#!/usr/bin/env python3 """ s13: 后台任务 — 基于线程的异步执行 + 通知注入。 运行: python s13_background_tasks/code.py 需要: pip install anthropic python-dotenv + .env 中配置 ANTHROPIC_API_KEY 相对 s12 的变化: - 使用 threading.Thread 做后台执行 - background_tasks 字典跟踪生命周期(bg_id、command、status) - background_results 字典 + threading.Lock 实现线程安全存储 - should_run_background:模型通过 run_in_background 参数显式请求 - is_slow_operation:当模型未指定时使用的兜底启发式判断 - start_background_task:分发到守护线程,返回后台任务 id - collect_background_results:收集已完成任务,并以通知形式返回 - agent_loop:慢操作 → 后台执行 + 占位结果,随后注入通知 - 通知使用 格式,不复用 tool_use_id 说明:教学代码保留一个基础 Agent 循环,以便聚焦后台任务。 S11 的完整错误恢复(RecoveryState、退避、升级、reactive compact、备用模型)被省略。 """ import os, subprocess, json, time, random, threading from pathlib import Path from dataclasses import dataclass, asdict try: import readline readline.parse_and_bind('set bind-tty-special-chars off') except ImportError: pass from anthropic import Anthropic from dotenv import load_dotenv load_dotenv(override=True) if os.getenv("ANTHROPIC_BASE_URL"): os.environ.pop("ANTHROPIC_AUTH_TOKEN", None) WORKDIR = Path.cwd() MEMORY_DIR = WORKDIR / ".memory" MEMORY_INDEX = MEMORY_DIR / "MEMORY.md" client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL")) MODEL = os.environ["MODEL_ID"] # ── 任务系统 (来自 s12,已同步) ── TASKS_DIR = WORKDIR / ".tasks" TASKS_DIR.mkdir(exist_ok=True) @dataclass class Task: id: str subject: str description: str status: str # pending | in_progress | completed owner: str | None blockedBy: list[str] def _task_path(task_id: str) -> Path: return TASKS_DIR / f"{task_id}.json" def create_task(subject: str, description: str = "", blockedBy: list[str] | None = None) -> Task: task = Task( id=f"task_{int(time.time())}_{random.randint(0, 9999):04d}", subject=subject, description=description, status="pending", owner=None, blockedBy=blockedBy or [], ) save_task(task) return task def save_task(task: Task): _task_path(task.id).write_text(json.dumps(asdict(task), indent=2)) def load_task(task_id: str) -> Task: return Task(**json.loads(_task_path(task_id).read_text())) def list_tasks() -> list[Task]: return [Task(**json.loads(p.read_text())) for p in sorted(TASKS_DIR.glob("task_*.json"))] def get_task(task_id: str) -> str: """以 JSON 返回完整任务详情。""" task = load_task(task_id) return json.dumps(asdict(task), indent=2) def can_start(task_id: str) -> bool: """检查所有 blockedBy 依赖是否已完成;缺失依赖视为阻塞。""" task = load_task(task_id) for dep_id in task.blockedBy: if not _task_path(dep_id).exists(): return False if load_task(dep_id).status != "completed": return False return True def claim_task(task_id: str, owner: str = "agent") -> str: task = load_task(task_id) if task.status != "pending": status = {"pending": "待处理", "in_progress": "进行中", "completed": "已完成"}.get(task.status, task.status) return f"任务 {task_id} 当前状态为 {status},无法认领" if not can_start(task_id): deps = [d for d in task.blockedBy if not _task_path(d).exists() or load_task(d).status != "completed"] return f"被阻塞于:{deps}" task.owner = owner task.status = "in_progress" save_task(task) print(f" \033[36m[认领] {task.subject} → in_progress(负责人:{owner})\033[0m") return f"已认领 {task.id} ({task.subject})" def complete_task(task_id: str) -> str: task = load_task(task_id) if task.status != "in_progress": status = {"pending": "待处理", "in_progress": "进行中", "completed": "已完成"}.get(task.status, task.status) return f"任务 {task_id} 当前状态为 {status},无法完成" task.status = "completed" save_task(task) unblocked = [t.subject for t in list_tasks() if t.status == "pending" and t.blockedBy and can_start(t.id)] print(f" \033[32m[完成] {task.subject} ✓\033[0m") msg = f"已完成 {task.id} ({task.subject})" if unblocked: msg += f"\n已解除阻塞:{', '.join(unblocked)}" print(f" \033[33m[已解除阻塞] {', '.join(unblocked)}\033[0m") return msg # ── 提示词组装 (来自 s10,已同步) ── PROMPT_SECTIONS = { "identity": "你是一个编码 Agent。