feat(agent): route chat through selected model

tests/unit/agent-chat.test.ts

@@ -84,3 +84,36 @@ describe("runAgentChat", () => {
     assert.ok(result.message.content.length > 0);
   });
 });
+
+it("passes a model override to the OpenAI-compatible client", async () => {
+  const originalBaseUrl = process.env.LLM_BASE_URL;
+  const originalModel = process.env.LLM_MODEL;
+  const originalProvider = process.env.LLM_PROVIDER;
+  const originalFetch = globalThis.fetch;
+  let requestBody: unknown = null;
+
+  process.env.LLM_BASE_URL = "https://llm.example.test/v1";
+  process.env.LLM_MODEL = "llama3.2";
+  delete process.env.LLM_PROVIDER;
+
+  globalThis.fetch = (async (_input: RequestInfo | URL, init?: RequestInit) => {
+    requestBody = JSON.parse(String(init?.body));
+    return Response.json({
+      choices: [{ message: { role: "assistant", content: "done" }, finish_reason: "stop" }],
+    });
+  }) as typeof fetch;
+
+  const { createLlmClient } = await import("../../src/lib/llm/index");
+  const client = createLlmClient({ model: "qwen2.5-coder" });
+  await client.chatCompletion({ messages: [{ role: "user", content: "hello" }] });
+
+  assert.equal((requestBody as { model?: string }).model, "qwen2.5-coder");
+
+  globalThis.fetch = originalFetch;
+  if (originalBaseUrl === undefined) delete process.env.LLM_BASE_URL;
+  else process.env.LLM_BASE_URL = originalBaseUrl;
+  if (originalModel === undefined) delete process.env.LLM_MODEL;
+  else process.env.LLM_MODEL = originalModel;
+  if (originalProvider === undefined) delete process.env.LLM_PROVIDER;
+  else process.env.LLM_PROVIDER = originalProvider;
+});

tests/unit/agent-messages.test.ts

@@ -25,4 +25,22 @@ describe("clientChatInputSchema", () => {
 
     assert.equal(parsed.success, false);
   });
+
+  it("accepts an optional model ID", () => {
+    const parsed = clientChatInputSchema.safeParse({
+      model: "qwen2.5-coder",
+      messages: [{ role: "user", content: "hello" }],
+    });
+
+    assert.equal(parsed.success, true);
+  });
+
+  it("rejects invalid model IDs", () => {
+    const parsed = clientChatInputSchema.safeParse({
+      model: "bad model",
+      messages: [{ role: "user", content: "hello" }],
+    });
+
+    assert.equal(parsed.success, false);
+  });
 });