feat: 移除 etcdutl 引用，增加 ctr/nerdctl 示例，实现 Agent 断点续传

- AI Agent Prompt 移除不存在的 etcdutl 命令引用
- Prompt 增加 containerd(ctr/nerdctl) 和 Linux 基础调优命令示例
- processing_runs 表新增 context_json 字段，保存 Agent 执行上下文
- 每次命令执行后自动保存上下文到 DB

backend/ai_agent.py

@@ -29,8 +29,10 @@ AGENT_SYSTEM_PROMPT = """你是 Kubernetes 自主诊断 Agent。你的首要职
 
 可用工具：
 1. kubectl 命令 - 查询集群内资源状态。例如: kubectl get pods -A, kubectl describe node <name>, kubectl logs <pod> -n <ns>
-2. 系统诊断 shell 命令 - 查询节点宿主机状态。例如: systemctl status kubelet, journalctl -u kubelet -n 100 --no-pager, crictl ps, df -h, free -m, ss -tlnp, ip addr
+2. 系统诊断 shell 命令 - 查询节点宿主机状态。例如: systemctl status kubelet, journalctl -u kubelet -n 100 --no-pager, crictl ps, df -h, free -m, ss -tlnp, ip addr, top, du -sh, curl, tcpdump
-3. etcd 诊断命令 - 检查 etcd 集群健康与数据。例如: etcdctl endpoint status, etcdctl member list, etcdctl alarm list, etcdctl get /kubernetes --prefix, etcdutl snapshot status <file>
+3. containerd 命令 - 查询容器运行时状态。例如: ctr containers list, ctr images list, ctr tasks ls, nerdctl ps -a, nerdctl logs <container>, nerdctl stats
+4. etcd 诊断命令 - 检查 etcd 集群健康与数据。例如: etcdctl endpoint status, etcdctl endpoint health, etcdctl member list, etcdctl alarm list, etcdctl get /kubernetes --prefix
+5. Linux 基础调优命令 - 例如: iostat -xz 1 3, vmstat 1 3, mpstat -P ALL 1 3, pidstat -d 1 3, lsof -i :<port>, ethtool <iface>, tcpdump -i any -c 10 -nn
 
 行为要求：
 1. 如果证据不足，必须返回 command 动作并逐条调查；至少检查与故障资源直接相关的状态、describe、events 或 logs。
@@ -112,6 +114,8 @@ async def run_diagnostic_agent(
     question: str = "",
     max_steps: int = 30,
     execution_mode: str = "ai",
+    run_id: str = "",
+    history_store=None,
 ):
     """自主诊断循环：AI 模式执行只读命令，手动模式等待用户执行。"""
     if execution_mode not in {"ai", "manual"}:
@@ -151,6 +155,8 @@ async def run_diagnostic_agent(
         command_counts=command_counts,
         report=report,
         question=question,
+        run_id=run_id,
+        history_store=history_store,
     ):
         yield event
 
@@ -163,6 +169,8 @@ async def _run_agent_loop(
     command_counts: Counter,
     report: str,
     question: str,
+    run_id: str = "",
+    history_store=None,
 ):
     invalid_response_count = 0
     step = start_step
@@ -266,6 +274,9 @@ async def _run_agent_loop(
                 "command": command, "reason": reason, "mode": decision.mode,
                 "message": "请在终端手动执行命令，并根据结果继续排查",
             }
+            # 手动模式也保存上下文，支持断点续传
+            self_save_context(run_id, history_store, messages, command_counts, step, step + 1,
+                              max_steps, report, question, execution_mode, content)
             return
 
         if decision.requires_approval:
@@ -274,15 +285,19 @@ async def _run_agent_loop(
                 "command": command,
                 "reason": reason,
                 "created_by": AI_MODEL,
-                "run_id": "",
+                "run_id": run_id,
                 "report": report,
                 "question": question,
                 "execution_mode": execution_mode,
+                "history_store": history_store,
                 "messages": messages + [{"role": "assistant", "content": content}],
                 "next_step": step + 1,
                 "max_steps": max_steps,
                 "command_counts": dict(command_counts),
             }
+            # 保存上下文到 DB，避免浏览器关闭/刷新丢失进度
+            self_save_context(run_id, history_store, messages, command_counts, step, step + 1,
+                              max_steps, report, question, execution_mode, content)
             yield {
                 "type": "approval_required", "approval_id": approval_id,
                 "command": command, "reason": reason,
@@ -296,6 +311,10 @@ async def _run_agent_loop(
             {"role": "user", "content": "命令实际执行结果：\n" + json.dumps(result, ensure_ascii=False)},
         ])
 