直接行动,不要只解释。", "tools": "可用工具:bash, read_file, write_file, " "create_task, list_tasks, get_task, claim_task, complete_task.", "workspace": f"工作目录:{WORKDIR}", "memory": "有可用的相关记忆时,会在下方注入。", } def assemble_system_prompt(context: dict) -> str: sections = [PROMPT_SECTIONS["identity"], PROMPT_SECTIONS["tools"], PROMPT_SECTIONS["workspace"]] memories = context.get("memories", "") if memories: sections.append(f"相关记忆:\n{memories}") return "\n\n".join(sections) _last_context_key, _last_prompt = None, None def get_system_prompt(context: dict) -> str: global _last_context_key, _last_prompt key = json.dumps(context, sort_keys=True, ensure_ascii=False, default=str) if key == _last_context_key and _last_prompt: return _last_prompt _last_context_key = key _last_prompt = assemble_system_prompt(context) return _last_prompt # ── 工具 ── def safe_path(p: str) -> Path: path = (WORKDIR / p).resolve() if not path.is_relative_to(WORKDIR): raise ValueError(f"路径逃逸出工作区:{p}") return path def run_bash(command: str, run_in_background: bool = False) -> str: # run_in_background 由 agent_loop 分发处理,不在这里处理 try: r = subprocess.run(command, shell=True, cwd=WORKDIR, capture_output=True, text=True, timeout=120) out = (r.stdout + r.stderr).strip() return out[:50000] if out else "(无输出)" except subprocess.TimeoutExpired: return "错误:执行超时(120 秒)" def run_read(path: str, limit: int | None = None) -> str: try: lines = safe_path(path).read_text().splitlines() if limit and limit < len(lines): lines = lines[:limit] + [f"... ({len(lines) - limit} 行更多内容)"] return "\n".join(lines) except Exception as e: return f"错误:{e}" def run_write(path: str, content: str) -> str: try: fp = safe_path(path) fp.parent.mkdir(parents=True, exist_ok=True) fp.write_text(content) return f"已写入 {len(content)} 字节到 {path}" except Exception as e: return f"错误:{e}" # 任务工具 def run_create_task(subject: str, description: str = "", blockedBy: list[str] | None = None) -> str: task = create_task(subject, description, blockedBy) deps = f"(依赖:{', '.join(blockedBy)})" if blockedBy else "" print(f" \033[34m[创建] {task.subject}{deps}\033[0m") return f"已创建 {task.id}: {task.subject}{deps}" def run_list_tasks() -> str: 个任务 = list_tasks() if not 个任务: return "暂无任务。请使用 create_task 添加任务。" lines = [] for t in 个任务: icon = {"pending": "○", "in_progress": "●", "completed": "✓"}.get(t.status, "?") deps = f"(依赖:{', '.join(t.blockedBy)})" if t.blockedBy else "" owner = f" [负责人:{t.owner}]" if t.owner else "" status = {"pending": "待处理", "in_progress": "进行中", "completed": "已完成"}.get(t.status, t.status) lines.append(f" {icon} {t.id}: {t.subject} " f"[{status}]{owner}{deps}") return "\n".join(lines) def run_get_task(task_id: str) -> str: try: return get_task(task_id) except FileNotFoundError: return f"错误:任务 {task_id} 未找到" def run_claim_task(task_id: str) -> str: return claim_task(task_id, owner="agent") def run_complete_task(task_id: str) -> str: return complete_task(task_id) TOOLS = [ {"name": "bash", "description": "运行一条 shell 命令。", "input_schema": {"type": "object", "properties": { "command": {"type": "string"}, "run_in_background": {"type": "boolean"}}, "required": ["command"]}}, {"name": "read_file", "description": "读取文件内容。", "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "limit": {"type": "integer"}}, "required": ["path"]}}, {"name": "write_file", "description": "向文件写入内容。", "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}}, {"name": "create_task", "description": "创建一个新任务,可选 blockedBy 依赖。", "input_schema": {"type": "object", "properties": { "subject": {"type": "string"}, "description": {"type": "string"}, "blockedBy": {"type": "array", "items": {"type": "string"}}}, "required": ["subject"]}}, {"name": "list_tasks", "description": "列出所有任务及其状态、负责人和依赖。", "input_schema": {"type": "object", "properties": {}, "required": []}}, {"name": "get_task", "description": "按 ID 获取指定任务的完整详情。", "input_schema": {"type": "object", "properties": {"task_id": {"type": "string"}}, "required": ["task_id"]}}, {"name": "claim_task", "description": "认领一个待处理任务。设置 owner,并将状态改为 in_progress。", "input_schema": {"type": "object", "properties": {"task_id": {"type": "string"}}, "required": ["task_id"]}}, {"name": "complete_task", "description": "完成一个进行中的任务。