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+import { describe, it, expect } from "vitest";
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+
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+// 由于 extractUsageMetrics 是内部函数，需要通过 parseUsageFromResponseText 间接测试
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+// 或者将其导出用于测试
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+// 这里我们通过构造 JSON 响应来测试 parseUsageFromResponseText
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+
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+import { parseUsageFromResponseText } from "@/app/v1/_lib/proxy/response-handler";
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+
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+describe("extractUsageMetrics", () => {
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+ describe("基本 token 提取", () => {
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+ it("应正确提取 input_tokens 和 output_tokens", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ input_tokens: 1000,
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+ output_tokens: 500,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics).not.toBeNull();
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+ expect(result.usageMetrics?.input_tokens).toBe(1000);
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+ expect(result.usageMetrics?.output_tokens).toBe(500);
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+ });
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+
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+ it("空值或非对象应返回 null", () => {
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+ expect(parseUsageFromResponseText("", "claude").usageMetrics).toBeNull();
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+ expect(parseUsageFromResponseText("null", "claude").usageMetrics).toBeNull();
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+ expect(parseUsageFromResponseText('"string"', "claude").usageMetrics).toBeNull();
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+ });
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+ });
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+
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+ describe("Claude 嵌套格式 (cache_creation.ephemeral_*)", () => {
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+ it("应从 cache_creation 嵌套对象提取 5m 和 1h token", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ input_tokens: 1000,
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+ output_tokens: 500,
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+ cache_creation_input_tokens: 800,
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 300,
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+ ephemeral_1h_input_tokens: 500,
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+ },
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+ cache_read_input_tokens: 200,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics).not.toBeNull();
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+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(800);
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(200);
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+ expect(result.usageMetrics?.cache_ttl).toBe("mixed");
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+ });
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+
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+ it("只有 5m 时应推断 cache_ttl 为 5m", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_input_tokens: 300,
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 300,
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+ },
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBeUndefined();
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+ expect(result.usageMetrics?.cache_ttl).toBe("5m");
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+ });
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+
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+ it("只有 1h 时应推断 cache_ttl 为 1h", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_input_tokens: 500,
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+ cache_creation: {
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+ ephemeral_1h_input_tokens: 500,
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+ },
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBeUndefined();
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+ expect(result.usageMetrics?.cache_ttl).toBe("1h");
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+ });
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+ });
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+
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+ describe("旧 relay 格式 (claude_cache_creation_*)", () => {
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+ it("应从旧 relay 字段提取 5m 和 1h token", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ input_tokens: 1000,
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+ output_tokens: 500,
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+ cache_creation_input_tokens: 800,
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+ claude_cache_creation_5_m_tokens: 300,
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+ claude_cache_creation_1_h_tokens: 500,
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+ cache_read_input_tokens: 200,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_ttl).toBe("mixed");
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+ });
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+
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+ it("嵌套格式应优先于旧 relay 格式", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 100,
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+ ephemeral_1h_input_tokens: 200,
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+ },
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+ claude_cache_creation_5_m_tokens: 999,
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+ claude_cache_creation_1_h_tokens: 888,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ // 嵌套格式优先
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(100);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(200);
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+ });
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+ });
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+
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+ describe("顶层扁平格式 (cache_creation_5m_input_tokens)", () => {
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+ it("应从顶层扁平字段提取 5m 和 1h token", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ input_tokens: 1000,
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+ output_tokens: 500,
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+ cache_creation_input_tokens: 800,
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+ cache_creation_5m_input_tokens: 300,
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+ cache_creation_1h_input_tokens: 500,
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+ cache_read_input_tokens: 200,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(800);
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(200);
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+ expect(result.usageMetrics?.cache_ttl).toBe("mixed");
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+ });
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+
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+ it("只有顶层 5m 时应正确提取并推断 TTL", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_input_tokens: 300,
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+ cache_creation_5m_input_tokens: 300,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_ttl).toBe("5m");
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+ });
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+