+        # 每次执行后保存上下文，支持断点续传
+        self_save_context(run_id, history_store, messages, command_counts, step, step + 1,
+                          max_steps, report, question, execution_mode)
+
         step += 1
 
     if max_steps > 0:
@@ -319,6 +338,8 @@ async def resume_diagnostic_agent(pending: dict, result: dict):
             + json.dumps(result, ensure_ascii=False)
         ),
     })
+    run_id = pending.get("run_id", "")
+    history_store = pending.get("history_store")
     async for event in _run_agent_loop(
         messages=messages,
         execution_mode=pending.get("execution_mode", "ai"),
@@ -327,6 +348,8 @@ async def resume_diagnostic_agent(pending: dict, result: dict):
         command_counts=Counter(pending.get("command_counts") or {}),
         report=pending.get("report", ""),
         question=pending.get("question", ""),
+        run_id=run_id,
+        history_store=history_store,
     ):
         yield event
 
@@ -335,6 +358,59 @@ def take_pending_approval(approval_id: str) -> dict | None:
     return _PENDING_APPROVALS.pop(approval_id, None)
 
 
+def self_save_context(
+    run_id: str, history_store,
+    messages: list, command_counts: Counter,
+    step: int, next_step: int,
+    max_steps: int, report: str, question: str,
+    execution_mode: str,
+    last_response_content: str = "",
+):
+    """保存 Agent 执行上下文到 DB，支持断点续传。"""
+    if not run_id or not history_store:
+        return
+    context = {
+        "messages": messages,
+        "command_counts": dict(command_counts),
+        "step": step,
+        "next_step": next_step,
+        "max_steps": max_steps,
+        "report": report,
+        "question": question,
+        "execution_mode": execution_mode,
+        "last_response": last_response_content,
+    }
+    history_store.update_context(run_id, context)
+
+
+async def resume_from_context(
+    ctx: dict,
+    run_id: str = "",
+    history_store=None,
+):
+    """从 DB 保存的上下文恢复 Agent 诊断，不重跑历史命令，直接进入下一轮。"""
+    messages = list(ctx.get("messages") or [])
+    command_counts = Counter(ctx.get("command_counts") or {})
+    next_step = int(ctx.get("next_step", 1))
+    max_steps = int(ctx.get("max_steps", 0))
+    report = ctx.get("report", "")
+    question = ctx.get("question", "")
+    execution_mode = ctx.get("execution_mode", "ai")
+
+    async for event in _run_agent_loop(
+        messages=messages,
+        execution_mode=execution_mode,
+        max_steps=max_steps,
+        start_step=next_step,
+        command_counts=command_counts,
+        report=report,
+        question=question,
+        run_id=run_id,
+        history_store=history_store,
+    ):
+        yield event
+
+
 async def _stream_chat(messages: list[dict]):
     """通用流式请求 - yield 文本 chunk"""
     # connect=10s 快速失败; read=90s 防止 AI 服务无响应时前端无限卡死

backend/history_store.py

@@ -53,6 +53,7 @@ class HistoryStore:
                     summary TEXT NOT NULL DEFAULT '',
                     started_at TEXT NOT NULL,
                     finished_at TEXT,
+                    context_json TEXT NOT NULL DEFAULT '',
                     FOREIGN KEY(diagnosis_id) REFERENCES diagnoses(id) ON DELETE CASCADE
                 );
                 CREATE INDEX IF NOT EXISTS idx_runs_diagnosis ON processing_runs(diagnosis_id, started_at);
@@ -68,6 +69,15 @@ class HistoryStore:
                     UNIQUE(run_id, sequence)
                 );
             """)
+            # 兼容旧表：确保 context_json 列存在
+            self._ensure_column(db, "processing_runs", "context_json", "TEXT NOT NULL DEFAULT ''")
+
+    def _ensure_column(self, db, table: str, column: str, col_def: str):
+        try:
+            db.execute(f"ALTER TABLE {table} ADD COLUMN {column} {col_def}")
+        except sqlite3.OperationalError as e:
+            if "duplicate column" not in str(e).lower():
+                raise
 
     def save_diagnosis(self, diagnosis: dict, report: str) -> str:
         record_id = uuid.uuid4().hex
@@ -130,6 +140,11 @@ class HistoryStore:
                     {"type": event["type"], "created_at": event["created_at"], **json.loads(event["payload_json"])}
                     for event in event_rows
                 ]
+                run["context_json"] = run.get("context_json") or ""
+                if run["context_json"]:
+                    run["context"] = json.loads(run["context_json"])
+                else:
+                    run["context"] = None
                 runs.append(run)
         return {
             "id": row["id"], "created_at": row["created_at"],
@@ -152,6 +167,30 @@ class HistoryStore:
             )
         return run_id
 
