/providers/pricing endpoint (#5690)
* Studio: per-session cost calculator + /api/providers/pricing endpoint

Neither the Anthropic Messages API nor the OpenAI Responses API
reports a `cost` field on the response. Both expose detailed token
counts (input, output, cache hits, server-tool invocations); pricing
multipliers live in the provider docs. The frontend's "cost so far"
display was impossible without scraping the server log.

Land the math + a snapshot endpoint so the cost calculator can run
client-side from the existing usage chunk plumbing. The actual UI
hookup belongs in a frontend follow-up (and is gated on PR #5670's
usage-chunk emission landing so the frontend sees the usage block
in the first place).

Changes:

- New `core/inference/pricing.py` with:
  - Per-MTok base pricing tables for every active Anthropic and
    gpt-5.x family member. Dated snapshots inherit the canonical-id
    price via prefix match so future snapshots cost the same as the
    canonical id until pricing changes.
  - Shared multipliers for Anthropic cache writes (5m: 1.25x, 1h: 2x)
    and reads (0.1x); OpenAI cache reads (0.1x); Anthropic server
    tool surcharges ($10 / 1k web_search, $0.05 / hour code_exec
    beyond the 50-hour daily free tier).
  - `calculate_cost(provider, model, usage)` returns a per-turn USD
    breakdown plus billable token counts, with priced=False for
    unknown models so the UI can still render token counts.
  - `pricing_snapshot()` returns the whole table for the frontend
    so it doesn't re-implement the multipliers.
- New `GET /api/providers/pricing` returning the snapshot, scoped
  behind the existing auth dependency.
- New `backend/tests/test_pricing.py` with 12 cases pinning the
  math against documented values: base input/output multiplication,
  5m / 1h / read multipliers, default-to-5m fallback when the
  breakdown is absent, web_search per-1k pricing, code_execution
  per-hour pricing, dated-snapshot fallback, OpenAI cache-read
  discount accounting (cached tokens subtracted from full-price
  bucket and re-billed at 0.1x), unknown model graceful-degrade,
  and the snapshot endpoint shape.

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* Studio: verified OpenAI pricing + fix billable input double-count

Address the cost-calculator review:

- OpenAI prices were 2-6x under the actual published rates.
  Cross-checked the live developers.openai.com/api/docs/pricing page
  and replaced every entry. gpt-5.5 is 5/30, gpt-5.5-pro is 30/180,
  gpt-5.4 is 2.5/15, gpt-5.4-mini 0.75/4.5, gpt-5.4-nano 0.20/1.25,
  gpt-5.3-codex 1.75/14. Added chat-latest alias to the canonical
  chat-snapshot rate. Dropped o3 / o4 / gpt-4.5 rows that are no
  longer listed on the page; calculator returns priced=False instead
  of silently billing at zero.

- billable_input_tokens was double-counting cached tokens for
  OpenAI. Anthropic excludes cache_* buckets from input_tokens so
  we add them; OpenAI folds cache_read_input_tokens into
  input_tokens already, so the tooltip read 1.8M for a 1.0M bill.
  Branched the math by provider and added a regression test.

Sourcing notes in the module docstring updated.

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* Address review: canonical 4.5 ids, long-context tier, OpenAI tool fees

Three Codex P1 follow-ups on the cost calculator:

1. Canonical Anthropic 4.5 ids missing from ANTHROPIC_PRICING.
   claude-opus-4-5 / claude-sonnet-4-5 / claude-haiku-4-5 (no date
   suffix) are the ids used by backend defaults
   (PROVIDER_REGISTRY['anthropic'].default_models), but the table
   only had the dated forms. _lookup's prefix fallback doesn't help
   because the canonical id is SHORTER than the dated key, so
   str.startswith goes the wrong way and the calculator returned
   priced=False + zero cost. Added the canonical aliases for
   opus-4-5, sonnet-4-5, haiku-4-5, and opus-4-1.

2. OpenAI long-context tier. gpt-5.5 and gpt-5.4 cross over at
   272k input tokens to a 2x input / 1.5x output rate (gpt-5.5:
   $5/$30 -> $10/$45; gpt-5.4: $2.50/$15 -> $5/$22.50). Turns past
   the threshold were systematically undercounted at headline
   rates. Added long_context_threshold / long_context_input_per_mtok /
   long_context_output_per_mtok columns and a tier-selection step
   in calculate_cost; model_priced gains a "(long-context >272000)"
   suffix when the higher tier applies so the tooltip can show
   which rate was used. gpt-5.5-pro / gpt-5.4-pro / mini / nano /
   codex have no published long-context tier today, so they keep a
   single rate.

3. OpenAI server-tool surcharges. web_search is $10/1000 calls and
   the hosted shell container is $0.03 per 20-minute session on the
   default 1g tier (~$0.09/hr). server_tools_usd was previously
   stuck at 0.0 for OpenAI even when web_search and shell tools
   fired, so sessions with tool use understated cost. Added
   OPENAI_WEB_SEARCH_USD_PER_1K and OPENAI_CONTAINER_USD_PER_HOUR
   constants plus a parallel of the Anthropic surcharge block that
   reads counts from usage["openai_tool_use"]. The SSE translator
   wires the counts in a follow-up commit; the calculator is now
   ready for them. pricing_snapshot also exposes both constants so
   the frontend tooltip can render the per-call rate.

Existing tests updated to stay in the short-context tier where they
were testing base rates; new tests pin canonical 4.5 lookups,
long-context crossover on gpt-5.5/gpt-5.4, the absence of crossover
on mini/nano/codex, and OpenAI tool surcharges (web_search,
container hours, combined total).

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2026-05-22 06:03:43 -07:00