优化 chat 交互链路并修复打包版参数传递问题

- 修复脚本配置文件路径处理问题，避免打包后 ZIP_FILE_PATH 等参数未生效并回退默认值
- 在 chat 模式执行前增加参数归一化和预检，提前检查 ZIP_FILE_PATH、脚本入口和 MCP 配置
- 优化 chat 交互体验，问候语不再触发结构化分析，分析前增加提示，执行中播报每步 action 状态
- 修复 action 失败被误判为 LangGraph 不可用的问题，失败后保留 checkpoint 并给出明确续跑提示
- 补齐 MCP 参数传递，支持向 action 传入 hashCode、nodeUrl、targetIp 等上下文
- 增强全局 action、单 IP action、回滚和日志下载的异常处理与进度回调
- 同步 README、打包 README 和 run.sh 帮助文案，更新打包后 chat 的实际使用说明
- 补充回归测试，覆盖 chat 预检、进度播报、问候处理、MCP 传参与配置路径修复

README.md

@@ -79,9 +79,11 @@ packaging/
 - 本地已安装 `langgraph` 和 `mcp`，并完成 LangGraph fake 全局流程 smoke。
 - CLI `analyze` 输出已做敏感字段脱敏。
 - 增加 `chat` 常驻式 CLI 对话框，支持自然语言分析、参数设置、执行确认、回滚确认、状态查看、事件查看、checkpoint 选择和续跑。
-- chat 可选启用 `rich` / `prompt_toolkit`，支持更清晰输出、命令补全和输入历史。
+- chat 在开发环境可选启用 `rich` / `prompt_toolkit`；PyInstaller 打包环境默认使用普通文本输入，避免交互兼容问题。
+- chat 执行前会归一化参数并展示实际写入脚本配置的值；`script_only` / `hybrid_node_mcp` 会提前检查 `ZIP_FILE_PATH` 是否存在。
+- chat 执行中会播报每个 action 的开始、完成或失败；action 执行失败会停在当前 checkpoint，不再误报 LangGraph 不可用。
 - 增加 action 后 LLM/规则诊断，可通过 `--analyze-actions` 或 `llm action-analysis on` 显式开启。
-- 添加基础测试，当前本地结果为 `42 passed, 1 skipped`。
+- 添加基础测试，当前本地结果为 `51 passed, 2 skipped`。
 
 未完成：
 
@@ -253,6 +255,8 @@ PAM> preview
 PAM> set VERSION_NUMBER=2.0.6
 PAM> run
 即将执行真实 action；确认执行请输入 yes: yes
+开始执行 action: get-token [backend=fake]
+完成 action: get-token [backend=fake]
 PAM> status
 PAM> params
 PAM> events 5
@@ -265,7 +269,7 @@ PAM> resume
 PAM> exit
 ```
 
-`chat` 默认仍要求在会话内显式输入 `run`，并确认参数、目标 IP 范围和最终执行后才会执行 action；如果某个 IP 失败，会通过 LangGraph interrupt 暂停并提示输入 `approve` 或 `reject [原因]`，确认后恢复同一个图线程继续执行。`chat` 也支持 `--llm-base-url` / `--llm-api-key` / `--llm-model`、`--mcp-config` 和 `--analyze-actions`。
+`chat` 默认仍要求在会话内显式输入 `run`，并确认参数、目标 IP 范围和最终执行后才会执行 action。输入 `你好`、`hello` 这类问候不会触发 LLM/结构化分析；需要分析部署需求时可直接描述部署任务，或显式使用 `analyze <需求>`。如果某个 IP 失败，会通过 LangGraph interrupt 暂停并提示输入 `approve` 或 `reject [原因]`，确认后恢复同一个图线程继续执行。`chat` 也支持 `--llm-base-url` / `--llm-api-key` / `--llm-model`、`--mcp-config` 和 `--analyze-actions`。
 
 预演：
 

packaging/README_packaged_agent.md

@@ -32,8 +32,9 @@ pam-deploy-agent-linux-x86_64/
 ./run.sh run-deploy --help
 ```
 
-发布包默认包含 `rich` 和 `prompt_toolkit`。如果终端支持，chat 会自动启用更清晰的输出、命令补全和输入历史；不可用时会自动降级为普通文本输入输出。
+发布包默认使用普通文本输入，避免 PyInstaller 环境下 `prompt_toolkit` 兼容性问题；输出仍会在可用时使用 `rich` 做更清晰的文本展示。
 chat 内的失败回滚确认由 LangGraph interrupt 托管；执行停在确认点后，输入 `approve` 或 `reject [原因]` 会恢复同一个图线程继续处理。
+chat 会在执行前归一化并展示实际写入脚本配置的参数；`script_only` / `hybrid_node_mcp` 会先检查 `ZIP_FILE_PATH` 是否存在，避免脚本运行后才用默认路径失败。执行过程中每个 action 都会输出开始、完成或失败状态。
 
