v0.11.3

ci(deps): bump actions/deploy-pages from 4 to 5 (#251)

Bumps [actions/deploy-pages](https://github.com/actions/deploy-pages) from 4 to 5.
- [Release notes](https://github.com/actions/deploy-pages/releases)
- [Commits](https://github.com/actions/deploy-pages/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/deploy-pages
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

ci(deps): bump actions/configure-pages from 5 to 6 (#252)

Bumps [actions/configure-pages](https://github.com/actions/configure-pages) from 5 to 6.
- [Release notes](https://github.com/actions/configure-pages/releases)
- [Commits](https://github.com/actions/configure-pages/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/configure-pages
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

ci(deps): bump actions/upload-pages-artifact from 4 to 5 (#260)

Bumps [actions/upload-pages-artifact](https://github.com/actions/upload-pages-artifact) from 4 to 5.
- [Release notes](https://github.com/actions/upload-pages-artifact/releases)
- [Commits](https://github.com/actions/upload-pages-artifact/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/upload-pages-artifact
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

ci(deps): bump conda-incubator/setup-miniconda from 3 to 4 (#261)

Bumps [conda-incubator/setup-miniconda](https://github.com/conda-incubator/setup-miniconda) from 3 to 4.
- [Release notes](https://github.com/conda-incubator/setup-miniconda/releases)
- [Changelog](https://github.com/conda-incubator/setup-miniconda/blob/main/CHANGELOG.md)
- [Commits](https://github.com/conda-incubator/setup-miniconda/compare/v3...v4)

---
updated-dependencies:
- dependency-name: conda-incubator/setup-miniconda
  dependency-version: '4'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

Add PLC communication guide (#264)

* Add post process station and related resources

- Created JSON configuration for post_process_station and its child post_process_deck.
- Added YAML definitions for post_process_station, bottle carriers, bottles, and deck resources.
- Implemented Python classes for bottle carriers, bottles, decks, and warehouses to manage resources in the post process.
- Established a factory method for creating warehouses with customizable dimensions and layouts.
- Defined the structure and behavior of the post_process_deck and its associated warehouses.

* feat(post_process): add post_process_station and related warehouse functionality

- Introduced post_process_station.json to define the post-processing station structure.
- Implemented post_process_warehouse.py to create warehouse configurations with customizable layouts.
- Added warehouses.py for specific warehouse configurations (4x3x1).
- Updated post_process_station.yaml to reflect new module paths for OpcUaClient.
- Refactored bottle carriers and bottles YAML files to point to the new module paths.
- Adjusted deck.yaml to align with the new organizational structure for post_process_deck.

* Add PLC communication guide for AI4M

Add a comprehensive developer guide (docs/developer_guide/add_PLC.md) describing the PLC integration standard used by Uni-Lab for workstation devices, using the AI4M implementation as reference. Covers rationale for using OPC UA, the opcua_nodes_*.csv node-table format, communication base classes (BaseOpcUaClient / OpcUaClientWithSubscription), data types, and subscription/cache/reconnect behavior. Documents driver patterns for AI4MDevice, three handshake paradigms (pulse, parameter handshake, id-based), registry/graph configuration (YAML/JSON), debugging tips (KEPServerEX sim, standalone run), and a checklist for onboarding new PLC-controlled equipment.

.conda/base/recipe.yaml

@@ -3,7 +3,7 @@
 
 package:
   name: unilabos
-  version: 0.11.2
+  version: 0.11.3
 
 source:
   path: ../../unilabos
@@ -54,7 +54,7 @@ requirements:
   - pymodbus
   - matplotlib
   - pylibftdi
-  - uni-lab::unilabos-env ==0.11.2
+  - uni-lab::unilabos-env ==0.11.3
 
 about:
   repository: https://github.com/deepmodeling/Uni-Lab-OS

.conda/environment/recipe.yaml

@@ -2,7 +2,7 @@
 
 package:
   name: unilabos-env
-  version: 0.11.2
+  version: 0.11.3
 
 build:
   noarch: generic

.conda/full/recipe.yaml

@@ -3,7 +3,7 @@
 
 package:
   name: unilabos-full
-  version: 0.11.2
+  version: 0.11.3
 
 build:
   noarch: generic
@@ -11,7 +11,7 @@ build:
 requirements:
   run:
   # Base unilabos package (includes unilabos-env)
-  - uni-lab::unilabos ==0.11.2
+  - uni-lab::unilabos ==0.11.3
   # Documentation tools
   - sphinx
   - sphinx_rtd_theme

.cursor/skills/add-device/SKILL.md

@@ -5,9 +5,98 @@ description: Guide for adding new devices to Uni-Lab-OS (接入新设备). Uses
 
 # 添加新设备到 Uni-Lab-OS
 
-**第一步：** 使用 Read 工具读取 `docs/ai_guides/add_device.md`，获取完整的设备接入指南。
+本 Skill 是自包含的设备接入指南，不依赖外部文档。迁移给别人时，只复制 `.cursor/skills/add-device/SKILL.md` 即可获得核心规则、模板、验证方式和常见错误清单。
 
-该指南包含设备类别（物模型）列表、通信协议模板、常见错误检查清单等。搜索 `unilabos/devices/` 获取已有设备的实现参考。
+开始实现前，仍应搜索 `unilabos/devices/` 获取同类别已有设备的接口、参数名、状态字符串和返回值风格作为参考。
+
+---
+
+## 接入工作流
+
+按下面顺序推进，并在工作中维护进度：
+
+```text
+设备接入进度：
+- [ ] 1. 确定设备类别（物模型）和对外单位
+- [ ] 2. 确定通信协议
+- [ ] 3. 收集指令协议（SDK、厂商文档、寄存器表、HTTP API、用户口述）
+- [ ] 4. 对齐同类设备接口（搜索 unilabos/devices/）
+- [ ] 5. 创建驱动 unilabos/devices/<category>/<file>.py
+- [ ] 6. 验证可导入、注册表扫描、启动测试
+- [ ] 7. 如需要，配置实验图文件
+```
+
+## 设备类别（物模型）
+
+优先使用已有类别。只有确实无法归类时才使用 `custom`。
+
+| 类别 ID | 说明 | 标准属性 | 标准动作 |
+|---|---|---|---|
+| `temperature` | 加热、冷却、温控 | `temp`, `temp_target`, `status` | `set_temperature`, `stop` |
+| `pump_and_valve` | 泵、阀门、注射器 | 见子类型表 | 见子类型表 |
+| `motor` | 电机、步进马达 | `position`, `status` | `enable`, `move_position`, `move_speed`, `stop` |
+| `heaterstirrer` | 加热搅拌一体机 | `temp`, `stir_speed`, `status` | `set_temperature`, `stir`, `stop` |
+| `balance` | 天平、称重 | `weight`, `unit`, `status` | `tare`, `read_weight` |
+| `sensor` | 传感器（液位、温度等） | `value`, `level`, `status` | `read_value`, `set_threshold` |
+| `liquid_handling` | 液体处理机器人 | `status`, `deck_state` | `transfer_liquid`, `aspirate`, `dispense` |
+| `robot_arm` | 机械臂 | `arm_pose`, `arm_status` | `moveit_task`, `pick_and_place` |
+| `workstation` | 工作站、组合设备 | `workflow_sequence`, `material_info` | `create_order`, `scheduler_start`, `scheduler_stop` |
+| `virtual` | 虚拟、模拟设备 | 按模拟的真实设备定义 | 按模拟的真实设备定义 |
+| `custom` | 不属于以上类别 | 用户自定义 | 用户自定义 |
+
+`pump_and_valve` 子类型：
+
+| 子类型 | 最小通用属性 | 最小通用动作 | 单位约定 |
+|---|---|---|---|
+| 注射泵（syringe pump） | `status`, `valve_position`, `position` | `initialize`, `set_valve_position`, `set_position`, `pull_plunger`, `push_plunger`, `stop_operation` | 体积=mL, 速度=mL/s |
+| 电磁阀（solenoid valve） | `status`, `valve_position` | `open`, `close`, `set_valve_position` | 无 |
+| 蠕动泵（peristaltic pump） | `status`, `speed` | `start`, `stop`, `set_speed` | 流速=mL/min |
+
+对外暴露的属性和动作参数必须使用用户友好的物理单位（mL、ul、degC、RPM 等），硬件原始值转换放在驱动内部。
+
+## 通信协议和指令来源
+
+先确认通信方式，再确认具体指令协议。物模型只定义设备“应该做什么”，不会告诉你硬件“具体发什么字节/请求”。
+
+| 协议 | 常用 config 参数 | 常用依赖 | 现有抽象 |
+|---|---|---|---|
+| Serial (RS232/RS485) | `port`, `baudrate`, `timeout` | `pyserial` | 直接使用 `serial.Serial` |
+| Modbus RTU | `port`, `baudrate`, `slave_id` | `pymodbus` | `device_comms/modbus_plc/` |
+| Modbus TCP | `host`, `port`, `slave_id` | `pymodbus` | `device_comms/modbus_plc/` |
+| TCP Socket | `host`, `port`, `timeout` | stdlib | 直接使用 `socket` |
+| HTTP API | `url`, `token`, `timeout` | `requests` | `device_comms/rpc.py` |
+| OPC UA | `url` | `opcua` | `device_comms/opcua_client/` |
+| 无通信（虚拟） | 无 | 无 | 在动作中模拟行为 |
+
+必须从以下来源之一获得指令细节：
+
+| 来源 | 处理方式 |
+|---|---|
+| 现成 SDK/驱动代码 | 读取代码，提取指令逻辑，包装进 Uni-Lab-OS 类 |
+| 协议文档/手册 | 解析命令、响应、校验、寄存器、错误码 |
+| 用户口述 | 按描述实现指令编解码，标出不确定点 |
+| 标准协议 | 使用标准实现，例如 Modbus 寄存器表、SCPI |
+| 虚拟设备 | 跳过硬件通信，在动作方法中维护模拟状态 |
+
+## 对齐已有实现（强制）
+
+实现前必须搜索 `unilabos/devices/` 中同类别设备：
+
+- 参数名必须与已有设备保持一致；动作方法参数名是接口契约，不要随意改成 `volume_ml`、`target_temp_c` 这类新名字。
+- `status` 字符串值要和同类设备一致，优先使用英文稳定值，例如 `Idle`、`Running`、`Error`。
+- 状态属性用 `@property` + `@topic_config()` 明确声明。
+- 返回值使用结构化 dict，至少包含 `success`，需要给前端展示的信息放在 `message`、`data`、`error` 等字段。
+
+## 架构选择
+
+| 场景 | 推荐方式 |
+|---|---|
+| 简单设备 | 纯 Python 类 + `@device` |
+| 工作站/组合设备 | `WorkstationBase` 或项目内已有工作站模式 |
+| 液体处理 | `LiquidHandlerAbstract` / PyLabRobot 相关模式 |
+| Modbus 设备 | 复用 `device_comms/modbus_plc/` 或项目内 Modbus 示例 |
+| OPC UA 设备 | 复用 `device_comms/opcua_client/` |
+| 外部独立包 | 使用 `create-device-package` skill |
 
