mirror of
https://github.com/anomalyco/opencode.git
synced 2026-05-14 16:42:38 +00:00
feat: update pricing schema for models to ensure more accurate cost tracking (#27184)
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@@ -10,11 +10,23 @@ import { AppFileSystem } from "@opencode-ai/core/filesystem"
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import { withTransientReadRetry } from "@/util/effect-http-client"
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import { CatalogModelStatus } from "./model-status"
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const CostTier = Schema.Struct({
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input: Schema.Finite,
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output: Schema.Finite,
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cache_read: Schema.optional(Schema.Finite),
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cache_write: Schema.optional(Schema.Finite),
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tier: Schema.Struct({
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type: Schema.Literal("context"),
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size: Schema.Finite,
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}),
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})
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const Cost = Schema.Struct({
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input: Schema.Finite,
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output: Schema.Finite,
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cache_read: Schema.optional(Schema.Finite),
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cache_write: Schema.optional(Schema.Finite),
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tiers: Schema.optional(Schema.Array(CostTier)),
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context_over_200k: Schema.optional(
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Schema.Struct({
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input: Schema.Finite,
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@@ -869,10 +869,21 @@ const ProviderCacheCost = Schema.Struct({
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write: Schema.Finite,
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})
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const ProviderCostTier = Schema.Struct({
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input: Schema.Finite,
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output: Schema.Finite,
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cache: ProviderCacheCost,
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tier: Schema.Struct({
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type: Schema.Literal("context"),
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size: Schema.Finite,
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}),
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})
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const ProviderCost = Schema.Struct({
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input: Schema.Finite,
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output: Schema.Finite,
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cache: ProviderCacheCost,
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tiers: optionalOmitUndefined(Schema.Array(ProviderCostTier)),
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experimentalOver200K: optionalOmitUndefined(
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Schema.Struct({
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input: Schema.Finite,
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@@ -977,6 +988,17 @@ function cost(c: ModelsDev.Model["cost"]): Model["cost"] {
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write: c?.cache_write ?? 0,
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},
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}
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if (c?.tiers) {
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result.tiers = c.tiers.map((item) => ({
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input: item.input,
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output: item.output,
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cache: {
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read: item.cache_read ?? 0,
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write: item.cache_write ?? 0,
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},
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tier: item.tier,
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}))
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}
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if (c?.context_over_200k) {
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result.experimentalOver200K = {
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cache: {
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@@ -418,10 +418,14 @@ export const getUsage = (input: { model: Provider.Model; usage: LanguageModelUsa
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},
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}
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const contextTokens = inputTokens
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const costInfo =
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input.model.cost?.experimentalOver200K && tokens.input + tokens.cache.read > 200_000
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input.model.cost?.tiers
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?.filter((item) => item.tier.type === "context" && contextTokens > item.tier.size)
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.sort((a, b) => b.tier.size - a.tier.size)[0] ??
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(input.model.cost?.experimentalOver200K && contextTokens > 200_000
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? input.model.cost.experimentalOver200K
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: input.model.cost
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: input.model.cost)
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return {
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cost: safe(
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new Decimal(0)
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@@ -1758,6 +1758,101 @@ describe("SessionNs.getUsage", () => {
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expect(result.cost).toBe(3 + 1.5)
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})
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test("uses matching context cost tier before over-200k fallback", () => {
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const model = createModel({
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context: 1_000_000,
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output: 32_000,
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cost: {
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input: 1,
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output: 2,
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cache: { read: 0.1, write: 0.5 },
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tiers: [
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{
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input: 3,
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output: 4,
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cache: { read: 0.3, write: 1.5 },
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tier: { type: "context", size: 200_000 },
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},
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{
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input: 5,
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output: 6,
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cache: { read: 0.5, write: 2.5 },
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tier: { type: "context", size: 500_000 },
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},
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],
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experimentalOver200K: {
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input: 100,
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output: 100,
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cache: { read: 100, write: 100 },
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},
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},
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})
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const result = SessionNs.getUsage({
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model,
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usage: {
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inputTokens: 650_000,
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outputTokens: 100_000,
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totalTokens: 750_000,
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inputTokenDetails: {
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noCacheTokens: undefined,
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cacheReadTokens: 100_000,
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cacheWriteTokens: undefined,
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},
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outputTokenDetails: {
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textTokens: undefined,
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reasoningTokens: undefined,
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},
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},
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})
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expect(result.tokens.input).toBe(550_000)
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expect(result.cost).toBe(2.75 + 0.6 + 0.05)
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})
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test("falls back to over-200k pricing when no cost tier matches", () => {
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const model = createModel({
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context: 1_000_000,
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output: 32_000,
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cost: {
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input: 1,
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output: 2,
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cache: { read: 0.1, write: 0.5 },
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tiers: [
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{
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input: 5,
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output: 6,
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cache: { read: 0.5, write: 2.5 },
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tier: { type: "context", size: 500_000 },
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},
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],
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experimentalOver200K: {
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input: 3,
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output: 4,
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cache: { read: 0.3, write: 1.5 },
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},
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},
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})
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const result = SessionNs.getUsage({
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model,
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usage: {
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inputTokens: 300_000,
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outputTokens: 100_000,
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totalTokens: 400_000,
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inputTokenDetails: {
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noCacheTokens: undefined,
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cacheReadTokens: undefined,
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cacheWriteTokens: undefined,
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},
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outputTokenDetails: {
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textTokens: undefined,
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reasoningTokens: undefined,
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},
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},
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})
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expect(result.cost).toBe(0.9 + 0.4)
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})
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test.each(["@ai-sdk/anthropic", "@ai-sdk/amazon-bedrock", "@ai-sdk/google-vertex/anthropic"])(
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"computes total from components for %s models",
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(npm) => {
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@@ -277,6 +277,25 @@ async function loadFixture(providerID: string, modelID: string) {
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return { provider, model }
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}
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function configModel(model: ModelsDev.Model) {
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return {
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id: model.id,
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name: model.name,
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family: model.family,
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release_date: model.release_date,
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attachment: model.attachment,
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reasoning: model.reasoning,
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temperature: model.temperature,
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tool_call: model.tool_call,
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interleaved: model.interleaved,
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cost: model.cost ? { ...model.cost, tiers: undefined } : undefined,
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limit: model.limit,
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modalities: model.modalities,
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status: model.status,
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provider: model.provider,
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}
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}
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function createEventStream(chunks: unknown[], includeDone = false) {
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const lines = chunks.map((chunk) => `data: ${typeof chunk === "string" ? chunk : JSON.stringify(chunk)}`)
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if (includeDone) {
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@@ -617,7 +636,7 @@ describe("session.llm.stream", () => {
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npm: "@ai-sdk/openai",
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api: "https://api.openai.com/v1",
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models: {
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[model.id]: model,
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[model.id]: configModel(model),
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},
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options: {
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apiKey: "test-openai-key",
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@@ -733,7 +752,7 @@ describe("session.llm.stream", () => {
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npm: "@ai-sdk/openai",
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api: "https://api.openai.com/v1",
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models: {
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[model.id]: model,
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[model.id]: configModel(model),
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},
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options: {
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apiKey: "test-openai-key",
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@@ -970,7 +989,7 @@ describe("session.llm.stream", () => {
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npm: "@ai-sdk/anthropic",
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api: "https://api.anthropic.com/v1",
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models: {
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[model.id]: model,
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[model.id]: configModel(model),
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},
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options: {
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apiKey: "test-anthropic-key",
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