mirror of
https://github.com/anomalyco/opencode.git
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803 lines
26 KiB
TypeScript
803 lines
26 KiB
TypeScript
import { afterEach, describe, expect, mock, spyOn, test } from "bun:test"
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import path from "path"
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import { Bus } from "../../src/bus"
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import { SessionCompaction } from "../../src/session/compaction"
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import { Token } from "../../src/util/token"
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import { Instance } from "../../src/project/instance"
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import { Log } from "../../src/util/log"
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import { tmpdir } from "../fixture/fixture"
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import { Session } from "../../src/session"
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import { MessageV2 } from "../../src/session/message-v2"
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import { MessageID, PartID, SessionID } from "../../src/session/schema"
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import { ModelID, ProviderID } from "../../src/provider/schema"
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import type { Provider } from "../../src/provider/provider"
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import * as ProviderModule from "../../src/provider/provider"
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import * as SessionProcessorModule from "../../src/session/processor"
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Log.init({ print: false })
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const ref = {
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providerID: ProviderID.make("test"),
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modelID: ModelID.make("test-model"),
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}
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afterEach(() => {
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mock.restore()
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})
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function createModel(opts: {
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context: number
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output: number
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input?: number
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cost?: Provider.Model["cost"]
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npm?: string
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}): Provider.Model {
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return {
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id: "test-model",
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providerID: "test",
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name: "Test",
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limit: {
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context: opts.context,
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input: opts.input,
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output: opts.output,
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},
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cost: opts.cost ?? { input: 0, output: 0, cache: { read: 0, write: 0 } },
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capabilities: {
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toolcall: true,
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attachment: false,
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reasoning: false,
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temperature: true,
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input: { text: true, image: false, audio: false, video: false },
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output: { text: true, image: false, audio: false, video: false },
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},
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api: { npm: opts.npm ?? "@ai-sdk/anthropic" },
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options: {},
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} as Provider.Model
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}
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async function user(sessionID: SessionID, text: string) {
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const msg = await Session.updateMessage({
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id: MessageID.ascending(),
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role: "user",
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sessionID,
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agent: "build",
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model: ref,
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time: { created: Date.now() },
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})
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await Session.updatePart({
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id: PartID.ascending(),
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messageID: msg.id,
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sessionID,
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type: "text",
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text,
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})
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return msg
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}
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async function assistant(sessionID: SessionID, parentID: MessageID, root: string) {
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const msg: MessageV2.Assistant = {
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id: MessageID.ascending(),
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role: "assistant",
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sessionID,
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mode: "build",
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agent: "build",
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path: { cwd: root, root },
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cost: 0,
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tokens: {
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output: 0,
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input: 0,
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reasoning: 0,
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cache: { read: 0, write: 0 },
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},
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modelID: ref.modelID,
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providerID: ref.providerID,
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parentID,
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time: { created: Date.now() },
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finish: "end_turn",
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}
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await Session.updateMessage(msg)
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return msg
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}
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async function tool(sessionID: SessionID, messageID: MessageID, tool: string, output: string) {
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return Session.updatePart({
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id: PartID.ascending(),
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messageID,
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sessionID,
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type: "tool",
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callID: crypto.randomUUID(),
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tool,
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state: {
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status: "completed",
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input: {},
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output,
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title: "done",
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metadata: {},
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time: { start: Date.now(), end: Date.now() },
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},
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})
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}