 ---
 
@@ -87,6 +176,29 @@ Args:
 - 如果只写 `param: 参数说明`，`title` 会兜底为字段名，`description` 使用参数说明。
 - 如果没有写参数文档，生成器也会兜底补齐 `title=<字段名>` 和 `description=""`，但新设备应优先写清楚显示名和说明。
 
+### 特殊参数类型：ResourceSlot / DeviceSlot
+
+需要前端选择资源或设备时，用特殊类型注解，registry 会自动生成 `placeholder_keys`：
+
+```python
+from typing import List
+from unilabos.registry.placeholder_type import DeviceSlot, ResourceSlot
+
+@action(description="转移液体")
+def transfer(self, source: ResourceSlot, target: ResourceSlot, volume_ul: float) -> dict:
+    """
+    Args:
+        source[源资源]: 源容器或孔位。
+        target[目标资源]: 目标容器或孔位。
+        volume_ul[体积(ul)]: 转移体积。
+    """
+    return {"success": True}
+
+@action(description="同步设备")
+def sync_devices(self, devices: List[DeviceSlot]) -> dict:
+    return {"success": True, "count": len(devices)}
+```
+
 ### @topic_config — 状态属性配置
 
 ```python
@@ -194,3 +306,154 @@ class MyDevice:
 - `post_init` 用 `@not_action` 标记，参数类型标注为 `BaseROS2DeviceNode`
 - 运行时状态存储在 `self.data` 字典中
 - 设备文件放在 `unilabos/devices/<category>/` 目录下
+
+---
+
+## 通信实现片段
+
+Serial 文本指令：
+
+```python
+def _send_command(self, cmd: str) -> str:
+    self.ser.write(f"{cmd}\r\n".encode())
+    return self.ser.readline().decode().strip()
+```
+
+RS-485 响应解析要先定位帧头，不要用硬编码索引直接解析原始响应：
+
+```python
+def _normalize_response(self, raw: str, start_marker: str = "/") -> str:
+    pos = raw.find(start_marker)
+    return raw[pos:] if pos >= 0 else raw
+```
+
+自定义二进制帧：
+
+```python
+def _build_frame(self, func_code: int, data: bytes) -> bytes:
+    frame = bytearray([0xFE, func_code]) + bytearray(data)
+    checksum = sum(frame[1:]) % 256
+    frame.append(checksum)
+    return bytes(frame)
+```
+
+Modbus 寄存器映射：
+
+```python
+REGISTER_MAP = {
+    "temp_target": {"addr": 0x000B, "scale": 10},
+}
+
+def set_temperature(self, temp: float, **kwargs) -> bool:
+    reg = REGISTER_MAP["temp_target"]
+    value = int(float(temp) * reg["scale"]) & 0xFFFF
+    self.client.write_register(reg["addr"], value, slave=self.slave_id)
+    self.data["temp_target"] = temp
+    return True
+```
+
+HTTP API 映射：
+
+```python
+API_MAP = {
+    "set_temperature": {
+        "method": "POST",
+        "endpoint": "/api/temperature",
+        "body_key": "target",
+    },
+}
+```
+
+SDK 封装：
+
+```python
+from my_device_sdk import DeviceController
+
+class MyDevice:
+    def __init__(self, device_id=None, config=None, **kwargs):
+        self.config = config or {}
+        self.controller = DeviceController(port=self.config.get("port", "COM1"))
+```
+
+---
+
+## 验证
+
+无需手写注册表 YAML。`@device` 装饰器 + AST 扫描会在启动或检查时生成注册表条目。
+
+```bash
+# 1. 模块可导入
+python -c "from unilabos.devices.<category>.<file> import <ClassName>"
+
+# 2. 启动测试
+unilab -g <graph>.json
+
+# 3. 仅检查注册表
+unilab --check_mode --skip_env_check
+```
+
+仅在旧代码无 `@device`、需要覆盖特殊字段、或做 `--complete_registry` 旧设备补全时，才考虑 YAML。新设备默认不要手写 YAML。
+
+## 图文件节点模板
+
+实验图 JSON 中的 `class` 对应 `@device(id=...)`，`config` 会传入 `__init__` 的 `config` 字典：
+
+```json
+{
+  "id": "my_device_1",
+  "name": "我的设备",
+  "children": [],
+  "parent": null,
+  "type": "device",
+  "class": "my_device",
+  "position": {"x": 0, "y": 0, "z": 0},
+  "config": {
+    "port": "/dev/ttyUSB0",
+    "baudrate": 9600
+  },
+  "data": {}
+}
+```
+
+工作站需要同时配置 `deck` 和 `children`：
+
+```json
+{
+  "nodes": [
+    {
+      "id": "my_station",
+      "type": "device",
+      "class": "my_workstation",
+      "children": ["my_deck"],
+      "config": {},
+      "deck": {
+        "data": {
+          "_resource_child_name": "my_deck",
+          "_resource_type": "unilabos.resources.my_module:MyDeck"
+        }
+      }
+    },
+    {
+      "id": "my_deck",
+      "type": "deck",
+      "class": "MyDeckClass",
+      "parent": "my_station",
+      "config": {"type": "MyDeckClass", "setup": true}
+    }
+  ]
+}
+```
+
+---
+
+## 常见错误清单
+
+- 缺少 `@device`：设备不会被 AST 扫描发现。
+- 只有 `@property` 没有 `@topic_config()`：属性不会稳定广播到 `status_types`。
+- `post_init` 没有 `@not_action`：会被误暴露为动作。
+- `self.data = {}`：空字典会导致属性读取和 schema 初始数据不稳定，必须预填充每个状态键。
+- 动作参数重命名：不要把同类设备已有的 `volume` 改成 `volume_ml`，参数名是接口契约。
+- `status` 使用中文或临时文本：前端和工作流依赖稳定英文状态值。
+- async 方法中使用 `time.sleep()`：应使用 `await self._ros_node.sleep(seconds)`。
+- 硬编码串口响应索引：RS-485 响应前可能有噪声字节，应先定位帧头。
+- 把硬件寄存器单位暴露给用户：对外使用物理单位，驱动内部做 scale 转换。

.cursor/skills/virtual-workbench/SKILL.md

@@ -10,7 +10,8 @@ description: Operate Virtual Workbench via REST API — prepare materials, move
 - **device_id**: `virtual_workbench`
 - **Python 源码**: `unilabos/devices/virtual/workbench.py`
 - **设备类**: `VirtualWorkbench`
-- **动作数**: 6（`auto-prepare_materials`, `auto-move_to_heating_station`, `auto-start_heating`, `auto-move_to_output`, `transfer`, `manual_confirm`）
+- **当前纳入动作**: 5 个（`auto-prepare_materials`, `auto-move_to_heating_station`, `auto-start_heating`, `auto-move_to_output`, `transfer`）
+- **暂跳过动作**: `manual_confirm`、扣电测试 `test`（需要启用时先从最新注册表重新提取 schema）
 - **设备描述**: 模拟工作台，包含 1 个机械臂（每次操作 2s，独占锁）和 3 个加热台（每次加热 60s，可并行）
 
 ### 典型工作流程
@@ -151,7 +152,8 @@ curl -s -X POST "$BASE/api/v1/lab/mcp/run/action" \
 | `auto-start_heating` | `UniLabJsonCommand` |
 | `auto-move_to_output` | `UniLabJsonCommand` |
 | `transfer` | `UniLabJsonCommandAsync` |
-| `manual_confirm` | `UniLabJsonCommand` |
+
+> `manual_confirm` 和扣电测试 `test` 当前不纳入本 skill 的推荐操作范围；不要基于历史 JSON 直接调用，需先重新生成并校验 schema。
 
 ### 10. 查询任务状态
 
@@ -225,11 +227,9 @@ curl -s -X PUT "$BASE/api/v1/edge/material/node" \
 | `transfer`        | `resource`       | ResourceSlot | 待转移物料数组       |
 | `transfer`        | `target_device`  | DeviceSlot   | 目标设备路径         |
 | `transfer`        | `mount_resource` | ResourceSlot | 目标孔位数组         |
-| `manual_confirm`  | `resource`       | ResourceSlot | 确认用物料数组       |
-| `manual_confirm`  | `target_device`  | DeviceSlot   | 确认用目标设备       |
-| `manual_confirm`  | `mount_resource` | ResourceSlot | 确认用目标孔位数组   |
 
 > `prepare_materials`、`move_to_heating_station`、`start_heating`、`move_to_output` 这 4 个动作**无 Slot 字段**，参数为纯数值/整数。
+> `manual_confirm` 先跳过，不维护其 Slot 字段表。
 
 ---
 
@@ -270,3 +270,13 @@ prepare_materials (count=5)
 ```
 
 创建节点时，`prepare_materials` 的 5 个 output handle（`channel_1` ~ `channel_5`）分别连接到 5 个 `move_to_heating_station` 节点的 `material_input` handle。每个 `move_to_heating_station` 的 `heating_station_output` 和 `material_number_output` 连接到对应 `start_heating` 的 `station_id_input` 和 `material_number_input`。
+
+`start_heating` 完成后还需要继续连接到 `move_to_output`，否则加热完成的物料不会移出加热台：
+
+| source action | source handle | target action | target handle | 传递参数 |
+| ------------- | ------------- | ------------- | ------------- | -------- |
+| `auto-prepare_materials` | `channel_N` | `auto-move_to_heating_station` | `material_input` | `material_number` |
+| `auto-move_to_heating_station` | `heating_station_output` | `auto-start_heating` | `station_id_input` | `station_id` |
+| `auto-move_to_heating_station` | `material_number_output` | `auto-start_heating` | `material_number_input` | `material_number` |
+| `auto-start_heating` | `heating_done_station` | `auto-move_to_output` | `output_station_input` | `station_id` |
+| `auto-start_heating` | `heating_done_material` | `auto-move_to_output` | `output_material_input` | `material_number` |

.cursor/skills/virtual-workbench/action-index.md

@@ -1,6 +1,8 @@
 # Action Index — virtual_workbench
 
-6 个动作，按功能分类。每个动作的完整 JSON Schema 在 `actions/<name>.json`。
+当前纳入 5 个动作，按功能分类。每个动作的完整 JSON Schema 在 `actions/<name>.json`。
+
+暂跳过：`manual_confirm`、扣电测试 `test`。这两个动作需要启用时，先从最新 `req_device_registry_upload.json` 重新提取 schema 并校验参数。
 
