{"version":3,"sources":["../src/pricing.ts","../src/shape/pricing.ts","../src/shape/capabilities.ts","../src/shape/thinking.ts","../src/catalog/anthropic.ts","../src/catalog/openai.ts","../src/catalog/google.ts","../src/catalog/index.ts","../src/catalog/pricing.ts"],"sourcesContent":["// `@odla-ai/ai/pricing` — the model price list, on its own.\n//\n// This entrypoint exists so cost accounting can depend on odla-ai's pricing\n// without depending on odla-ai's runtime. It pulls in the catalog and the two\n// pure pricing/usage shapes and nothing else: no provider adapters, no client,\n// no `@anthropic-ai/sdk` / `openai` / `@google/genai`. `@odla-ai/o11y` imports\n// it to price LLM telemetry from one source of truth instead of maintaining a\n// second, drifting price table.\n//\n// Everything here is re-exported from the package root as well; importing the\n// subpath only buys you the smaller bundle.\n\nexport { costUsd, promptTokens, ratesForPrompt, scaleLongContext } from \"./shape/pricing\";\nexport type { LongContextPricing, ModelPricing, TokenRates } from \"./shape/pricing\";\nexport type { OracleUsage } from \"./shape/usage\";\nexport { modelPricing, priceCall, pricedModels } from \"./catalog/pricing\";\nexport { DEFAULT_CATALOG, buildCatalog } from \"./catalog/index\";\nexport type { Catalog } from \"./catalog/index\";\nexport type { ModelSpec } from \"./shape/capabilities\";\n","// Model pricing — USD per million tokens, carried on the catalog's ModelSpec.\n// Field names deliberately mirror @odla/o11y-core's ModelPrice so a spec's\n// pricing can back its costUsd() override without adaptation.\n\nimport type { OracleUsage } from \"./usage\";\n\n/** The four per-token rates one request is billed at. */\nexport interface TokenRates {\n /** USD per MTok of input. */\n inputPerMTok: number;\n /** USD per MTok of output (thinking tokens bill as output). */\n outputPerMTok: number;\n /** USD per MTok read from the prompt cache. Falls back to `inputPerMTok`. */\n cacheReadPerMTok?: number;\n /** USD per MTok written to the prompt cache (default-TTL tier). Falls back to\n * `inputPerMTok`. */\n cacheWritePerMTok?: number;\n}\n\n/**\n * The rates a model charges once a request's prompt is longer than a\n * threshold. Every provider that prices this way replaces the rate of the\n * WHOLE request, not of the tokens past the threshold, so one extra prompt\n * token can multiply the bill. Cache rates left out here fall back to this\n * tier's `inputPerMTok`, never to the base tier's cheaper cache rates.\n */\nexport interface LongContextPricing extends TokenRates {\n /** Prompt length in tokens. A request whose prompt is longer than this pays\n * these rates; a prompt of exactly this length still pays the base rates. */\n aboveTokens: number;\n}\n\n/** USD prices per million tokens (MTok) for one model. Absent pricing means\n * \"unknown\" — never assume free. */\nexport interface ModelPricing extends TokenRates {\n /** Rates for requests whose prompt exceeds a length threshold. Absent means\n * the model charges one rate at every prompt length. */\n longContext?: LongContextPricing;\n /** Free-text qualifier, e.g. \"intro $2/$10 per MTok through 2026-08-31\". */\n note?: string;\n}\n\n/**\n * The prompt length of one request: every token the model read, however it was\n * billed. The token classes in `OracleUsage` are disjoint, so a prompt served\n * mostly from the cache is still as long as the three classes summed — and it\n * is that length, not the uncached part, that selects a long-context rate.\n */\nexport function promptTokens(usage: OracleUsage): number {\n return usage.inputTokens + (usage.cacheReadTokens ?? 0) + (usage.cacheCreationTokens ?? 0);\n}\n\n/**\n * The rates a request with a prompt of `prompt` tokens is billed at: the\n * long-context tier when the model has one and the prompt is over its\n * threshold, the base rates otherwise.\n */\nexport function ratesForPrompt(pricing: ModelPricing, prompt: number): TokenRates {\n const long = pricing.longContext;\n return long && prompt > long.aboveTokens ? long : pricing;\n}\n\n/**\n * Build a long-context tier from multipliers over a model's base rates — the\n * way OpenAI states it (\"2x input and 1.5x output\"). The input multiplier\n * covers every prompt-side rate: input, cache read, and cache write. A cache\n * rate the base does not carry stays absent, so it falls back to the tier's\n * input rate rather than inventing a discount.\n */\nexport function scaleLongContext(\n base: TokenRates,\n aboveTokens: number,\n inputFactor: number,\n outputFactor: number,\n): LongContextPricing {\n return {\n aboveTokens,\n inputPerMTok: base.inputPerMTok * inputFactor,\n outputPerMTok: base.outputPerMTok * outputFactor,\n ...(base.cacheReadPerMTok === undefined ? {} : { cacheReadPerMTok: base.cacheReadPerMTok * inputFactor }),\n ...(base.cacheWritePerMTok === undefined ? {} : { cacheWritePerMTok: base.cacheWritePerMTok * inputFactor }),\n };\n}\n\n/**\n * Compute the USD cost of one request from its token usage. The four token\n * classes in `OracleUsage` are disjoint (Anthropic semantics, which the shape\n * mirrors), so each is priced at its own rate and summed. Callers must check\n * that pricing exists first — unknown pricing is \"no number\", never $0.\n *\n * `usage` must be ONE request's usage. A long-context tier is chosen by that\n * request's prompt length, so pricing a sum of several requests would bill\n * short prompts at the long rate; price each request, then add the dollars.