diff --git a/panel.js b/panel.js
index 5da13dc..75ffcb5 100644
--- a/panel.js
+++ b/panel.js
@@ -663,6 +663,14 @@ function _refreshConfigTab() {
_setCheckboxValue("bme-setting-enabled", settings.enabled ?? false);
_setCheckboxValue("bme-setting-recall-enabled", settings.recallEnabled ?? true);
_setCheckboxValue("bme-setting-recall-llm", settings.recallEnableLLM ?? true);
+ _setCheckboxValue(
+ "bme-setting-recall-vector-prefilter-enabled",
+ settings.recallEnableVectorPrefilter ?? true,
+ );
+ _setCheckboxValue(
+ "bme-setting-recall-graph-diffusion-enabled",
+ settings.recallEnableGraphDiffusion ?? true,
+ );
_setCheckboxValue("bme-setting-evolution-enabled", settings.enableEvolution ?? true);
_setCheckboxValue(
"bme-setting-precise-conflict-enabled",
@@ -699,9 +707,17 @@ function _refreshConfigTab() {
"bme-setting-extract-context-turns",
settings.extractContextTurns ?? 2,
);
- _setInputValue("bme-setting-recall-top-k", settings.recallTopK ?? 15);
+ _setInputValue("bme-setting-recall-top-k", settings.recallTopK ?? 20);
_setInputValue("bme-setting-recall-max-nodes", settings.recallMaxNodes ?? 8);
- _setInputValue("bme-setting-inject-depth", settings.injectDepth ?? 4);
+ _setInputValue(
+ "bme-setting-recall-diffusion-top-k",
+ settings.recallDiffusionTopK ?? 100,
+ );
+ _setInputValue(
+ "bme-setting-recall-llm-candidate-pool",
+ settings.recallLlmCandidatePool ?? 30,
+ );
+ _setInputValue("bme-setting-inject-depth", settings.injectDepth ?? 9999);
_setInputValue("bme-setting-graph-weight", settings.graphWeight ?? 0.6);
_setInputValue("bme-setting-vector-weight", settings.vectorWeight ?? 0.3);
_setInputValue(
@@ -780,6 +796,7 @@ function _refreshConfigTab() {
_setInputValue("bme-setting-reflection-prompt", settings.reflectionPrompt || DEFAULT_PROMPTS.reflection);
_refreshGuardedConfigStates(settings);
+ _refreshStageCardStates(settings);
_refreshPromptCardStates(settings);
_highlightThemeChoice(settings.panelTheme || "crimson");
_syncConfigSectionState();
@@ -803,10 +820,20 @@ function _bindConfigControls() {
bindCheckbox("bme-setting-recall-enabled", (checked) => {
_patchSettings({ recallEnabled: checked });
_refreshGuardedConfigStates();
+ _refreshStageCardStates();
});
bindCheckbox("bme-setting-recall-llm", (checked) => {
_patchSettings({ recallEnableLLM: checked });
_refreshGuardedConfigStates();
+ _refreshStageCardStates();
+ });
+ bindCheckbox("bme-setting-recall-vector-prefilter-enabled", (checked) => {
+ _patchSettings({ recallEnableVectorPrefilter: checked });
+ _refreshStageCardStates();
+ });
+ bindCheckbox("bme-setting-recall-graph-diffusion-enabled", (checked) => {
+ _patchSettings({ recallEnableGraphDiffusion: checked });
+ _refreshStageCardStates();
});
bindCheckbox("bme-setting-evolution-enabled", (checked) => {
_patchSettings({ enableEvolution: checked });
@@ -849,13 +876,19 @@ function _bindConfigControls() {
bindNumber("bme-setting-extract-context-turns", 2, 0, 20, (value) =>
_patchSettings({ extractContextTurns: value }),
);
- bindNumber("bme-setting-recall-top-k", 15, 1, 100, (value) =>
