封装Agent
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ACT丶流星雨
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91
src/agents/productionAgent/index.ts
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91
src/agents/productionAgent/index.ts
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@ -0,0 +1,91 @@
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import { createAGUIStream } from "@/utils/agent/aguiTools";
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import u from "@/utils";
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import Memory from "@/utils/agent/memory";
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import { useSkill } from "@/utils/agent/skillsTools";
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// import tools from "@/agents/productionAgent/tools";
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function buildSystemPrompt(skillPrompt: string, mem: Awaited<ReturnType<Memory["get"]>>): string {
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let memoryContext = "";
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if (mem.rag.length) {
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memoryContext += `[相关记忆]\n${mem.rag.map((r) => r.content).join("\n")}`;
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}
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if (mem.summaries.length) {
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if (memoryContext) memoryContext += "\n\n";
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memoryContext += `[历史摘要]\n${mem.summaries.map((s, i) => `${i + 1}. ${s.content}`).join("\n")}`;
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}
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if (mem.shortTerm.length) {
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if (memoryContext) memoryContext += "\n\n";
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memoryContext += `[近期对话]\n${mem.shortTerm.map((m) => `${m.role}: ${m.content}`).join("\n")}`;
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}
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if (!memoryContext) return skillPrompt;
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return `${skillPrompt}\n\n## Memory\n以下是你对用户的记忆，可作为参考但不要主动提及：\n${memoryContext}`;
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}
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export async function decisionAI(agui: ReturnType<typeof createAGUIStream>, isolationKey: string, text: string) {
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const memory = new Memory("productionAgent", isolationKey);
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await memory.add("user", text);
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const [skill, mem] = await Promise.all([useSkill("production-agent", "decision"), memory.get(text)]);
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const systemPrompt = buildSystemPrompt(skill.prompt, mem);
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console.log("%c Line:30 🍊 systemPrompt", "background:#33a5ff", systemPrompt);
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const { textStream } = await u.Ai.Text("productionAgent").stream({
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system: systemPrompt,
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messages: [{ role: "user", content: text }],
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tools: {
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...skill.tools,
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...memory.getTools(),
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},
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onFinish: async (completion) => {
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await memory.add("decisionAI", completion.text);
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},
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});
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return textStream;
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}
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export async function executionAI(agui: ReturnType<typeof createAGUIStream>, isolationKey: string, text: string) {
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const memory = new Memory("productionAgent", isolationKey);
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await memory.add("user", text);
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const [skill, mem] = await Promise.all([useSkill("production-agent", "execution"), memory.get(text)]);
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const systemPrompt = buildSystemPrompt(skill.prompt, mem);
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const { textStream } = await u.Ai.Text("productionAgent").stream({
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system: systemPrompt,
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messages: [{ role: "user", content: text }],
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tools: {
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...skill.tools,
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...memory.getTools(),
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},
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onFinish: async (completion) => {
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await memory.add("executionAI", completion.text);
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},
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});
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return textStream;
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}
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export async function supervisionAI(agui: ReturnType<typeof createAGUIStream>, isolationKey: string, text: string) {
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agui.custom("systemMessage", "已由 监督层AI 接管对话");
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const memory = new Memory("productionAgent", isolationKey);
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await memory.add("user", text);
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const [skill, mem] = await Promise.all([useSkill("production-agent", "supervision"), memory.get(text)]);
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const systemPrompt = buildSystemPrompt(skill.prompt, mem);
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const { textStream } = await u.Ai.Text("productionAgent").stream({
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system: systemPrompt,
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messages: [{ role: "user", content: text }],
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tools: {
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...skill.tools,
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...memory.getTools(),
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},
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onFinish: async (completion) => {
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await memory.add("supervisionAI", completion.text);
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},
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});
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return textStream;
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}
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@ -2,74 +2,5 @@ import { tool } from "ai";
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import { z } from "zod";
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import u from "@/utils";
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import { useSkill } from "@/utils/agent/skillsTools";
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import { createAGUIStream } from "@/utils/agent/aguiTools";
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interface FlowData {
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script: {
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blocks: string[];
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};
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}
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export default (isolationKey: string, agui: ReturnType<typeof createAGUIStream>) => {
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const flowData: FlowData = {
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script: {
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blocks: [],
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},
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};
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return {
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get_project_info: tool({
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description: "获取项目信息",
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inputSchema: z.object({}),
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execute: async () => {
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return `
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项目名称：仙逆
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视频风格：玄幻3D动漫
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视频类型：短剧
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项目描述：讲述了乡村平凡少年王林以心中之感动，逆仙而修，求的不仅是长生，更多的是摆脱那背后的蝼蚁之身。他坚信道在人为，以平庸的资质踏入修真仙途，历经坎坷风雨，凭着其聪睿的心智，一步一步走向巅峰，凭一己之力，扬名修真界。
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总集数：24集每集2分钟
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当前集数：3集
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`;
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},
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}),
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get_state: tool({
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description: "获取工作流指定板块数据",
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inputSchema: z.object({
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block: z.enum(["script"]).describe("板块名称，如 script"),
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}),
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execute: async ({ block }) => {
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return flowData[block];
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},
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}),
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execution: tool({
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description: "执行层，负责具体执行具体的任务",
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inputSchema: z.object({
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taskDescription: z.string().describe("具体的任务描述详细信息"),
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}),
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execute: async ({ taskDescription }) => {
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agui.custom("systemMessage", "已由 执行层AI 接管对话");
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const skill = await useSkill("production-agent", "execution");
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const { textStream } = await u.Ai.Text("productionAgent").stream({
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system: skill.prompt,
