refactor(knowledge-extraction): convert questioner and answerer to createRole four-tuple

- questioner: createRole(adapter, questionerPrompt, schema, extract) + queue short-circuit + meta post-processing
- answerer: createRole(adapter, answererPrompt, schema, extract) + empty-questions short-circuit
- build.ts: use createLlmAdapter(extract.provider) as default LLM adapter for questioner/answerer

Refs uncaged/nerve#277

workflows/knowledge-extraction/build.ts

@@ -1,5 +1,6 @@
 import type { AgentFn, WorkflowDefinition } from "@uncaged/nerve-core";
 import type { LlmExtractorConfig } from "@uncaged/nerve-workflow-utils";
+import { createLlmAdapter } from "@uncaged/nerve-workflow-utils";
 
 import { moderator } from "./moderator.js";
 import type { WorkflowMeta } from "./moderator.js";
@@ -19,11 +20,12 @@ export function createKnowledgeExtractionWorkflow({
   extract,
 }: CreateKnowledgeExtractionDeps): WorkflowDefinition<WorkflowMeta> {
   const a = (role: keyof WorkflowMeta) => adapters?.[role] ?? defaultAdapter;
+  const llmAdapter = createLlmAdapter(extract.provider);
   return {
     name: "knowledge-extraction",
     roles: {
-      questioner: createQuestionerRole({ extract }),
-      answerer: createAnswererRole({ extract }),
+      questioner: createQuestionerRole(adapters?.questioner ?? llmAdapter, { extract }),
+      answerer: createAnswererRole(adapters?.answerer ?? llmAdapter, { extract }),
       explorer: createExplorerRole(a("explorer"), { extract }),
     },
     moderator,

workflows/knowledge-extraction/roles/answerer.ts

@@ -1,6 +1,6 @@
-import type { Role, ThreadContext, WorkflowMessage } from "@uncaged/nerve-core";
+import type { AgentFn, Role, ThreadContext, WorkflowMessage } from "@uncaged/nerve-core";
 import type { LlmExtractorConfig } from "@uncaged/nerve-workflow-utils";
-import { llmExtract, nerveCommandEnv, spawnSafe } from "@uncaged/nerve-workflow-utils";
+import { createRole, nerveCommandEnv, spawnSafe } from "@uncaged/nerve-workflow-utils";
 import { z } from "zod";
 
 import { resolveWorkdir } from "../lib/workdir.js";
@@ -34,18 +34,12 @@ function lastQuestionerMeta(messages: WorkflowMessage[]): QuestionerMeta | undef
   return undefined;
 }
 
-export function createAnswererRole(deps: CreateAnswererRoleDeps): Role<AnswererMeta> {
-  const { extract } = deps;
-
-  return async (ctx: ThreadContext) => {
+export async function answererPrompt(ctx: ThreadContext): Promise<string> {
   const messages = ctx.steps as unknown as WorkflowMessage[];
   const cwd = resolveWorkdir(ctx.start);
   const qm = lastQuestionerMeta(messages);
   if (!qm || qm.questions.length === 0) {
-      return {
-        content: "answerer: no questions from questioner; skipping CLI lookup.",
-        meta: { results: [], has_unanswered: false },
-      };
+    throw new Error("answerer: prompt invoked without questioner questions — wrapped role should short-circuit");
   }
 
   const blocks: string[] = [];
@@ -81,7 +75,7 @@ export function createAnswererRole(deps: CreateAnswererRoleDeps): Role<AnswererM
     }
   }
 
-    const bundle = [
+  return [
     "You are the **answerer**. You MUST NOT read repository source code — only the CLI retrieval excerpts below.",
     "For each question id, decide whether the knowledge base already answers it.",
     "Set found=true only when the excerpt supports a confident answer; otherwise found=false.",
@@ -89,17 +83,20 @@ export function createAnswererRole(deps: CreateAnswererRoleDeps): Role<AnswererM
     "",
     ...blocks,
   ].join("\n");
-
-    const metaR = await llmExtract({
-      text: bundle,
-      schema: answererMetaSchema,
-      provider: extract.provider,
-      dryRun: false,
-    });
-    if (!metaR.ok) {
-      throw new Error(`answerer llmExtract: ${JSON.stringify(metaR.error)}`);
 }
 