+ bindNumber("bme-setting-recall-top-k", 20, 1, 100, (value) =>
_patchSettings({ recallTopK: value }),
);
bindNumber("bme-setting-recall-max-nodes", 8, 1, 50, (value) =>
_patchSettings({ recallMaxNodes: value }),
);
- bindNumber("bme-setting-inject-depth", 4, 0, 9999, (value) =>
+ bindNumber("bme-setting-recall-diffusion-top-k", 100, 1, 300, (value) =>
+ _patchSettings({ recallDiffusionTopK: value }),
+ );
+ bindNumber("bme-setting-recall-llm-candidate-pool", 30, 1, 100, (value) =>
+ _patchSettings({ recallLlmCandidatePool: value }),
+ );
+ bindNumber("bme-setting-inject-depth", 9999, 0, 9999, (value) =>
_patchSettings({ injectDepth: value }),
);
bindFloat("bme-setting-graph-weight", 0.6, 0, 1, (value) =>
@@ -1131,6 +1164,28 @@ function _refreshGuardedConfigStates(settings = _getSettings?.() || {}) {
});
}
+function _refreshStageCardStates(settings = _getSettings?.() || {}) {
+ if (!panelEl) return;
+ panelEl.querySelectorAll(".bme-stage-card").forEach((card) => {
+ const toggleId = card.dataset.stageToggleId;
+ const toggle = toggleId ? document.getElementById(toggleId) : null;
+ const cardDisabled = card.classList.contains("is-disabled");
+ const stageEnabled =
+ toggleId === "bme-setting-recall-llm"
+ ? settings.recallEnableLLM ?? true
+ : toggle
+ ? Boolean(toggle.checked)
+ : true;
+
+ card.classList.toggle("stage-disabled", !cardDisabled && !stageEnabled);
+ card.querySelectorAll(".bme-stage-param").forEach((section) => {
+ section.querySelectorAll("input, select, textarea, button").forEach((element) => {
+ element.disabled = cardDisabled || !stageEnabled;
+ });
+ });
+ });
+}
+
function _refreshPromptCardStates(settings = _getSettings?.() || {}) {
if (!panelEl) return;
panelEl.querySelectorAll(".bme-prompt-card").forEach((card) => {
diff --git a/retriever.js b/retriever.js
index 2dbed86..3f6ff4d 100644
--- a/retriever.js
+++ b/retriever.js
@@ -13,15 +13,6 @@ import {
import { callLLMForJSON } from "./llm.js";
import { findSimilarNodesByText, validateVectorConfig } from "./vector-index.js";
-/**
- * 自适应阈值
- */
-const STRATEGY_THRESHOLDS = {
- SMALL: 20, // < 20 节点：跳过向量，全图 + LLM
- MEDIUM: 200, // 20-200 节点：向量 + 图扩散 + 评分（不调 LLM）
- // > 200 节点：三层全开
-};
-
/**
* 三层混合检索管线
*
@@ -42,9 +33,13 @@ export async function retrieve({
schema,
options = {},
}) {
- const topK = options.topK ?? 15;
+ const topK = options.topK ?? 20;
const maxRecallNodes = options.maxRecallNodes ?? 8;
const enableLLMRecall = options.enableLLMRecall ?? true;
+ const enableVectorPrefilter = options.enableVectorPrefilter ?? true;
+ const enableGraphDiffusion = options.enableGraphDiffusion ?? true;
+ const diffusionTopK = options.diffusionTopK ?? 100;
+ const llmCandidatePool = options.llmCandidatePool ?? 30;
const weights = options.weights ?? {};
// v2 options
@@ -69,6 +64,11 @@ export async function retrieve({
const nodeCount = activeNodes.length;
const normalizedTopK = Math.max(1, topK);
const normalizedMaxRecallNodes = Math.max(1, maxRecallNodes);
+ const normalizedDiffusionTopK = Math.max(1, diffusionTopK);
