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175 lines
6.9 KiB
175 lines
6.9 KiB
# s09: Agent Teams (智能体团队)
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`s01 > s02 > s03 > s04 > s05 > s06 | s07 > s08 > [ s09 ] s10 > s11 > s12`
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> *"任务太大一个人干不完, 要能分给队友"* -- 持久化队友 + JSONL 邮箱。
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>
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> **Harness 层**: 团队邮箱 -- 多个模型, 通过文件协调。
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## 问题
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子智能体 (s04) 是一次性的: 生成、干活、返回摘要、消亡。没有身份, 没有跨调用的记忆。后台任务 (s08) 能跑 shell 命令, 但做不了 LLM 引导的决策。
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真正的团队协作需要三样东西: (1) 能跨多轮对话存活的持久智能体, (2) 身份和生命周期管理, (3) 智能体之间的通信通道。
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## 解决方案
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```
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Teammate lifecycle:
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spawn -> WORKING -> IDLE -> WORKING -> ... -> SHUTDOWN
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Communication:
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.team/
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config.json <- team roster + statuses
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inbox/
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alice.jsonl <- append-only, drain-on-read
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bob.jsonl
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lead.jsonl
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+--------+ send("alice","bob","...") +--------+
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| alice | -----------------------------> | bob |
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| loop | bob.jsonl << {json_line} | loop |
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+--------+ +--------+
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^ |
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| BUS.read_inbox("alice") |
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+---- alice.jsonl -> read + drain ---------+
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```
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## 工作原理
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1. TeammateManager 通过 config.json 维护团队名册。
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```java
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// src/main/java/io/mybatis/learn/s09/TeammateManager.java
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public class TeammateManager {
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private final ChatModel chatModel;
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private final MessageBus bus;
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private final Path configPath;
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private final ObjectMapper mapper = new ObjectMapper();
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private Map<String, Object> config;
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// Python用threading.Thread + dict; Java用ConcurrentHashMap天然线程安全
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private final Map<String, Thread> threads = new ConcurrentHashMap<>();
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public TeammateManager(ChatModel chatModel, MessageBus bus, Path teamDir) {
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this.chatModel = chatModel;
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this.bus = bus;
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this.configPath = teamDir.resolve("config.json");
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Files.createDirectories(teamDir);
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this.config = loadConfig();
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}
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```
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2. `spawn()` 创建队友并在线程中启动 agent loop。
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```java
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// Python用threading.Thread; Java用Thread.startVirtualThread()虚拟线程
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public synchronized String spawn(String name, String role, String prompt) {
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Map<String, Object> member = new LinkedHashMap<>();
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member.put("name", name);
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member.put("role", role);
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member.put("status", "working");
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((List<Map<String, Object>>) config.get("members")).add(member);
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saveConfig();
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// 虚拟线程：轻量级，由JVM调度，不占用OS线程
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Thread thread = Thread.startVirtualThread(
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() -> teammateLoop(name, role, prompt));
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threads.put(name, thread);
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return "Spawned '" + name + "' (role: " + role + ")";
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}
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```
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3. MessageBus: append-only 的 JSONL 收件箱。`send()` 追加一行; `read_inbox()` 读取全部并清空。
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```java
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// src/main/java/io/mybatis/learn/core/team/MessageBus.java
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// Python靠GIL隐式保证线程安全; Java用synchronized显式保证
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public class MessageBus {
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private final Path inboxDir;
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private final ObjectMapper mapper = new ObjectMapper();
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public synchronized String send(String sender, String to, String content,
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String msgType, Map<String, Object> extra) {
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Map<String, Object> msg = new LinkedHashMap<>();
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msg.put("type", msgType);
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msg.put("from", sender);
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msg.put("content", content);
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msg.put("timestamp", System.currentTimeMillis() / 1000.0);
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if (extra != null) msg.putAll(extra);
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Path inbox = inboxDir.resolve(to + ".jsonl");
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Files.writeString(inbox, mapper.writeValueAsString(msg) + "\n",
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StandardOpenOption.CREATE, StandardOpenOption.APPEND);
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return "Sent " + msgType + " to " + to;
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}
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public synchronized List<Map<String, Object>> readInbox(String name) {
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Path inbox = inboxDir.resolve(name + ".jsonl");
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if (!Files.exists(inbox)) return List.of();
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List<Map<String, Object>> messages = new ArrayList<>();
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for (String line : Files.readAllLines(inbox)) {
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if (!line.isBlank())
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messages.add(mapper.readValue(line, new TypeReference<>() {}));
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}
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Files.writeString(inbox, ""); // drain
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return messages;
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}
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}
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```
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4. 每个队友在每次 `call()` 调用间检查收件箱, 将消息注入上下文。ChatClient 的 `call()` 等价于 Python 的完整工具循环（循环到 `stop_reason != "tool_use"` 为止）。
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```java
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// Python队友在每次LLM调用前检查收件箱; Java在每次call()调用间检查
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protected void teammateLoop(String name, String role, String initialPrompt) {
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String sysPrompt = String.format(
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"You are '%s', role: %s. Use send_message to communicate.",
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name, role);
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var messageTool = new TeammateMessageTool(bus, name);
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ChatClient client = ChatClient.builder(chatModel)
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.defaultSystem(sysPrompt)
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.defaultTools(new BashTool(), new ReadFileTool(),
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new WriteFileTool(), new EditFileTool(), messageTool)
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.build();
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// 初始工作（call() = 完整工具链，等价于Python循环到stop_reason != "tool_use"）
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String response = client.prompt(initialPrompt).call().content();
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// 每次call()之间检查收件箱（而非Python的每次LLM调用之间）
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for (int round = 0; round < 50; round++) {
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Thread.sleep(2000);
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var inbox = bus.readInbox(name);
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if (inbox.isEmpty()) break;
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String inboxJson = mapper.writeValueAsString(inbox);
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response = client.prompt("<inbox>" + inboxJson + "</inbox>").call().content();
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}
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setStatus(name, "idle");
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}
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```
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## 相对 s08 的变更
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| 组件 | 之前 (s08) | 之后 (s09) |
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|----------------|------------------|------------------------------------|
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| Tools | 6 | 9 (+spawn/send/read_inbox) |
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| 智能体数量 | 单一 | 领导 + N 个队友 |
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| 持久化 | 无 | config.json + JSONL 收件箱 |
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| 线程 | 后台命令 | 每线程完整 agent loop |
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| 生命周期 | 一次性 | idle -> working -> idle |
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| 通信 | 无 | message + broadcast |
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## 试一试
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```sh
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cd learn-claude-code
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mvn exec:java -Dexec.mainClass=io.mybatis.learn.s09.S09AgentTeams
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```
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试试这些 prompt (英文 prompt 对 LLM 效果更好, 也可以用中文):
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1. `Spawn alice (coder) and bob (tester). Have alice send bob a message.`
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2. `Broadcast "status update: phase 1 complete" to all teammates`
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3. `Check the lead inbox for any messages`
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4. 输入 `/team` 查看团队名册和状态
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5. 输入 `/inbox` 手动检查领导的收件箱
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