 ---
 
@@ -60,17 +62,18 @@
 
 ---
 
-## 人工确认
+## 暂跳过动作
 
 ### `manual_confirm`
 
-创建人工确认节点，等待用户手动确认后继续（含物料转移上下文）
+创建人工确认节点，等待用户手动确认后继续（含物料转移上下文）。当前先不纳入推荐操作范围。
 
 - **action_type**: `UniLabJsonCommand`
 - **Schema**: [`actions/manual_confirm.json`](actions/manual_confirm.json)
-- **核心参数**: `resource`, `target_device`, `mount_resource`, `timeout_seconds`, `assignee_user_ids`
+- **状态**: 暂跳过。源码参数已包含扣电测试相关字段，历史 JSON 可能过期；需要启用时重新提取 schema。
-- **占位符字段**:
+
-  - `resource` — **ResourceSlot**，物料数组
+### `test`
-  - `target_device` — **DeviceSlot**，目标设备路径
+
-  - `mount_resource` — **ResourceSlot**，目标孔位数组
+启动扣电测试。当前先不纳入本 skill。
-  - `assignee_user_ids` — `unilabos_manual_confirm` 类型
+
+- **状态**: 暂跳过。需要启用时从注册表生成 `actions/test.json` 后再补充索引。

.github/workflows/ci-check.yml

@@ -25,7 +25,7 @@ jobs:
           fetch-depth: 0
 
       - name: Setup Miniforge
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniforge-version: latest
           use-mamba: true

.github/workflows/conda-pack-build.yml

@@ -43,7 +43,7 @@ jobs:
             platform: linux-64
             env_file: unilabos-linux-64.yaml
             script_ext: sh
-          - os: macos-15 # Intel (via Rosetta)
+          - os: macos-15-intel # Intel x86_64
             platform: osx-64
             env_file: unilabos-osx-64.yaml
             script_ext: sh
@@ -86,7 +86,7 @@ jobs:
 
       - name: Setup Miniforge (with mamba)
         if: steps.should_build.outputs.should_build == 'true'
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniforge-version: latest
           use-mamba: true

.github/workflows/deploy-docs.yml

@@ -51,7 +51,7 @@ jobs:
           fetch-depth: 0
 
       - name: Setup Miniforge (with mamba)
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniforge-version: latest
           use-mamba: true
@@ -84,7 +84,7 @@ jobs:
 
       - name: Setup Pages
         id: pages
-        uses: actions/configure-pages@v5
+        uses: actions/configure-pages@v6
         if: |
           github.event.workflow_run.head_branch == 'main' ||
           (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
@@ -105,7 +105,7 @@ jobs:
           test -f docs/_build/html/index.html && echo "✓ index.html exists" || echo "✗ index.html missing"
 
       - name: Upload build artifacts
-        uses: actions/upload-pages-artifact@v4
+        uses: actions/upload-pages-artifact@v5
         if: |
           github.event.workflow_run.head_branch == 'main' ||
           (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
@@ -125,4 +125,4 @@ jobs:
     steps:
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v4
+        uses: actions/deploy-pages@v5

.github/workflows/multi-platform-build.yml

@@ -63,7 +63,7 @@ jobs:
           - os: ubuntu-latest
             platform: linux-64
             env_file: unilabos-linux-64.yaml
-          - os: macos-15 # Intel (via Rosetta)
+          - os: macos-15-intel # Intel x86_64
             platform: osx-64
             env_file: unilabos-osx-64.yaml
           - os: macos-latest # ARM64
@@ -101,10 +101,11 @@ jobs:
 
       - name: Setup Miniforge
         if: steps.should_build.outputs.should_build == 'true'
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniforge-version: latest
           use-mamba: true
+          python-version: '3.11.14'
           channels: conda-forge,robostack-staging
           channel-priority: strict
           activate-environment: build-env
@@ -114,24 +115,22 @@ jobs:
       - name: Install rattler-build and anaconda-client
         if: steps.should_build.outputs.should_build == 'true'
         run: |
-          mamba install --override-channels -c conda-forge rattler-build anaconda-client -y
+          mamba install -n build-env --override-channels -c conda-forge rattler-build anaconda-client -y
 
       - name: Show environment info
         if: steps.should_build.outputs.should_build == 'true'
         run: |
           conda info
-          conda list | grep -E "(rattler-build|anaconda-client)"
+          conda list -n build-env | grep -E "(rattler-build|anaconda-client)"
+          conda run -n build-env rattler-build --version
+          conda run -n build-env anaconda --version
           echo "Platform: ${{ matrix.platform }}"
           echo "OS: ${{ matrix.os }}"
 
       - name: Build conda package
         if: steps.should_build.outputs.should_build == 'true'
         run: |
-          if [[ "${{ matrix.platform }}" == "osx-arm64" ]]; then
+          conda run -n build-env rattler-build build -r ./recipes/msgs/recipe.yaml --target-platform ${{ matrix.platform }} -c robostack -c robostack-staging -c conda-forge
-            rattler-build build -r ./recipes/msgs/recipe.yaml -c robostack -c robostack-staging -c conda-forge
-          else
-            rattler-build build -r ./recipes/msgs/recipe.yaml -c robostack -c robostack-staging -c conda-forge
-          fi
 
       - name: List built packages
         if: steps.should_build.outputs.should_build == 'true'
@@ -171,5 +170,5 @@ jobs:
         run: |
           for package in $(find ./output -name "*.conda"); do
             echo "Uploading $package to unilab organization..."
-            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
           done

.github/workflows/unilabos-conda-build.yml

@@ -59,7 +59,7 @@ jobs:
         include:
           - os: ubuntu-latest
             platform: linux-64
-          - os: macos-15 # Intel (via Rosetta)
+          - os: macos-15-intel # Intel x86_64
             platform: osx-64
           - os: macos-latest # ARM64
             platform: osx-arm64
@@ -94,10 +94,11 @@ jobs:
 
       - name: Setup Miniforge
         if: steps.should_build.outputs.should_build == 'true'
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniforge-version: latest
           use-mamba: true
+          python-version: '3.11.14'
           channels: conda-forge,robostack-staging,uni-lab
           channel-priority: strict
           activate-environment: build-env
@@ -107,13 +108,15 @@ jobs:
       - name: Install rattler-build and anaconda-client
         if: steps.should_build.outputs.should_build == 'true'
         run: |
-          mamba install --override-channels -c conda-forge rattler-build anaconda-client -y
+          mamba install -n build-env --override-channels -c conda-forge rattler-build anaconda-client -y
 
       - name: Show environment info
         if: steps.should_build.outputs.should_build == 'true'
         run: |
           conda info
-          conda list | grep -E "(rattler-build|anaconda-client)"
+          conda list -n build-env | grep -E "(rattler-build|anaconda-client)"
+          conda run -n build-env rattler-build --version
+          conda run -n build-env anaconda --version
           echo "Platform: ${{ matrix.platform }}"
           echo "OS: ${{ matrix.os }}"
           echo "Build full package: ${{ github.event_name == 'workflow_dispatch' && github.event.inputs.build_full == 'true' }}"
@@ -128,7 +131,7 @@ jobs:
         if: steps.should_build.outputs.should_build == 'true'
         run: |
           echo "Building unilabos-env (conda environment dependencies)..."
-          rattler-build build -r .conda/environment/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge
+          conda run -n build-env rattler-build build -r .conda/environment/recipe.yaml --target-platform ${{ matrix.platform }} -c uni-lab -c robostack-staging -c conda-forge
 
       - name: Upload unilabos-env to Anaconda.org (if enabled)
         if: |
@@ -140,7 +143,7 @@ jobs:
         run: |
           echo "Uploading unilabos-env to uni-lab organization..."
           for package in $(find ./output -name "unilabos-env*.conda"); do
-            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
           done
 
       - name: Build unilabos (with pip package)
@@ -148,7 +151,7 @@ jobs:
         run: |
           echo "Building unilabos package..."
           # 如果已上传到 Anaconda，从 uni-lab channel 获取 unilabos-env；否则从本地 output 获取
-          rattler-build build -r .conda/base/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge --channel ./output
+          conda run -n build-env rattler-build build -r .conda/base/recipe.yaml --target-platform ${{ matrix.platform }} -c uni-lab -c robostack-staging -c conda-forge --channel ./output
 
       - name: Upload unilabos to Anaconda.org (if enabled)
         if: |
@@ -160,7 +163,7 @@ jobs:
         run: |
           echo "Uploading unilabos to uni-lab organization..."
           for package in $(find ./output -name "unilabos-0*.conda" -o -name "unilabos-[0-9]*.conda"); do
-            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
           done
 
       - name: Build unilabos-full - Only when explicitly requested
@@ -170,7 +173,7 @@ jobs:
           github.event.inputs.build_full == 'true'
         run: |
           echo "Building unilabos-full package on ${{ matrix.platform }}..."
-          rattler-build build -r .conda/full/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge --channel ./output
+          conda run -n build-env rattler-build build -r .conda/full/recipe.yaml --target-platform ${{ matrix.platform }} -c uni-lab -c robostack-staging -c conda-forge --channel ./output
 
       - name: Upload unilabos-full to Anaconda.org (if enabled)
         if: |
@@ -181,7 +184,7 @@ jobs:
         run: |
           echo "Uploading unilabos-full to uni-lab organization..."
           for package in $(find ./output -name "unilabos-full*.conda"); do
-            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
           done
 
