Address copilot-pull-request-reviewer feedback on #2157:
- billing_service_test.go: extend TestGetFallbackPricing_FamilyMatching
with optional expectedOutput / expectedCacheRead fields and assert
full Input/Output/CacheRead pricing for all 4 DeepSeek cases
(v4-pro, v4-flash, deepseek-chat→flash, deepseek-reasoner→flash),
preventing silent regression to 0 output/cache cost.
- billing_service.go: rewrite the DeepSeek block comment to explicitly
describe its scope (V4 Pro/Flash + chat/reasoner aliases, no
unknown-deepseek fallback) and tighten the OpenAI comment to make
it unambiguous that it only describes the OpenAI/Codex branch
immediately below it.
When channel pricing is configured, image output token price now
correctly overrides all other sources (LiteLLM, group config).
Add ImageOutputPriceExplicit flag to distinguish intentional zero
price from missing price, preventing fallback to output price.
Affects Gemini, OpenAI inline image gen, and Images API paths.
Follow-up to #2816 (already merged): the same long-context pricing
exemption that affected cache_read also applies to all three
cache_creation price fields (standard, 5m ephemeral, 1h ephemeral).
computeCacheCreationCost reads these prices directly from pricing and
never sees the LongContextInputMultiplier that computeTokenBreakdown
applies to inputPrice / outputPrice / cacheReadPrice.
For GPT-5.4 / 5.5 above the 272k threshold, this causes the cache_write
portion of long sessions to be billed at roughly half what it should
be (default multiplier 2.0). Cache writes are conceptually input-side
operations and should share the same long-context treatment as input /
cache_read.
This patch threads an explicit multiplier into computeCacheCreationCost
so the function can be unit-tested in isolation and matches the existing
pattern used for cache_read. computeTokenBreakdown captures the long
context decision once and passes LongContextInputMultiplier when it
applies, 1.0 otherwise.
Adds three regression tests mirroring the #2816 cache_read tests:
- positive: long-context triggered -> cache_creation scaled by 2.0x
- negative: below threshold -> cache_creation stays at base price
- breakdown: 5m + 1h ephemeral prices both scaled when applicable
Refs #2816
Co-authored-by: Cursor <cursoragent@cursor.com>
When session long-context pricing is triggered in computeTokenBreakdown
(e.g. GPT-5.4 / GPT-5.5 above the 272k token threshold), the multiplier
was only being applied to InputPricePerToken and OutputPricePerToken.
The cache_read price was left at its base value, so CacheReadCost was
silently undercharged whenever a long-context session also had cache
hits — which is essentially every long Codex / Claude Code session.
Concretely for gpt-5.4 with 300k cache_read tokens, the bug
under-billed the request by exactly 1x the LongContextInputMultiplier
on the cache portion (e.g. 0.075 instead of 0.150 in the regression
test).
Cache reads are conceptually input-side replays, so they should scale
with LongContextInputMultiplier, matching the treatment of
InputPricePerToken.
Adds two regression tests:
- positive: long-context triggered -> cache_read scaled by 2.0x
- negative: below threshold -> cache_read stays at base price
Fixes#2293
Co-authored-by: Cursor <cursoragent@cursor.com>
- applyRequestTierOverrides now uses filterValidIntervals consistently
with applyTokenOverrides (per_request/image modes were not filtering)
- CostInput accepts optional pre-resolved pricing via Resolved field,
eliminating duplicate Resolver.Resolve() calls in gateway billing paths
- calculateTokenCost reduced from 80 to 15 lines
- calculateCostInternal reduced from 91 to 15 lines
- Shared logic in computeTokenBreakdown + computeCacheCreationCost
- Unified rateMultiplier <= 0 protection in both paths
Instead of hardcoding BillingMode="image" when ImageCount>0,
let cost.BillingMode (set by CalculateCostUnified/CalculateImageCost)
take priority. This ensures channel token pricing shows "token" mode.
- Parse candidatesTokensDetails from Gemini API to separate image/text output tokens
- Add image_output_tokens and image_output_cost to usage_log (migration 089)
- Support per-image-token pricing via output_cost_per_image_token from model pricing data
- Channel pricing ImageOutputPrice override works in token billing mode
- Auto-fill image_output_price in channel pricing form from model defaults
- Add "channel_mapped" billing model source as new default (migration 088)
- Bills by model name after channel mapping, before account mapping
- Fix channel cache error TTL sign error (115s → 5s)
- Fix Update channel only invalidating new groups, not removed groups
- Fix frontend model_mapping clearing sending undefined instead of {}
- Credits balance precheck via shared AccountUsageService cache before injection
- Skip credits injection for accounts with insufficient balance
- Don't mark credits exhausted for "exhausted your capacity on this model" 429s
Previously 2K images used the same base price as 1K ($0.134).
Now 2K uses 1.5x multiplier ($0.201), consistent with 4K using 2x ($0.268).
- Backend: add 2K size branch in getDefaultImagePrice
- Frontend: update 2K placeholder from 0.134 to 0.201
- Tests: update assertions for new 2K default price
Heatherm Huang