+ const normalizedLlmCandidatePool = Math.max(
+ normalizedMaxRecallNodes,
+ llmCandidatePool,
+ );
console.log(
`[ST-BME] 检索开始: ${nodeCount} 个活跃节点${enableVisibility ? " (认知边界已启用)" : ""}`,
);
@@ -83,7 +83,7 @@ export async function retrieve({
// ========== 第 1 层：向量预筛 ==========
if (
- nodeCount >= STRATEGY_THRESHOLDS.SMALL &&
+ enableVectorPrefilter &&
validateVectorConfig(embeddingConfig).valid
) {
console.log("[ST-BME] 第1层: 向量预筛");
@@ -97,7 +97,7 @@ export async function retrieve({
}
// ========== 第 2 层：图扩散 ==========
- if (nodeCount >= STRATEGY_THRESHOLDS.SMALL) {
+ if (enableGraphDiffusion) {
console.log("[ST-BME] 第2层: PEDSA 图扩散");
const entityAnchors = extractEntityAnchors(userMessage, activeNodes);
@@ -139,7 +139,7 @@ export async function retrieve({
diffusionResults = diffuseAndRank(adjacencyMap, uniqueSeeds, {
maxSteps: 2,
decayFactor: 0.6,
- topK: 100,
+ topK: normalizedDiffusionTopK,
}).filter((item) => {
const node = getNode(graph, item.nodeId);
return node && !node.archived;
@@ -167,8 +167,8 @@ export async function retrieve({
scoreMap.set(d.nodeId, entry);
}
- // 小图模式：所有节点都参与评分
- if (nodeCount < STRATEGY_THRESHOLDS.SMALL) {
+ // 两个上游阶段都未产出候选时，退回到全部活跃节点参与评分
+ if (scoreMap.size === 0) {
for (const node of activeNodes) {
if (!scoreMap.has(node.id)) {
scoreMap.set(node.id, { graphScore: 0, vectorScore: 0 });
@@ -198,10 +198,7 @@ export async function retrieve({
scoredNodes.sort((a, b) => b.finalScore - a.finalScore);
// 决定是否使用 LLM 精确召回
- useLLM =
- enableLLMRecall &&
- (nodeCount < STRATEGY_THRESHOLDS.SMALL || // 小图：直接 LLM
- nodeCount > STRATEGY_THRESHOLDS.MEDIUM); // 大图：LLM 精确
+ useLLM = enableLLMRecall;
let selectedNodeIds;
@@ -209,7 +206,7 @@ export async function retrieve({
console.log("[ST-BME] LLM 精确召回");
const candidateNodes = scoredNodes.slice(
0,
- Math.min(30, scoredNodes.length),
+ Math.min(normalizedLlmCandidatePool, scoredNodes.length),
);
selectedNodeIds = await llmRecall(
userMessage,
diff --git a/style.css b/style.css
index 10ad23d..ed1965f 100644
--- a/style.css
+++ b/style.css
@@ -1006,6 +1006,32 @@
opacity: 0.72;
}
+.bme-stage-card.stage-disabled {
+ border-color: rgba(255, 255, 255, 0.08);
+}
+
+.bme-inline-checkbox {
+ display: inline-flex;
+ align-items: center;
+ gap: 10px;
+ margin-bottom: 12px;
+ font-size: 12px;
+ font-weight: 700;
+ color: var(--bme-on-surface);
+ cursor: pointer;
+}
+
+.bme-inline-checkbox input {
+ width: 16px;
+ height: 16px;
+ margin: 0;
+ accent-color: var(--bme-primary);
+}
+
+.bme-stage-card.stage-disabled .bme-stage-param {
+ opacity: 0.6;
+}
+
.bme-config-placeholder {
background: var(--bme-surface-low);
border: 1px dashed var(--bme-border);
diff --git a/tests/default-settings.mjs b/tests/default-settings.mjs
new file mode 100644
index 0000000..ef3befc
--- /dev/null
+++ b/tests/default-settings.mjs
@@ -0,0 +1,37 @@
+import assert from "node:assert/strict";
+import fs from "node:fs/promises";
+import path from "node:path";
+import { fileURLToPath } from "node:url";
+import vm from "node:vm";
+
+async function loadDefaultSettings() {
