fix(ai): preserve cache_write_tokens in completions stream usage closes #2802

This commit is contained in:
Mario Zechner
2026-04-04 21:39:11 +02:00
parent a7acef92a7
commit 6044cabb15
4 changed files with 185 additions and 8 deletions

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@@ -2,6 +2,10 @@
## [Unreleased]
### Fixed
- Fixed OpenAI-compatible completions streaming usage to preserve `prompt_tokens_details.cache_write_tokens` and normalize OpenRouter `cached_tokens` to previous-request cache hits only, preventing cache read/write double counting in `usage` and cost calculation ([#2802](https://github.com/badlogic/pi-mono/issues/2802))
## [0.65.0] - 2026-04-03
### Added

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@@ -734,24 +734,34 @@ function parseChunkUsage(
rawUsage: {
prompt_tokens?: number;
completion_tokens?: number;
prompt_tokens_details?: { cached_tokens?: number };
prompt_tokens_details?: { cached_tokens?: number; cache_write_tokens?: number };
completion_tokens_details?: { reasoning_tokens?: number };
},
model: Model<"openai-completions">,
): AssistantMessage["usage"] {
const cachedTokens = rawUsage.prompt_tokens_details?.cached_tokens || 0;
const promptTokens = rawUsage.prompt_tokens || 0;
const reportedCachedTokens = rawUsage.prompt_tokens_details?.cached_tokens || 0;
const cacheWriteTokens = rawUsage.prompt_tokens_details?.cache_write_tokens || 0;
const reasoningTokens = rawUsage.completion_tokens_details?.reasoning_tokens || 0;
// OpenAI includes cached tokens in prompt_tokens, so subtract to get non-cached input
const input = (rawUsage.prompt_tokens || 0) - cachedTokens;
// Normalize to pi-ai semantics:
// - cacheRead: hits from cache created by previous requests only
// - cacheWrite: tokens written to cache in this request
// Some OpenAI-compatible providers (observed on OpenRouter) report cached_tokens
// as (previous hits + current writes). In that case, remove cacheWrite from cacheRead.
const cacheReadTokens =
cacheWriteTokens > 0 ? Math.max(0, reportedCachedTokens - cacheWriteTokens) : reportedCachedTokens;
const input = Math.max(0, promptTokens - cacheReadTokens - cacheWriteTokens);
// Compute totalTokens ourselves since we add reasoning_tokens to output
// and some providers (e.g., Groq) don't include them in total_tokens
const outputTokens = (rawUsage.completion_tokens || 0) + reasoningTokens;
const usage: AssistantMessage["usage"] = {
input,
output: outputTokens,
cacheRead: cachedTokens,
cacheWrite: 0,
totalTokens: input + outputTokens + cachedTokens,
cacheRead: cacheReadTokens,
cacheWrite: cacheWriteTokens,
totalTokens: input + outputTokens + cacheReadTokens + cacheWriteTokens,
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
};
calculateCost(model, usage);