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function fake(
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input: Parameters<(typeof SessionProcessorModule.SessionProcessor)["create"]>[0],
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result: "continue" | "compact",
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): ReturnType<(typeof SessionProcessorModule.SessionProcessor)["create"]> {
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const msg = input.assistantMessage
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return {
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get message() {
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return msg
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},
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partFromToolCall() {
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return {
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id: PartID.ascending(),
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messageID: msg.id,
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sessionID: msg.sessionID,
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type: "tool",
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callID: "fake",
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tool: "fake",
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state: { status: "pending", input: {}, raw: "" },
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}
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},
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process: async () => result,
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}
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}
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function wait(ms = 50) {
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return new Promise((resolve) => setTimeout(resolve, ms))
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}
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function defer() {
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let resolve!: () => void
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const promise = new Promise<void>((done) => {
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resolve = done
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})
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return { promise, resolve }
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}
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describe("session.compaction.isOverflow", () => {
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test("returns true when token count exceeds usable context", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 100_000, output: 32_000 })
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const tokens = { input: 75_000, output: 5_000, reasoning: 0, cache: { read: 0, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(true)
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},
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})
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})
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test("returns false when token count within usable context", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 200_000, output: 32_000 })
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const tokens = { input: 100_000, output: 10_000, reasoning: 0, cache: { read: 0, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(false)
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},
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})
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})
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test("includes cache.read in token count", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 100_000, output: 32_000 })
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const tokens = { input: 60_000, output: 10_000, reasoning: 0, cache: { read: 10_000, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(true)
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},
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})
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})
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test("respects input limit for input caps", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 400_000, input: 272_000, output: 128_000 })
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const tokens = { input: 271_000, output: 1_000, reasoning: 0, cache: { read: 2_000, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(true)
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},
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})
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})
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test("returns false when input/output are within input caps", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 400_000, input: 272_000, output: 128_000 })
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const tokens = { input: 200_000, output: 20_000, reasoning: 0, cache: { read: 10_000, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(false)
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},
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})
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})
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test("returns false when output within limit with input caps", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 200_000, input: 120_000, output: 10_000 })
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const tokens = { input: 50_000, output: 9_999, reasoning: 0, cache: { read: 0, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(false)
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},
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})
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})
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// ─── Bug reproduction tests ───────────────────────────────────────────
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// These tests demonstrate that when limit.input is set, isOverflow()
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// does not subtract any headroom for the next model response. This means
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// compaction only triggers AFTER we've already consumed the full input
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// budget, leaving zero room for the next API call's output tokens.
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//
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// Compare: without limit.input, usable = context - output (reserves space).
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// With limit.input, usable = limit.input (reserves nothing).
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//
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// Related issues: #10634, #8089, #11086, #12621
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// Open PRs: #6875, #12924
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test("BUG: no headroom when limit.input is set — compaction should trigger near boundary but does not", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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// Simulate Claude with prompt caching: input limit = 200K, output limit = 32K
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const model = createModel({ context: 200_000, input: 200_000, output: 32_000 })
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// We've used 198K tokens total. Only 2K under the input limit.
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// On the next turn, the full conversation (198K) becomes input,
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// plus the model needs room to generate output — this WILL overflow.
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const tokens = { input: 180_000, output: 15_000, reasoning: 0, cache: { read: 3_000, write: 0 } }
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// count = 180K + 3K + 15K = 198K
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// usable = limit.input = 200K (no output subtracted!)
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// 198K > 200K = false → no compaction triggered
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// WITHOUT limit.input: usable = 200K - 32K = 168K, and 198K > 168K = true ✓
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// WITH limit.input: usable = 200K, and 198K > 200K = false ✗
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// With 198K used and only 2K headroom, the next turn will overflow.
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// Compaction MUST trigger here.