-    return { content: bundle, meta: metaR.value };
+export function createAnswererRole(adapter: AgentFn, { extract }: CreateAnswererRoleDeps): Role<AnswererMeta> {
+  const inner = createRole(adapter, answererPrompt, answererMetaSchema, extract);
+
+  return async (ctx: ThreadContext) => {
+    const messages = ctx.steps as unknown as WorkflowMessage[];
+    const qm = lastQuestionerMeta(messages);
+    if (!qm || qm.questions.length === 0) {
+      return {
+        content: "answerer: no questions from questioner; skipping CLI lookup.",
+        meta: { results: [], has_unanswered: false },
+      };
+    }
+    return inner(ctx);
   };
 }

workflows/knowledge-extraction/roles/questioner.ts

@@ -1,9 +1,9 @@
 import { readFile } from "node:fs/promises";
 import { join } from "node:path";
 
-import type { Role, ThreadContext, WorkflowMessage } from "@uncaged/nerve-core";
+import type { AgentFn, Role, ThreadContext, WorkflowMessage } from "@uncaged/nerve-core";
 import type { LlmExtractorConfig } from "@uncaged/nerve-workflow-utils";
-import { createLlmRole } from "@uncaged/nerve-workflow-utils";
+import { createRole } from "@uncaged/nerve-workflow-utils";
 import { z } from "zod";
 
 import { resolveQueueForQuestioner } from "../lib/knowledge-queue.js";
@@ -53,8 +53,29 @@ Remaining queue after this card (paths, may be empty): ${JSON.stringify(remainin
 ${cardBody}`;
 }
 
-export function createQuestionerRole(adapterExtract: CreateQuestionerRoleDeps): Role<QuestionerMeta> {
-  const { extract } = adapterExtract;
+export async function questionerPrompt(ctx: ThreadContext): Promise<string> {
+  const messages = ctx.steps as unknown as WorkflowMessage[];
+  const cwd = resolveWorkdir(ctx.start);
+  const queue = await resolveQueueForQuestioner(ctx.start, messages, cwd);
+  if (queue.length === 0) {
+    throw new Error(
+      "questioner: prompt invoked with empty queue — wrapped role should short-circuit before LLM",
+    );
+  }
+  const card = queue[0]!;
+  const remaining_queue = queue.slice(1);
+  let cardBody: string;
+  try {
+    cardBody = await readFile(join(cwd, card), "utf8");
+  } catch (e) {
+    const msg = e instanceof Error ? e.message : String(e);
+    throw new Error(`questioner: failed to read ${card}: ${msg}`);
+  }
+  return `${questionerSystem()}\n\n${questionerUser(card, cardBody, remaining_queue)}`;
+}
+
+export function createQuestionerRole(adapter: AgentFn, { extract }: CreateQuestionerRoleDeps): Role<QuestionerMeta> {
+  const inner = createRole(adapter, questionerPrompt, questionerExtractSchema, extract);
 
   return async (ctx: ThreadContext) => {
     const messages = ctx.steps as unknown as WorkflowMessage[];
@@ -74,26 +95,6 @@ export function createQuestionerRole(adapterExtract: CreateQuestionerRoleDeps):
 
     const card = queue[0]!;
     const remaining_queue = queue.slice(1);
-    let cardBody: string;
-    try {
-      cardBody = await readFile(join(cwd, card), "utf8");
-    } catch (e) {
-      const msg = e instanceof Error ? e.message : String(e);
-      throw new Error(`questioner: failed to read ${card}: ${msg}`);
-    }
-
-    const inner = createLlmRole({
-      provider: extract.provider,
-      prompt: async () => [
-        { role: "system", content: questionerSystem() },
-        { role: "user", content: questionerUser(card, cardBody, remaining_queue) },
-      ],
-      extract: {
-        schema: questionerExtractSchema,
-        provider: extract.provider,
-      },
-    });
-
     const r = await inner(ctx);
     return {
       content: r.content,