+ const __dirname = path.dirname(fileURLToPath(import.meta.url));
+ const indexPath = path.resolve(__dirname, "../index.js");
+ const source = await fs.readFile(indexPath, "utf8");
+ const settingsMatch = source.match(/const defaultSettings = \{[\s\S]*?^\};/m);
+
+ if (!settingsMatch) {
+ throw new Error("无法从 index.js 提取 defaultSettings");
+ }
+
+ const context = vm.createContext({});
+ const script = new vm.Script(`
+${settingsMatch[0]}
+this.defaultSettings = defaultSettings;
+`);
+ script.runInContext(context);
+ return context.defaultSettings;
+}
+
+const defaultSettings = await loadDefaultSettings();
+
+assert.equal(defaultSettings.extractContextTurns, 2);
+assert.equal(defaultSettings.recallTopK, 20);
+assert.equal(defaultSettings.recallMaxNodes, 8);
+assert.equal(defaultSettings.recallEnableVectorPrefilter, true);
+assert.equal(defaultSettings.recallEnableGraphDiffusion, true);
+assert.equal(defaultSettings.recallDiffusionTopK, 100);
+assert.equal(defaultSettings.recallLlmCandidatePool, 30);
+assert.equal(defaultSettings.injectDepth, 9999);
+
+console.log("default-settings tests passed");
diff --git a/tests/retrieval-config.mjs b/tests/retrieval-config.mjs
new file mode 100644
index 0000000..1fe3667
--- /dev/null
+++ b/tests/retrieval-config.mjs
@@ -0,0 +1,191 @@
+import assert from "node:assert/strict";
+import fs from "node:fs/promises";
+import path from "node:path";
+import { fileURLToPath } from "node:url";
+import vm from "node:vm";
+
+async function loadRetrieve(stubs) {
+ const __dirname = path.dirname(fileURLToPath(import.meta.url));
+ const retrieverPath = path.resolve(__dirname, "../retriever.js");
+ const source = await fs.readFile(retrieverPath, "utf8");
+ const transformed = `${source
+ .replace(/^import[\s\S]*?from\s+["'][^"']+["'];\r?\n/gm, "")
+ .replace("export async function retrieve", "async function retrieve")}
+this.retrieve = retrieve;
+`;
+
+ const context = vm.createContext({
+ console: { log() {}, error() {}, warn() {} },
+ ...stubs,
+ });
+ new vm.Script(transformed).runInContext(context);
+ return context.retrieve;
+}
+
+function createGraph() {
+ const nodes = [
+ {
+ id: "rule-1",
+ type: "rule",
+ importance: 9,
+ createdTime: 1,
+ archived: false,
+ fields: { title: "规则一" },
+ seqRange: [1, 1],
+ },
+ {
+ id: "rule-2",
+ type: "rule",
+ importance: 7,
+ createdTime: 2,
+ archived: false,
+ fields: { title: "规则二" },
+ seqRange: [2, 2],
+ },
+ {
+ id: "rule-3",
+ type: "rule",
+ importance: 3,
+ createdTime: 3,
+ archived: false,
+ fields: { title: "规则三" },
+ seqRange: [3, 3],
+ },
+ ];
+ return { nodes, edges: [] };
+}
+
+function createGraphHelpers(graph) {
+ return {
+ getActiveNodes(target, type = null) {
+ const source = target?.nodes || graph.nodes;
+ return source.filter(
+ (node) => !node.archived && (!type || node.type === type),
+ );
+ },
+ getNode(target, id) {
+ return (target?.nodes || graph.nodes).find((node) => node.id === id) || null;
+ },
+ getNodeEdges(target, nodeId) {
+ return (target?.edges || graph.edges).filter(
+ (edge) => edge.fromId === nodeId || edge.toId === nodeId,
