chore: import upstream snapshot with attribution

tests/unit/opencode-zen-alias-combo-e2e.test.ts

@@ -0,0 +1,208 @@
+/**
+ * End-to-end runtime test for the opencode-zen ↔ opencode alias fix.
+ *
+ * Proves that the full catalog chain — buildComboCatalogMetadata →
+ * getComboTargetCatalogMetadata → getCanonicalModelMetadata →
+ * getSyncedCapability — returns the correct context window for combos
+ * whose targets are stored under the historical "opencode-zen" provider
+ * key in model_capabilities.
+ *
+ * This test uses the REAL catalog code paths with an in-memory DB. The
+ * only mocked piece is the persistence layer (DB) itself.
+ */
+
+import { describe, it, before, after } from "node:test";
+import assert from "node:assert/strict";
+import fs from "node:fs";
+import os from "node:os";
+import path from "node:path";
+
+const TEST_DATA_DIR = fs.mkdtempSync(path.join(os.tmpdir(), "omniroute-combo-e2e-"));
+process.env.DATA_DIR = TEST_DATA_DIR;
+
+const core = await import("../../src/lib/db/core.ts");
+const modelsDevSync = await import("../../src/lib/modelsDevSync.ts");
+const registry = await import("../../src/lib/modelMetadataRegistry.ts");
+
+// ─── Real-world fixtures ────────────────────────────────────────────────
+// These mirror the actual data that models.dev ships today for the
+// "opencode" provider, and how the previous sync wrote it under the
+// "opencode-zen" alias.
+
+const REAL_OPENCODE_DATA = {
+  "big-pickle": {
+    tool_call: true,
+    reasoning: true,
+    attachment: false,
+    structured_output: true,
+    temperature: true,
+    modalities_input: JSON.stringify(["text"]),
+    modalities_output: JSON.stringify(["text"]),
+    knowledge_cutoff: "2025-04",
+    release_date: "2025-04-15",
+    last_updated: "2025-05-01",
+    status: "alpha",
+    family: "big-pickle",
+    open_weights: false,
+    limit_context: 200000,
+    limit_input: 200000,
+    limit_output: 128000,
+    interleaved_field: null,
+  },
+  "gpt-5-nano": {
+    tool_call: true,
+    reasoning: true,
+    attachment: true,
+    structured_output: true,
+    temperature: false,
+    modalities_input: JSON.stringify(["text", "image"]),
+    modalities_output: JSON.stringify(["text"]),
+    knowledge_cutoff: "2025-04",
+    release_date: "2025-04-15",
+    last_updated: "2025-05-01",
+    status: "alpha",
+    family: "gpt-5",
+    open_weights: false,
+    limit_context: 400000,
+    limit_input: 400000,
+    limit_output: 128000,
+    interleaved_field: null,
+  },
+  "minimax-m2": {
+    tool_call: true,
+    reasoning: true,
+    attachment: false,
+    structured_output: true,
+    temperature: true,
+    modalities_input: JSON.stringify(["text"]),
+    modalities_output: JSON.stringify(["text"]),
+    knowledge_cutoff: "2025-04",
+    release_date: "2025-04-15",
+    last_updated: "2025-05-01",
+    status: "alpha",
+    family: "minimax",
+    open_weights: false,
+    limit_context: 200000,
+    limit_input: 200000,
+    limit_output: 128000,
+    interleaved_field: null,
+  },
+  "kimi-k2": {
+    tool_call: true,
+    reasoning: false,
+    attachment: false,
+    structured_output: true,
+    temperature: true,
+    modalities_input: JSON.stringify(["text"]),
+    modalities_output: JSON.stringify(["text"]),
+    knowledge_cutoff: "2025-04",
+    release_date: "2025-04-15",
+    last_updated: "2025-05-01",
+    status: "alpha",
+    family: "kimi",
+    open_weights: false,
+    limit_context: 200000,
+    limit_input: 200000,
+    limit_output: 128000,
+    interleaved_field: null,
+  },
+};
+
+// ─── Lifecycle ───────────────────────────────────────────────────────────
+
+before(async () => {
+  // Seed the DB exactly the way the previous sync wrote it: under the
+  // historical "opencode-zen" alias, NOT under "opencode".
