Replace response.BadRequest with response.ErrorFrom + infraerrors.BadRequest
to provide machine-readable reason codes (VALIDATION_ERROR, INVALID_CHANNEL_ID,
MISSING_PARAMETER) for frontend i18n support.
- Extract newEmptyChannelCache() factory to deduplicate map init
- Extract expandPricingToCache() for model pricing expansion
- Extract expandMappingToCache() for model mapping expansion
- buildCache reduced from 110 to 50 lines
- PricingSourceChannel/LiteLLM/Fallback for resolver source
- MediaTypeImage/Video/Prompt for result.MediaType
- Reuse BillingModeToken/BillingModeImage for billing mode
- Reuse BillingModelSourceChannelMapped/PlatformAnthropic in handler
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.
When ImageCount > 0, check if channel has token pricing configured:
- YES (source=channel, mode=token) → use token billing with image_output_tokens
- NO → fall back to CalculateImageCost (original per-image billing)
This allows channels to configure $/MTok pricing for image generation
models while maintaining backward compatibility for setups without
channel pricing.
- Backend: reject intervals with all-null price fields on save
- Backend: filterValidIntervals skips empty intervals in pricing resolver
- Frontend: red border + asterisk on empty interval rows
- Backend: antigravity groups now match anthropic/gemini channel pricing
Antigravity platform serves both Claude and Gemini models, but channel
pricing/mapping is configured under Anthropic/Gemini tabs. The cache
builder was using strict platform equality, causing antigravity groups
to miss all channel pricing entries, resulting in $0 billing.
Add isPlatformPricingMatch() to treat antigravity as superset of
anthropic+gemini for pricing and mapping cache indexing.
- Fix errcheck: defer rows.Close() with nolint
- Fix errcheck: type assertion with ok check in channel cache
- Fix staticcheck ST1005: lowercase error string
- Fix staticcheck SA5011: nil check cost before use in openai gateway
- Fix gofmt: format chatcompletions_to_responses.go
- 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
Allow redeem codes with negative values to enable refund scenarios:
- Balance: negative value deducts balance (clamped to 0, never negative)
- Concurrency: negative value reduces concurrency (clamped to 0)
- Subscription: negative validity_days reduces remaining days; if
remaining days <= 0, the subscription is canceled (set to expired)
All deductions generate standard redeem code records for audit trail.
- ratelimit_service: detect non-standard OpenAI 401 format and permanently disable account
- account_test_service: mark account error on 401 during connection test
Made-with: Cursor
When no explicit session signals (session_id, conversation_id, prompt_cache_key)
are provided, derive a stable session seed from the request body content
(model + tools + system prompt + first user message) to enable sticky routing
and prompt caching for non-Codex clients using the Chat Completions API.
This mirrors the content-based fallback already present in GatewayService.
GenerateSessionHash, adapted for the OpenAI gateway's request formats (both
Chat Completions messages and Responses API input).
JSON fragments are canonicalized via normalizeCompatSeedJSON to ensure
semantically identical requests produce the same seed regardless of
whitespace or key ordering.
Closes#1421