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+ it("只有顶层 1h 时应正确提取并推断 TTL", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_input_tokens: 500,
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+ cache_creation_1h_input_tokens: 500,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_ttl).toBe("1h");
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+ });
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+
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+ it("嵌套格式应优先于顶层扁平格式", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 100,
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+ ephemeral_1h_input_tokens: 200,
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+ },
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+ cache_creation_5m_input_tokens: 999,
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+ cache_creation_1h_input_tokens: 888,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ // 嵌套格式优先
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(100);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(200);
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+ });
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+
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+ it("顶层扁平格式应优先于旧 relay 格式", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_5m_input_tokens: 300,
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+ cache_creation_1h_input_tokens: 500,
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+ claude_cache_creation_5_m_tokens: 999,
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+ claude_cache_creation_1_h_tokens: 888,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ // 顶层扁平格式优先于旧 relay 格式
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(500);
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+ });
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+
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+ it("三种格式同时存在时应按优先级提取", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 100,
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+ ephemeral_1h_input_tokens: 200,
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+ },
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+ cache_creation_5m_input_tokens: 300,
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+ cache_creation_1h_input_tokens: 400,
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+ claude_cache_creation_5_m_tokens: 500,
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+ claude_cache_creation_1_h_tokens: 600,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ // 嵌套格式最优先
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(100);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(200);
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+ expect(result.usageMetrics?.cache_ttl).toBe("mixed");
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+ });
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+ });
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+
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+ describe("cache_creation_input_tokens 自动计算", () => {
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+ it("当 cache_creation_input_tokens 缺失时应自动计算总量", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 300,
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+ ephemeral_1h_input_tokens: 500,
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+ },
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(800);
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+ });
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+
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+ it("顶层扁平格式缺失 cache_creation_input_tokens 时应自动计算总量", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_5m_input_tokens: 400,
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+ cache_creation_1h_input_tokens: 600,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(1000);
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(400);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(600);
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+ });
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+
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+ it("混合回退：嵌套缺失某字段时顶层扁平补齐", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 200,
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+ // 缺失 ephemeral_1h_input_tokens
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+ },
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+ cache_creation_1h_input_tokens: 300, // 顶层扁平补齐
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ // 5m 来自嵌套，1h 来自顶层扁平
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+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(200);
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+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(300);
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+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_ttl).toBe("mixed");
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+ });
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+
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+ it("当 cache_creation_input_tokens 存在时不应覆盖", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ cache_creation_input_tokens: 1000,
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+ cache_creation: {
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+ ephemeral_5m_input_tokens: 300,
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+ ephemeral_1h_input_tokens: 500,
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+ },
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "claude");
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+
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+ // 保留原值
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+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(1000);
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+ });
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+ });
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+
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+ describe("Gemini 格式支持", () => {
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+ it("应正确提取 Gemini usage 字段", () => {
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+ const response = JSON.stringify({
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+ usageMetadata: {
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+ promptTokenCount: 1000,
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+ candidatesTokenCount: 500,
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+ cachedContentTokenCount: 200,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "gemini");
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+
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+ expect(result.usageMetrics).not.toBeNull();
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+ // input_tokens = promptTokenCount - cachedContentTokenCount
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+ expect(result.usageMetrics?.input_tokens).toBe(800);
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+ expect(result.usageMetrics?.output_tokens).toBe(500);
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+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(200);
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+ });
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+
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+ it("应正确处理 Gemini thoughtsTokenCount", () => {
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+ const response = JSON.stringify({
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+ usageMetadata: {
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+ promptTokenCount: 1000,
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+ candidatesTokenCount: 500,
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+ thoughtsTokenCount: 100,
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "gemini");