+ );
+ },
+ buildTemporalAdjacencyMap() {
+ return new Map();
+ },
+ };
+}
+
+const schema = [{ id: "rule", label: "规则", alwaysInject: false }];
+
+const state = {
+ vectorCalls: [],
+ diffusionCalls: [],
+ llmCalls: [],
+ llmCandidateCount: 0,
+};
+
+const graph = createGraph();
+const helpers = createGraphHelpers(graph);
+const retrieve = await loadRetrieve({
+ ...helpers,
+ hybridScore: ({ graphScore = 0, vectorScore = 0, importance = 0 }) =>
+ graphScore + vectorScore + importance,
+ reinforceAccessBatch() {},
+ validateVectorConfig() {
+ return { valid: true };
+ },
+ async findSimilarNodesByText(_graph, _message, _embeddingConfig, topK) {
+ state.vectorCalls.push(topK);
+ return [
+ { nodeId: "rule-1", score: 0.9 },
+ { nodeId: "rule-2", score: 0.8 },
+ { nodeId: "rule-3", score: 0.7 },
+ ];
+ },
+ diffuseAndRank(_adjacencyMap, seeds, options) {
+ state.diffusionCalls.push({ seeds, options });
+ return [
+ { nodeId: "rule-2", energy: 1.2 },
+ { nodeId: "rule-3", energy: 0.9 },
+ ];
+ },
+ async callLLMForJSON({ userPrompt }) {
+ state.llmCalls.push(userPrompt);
+ state.llmCandidateCount = userPrompt
+ .split("\n")
+ .filter((line) => line.trim().startsWith("[")).length;
+ return { selected_ids: ["rule-2", "rule-1"] };
+ },
+});
+
+state.vectorCalls.length = 0;
+state.diffusionCalls.length = 0;
+state.llmCalls.length = 0;
+const noStageResult = await retrieve({
+ graph,
+ userMessage: "只看当前规则",
+ recentMessages: [],
+ embeddingConfig: {},
+ schema,
+ options: {
+ topK: 2,
+ maxRecallNodes: 2,
+ enableVectorPrefilter: false,
+ enableGraphDiffusion: false,
+ enableLLMRecall: false,
+ },
+});
+assert.equal(state.vectorCalls.length, 0);
+assert.equal(state.diffusionCalls.length, 0);
+assert.equal(state.llmCalls.length, 0);
+assert.deepEqual(Array.from(noStageResult.selectedNodeIds), ["rule-1", "rule-2"]);
+
+state.vectorCalls.length = 0;
+state.diffusionCalls.length = 0;
+state.llmCalls.length = 0;
+state.llmCandidateCount = 0;
+const llmPoolResult = await retrieve({
+ graph,
+ userMessage: "请根据规则给出结论",
+ recentMessages: ["用户：现在该怎么做？"],
+ embeddingConfig: {},
+ schema,
+ options: {
+ topK: 4,
+ maxRecallNodes: 2,
+ enableVectorPrefilter: true,
+ enableGraphDiffusion: false,
+ enableLLMRecall: true,
+ llmCandidatePool: 2,
+ },
+});
+assert.deepEqual(state.vectorCalls, [4]);
+assert.equal(state.diffusionCalls.length, 0);
+assert.equal(state.llmCandidateCount, 2);
+assert.deepEqual(Array.from(llmPoolResult.selectedNodeIds), ["rule-2", "rule-1"]);
+
+state.vectorCalls.length = 0;
+state.diffusionCalls.length = 0;
+state.llmCalls.length = 0;
+await retrieve({
+ graph,
+ userMessage: "规则一和规则二有什么关联",
+ recentMessages: [],
+ embeddingConfig: {},
+ schema,
+ options: {
+ topK: 3,
+ maxRecallNodes: 2,
+ enableVectorPrefilter: true,
+ enableGraphDiffusion: true,
+ diffusionTopK: 7,
+ enableLLMRecall: false,
+ },
+});
+assert.deepEqual(state.vectorCalls, [3]);
+assert.equal(state.diffusionCalls.length, 1);
+assert.equal(state.diffusionCalls[0].options.topK, 7);
+
+console.log("retrieval-config tests passed");