\n */\nexport function costUsd(pricing: ModelPricing, usage: OracleUsage): number {\n const rates = ratesForPrompt(pricing, promptTokens(usage));\n const cacheRead = rates.cacheReadPerMTok ?? rates.inputPerMTok;\n const cacheWrite = rates.cacheWritePerMTok ?? rates.inputPerMTok;\n return (\n (usage.inputTokens / 1e6) * rates.inputPerMTok +\n (usage.outputTokens / 1e6) * rates.outputPerMTok +\n ((usage.cacheReadTokens ?? 0) / 1e6) * cacheRead +\n ((usage.cacheCreationTokens ?? 0) / 1e6) * cacheWrite\n );\n}\n","// Model capabilities + request validation. This is the \"config is data\"\n// doctrine from odla-kg: what a model can do is a data descriptor, and every\n// request is checked against it *before* dispatch so a mismatch fails fast with\n// a clear CapabilityError instead of a confusing provider 400 (the canonical\n// example: audio input to a Claude model — Claude has no audio input).\n\nimport {\n CapabilityError,\n blocksOf,\n type OracleRequest,\n type ProviderId,\n} from \"./index\";\nimport type { ModelPricing } from \"./pricing\";\nimport type { Superpowers } from \"./superpowers\";\nimport type { ThinkingSupport } from \"./thinking\";\n\n/** The kind of model — chat/multimodal is the v1 focus; the others are modeled\n * so embeddings, transcription, TTS, and image generation slot in later. */\nexport type ModelKind = \"chat\" | \"embed\" | \"transcribe\" | \"tts\" | \"image\";\n\nexport interface Capabilities {\n kind: ModelKind;\n /** Accepts text input. */\n textIn: boolean;\n /** Accepts image input (ImageBlock). */\n imageIn: boolean;\n /** Accepts audio input (AudioBlock). */\n audioIn: boolean;\n /** Accepts document/PDF input (DocumentBlock). */\n documentIn: boolean;\n /** Supports tool / function calling. */\n toolUse: boolean;\n /** Supports a native reasoning/thinking mode. */\n thinking: boolean;\n /** Supports an effort/reasoning-depth knob. */\n effort: boolean;\n /** Supports streaming responses. */\n streaming: boolean;\n /** Supports constrained JSON / structured output. */\n structuredOutput: boolean;\n /** Supports a provider server-side web-search tool. */\n webSearch: boolean;\n /** Tool results may carry content blocks natively (image/document blocks\n * inside a `tool_result`). When absent or false, the provider adapter\n * degrades non-text blocks in tool results to `[type]` text placeholders —\n * a lossy but non-fatal fallback, so this flag is discovery metadata for\n * consumers (e.g. vision-feeding tools) rather than a validation gate. */\n toolResultBlocks?: boolean;\n}\n\n/** A catalog entry: a canonical model id mapped to a provider, that provider's\n * native model id, and what the model can do. */\nexport interface ModelSpec {\n /** Canonical id used across odla-ai (e.g. \"claude-opus-4-8\", \"gpt-5\"). */\n id: string;\n provider: ProviderId;\n /** The id passed to the provider SDK. Often equal to `id`. */\n nativeId: string;\n capabilities: Capabilities;\n contextWindow?: number;\n maxOutput?: number;\n /** Provider display name, for catalog/dashboard rendering. */\n displayName?: string;\n /** USD pricing per MTok; absent means unknown — never assume free. */\n pricing?: ModelPricing;\n /** Reasoning descriptor (thinking control + effort ladder). Authoritative\n * over the `capabilities.thinking`/`effort` booleans when present. */\n thinking?: ThinkingSupport;\n /** Provider server-side capabilities (web search, grounding, …) with typed\n * per-provider config. */\n superpowers?: Superpowers;\n /** Which of the provider's endpoints to call. OpenAI only today: `\"chat\"` is\n * Chat Completions, `\"responses\"` is `/v1/responses` — the only OpenAI\n * endpoint where reasoning and function tools coexist. Omit to let the\n * adapter choose (see `openaiApiFor`). */\n api?: \"chat\" | \"responses\";\n}\n\n/** Sensible chat/multimodal defaults; per-model tables override what differs. */\nexport function chatCapabilities(overrides: Partial = {}): Capabilities {\n return {\n kind: \"chat\",\n textIn: true,\n imageIn: true,\n audioIn: false,\n documentIn: false,\n toolUse: true,\n thinking: false,\n effort: false,\n streaming: true,\n structuredOutput: true,\n webSearch: false,\n toolResultBlocks: false,\n ...overrides,\n };\n}\n\n/**\n * Validate a request against a model's capabilities. Throws CapabilityError on\n * the first violation. Runs before any provider call — the single choke point\n * that turns \"audio to Claude\" from an opaque upstream 400 into a clear error.\n */\nexport function validateRequest(spec: ModelSpec, req: OracleRequest): void {\n const caps = spec.capabilities;\n const fail = (what: string): never => {\n throw new CapabilityError(\n `Model \"${spec.id}\" (${spec.provider}) does not support ${what}.`,\n );\n };\n\n if (caps.kind !== \"chat\") fail(`chat requests (it is a \"${caps.kind}\" model)`);\n\n for (const msg of req.messages) {\n for (const block of blocksOf(msg.content)) {\n if (block.type === \"image\" && !caps.imageIn) fail(\"image input\");\n if (block.type === \"audio\" && !caps.audioIn) fail(\"audio input\");\n if (block.type === \"document\" && !caps.documentIn) fail(\"document (PDF) input\");\n }\n }\n\n if (req.tools && req.tools.length > 0 && !caps.toolUse) fail(\"tool use\");\n if (req.webSearch && !caps.webSearch && !spec.superpowers?.webSearch) fail(\"web search\");\n if (req.responseFormat && !caps.structuredOutput) fail(\"structured output\");\n\n const descriptor = spec.thinking;\n if (descriptor) {\n // Descriptor-aware gating: the per-model ThinkingSupport is authoritative.