 ## 交互式使用
 
@@ -61,6 +62,8 @@ PAM> preview
 PAM> set VERSION_NUMBER=2.0.6
 PAM> run
 即将执行真实 action；确认执行请输入 yes: yes
+开始执行 action: get-token [backend=fake]
+完成 action: get-token [backend=fake]
 PAM> status
 PAM> params
 PAM> events 5
@@ -199,5 +202,6 @@ MCP token 获取方式与 HOME 一致，默认按 `client_credentials` POST 到
 ## 注意事项
 
 - 执行真实 action 前请确认配置文件中的 `HOME_BASE_URL`、`CLIENT_ID`、`CLIENT_SECRET`、`AIRPORT_CODE`、`APP_NAME`、`MODULE_NAME`、`VERSION_NUMBER`、`ZIP_FILE_PATH`。
+- `chat` 中输入 `你好`、`hello` 这类问候不会触发 LLM/结构化分析；需要分析部署需求时请直接描述部署任务，或显式使用 `analyze <需求>`。
 - `checkpoint` 会保存完整运行参数，请放在受控目录。
 - `hybrid_node_mcp`、`resume`、`confirm` 如果需要执行 MCP action，请同时传入 `--mcp-config`。

packaging/build_linux_self_contained.sh

@@ -121,7 +121,7 @@ PAM 部署 Agent 解压即用包
 
   --confirm
       非交互命令执行真实 action 前必须显式传入。
-      chat 模式会在会话中要求输入 run 和 yes。
+      chat 模式会在会话中要求输入 run，并分别确认参数、目标范围和最终执行。
 
   --analyze-actions
       每个 action 完成后追加 LLM/规则诊断建议。诊断只作为辅助建议，
@@ -164,8 +164,10 @@ LLM 环境变量：
   2. doc_scripts 只包含运行必需文件：deploy.sh、config.txt.example、PAM_AUTO_DEPLY_SKILL.md。
   3. mcp_client.example.json 是 MCP server URL + 独立鉴权配置示例，需要按真实 MCP server 修改。
   4. confirm 会通过 LangGraph interrupt resume 处理确认，并继续后续图节点；进程中断时再使用 resume。
-  5. chat 内可使用 params、events、list checkpoints、load checkpoint、llm config、mcp config 等命令。
-  6. checkpoint 会保存完整运行参数，请放在受控目录。
+  5. chat 会在执行前归一化并展示实际写入脚本配置的参数；script_only / hybrid_node_mcp 会先检查 ZIP_FILE_PATH 是否存在。
+  6. chat 执行过程中会播报每个 action 的开始、完成或失败；普通问候不会触发 LLM/结构化分析。
+  7. chat 内可使用 params、events、list checkpoints、load checkpoint、llm config、mcp config 等命令。
+  8. checkpoint 会保存完整运行参数，请放在受控目录。
 HELP_TEXT
 }
 

pam_deploy_graph/action_router.py

@@ -45,7 +45,16 @@ class ActionRouter:
         if backend == "mcp":
             if self.mcp_runner is None:
                 raise RuntimeError(f"action 需要 MCP runner: {action}")
-            return self.mcp_runner.run(action, params=state.params, **kwargs)
+            mcp_kwargs = dict(kwargs)
+            hash_code = mcp_kwargs.pop("hash_code", None) or state.hash_code
+            node_url = mcp_kwargs.pop("node_url", None) or state.node_url
+            return self.mcp_runner.run(
+                action,
+                params=state.params,
+                hash_code=hash_code,
+                node_url=node_url,
+                **mcp_kwargs,
+            )
         if self.fake_runner is None:
             raise RuntimeError(f"action 需要 fake runner: {action}")
         return self.fake_runner.run(action, params=state.params, **kwargs)

pam_deploy_graph/agent.py

@@ -6,10 +6,11 @@
 
 from __future__ import annotations
 
+import re
 import time
 from dataclasses import asdict
 from pathlib import Path
-from typing import Any
+from typing import Any, Callable
 
 from .action_router import ActionRouter, build_action_backends
 from .checkpoint_store import save_checkpoint
@@ -18,10 +19,15 @@ from .constants import DEFAULT_PARAMS, GLOBAL_ACTION_SEQUENCE, IP_ACTION_SEQUENC
 from .fake_runner import FakeActionRunner
 from .llm import LlmClient, RuleBasedLlmClient, validate_deploy_plan, validate_intent_result
 from .mcp_runner import McpActionRunner
-from .models import AgentState, ExecutionStrategy, LlmDeployPlan, LlmIntentResult, LlmParamResult
+from .models import ActionResult, AgentState, ExecutionStrategy, LlmDeployPlan, LlmIntentResult, LlmParamResult
 from .script_runner import ScriptActionRunner, select_script_entry
 from .skill_policy import load_skill_policy
 