       - name: List built packages

docs/developer_guide/add_PLC.md

@@ -0,0 +1,611 @@
+# PLC 通信标准与设备驱动编写指南（基于 AI4M 工站）
+
+> 本文档以 `unilabos/devices/workstation/AI4M`（水凝胶检测工站）为参考实现，
+> 介绍如何将 PLC 控制的实验设备接入 Uni-Lab-OS：包含通信协议选型、节点表标准、
+> 通信基类、设备驱动、Registry 配置以及调试方法。
+>
+> 阅读对象：负责现场调试与设备接入的同学。
+
+---
+
+## 0. 总览：一台 PLC 设备从硬件到云端的链路
+
+```
+       PLC（西门子 / 倍福 / 三菱 / 汇川 / 国产 PLC ...）
+                   ▲
+                   │  各家 PLC 私有协议（S7 / Modbus / EtherCAT ...）
+                   │
+        ┌──────────┴──────────┐
+        │  OPC UA Server      │  ← 统一在 PLC 侧或独立网关上配置
+        │  （内置或 KEPServer）│
+        └──────────┬──────────┘
+                   │  OPC UA over TCP（标准协议）
+                   │
+        ┌──────────┴──────────┐
+        │  Uni-Lab 设备驱动    │  ← 本教程主体
+        │  AI4MDevice         │
+        │  ├─ base_opcua_client.py  通信基类
+        │  ├─ opcua_nodes_*.csv     节点表（标准）
+        │  └─ AI4M.py               动作函数
+        └──────────┬──────────┘
+                   │  ROS2 Action / 云端 HTTP
+                   ▼
+              实验记录本 / 云端调度
+```
+
+**统一约定**：所有 PLC 设备**只暴露 OPC UA 接口**给 Uni-Lab，PC 端不直接处理 S7 / Modbus 等底层协议。
+这是 Uni-Lab 在工站类设备上的 PLC 通信标准。
+
+---
+
+## 1. 为什么选 OPC UA 作为标准？
+
+| 维度 | 自研 TCP/串口协议 | Modbus | **OPC UA** |
+|---|---|---|---|
+| 厂家无关 | ✗ | 部分 | **✓** |
+| 自带类型系统 | ✗ | ✗（裸寄存器） | **✓（Boolean/Int16/Float...）** |
+| 命名空间 / 节点树 | ✗ | ✗（地址=魔数） | **✓（带名字、可分组）** |
+| 订阅推送 | ✗ | ✗ | **✓（DataChange Notification）** |
+| 鉴权 / 加密 | 自己造 | ✗ | **✓** |
+| 与 PLC 工程师沟通成本 | 高 | 中 | **低（按变量名沟通）** |
+
+实际接入时，PLC 工程师只需要在 PLC 侧把约定的"上位通讯变量"暴露到 OPC UA Server，
+我们在 PC 侧就能用 `节点名 + 数据类型` 直接读写，不用管底层是 S7 还是 Modbus。
+
+---
+
+## 2. 节点表标准：`opcua_nodes_xxx.csv`
+
+PLC 侧暴露的所有变量统一**用一张 CSV 表**描述，这是 PC 端和 PLC 端**唯一的接口契约**。
+位置示例：`unilabos/devices/workstation/AI4M/opcua_nodes_AI4M.csv`。
+
+### 2.1 列定义
+
+| 列名 | 是否必填 | 说明 |
+|---|---|---|
+| `Name` | ✅ | 节点名（PLC 工程师在 PLC 项目中真实使用的变量名，通常是中文/原始名） |
+| `EnglishName` | 推荐 | 英文别名，**PC 端代码全部用这个名字**调用 |
+| `NodeType` | ✅ | `VARIABLE`（变量）或 `METHOD`（方法），AI4M 全部用变量 |
+| `DataType` | ✅ | `BOOLEAN` / `INT16` / `INT32` / `FLOAT` / `DOUBLE` / `STRING` ... |
+| `NodeLanguage` | 推荐 | `Chinese` / `English`，配合 `EnglishName` 做映射 |
+| `NodeId` | ✅ | OPC UA 标准 NodeId，格式 `ns=<namespace>;s=<string>` 或 `ns=<n>;i=<int>` |
+
+### 2.2 真实样例（节选自 `opcua_nodes_AI4M.csv`）
+
+| Name | EnglishName | NodeType | DataType | NodeLanguage | NodeId |
+|---|---|---|---|---|---|
+| 机器人空闲 | `robot_ready` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|机器人空闲` |
+| 机器人取烧杯编号 | `robot_pick_beaker_id` | VARIABLE | INT16 | Chinese | `ns=4;s=上位通讯变量\|机器人取烧杯编号` |
+| 检测1请求参数 | `station_1_request_params` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|检测1请求参数` |
+| 检测1工艺完成 | `station_1_process_complete` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|检测1工艺完成` |
+| 磁力搅拌参数设置_C[0].搅拌速度 | `mag_stirrer_c0_stir_speed` | VARIABLE | INT16 | Chinese | `ns=4;s=上位通讯变量\|磁力搅拌参数设置_C[0].搅拌速度` |
+| 报警复位 | `alarm_reset` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|报警复位` |
+
+### 2.3 设计规范（必读）
+
+1. **命名按"角色-编号-属性"分层**，便于代码批量寻址：
+   - `mag_stirrer_c{0..4}_stir_speed`（搅拌仪 0~4 的搅拌速度）
+   - `station_{1..3}_process_complete`（检测站 1~3 的完成信号）
+   - `robot_rack_pick_beaker_{1..5}_complete`（取烧杯 1~5 的完成信号）
+
+   这样在驱动里可以直接 `f"mag_stirrer_c{idx}_stir_speed"` 拼出节点名。
+
+2. **数据类型与 PLC 侧严格一致**：
+   - `BOOL` → `BOOLEAN`，`INT/WORD` → `INT16/UINT16`，`DINT` → `INT32`，`REAL` → `FLOAT`。
+   - 类型不一致会触发 `BadTypeMismatch`，写入失败。
+
+3. **NodeId 必须从 PLC 工程或 OPC UA Server 中导出**，不要自己拼。
+   常见格式：
+   - 西门子 1500：`ns=4;s=上位通讯变量|<变量名>`
+   - 倍福 TwinCAT：`ns=4;s=PLC1.MAIN.<变量名>`
+   - KEPServerEX：`ns=2;s=Channel1.Device1.<Tag>`
+
+4. **每个工站一个独立 CSV**，不要共用。
+   AI4M 中真机用 `opcua_nodes_AI4M.csv`，仿真用 `opcua_nodes_AI4M_sim.csv`。
+
+---
+
+## 3. 通信基类架构
+
+文件：`unilabos/devices/workstation/AI4M/base_opcua_client.py`
+
+整个通信层分两层：
+
+```
+BaseOpcUaClient                       # 最小可用：连接 + 节点注册 + 读写 + 方法调用
+        ▲
+        │ 继承
+        │
+OpcUaClientWithSubscription           # 生产可用：+ 订阅推送 + 缓存 + 自动重连
+        ▲
+        │ 继承
+        │
+AI4MDevice                            # 业务驱动：在它之上写设备动作函数
+```
+
+### 3.1 `BaseOpcUaClient` 核心能力
+
+```python
+class BaseOpcUaClient(UniversalDriver):
+    client: Optional[Client] = None
+    _node_registry: Dict[str, OpcUaNodeBase] = {}     # name -> Variable/Method
+    _name_mapping: Dict[str, str] = {}                # 英文名 -> 中文名
+    _reverse_mapping: Dict[str, str] = {}             # 中文名 -> 英文名
+    _found_node_objects: Dict[str, Any] = {}          # 缓存 ua.Node 用于订阅
+
+    @classmethod
+    def load_csv(cls, file_path) -> Tuple[List[OpcUaNode], dict, dict]: ...
+    def register_node_list(self, node_list) -> "BaseOpcUaClient": ...
+    def use_node(self, name) -> OpcUaNodeBase: ...
+    def read_node(self, node_name: str) -> str: ...   # 返回 JSON
+    def write_node(self, json_input: str) -> str: ...
+    def call_method(self, node_name, *args) -> Tuple[Any, bool]: ...
+```
+
+它做的事情可以归纳为四步：
+
+1. **`load_csv`**：读取节点表，建立 `Name ↔ EnglishName` 双向映射。
+2. **`register_node_list`**：把节点登记进 `_variables_to_find` 待查找列表。
+3. **`_connect` → `_find_nodes`**：连上 OPC UA 后，按 `NodeId` 把每个节点解析成 `Variable` / `Method` 对象，放进 `_node_registry`。
+4. **`use_node(name)`**：业务代码取节点的唯一入口，**支持中英文混用**，找不到会自动重试一次。
+
+### 3.2 `OpcUaClientWithSubscription` 增强能力
+
+在 `BaseOpcUaClient` 基础上提供三个生产环境必备的能力：
+
+#### a) 订阅缓存（高频读零开销）
+
+```python
+def _setup_subscriptions(self):
+    self._subscription = self.client.create_subscription(
+        self._subscription_interval,    # 默认 500ms
+        SubscriptionHandler(self),
+    )
+    for node_name, node in self._node_registry.items():
+        if node.type == NodeType.VARIABLE and node.node_id:
+            handle = self._subscription.subscribe_data_change(ua_node)
+            self._subscription_handles[node_name] = handle
+```
+
+当 PLC 侧变量变化时，`datachange_notification` 回调会把新值写进 `self._node_values[name]`，
+后续 `get_node_value` 优先读缓存——**业务代码可以放心地写 `while not self.get_node_value(...): time.sleep(1)` 而不用担心 OPC UA 频繁请求**。
+
+#### b) 智能缓存的 `get_node_value`
+
+```python
+def get_node_value(self, name, use_cache=True, force_read=False):
+    # 1. 中英文名归一化
+    chinese_name = self._name_mapping.get(name, name)
+
+    # 2. force_read=True 强制透传到 OPC UA Server
+    if force_read: ...
+
+    # 3. 命中订阅推送 → 直接返回缓存
+    # 4. 命中按需读 + 未过期（cache_timeout=5s）→ 返回缓存
+    # 5. 否则发起 read 并更新缓存
+```
+
+#### c) 连接监控 + 自动重连
+
+后台线程每 30s 调一次 `client.get_namespace_array()` 探活，断线则自动 `disconnect → connect → 重新订阅`，最多重试 5 次。
+
+### 3.3 数据类型 / 节点类型
+
+`unilabos/device_comms/opcua_client/node/uniopcua.py`：
+
+```python
+class DataType(Enum):
+    BOOLEAN = VariantType.Boolean
+    INT16   = VariantType.Int16
+    INT32   = VariantType.Int32
+    FLOAT   = VariantType.Float
+    STRING  = VariantType.String
+    # ...
+
+class NodeType(Enum):
+    VARIABLE = NodeClass.Variable
+    METHOD   = NodeClass.Method
+    OBJECT   = NodeClass.Object
+```
+
+`Variable.write()` 内部会按 `DataType` 做强制类型转换，
+所以 CSV 里的 `DataType` 列就是"PC 端转换写入值的类型说明书"。
+
+---
+
+## 4. 编写设备驱动：以 `AI4MDevice` 为例
+
+文件：`unilabos/devices/workstation/AI4M/AI4M.py`
+
+### 4.1 继承通信基类，最小骨架
+
+```python
+from typing import Optional
+from unilabos.devices.workstation.AI4M.base_opcua_client import OpcUaClientWithSubscription
+
+class AI4MDevice(OpcUaClientWithSubscription):
+    def __init__(
+        self,
+        url: str,                              # opc.tcp://192.168.1.10:4840
+        deck: Optional[AI4M_deck] = None,      # 物料台面（资源树）
+        csv_path: str = None,                  # 节点表 CSV
+        username: str = None,
+        password: str = None,
+        use_subscription: bool = True,
+        cache_timeout: float = 5.0,
+        subscription_interval: int = 500,
+        *args, **kwargs,
+    ):
+        super().__init__(
+            url=url, username=username, password=password,
+            use_subscription=use_subscription,
+            cache_timeout=cache_timeout,
+            subscription_interval=subscription_interval,
+            *args, **kwargs,
+        )
+
+        # 物料台面初始化（见教程 4. 物料系统）
+        self.deck = deck or AI4M_deck(setup=True)
+        self._robot_lock = threading.Lock()
+
+        # 关键：加载节点表
+        if csv_path:
+            self.load_nodes_from_csv(csv_path)
+```
+
+`load_nodes_from_csv` 会一次性完成：解析 CSV → 注册节点 → 解析 NodeId → 建立订阅，
+**之后整个驱动都通过 `self.get_node_value(name)` / `self.set_node_value(name, value)` 操作 PLC**。
+
+### 4.2 PLC 通信的核心模式：握手协议（Handshake）
+
+PLC 编程的本质是"扫描周期 + 状态机"，PC 端**绝对不能用 fire-and-forget 的方式发指令**。
+和 PLC 配合的标准模式是 **"PC 写指令 → PC 等待 PLC 回执 → PC 复位指令"**。
+
+AI4M 中所有 `trigger_*` 函数都遵循以下三种握手范式之一：
+
+#### 范式 A：脉冲触发 + 完成信号（最常用）
+
+```python
+def trigger_init(self) -> dict:
+    # ① 复位上一轮残留
+    self.set_node_value("alarm_reset", True); time.sleep(1.0)
+    self.set_node_value("alarm_reset", False)
+    self.set_node_value("manual_auto_switch", False)
+
+    # ② 等待 PLC 退出自动模式
+    while self.get_node_value("auto_mode"):
+        time.sleep(1.0)
+
+    # ③ 发起初始化脉冲（True → False）
+    self.set_node_value("initialize", True); time.sleep(1.0)
+    self.set_node_value("initialize", False)
+
+    # ④ 等待 PLC 给出完成信号
+    while not self.get_node_value("init finished"):
+        time.sleep(1.0)
+
+    return {"message": "设备初始化完成"}
+```
+
+要点：
+- **"PC 写一个 BOOL 拉高再拉低"** 模拟脉冲，PLC 用上升沿触发动作。
+- **`get_node_value` 要在 while 循环里轮询**，配合订阅缓存基本无压力。
+- **每个动作必须有"开始"和"完成"两个独立的 BOOL 节点**，不能复用。
+
+#### 范式 B：参数下发 + 请求/已执行/完成 三步握手（带数据的工艺）
+
+```python
+def trigger_station_process(self, station_id: int, mag_stir_speed: int, ...):
+    request_node        = f"station_{station_id}_request_params"
+    params_received_node = f"station_{station_id}_params_received"
+    start_node          = f"station_{station_id}_start"
+    complete_node       = f"station_{station_id}_process_complete"