报告被解除阻塞的下游任务。", "input_schema": {"type": "object", "properties": {"task_id": {"type": "string"}}, "required": ["task_id"]}}, ] TOOL_HANDLERS = { "bash": run_bash, "read_file": run_read, "write_file": run_write, "create_task": run_create_task, "list_tasks": run_list_tasks, "get_task": run_get_task, "claim_task": run_claim_task, "complete_task": run_complete_task, } # ── 后台任务 (s13 新增) ── _bg_计数器 = 0 background_tasks: dict[str, dict] = {} # bg_id → {tool_use_id, command, status} background_results: dict[str, str] = {} # bg_id → 输出 background_lock = threading.Lock() def is_slow_operation(tool_name: str, tool_input: dict) -> bool: """兜底启发式:判断命令是否可能超过 30 秒。""" if tool_name != "bash": return False cmd = tool_input.get("command", "").lower() slow_keywords = ["install", "build", "test", "deploy", "compile", "docker build", "pip install", "npm install", "cargo build", "pytest", "make"] return any(kw in cmd for kw in slow_keywords) def should_run_background(tool_name: str, tool_input: dict) -> bool: """模型的显式请求优先;否则使用启发式兜底。""" if tool_input.get("run_in_background"): return True return is_slow_operation(tool_name, tool_input) def execute_tool(block) -> str: """执行工具调用块并返回输出。""" handler = TOOL_HANDLERS.get(block.name) if handler: return handler(**block.input) return f"未知工具:{block.name}" def start_background_task(block) -> str: """在守护线程中运行工具,并返回后台任务 ID。""" global _bg_计数器 _bg_计数器 += 1 bg_id = f"bg_{_bg_计数器:04d}" cmd = block.input.get("command", block.name) def worker(): result = execute_tool(block) with background_lock: background_tasks[bg_id]["status"] = "completed" background_results[bg_id] = result with background_lock: background_tasks[bg_id] = { "tool_use_id": block.id, "command": cmd, "status": "running", } thread = threading.Thread(target=worker, daemon=True) thread.start() print(f" \033[33m[后台] 已分发 {bg_id}: {cmd[:40]}\033[0m") return bg_id def collect_background_results() -> list[str]: """将已完成的后台结果收集为 task_notification 消息。""" with background_lock: ready_ids = [bid for bid, task in background_tasks.items() if task["status"] == "completed"] notifications = [] for bg_id in ready_ids: with background_lock: task = background_tasks.pop(bg_id) output = background_results.pop(bg_id, "") summary = output[:200] if len(output) > 200 else output notifications.append( f"\n" f" {bg_id}\n" f" completed\n" f" {task['command']}\n" f" {summary}\n" f"") print(f" \033[32m[后台完成] {bg_id}: " f"{task['command'][:40]} ({len(output)} 个字符)\033[0m") return notifications # ── 上下文 ── def update_context(context: dict, messages: list) -> dict: """从真实状态推导上下文。""" memories = "" if MEMORY_INDEX.exists(): content = MEMORY_INDEX.read_text().strip() if content: memories = content return { "enabled_tools": list(TOOL_HANDLERS.keys()), "workspace": str(WORKDIR), "memories": memories, } # ── Agent 循环(简化版,聚焦后台任务) ── def agent_loop(messages: list, context: dict): system = get_system_prompt(context) while True: try: response = client.messages.create( model=MODEL, system=system, messages=messages, tools=TOOLS, max_tokens=8000) except Exception as e: messages.append({"role": "assistant", "content": [ {"type": "text", "text": f"[错误] {type(e).__name__}: {e}"}]}) return messages.append({"role": "assistant", "content": response.content}) if response.stop_reason != "tool_use": return results = [] for block in response.content: if block.type != "tool_use": continue print(f"\033[36m> {block.name}\033[0m") if should_run_background(block.name, block.input): bg_id = start_background_task(block) results.append({"type": "tool_result", "tool_use_id": block.id, "content": f"[后台任务 {bg_id} 已启动] " f"命令:{block.input.get('command', '')}. " f"完成后结果将可用。"}) else: output = execute_tool(block) print(str(output)[:300]) results.append({"type": "tool_result", "tool_use_id": block.id, "content": output}) # 在一条用户消息中注入工具结果 + 后台通知 user_content = list(results) bg_notifications = collect_background_results() if bg_notifications: for notif in bg_notifications: user_content.append({"type": "text", "text": notif}) print(f" \033[32m[注入] {len(bg_notifications)} 条后台通知\033[0m") messages.append({"role": "user", "content": user_content}) context = update_context(context, messages) system = get_system_prompt(context) if __name__ == "__main__": print("s13: 后台任务") print("输入问题后按回车发送。输入 q 退出。\n") history = [] context = update_context({}, []) while True: try: query = input("\033[36ms13 >> \033[0m") except (EOFError, KeyboardInterrupt): break if query.strip().lower() in ("q", "exit", ""): break history.append({"role": "user", "content": query}) agent_loop(history, context) context = update_context(context, history) for block in history[-1]["content"]: if getattr(block, "type", None) == "text": print(block.text) elif isinstance(block, dict) and block.get("type") == "text": print(block.get("text", "")) print()