+REQUIRED_ACTION_VALUES = {
+    "upload-package": ("HASH_CODE",),
+    "get-node-url": ("NODE_URL",),
+}
+
 
 class PamDeployAgent:
     """PAM 部署主 Agent，串联 LLM、action 路由、确认和续跑状态。"""
@@ -35,6 +41,7 @@ class PamDeployAgent:
         fake_runner: FakeActionRunner | None = None,
         llm_client: LlmClient | None = None,
         action_analysis_enabled: bool = False,
+        progress_callback: Callable[[dict[str, Any]], None] | None = None,
     ) -> None:
         """初始化策略、脚本 runner、MCP runner、fake runner 和 LLM client。"""
         self.skill_policy = load_skill_policy(skill_path)
@@ -44,6 +51,7 @@ class PamDeployAgent:
         self.mcp_runner = mcp_runner
         self.llm_client = llm_client or RuleBasedLlmClient()
         self.action_analysis_enabled = action_analysis_enabled
+        self.progress_callback = progress_callback
         self.router = ActionRouter(
             script_runner=self.script_runner,
             mcp_runner=mcp_runner,
@@ -94,6 +102,7 @@ class PamDeployAgent:
         missing = [key for key in REQUIRED_PARAMS if not normalized.get(key)]
         if missing:
             raise ValueError(f"缺少必填参数: {', '.join(missing)}")
+        normalized["ZIP_FILE_PATH"] = _normalize_local_file_path(str(normalized["ZIP_FILE_PATH"]).strip())
         return normalized
 
     def _choose_strategy(self, preference: str) -> ExecutionStrategy:
@@ -119,8 +128,8 @@ class PamDeployAgent:
         actual_run_id = run_id or time.strftime("%Y%m%d_%H%M%S")
         actual_script_entry = script_entry or select_script_entry()
         runtime_dir = Path("runtime")
-        actual_config_path = config_path or str(runtime_dir / f"config_{actual_run_id}.txt")
-        actual_trace_path = trace_file_path or str(Path("logs") / f"api_trace_{actual_run_id}.log")
+        actual_config_path = _absolute_path(config_path or runtime_dir / f"config_{actual_run_id}.txt")
+        actual_trace_path = _absolute_path(trace_file_path or Path("logs") / f"api_trace_{actual_run_id}.log")
         write_config(normalized, actual_config_path)
         return AgentState(
             run_id=actual_run_id,
@@ -129,8 +138,8 @@ class PamDeployAgent:
             action_backends=build_action_backends(execution_strategy),
             script_entry=actual_script_entry,
             script_base_dir=str(self.script_base_dir),
-            config_path=actual_config_path,
-            trace_file_path=actual_trace_path,
+            config_path=str(actual_config_path),
+            trace_file_path=str(actual_trace_path),
             checkpoint_path=checkpoint_path or "",
             target_ips=target_ips or [],
         )
@@ -188,8 +197,22 @@ class PamDeployAgent:
             return state
         kwargs: dict[str, Any] = {}
         if action == "publish-version":
+            if not state.hash_code:
+                state.last_failed_step = action
+                self._save_checkpoint(state)
+                raise RuntimeError("publish-version 缺少 HASH_CODE，请确认 upload-package 是否成功返回 HASH_CODE")
             kwargs["hash_code"] = state.hash_code
-        result = self.router.run_action(state, action, **kwargs)
+        backend = state.action_backends.get(action, "script")
+        self._emit_progress({"type": "ACTION_START", "stage": action, "backend": backend})
+        try:
+            result = self.router.run_action(state, action, **kwargs)
+        except Exception as exc:
+            result = ActionResult(
+                action=action,
+                backend=backend,
+                ok=False,
+                error_summary=str(exc),
+            )
         state.events.append(
             {
                 "type": "ACTION_DONE" if result.ok else "ACTION_FAIL",
@@ -200,15 +223,50 @@ class PamDeployAgent:
         )
         self._append_action_analysis(state, action, result)
         if not result.ok:
+            self._emit_progress(
+                {
+                    "type": "ACTION_FAIL",
+                    "stage": action,
+                    "backend": result.backend,
+                    "message": result.error_summary or "action 执行失败",
+                }
+            )
             state.last_failed_step = action
             self._save_checkpoint(state)
             raise RuntimeError(f"{action} 执行失败: {result.error_summary}")
+        missing_values = self._missing_required_values(action, result.values)
+        if missing_values:
+            message = f"{action} 返回缺少必要字段: {', '.join(missing_values)}"
+            self._emit_progress(
+                {
+                    "type": "ACTION_FAIL",
+                    "stage": action,
+                    "backend": result.backend,
+                    "message": message,
+                }
+            )
+            state.last_failed_step = action
+            self._save_checkpoint(state)
+            raise RuntimeError(message)
         self._apply_result(state, action, result.values)
         state.completed_global_steps.append(action)
         state.last_success_step = action
+        self._emit_progress(
+            {
+                "type": "ACTION_DONE",
+                "stage": action,
+                "backend": result.backend,
+                "message": result.values.get("MESSAGE", "ok"),
+            }
+        )
         self._save_checkpoint(state)
         return state
 