\n if (req.thinking === \"off\" && descriptor.control === \"always-on\") {\n fail(\"disabling thinking (thinking is always on for this model)\");\n }\n if (req.thinking === \"adaptive\" && descriptor.control === \"none\") fail(\"thinking\");\n if (req.effort) {\n const levels = descriptor.effortLevels ?? [];\n if (!levels.includes(req.effort)) {\n throw new CapabilityError(\n `Model \"${spec.id}\" (${spec.provider}) does not support effort \"${req.effort}\". ` +\n `Supported levels: ${levels.join(\", \") || \"(none)\"}.`,\n );\n }\n }\n } else {\n // Legacy boolean fallback for specs authored before ThinkingSupport existed.\n if (req.effort && !caps.effort) fail(\"the effort parameter\");\n if (req.thinking === \"adaptive\" && !caps.thinking) fail(\"thinking\");\n }\n}\n","// Per-model reasoning descriptor: how a model's thinking toggle behaves and how\n// the unified cross-provider effort ladder maps to that model's native knob.\n// This replaces the old lossy adapter heuristics (OpenAI silently collapsing\n// high/xhigh/max → \"high\"; Gemini ignoring effort entirely) with explicit,\n// per-model data that validateRequest can enforce.\n\nimport type { ProviderId } from \"./blocks\";\nimport type { Effort } from \"./request\";\nimport type { ModelSpec } from \"./capabilities\";\n\n/** How a model's `thinking` request field behaves. Describes the request\n * toggle, not whether the model reasons internally. */\nexport type ThinkingControl =\n /** No native thinking toggle; `thinking: \"adaptive\"` is rejected. */\n | \"none\"\n /** Thinking cannot be disabled; `thinking: \"off\"` is rejected. */\n | \"always-on\"\n /** Off unless the request sets `thinking: \"adaptive\"`. */\n | \"opt-in\"\n /** Adaptive unless the request sets `thinking: \"off\"`. */\n | \"on-by-default\"\n /** Legacy token-budget style; `\"adaptive\"` maps to a budget_tokens value. */\n | \"budget\";\n\n/** The provider-native knob one unified `Effort` level maps to. The `param`\n * discriminant lets each adapter assert the variant it expects and fail loudly\n * on a mis-authored catalog entry. */\nexport type NativeEffort =\n /** Anthropic `output_config.effort`. */\n | { param: \"outputConfigEffort\"; value: Effort }\n /** OpenAI `reasoning_effort`. */\n | { param: \"reasoningEffort\"; value: string }\n /** Google `thinkingConfig.thinkingBudget` (-1 = dynamic). */\n | { param: \"thinkingBudget\"; value: number }\n /** Google `thinkingConfig.thinkingLevel` (Gemini 3.x generation). */\n | { param: \"thinkingLevel\"; value: \"minimal\" | \"low\" | \"medium\" | \"high\" };\n\n/** A model's reasoning descriptor: the effort-ladder levels it actually\n * supports and how each maps to the provider-native knob. */\nexport interface ThinkingSupport {\n control: ThinkingControl;\n /** Ladder levels the model accepts, ascending. Omitted/empty = no effort knob. */\n effortLevels?: Effort[];\n /** Native mapping per supported level; keys must equal `effortLevels`. */\n effortMap?: Partial>;\n /** `control: \"budget\"` only — the budget_tokens sent when a request asks for\n * `thinking: \"adaptive\"` (clamped below maxTokens by the adapter). */\n defaultBudgetTokens?: number;\n /** The native effort value to send when the request carries FUNCTION TOOLS.\n *\n * Some reasoning models refuse tools while any reasoning is in play on the\n * provider's chat endpoint, and reason by default when the parameter is\n * omitted — so sending nothing is what fails. OpenAI's gpt-5.6 line says so\n * outright: \"Function tools with reasoning_effort are not supported … use\n * /v1/responses or set reasoning_effort to 'none'\".\n *\n * Set it and the adapter sends this value for tool-carrying requests instead\n * of leaving the model on its default. Requesting an explicit `effort`\n * alongside tools on such a model is a CapabilityError, not a silent\n * downgrade — the caller asked for depth the endpoint cannot give. */\n toolsEffort?: NativeEffort;\n}\n\n/** The full unified effort ladder, ascending. */\nexport const EFFORT_LEVELS: readonly Effort[] = [\"low\", \"medium\", \"high\", \"xhigh\", \"max\"];\n\n/** Resolve the provider-native mapping for an effort level on a model, or\n * undefined when the model does not map that level. */\nexport function nativeEffort(spec: ModelSpec, effort: Effort): NativeEffort | undefined {\n return spec.thinking?.effortMap?.[effort];\n}\n\n/** The effort levels a spec supports — descriptor first; specs authored before\n * the descriptor existed fall back to the legacy capability boolean (all\n * levels when `capabilities.effort` is true). */\nexport function supportedEffortLevels(spec: ModelSpec): Effort[] {\n if (spec.thinking) return spec.thinking.effortLevels ?? [];\n return spec.capabilities.effort ? [...EFFORT_LEVELS] : [];\n}\n\n/** Generic Gemini thinkingBudget ladder used when no hand-tuned map exists. */\nconst GOOGLE_BUDGETS: Record = {\n low: 1_024,\n medium: 4_096,\n high: 8_192,\n xhigh: 16_384,\n max: 24_576,\n};\n\n/**\n * Derive a sensible per-provider `effortMap` for a set of levels: identity\n * maps for Anthropic (`output_config.effort`) and OpenAI (`reasoning_effort`),\n * a generic token-budget ladder for Google. Used by callers (e.g. the odla\n * platform's catalog editor) that know a model's levels but not its native\n * knob values; hand-tuned catalog entries override this.