feat(workflow-utils): add createLlmAdapter AgentFn factory

Single-turn chat via chatCompletionText: system from createRole prompt, user from ctx.start.content.

Fixes #277

Made-with: Cursor

packages/workflow-utils/src/__tests__/create-llm-adapter.test.ts

@@ -0,0 +1,54 @@
+import { afterEach, describe, expect, it, vi } from "vitest";
+
+import { START, type ThreadContext } from "@uncaged/nerve-core";
+
+import { createLlmAdapter } from "../create-llm-adapter.js";
+
+function makeCtx(threadId: string, userContent: string): ThreadContext {
+  return {
+    threadId,
+    start: {
+      role: START,
+      content: userContent,
+      meta: { maxRounds: 10, threadId },
+      timestamp: 1,
+    },
+    steps: [],
+  };
+}
+
+describe("createLlmAdapter", () => {
+  afterEach(() => {
+    vi.unstubAllGlobals();
+    vi.restoreAllMocks();
+  });
+
+  it("posts system + user (start.content) and returns assistant text", async () => {
+    const fetchMock = vi.fn().mockResolvedValue({
+      ok: true,
+      status: 200,
+      text: async () =>
+        JSON.stringify({
+          choices: [{ message: { content: "model reply" } }],
+        }),
+    });
+    vi.stubGlobal("fetch", fetchMock);
+
+    const provider = { baseUrl: "https://api.example/v1", apiKey: "k", model: "m" };
+    const adapter = createLlmAdapter(provider);
+    const out = await adapter(makeCtx("t1", "trigger text"), "system instructions");
+
+    expect(out).toBe("model reply");
+    expect(fetchMock).toHaveBeenCalledTimes(1);
+    const [, init] = fetchMock.mock.calls[0] as [string, RequestInit];
+    const body = JSON.parse(init.body as string) as {
+      model: string;
+      messages: Array<{ role: string; content: string }>;
+    };
+    expect(body.model).toBe("m");
+    expect(body.messages).toEqual([
+      { role: "system", content: "system instructions" },
+      { role: "user", content: "trigger text" },
+    ]);
+  });
+});

packages/workflow-utils/src/create-llm-adapter.ts

@@ -0,0 +1,22 @@
+import type { AgentFn, ThreadContext } from "@uncaged/nerve-core";
+
+import { formatLlmError } from "./shared/format-error.js";
+import { chatCompletionText } from "./shared/llm-chat.js";
+import type { LlmProvider } from "./shared/llm-extract.js";
+
+/** Single-turn chat adapter: system comes from `createRole` prompt; user is the thread start frame. */
+export function createLlmAdapter(provider: LlmProvider): AgentFn {
+  return async (ctx: ThreadContext, systemPrompt: string) => {
+    const result = await chatCompletionText({
+      provider,
+      messages: [
+        { role: "system", content: systemPrompt },
+        { role: "user", content: ctx.start.content },
+      ],
+    });
+    if (!result.ok) {
+      throw new Error(`llm: ${formatLlmError(result.error)}`);
+    }
+    return result.value;
+  };
+}

packages/workflow-utils/src/index.ts

@@ -1,4 +1,5 @@
 // Primary API — role factory templates
+export { createLlmAdapter } from "./create-llm-adapter.js";
 export { createRole, type LlmExtractorConfig } from "./create-role.js";
 export { createCursorRole } from "./role-cursor.js";
 export { createHermesRole } from "./role-hermes.js";