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(true)
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},
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})
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})
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test("BUG: without limit.input, same token count correctly triggers compaction", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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// Same model but without limit.input — uses context - output instead
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const model = createModel({ context: 200_000, output: 32_000 })
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// Same token usage as above
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const tokens = { input: 180_000, output: 15_000, reasoning: 0, cache: { read: 3_000, write: 0 } }
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// count = 198K
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// usable = context - output = 200K - 32K = 168K
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// 198K > 168K = true → compaction correctly triggered
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const result = await SessionCompaction.isOverflow({ tokens, model })
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expect(result).toBe(true) // ← Correct: headroom is reserved
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},
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})
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})
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test("BUG: asymmetry — limit.input model allows 30K more usage before compaction than equivalent model without it", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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// Two models with identical context/output limits, differing only in limit.input
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const withInputLimit = createModel({ context: 200_000, input: 200_000, output: 32_000 })
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const withoutInputLimit = createModel({ context: 200_000, output: 32_000 })
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// 170K total tokens — well above context-output (168K) but below input limit (200K)
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const tokens = { input: 166_000, output: 10_000, reasoning: 0, cache: { read: 5_000, write: 0 } }
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const withLimit = await SessionCompaction.isOverflow({ tokens, model: withInputLimit })
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const withoutLimit = await SessionCompaction.isOverflow({ tokens, model: withoutInputLimit })
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// Both models have identical real capacity — they should agree:
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expect(withLimit).toBe(true) // should compact (170K leaves no room for 32K output)
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expect(withoutLimit).toBe(true) // correctly compacts (170K > 168K)
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},
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})
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})
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test("returns false when model context limit is 0", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 0, output: 32_000 })
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const tokens = { input: 100_000, output: 10_000, reasoning: 0, cache: { read: 0, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(false)
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},
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})
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})
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test("returns false when compaction.auto is disabled", async () => {
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await using tmp = await tmpdir({
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init: async (dir) => {
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await Bun.write(
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path.join(dir, "opencode.json"),
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JSON.stringify({
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compaction: { auto: false },
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}),
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)
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},
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})
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const model = createModel({ context: 100_000, output: 32_000 })
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const tokens = { input: 75_000, output: 5_000, reasoning: 0, cache: { read: 0, write: 0 } }
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expect(await SessionCompaction.isOverflow({ tokens, model })).toBe(false)
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},
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})
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})
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})
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describe("session.compaction.create", () => {
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test("creates a compaction user message and part", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const session = await Session.create({})
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await SessionCompaction.create({
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sessionID: session.id,
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agent: "build",
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model: ref,
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auto: true,
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overflow: true,
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})