\n */\nexport function defaultEffortMap(\n provider: ProviderId,\n levels: Effort[],\n nativeId?: string,\n): Partial> {\n const out: Partial> = {};\n for (const level of levels) {\n if (provider === \"google\" && nativeId?.startsWith(\"gemini-3\")) {\n if (level === \"low\" || level === \"medium\" || level === \"high\") {\n out[level] = { param: \"thinkingLevel\", value: level };\n }\n } else if (provider === \"google\") out[level] = { param: \"thinkingBudget\", value: GOOGLE_BUDGETS[level] };\n else if (provider === \"openai\") out[level] = { param: \"reasoningEffort\", value: level };\n else out[level] = { param: \"outputConfigEffort\", value: level };\n }\n return out;\n}\n","// Anthropic (Claude) model catalog — config as data.\n//\n// VERIFIED 2026-07-15 against the live Models API (GET /v1/models via\n// listModels() with a real key): ids, display names, context windows, max\n// output, adaptive-thinking support, and per-model effort ladders all come\n// from the listing (opus-4-6/sonnet-4-6 have no \"xhigh\"; haiku-4-5 has no\n// adaptive thinking — it is budget_tokens-style). Pricing from the Anthropic\n// docs the same day (cache rates from the documented multipliers: read 0.1×,\n// default-TTL write 1.25×). web_search_20260209 verified with a live call on\n// claude-fable-5. Re-verify via listModels() before shipping if time has\n// passed — never hardcode model ids from memory.\n//\n// 2026-10-09, from Anthropic's models overview, the Haiku 5.5 model page and\n// migration guide, the programmatic tool calling page and the pricing page\n// (docs, not a Models API listing): Claude Haiku 5.5 added, the first model\n// here priced by prompt length; Sonnet 5's $2/$10 \"intro\" price is now its\n// standard price; Haiku 4.5 is a legacy model.\n\nimport { chatCapabilities, type ModelSpec } from \"../shape/capabilities\";\nimport type { ModelPricing, TokenRates } from \"../shape/pricing\";\nimport type { Effort } from \"../shape/request\";\nimport type { Superpowers } from \"../shape/superpowers\";\nimport { defaultEffortMap, type ThinkingControl, type ThinkingSupport } from \"../shape/thinking\";\n\nconst FRONTIER = () =>\n chatCapabilities({\n documentIn: true, // PDF\n thinking: true, // adaptive\n effort: true, // output_config.effort\n webSearch: true, // web_search_20260209\n audioIn: false, // Claude has no audio input\n toolResultBlocks: true, // adapter maps image/document blocks inside tool_result\n });\n\nconst WEB_SEARCH: Superpowers = {\n webSearch: { type: \"anthropic-web-search\", toolType: \"web_search_20260209\" },\n};\n\nconst FIVE: Effort[] = [\"low\", \"medium\", \"high\", \"xhigh\", \"max\"];\nconst FOUR: Effort[] = [\"low\", \"medium\", \"high\", \"max\"]; // 4.6 tier: no xhigh\n\nconst thinking = (control: ThinkingControl, levels: Effort[]): ThinkingSupport => ({\n control,\n effortLevels: levels,\n effortMap: defaultEffortMap(\"anthropic\", levels),\n});\n\nconst rates = (inputPerMTok: number, outputPerMTok: number): TokenRates => ({\n inputPerMTok,\n outputPerMTok,\n cacheReadPerMTok: inputPerMTok * 0.1,\n cacheWritePerMTok: inputPerMTok * 1.25,\n});\n\nconst price = (inputPerMTok: number, outputPerMTok: number, note?: string): ModelPricing => ({\n ...rates(inputPerMTok, outputPerMTok),\n ...(note ? { note } : {}),\n});\n\n/** Built-in Anthropic (Claude) catalog: one `ModelSpec` per model (canonical id, native id, capabilities, limits, pricing, thinking descriptor). */\nexport const ANTHROPIC_MODELS: ModelSpec[] = [\n {\n id: \"claude-opus-5\",\n provider: \"anthropic\",\n nativeId: \"claude-opus-5\",\n displayName: \"Claude Opus 5\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(5, 25),\n thinking: thinking(\"on-by-default\", FIVE),\n superpowers: WEB_SEARCH,\n },\n {\n id: \"claude-opus-4-8\",\n provider: \"anthropic\",\n nativeId: \"claude-opus-4-8\",\n displayName: \"Claude Opus 4.8\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(5, 25),\n thinking: thinking(\"opt-in\", FIVE),\n superpowers: WEB_SEARCH,\n },\n {\n id: \"claude-opus-4-7\",\n provider: \"anthropic\",\n nativeId: \"claude-opus-4-7\",\n displayName: \"Claude Opus 4.7\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(5, 25),\n thinking: thinking(\"opt-in\", FIVE),\n superpowers: WEB_SEARCH,\n },\n {\n id: \"claude-opus-4-6\",\n provider: \"anthropic\",\n nativeId: \"claude-opus-4-6\",\n displayName: \"Claude Opus 4.6\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(5, 25),\n thinking: thinking(\"opt-in\", FOUR),\n superpowers: WEB_SEARCH,\n },\n {\n // Thinking is always on for Fable 5 — thinking:\"off\" is rejected.\n id: \"claude-fable-5\",\n provider: \"anthropic\",\n nativeId: \"claude-fable-5\",\n displayName: \"Claude Fable 5\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(10, 50),\n thinking: thinking(\"always-on\", FIVE),\n superpowers: WEB_SEARCH,\n },\n {\n // Sonnet 5 runs adaptive thinking unless the request turns it off.\n id: \"claude-sonnet-5\",\n provider: \"anthropic\",\n nativeId: \"claude-sonnet-5\",\n displayName: \"Claude Sonnet 5\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(2, 10),\n thinking: thinking(\"on-by-default\", FIVE),\n superpowers: WEB_SEARCH,\n },\n {\n id: \"claude-sonnet-4-6\",\n provider: \"anthropic\",\n nativeId: \"claude-sonnet-4-6\",\n displayName: \"Claude Sonnet 4.6\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: price(3, 15),\n thinking: thinking(\"opt-in\", FOUR),\n superpowers: WEB_SEARCH,\n },\n {\n // Haiku 5.5 is the first Haiku on the frontier request shape: adaptive\n // thinking on unless the request turns it off, the full effort ladder, no\n // sampling params. Unlike Haiku 4.5 it supports programmatic tool calling,\n // which web_search_20260209's dynamic filtering runs through, so it takes\n // the same web search the frontier tier does. It is also priced by prompt\n // length — a request whose prompt is over 100K tokens pays five times as\n // much on every token, cache reads and writes included.