""" agentos check — 全系统健康检查 """ import sys import subprocess from pathlib import Path from .utils import ( get_sync_root, get_local_root, get_python, get_npx, info, ok, warn, err, run, banner ) def check_item(name: str, status: str, detail: str = ""): """输出检查项""" icon = {"ok": "✅", "warn": "⚠️ ", "fail": "❌"} label = {"ok": "通过", "warn": "警告", "fail": "失败"} print(f" {icon.get(status, '❓')} [{label.get(status, '未知')}] {name}") if detail: print(f" {detail}") def cmd_check(quick: bool = False): """执行全系统健康检查""" banner() sync_root = get_sync_root() local_root = get_local_root() print("=" * 60) print(" 全系统健康检查") print("=" * 60) print() # 1. 目录结构 print("📁 目录结构:") check_item("agent-sync 根目录", "ok" if sync_root.exists() else "fail", str(sync_root)) check_item("agent-local 根目录", "ok" if local_root.exists() else "fail", str(local_root)) sync_skills = sync_root / "02_skills" sync_skills_count = len([d for d in sync_skills.iterdir() if d.is_dir() and (d / "SKILL.md").exists()]) if sync_skills.exists() else 0 check_item(f"技能目录 ({sync_skills_count} 个)", "ok" if sync_skills_count > 0 else "warn") local_materials = local_root / "materials" if local_root.exists() else None local_raw = local_root / "memory/raw" if local_root.exists() else None materials_exist = local_materials and local_materials.exists() raw_exist = local_raw and local_raw.exists() check_item("materials/", "ok" if materials_exist else "warn", "采集素材目录") check_item("memory/raw/", "ok" if raw_exist else "warn", "L3 记忆原文目录") # 2. 软链接 print("\n🔗 软链接:") symlinks_to_check = [ ("04_memory/long_term/raw", local_root / "memory/raw"), ("04_memory/vector_db", local_root / "memory/vector_db"), ("06_runtime/cache", local_root / "runtime/cache"), ] for link_rel, target in symlinks_to_check: link_path = sync_root / link_rel if link_path.is_symlink(): actual = link_path.resolve() expected = target.resolve() if actual == expected: check_item(f"{link_rel} → OK", "ok") else: check_item(f"{link_rel} → 指向错误", "warn", f"实际: {actual}, 期望: {expected}") elif link_path.exists(): check_item(f"{link_rel} → 真实目录", "ok") else: check_item(f"{link_rel} → 不存在", "fail") # 3. Python 环境 print("\n🐍 Python 环境:") py = get_python() if Path(py).exists(): result = run([py, "--version"]) check_item("Python 版本", "ok" if result.returncode == 0 else "fail", result.stdout.strip() if result.returncode == 0 else "") else: check_item("Python 可执行文件", "fail", py) # 关键依赖检查 deps = ["chromadb", "trafilatura", "feedparser", "sqlite_utils"] for dep in deps: result = run([py, "-c", f"import {dep}"]) check_item(f"依赖: {dep}", "ok" if result.returncode == 0 else "fail") if quick: print("\n" + "=" * 60) ok("快速检查完成") return # 4. oMLX print("\n🤖 本地 LLM 引擎:") try: import json, urllib.request data = json.dumps({"model": "Qwen3-Embedding-0.6B-4bit-DWQ", "input": ["test"]}).encode() req = urllib.request.Request( "http://localhost:8000/v1/embeddings", data=data, headers={"Authorization": "Bearer omlx", "Content-Type": "application/json"}, method="POST", ) resp = urllib.request.urlopen(req, timeout=5) check_item("oMLX Embedding API", "ok" if resp.status == 200 else "fail", f"状态码 {resp.status}") except Exception as e: check_item("oMLX Embedding API", "fail", str(e)) # 音频转文字能力检查 print("\n🎙️ 音频转文字:") ffmpeg = run(["which", "ffmpeg"]) if ffmpeg.returncode == 0: check_item("ffmpeg（系统工具）", "ok", "已安装") else: check_item("ffmpeg（系统工具）", "warn", "未安装，音频转文字不可用。