feat(agent): add llm model discovery helper

tests/unit/llm-models.test.ts

@@ -0,0 +1,138 @@
+import assert from "node:assert/strict";
+import { describe, it } from "node:test";
+import {
+  isValidLlmModelId,
+  listLlmModels,
+  normalizeLlmModelsPayload,
+  resolveAssistantModel,
+} from "../../src/lib/llm/models";
+import type { LlmConfig } from "../../src/lib/llm/config";
+
+const openAiConfig: LlmConfig = {
+  provider: "openai",
+  baseUrl: "https://llm.example.test/v1",
+  apiKey: "secret",
+  model: "llama3.2",
+};
+
+describe("normalizeLlmModelsPayload", () => {
+  it("normalizes OpenAI-compatible data arrays", () => {
+    const models = normalizeLlmModelsPayload({
+      data: [{ id: "qwen2.5-coder" }, { id: "llama3.2" }, { id: "qwen2.5-coder" }],
+    });
+
+    assert.deepEqual(models, [
+      { id: "llama3.2", label: "llama3.2" },
+      { id: "qwen2.5-coder", label: "qwen2.5-coder" },
+    ]);
+  });
+
+  it("ignores invalid or empty model rows", () => {
+    const models = normalizeLlmModelsPayload({
+      data: [{ id: "" }, { id: "   " }, { id: "bad model" }, { object: "model" }],
+    });
+
+    assert.deepEqual(models, []);
+  });
+});
+
+describe("isValidLlmModelId", () => {
+  it("accepts common provider model IDs", () => {
+    assert.equal(isValidLlmModelId("llama3.2"), true);
+    assert.equal(isValidLlmModelId("qwen2.5-coder:latest"), true);
+    assert.equal(isValidLlmModelId("hf.co/ginnoir/model-v1"), true);
+  });
+
+  it("rejects empty, whitespace, and overlong model IDs", () => {
+    assert.equal(isValidLlmModelId(""), false);
+    assert.equal(isValidLlmModelId("bad model"), false);
+    assert.equal(isValidLlmModelId("x".repeat(129)), false);
+  });
+});
+
+describe("listLlmModels", () => {
+  it("fetches provider models with API key auth and includes the fallback model", async () => {
+    const requests: Request[] = [];
+    const result = await listLlmModels({
+      config: openAiConfig,
+      fetchImpl: async (input, init) => {
+        requests.push(new Request(input, init));
+        return Response.json({ data: [{ id: "qwen2.5-coder" }] });
+      },
+    });
+
+    assert.equal(requests[0]?.url, "https://llm.example.test/v1/models");
+    assert.equal(requests[0]?.headers.get("authorization"), "Bearer secret");
+    assert.deepEqual(result.models, [
+      { id: "llama3.2", label: "llama3.2" },
+      { id: "qwen2.5-coder", label: "qwen2.5-coder" },
+    ]);
+    assert.equal(result.fallbackModel, "llama3.2");
+    assert.equal(result.degraded, false);
+  });
+
+  it("falls back to LLM_MODEL when provider discovery fails", async () => {
+    const result = await listLlmModels({
+      config: openAiConfig,
+      fetchImpl: async () => new Response("nope", { status: 500 }),
+    });
+
+    assert.deepEqual(result.models, [{ id: "llama3.2", label: "llama3.2" }]);
+    assert.equal(result.fallbackModel, "llama3.2");
+    assert.equal(result.degraded, true);
+  });
+
+  it("uses fallback only for mock provider config", async () => {
+    const result = await listLlmModels({
+      config: { provider: "mock", baseUrl: null, apiKey: null, model: "llama3.2" },
+      fetchImpl: async () => {
+        throw new Error("fetch should not run for mock config");
+      },
+    });
+
+    assert.deepEqual(result.models, [{ id: "llama3.2", label: "llama3.2" }]);
+    assert.equal(result.degraded, false);
+  });
+});
+
+describe("resolveAssistantModel", () => {
+  it("uses a valid requested model before saved and fallback values", () => {
+    const resolved = resolveAssistantModel({
+      requestedModel: "qwen2.5-coder",
+      savedModel: "llama3.2",
+      fallbackModel: "llama3.2",
+      models: [
+        { id: "llama3.2", label: "llama3.2" },
+        { id: "qwen2.5-coder", label: "qwen2.5-coder" },
+      ],
+    });
+
+    assert.deepEqual(resolved, { ok: true, model: "qwen2.5-coder" });
+  });
+
+  it("rejects invalid requested models", () => {
+    const resolved = resolveAssistantModel({
+      requestedModel: "missing",
+      savedModel: null,
+      fallbackModel: "llama3.2",
+      models: [{ id: "llama3.2", label: "llama3.2" }],
+    });
+
+    assert.deepEqual(resolved, {
+      ok: false,
+      model: "llama3.2",
+      error: "Invalid assistant model",
+    });
+  });
+
+  it("silently falls back when a saved model is gone", () => {
+    const resolved = resolveAssistantModel({
+      requestedModel: null,
+      savedModel: "old-model",
+      fallbackModel: "llama3.2",
+      models: [{ id: "llama3.2", label: "llama3.2" }],
+    });
+
+    assert.deepEqual(resolved, { ok: true, model: "llama3.2" });
+  });
+});