fix(stats): better stat table periods, provider/model norm

packages/stats/core/src/domain/inference.test.ts

@@ -0,0 +1,66 @@
+import { describe, expect, test } from "bun:test"
+import { toModelAggregate } from "./inference"
+import { modelAuthor, normalizeInferenceModel } from "./model-normalization"
+
+describe("inference stat normalization", () => {
+  test("normalizes model suffixes used by router/provider variants", () => {
+    expect(normalizeInferenceModel("deepseek-v4-flash-free")).toBe("deepseek-v4-flash")
+    expect(normalizeInferenceModel("deepseek-v4-flash:global")).toBe("deepseek-v4-flash")
+    expect(normalizeInferenceModel("mimo-v2.5-free")).toBe("mimo-v2.5")
+    expect(normalizeInferenceModel("nemotron-3-super-free")).toBe("nemotron-3-super")
+    expect(normalizeInferenceModel("mimo-v2.5-free:global")).toBe("mimo-v2.5")
+  })
+
+  test("maps normalized model ids to public authors", () => {
+    expect(modelAuthor("big-pickle")).toBe("opencode")
+    expect(modelAuthor("claude-sonnet-4-5")).toBe("anthropic")
+    expect(modelAuthor("deepseek-v4-pro")).toBe("deepseek")
+    expect(modelAuthor("gemini-3.5-flash")).toBe("google")
+    expect(modelAuthor("glm-5.1")).toBe("zhipu")
+    expect(modelAuthor("gpt-5.5-pro")).toBe("openai")
+    expect(modelAuthor("grok-build-0.1")).toBe("xai")
+    expect(modelAuthor("hy3-preview")).toBe("tencent")
+    expect(modelAuthor("kimi-k2.6")).toBe("moonshot")
+    expect(modelAuthor("mimo-v2-omni")).toBe("xiaomi")
+    expect(modelAuthor("minimax-m2.7")).toBe("minimax")
+    expect(modelAuthor("nemotron-3-super-free")).toBe("nvidia")
+    expect(modelAuthor("qwen3.7-max")).toBe("qwen")
+    expect(modelAuthor("alpha-gpt-next")).toBeUndefined()
+  })
+
+  test("model aggregates ignore datalake provider and use normalized author/model", () => {
+    expect(toModelAggregate(aggregate("alpha-gpt-next", "openai"))).toEqual([])
+
+    expect(toModelAggregate(aggregate("deepseek-v4-flash-free", "not-public-provider"))).toMatchObject([
+      {
+        period_key: "2026-05-20",
+        provider: "deepseek",
+        model: "deepseek-v4-flash",
+      },
+    ])
+  })
+
+  test("model aggregates use ISO week period keys", () => {
+    expect(
+      toModelAggregate({
+        ...aggregate("gpt-5.5-pro", "openai"),
+        grain: "week",
+        period_key: "2026-W20",
+      }),
+    ).toMatchObject([{ period_key: "2026-W20" }])
+  })
+})
+
+function aggregate(model: string, provider: string) {
+  return {
+    grain: "day",
+    period_key: "2026-05-20",
+    dataset: "zen",
+    tier: "Paid",
+    provider,
+    model,
+    sessions: "1",
+    requests: "1",
+    sample_count: "1",
+  }
+}