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const msgs = await Session.messages({ sessionID: session.id })
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expect(msgs).toHaveLength(1)
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expect(msgs[0].info.role).toBe("user")
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expect(msgs[0].parts).toHaveLength(1)
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expect(msgs[0].parts[0]).toMatchObject({
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type: "compaction",
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auto: true,
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overflow: true,
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})
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},
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})
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})
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})
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describe("session.compaction.prune", () => {
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test("compacts old completed tool output", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const session = await Session.create({})
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const a = await user(session.id, "first")
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const b = await assistant(session.id, a.id, tmp.path)
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await tool(session.id, b.id, "bash", "x".repeat(200_000))
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await user(session.id, "second")
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await user(session.id, "third")
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await SessionCompaction.prune({ sessionID: session.id })
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const msgs = await Session.messages({ sessionID: session.id })
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const part = msgs.flatMap((msg) => msg.parts).find((part) => part.type === "tool")
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expect(part?.type).toBe("tool")
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expect(part?.state.status).toBe("completed")
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if (part?.type === "tool" && part.state.status === "completed") {
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expect(part.state.time.compacted).toBeNumber()
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}
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},
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})
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})
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test("skips protected skill tool output", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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const session = await Session.create({})
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const a = await user(session.id, "first")
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const b = await assistant(session.id, a.id, tmp.path)
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await tool(session.id, b.id, "skill", "x".repeat(200_000))
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await user(session.id, "second")
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await user(session.id, "third")
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await SessionCompaction.prune({ sessionID: session.id })
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const msgs = await Session.messages({ sessionID: session.id })
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const part = msgs.flatMap((msg) => msg.parts).find((part) => part.type === "tool")
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expect(part?.type).toBe("tool")
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if (part?.type === "tool" && part.state.status === "completed") {
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expect(part.state.time.compacted).toBeUndefined()
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}
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},
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})
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})
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})
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describe("session.compaction.process", () => {
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test("publishes compacted event on continue", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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spyOn(ProviderModule.Provider, "getModel").mockResolvedValue(createModel({ context: 100_000, output: 32_000 }))
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spyOn(SessionProcessorModule.SessionProcessor, "create").mockImplementation((input) => fake(input, "continue"))
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const session = await Session.create({})
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const msg = await user(session.id, "hello")
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const msgs = await Session.messages({ sessionID: session.id })
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const done = defer()
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let seen = false
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const unsub = Bus.subscribe(SessionCompaction.Event.Compacted, (evt) => {
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if (evt.properties.sessionID !== session.id) return
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seen = true
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done.resolve()
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})
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const result = await SessionCompaction.process({
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parentID: msg.id,
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messages: msgs,
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sessionID: session.id,