+  modelsDevSync.saveModelsDevCapabilities({
+    "opencode-zen": REAL_OPENCODE_DATA,
+  });
+});
+
+after(async () => {
+  core.resetDbInstance();
+  fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true });
+});
+
+// ─── Tests ──────────────────────────────────────────────────────────────
+
+describe("opencode-zen ↔ opencode alias fix (end-to-end)", () => {
+  it("getSyncedCapability('opencode', 'big-pickle') finds data stored under 'opencode-zen'", () => {
+    // Pre-fix: returns null (the bug)
+    // Post-fix: returns the opencode-zen row
+    const cap = modelsDevSync.getSyncedCapability("opencode", "big-pickle");
+    assert.ok(cap, "expected the alias fallback to find the opencode-zen row");
+    assert.equal(cap?.limit_context, 200000);
+    assert.equal(cap?.limit_output, 128000);
+  });
+
+  it("getSyncedCapability('opencode', 'gpt-5-nano') finds the 400K context row", () => {
+    const cap = modelsDevSync.getSyncedCapability("opencode", "gpt-5-nano");
+    assert.ok(cap);
+    assert.equal(cap?.limit_context, 400000);
+  });
+
+  it("getCanonicalModelMetadata({provider:'opencode', model:'big-pickle'}) returns full metadata", () => {
+    const md = registry.getCanonicalModelMetadata({
+      provider: "opencode",
+      model: "big-pickle",
+    });
+    assert.ok(md, "expected metadata to be found via the alias fallback");
+    // The `provider` field gets resolved by resolveCanonicalProviderModel;
+    // what matters for the catalog is the context window. The fix ensures
+    // the opencode-zen row is found, so contextWindow is 200k.
+    assert.equal(md?.model, "big-pickle");
+    assert.equal(md?.limits.contextWindow, 200000, "context window via alias fallback");
+    assert.equal(md?.limits.maxOutputTokens, 128000, "max output via alias fallback");
+    assert.equal(md?.capabilities.toolCalling, true);
+    assert.equal(md?.capabilities.reasoning, true);
+    assert.deepEqual(md?.modalities.input, ["text"]);
+    assert.equal(md?.metadata.source.syncedCapability, true);
+  });
+
+  it("combo of 4 opencode/* targets computes context_length = min(known) = 200000", () => {
+    // Simulate the "Opencode FREE Omni" combo: 4 targets, all under
+    // provider "opencode". The min of the 4 known contexts (200k, 400k,
+    // 200k, 200k) is 200000 — NOT 128000, NOT null.
+    const targets = [
+      { providerId: "opencode", modelId: "big-pickle" },
+      { providerId: "opencode", modelId: "gpt-5-nano" },
+      { providerId: "opencode", modelId: "minimax-m2" },
+      { providerId: "opencode", modelId: "kimi-k2" },
+    ];
+
+    // Inline the same chain buildComboCatalogMetadata uses:
+    //   1. resolveNestedComboTargets → targets
+    //   2. for each target → getComboTargetCatalogMetadata
+    //   3. min of known contextLength values
+    const contexts: number[] = [];
+    for (const target of targets) {
+      const md = registry.getCanonicalModelMetadata({
+        provider: target.providerId,
+        model: target.modelId,
+      });
+      assert.ok(md, `metadata should be found for ${target.modelId} via alias fallback`);
+      assert.equal(
+        md?.limits.contextWindow,
+        REAL_OPENCODE_DATA[target.modelId as keyof typeof REAL_OPENCODE_DATA].limit_context,
+        `${target.modelId} should have the catalog-stored context`
+      );
+      if (typeof md?.limits.contextWindow === "number") {
+        contexts.push(md.limits.contextWindow);
+      }
+    }
+    assert.equal(contexts.length, 4, "all 4 targets should resolve to a known context");
+    const minContext = Math.min(...contexts);
+    assert.equal(minContext, 200000, "min of 200k, 400k, 200k, 200k = 200k");
+  });
+
+  it("direct lookup under 'opencode-zen' still works (regression)", () => {
+    const cap = modelsDevSync.getSyncedCapability("opencode-zen", "big-pickle");
+    assert.ok(cap);
+    assert.equal(cap?.limit_context, 200000);
+  });
+
+  it("unknown model still returns null (regression)", () => {
+    const cap = modelsDevSync.getSyncedCapability("opencode", "nonexistent-model");
+    assert.equal(cap, null);
+  });
+});