Add files via upload

core/fractal-memory.js

@@ -0,0 +1,229 @@
+import { getContext, extension_settings } from "/scripts/extensions.js";
+import { setExtensionPrompt, eventSource, event_types } from "/script.js";
+import { callAI } from "./api.js";
+import { callNgmsAI } from "./api/Ngms_api.js";
+import { extensionName } from "../utils/settings.js";
+import { getMemoryState, updateRow, insertRow, deleteRow, clearAllTables } from "./table-system/manager.js";
+
+const FRACTAL_INJECTION_KEY = 'HANLINYUAN_FRACTAL_MEMORY';
+const BUFFER_SIZE = 5;
+const UPDATE_INTERVAL = 5;
+
+
+
+export async function initializeFractalMemory() {
+    eventSource.on(event_types.MESSAGE_RECEIVED, handleMessageReceived);
+    console.log('[分形记忆] 系统已启动，正在构建多维记忆...');
+}
+
+let messageCounter = 0;
+
+async function handleMessageReceived() {
+    messageCounter++;
+    if (messageCounter >= UPDATE_INTERVAL) {
+        messageCounter = 0;
+        await updateSceneLayer();
+    }
+}
+
+async function updateSceneLayer() {
+    const context = getContext();
+    const settings = extension_settings[extensionName];
+    
+    if (!settings.fractalMemory) {
+        settings.fractalMemory = {
+            saga: "故事刚刚开始...",
+            arc: [],
+            scene: []
+        };
+    }
+    const memory = settings.fractalMemory;
+
+    console.log('[分形记忆] 正在提取近期事态...');
+
+    const recentChat = context.chat.slice(-UPDATE_INTERVAL).map(m => `${m.name}: ${m.mes}`).join('\n');
+    
+    const prompt = `
+请将以下对话总结为一句话的“场景事件”，描述发生了什么。
+要求：简洁、客观、包含关键动作。
+
+【对话内容】
+${recentChat}
+
+【输出】
+(仅输出一句话总结)
+`;
+    
+    const newEvent = await _callLLM(prompt);
+    if (!newEvent) return;
+
+    console.log(`[分形记忆] 新增场景事件: ${newEvent}`);
+    memory.scene.push(newEvent);
+
+    if (memory.scene.length >= BUFFER_SIZE) {
+        await compressSceneToArc();
+    }
+
+    context.saveSettingsDebounced();
+    injectFractalMemory();
+    syncToTables();
+}
+
+async function compressSceneToArc() {
+    const context = getContext();
+    const settings = extension_settings[extensionName];
+    const memory = settings.fractalMemory;
+
+    console.log('[分形记忆] 场景层已满，正在压缩至篇章层...');
+
+    const sceneEvents = memory.scene.join('\n');
+    const prompt = `
+请将以下 5 个连续的“场景事件”合并总结为一条“篇章节点”。
+这条节点应该概括这一系列事件对剧情的推动作用。
+
+【场景事件列表】
+${sceneEvents}
+
+【输出】
+(仅输出一句话总结)
+`;
+
+    const newArcEvent = await _callLLM(prompt);
+    if (!newArcEvent) return;
+
+    console.log(`[分形记忆] 新增篇章节点: ${newArcEvent}`);
+    
+    memory.arc.push(newArcEvent);
+    memory.scene = [];
+
+    if (memory.arc.length >= BUFFER_SIZE) {
+        await compressArcToSaga();
+    }
+}
+
+async function compressArcToSaga() {
+    const context = getContext();
+    const settings = extension_settings[extensionName];
+    const memory = settings.fractalMemory;
+
+    console.log('[分形记忆] 篇章层已满，正在重写宏观史诗...');
+
+    const arcEvents = memory.arc.join('\n');
+    const oldSaga = memory.saga;
+
+    const prompt = `
+请根据“旧的宏观史诗”和新发生的“篇章事件”，重写并更新整个故事的“宏观史诗”。
+宏观史诗应该是一个高度概括的段落，描述故事的起因、经过和当前状态。
+
+【旧史诗】
+${oldSaga}
+
+【新篇章事件】
+${arcEvents}
+
+【输出】
+(输出一段更新后的宏观史诗，约 100-200 字)
+`;
+
+    const newSaga = await _callLLM(prompt);
+    if (!newSaga) return;
+
+    console.log(`[分形记忆] 宏观史诗已更新。`);
+    
+    memory.saga = newSaga;
+    memory.arc = [];
+}
+
+function syncToTables() {
+    const settings = extension_settings[extensionName];
+    if (!settings || !settings.fractalMemory) return;
+    const memory = settings.fractalMemory;
+    const tables = getMemoryState();
+    if (!tables) return;
+
+    const targetTableName = '【系统】分形记忆';
+    const tableIndex = tables.findIndex(t => t.name === targetTableName);
+    
+    if (tableIndex !== -1) {
+        const table = tables[tableIndex];
+        const targetRows = [];
+
+        targetRows.push({
+            0: '宏观史诗',
+            1: memory.saga
+        });
+
+        memory.arc.forEach((event, i) => {
+            targetRows.push({
+                0: `篇章-${i+1}`,
+                1: event
+            });
+        });
+
+        memory.scene.forEach((event, i) => {
+            targetRows.push({
+                0: `场景-${i+1}`,
+                1: event
+            });
+        });
+
+        while (table.rows.length > targetRows.length) {
+            deleteRow(tableIndex, table.rows.length - 1);
+        }
+
+        targetRows.forEach((rowData, i) => {
+            if (i < table.rows.length) {
+                updateRow(tableIndex, i, rowData);
+            } else {
+                insertRow(tableIndex, rowData);
+            }
+        });
+    }
+}
+
+export function injectFractalMemory() {
+    const settings = extension_settings[extensionName];
+    if (!settings || !settings.fractalMemory) return;
+
+    const memory = settings.fractalMemory;
+
+    let content = `【分形记忆系统】\n`;
+    
+    content += `[宏观史诗]\n${memory.saga}\n\n`;
+    
+    if (memory.arc.length > 0) {
+        content += `[当前篇章]\n${memory.arc.map(e => `- ${e}`).join('\n')}\n\n`;
+    }
+    
+    if (memory.scene.length > 0) {
+        content += `[近期事态]\n${memory.scene.map(e => `- ${e}`).join('\n')}`;
+    }
+
+    setExtensionPrompt(
+        FRACTAL_INJECTION_KEY,
+        content,
+        0, 
+        4, 
+        false,
+        0
+    );
+}
+
+
+async function _callLLM(prompt) {
+    const settings = extension_settings[extensionName];
+    const messages = [{ role: 'user', content: prompt }];
+    
+    try {
+        let responseText = '';
+        if (settings.ngmsEnabled) {
+            responseText = await callNgmsAI(messages);
+        } else {
+            responseText = await callAI(messages);
+        }
+        return responseText.trim();
+    } catch (error) {
+        console.error('[分形记忆] AI 调用失败:', error);
+        return null;
+    }
+}