+    def _missing_required_values(self, action: str, values: dict[str, Any]) -> list[str]:
+        """检查 action 成功返回后是否带回后续步骤必需字段。"""
+        required = REQUIRED_ACTION_VALUES.get(action, ())
+        return [key for key in required if not values.get(key)]
+
     def run_deploy_flow(self, state: AgentState) -> AgentState:
         """执行完整部署流程：全局阶段后进入逐 IP 阶段。"""
         if state.pending_confirmation:
@@ -272,7 +330,24 @@ class PamDeployAgent:
         completed_steps = ip_state.setdefault("completed_steps", [])
         if action in completed_steps:
             return state
-        result = self.router.run_action(state, action, ip=ip)
+        self._emit_progress(
+            {
+                "type": "ACTION_START",
+                "stage": action,
+                "backend": state.action_backends.get(action, ""),
+                "ip": ip,
+            }
+        )
+        backend = state.action_backends.get(action, "script")
+        try:
+            result = self.router.run_action(state, action, ip=ip)
+        except Exception as exc:
+            result = ActionResult(
+                action=action,
+                backend=backend,
+                ok=False,
+                error_summary=str(exc),
+            )
         failed = (not result.ok) or self._business_failed(action, result.values)
         state.events.append(
             {
@@ -286,6 +361,15 @@ class PamDeployAgent:
         self._append_action_analysis(state, action, result, ip=ip)
 
         if failed:
+            self._emit_progress(
+                {
+                    "type": "ACTION_FAIL",
+                    "stage": action,
+                    "backend": result.backend,
+                    "ip": ip,
+                    "message": result.error_summary or result.values.get("MESSAGE", "action 执行失败"),
+                }
+            )
             self._record_ip_failure(state, ip, action, result.error_summary or str(result.values))
             if action != "download-log":
                 self._download_log_best_effort(state, ip)
@@ -295,6 +379,15 @@ class PamDeployAgent:
 
         self._apply_ip_result(ip_state, action, result.values)
         completed_steps.append(action)
+        self._emit_progress(
+            {
+                "type": "ACTION_DONE",
+                "stage": action,
+                "backend": result.backend,
+                "ip": ip,
+                "message": result.values.get("MESSAGE", "ok"),
+            }
+        )
         self._save_checkpoint(state)
         return state
 
@@ -343,12 +436,29 @@ class PamDeployAgent:
             self._save_checkpoint(state)
             return state
 
-        result = self.router.run_action(
-            state,
-            "rollback-ip",
-            ip=ip,
-            stop_first=bool(ip_state.get("rollback_stop_first", False)),
+        backend = state.action_backends.get("rollback-ip", "script")
+        self._emit_progress(
+            {
+                "type": "ACTION_START",
+                "stage": "rollback-ip",
+                "backend": backend,
+                "ip": ip,
+            }
         )
+        try:
+            result = self.router.run_action(
+                state,
+                "rollback-ip",
+                ip=ip,
+                stop_first=bool(ip_state.get("rollback_stop_first", False)),
+            )
+        except Exception as exc:
+            result = ActionResult(
+                action="rollback-ip",
+                backend=backend,
+                ok=False,
+                error_summary=str(exc),
+            )
         ip_state["rollback_status"] = "ROLLBACK_DONE" if result.ok else "ROLLBACK_FAILED"
         state.events.append(
             {
@@ -364,12 +474,39 @@ class PamDeployAgent:
             state.pending_confirmation = ""
             state.last_success_step = "rollback-ip"
             state.last_failed_step = ""
+            self._emit_progress(
+                {
+                    "type": "ACTION_DONE",
+                    "stage": "rollback-ip",
+                    "backend": result.backend,
+                    "ip": ip,
+                    "message": result.values.get("MESSAGE", "ok"),
+                }
+            )
         else:
             state.pending_confirmation = f"rollback-ip:{ip}"
             state.last_failed_step = "rollback-ip"
+            self._emit_progress(
+                {
+                    "type": "ACTION_FAIL",
+                    "stage": "rollback-ip",
+                    "backend": result.backend,
+                    "ip": ip,
+                    "message": result.error_summary or result.values.get("MESSAGE", "rollback 执行失败"),
+                }
+            )
         self._save_checkpoint(state)
         return state
 