+
+    # ① PC 复位三个状态位（避免上一轮影响）
+    self._reset_station_process_flags(station_id)
+
+    # ② 等 PLC 主动请求参数（PLC 准备好了才接收）
+    while not self.get_node_value(request_node):
+        time.sleep(1.0)
+
+    # ③ PC 下发参数（注意：PLC 内部数组是 0-based，PC 暴露给用户是 1-based）
+    station_idx = station_id - 1
+    self.set_node_value(f"mag_stirrer_c{station_idx}_stir_speed", mag_stir_speed)
+    self.set_node_value(f"mag_stirrer_c{station_idx}_heat_temp",  mag_stir_heat_temp)
+    self.set_node_value(f"mag_stirrer_c{station_idx}_time_set",   mag_stir_time_set)
+    self.set_node_value(f"syringe_pump_{station_idx}_abs_position_set", syringe_pump_abs_pos)
+
+    # ④ PC 通知 PLC "参数已就绪"，等 PLC 回复"已执行"
+    self.set_node_value(start_node, True)
+    while not self.get_node_value(params_received_node):
+        time.sleep(1.0)
+
+    # ⑤ 等 PLC 完成整个工艺
+    while not self.get_node_value(complete_node):
+        time.sleep(5.0)
+
+    self.set_node_value(start_node, False)   # 复位，方便下一轮
+    return {"station_id": station_id, "message": "..."}
+```
+
+四个状态位的语义：
+
+| 信号 | 方向 | 含义 |
+|---|---|---|
+| `station_X_request_params` | **PLC → PC** | "我准备好了，把参数给我" |
+| `station_X_start` | **PC → PLC** | "参数我已经写好了，开干" |
+| `station_X_params_received` | **PLC → PC** | "参数我已经吃下了" |
+| `station_X_process_complete` | **PLC → PC** | "工艺已经做完" |
+
+**这是 PLC 通信教科书级别的标准范式**，所有带数据下发的动作都建议照抄。
+
+#### 范式 C：编号下发 + 编号对应的完成信号（多目标互锁）
+
+```python
+def trigger_robot_pick_beaker(self, pick_beaker_id: int, place_station_id: int = None, ...):
+    # ① 等机器人空闲（互锁）
+    while not self.get_node_value("robot_ready"):
+        time.sleep(1.0)
+
+    # ② 阶段一：下发"取哪一杯"编号 + 等"取这一杯完成"
+    pick_complete_node  = f"robot_rack_pick_beaker_{pick_beaker_id}_complete"
+    self.set_node_value("robot_pick_beaker_id", pick_beaker_id)
+    while not self.get_node_value(pick_complete_node):
+        time.sleep(1.0)
+
+    # ③ 阶段二：下发"放到哪个工站"编号 + 等"放完成"
+    place_complete_node = f"robot_place_station_{place_station_id}_complete"
+    self._reset_station_process_flags(place_station_id)
+    self.set_node_value("robot_place_station_id", place_station_id)
+    while not self.get_node_value(place_complete_node):
+        time.sleep(1.0)
+```
+
+要点：
+- **同一个动作的多个目标用"编号变量 + 编号对应的完成信号"实现**，不要每个目标都开一个开始位。
+- **配合 Python 端 `threading.Lock()` 做软互锁**，避免多个线程争抢机器人。
+- **每个阶段有独立的完成信号**，串行等待，不能合并。
+
+### 4.3 一些容易踩坑的细节
+
+1. **节点名映射**
+   `set_node_value("alarm_reset", True)` 实际写入的是 CSV 中文名 `报警复位`，
+   `get_node_value` 同理。**业务代码全部用 EnglishName**，不要直接用中文。
+
+2. **PLC 数组索引和 PC 不一致**
+   AI4M 里 PC 暴露 `station_id ∈ {1, 2, 3}`，但 PLC 内部数组是 `C[0..2]`，
+   驱动里要做 `station_idx = station_id - 1`，**这种映射只在驱动层做一次**，
+   不要让上层（registry / 实验记录本）感知。
+
+3. **订阅模式下 BOOL 节点的边沿同步**
+   订阅有 ~500ms 延迟。如果你刚 `set_node_value(x, True)` 就立刻 `get_node_value(x)`，
+   读到的可能还是 `False`（订阅还没推回来）。
+   解决方案：**写完后用 `force_read=True` 透传一次** 或加一段 `time.sleep`。
+
+4. **永远不要忘记复位**
+   `start` 拉 True 后必须有地方拉回 False，否则下一轮 PLC 上升沿不触发。
+   AI4M 在 `_reset_station_process_flags` 中统一做：
+
+   ```python
+   def _reset_station_process_flags(self, station_id: int) -> None:
+       self.set_node_value(f"station_{station_id}_process_complete", False)
+       self.set_node_value(f"station_{station_id}_start", False)
+       self.set_node_value(f"station_{station_id}_params_received", False)
+   ```
+
+5. **耗时长的等待 sleep 加大**
+   工艺等待用 `time.sleep(5.0)`，机器人等待用 `time.sleep(1.0)`，初始化等待 `time.sleep(1.0)`，
+   不要全部用 0.1s 轮询，会把日志刷爆。
+
+---
+
+## 5. 把驱动接到 Uni-Lab：Registry + Graph
+
+### 5.1 Registry YAML（动作 schema）
+
+文件：`unilabos/registry/devices/AI4M_station.yaml`
+
+```yaml
+AI4M_station:
+  category: [AI4M_station]
+  class:
+    module: unilabos.devices.workstation.AI4M.AI4M:AI4MDevice    # ← 入口类
+    type: python
+    action_value_mappings:
+      auto-trigger_init:
+        schema:
+          description: 设备初始化...
+          properties:
+            goal:    { properties: {}, required: [], type: object }
+            result:
+              properties: { message: { type: string } }
+              required: [message]
+              type: object
+          type: object
+        type: UniLabJsonCommand
+
+      auto-trigger_station_process:
+        always_free: true
+        schema:
+          description: 执行检测工艺流程
+          properties:
+            goal:
+              properties:
+                station_id:                   { type: integer, description: 检测编号 1-3 }
+                mag_stir_stir_speed:          { type: integer }
+                mag_stir_heat_temp:           { type: integer }
+                mag_stir_time_set:            { type: integer }
+                syringe_pump_abs_position_set:{ type: integer }
+              required: [station_id, mag_stir_stir_speed, mag_stir_heat_temp,
+                         mag_stir_time_set, syringe_pump_abs_position_set]
+              type: object
+            result: { ... }
+        type: UniLabJsonCommand
+
+  init_param_schema:
+    config:
+      type: object
+      required: [url]
+      properties:
+        url:                   { type: string,  description: OPC UA 服务器地址 }
+        csv_path:              { type: string,  description: 节点配置 CSV 路径 }
+        deck:                  { type: string,  description: 资源树配置 }
+        username:              { type: string }
+        password:              { type: string }
+        use_subscription:      { type: boolean, default: true }
+        cache_timeout:         { type: number,  default: 5.0 }
+        subscription_interval: { type: integer, default: 500 }
+```
+
+规则总结：
+- `class.module` 指向驱动类（`module:ClassName`）。
+- `action_value_mappings` 中的 key 形如 `auto-<方法名>`，对应驱动里的同名 Python 方法。
+- `schema.goal` 自动转成 ROS2 Action 的 goal 消息，`schema.result` 转 result。
+- `init_param_schema.config` 对应 `__init__` 的入参，**所有需要现场改的参数都要列出来**（最重要的就是 `url` 和 `csv_path`）。
+- `always_free: true` 表示该动作不占用工站独占锁（多检测站可并发执行）。
+
+### 5.2 Graph JSON（实例化）
+
+文件：`unilabos/devices/workstation/AI4M/AI4M.json`
+
+```json
+{
+  "nodes": [
+    {
+      "id": "AI4M_station",
+      "name": "AI4M_station",
+      "type": "device",
+      "class": "AI4M_station",
+      "children": ["AI4M_deck"],
+      "parent": null,
+      "config": {
+        "url": "opc.tcp://192.168.1.10:4840",
+        "csv_path": "opcua_nodes_AI4M.csv",
+        "deck": {
+          "data": {
+            "_resource_child_name": "AI4M_deck",
+            "_resource_type": "unilabos.devices.workstation.AI4M.decks:AI4M_deck"
+          }
+        }
+      }
+    },
+    {
+      "id": "AI4M_deck",
+      "type": "deck",
+      "class": "AI4M_deck",
+      "parent": "AI4M_station",
+      "config": { "type": "AI4M_deck" }
+    }
+  ]
+}
+```
+
+要点：
+- `class` 必须和 Registry YAML 的顶层 key 完全一致（`AI4M_station`）。
+- `config` 字段**逐字传给驱动 `__init__`**，所以 Graph JSON = "现场参数表"。
+- 多套相同设备时拷贝一份，把 `id` / `url` 改掉即可（参考 `AI4M002_station`）。
+
+### 5.3 启动命令（来自 `start.md`）
+
+```cmd
+# 真机
+python unilabos/app/main.py -g unilabos/devices/workstation/AI4M/AI4M.json `
+  --ak <ak> --sk <sk> --upload_registry --addr <api_url> --disable_browser
+
+# 仿真（KEPServerEX 跑在本机 49320 端口）
+python unilabos/app/main.py -g unilabos/devices/workstation/AI4M/AI4Msim.json `
+  --ak <ak> --sk <sk> --upload_registry --disable_browser
+```
+
+`--upload_registry` 会把 `AI4M_station.yaml` 的 schema 上传到云端，
+之后实验记录本就能看到所有 `auto-*` 动作。
+
+---
+
+## 6. 调试方法
+
+### 6.1 用 KEPServerEX 仿真 PLC
+
+不带 PLC 的开发机上，可以用 KEPServerEX（或 `python-opcua` 自建 server）模拟。
+AI4M 提供了一份仿真节点表 `opcua_nodes_AI4M_sim.csv`，**只改 NodeId 不改语义**，
+所以驱动代码无需任何改动即可在本机调试。
+
+### 6.2 单独跑驱动（不开 ROS）
+
+在驱动文件末尾的 `if __name__ == '__main__':` 段：
+
+```python
+if __name__ == '__main__':
+    A4 = AI4MDevice(
+        url="opc.tcp://192.168.1.10:4840",
+        csv_path="opcua_nodes_AI4M.csv",
+    )
+    A4.trigger_init()
+    print("初始化完成")
+    A4.trigger_robot_pick_beaker(1, 1)
+```
+
+**新动作上线前一定要在这里裸跑一遍**，确认握手时序正确，再往上接 ROS。
+
+### 6.3 看日志判断卡在哪
+
+`base_opcua_client.py` 的日志已经覆盖了所有关键节点：
+
+```
+✓ 客户端已连接!
+✓ 找到变量节点: 'robot_ready', NodeId: ns=4;s=...
+✓ 已订阅节点: robot_ready
+✓ 节点查找完成：所有 142 个节点均已找到
+```
+
+如果看到 `⚠ 以下 N 个节点未找到`，**99% 是 CSV 里的 NodeId 写错了**，回去对一下 PLC 工程导出的 NodeId。
+
+### 6.4 检查节点是否能直接读写
+
+```python
+# 透传读，绕过订阅缓存
+A4.get_node_value("robot_ready", force_read=True)
+
+# 直接读 JSON 形式（适合从 HTTP/调试面板调）
+A4.read_node("robot_ready")
+
+# 写
+A4.set_node_value("alarm_reset", True)
+A4.write_node('{"node_name": "alarm_reset", "value": false}')
+```
+
+---
+
+## 7. 接入新 PLC 设备的 Checklist
+
+接到一台新工站时，按下面顺序做就能保证不漏：
+
+- [ ] 1. 让 PLC 工程师把上位通讯变量整理到 OPC UA Server，导出 NodeId 清单。
+- [ ] 2. 在 `unilabos/devices/workstation/<设备名>/` 下新建目录，复制 `AI4M/base_opcua_client.py` 不动。
+- [ ] 3. 整理 `opcua_nodes_<设备名>.csv`，6 列填齐，并补上 `EnglishName`。
+- [ ] 4. 在该目录写设备驱动 `<设备名>.py`，继承 `OpcUaClientWithSubscription`：
+  - [ ] `__init__` 调用 `super().__init__` + `self.load_nodes_from_csv(csv_path)`。
+  - [ ] 每个动作函数用范式 A/B/C 写握手协议。
+  - [ ] 每个动作函数都返回 `dict`，至少含 `message` 字段。
+- [ ] 5. 在 `unilabos/registry/devices/` 下新建 `<设备名>_station.yaml`，配置 `init_param_schema` 和 `action_value_mappings`。
+- [ ] 6. 在该目录新建 `<设备名>.json`（Graph），填好 `url` 和 `csv_path`。
+- [ ] 7. 用 `if __name__ == '__main__':` 单独跑驱动确认握手 OK。
+- [ ] 8. 用 `python unilabos/app/main.py -g <Graph> --upload_registry ...` 上线，到实验记录本下发动作回归。
+
+---
+
+## 8. 参考实现速查
+
+| 关注点 | 在 AI4M 中看哪里 |
+|---|---|
+| OPC UA 通信基类 | `base_opcua_client.py` |
+| 节点定义类型系统 | `unilabos/device_comms/opcua_client/node/uniopcua.py` |
+| 节点表 CSV 标准 | `opcua_nodes_AI4M.csv` |
+| 设备驱动入口类 | `AI4M.py: AI4MDevice` |
+| 握手范式 A（脉冲+完成） | `AI4M.py: trigger_init` |
+| 握手范式 B（请求/参数/完成） | `AI4M.py: trigger_station_process` |
+| 握手范式 C（编号+完成） | `AI4M.py: trigger_robot_pick_beaker` |
+| 自动模式批量参数下发 | `AI4M.py: download_auto_params` |
+| Registry schema | `unilabos/registry/devices/AI4M_station.yaml` |
+| Graph 实例化 | `AI4M.json` / `AI4Msim.json` |
+| 启动命令 | `start.md` |