\n id: \"claude-haiku-5-5\",\n provider: \"anthropic\",\n nativeId: \"claude-haiku-5-5\",\n displayName: \"Claude Haiku 5.5\",\n capabilities: FRONTIER(),\n contextWindow: 1_000_000,\n maxOutput: 128_000,\n pricing: { ...price(0.1, 0.5), longContext: { aboveTokens: 100_000, ...rates(0.5, 2.5) } },\n thinking: thinking(\"on-by-default\", FIVE),\n superpowers: WEB_SEARCH,\n },\n {\n // Haiku 4.5 (legacy since Haiku 5.5, which costs a tenth as much up to\n // 100K prompt tokens): no effort param, no adaptive thinking (budget_tokens\n // style), web search needs Sonnet-4.6+ — all reflected below.\n id: \"claude-haiku-4-5\",\n provider: \"anthropic\",\n // The convenient canonical id routes to Anthropic's pinned dated model.\n nativeId: \"claude-haiku-4-5-20251001\",\n displayName: \"Claude Haiku 4.5\",\n capabilities: chatCapabilities({\n documentIn: true,\n thinking: true, // budget-style thinking (mapped to budget_tokens)\n effort: false,\n webSearch: false,\n audioIn: false,\n toolResultBlocks: true, // same messages API + adapter mapping as the frontier tier\n }),\n contextWindow: 200_000,\n maxOutput: 64_000,\n pricing: price(1, 5),\n thinking: { control: \"budget\", defaultBudgetTokens: 8_192 },\n },\n];\n","// OpenAI model catalog — config as data.\n//\n// VERIFIED 2026-08-30 against the account's live /v1/models list (via\n// listModels() with a real key) and the official model/pricing pages\n// (developers.openai.com). reasoning_effort ladders verified EMPIRICALLY with\n// live calls per model: the gpt-5.4/5.5 generation accepts low/medium/high/\n// xhigh (plus \"none\", not part of the unified ladder — reachable via\n// providerExtras); the gpt-5 generation accepts low/medium/high only; search/\n// audio/4o lines reject reasoning_effort outright. OpenAI now publishes full\n// limits, modalities, effort ladders, tools, and token/cache prices for the\n// gpt-5.6 Sol/Terra/Luna family, so those stable ids are authoritative builtins\n// rather than mutable provider-discovery imports. Re-verify via listModels()\n// and the official model pages as the lineup drifts; do NOT trust ids from\n// memory. Pass a custom catalog to init() to add models without a release.\n\nimport { chatCapabilities, type ModelSpec } from \"../shape/capabilities\";\nimport { scaleLongContext, type ModelPricing } from \"../shape/pricing\";\nimport type { Effort } from \"../shape/request\";\nimport { defaultEffortMap, type ThinkingSupport } from \"../shape/thinking\";\n\nconst LADDER_54: Effort[] = [\"low\", \"medium\", \"high\", \"xhigh\"];\nconst LADDER_5: Effort[] = [\"low\", \"medium\", \"high\"];\nconst LADDER_56: Effort[] = [\"low\", \"medium\", \"high\", \"xhigh\", \"max\"];\n\n// OpenAI reasoning models have no thinking on/off toggle in the canonical\n// shape (control:\"none\"); depth is driven purely by the effort ladder.\nconst reasoning = (levels: Effort[]): ThinkingSupport => ({\n control: \"none\",\n effortLevels: levels,\n effortMap: defaultEffortMap(\"openai\", levels),\n});\n\n// GPT-5.6 reasons at medium by default and accepts `none` as the native off\n// value. The canonical toggle therefore starts on while the explicit effort\n// ladder remains low..max.\nconst reasoning56 = (): ThinkingSupport => ({\n control: \"on-by-default\",\n effortLevels: LADDER_56,\n effortMap: defaultEffortMap(\"openai\", LADDER_56),\n});\n\nconst price = (\n inputPerMTok: number,\n outputPerMTok: number,\n cacheReadPerMTok: number,\n note?: string,\n): ModelPricing => ({ inputPerMTok, outputPerMTok, cacheReadPerMTok, ...(note ? { note } : {}) });\n\n/** OpenAI's long-context rule, verified against its pricing page 2026-10-09:\n * a prompt over 272K input tokens bills the whole request at 2× on every\n * prompt-side rate (input, cached input, cache writes) and 1.5× on output. */\nconst longContext = (base: ModelPricing): ModelPricing => ({\n ...base,\n longContext: scaleLongContext(base, 272_000, 2, 1.5),\n});\n\nconst price56 = (\n inputPerMTok: number,\n outputPerMTok: number,\n cacheReadPerMTok: number,\n note?: string,\n): ModelPricing => longContext({\n inputPerMTok,\n outputPerMTok,\n cacheReadPerMTok,\n cacheWritePerMTok: inputPerMTok * 1.25,\n ...(note ? { note } : {}),\n});\n\n/** Built-in OpenAI catalog: one `ModelSpec` per model (canonical id == native id, capabilities, limits, pricing, thinking descriptor). */\nexport const OPENAI_MODELS: ModelSpec[] = [\n {\n id: \"gpt-5.6-sol\",\n provider: \"openai\",\n nativeId: \"gpt-5.6-sol\",\n displayName: \"GPT-5.6 Sol\",\n capabilities: chatCapabilities({ thinking: true, effort: true, webSearch: true }),\n contextWindow: 1_050_000,\n maxOutput: 128_000,\n pricing: price56(4, 20, 0.4, \"promotional pricing through at least 2026-11-21\"),\n thinking: reasoning56(),\n superpowers: { webSearch: { type: \"openai-web-search\", contextSize: \"medium\" } },\n api: \"responses\",\n },\n {\n id: \"gpt-5.6-terra\",\n provider: \"openai\",\n nativeId: \"gpt-5.6-terra\",\n displayName: \"GPT-5.6 Terra\",\n capabilities: chatCapabilities({ thinking: true, effort: true, webSearch: true }),\n contextWindow: 1_050_000,\n maxOutput: 128_000,\n pricing: price56(2, 12, 0.2),\n thinking: reasoning56(),\n superpowers: { webSearch: { type: \"openai-web-search\", contextSize: \"medium\" } },\n api: \"responses\",\n },\n {\n id: \"gpt-5.6-luna\",\n provider: \"openai\",\n nativeId: \"gpt-5.6-luna\",\n displayName: \"GPT-5.6 Luna\",\n capabilities: chatCapabilities({ thinking: true, effort: true, webSearch: true }),\n contextWindow: 1_050_000,\n maxOutput: 128_000,\n pricing: price56(0.2, 1.2, 0.02),\n thinking: reasoning56(),\n superpowers: { webSearch: { type: \"openai-web-search\", contextSize: \"medium\" } },\n api: \"responses\",\n },\n {\n id: \"gpt-5.5\",\n provider: \"openai\",\n nativeId: \"gpt-5.5\",\n displayName: \"GPT-5.5\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 1_050_000,\n maxOutput: 128_000,\n pricing: longContext(price(5, 30, 0.5)),\n thinking: reasoning(LADDER_54),\n },\n {\n id: \"gpt-5.4\",\n provider: \"openai\",\n nativeId: \"gpt-5.4\",\n displayName: \"GPT-5.4\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 1_050_000,\n maxOutput: 128_000,\n pricing: longContext(price(2.5, 15, 0.25)),\n thinking: reasoning(LADDER_54),\n },\n {\n // Compact GPT-5.4 reasoning model. The default for odla-o11y AI triage.\n id: \"gpt-5.4-mini\",\n provider: \"openai\",\n nativeId: \"gpt-5.4-mini\",\n displayName: \"GPT-5.4 mini\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 400_000,\n maxOutput: 128_000,\n pricing: price(0.75, 4.5, 0.075),\n thinking: reasoning(LADDER_54),\n },\n {\n id: \"gpt-5.4-nano\",\n provider: \"openai\",\n nativeId: \"gpt-5.4-nano\",\n displayName: \"GPT-5.4 nano\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 400_000,\n maxOutput: 128_000,\n pricing: price(0.2, 1.25, 0.02),\n thinking: reasoning(LADDER_54),\n },\n {\n id: \"gpt-5\",\n provider: \"openai\",\n nativeId: \"gpt-5\",\n displayName: \"GPT-5\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 400_000,\n maxOutput: 128_000,\n pricing: price(1.25, 10, 0.125),\n thinking: reasoning(LADDER_5),\n },\n {\n id: \"gpt-5-mini\",\n provider: \"openai\",\n nativeId: \"gpt-5-mini\",\n displayName: \"GPT-5 mini\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 400_000,\n maxOutput: 128_000,\n pricing: price(0.25, 2, 0.025),\n thinking: reasoning(LADDER_5),\n },\n {\n id: \"gpt-5-nano\",\n provider: \"openai\",\n nativeId: \"gpt-5-nano\",\n displayName: \"GPT-5 nano\",\n capabilities: chatCapabilities({ effort: true }),\n contextWindow: 400_000,\n maxOutput: 128_000,\n pricing: price(0.05, 0.4, 0.005),\n thinking: reasoning(LADDER_5),\n },\n {\n // Search-tuned chat model: the adapter sends web_search_options when a\n // request sets webSearch. No reasoning-effort knob (verified: 400).\n id: \"gpt-5-search-api\",\n provider: \"openai\",\n nativeId: \"gpt-5-search-api\",\n displayName: \"GPT-5 Search API\",\n capabilities: chatCapabilities({ webSearch: true }),\n contextWindow: 400_000,\n maxOutput: 128_000,\n pricing: price(1.25, 10, 0.125, \"plus per-search-call tool fees\"),\n thinking: { control: \"none\" },\n superpowers: { webSearch: { type: \"openai-web-search\", contextSize: \"medium\" } },\n },\n {\n // Non-reasoning multimodal chat (image input, no effort knob).\n id: \"gpt-4o\",\n provider: \"openai\",\n nativeId: \"gpt-4o\",\n displayName: \"GPT-4o\",\n capabilities: chatCapabilities(),\n contextWindow: 128_000,\n maxOutput: 16_384,\n pricing: price(2.5, 10, 1.25),\n thinking: { control: \"none\" },\n },\n {\n // Audio-input model line — accepts audio, not images.\n id: \"gpt-audio\",\n provider: \"openai\",\n nativeId: \"gpt-audio\",\n displayName: \"GPT Audio\",\n capabilities: chatCapabilities({ imageIn: false, audioIn: true }),\n contextWindow: 128_000,\n maxOutput: 16_384,\n pricing: price(2.5, 10, 0.25, \"text tokens; audio tokens bill separately\"),\n thinking: { control: \"none\" },\n },\n];\n","// Google (Gemini) model catalog — config as data.\n//\n// VERIFIED 2026-07-15 against the live models.list (via listModels() with a\n// real key) and ai.google.dev pricing. Thinking knobs verified EMPIRICALLY per\n// model: the Gemini 3.x generation takes thinkingConfig.thinkingLevel\n// (minimal/low/medium/high — pro rejects minimal) and still accepts budgets;\n// the 2.5 generation takes thinkingBudget only (pro: 128–32768, cannot\n// disable; flash: 0–24576, 0 = off); 2.0-flash has no thinking. Note\n// gemini-3-pro-preview was RETIRED upstream (404) — hence its absence.\n// Re-verify via listModels() before shipping; do NOT trust ids from memory.\n//\n// Gemini is natively multimodal: text + image + audio + PDF input, tool\n// calling via functionDeclarations, structured output via responseSchema, and\n// web grounding via the googleSearch tool — hence the broad default caps.\n\nimport { chatCapabilities, type ModelSpec } from \"../shape/capabilities\";\nimport type { ModelPricing } from \"../shape/pricing\";\nimport type { Effort } from \"../shape/request\";\nimport type { Superpowers } from \"../shape/superpowers\";\nimport type { NativeEffort, ThinkingControl, ThinkingSupport } from \"../shape/thinking\";\n\nconst GEMINI = (over: { thinking?: boolean; effort?: boolean } = {}) =>\n chatCapabilities({\n audioIn: true,\n documentIn: true,\n thinking: over.thinking ?? true,\n effort: over.effort ?? true,\n webSearch: true, // googleSearch grounding\n });\n\nconst GROUNDING: Superpowers = { webSearch: { type: \"google-search-grounding\" } };\n\n// Gemini 3.x: unified ladder → thinkingConfig.thinkingLevel (identity).