recall: sectioned recentMessages with context/target split for LLM prompt

- prompt-builder.js: add RECALL_TARGET_CONTENT_HEADER, update splitSectionedTranscriptPayloadMessage to recognize recall-specific target header
- retriever.js: add buildRecallSectionedTranscript helper, format recentMessages as sectioned transcript with context-review and recall-target headers for prompt building while keeping flat string[] for ranking
- p0-regressions.mjs: add testRecallUsesSectionedPromptMessagesForContextAndTarget regression asserting two system messages with correct transcriptSection and headers

prompting/prompt-builder.js

@@ -328,10 +328,12 @@ function isPromptMessageArray(value) {
   );
 }
 
-const EXTRACTION_CONTEXT_REVIEW_HEADER =
+export const EXTRACTION_CONTEXT_REVIEW_HEADER =
   "--- 以下是上下文回顾（已提取过），仅供理解剧情 ---";
-const EXTRACTION_TARGET_CONTENT_HEADER =
+export const EXTRACTION_TARGET_CONTENT_HEADER =
   "--- 以下是本次需要提取记忆的新对话内容 ---";
+export const RECALL_TARGET_CONTENT_HEADER =
+  "--- 以下是本次需要召回记忆的新对话内容 ---";
 
 function getPromptMessageContextGroup(value) {
   const descriptor = getPromptMessageLikeDescriptor(value);
@@ -1927,11 +1929,16 @@ function splitSectionedTranscriptPayloadMessage(message = {}) {
   const normalizedRole = normalizeRole(message?.role);
   const sourceKey = String(message?.sourceKey || "").trim();
   const content = String(message?.content || "").trim();
+  const targetSectionHeader = content.includes(RECALL_TARGET_CONTENT_HEADER)
+    ? RECALL_TARGET_CONTENT_HEADER
+    : content.includes(EXTRACTION_TARGET_CONTENT_HEADER)
+      ? EXTRACTION_TARGET_CONTENT_HEADER
+      : "";
   if (
     normalizedRole !== "system" ||
     !["recentMessages", "dialogueText"].includes(sourceKey) ||
     !content.includes(EXTRACTION_CONTEXT_REVIEW_HEADER) ||
-    !content.includes(EXTRACTION_TARGET_CONTENT_HEADER)
+    !targetSectionHeader
   ) {
     return [message];
   }
@@ -1943,10 +1950,9 @@ function splitSectionedTranscriptPayloadMessage(message = {}) {
       EXTRACTION_CONTEXT_REVIEW_HEADER,
       searchIndex,
     );
-    const targetIndex = content.indexOf(
+    const targetIndex = targetSectionHeader
-      EXTRACTION_TARGET_CONTENT_HEADER,
+      ? content.indexOf(targetSectionHeader, searchIndex)
-      searchIndex,
+      : -1;
-    );
     let nextIndex = -1;
     let nextHeader = "";
     if (contextIndex >= 0 && (targetIndex < 0 || contextIndex <= targetIndex)) {
@@ -1954,7 +1960,7 @@ function splitSectionedTranscriptPayloadMessage(message = {}) {
       nextHeader = EXTRACTION_CONTEXT_REVIEW_HEADER;
     } else if (targetIndex >= 0) {
       nextIndex = targetIndex;
-      nextHeader = EXTRACTION_TARGET_CONTENT_HEADER;
+      nextHeader = targetSectionHeader;
     }
     if (nextIndex < 0 || !nextHeader) {
       break;

retrieval/retriever.js

@@ -16,6 +16,8 @@ import {
   buildTaskExecutionDebugContext,
   buildTaskLlmPayload,
   buildTaskPrompt,
+  EXTRACTION_CONTEXT_REVIEW_HEADER,
+  RECALL_TARGET_CONTENT_HEADER,
 } from "../prompting/prompt-builder.js";
 import {
   applyCooccurrenceBoost,
@@ -93,6 +95,32 @@ function resolveTaskLlmSystemPrompt(promptPayload, fallbackSystemPrompt = "") {
   return String(promptPayload?.systemPrompt || fallbackSystemPrompt || "");
 }
 
+function buildRecallSectionedTranscript(recentMessages = []) {
+  const lines = (Array.isArray(recentMessages) ? recentMessages : [])
+    .map((line) => String(line || "").trim())
+    .filter(Boolean);
+  if (lines.length === 0) {
+    return "";
+  }
+
+  const targetLines = [lines[lines.length - 1]].filter(Boolean);
+  const contextLines = lines.slice(0, -1).filter(Boolean);
+  const sections = [];
+
+  if (contextLines.length > 0) {
+    sections.push(
+      `${EXTRACTION_CONTEXT_REVIEW_HEADER}\n\n${contextLines.join("\n---\n")}`,
+    );
+  }
+  if (targetLines.length > 0) {
+    sections.push(
+      `${RECALL_TARGET_CONTENT_HEADER}\n\n${targetLines.join("\n---\n")}`,
+    );
+  }
+
+  return sections.join("\n\n");
+}
+
 function buildRecallFallbackReason(llmResult) {
   const failureType = String(llmResult?.errorType || "").trim();
   const failureReason = String(llmResult?.failureReason || "").trim();
@@ -2153,6 +2181,8 @@ async function llmRecall(
 ) {
   throwIfAborted(signal);
   const contextStr = recentMessages.join("\n---\n");
+  const sectionedContextStr =
+    buildRecallSectionedTranscript(recentMessages) || contextStr;
   const sceneOwnerCandidateText = buildSceneOwnerCandidateText(sceneOwnerCandidates);
   const {
     candidateKeyToNodeId,
@@ -2177,7 +2207,7 @@ async function llmRecall(
 