recipes/msgs/recipe.yaml

@@ -1,6 +1,6 @@
 package:
   name: ros-humble-unilabos-msgs
-  version: 0.11.2
+  version: 0.11.3
 source:
   path: ../../unilabos_msgs
   target_directory: src

recipes/unilabos/recipe.yaml

@@ -1,6 +1,6 @@
 package:
   name: unilabos
-  version: "0.11.2"
+  version: "0.11.3"
 
 source:
   path: ../..

scripts/workflow.py

@@ -2,7 +2,6 @@ import json
 import logging
 import traceback
 import uuid
-import xml.etree.ElementTree as ET
 from typing import Any, Dict, List
 
 import networkx as nx
@@ -25,7 +24,15 @@ class SimpleGraph:
 
     def add_edge(self, source, target, **attrs):
         """添加边"""
-        edge = {"source": source, "target": target, **attrs}
+        # edge = {"source": source, "target": target, **attrs}
+        edge = {
+            "source": source, "target": target,
+            "source_node_uuid": source,
+            "target_node_uuid": target,
+            "source_handle_io": "source",
+            "target_handle_io": "target",
+            **attrs
+        }
         self.edges.append(edge)
 
     def to_dict(self):
@@ -42,6 +49,7 @@ class SimpleGraph:
             "multigraph": False,
             "graph": {},
             "nodes": nodes_list,
+            "edges": self.edges,
             "links": self.edges,
         }
 
@@ -58,495 +66,8 @@ def extract_json_from_markdown(text: str) -> str:
     return text
 
 
-def convert_to_type(val: str) -> Any:
-    """将字符串值转换为适当的数据类型"""
-    if val == "True":
-        return True
-    if val == "False":
-        return False
-    if val == "?":
-        return None
-    if val.endswith(" g"):
-        return float(val.split(" ")[0])
-    if val.endswith("mg"):
-        return float(val.split("mg")[0])
-    elif val.endswith("mmol"):
-        return float(val.split("mmol")[0]) / 1000
-    elif val.endswith("mol"):
-        return float(val.split("mol")[0])
-    elif val.endswith("ml"):
-        return float(val.split("ml")[0])
-    elif val.endswith("RPM"):
-        return float(val.split("RPM")[0])
-    elif val.endswith(" °C"):
-        return float(val.split(" ")[0])
-    elif val.endswith(" %"):
-        return float(val.split(" ")[0])
-    return val
 