+    def _emit_progress(self, payload: dict[str, Any]) -> None:
+        """向 CLI/chat 回调 action 执行进度，回调失败不影响主流程。"""
+        if self.progress_callback is None:
+            return
+        try:
+            self.progress_callback(payload)
+        except Exception:
+            return
+
     def _apply_result(self, state: AgentState, action: str, values: dict[str, Any]) -> None:
         """把全局 action 返回值写回 AgentState。"""
         if "HASH_CODE" in values:
@@ -442,7 +579,25 @@ class PamDeployAgent:
 
     def _download_log_best_effort(self, state: AgentState, ip: str) -> None:
         """失败后尽力下载日志，日志失败不覆盖原失败原因。"""
-        result = self.router.run_action(state, "download-log", ip=ip)
+        backend = state.action_backends.get("download-log", "script")
+        self._emit_progress(
+            {
+                "type": "ACTION_START",
+                "stage": "download-log",
+                "backend": backend,
+                "ip": ip,
+                "message": "失败后尝试下载日志",
+            }
+        )
+        try:
+            result = self.router.run_action(state, "download-log", ip=ip)
+        except Exception as exc:
+            result = ActionResult(
+                action="download-log",
+                backend=backend,
+                ok=False,
+                error_summary=str(exc),
+            )
         ip_state = state.ip_states[ip]
         if result.ok:
             ip_state["log_file"] = str(result.values.get("LOG_FILE", ""))
@@ -455,6 +610,15 @@ class PamDeployAgent:
                     "message": "已尽力下载日志",
                 }
             )
+            self._emit_progress(
+                {
+                    "type": "ACTION_DONE",
+                    "stage": "download-log",
+                    "backend": result.backend,
+                    "ip": ip,
+                    "message": result.values.get("MESSAGE", "已尽力下载日志"),
+                }
+            )
         else:
             state.events.append(
                 {
@@ -465,6 +629,15 @@ class PamDeployAgent:
                     "message": result.error_summary or "尽力下载日志失败",
                 }
             )
+            self._emit_progress(
+                {
+                    "type": "ACTION_FAIL",
+                    "stage": "download-log",
+                    "backend": result.backend,
+                    "ip": ip,
+                    "message": result.error_summary or "尽力下载日志失败",
+                }
+            )
         self._append_action_analysis(state, "download-log", result, ip=ip)
 
     def _save_checkpoint(self, state: AgentState) -> None:
@@ -552,3 +725,20 @@ class PamDeployAgent:
                 )
             )
         return "\n".join(lines)
+
+
+def _absolute_path(path: str | Path) -> Path:
+    """把传给脚本的文件路径转换为绝对路径，避免 cwd 切换后读错文件。"""
+    return Path(path).expanduser().resolve()
+
+
+def _normalize_local_file_path(path: str) -> str:
+    """把本地相对文件路径转换为绝对路径，Windows/Unix 绝对路径保持不变。"""
+    if re.match(r"^[A-Za-z]:[\\/]", path):
+        return path
+    if path.startswith("/"):
+        return path
+    value = Path(path).expanduser()
+    if value.is_absolute():
+        return str(value)
+    return str(value.resolve())

pam_deploy_graph/interactive.py

@@ -75,6 +75,7 @@ class InteractiveCliSession:
         self.llm_config: dict[str, str] = {}
         self.mcp_config_path: str = ""
         self.graph_runtime: LangGraphDeploymentRuntime | None = None
+        self.agent.progress_callback = self._on_progress
 
     def run(self) -> None:
         """启动 REPL 循环，直到用户 exit 或输入流结束。"""
@@ -151,6 +152,14 @@ class InteractiveCliSession:
             self._load_checkpoint(rest.strip()[len("checkpoint") :].strip())
             return True
 
+        if _is_small_talk(text):
+            self.output("你好。可以输入 help 查看命令，或直接描述部署需求；执行前仍需输入 run 并确认。")
+            return True
+        if not _looks_like_deploy_request(text):
+            self.output("我没有识别到明确的部署需求。可以输入 help 查看命令，或用 analyze <需求> 明确触发需求分析。")
+            return True
+
+        self.output("正在分析需求...")
         self._analyze(text)
         return True
 
@@ -160,7 +169,11 @@ class InteractiveCliSession:
             self.output("请输入要分析的自然语言需求，例如：analyze 请用 MCP 预演部署 HET。")
             return
 
-        result = self.agent.analyze_request(text, self.params)
+        try:
+            result = self.agent.analyze_request(text, self.params)
+        except Exception as exc:
+            self.output(f"需求分析失败: {exc}")
+            return
         self.last_analysis = result
         param_result = result["params"]
         intent_result = result["intent"]
@@ -309,6 +322,17 @@ class InteractiveCliSession:
             self._print_confirmation()
             return
 