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+
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+ // output_tokens = candidatesTokenCount + thoughtsTokenCount
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+ expect(result.usageMetrics?.output_tokens).toBe(600);
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+ });
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+ });
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+
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+ describe("OpenAI Response API 格式", () => {
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+ it("应从 input_tokens_details.cached_tokens 提取缓存读取", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ input_tokens: 1000,
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+ output_tokens: 500,
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+ input_tokens_details: {
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+ cached_tokens: 200,
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+ },
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "openai");
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+
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+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(200);
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+ });
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+
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+ it("顶层 cache_read_input_tokens 应优先于嵌套格式", () => {
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+ const response = JSON.stringify({
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+ usage: {
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+ input_tokens: 1000,
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+ cache_read_input_tokens: 300,
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+ input_tokens_details: {
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+ cached_tokens: 200,
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+ },
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+ },
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+ });
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+
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+ const result = parseUsageFromResponseText(response, "openai");
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+
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+ // 顶层优先
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+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(300);
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+ });
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+ });
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+
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+ describe("SSE 流式响应解析", () => {
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+ it("应正确合并 message_start 和 message_delta 的 usage", () => {
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+ // 模拟 Claude SSE 流式响应
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+ const sseResponse = [
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+ "event: message_start",
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+ 'data: {"type":"message_start","message":{"usage":{"input_tokens":1000,"cache_creation_input_tokens":500,"cache_creation":{"ephemeral_5m_input_tokens":200,"ephemeral_1h_input_tokens":300},"cache_read_input_tokens":100}}}',
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|
|
+ "",
|
|
|
+ "event: message_delta",
|
|
|
+ 'data: {"type":"message_delta","usage":{"output_tokens":800}}',
|
|
|
+ "",
|
|
|
+ ].join("\n");
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(sseResponse, "claude");
|
|
|
+
|
|
|
+ expect(result.usageMetrics).not.toBeNull();
|
|
|
+ expect(result.usageMetrics?.input_tokens).toBe(1000);
|
|
|
+ expect(result.usageMetrics?.output_tokens).toBe(800);
|
|
|
+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(500);
|
|
|
+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(200);
|
|
|
+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(300);
|
|
|
+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(100);
|
|
|
+ });
|
|
|
+
|
|
|
+ it("message_delta 的值应优先于 message_start", () => {
|
|
|
+ const sseResponse = [
|
|
|
+ "event: message_start",
|
|
|
+ 'data: {"type":"message_start","message":{"usage":{"input_tokens":100,"output_tokens":50}}}',
|
|
|
+ "",
|
|
|
+ "event: message_delta",
|
|
|
+ 'data: {"type":"message_delta","usage":{"input_tokens":1000,"output_tokens":500}}',
|
|
|
+ "",
|
|
|
+ ].join("\n");
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(sseResponse, "claude");
|
|
|
+
|
|
|
+ // message_delta 优先
|
|
|
+ expect(result.usageMetrics?.input_tokens).toBe(1000);
|
|
|
+ expect(result.usageMetrics?.output_tokens).toBe(500);
|
|
|
+ });
|
|
|
+
|
|
|
+ it("message_start 的 cache 细分应补充 message_delta 缺失的字段", () => {
|
|
|
+ const sseResponse = [
|
|
|
+ "event: message_start",
|
|
|
+ 'data: {"type":"message_start","message":{"usage":{"cache_creation":{"ephemeral_5m_input_tokens":200,"ephemeral_1h_input_tokens":300}}}}',
|
|
|
+ "",
|
|
|
+ "event: message_delta",
|
|
|
+ 'data: {"type":"message_delta","usage":{"input_tokens":1000,"output_tokens":500,"cache_creation_input_tokens":500}}',
|
|
|
+ "",
|
|
|
+ ].join("\n");
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(sseResponse, "claude");
|
|
|
+
|
|
|
+ // message_delta 的值
|
|
|
+ expect(result.usageMetrics?.input_tokens).toBe(1000);
|
|
|
+ expect(result.usageMetrics?.output_tokens).toBe(500);
|
|
|
+ expect(result.usageMetrics?.cache_creation_input_tokens).toBe(500);
|
|
|
+ // message_start 补充的细分字段
|
|
|
+ expect(result.usageMetrics?.cache_creation_5m_input_tokens).toBe(200);
|
|
|
+ expect(result.usageMetrics?.cache_creation_1h_input_tokens).toBe(300);
|
|
|
+ });
|
|
|
+ });
|
|
|
+
|
|
|
+ describe("Codex provider 特殊处理", () => {
|
|
|
+ it("Codex 应从 input_tokens 中减去 cached_tokens", () => {
|
|
|
+ const response = JSON.stringify({
|
|
|
+ usage: {
|
|
|
+ input_tokens: 1000,
|
|
|
+ output_tokens: 500,
|
|
|
+ cache_read_input_tokens: 300,
|
|
|
+ },
|
|
|
+ });
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(response, "codex");
|
|
|
+
|
|
|
+ // adjustUsageForProviderType 会调整 input_tokens
|
|
|
+ expect(result.usageMetrics?.input_tokens).toBe(700); // 1000 - 300
|
|
|
+ expect(result.usageMetrics?.cache_read_input_tokens).toBe(300);
|
|
|
+ });
|
|
|
+ });
|
|
|
+
|
|
|
+ describe("边界情况", () => {
|
|
|
+ it("应处理所有值为 0 的情况", () => {
|
|
|
+ const response = JSON.stringify({
|
|
|
+ usage: {
|
|
|
+ input_tokens: 0,
|
|
|
+ output_tokens: 0,
|
|
|
+ cache_creation_input_tokens: 0,
|
|
|
+ cache_read_input_tokens: 0,
|
|
|
+ },
|
|
|
+ });
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(response, "claude");
|
|
|
+
|
|
|
+ expect(result.usageMetrics).not.toBeNull();
|
|
|
+ expect(result.usageMetrics?.input_tokens).toBe(0);
|
|
|
+ expect(result.usageMetrics?.output_tokens).toBe(0);
|
|
|
+ });
|
|
|
+
|
|
|
+ it("应处理部分字段缺失的情况", () => {
|
|
|
+ const response = JSON.stringify({
|
|
|
+ usage: {
|
|
|
+ input_tokens: 1000,
|
|
|
+ },
|
|
|
+ });
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(response, "claude");
|
|
|
+
|
|
|
+ expect(result.usageMetrics?.input_tokens).toBe(1000);
|
|
|
+ expect(result.usageMetrics?.output_tokens).toBeUndefined();
|
|
|
+ expect(result.usageMetrics?.cache_creation_input_tokens).toBeUndefined();
|
|
|
+ });
|
|
|
+
|
|
|
+ it("应处理无效的 JSON", () => {
|
|
|
+ const result = parseUsageFromResponseText("invalid json", "claude");
|
|
|
+
|
|
|
+ expect(result.usageMetrics).toBeNull();
|
|
|
+ });
|
|
|
+
|
|
|
+ it("应处理空的 usage 对象", () => {
|
|
|
+ const response = JSON.stringify({
|
|
|
+ usage: {},
|
|
|
+ });
|
|
|
+
|
|
|
+ const result = parseUsageFromResponseText(response, "claude");
|
|
|
+
|
|
|
+ expect(result.usageMetrics).toBeNull();
|
|
|
+ });
|
|
|
+ });
|
|
|
+});
|
ding113