   const recallPromptBuild = await buildTaskPrompt(settings, "recall", {
     taskName: "recall",
-    recentMessages: contextStr || "(无)",
+    recentMessages: sectionedContextStr || "(无)",
     userMessage,
     candidateNodes: candidateDescriptions,
     candidateText: candidateDescriptions,
@@ -2212,7 +2242,7 @@ async function llmRecall(
     activeStoryTimeLabel || "(未确定)",
     "",
     "## 最近对话上下文",
-    contextStr || "(无)",
+    sectionedContextStr || contextStr || "(无)",
     "",
     "## 用户最新输入",
     userMessage,

tests/p0-regressions.mjs

@@ -162,6 +162,7 @@ const {
   generateSynopsis,
 } = await import("../maintenance/extractor.js");
 const { consolidateMemories } = await import("../maintenance/consolidator.js");
+const { retrieve } = await import("../retrieval/retriever.js");
 const {
   createBatchJournalEntry,
   buildReverseJournalRecoveryPlan,
@@ -169,6 +170,10 @@ const {
   rollbackBatch,
 } = await import("../runtime/runtime-state.js");
 const { createDefaultTaskProfiles } = await import("../prompting/prompt-profiles.js");
+const {
+  EXTRACTION_CONTEXT_REVIEW_HEADER,
+  RECALL_TARGET_CONTENT_HEADER,
+} = await import("../prompting/prompt-builder.js");
 const extensionsApi = await import("../../../../extensions.js");
 const llm = await import("../llm/llm.js");
 const embedding = await import("../vector/embedding.js");
@@ -6238,6 +6243,84 @@ async function testSynopsisUsesPromptMessagesWithoutFallbackSystemPrompt() {
   }
 }
 
+async function testRecallUsesSectionedPromptMessagesForContextAndTarget() {
+  const graph = createEmptyGraph();
+  addNode(graph, makeEvent(1, "仓库争执"));
+  addNode(graph, makeEvent(2, "走廊追问"));
+
+  const captured = [];
+  const restoreOverrides = pushTestOverrides({
+    llm: {
+      async callLLMForJSON(params = {}) {
+        captured.push(params);
+        return {
+          selected_keys: ["R1"],
+          reason: "R1: 与当前追问直接相关",
+          active_owner_keys: [],
+          active_owner_scores: [],
+        };
+      },
+    },
+  });
+
+  try {
+    const result = await retrieve({
+      graph,
+      userMessage: "她为什么突然改口？",
+      recentMessages: [
+        "[assistant]: 她先否认自己去过仓库。",
+        "[user]: 我记得她当时很紧张。",
+        "[user]: 她为什么突然改口？",
+      ],
+      embeddingConfig: null,
+      schema,
+      settings: {
+        taskProfilesVersion: 3,
+        taskProfiles: createDefaultTaskProfiles(),
+      },
+      options: {
+        topK: 4,
+        maxRecallNodes: 2,
+        enableLLMRecall: true,
+        enableVectorPrefilter: false,
+        enableGraphDiffusion: false,
+        llmCandidatePool: 2,
+        enableScopedMemory: false,
+        enablePovMemory: false,
+        enableRegionScopedObjective: false,
+        enableCognitiveMemory: false,
+        enableSpatialAdjacency: false,
+        enableStoryTimeline: false,
+        injectStoryTimeLabel: false,
+        injectUserPovMemory: false,
+        injectObjectiveGlobalMemory: false,
+        enableContextQueryBlend: true,
+      },
+    });
+
+    assert.ok(Array.isArray(result?.selectedNodeIds));
+    assert.equal(captured.length, 1);
+    const promptMessages = Array.isArray(captured[0].promptMessages)
+      ? captured[0].promptMessages
+      : [];
+    const recentMessageSections = promptMessages.filter(
+      (message) => message.sourceKey === "recentMessages",
+    );
+    assert.equal(recentMessageSections.length, 2);
+    assert.equal(recentMessageSections[0].role, "system");
+    assert.equal(recentMessageSections[1].role, "system");
+    assert.equal(recentMessageSections[0].transcriptSection, "context");
+    assert.equal(recentMessageSections[1].transcriptSection, "target");
+    assert.match(recentMessageSections[0].content, new RegExp(EXTRACTION_CONTEXT_REVIEW_HEADER.replace(/[.*+?^${}()|[\]\\]/g, "\\$&")));
+    assert.match(recentMessageSections[1].content, new RegExp(RECALL_TARGET_CONTENT_HEADER.replace(/[.*+?^${}()|[\]\\]/g, "\\$&")));
+    assert.match(recentMessageSections[0].content, /她先否认自己去过仓库/);
+    assert.match(recentMessageSections[0].content, /我记得她当时很紧张/);
+    assert.match(recentMessageSections[1].content, /她为什么突然改口/);
+  } finally {
+    restoreOverrides();
+  }
+}
+
 async function testReflectionUsesPromptMessagesWithoutFallbackSystemPrompt() {
   const graph = createEmptyGraph();
   addNode(
@@ -6736,6 +6819,7 @@ await testLlmDebugSnapshotRedactsSecretsBeforeStorage();
 await testEmbeddingUsesConfigTimeoutInsteadOfDefault();
 await testLlmOutputRegexCleansResponseBeforeJsonParse();
 await testSynopsisUsesPromptMessagesWithoutFallbackSystemPrompt();
+await testRecallUsesSectionedPromptMessagesForContextAndTarget();
 await testReflectionUsesPromptMessagesWithoutFallbackSystemPrompt();
 await testManualCompressSkipsWithoutCandidatesAndDoesNotPretendItRan();
 await testManualCompressUsesForcedCompressionAndPersistsRealMutation();