+        if not self._prepare_params_for_run():
+            return
+
+        problems = self._validate_run_prerequisites(self.params)
+        if problems:
+            self.output("执行前检查未通过：")
+            for problem in problems:
+                self.output(f"- {problem}")
+            self.output("请修正参数或配置后再输入 run。")
+            return
+
         if not self._confirm_params_and_scope():
             self.output("已取消执行。")
             return
@@ -356,18 +380,63 @@ class InteractiveCliSession:
         if self.state is None:
             self.output("当前没有运行状态。")
             return
-        try:
-            if self.graph_runtime is None or not self.graph_runtime.waiting_confirmation:
+        if self.graph_runtime is None or not self.graph_runtime.waiting_confirmation:
+            try:
                 self.graph_runtime = LangGraphDeploymentRuntime(agent=self.agent)
+            except RuntimeError as exc:
+                self.output(f"LangGraph 确认运行器不可用，降级为本地执行: {exc}")
+                self.graph_runtime = None
+                try:
+                    self.state = self.agent.run_deploy_flow(self.state)
+                except Exception as fallback_exc:
+                    self._handle_execution_error(fallback_exc)
+                    return
+                self._print_state_report_and_checkpoint()
+                return
+        try:
             result = self.graph_runtime.start(self.state)
-        except RuntimeError as exc:
-            self.output(f"LangGraph 确认运行器不可用，降级为本地执行: {exc}")
-            self.graph_runtime = None
-            self.state = self.agent.run_deploy_flow(self.state)
-            self._print_state_report_and_checkpoint()
+        except Exception as exc:
+            self._handle_execution_error(exc)
             return
         self._apply_graph_result(result)
 
+    def _prepare_params_for_run(self) -> bool:
+        """执行前归一化参数，确保确认值和实际写入脚本配置一致。"""
+        try:
+            self.params = self.agent.normalize_params(self.params)
+        except ValueError as exc:
+            self.output(f"参数检查失败: {exc}")
+            return False
+        return True
+
+    def _validate_run_prerequisites(self, params: dict[str, Any]) -> list[str]:
+        """在创建 state 前检查可提前发现的运行问题。"""
+        problems: list[str] = []
+        if self.strategy != "fake":
+            zip_path = str(params.get("ZIP_FILE_PATH", "")).strip()
+            if not _path_exists(zip_path):
+                problems.append(f"ZIP_FILE_PATH 不存在: {zip_path}")
+        if self.strategy in ("script_only", "hybrid_node_mcp"):
+            script_entry = self.agent.script_base_dir / "deploy.sh"
+            ps_entry = self.agent.script_base_dir / "deploy.ps1"
+            if not script_entry.exists() and not ps_entry.exists():
+                problems.append(f"脚本入口不存在: {script_entry} 或 {ps_entry}")
+        if self.strategy == "hybrid_node_mcp" and self.agent.mcp_runner is None:
+            problems.append("当前策略需要 MCP runner，请启动时传 --mcp-config 或在 chat 内执行 mcp config <路径>。")
+        return problems
+
+    def _handle_execution_error(self, exc: Exception) -> None:
+        """输出 action 执行失败后的可恢复提示，不再误报 LangGraph 不可用。"""
+        self.output(f"执行已停止: {exc}")
+        if self.state is None:
+            return
+        if self.state.last_failed_step:
+            self.output(f"最后失败步骤: {self.state.last_failed_step}")
+        if self.state.pending_confirmation:
+            self._print_confirmation()
+        self.output(f"checkpoint: {self.state.checkpoint_path or self.checkpoint_path}")
+        self.output("请修正参数或外部环境后，使用 load checkpoint <路径> / resume 继续，或重新 run。")
+
     def _apply_graph_result(self, result: LangGraphRunResult) -> None:
         """把 LangGraph 运行结果同步回 chat 会话并输出用户可见状态。"""
         if result.state is not None:
@@ -429,6 +498,28 @@ class InteractiveCliSession:
         if self.state.pending_confirmation:
             self._print_confirmation()
 
+    def _on_progress(self, payload: dict[str, Any]) -> None:
+        """把 Agent action 进度转成 chat 可见输出。"""
+        event_type = str(payload.get("type", ""))
+        stage = str(payload.get("stage", ""))
+        backend = str(payload.get("backend", ""))
+        ip = str(payload.get("ip", ""))
+        message = str(payload.get("message", ""))
+        suffix_parts = []
+        if backend:
+            suffix_parts.append(f"backend={backend}")
+        if ip:
+            suffix_parts.append(f"ip={ip}")
+        suffix = f" [{', '.join(suffix_parts)}]" if suffix_parts else ""
+        if event_type == "ACTION_START":
+            self.output(f"开始执行 action: {stage}{suffix}")
+        elif event_type == "ACTION_DONE":
+            detail = f": {message}" if message and message != "ok" else ""
+            self.output(f"完成 action: {stage}{suffix}{detail}")
+        elif event_type == "ACTION_FAIL":
+            detail = f": {message}" if message else ""
+            self.output(f"失败 action: {stage}{suffix}{detail}")
+
     def _print_confirmation(self) -> None:
         """输出当前待人工确认事项。"""
         if self.state is None:
@@ -526,10 +617,68 @@ def _parse_key_values(parts: list[str]) -> dict[str, str]:
     return values
 