\nconst levels = (control: ThinkingControl): ThinkingSupport => ({\n control,\n effortLevels: [\"low\", \"medium\", \"high\"],\n effortMap: {\n low: { param: \"thinkingLevel\", value: \"low\" },\n medium: { param: \"thinkingLevel\", value: \"medium\" },\n high: { param: \"thinkingLevel\", value: \"high\" },\n },\n});\n\n// Gemini 2.5: unified ladder → thinkingConfig.thinkingBudget token values.\nconst budgets = (control: ThinkingControl, values: [number, number, number, number, number]): ThinkingSupport => {\n const ladder: Effort[] = [\"low\", \"medium\", \"high\", \"xhigh\", \"max\"];\n const effortMap: Partial> = {};\n ladder.forEach((level, i) => {\n effortMap[level] = { param: \"thinkingBudget\", value: values[i]! };\n });\n return { control, effortLevels: ladder, effortMap };\n};\n\nconst price = (\n inputPerMTok: number,\n outputPerMTok: number,\n cacheReadPerMTok: number,\n note?: string,\n): ModelPricing => ({ inputPerMTok, outputPerMTok, cacheReadPerMTok, ...(note ? { note } : {}) });\n\n/** A Gemini Pro price with its second rate card: a prompt over 200K tokens\n * bills the whole request at the higher rates. Verified against\n * ai.google.dev/gemini-api/docs/pricing on 2026-10-09. */\nconst tiered = (base: ModelPricing, input: number, output: number, cacheRead: number): ModelPricing => ({\n ...base,\n longContext: { aboveTokens: 200_000, inputPerMTok: input, outputPerMTok: output, cacheReadPerMTok: cacheRead },\n});\n\n/** Built-in Google (Gemini) catalog: one `ModelSpec` per model (canonical id == native id, capabilities, limits, pricing, thinking descriptor). */\nexport const GOOGLE_MODELS: ModelSpec[] = [\n {\n // Stable model and limits verified 2026-08-29 against Google's model and\n // pricing pages. The single output price is intentionally the conservative\n // image-token rate; text/thinking output is cheaper, as the note records.\n id: \"gemini-3.1-flash-lite-image\",\n provider: \"google\",\n nativeId: \"gemini-3.1-flash-lite-image\",\n displayName: \"Nano Banana 2 Lite\",\n capabilities: chatCapabilities({\n audioIn: false,\n documentIn: false,\n thinking: true,\n effort: true,\n structuredOutput: false,\n webSearch: false,\n }),\n contextWindow: 65_536,\n maxOutput: 4_096,\n pricing: {\n inputPerMTok: 0.25,\n outputPerMTok: 30,\n note: \"image output; text/thinking output is $1.50/MTok; one 1K image is 1,120 tokens ($0.0336)\",\n },\n thinking: {\n control: \"always-on\",\n effortLevels: [\"low\", \"high\"],\n effortMap: {\n low: { param: \"thinkingLevel\", value: \"minimal\" },\n high: { param: \"thinkingLevel\", value: \"high\" },\n },\n },\n },\n {\n // Stable identity, limits, capabilities, and paid standard pricing\n // verified 2026-08-30 against Google's model, image-generation, and\n // pricing pages. Image output is the conservative catalog rate.\n id: \"gemini-3.1-flash-image\",\n provider: \"google\",\n nativeId: \"gemini-3.1-flash-image\",\n displayName: \"Nano Banana 2\",\n capabilities: chatCapabilities({\n audioIn: false,\n documentIn: true,\n toolUse: false,\n thinking: true,\n effort: true,\n structuredOutput: false,\n webSearch: true,\n }),\n contextWindow: 131_072,\n maxOutput: 32_768,\n pricing: {\n inputPerMTok: 0.5,\n outputPerMTok: 60,\n note: \"image output; text/thinking output is $3/MTok; 0.5K/1K/2K/4K images cost $0.045/$0.067/$0.101/$0.151\",\n },\n thinking: {\n control: \"always-on\",\n effortLevels: [\"low\", \"high\"],\n effortMap: {\n low: { param: \"thinkingLevel\", value: \"minimal\" },\n high: { param: \"thinkingLevel\", value: \"high\" },\n },\n },\n superpowers: GROUNDING,\n },\n {\n id: \"gemini-3-pro-image\",\n provider: \"google\",\n nativeId: \"gemini-3-pro-image\",\n displayName: \"Nano Banana Pro\",\n capabilities: chatCapabilities({\n audioIn: false,\n documentIn: false,\n toolUse: false,\n thinking: true,\n effort: false,\n structuredOutput: false,\n webSearch: true,\n }),\n contextWindow: 65_536,\n maxOutput: 32_768,\n pricing: {\n inputPerMTok: 2,\n outputPerMTok: 120,\n note: \"image output; text/thinking output is $12/MTok; 1K/2K images cost $0.134 and 4K images cost $0.24\",\n },\n thinking: { control: \"always-on\" },\n superpowers: GROUNDING,\n },\n {\n id: \"gemini-3.5-flash\",\n provider: \"google\",\n nativeId: \"gemini-3.5-flash\",\n displayName: \"Gemini 3.5 Flash\",\n capabilities: GEMINI(),\n contextWindow: 1_048_576,\n maxOutput: 65_536,\n pricing: price(1.5, 9, 0.15),\n thinking: levels(\"on-by-default\"),\n superpowers: GROUNDING,\n },\n {\n id: \"gemini-3.1-pro-preview\",\n provider: \"google\",\n nativeId: \"gemini-3.1-pro-preview\",\n displayName: \"Gemini 3.1 Pro Preview\",\n capabilities: GEMINI(),\n contextWindow: 1_048_576,\n maxOutput: 65_536,\n pricing: tiered(price(2, 12, 0.2), 4, 18, 0.4),\n thinking: levels(\"always-on\"),\n superpowers: GROUNDING,\n },\n {\n id: \"gemini-3-flash-preview\",\n provider: \"google\",\n nativeId: \"gemini-3-flash-preview\",\n displayName: \"Gemini 3 Flash Preview\",\n capabilities: GEMINI(),\n contextWindow: 1_048_576,\n maxOutput: 65_536,\n pricing: price(0.5, 3, 0.05),\n thinking: levels(\"on-by-default\"),\n superpowers: GROUNDING,\n },\n {\n // 2.5 Pro only works in thinking mode (budget 0 rejected upstream).