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abort: new AbortController().signal,
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auto: false,
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})
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await Promise.race([
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done.promise,
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wait(500).then(() => {
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throw new Error("timed out waiting for compacted event")
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}),
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])
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unsub()
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expect(result).toBe("continue")
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expect(seen).toBe(true)
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},
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})
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})
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test("marks summary message as errored on compact result", async () => {
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await using tmp = await tmpdir()
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await Instance.provide({
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directory: tmp.path,
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fn: async () => {
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spyOn(ProviderModule.Provider, "getModel").mockResolvedValue(createModel({ context: 100_000, output: 32_000 }))
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spyOn(SessionProcessorModule.SessionProcessor, "create").mockImplementation((input) => fake(input, "compact"))
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const session = await Session.create({})
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const msg = await user(session.id, "hello")
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const result = await SessionCompaction.process({
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parentID: msg.id,
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messages: await Session.messages({ sessionID: session.id }),
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sessionID: session.id,
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abort: new AbortController().signal,
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auto: false,
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})
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const summary = (await Session.messages({ sessionID: session.id })).find(
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(msg) => msg.info.role === "assistant" && msg.info.summary,
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)
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expect(result).toBe("stop")
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expect(summary?.info.role).toBe("assistant")
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if (summary?.info.role === "assistant") {
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expect(summary.info.finish).toBe("error")
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expect(JSON.stringify(summary.info.error)).toContain("Session too large to compact")
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}
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},
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})
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})
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test("adds synthetic continue prompt when auto is enabled", async () => {
|
|
await using tmp = await tmpdir()
|
|
await Instance.provide({
|
|
directory: tmp.path,
|
|
fn: async () => {
|
|
spyOn(ProviderModule.Provider, "getModel").mockResolvedValue(createModel({ context: 100_000, output: 32_000 }))
|
|
spyOn(SessionProcessorModule.SessionProcessor, "create").mockImplementation((input) => fake(input, "continue"))
|
|
|
|
const session = await Session.create({})
|
|
const msg = await user(session.id, "hello")
|
|
|
|
const result = await SessionCompaction.process({
|
|
parentID: msg.id,
|
|
messages: await Session.messages({ sessionID: session.id }),
|
|
sessionID: session.id,
|
|
abort: new AbortController().signal,
|
|
auto: true,
|
|
})
|
|
|
|
const msgs = await Session.messages({ sessionID: session.id })
|
|
const last = msgs.at(-1)
|
|
|
|
expect(result).toBe("continue")
|
|
expect(last?.info.role).toBe("user")
|
|
expect(last?.parts[0]).toMatchObject({
|
|
type: "text",
|
|
synthetic: true,
|
|
})
|
|
if (last?.parts[0]?.type === "text") {
|
|
expect(last.parts[0].text).toContain("Continue if you have next steps")
|
|
}
|
|
},
|
|
})
|
|
})
|
|
|
|
test("replays the prior user turn on overflow when earlier context exists", async () => {
|
|
await using tmp = await tmpdir()
|
|
await Instance.provide({
|
|
directory: tmp.path,
|
|
fn: async () => {
|
|
spyOn(ProviderModule.Provider, "getModel").mockResolvedValue(createModel({ context: 100_000, output: 32_000 }))
|
|
spyOn(SessionProcessorModule.SessionProcessor, "create").mockImplementation((input) => fake(input, "continue"))
|
|
|
|
const session = await Session.create({})
|
|
await user(session.id, "root")
|
|
const replay = await user(session.id, "image")
|
|
await Session.updatePart({
|
|
id: PartID.ascending(),
|
|
messageID: replay.id,
|
|
sessionID: session.id,
|
|
type: "file",
|
|
mime: "image/png",
|
|
filename: "cat.png",
|
|
url: "https://example.com/cat.png",
|
|
})
|
|
const msg = await user(session.id, "current")
|
|
|
|
const result = await SessionCompaction.process({
|
|
parentID: msg.id,
|
|
messages: await Session.messages({ sessionID: session.id }),
|
|
sessionID: session.id,
|
|
abort: new AbortController().signal,
|
|
auto: true,
|
|
overflow: true,
|
|
})
|
|
|
|
const last = (await Session.messages({ sessionID: session.id })).at(-1)
|
|
|
|
expect(result).toBe("continue")
|
|
expect(last?.info.role).toBe("user")
|
|
expect(last?.parts.some((part) => part.type === "file")).toBe(false)