 
+def _is_small_talk(text: str) -> bool:
+    """识别不应触发 LLM/结构化分析的简单寒暄。"""
+    normalized = text.strip().lower()
+    return normalized in {
+        "你好",
+        "您好",
+        "hello",
+        "hi",
+        "hey",
+        "在吗",
+        "谢谢",
+        "thanks",
+        "thank you",
+    }
+
+
+def _looks_like_deploy_request(text: str) -> bool:
+    """粗筛自然语言部署需求，避免任意闲聊都触发耗时分析。"""
+    lowered = text.lower()
+    deploy_keywords = (
+        "部署",
+        "发布",
+        "升级",
+        "回滚",
+        "预演",
+        "执行",
+        "pam",
+        "mcp",
+        "node",
+        "版本",
+        "机场",
+        "deploy",
+        "release",
+        "upgrade",
+        "rollback",
+        "preview",
+    )
+    param_markers = (
+        "HOME_BASE_URL",
+        "CLIENT_ID",
+        "AIRPORT_CODE",
+        "APP_NAME",
+        "MODULE_NAME",
+        "VERSION_NUMBER",
+        "ZIP_FILE_PATH",
+    )
+    return any(keyword in lowered for keyword in deploy_keywords) or any(marker in text for marker in param_markers)
+
+
+def _path_exists(path: str) -> bool:
+    """检查本地路径是否存在，兼容打包到 Linux 后的绝对路径。"""
+    if not path:
+        return False
+    return Path(path).expanduser().exists()
+
+
 def _build_prompt_input(input_func: InputFunc) -> InputFunc:
     """如果安装了 prompt_toolkit，则启用历史记录和命令补全。"""
     if input_func is not builtins.input:
         return input_func
+    if getattr(sys, "frozen", False):
+        return input_func
     try:
         from prompt_toolkit import PromptSession
         from prompt_toolkit.completion import WordCompleter

pam_deploy_graph/mcp_runner.py

@@ -54,6 +54,7 @@ class McpActionRunner:
         params: dict[str, Any],
         ip: str | None = None,
         hash_code: str | None = None,
+        node_url: str | None = None,
         stop_first: bool = False,
         **_: Any,
     ) -> ActionResult:
@@ -66,6 +67,7 @@ class McpActionRunner:
             params=params,
             ip=ip,
             hash_code=hash_code,
+            node_url=node_url,
             stop_first=stop_first,
         )
         try:
@@ -116,6 +118,7 @@ class McpActionRunner:
         params: dict[str, Any],
         ip: str | None,
         hash_code: str | None,
+        node_url: str | None,
         stop_first: bool,
     ) -> dict[str, Any]:
         """把 Agent 参数转换为 MCP tool 所需的入参。"""
@@ -133,6 +136,8 @@ class McpActionRunner:
             arguments["targetIp"] = ip
         if hash_code:
             arguments["hashCode"] = hash_code
+        if node_url:
+            arguments["nodeUrl"] = node_url
         if action == "rollback-ip":
             arguments["stopFirst"] = stop_first
         return {key: value for key, value in arguments.items() if value not in (None, "")}

tests/test_agent_flow.py

@@ -1,5 +1,7 @@
 from pathlib import Path
 
+import pytest
+
 from pam_deploy_graph.agent import PamDeployAgent
 from pam_deploy_graph.checkpoint_store import load_agent_state
 from pam_deploy_graph.constants import GLOBAL_ACTION_SEQUENCE
@@ -33,6 +35,41 @@ def test_run_deploy_flow_success(tmp_path: Path):
     assert all(item["status"] == "SUCCESS" for item in state.ip_states.values())
 
 
+def test_create_state_writes_absolute_script_config_path_and_normalized_zip(tmp_path: Path):
+    package_path = tmp_path / "pkg.zip"
+    params = {**PARAMS, "ZIP_FILE_PATH": str(package_path)}
+    agent = PamDeployAgent(fake_runner=FakeActionRunner())
+
+    state = agent.create_state(
+        params=params,
+        execution_strategy="fake",
+        config_path=str(tmp_path / "runtime" / "config.txt"),
+        trace_file_path=str(tmp_path / "logs" / "trace.log"),
+    )
+
+    assert Path(state.config_path).is_absolute()
+    assert Path(state.trace_file_path).is_absolute()
+    config_text = Path(state.config_path).read_text(encoding="utf-8")
+    assert f"ZIP_FILE_PATH={package_path.resolve()}" in config_text
+
+
+def test_global_action_requires_hash_code_from_upload_package(tmp_path: Path):
+    fake = FakeActionRunner({"upload-package": {"ACTION": "upload-package"}})
+    agent = PamDeployAgent(fake_runner=fake)
+    state = agent.create_state(
+        params=PARAMS,
+        execution_strategy="fake",
+        config_path=str(tmp_path / "config.txt"),
+        checkpoint_path=str(tmp_path / "checkpoint.json"),
+    )
+
+    with pytest.raises(RuntimeError, match="缺少必要字段: HASH_CODE"):
+        agent.run_deploy_flow(state)
+
+    assert state.last_failed_step == "upload-package"
+    assert "upload-package" not in state.completed_global_steps
+
+
 def test_run_deploy_flow_stops_on_verify_failure(tmp_path: Path):
     fake = FakeActionRunner(
         {