运行: brew install ffmpeg") whisper_check = run([py, "-m", "pip", "show", "openai-whisper"]) if whisper_check.returncode == 0: import re ver_match = re.search(r"Version:\s*(\S+)", whisper_check.stdout) ver = ver_match.group(1) if ver_match else "?" check_item("openai-whisper（Python包）", "ok", f"v{ver}") # 检查模型是否已下载 import os as _os whisper_cache = _os.path.expanduser("~/.cache/whisper") if _os.path.exists(whisper_cache): models = [f for f in _os.listdir(whisper_cache) if f.endswith(('.pt', '.bin'))] if models: model_sizes = [_os.path.getsize(_os.path.join(whisper_cache, m)) / 1024 / 1024 for m in models] detail = ", ".join([f"{m} ({s:.0f}MB)" for m, s in zip(models, model_sizes)]) check_item("Whisper 模型权重", "ok", f"已缓存: {detail}") else: check_item("Whisper 模型权重", "warn", "首次使用时会自动下载（~1.5GB）") else: check_item("Whisper 模型权重", "warn", "未下载，首次运行自动下载（~1.5GB）") else: check_item("openai-whisper（Python包）", "fail", "未安装，运行: pip install openai-whisper") # 5. facts.db print("\n🗄️ 记忆层:") facts_db = sync_root / "04_memory" / "long_term" / "facts.db" if facts_db.exists(): size_kb = facts_db.stat().st_size / 1024 result = run([py, "-c", f""" import sqlite3 conn = sqlite3.connect('{facts_db}') c = conn.cursor() c.execute("SELECT COUNT(*) FROM facts") count = c.fetchone()[0] c.execute("SELECT COUNT(DISTINCT subject) FROM facts") subjects = c.fetchone()[0] conn.close() print(f"条目: {{count}}, 主题: {{subjects}}") """]) check_item(f"facts.db ({size_kb:.1f} KB)", "ok", result.stdout.strip() if result.returncode == 0 else "读取异常") else: check_item("facts.db", "warn", "不存在（首次初始化正常）") # 6. 向量库 vector_db = local_root / "vector_db" / "global" / "chroma" if vector_db.exists(): chroma_files = list(vector_db.glob("*.sqlite3")) check_item("global 向量库", "ok" if chroma_files else "warn", f"目录存在但无 .sqlite3 文件" if not chroma_files else "") else: check_item("global 向量库", "warn", "未建，运行 agentos init 或 vector_db_rebuild.py 重建") # 7. WorkBuddy 技能注册 print("\n📦 技能注册状态:") wb_skills = Path.home() / ".workbuddy" / "skills" sync_skills_dir = sync_root / "02_skills" if wb_skills.exists() and sync_skills_dir.exists(): wb_names = {d.name for d in wb_skills.iterdir() if d.is_dir()} src_names = {d.name for d in sync_skills_dir.iterdir() if d.is_dir() and (d / "SKILL.md").exists()} missing = src_names - wb_names extra = wb_names - src_names if missing: check_item(f"未注册到 WorkBuddy ({len(missing)} 个)", "warn", ", ".join(sorted(missing))) if extra: check_item(f"WB 中多余的 ({len(extra)} 个)", "warn", ", ".join(sorted(extra))) if not missing and not extra: check_item(f"技能一致性 ({len(src_names)} 个)", "ok", "源目录与 WB 注册一致") # 8. 磁盘 print("\n💾 磁盘空间:") import shutil usage = shutil.disk_usage(str(Path.home())) free_gb = usage.free / (1024 ** 3) total_gb = usage.total / (1024 ** 3) pct = usage.free / usage.total * 100 status = "ok" if pct > 10 else "warn" check_item(f"磁盘剩余", status, f"{free_gb:.0f} GB / {total_gb:.0f} GB ({pct:.0f}%)") print() print("=" * 60) ok("健康检查完成") print() def install_deps(dry_run: bool = False): """安装 Python 依赖（被 init 调用）""" py = get_python() req_file = get_sync_root() / "requirements.txt" if not req_file.exists(): warn(f"requirements.txt 不存在: {req_file}") return if dry_run: info(f" [DRY-RUN] pip install -r {req_file}") return info("安装 Python 依赖...") result = run([py, "-m", "pip", "install", "-r", str(req_file), "--quiet"]) if result.returncode == 0: ok("Python 依赖安装完成") else: warn(f"部分依赖安装失败:\n{result.stderr[:200]}") # 检查并提示安装 ffmpeg（音频转文字需要） ffmpeg = run(["which", "ffmpeg"]) if ffmpeg.returncode != 0: print() warn("音频转文字功能需要 ffmpeg 系统工具") info(" 运行以下命令安装:") info(" brew install ffmpeg") print() def cmd_run(args): cmd_check(quick=args.quick)