opencode/packages/ai/test/provider/anthropic-messages-cache.recorded.test.ts
2026-07-24 18:02:35 +00:00

110 lines
4.2 KiB
TypeScript

import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { CacheHint, LLM, LLMRequest, Message, ToolCallPart, ToolDefinition } from "../../src"
import { LLMClient } from "../../src/route"
import * as Anthropic from "../../src/providers/anthropic"
import { LARGE_CACHEABLE_SYSTEM } from "../recorded-scenarios"
import { recordedTests } from "../recorded-test"
const model = Anthropic.configure({
apiKey: process.env.ANTHROPIC_API_KEY ?? "fixture",
}).model("claude-haiku-4-5-20251001")
// Two identical generations in a row. The first call writes the prefix into
// Anthropic's cache; the second should report a cache read against the same
// prefix. Cassette captures both interactions in order.
const cacheRequest = LLM.request({
id: "recorded_anthropic_cache",
model,
system: [{ type: "text", text: LARGE_CACHEABLE_SYSTEM, cache: new CacheHint({ type: "ephemeral" }) }],
prompt: "Say hi.",
// Manual hint on the system part is the only marker we want here — skip the
// auto-policy's latest-user-message breakpoint so the cassette body matches.
cache: "none",
generation: { maxTokens: 16, temperature: 0 },
})
const lookup = ToolDefinition.make({
name: "lookup",
description: "Look up a fixture value.",
inputSchema: {
type: "object",
properties: { index: { type: "number" } },
required: ["index"],
additionalProperties: false,
},
})
const longToolTurn = [
Message.user("Run the fixture lookups."),
...Array.from({ length: 11 }, (_, index) => {
const id = `lookup_${index}`
return [
Message.assistant(ToolCallPart.make({ id, name: lookup.name, input: { index } })),
Message.tool({
id,
name: lookup.name,
result: `Fixture result ${index}. `.repeat(80),
}),
]
}).flat(),
]
const longToolTurnRequest = LLM.request({
id: "recorded_anthropic_cache_long_tool_turn",
model,
system: LARGE_CACHEABLE_SYSTEM,
messages: longToolTurn,
tools: [lookup],
generation: { maxTokens: 16, temperature: 0 },
})
const recorded = recordedTests({
prefix: "anthropic-messages-cache",
provider: "anthropic",
protocol: "anthropic-messages",
requires: ["ANTHROPIC_API_KEY"],
// Two identical requests in one cassette — replay walks the cassette in
// recording order so the second call replays the cached-hit interaction.
options: {
redact: { allowRequestHeaders: ["anthropic-version"] },
},
})
describe("Anthropic Messages cache recorded", () => {
recorded.effect.with("writes then reads cache_control on identical second call", { tags: ["cache"] }, () =>
Effect.gen(function* () {
const first = yield* LLMClient.generate(cacheRequest)
// The first call may write the cache (cacheWriteInputTokens > 0) or it
// may be a fresh miss (both fields 0) depending on whether the prefix is
// already warm on Anthropic's side. The assertion that matters is that
// the SECOND call reports a non-zero cache read.
expect(first.usage?.cacheReadInputTokens ?? 0).toBeGreaterThanOrEqual(0)
const second = yield* LLMClient.generate(cacheRequest)
expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThan(0)
}),
)
recorded.effect.with("keeps a long tool turn inside the cache lookback", { tags: ["cache", "tool"] }, () =>
Effect.gen(function* () {
const first = yield* LLMClient.generate(longToolTurnRequest)
const firstRead = first.usage?.cacheReadInputTokens ?? 0
const firstWrite = first.usage?.cacheWriteInputTokens ?? 0
const firstCached = firstRead + firstWrite
// The prefix may already be warm when recording, so either a read or a
// write establishes that Anthropic recognized the cache boundary.
expect(firstCached).toBeGreaterThan(0)
const second = yield* LLMClient.generate(
LLMRequest.update(longToolTurnRequest, {
messages: [
...longToolTurn,
Message.assistant("The fixture lookups are complete."),
Message.user("Reply exactly: OK"),
],
}),
)
expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThanOrEqual(firstCached)
expect(second.usage?.cacheWriteInputTokens ?? 0).toBeLessThan(firstCached)
}),
)
})