\n id: \"gemini-2.5-pro\",\n provider: \"google\",\n nativeId: \"gemini-2.5-pro\",\n displayName: \"Gemini 2.5 Pro\",\n capabilities: GEMINI(),\n contextWindow: 1_048_576,\n maxOutput: 65_536,\n pricing: tiered(price(1.25, 10, 0.125), 2.5, 15, 0.25),\n thinking: budgets(\"always-on\", [2_048, 8_192, 16_384, 24_576, 32_768]),\n superpowers: GROUNDING,\n },\n {\n id: \"gemini-2.5-flash\",\n provider: \"google\",\n nativeId: \"gemini-2.5-flash\",\n displayName: \"Gemini 2.5 Flash\",\n capabilities: GEMINI(),\n contextWindow: 1_048_576,\n maxOutput: 65_536,\n pricing: price(0.3, 2.5, 0.03),\n thinking: budgets(\"on-by-default\", [1_024, 4_096, 8_192, 16_384, 24_576]),\n superpowers: GROUNDING,\n },\n {\n id: \"gemini-2.5-flash-image\",\n provider: \"google\",\n nativeId: \"gemini-2.5-flash-image\",\n displayName: \"Nano Banana\",\n capabilities: chatCapabilities({\n audioIn: false,\n documentIn: false,\n toolUse: false,\n thinking: false,\n effort: false,\n structuredOutput: true,\n webSearch: false,\n }),\n contextWindow: 65_536,\n maxOutput: 32_768,\n pricing: {\n inputPerMTok: 0.3,\n outputPerMTok: 30,\n note: \"image output; text output is $2.50/MTok; one 1K image is 1,290 tokens ($0.039)\",\n },\n thinking: { control: \"none\" },\n },\n {\n id: \"gemini-2.0-flash\",\n provider: \"google\",\n nativeId: \"gemini-2.0-flash\",\n displayName: \"Gemini 2.0 Flash\",\n capabilities: GEMINI({ thinking: false, effort: false }),\n contextWindow: 1_048_576,\n maxOutput: 8_192,\n pricing: price(0.1, 0.4, 0.025),\n thinking: { control: \"none\" },\n superpowers: GROUNDING,\n },\n];\n","// The model catalog: canonical model id → ModelSpec (provider, native id,\n// capabilities). The default catalog merges the three per-provider tables;\n// init() accepts a custom or extended catalog so apps can add/override models\n// without waiting on a release.\n\nimport { ConfigError, type ProviderId } from \"../shape/index\";\nimport type { ModelSpec } from \"../shape/capabilities\";\nimport { ANTHROPIC_MODELS } from \"./anthropic\";\nimport { OPENAI_MODELS } from \"./openai\";\nimport { GOOGLE_MODELS } from \"./google\";\n\n/** Canonical id → spec. */\nexport type Catalog = Record;\n\nfunction index(specs: ModelSpec[]): Catalog {\n const out: Catalog = {};\n for (const spec of specs) out[spec.id] = spec;\n return out;\n}\n\n/** The built-in catalog across Anthropic, OpenAI, and Google. */\nexport const DEFAULT_CATALOG: Catalog = index([\n ...ANTHROPIC_MODELS,\n ...OPENAI_MODELS,\n ...GOOGLE_MODELS,\n]);\n\n/** Merge extra specs over a base catalog (later entries win by id). */\nexport function buildCatalog(base: Catalog, extra: ModelSpec[] = []): Catalog {\n return { ...base, ...index(extra) };\n}\n\n/** Look up a model, throwing a ConfigError (with the known ids) if unknown. */\nexport function resolveModel(catalog: Catalog, id: string): ModelSpec {\n const spec = catalog[id];\n if (!spec) {\n const known = Object.keys(catalog).sort().join(\", \");\n throw new ConfigError(`Unknown model \"${id}\". Known models: ${known || \"(none)\"}.`);\n }\n return spec;\n}\n\n/** List every provider the catalog can route to. */\nexport function providersInCatalog(catalog: Catalog): ProviderId[] {\n const set = new Set();\n for (const spec of Object.values(catalog)) set.add(spec.provider);\n return [...set];\n}\n\nexport { ANTHROPIC_MODELS, OPENAI_MODELS, GOOGLE_MODELS };\n","// Catalog-backed pricing lookup. The catalog already carries per-model\n// `ModelPricing`; this is the seam that lets a cost-accounting consumer price a\n// call from a model id alone, without holding a Catalog or an Ai client.\n//\n// Deliberately free of provider-SDK imports (the whole `catalog/` + `shape/`\n// subtree is), so `@odla-ai/ai/pricing` stays a few KB in a Worker bundle.\n\nimport { costUsd, type ModelPricing } from \"../shape/pricing\";\nimport type { OracleUsage } from \"../shape/usage\";\nimport { DEFAULT_CATALOG, type Catalog } from \"./index\";\n\n/**\n * Look up a model's USD pricing by canonical id.\n *\n * Returns `undefined` for an unknown model *and* for a known model whose spec\n * carries no `pricing` — the two are the same answer to the only question that\n * matters downstream: \"can this call be priced?\". Unlike `resolveModel`, an\n * unknown id is not an error, because a cost path must degrade to \"unpriced\"\n * rather than throw inside telemetry.\n *\n * @param id Canonical model id, e.g. `\"claude-opus-4-8\"`.\n * @param catalog Catalog to read; defaults to the built-in `DEFAULT_CATALOG`.\n */\nexport function modelPricing(id: string, catalog: Catalog = DEFAULT_CATALOG): ModelPricing | undefined {\n return catalog[id]?.pricing;\n}\n\n/**\n * Price one call from a model id and its token usage.\n *\n * Returns `undefined` when the model has no known pricing, so a caller can\n * never mistake missing catalog data for a free call. Cache-read and\n * cache-write tokens are priced at their own rates when the spec declares them\n * and fall back to the input rate otherwise (see `costUsd`).\n *\n * @param id Canonical model id, e.g. `\"gpt-5\"`.\n * @param usage Token counts for the call.\n * @param catalog Catalog to read; defaults to the built-in `DEFAULT_CATALOG`.\n */\nexport function priceCall(id: string, usage: OracleUsage, catalog: Catalog = DEFAULT_CATALOG): number | undefined {\n const pricing = modelPricing(id, catalog);\n return pricing ? costUsd(pricing, usage) : undefined;\n}\n\n/**\n * The canonical ids of every model in `catalog` that carries pricing, sorted.\n * Useful for a coverage assertion (\"does our catalog price everything we\n * route to?\") and for rendering a pricing table.\n *\n * @param catalog Catalog to read; defaults to the built-in `DEFAULT_CATALOG`.\n */\nexport function pricedModels(catalog: Catalog = DEFAULT_CATALOG): string[] {\n return Object.keys(catalog)\n .filter((id) => catalog[id]?.pricing !== undefined)\n 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