 
-def refactor_data(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
-    """统一的数据重构函数，根据操作类型自动选择模板"""
-    refactored_data = []
-
-    # 定义操作映射，包含生物实验和有机化学的所有操作
-    OPERATION_MAPPING = {
-        # 生物实验操作
-        "transfer_liquid": "SynBioFactory-liquid_handler.prcxi-transfer_liquid",
-        "transfer": "SynBioFactory-liquid_handler.biomek-transfer",
-        "incubation": "SynBioFactory-liquid_handler.biomek-incubation",
-        "move_labware": "SynBioFactory-liquid_handler.biomek-move_labware",
-        "oscillation": "SynBioFactory-liquid_handler.biomek-oscillation",
-        # 有机化学操作
-        "HeatChillToTemp": "SynBioFactory-workstation-HeatChillProtocol",
-        "StopHeatChill": "SynBioFactory-workstation-HeatChillStopProtocol",
-        "StartHeatChill": "SynBioFactory-workstation-HeatChillStartProtocol",
-        "HeatChill": "SynBioFactory-workstation-HeatChillProtocol",
-        "Dissolve": "SynBioFactory-workstation-DissolveProtocol",
-        "Transfer": "SynBioFactory-workstation-TransferProtocol",
-        "Evaporate": "SynBioFactory-workstation-EvaporateProtocol",
-        "Recrystallize": "SynBioFactory-workstation-RecrystallizeProtocol",
-        "Filter": "SynBioFactory-workstation-FilterProtocol",
-        "Dry": "SynBioFactory-workstation-DryProtocol",
-        "Add": "SynBioFactory-workstation-AddProtocol",
-    }
-
-    UNSUPPORTED_OPERATIONS = ["Purge", "Wait", "Stir", "ResetHandling"]
-
-    for step in data:
-        operation = step.get("action")
-        if not operation or operation in UNSUPPORTED_OPERATIONS:
-            continue
-
-        # 处理重复操作
-        if operation == "Repeat":
-            times = step.get("times", step.get("parameters", {}).get("times", 1))
-            sub_steps = step.get("steps", step.get("parameters", {}).get("steps", []))
-            for i in range(int(times)):
-                sub_data = refactor_data(sub_steps)
-                refactored_data.extend(sub_data)
-            continue
-
-        # 获取模板名称
-        template = OPERATION_MAPPING.get(operation)
-        if not template:
-            # 自动推断模板类型
-            if operation.lower() in ["transfer", "incubation", "move_labware", "oscillation"]:
-                template = f"SynBioFactory-liquid_handler.biomek-{operation}"
-            else:
-                template = f"SynBioFactory-workstation-{operation}Protocol"
-
-        # 创建步骤数据
-        step_data = {
-            "template": template,
-            "description": step.get("description", step.get("purpose", f"{operation} operation")),
-            "lab_node_type": "Device",
-            "parameters": step.get("parameters", step.get("action_args", {})),
-        }
-        refactored_data.append(step_data)
-
-    return refactored_data
-
-
-def build_protocol_graph(
-    labware_info: List[Dict[str, Any]], protocol_steps: List[Dict[str, Any]], workstation_name: str
-) -> SimpleGraph:
-    """统一的协议图构建函数，根据设备类型自动选择构建逻辑"""
-    G = SimpleGraph()
-    resource_last_writer = {}
-    LAB_NAME = "SynBioFactory"
-
-    protocol_steps = refactor_data(protocol_steps)
-
-    # 检查协议步骤中的模板来判断协议类型
-    has_biomek_template = any(
-        ("biomek" in step.get("template", "")) or ("prcxi" in step.get("template", ""))
-        for step in protocol_steps
-    )
-
-    if has_biomek_template:
-        # 生物实验协议图构建
-        for labware_id, labware in labware_info.items():
-            node_id = str(uuid.uuid4())
-
-            labware_attrs = labware.copy()
-            labware_id = labware_attrs.pop("id", labware_attrs.get("name", f"labware_{uuid.uuid4()}"))
-            labware_attrs["description"] = labware_id
-            labware_attrs["lab_node_type"] = (
-                "Reagent" if "Plate" in str(labware_id) else "Labware" if "Rack" in str(labware_id) else "Sample"
-            )
-            labware_attrs["device_id"] = workstation_name
-
-            G.add_node(node_id, template=f"{LAB_NAME}-host_node-create_resource", **labware_attrs)
-            resource_last_writer[labware_id] = f"{node_id}:labware"
-
-        # 处理协议步骤
-        prev_node = None
-        for i, step in enumerate(protocol_steps):
-            node_id = str(uuid.uuid4())
-            G.add_node(node_id, **step)
-
-            # 添加控制流边
-            if prev_node is not None:
-                G.add_edge(prev_node, node_id, source_port="ready", target_port="ready")
-            prev_node = node_id
-
-            # 处理物料流
-            params = step.get("parameters", {})
-            if "sources" in params and params["sources"] in resource_last_writer:
-                source_node, source_port = resource_last_writer[params["sources"]].split(":")
-                G.add_edge(source_node, node_id, source_port=source_port, target_port="labware")
-
-            if "targets" in params:
-                resource_last_writer[params["targets"]] = f"{node_id}:labware"
-
-        # 添加协议结束节点
-        end_id = str(uuid.uuid4())
-        G.add_node(end_id, template=f"{LAB_NAME}-liquid_handler.biomek-run_protocol")
-        if prev_node is not None:
-            G.add_edge(prev_node, end_id, source_port="ready", target_port="ready")
-
-    else:
-        # 有机化学协议图构建
-        WORKSTATION_ID = workstation_name
-
-        # 为所有labware创建资源节点
-        for item_id, item in labware_info.items():
-            # item_id = item.get("id") or item.get("name", f"item_{uuid.uuid4()}")
-            node_id = str(uuid.uuid4())
-
-            # 判断节点类型
-            if item.get("type") == "hardware" or "reactor" in str(item_id).lower():
-                if "reactor" not in str(item_id).lower():
-                    continue
-                lab_node_type = "Sample"
-                description = f"Prepare Reactor: {item_id}"
-                liquid_type = []
-                liquid_volume = []
-            else:
-                lab_node_type = "Reagent"
-                description = f"Add Reagent to Flask: {item_id}"
-                liquid_type = [item_id]
-                liquid_volume = [1e5]
-
-            G.add_node(
-                node_id,
-                template=f"{LAB_NAME}-host_node-create_resource",
-                description=description,
-                lab_node_type=lab_node_type,
-                res_id=item_id,
-                device_id=WORKSTATION_ID,
-                class_name="container",
-                parent=WORKSTATION_ID,
-                bind_locations={"x": 0.0, "y": 0.0, "z": 0.0},
-                liquid_input_slot=[-1],
-                liquid_type=liquid_type,
-                liquid_volume=liquid_volume,
-                slot_on_deck="",
-                role=item.get("role", ""),
-            )
-            resource_last_writer[item_id] = f"{node_id}:labware"
-
-        last_control_node_id = None
-
-        # 处理协议步骤
-        for step in protocol_steps:
-            node_id = str(uuid.uuid4())
-            G.add_node(node_id, **step)
-
-            # 控制流
-            if last_control_node_id is not None:
-                G.add_edge(last_control_node_id, node_id, source_port="ready", target_port="ready")
-            last_control_node_id = node_id
-
-            # 物料流
-            params = step.get("parameters", {})
-            input_resources = {
-                "Vessel": params.get("vessel"),
-                "ToVessel": params.get("to_vessel"),
-                "FromVessel": params.get("from_vessel"),
-                "reagent": params.get("reagent"),
-                "solvent": params.get("solvent"),
-                "compound": params.get("compound"),
-                "sources": params.get("sources"),
-                "targets": params.get("targets"),
-            }
-
-            for target_port, resource_name in input_resources.items():
-                if resource_name and resource_name in resource_last_writer:
-                    source_node, source_port = resource_last_writer[resource_name].split(":")
-                    G.add_edge(source_node, node_id, source_port=source_port, target_port=target_port)
-
-            output_resources = {
-                "VesselOut": params.get("vessel"),
-                "FromVesselOut": params.get("from_vessel"),
-                "ToVesselOut": params.get("to_vessel"),
-                "FiltrateOut": params.get("filtrate_vessel"),
-                "reagent": params.get("reagent"),
-                "solvent": params.get("solvent"),
-                "compound": params.get("compound"),
-                "sources_out": params.get("sources"),
-                "targets_out": params.get("targets"),
-            }
-
-            for source_port, resource_name in output_resources.items():
-                if resource_name:
-                    resource_last_writer[resource_name] = f"{node_id}:{source_port}"
-
-    return G
-
-
-def draw_protocol_graph(protocol_graph: SimpleGraph, output_path: str):
-    """
-    (辅助功能) 使用 networkx 和 matplotlib 绘制协议工作流图，用于可视化。
-    """
-    if not protocol_graph:
-        print("Cannot draw graph: Graph object is empty.")
-        return
-
-    G = nx.DiGraph()
-
-    for node_id, attrs in protocol_graph.nodes.items():
-        label = attrs.get("description", attrs.get("template", node_id[:8]))
-        G.add_node(node_id, label=label, **attrs)
-
-    for edge in protocol_graph.edges:
-        G.add_edge(edge["source"], edge["target"])
-
-    plt.figure(figsize=(20, 15))
-    try:
-        pos = nx.nx_agraph.graphviz_layout(G, prog="dot")
-    except Exception:
-        pos = nx.shell_layout(G)  # Fallback layout
-
-    node_labels = {node: data["label"] for node, data in G.nodes(data=True)}
-    nx.draw(
-        G,
-        pos,
-        with_labels=False,
-        node_size=2500,
-        node_color="skyblue",
-        node_shape="o",
-        edge_color="gray",
-        width=1.5,
-        arrowsize=15,
-    )
-    nx.draw_networkx_labels(G, pos, labels=node_labels, font_size=8, font_weight="bold")
-
-    plt.title("Chemical Protocol Workflow Graph", size=15)
-    plt.savefig(output_path, dpi=300, bbox_inches="tight")
-    plt.close()
-    print(f"  - Visualization saved to '{output_path}'")
-
-
-from networkx.drawing.nx_agraph import to_agraph
-import re
-
-COMPASS = {"n","e","s","w","ne","nw","se","sw","c"}
-
-def _is_compass(port: str) -> bool:
-    return isinstance(port, str) and port.lower() in COMPASS
-
-def draw_protocol_graph_with_ports(protocol_graph, output_path: str, rankdir: str = "LR"):
-    """
-    使用 Graphviz 端口语法绘制协议工作流图。
-    - 若边上的 source_port/target_port 是 compass（n/e/s/w/...），直接用 compass。
-    - 否则自动为节点创建 record 形状并定义命名端口 <portname>。
-    最终由 PyGraphviz 渲染并输出到 output_path（后缀决定格式，如 .png/.svg/.pdf）。
-    """
-    if not protocol_graph:
-        print("Cannot draw graph: Graph object is empty.")
-        return
-
-    # 1) 先用 networkx 搭建有向图，保留端口属性
-    G = nx.DiGraph()
-    for node_id, attrs in protocol_graph.nodes.items():
-        label = attrs.get("description", attrs.get("template", node_id[:8]))
-        # 保留一个干净的“中心标签”，用于放在 record 的中间槽
-        G.add_node(node_id, _core_label=str(label), **{k:v for k,v in attrs.items() if k not in ("label",)})
-
-    edges_data = []
-    in_ports_by_node  = {}  # 收集命名输入端口
-    out_ports_by_node = {}  # 收集命名输出端口
-
-    for edge in protocol_graph.edges:
-        u = edge["source"]
-        v = edge["target"]
-        sp = edge.get("source_port")
-        tp = edge.get("target_port")
-
-        # 记录到图里（保留原始端口信息）
-        G.add_edge(u, v, source_port=sp, target_port=tp)
-        edges_data.append((u, v, sp, tp))
-
-        # 如果不是 compass，就按“命名端口”先归类，等会儿给节点造 record
-        if sp and not _is_compass(sp):
-            out_ports_by_node.setdefault(u, set()).add(str(sp))
-        if tp and not _is_compass(tp):
-            in_ports_by_node.setdefault(v, set()).add(str(tp))
-
-    # 2) 转为 AGraph，使用 Graphviz 渲染
-    A = to_agraph(G)
-    A.graph_attr.update(rankdir=rankdir, splines="true", concentrate="false", fontsize="10")
-    A.node_attr.update(shape="box", style="rounded,filled", fillcolor="lightyellow", color="#999999", fontname="Helvetica")
-    A.edge_attr.update(arrowsize="0.8", color="#666666")
-
-    # 3) 为需要命名端口的节点设置 record 形状与 label
-    #    左列 = 输入端口；中间 = 核心标签；右列 = 输出端口
-    for n in A.nodes():
-        node = A.get_node(n)
-        core = G.nodes[n].get("_core_label", n)
-
-        in_ports  = sorted(in_ports_by_node.get(n, []))
-        out_ports = sorted(out_ports_by_node.get(n, []))
-
-        # 如果该节点涉及命名端口，则用 record；否则保留原 box
-        if in_ports or out_ports:
-            def port_fields(ports):
-                if not ports:
-                    return " "  # 必须留一个空槽占位
-                # 每个端口一个小格子，<p> name
-                return "|".join(f"<{re.sub(r'[^A-Za-z0-9_:.|-]', '_', p)}> {p}" for p in ports)
-
-            left  = port_fields(in_ports)
-            right = port_fields(out_ports)
-
-            # 三栏：左(入) | 中(节点名) | 右(出)
-            record_label = f"{{ {left} | {core} | {right} }}"
-            node.attr.update(shape="record", label=record_label)
-        else:
-            # 没有命名端口：普通盒子，显示核心标签
-            node.attr.update(label=str(core))
-
-    # 4) 给边设置 headport / tailport
-    #    - 若端口为 compass：直接用 compass（e.g., headport="e"）
-    #    - 若端口为命名端口：使用在 record 中定义的 <port> 名（同名即可）
-    for (u, v, sp, tp) in edges_data:
-        e = A.get_edge(u, v)
-
-        # Graphviz 属性：tail 是源，head 是目标
-        if sp:
-            if _is_compass(sp):
-                e.attr["tailport"] = sp.lower()
-            else:
-                # 与 record label 中 <port> 名一致；特殊字符已在 label 中做了清洗
-                e.attr["tailport"] = re.sub(r'[^A-Za-z0-9_:.|-]', '_', str(sp))
-
-        if tp:
-            if _is_compass(tp):
-                e.attr["headport"] = tp.lower()
-            else:
-                e.attr["headport"] = re.sub(r'[^A-Za-z0-9_:.|-]', '_', str(tp))
-
-        # 可选：若想让边更贴边缘，可设置 constraint/spline 等
-        # e.attr["arrowhead"] = "vee"
-
-    # 5) 输出
-    A.draw(output_path, prog="dot")
-    print(f"  - Port-aware workflow rendered to '{output_path}'")
-
-
-def flatten_xdl_procedure(procedure_elem: ET.Element) -> List[ET.Element]:
-    """展平嵌套的XDL程序结构"""
-    flattened_operations = []
-    TEMP_UNSUPPORTED_PROTOCOL = ["Purge", "Wait", "Stir", "ResetHandling"]
-
-    def extract_operations(element: ET.Element):
-        if element.tag not in ["Prep", "Reaction", "Workup", "Purification", "Procedure"]:
-            if element.tag not in TEMP_UNSUPPORTED_PROTOCOL:
-                flattened_operations.append(element)
-
-        for child in element:
-            extract_operations(child)
-
-    for child in procedure_elem:
-        extract_operations(child)
-
-    return flattened_operations
-
-
-def parse_xdl_content(xdl_content: str) -> tuple:
-    """解析XDL内容"""
-    try:
-        xdl_content_cleaned = "".join(c for c in xdl_content if c.isprintable())
-        root = ET.fromstring(xdl_content_cleaned)
-
-        synthesis_elem = root.find("Synthesis")
-        if synthesis_elem is None:
-            return None, None, None
-
-        # 解析硬件组件
-        hardware_elem = synthesis_elem.find("Hardware")
-        hardware = []
-        if hardware_elem is not None:
-            hardware = [{"id": c.get("id"), "type": c.get("type")} for c in hardware_elem.findall("Component")]
-
-        # 解析试剂
-        reagents_elem = synthesis_elem.find("Reagents")
-        reagents = []
-        if reagents_elem is not None:
-            reagents = [{"name": r.get("name"), "role": r.get("role", "")} for r in reagents_elem.findall("Reagent")]
-
-        # 解析程序
-        procedure_elem = synthesis_elem.find("Procedure")
-        if procedure_elem is None:
-            return None, None, None
-
-        flattened_operations = flatten_xdl_procedure(procedure_elem)
-        return hardware, reagents, flattened_operations
-
-    except ET.ParseError as e:
-        raise ValueError(f"Invalid XDL format: {e}")
-
-
-def convert_xdl_to_dict(xdl_content: str) -> Dict[str, Any]:
-    """
-    将XDL XML格式转换为标准的字典格式
-
-    Args:
-        xdl_content: XDL XML内容
-
-    Returns:
-        转换结果，包含步骤和器材信息
-    """
-    try:
-        hardware, reagents, flattened_operations = parse_xdl_content(xdl_content)
-        if hardware is None:
-            return {"error": "Failed to parse XDL content", "success": False}
-
-        # 将XDL元素转换为字典格式
-        steps_data = []
-        for elem in flattened_operations:
-            # 转换参数类型
-            parameters = {}
-            for key, val in elem.attrib.items():
-                converted_val = convert_to_type(val)
-                if converted_val is not None:
-                    parameters[key] = converted_val
-
-            step_dict = {
-                "operation": elem.tag,
-                "parameters": parameters,
-                "description": elem.get("purpose", f"Operation: {elem.tag}"),
-            }
-            steps_data.append(step_dict)
-
-        # 合并硬件和试剂为统一的labware_info格式
-        labware_data = []
-        labware_data.extend({"id": hw["id"], "type": "hardware", **hw} for hw in hardware)
-        labware_data.extend({"name": reagent["name"], "type": "reagent", **reagent} for reagent in reagents)
-
-        return {
-            "success": True,
-            "steps": steps_data,
-            "labware": labware_data,
-            "message": f"Successfully converted XDL to dict format. Found {len(steps_data)} steps and {len(labware_data)} labware items.",
-        }
-
-    except Exception as e:
-        error_msg = f"XDL conversion failed: {str(e)}"
-        logger.error(error_msg)
-        return {"error": error_msg, "success": False}
 