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messages: [{ role: "user", content: `请完成任务：${taskDescription}` }],
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tools: {
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...skill.tools,
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},
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});
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let msg: ReturnType<typeof agui.textMessage> | null = null;
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let fullResponse = "";
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for await (const chunk of textStream) {
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if (!msg) msg = agui.textMessage();
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msg.send(chunk);
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fullResponse += chunk;
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}
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msg?.end();
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return { found: true, memories: ["第一条记忆内容", "第二条记忆内容"] };
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},
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}),
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};
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};
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@ -1,59 +1,17 @@
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import express from "express";
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import { createAGUIStream } from "@/utils/agent/aguiTools";
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import u from "@/utils";
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import Memory from "@/utils/agent/memory";
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import { useSkill } from "@/utils/agent/skillsTools";
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import tools from "@/agents/productionAgent/tools";
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import * as agent from "@/agents/productionAgent/index";
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const router = express.Router();
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function delay(ms: number) {
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return new Promise((resolve) => setTimeout(resolve, ms));
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}
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export default router.post("/", async (req, res) => {
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const { prompt: text, projectId, episodesId } = req.body;
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const isolationKey = `${projectId}:${episodesId}`;
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//记忆
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const memory = new Memory("productionAgent", isolationKey);
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//skill
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const skill = await useSkill("production-agent", "decision");
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const agui = createAGUIStream(res);
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agui.runStarted();
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agui.custom("systemMessage", "已由 决策层AI 接管对话");
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// 存入用户消息
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await memory.add("user", text);
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// 获取记忆上下文
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const mem = await memory.get(text);
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const memoryContext = [
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mem.rag.length > 0 && `[相关记忆]\n${mem.rag.map((r) => r.content).join("\n")}`,
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mem.summaries.length > 0 && `[历史摘要]\n${mem.summaries.map((s, i) => `${i + 1}. ${s.content}`).join("\n")}`,
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mem.shortTerm.length > 0 && `[近期对话]\n${mem.shortTerm.map((m) => `${m.role}: ${m.content}`).join("\n")}`,
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]
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.filter(Boolean)
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.join("\n\n");
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const systemPrompt = [skill.prompt, memoryContext && `## Memory\n以下是你对用户的记忆，可作为参考但不要主动提及：\n${memoryContext}`]
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.filter(Boolean)
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.join("\n\n");
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const { textStream } = await u.Ai.Text("productionAgent").stream({
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system: systemPrompt,
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messages: [{ role: "user", content: text }],
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tools: {
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...skill.tools,
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...memory.getTools(),
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...tools(isolationKey, agui),
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},
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onFinish: async (completion) => {
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// 存入助手回复
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await memory.add("decisionAI", completion.text);
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},
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});
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const textStream = await agent.decisionAI(agui, isolationKey, text);
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let msg: ReturnType<typeof agui.textMessage> | null = null;
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let fullResponse = "";
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@ -97,11 +97,11 @@ class Memory {
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embedding: JSON.stringify(embedding),
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relatedMessageIds: null,
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summarized: 0,
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createdAt: Date.now(),
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createTime: Date.now(),
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} as any);
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// 检查未总结消息数量
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const unsummarized = await u.db("memories").where({ isolationKey, type: "message", summarized: 0 }).orderBy("createdAt", "asc");
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const unsummarized = await u.db("memories").where({ isolationKey, type: "message", summarized: 0 }).orderBy("createTime", "asc");
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if (unsummarized.length >= Number(messagesPerSummary)) {
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const batch = unsummarized.slice(0, Number(messagesPerSummary));
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@ -120,7 +120,7 @@ class Memory {
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embedding: JSON.stringify(summaryEmbedding),
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relatedMessageIds: JSON.stringify(batchIds),
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summarized: 0,
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createdAt: Date.now(),
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createTime: Date.now(),
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} as any);
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// 标记已总结
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@ -140,12 +140,12 @@ class Memory {
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const shortTerm = await u
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.db("memories")
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.where({ isolationKey, type: "message", summarized: 0 })
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.orderBy("createdAt", "desc")
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.orderBy("createTime", "desc")
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.limit(Number(shortTermLimit));
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shortTerm.reverse(); // 最旧在前
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// summaries: 最近的 summary
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const summaries = await u.db("memories").where({ isolationKey, type: "summary" }).orderBy("createdAt", "desc").limit(Number(summaryLimit));
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const summaries = await u.db("memories").where({ isolationKey, type: "summary" }).orderBy("createTime", "desc").limit(Number(summaryLimit));
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summaries.reverse();
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// rag: 向量搜索所有 messages
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@ -154,12 +154,12 @@ class Memory {
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const ragResults = vectorSearch(allMessages, queryEmbedding, Number(ragLimit));
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return {
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shortTerm: shortTerm.map((m: any) => ({ id: m.id, role: m.role, content: m.content, createdAt: m.createdAt })),
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shortTerm: shortTerm.map((m: any) => ({ id: m.id, role: m.role, content: m.content, createTime: m.createTime })),
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summaries: summaries.map((s) => ({
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id: s.id,
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content: s.content,
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relatedMessageIds: JSON.parse(s.relatedMessageIds || "[]"),
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createdAt: (s as any).createdAt,
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createTime: (s as any).createTime,
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})),
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rag: ragResults.map((r) => ({ id: r.id, content: r.content, similarity: r.similarity })),
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};
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@ -190,9 +190,9 @@ class Memory {
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if (messageIds.length === 0) return [];
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const messages = await u.db("memories").whereIn("id", messageIds).orderBy("createdAt", "asc");
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const messages = await u.db("memories").whereIn("id", messageIds).orderBy("createTime", "asc");
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return messages.map((m) => ({ id: m.id, content: m.content, createdAt: m.createdAt }));
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return messages.map((m) => ({ id: m.id, content: m.content, createTime: m.createTime }));
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}
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getTools() {
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