tests/test_interactive_cli.py

@@ -61,6 +61,69 @@ def test_chat_run_executes_fake_deploy_and_writes_checkpoint(tmp_path: Path):
     assert all(item["status"] == "SUCCESS" for item in session.state.ip_states.values())
 
 
+def test_chat_run_prints_action_progress(tmp_path: Path):
+    checkpoint = tmp_path / "checkpoint.json"
+    session = InteractiveCliSession(
+        agent=PamDeployAgent(fake_runner=FakeActionRunner()),
+        params=PARAMS,
+        strategy="fake",
+        checkpoint_path=str(checkpoint),
+    )
+
+    output = run_session(session, ["run", "yes", "yes", "yes", "exit"])
+
+    assert any("开始执行 action: get-token" in item for item in output)
+    assert any("完成 action: verify-ip" in item for item in output)
+
+
+def test_chat_greeting_does_not_trigger_structured_analysis(tmp_path: Path):
+    session = InteractiveCliSession(
+        agent=PamDeployAgent(),
+        params=PARAMS,
+        strategy="fake",
+        checkpoint_path=str(tmp_path / "checkpoint.json"),
+    )
+
+    output = run_session(session, ["你好", "exit"])
+
+    assert session.last_analysis is None
+    assert any("可以输入 help 查看命令" in item for item in output)
+    assert not any("已生成结构化理解" in item for item in output)
+
+
+def test_chat_preflight_blocks_missing_zip_path_before_confirm(tmp_path: Path):
+    missing_package = tmp_path / "missing.zip"
+    session = InteractiveCliSession(
+        agent=PamDeployAgent(),
+        params={**PARAMS, "ZIP_FILE_PATH": str(missing_package)},
+        strategy="script_only",
+        checkpoint_path=str(tmp_path / "checkpoint.json"),
+    )
+
+    output = run_session(session, ["run", "exit"])
+
+    assert session.state is None
+    assert any("执行前检查未通过" in item for item in output)
+    assert any("ZIP_FILE_PATH 不存在" in item for item in output)
+
+
+def test_chat_action_failure_does_not_report_langgraph_unavailable(tmp_path: Path):
+    fake = FakeActionRunner({"upload-package": {"ACTION": "upload-package"}})
+    session = InteractiveCliSession(
+        agent=PamDeployAgent(fake_runner=fake),
+        params=PARAMS,
+        strategy="fake",
+        checkpoint_path=str(tmp_path / "checkpoint.json"),
+    )
+
+    output = run_session(session, ["run", "yes", "yes", "yes", "exit"])
+
+    assert session.state is not None
+    assert session.state.last_failed_step == "upload-package"
+    assert any("执行已停止" in item for item in output)
+    assert not any("LangGraph 确认运行器不可用" in item for item in output)
+
+
 def test_chat_approve_then_resume_continues_after_failed_ip(tmp_path: Path):
     fake = FakeActionRunner(
         {
@@ -143,4 +206,3 @@ def test_prompt_history_creates_runtime_dir(tmp_path: Path, monkeypatch):
 
     assert callable(prompt)
     assert (tmp_path / "runtime").is_dir()
-

tests/test_mcp_client.py

@@ -191,6 +191,30 @@ def test_mcp_runner_auto_discovers_tool_name():
     assert result.tool_name == "pam_get_online_ips"
 
 
+def test_mcp_runner_passes_hash_code_and_node_url():
+    calls = []
+
+    class Client:
+        def call_tool(self, tool_name, arguments):
+            calls.append((tool_name, arguments))
+            return {"ACTION": "upgrade-ip", "SUCCESS": "true"}
+
+    runner = McpActionRunner(client=Client())
+
+    result = runner.run(
+        "upgrade-ip",
+        params={"HOME_BASE_URL": "https://pam.home", "AIRPORT_CODE": "HET"},
+        ip="192.168.1.10",
+        hash_code="hash-1",
+        node_url="https://pam.node",
+    )
+
+    assert result.ok is True
+    assert calls[0][1]["targetIp"] == "192.168.1.10"
+    assert calls[0][1]["hashCode"] == "hash-1"
+    assert calls[0][1]["nodeUrl"] == "https://pam.node"
+
+
 def _write_json_config(tmpdir, payload):
     path = tmpdir / "mcp.json"
     path.write_text(__import__("json").dumps(payload), encoding="utf-8")