+    def update_context(self, run_id: str, context: dict):
+        """保存/更新 Agent 执行上下文到 processing_runs，支持断点续传。"""
+        with self._connect() as db:
+            db.execute(
+                "UPDATE processing_runs SET context_json = ? WHERE id = ?",
+                (json.dumps(context, ensure_ascii=False), run_id),
+            )
+
+    def get_context(self, run_id: str) -> Optional[dict]:
+        """读取 Agent 执行上下文，如果不存在或为空则返回 None。"""
+        with self._connect() as db:
+            row = db.execute(
+                "SELECT context_json, diagnosis_id, report FROM processing_runs pr JOIN diagnoses d ON pr.diagnosis_id = d.id WHERE pr.id = ?",
+                (run_id,),
+            ).fetchone()
+            if row is None:
+                return None
+            ctx_str = row["context_json"] or ""
+            if not ctx_str:
+                return None
+            ctx = json.loads(ctx_str)
+            ctx["report"] = row["report"]
+            return ctx
+
     def append_event(self, run_id: str, event_type: str, payload: dict):
         with self._connect() as db:
             sequence = db.execute(

backend/main.py

@@ -22,7 +22,8 @@ from backend.diagnosis import (
 from backend.ai_agent import (
     analyze_with_ai, chat_with_ai,
     analyze_with_ai_stream, chat_with_ai_stream,
-    run_diagnostic_agent, resume_diagnostic_agent, take_pending_approval,
+    run_diagnostic_agent, resume_diagnostic_agent, resume_from_context,
+    take_pending_approval,
 )
 from backend.agent_tools import execute_command
 from backend.history_store import HistoryStore
@@ -329,6 +330,8 @@ async def agent_diagnose_stream(question: str = "", execution_mode: str = "ai"):
                 question=question,
                 max_steps=0,
                 execution_mode=execution_mode,
+                run_id=run_id,
+                history_store=history_store,
             ):
                 history_store.append_event(run_id, event.get("type", "event"), {k: v for k, v in event.items() if k != "type"})
                 if event.get("type") == "final":
@@ -409,6 +412,53 @@ async def execute_approved_agent_command(req: AgentApprovalRequest):
     )
 
 
+@app.get("/api/agent/resume-stream/{run_id}")
+async def agent_resume_stream(run_id: str):
+    """从 DB 上下文恢复 Agent 诊断，不重跑历史命令，直接继续诊断。"""
+    ctx = history_store.get_context(run_id)
+    if ctx is None:
+        raise HTTPException(status_code=404, detail="该运行记录不存在或不支持断点续传")
+    ctx.pop("report", None)  # get_context 已经注入了 report
+
+    async def event_generator():
+        yield f"data: {json.dumps({'type': 'start', 'mode': ctx.get('execution_mode', 'ai'), 'run_id': run_id, 'resumed': True}, ensure_ascii=False)}\n\n"
+        final_status = "completed"
+        summary = ""
+        try:
+            async for event in resume_from_context(
+                ctx=ctx,
+                run_id=run_id,
+                history_store=history_store,
+            ):
+                history_store.append_event(run_id, event.get("type", "event"), {k: v for k, v in event.items() if k != "type"})
+                if event.get("type") == "final":
+                    summary = event.get("content", "")
+                elif event.get("type") == "error":
+                    final_status = "failed"
+                    summary = event.get("message", "")
+                elif event.get("type") in {"manual_command", "approval_required"}:
+                    final_status = "waiting"
+                    if event.get("type") == "approval_required":
+                        from backend.ai_agent import _PENDING_APPROVALS
+                        pending = _PENDING_APPROVALS.get(event.get("approval_id"))
+                        if pending is not None:
+                            pending["run_id"] = run_id
+                yield f"data: {json.dumps(event, ensure_ascii=False)}\n\n"
+            history_store.finish_run(run_id, final_status, summary)
+            yield f"data: {json.dumps({'type': 'done', 'run_id': run_id}, ensure_ascii=False)}\n\n"
+        except Exception as exc:
+            message = f"断点续传诊断失败: {exc}"
+            history_store.append_event(run_id, "error", {"message": message})
+            history_store.finish_run(run_id, "failed", message)
+            yield f"data: {json.dumps({'type': 'error', 'message': message}, ensure_ascii=False)}\n\n"
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
+    )
+
+
 @app.post("/api/chat")
 async def chat(req: ChatRequest):
     """AI 多轮对话 (非流式，兼容旧接口)"""