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@@ -13,7 +13,7 @@ const mockState = vi.hoisted(() => ({
usage?: {
prompt_tokens: number;
completion_tokens: number;
prompt_tokens_details: { cached_tokens: number };
prompt_tokens_details: { cached_tokens: number; cache_write_tokens?: number };
completion_tokens_details: { reasoning_tokens: number };
};
}>
@@ -430,6 +430,91 @@ describe("openai-completions tool_choice", () => {
expect(response.content).toEqual([{ type: "text", text: "OK" }]);
});
it("preserves prompt_tokens_details.cache_write_tokens from chunk usage", async () => {
mockState.chunks = [
{
id: "chatcmpl-cache-write",
choices: [{ delta: { content: "OK" }, finish_reason: null }],
},
{
id: "chatcmpl-cache-write",
choices: [{ delta: {}, finish_reason: "stop" }],
usage: {
prompt_tokens: 100,
completion_tokens: 5,
prompt_tokens_details: { cached_tokens: 50, cache_write_tokens: 30 },
completion_tokens_details: { reasoning_tokens: 0 },
},
},
];
const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
const model = { ...baseModel, api: "openai-completions" } as const;
const response = await streamSimple(
model,
{
messages: [
{
role: "user",
content: "Reply with exactly OK",
timestamp: Date.now(),
},
],
},
{ apiKey: "test" },
).result();
expect(response.usage.input).toBe(50);
expect(response.usage.cacheRead).toBe(20);
expect(response.usage.cacheWrite).toBe(30);
expect(response.usage.totalTokens).toBe(105);
});
it("preserves prompt_tokens_details.cache_write_tokens from choice usage fallback", async () => {
mockState.chunks = [
{
id: "chatcmpl-cache-write-choice",
choices: [{ delta: { content: "OK" }, finish_reason: null }],
},
{
id: "chatcmpl-cache-write-choice",
choices: [
{
delta: {},
finish_reason: "stop",
usage: {
prompt_tokens: 100,
completion_tokens: 5,
prompt_tokens_details: { cached_tokens: 50, cache_write_tokens: 30 },
completion_tokens_details: { reasoning_tokens: 0 },
},
},
],
},
];
const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
const model = { ...baseModel, api: "openai-completions" } as const;
const response = await streamSimple(
model,
{
messages: [
{
role: "user",
content: "Reply with exactly OK",
timestamp: Date.now(),
},
],
},
{ apiKey: "test" },
).result();
expect(response.usage.input).toBe(50);
expect(response.usage.cacheRead).toBe(20);
expect(response.usage.cacheWrite).toBe(30);
expect(response.usage.totalTokens).toBe(105);
});
it("uses OpenRouter reasoning object instead of reasoning_effort", async () => {
const model = getModel("openrouter", "deepseek/deepseek-r1")!;
let payload: unknown;

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@@ -0,0 +1,78 @@
import { describe, expect, it } from "vitest";
import { getModel } from "../src/models.js";
import { completeSimple } from "../src/stream.js";
function createLongSystemPrompt(): string {
const nonce = `${Date.now()}-${Math.random()}`;
return `You are a concise assistant.\nCache nonce: ${nonce}\n\n${Array(80)
.fill(
"Prompt-caching probe content. Keep this exact text stable across requests so the provider can reuse prefix tokens and report cache read and cache write usage.",
)
.join("\n\n")}`;
}
describe.skipIf(!process.env.OPENROUTER_API_KEY)("OpenRouter cache_write repro E2E", () => {
it(
"regression: preserves cache_write_tokens on openai-completions stream path",
{ retry: 2, timeout: 90000 },
async () => {
const model = getModel("openrouter", "google/gemini-2.5-flash");
const context = {
systemPrompt: createLongSystemPrompt(),
messages: [
{
role: "user" as const,
content: "Reply with exactly: OK",
timestamp: Date.now(),
},
],
};
const options = {
apiKey: process.env.OPENROUTER_API_KEY!,
maxTokens: 32,
temperature: 0,
onPayload: (payload: unknown) => {
const params = payload as {
messages?: Array<{
role?: string;
content?: string | Array<{ type?: string; text?: string; cache_control?: { type: string } }>;
}>;
};
const messages = params.messages;
if (!Array.isArray(messages)) return payload;
for (let i = messages.length - 1; i >= 0; i--) {
const msg = messages[i];
if (msg.role !== "user") continue;
if (typeof msg.content === "string") {
msg.content = [{ type: "text", text: msg.content, cache_control: { type: "ephemeral" } }];
break;
}
if (!Array.isArray(msg.content)) continue;
for (let j = msg.content.length - 1; j >= 0; j--) {
const part = msg.content[j];
if (part.type === "text") {
part.cache_control = { type: "ephemeral" };
break;
}
}
break;
}
return payload;
},
};
const first = await completeSimple(model, context, options);
expect(first.stopReason, first.errorMessage).toBe("stop");
const second = await completeSimple(model, context, options);
expect(second.stopReason, second.errorMessage).toBe("stop");
// Regression expectation: cache_write_tokens from provider usage must be preserved.
// With the cache_control marker above, at least one of the two calls should create cache.
const hasCacheWrite = first.usage.cacheWrite > 0 || second.usage.cacheWrite > 0;
expect(hasCacheWrite).toBe(true);
},
);
});