File size: 3,519 Bytes
5f24abe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | import { describe, expect, test } from "bun:test"
import type { ZenData } from "@opencode-ai/console-core/model.js"
import type { ProviderHelper } from "../src/routes/zen/util/provider/provider"
import { anthropicHelper } from "../src/routes/zen/util/provider/anthropic"
import { googleHelper } from "../src/routes/zen/util/provider/google"
import { oaCompatHelper } from "../src/routes/zen/util/provider/openai-compatible"
import { openaiHelper } from "../src/routes/zen/util/provider/openai"
const providers = {
anthropic: anthropicHelper({ reqModel: "claude-haiku-4-5", providerModel: "claude-haiku-4-5" }),
google: googleHelper({ reqModel: "gemini-3-flash", providerModel: "gemini-3-flash" }),
openai: openaiHelper({ reqModel: "gpt-5", providerModel: "gpt-5" }),
"oa-compat": oaCompatHelper({ reqModel: "gpt-5-nano", providerModel: "gpt-5-nano" }),
} satisfies Record<ZenData.Format, ReturnType<ProviderHelper>>
describe("provider usage extraction", () => {
test("extracts Google non-stream usage metadata", () => {
const usage = providers.google.extractUsage({
usageMetadata: {
promptTokenCount: 10,
candidatesTokenCount: 3,
thoughtsTokenCount: 2,
cachedContentTokenCount: 4,
},
})
expect(providers.google.normalizeUsage(usage)).toEqual({
inputTokens: 6,
outputTokens: 5,
reasoningTokens: 2,
cacheReadTokens: 4,
cacheWrite5mTokens: undefined,
cacheWrite1hTokens: undefined,
})
})
test("parses Google stream usage metadata", () => {
const usageParser = providers.google.createUsageParser()
usageParser.parse(
'data: {"usageMetadata":{"promptTokenCount":10,"candidatesTokenCount":3,"thoughtsTokenCount":2,"cachedContentTokenCount":4}}',
)
expect(providers.google.normalizeUsage(usageParser.retrieve())).toEqual({
inputTokens: 6,
outputTokens: 5,
reasoningTokens: 2,
cacheReadTokens: 4,
cacheWrite5mTokens: undefined,
cacheWrite1hTokens: undefined,
})
})
test("extracts nested OpenAI Responses usage", () => {
expect(
providers.openai.extractUsage({
response: {
usage: {
input_tokens: 5,
output_tokens: 7,
},
},
}),
).toEqual({
input_tokens: 5,
output_tokens: 7,
})
})
test("parses OpenAI stream cache write usage", () => {
const usageParser = providers.openai.createUsageParser()
usageParser.parse(
'event: response.completed\ndata: {"response":{"usage":{"input_tokens":10,"input_tokens_details":{"cached_tokens":4,"cache_write_tokens":3},"output_tokens":2}}}',
)
expect(providers.openai.normalizeUsage(usageParser.retrieve())).toEqual({
inputTokens: 3,
outputTokens: 2,
reasoningTokens: undefined,
cacheReadTokens: 4,
cacheWrite5mTokens: 3,
cacheWrite1hTokens: undefined,
})
})
test("clamps input tokens when detail fields overlap", () => {
const usageParser = providers.openai.createUsageParser()
usageParser.parse(
'event: response.completed\ndata: {"response":{"usage":{"input_tokens":5,"input_tokens_details":{"cached_tokens":4,"cache_write_tokens":3},"output_tokens":2}}}',
)
expect(providers.openai.normalizeUsage(usageParser.retrieve())).toEqual({
inputTokens: 0,
outputTokens: 2,
reasoningTokens: undefined,
cacheReadTokens: 4,
cacheWrite5mTokens: 3,
cacheWrite1hTokens: undefined,
})
})
})
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