|
|
expect(
|
|
last?.parts.some((part) => part.type === "text" && part.text.includes("Attached image/png: cat.png")),
|
|
).toBe(true)
|
|
},
|
|
})
|
|
})
|
|
|
|
test("falls back to overflow guidance when no replayable turn exists", async () => {
|
|
await using tmp = await tmpdir()
|
|
await Instance.provide({
|
|
directory: tmp.path,
|
|
fn: async () => {
|
|
spyOn(ProviderModule.Provider, "getModel").mockResolvedValue(createModel({ context: 100_000, output: 32_000 }))
|
|
spyOn(SessionProcessorModule.SessionProcessor, "create").mockImplementation((input) => fake(input, "continue"))
|
|
|
|
const session = await Session.create({})
|
|
await user(session.id, "earlier")
|
|
const msg = await user(session.id, "current")
|
|
|
|
const result = await SessionCompaction.process({
|
|
parentID: msg.id,
|
|
messages: await Session.messages({ sessionID: session.id }),
|
|
sessionID: session.id,
|
|
abort: new AbortController().signal,
|
|
auto: true,
|
|
overflow: true,
|
|
})
|
|
|
|
const last = (await Session.messages({ sessionID: session.id })).at(-1)
|
|
|
|
expect(result).toBe("continue")
|
|
expect(last?.info.role).toBe("user")
|
|
if (last?.parts[0]?.type === "text") {
|
|
expect(last.parts[0].text).toContain("previous request exceeded the provider's size limit")
|
|
}
|
|
},
|
|
})
|
|
})
|
|
})
|
|
|
|
describe("util.token.estimate", () => {
|
|
test("estimates tokens from text (4 chars per token)", () => {
|
|
const text = "x".repeat(4000)
|
|
expect(Token.estimate(text)).toBe(1000)
|
|
})
|
|
|
|
test("estimates tokens from larger text", () => {
|
|
const text = "y".repeat(20_000)
|
|
expect(Token.estimate(text)).toBe(5000)
|
|
})
|
|
|
|
test("returns 0 for empty string", () => {
|
|
expect(Token.estimate("")).toBe(0)
|
|
})
|
|
})
|
|
|
|
describe("session.getUsage", () => {
|
|
test("normalizes standard usage to token format", () => {
|
|
const model = createModel({ context: 100_000, output: 32_000 })
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 1000,
|
|
outputTokens: 500,
|
|
totalTokens: 1500,
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.input).toBe(1000)
|
|
expect(result.tokens.output).toBe(500)
|
|
expect(result.tokens.reasoning).toBe(0)
|
|
expect(result.tokens.cache.read).toBe(0)
|
|
expect(result.tokens.cache.write).toBe(0)
|
|
})
|
|
|
|
test("extracts cached tokens to cache.read", () => {
|
|
const model = createModel({ context: 100_000, output: 32_000 })
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 1000,
|
|
outputTokens: 500,
|
|
totalTokens: 1500,
|
|
cachedInputTokens: 200,
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.input).toBe(800)
|
|
expect(result.tokens.cache.read).toBe(200)
|
|
})
|
|
|
|
test("handles anthropic cache write metadata", () => {
|
|
const model = createModel({ context: 100_000, output: 32_000 })
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 1000,
|
|
outputTokens: 500,
|
|
totalTokens: 1500,
|
|
},
|
|
metadata: {
|
|
anthropic: {
|
|
cacheCreationInputTokens: 300,
|
|
},
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.cache.write).toBe(300)
|
|
})
|
|
|
|
test("does not subtract cached tokens for anthropic provider", () => {
|
|
const model = createModel({ context: 100_000, output: 32_000 })
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 1000,
|
|
outputTokens: 500,
|
|
totalTokens: 1500,
|
|
cachedInputTokens: 200,
|
|
},
|
|
metadata: {
|
|
anthropic: {},
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.input).toBe(1000)
|
|
expect(result.tokens.cache.read).toBe(200)
|
|
})
|
|
|
|
test("handles reasoning tokens", () => {
|
|
const model = createModel({ context: 100_000, output: 32_000 })
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 1000,
|
|
outputTokens: 500,
|
|
totalTokens: 1500,
|
|
reasoningTokens: 100,
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.reasoning).toBe(100)
|
|
})
|
|
|
|
test("handles undefined optional values gracefully", () => {
|
|
const model = createModel({ context: 100_000, output: 32_000 })
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 0,
|
|
outputTokens: 0,
|
|
totalTokens: 0,
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.input).toBe(0)
|
|
expect(result.tokens.output).toBe(0)
|
|
expect(result.tokens.reasoning).toBe(0)
|
|
expect(result.tokens.cache.read).toBe(0)
|
|
expect(result.tokens.cache.write).toBe(0)
|
|
expect(Number.isNaN(result.cost)).toBe(false)
|
|
})
|
|
|
|
test("calculates cost correctly", () => {
|
|
const model = createModel({
|
|
context: 100_000,
|
|
output: 32_000,
|
|
cost: {
|
|
input: 3,
|
|
output: 15,
|
|
cache: { read: 0.3, write: 3.75 },
|
|
},
|
|
})
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage: {
|
|
inputTokens: 1_000_000,
|
|
outputTokens: 100_000,
|
|
totalTokens: 1_100_000,
|
|
},
|
|
})
|
|
|
|
expect(result.cost).toBe(3 + 1.5)
|
|
})
|
|
|
|
test.each(["@ai-sdk/anthropic", "@ai-sdk/amazon-bedrock", "@ai-sdk/google-vertex/anthropic"])(
|
|
"computes total from components for %s models",
|
|
(npm) => {
|
|
const model = createModel({ context: 100_000, output: 32_000, npm })
|
|
const usage = {
|
|
inputTokens: 1000,
|
|
outputTokens: 500,
|
|
// These providers typically report total as input + output only,
|
|
// excluding cache read/write.
|
|
totalTokens: 1500,
|
|
cachedInputTokens: 200,
|
|
}
|
|
if (npm === "@ai-sdk/amazon-bedrock") {
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage,
|
|
metadata: {
|
|
bedrock: {
|
|
usage: {
|
|
cacheWriteInputTokens: 300,
|
|
},
|
|
},
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.input).toBe(1000)
|
|
expect(result.tokens.cache.read).toBe(200)
|
|
expect(result.tokens.cache.write).toBe(300)
|
|
expect(result.tokens.total).toBe(2000)
|
|
return
|
|
}
|
|
|
|
const result = Session.getUsage({
|
|
model,
|
|
usage,
|
|
metadata: {
|
|
anthropic: {
|
|
cacheCreationInputTokens: 300,
|
|
},
|
|
},
|
|
})
|
|
|
|
expect(result.tokens.input).toBe(1000)
|
|
expect(result.tokens.cache.read).toBe(200)
|
|
expect(result.tokens.cache.write).toBe(300)
|
|
expect(result.tokens.total).toBe(2000)
|
|
},
|
|
)
|
|
})
|