 
 def create_workflow(

setup.py

@@ -4,7 +4,7 @@ package_name = 'unilabos'
 
 setup(
     name=package_name,
-    version='0.11.2',
+    version='0.11.3',
     packages=find_packages(),
     include_package_data=True,
     install_requires=['setuptools'],

unilabos/__init__.py

@@ -1 +1 @@
-__version__ = "0.11.2"
+__version__ = "0.11.3"

unilabos/app/model.py

@@ -59,6 +59,7 @@ class JobAddReq(BaseModel):
     task_id: str = Field(examples=["task_id"], description="task uuid (auto-generated if empty)", default="")
     job_id: str = Field(examples=["job_id"], description="goal uuid (auto-generated if empty)", default="")
     node_id: str = Field(examples=["node_id"], description="node uuid", default="")
+    notebook_id: str = Field(examples=["notebook_id"], description="notebook uuid", default="")
     server_info: dict = Field(
         examples=[{"send_timestamp": 1717000000.0}],
         description="server info (auto-generated if empty)",

unilabos/app/web/controller.py

@@ -320,6 +320,7 @@ def job_add(req: JobAddReq) -> JobData:
             action_name=action_name,
             task_id=task_id,
             job_id=job_id,
+            notebook_id=req.notebook_id,
             device_action_key=device_action_key,
         )
 

unilabos/app/ws_client.py

@@ -59,6 +59,7 @@ class QueueItem:
     action_name: str
     task_id: str
     job_id: str
+    notebook_id: str
     device_action_key: str
     next_run_time: float = 0  # 下次执行时间戳
     retry_count: int = 0  # 重试次数
@@ -71,6 +72,7 @@ class JobInfo:
     job_id: str
     task_id: str
     device_id: str
+    notebook_id: str
     action_name: str
     device_action_key: str
     status: JobStatus
@@ -539,7 +541,10 @@ class MessageProcessor:
                 self.reconnect_count += 1
                 backoff = WSConfig.reconnect_interval
                 logger.info(
-                    f"[MessageProcessor] 即将在 {backoff} 秒后重连 (已尝试 {self.reconnect_count}/{WSConfig.max_reconnect_attempts})"
+                    "[MessageProcessor] 即将在 %s 秒后重连 (已尝试 %s/%s)",
+                    backoff,
+                    self.reconnect_count,
+                    WSConfig.max_reconnect_attempts,
                 )
                 await asyncio.sleep(backoff)
             else:
@@ -703,6 +708,7 @@ class MessageProcessor:
         action_name = data.get("action_name", "")
         task_id = data.get("task_id", "")
         job_id = data.get("job_id", "")
+        notebook_id = data.get("notebook_id", "")
 
         if not all([device_id, action_name, task_id, job_id]):
             logger.error("[MessageProcessor] Missing required fields in query_action_state")
@@ -718,6 +724,7 @@ class MessageProcessor:
             job_id=job_id,
             task_id=task_id,
             device_id=device_id,
+            notebook_id=notebook_id,
             action_name=action_name,
             device_action_key=device_action_key,
             status=JobStatus.QUEUE,
@@ -732,13 +739,27 @@ class MessageProcessor:
         if can_start_immediately:
             # 可以立即开始
             await self._send_action_state_response(
-                device_id, action_name, task_id, job_id, "query_action_status", True, 0
+                device_id,
+                action_name,
+                task_id,
+                job_id,
+                "query_action_status",
+                True,
+                0,
+                notebook_id=notebook_id,
             )
             logger.trace(f"[MessageProcessor] Job {job_log} can start immediately")
         else:
             # 需要排队
             await self._send_action_state_response(
-                device_id, action_name, task_id, job_id, "query_action_status", False, 10
+                device_id,
+                action_name,
+                task_id,
+                job_id,
+                "query_action_status",
+                False,
+                10,
+                notebook_id=notebook_id,
             )
             logger.trace(f"[MessageProcessor] Job {job_log} queued")
 
@@ -768,6 +789,7 @@ class MessageProcessor:
                         job_id=req.job_id,
                         task_id=req.task_id,
                         device_id=req.device_id,
+                        notebook_id=req.notebook_id,
                         action_name=action_name,
                         device_action_key=device_action_key,
                         status=JobStatus.QUEUE,
@@ -775,11 +797,16 @@ class MessageProcessor:
                         always_free=True,
                     )
                     self.device_manager.add_queue_request(job_info)
+                    existing_job = job_info
                     logger.info(f"[MessageProcessor] Job {job_log} always_free, auto-registered from direct job_start")
                 else:
                     logger.error(f"[MessageProcessor] Job {job_log} not registered (missing query_action_state)")
                     return
 
+            if existing_job and req.notebook_id and not existing_job.notebook_id:
+                existing_job.notebook_id = req.notebook_id
+            notebook_id = req.notebook_id or (existing_job.notebook_id if existing_job else "")
+
             success = self.device_manager.start_job(req.job_id)
             if not success:
                 logger.error(f"[MessageProcessor] Failed to start job {job_log}")
@@ -795,6 +822,7 @@ class MessageProcessor:
                 action_name=req.action,
                 task_id=req.task_id,
                 job_id=req.job_id,
+                notebook_id=notebook_id,
                 device_action_key=device_action_key,
             )
 
@@ -834,6 +862,7 @@ class MessageProcessor:
                             "job_id": req.job_id,
                             "task_id": req.task_id,
                             "device_id": req.device_id,
+                            "notebook_id": queue_item.notebook_id,
                             "action_name": req.action,
                             "status": "failed",
                             "feedback_data": {},
@@ -855,6 +884,7 @@ class MessageProcessor:
                             "query_action_status",
                             True,
                             0,
+                            notebook_id=next_job.notebook_id,
                         )
                         next_job_log = format_job_log(
                             next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name
@@ -1004,11 +1034,16 @@ class MessageProcessor:
 
                     success = host_node.notify_resource_tree_update(dev_id, act, item_list)
 
-                    if success:
+                    if success is True:
                         logger.info(
                             f"[MessageProcessor] Resource tree {act} completed for device {dev_id}, "
                             f"items: {len(item_list)}"
                         )
+                    elif success is None:
+                        logger.info(
+                            f"[MessageProcessor] Resource tree {act} skipped for device {dev_id}: "
+                            "在线增加设备暂不支持"
+                        )
                     else:
                         logger.warning(f"[MessageProcessor] Resource tree {act} failed for device {dev_id}")
 
@@ -1032,6 +1067,11 @@ class MessageProcessor:
 
         for item in device_list:
             target_node_id = item.get("target_node_id", "host_node")
+            if action == "add":
+                logger.info(
+                    f"[DeviceManage] 在线增加设备暂不支持，跳过 add_device: {item.get('id', '')}"
+                )
+                continue
 
             def _notify(target_id: str, act: str, cfg: ResourceDictType):
                 try:
@@ -1101,7 +1141,15 @@ class MessageProcessor:
         logger.info(f"[MessageProcessor] Restart cleanup scheduled")
 
     async def _send_action_state_response(
-        self, device_id: str, action_name: str, task_id: str, job_id: str, typ: str, free: bool, need_more: int
+        self,
+        device_id: str,
+        action_name: str,
+        task_id: str,
+        job_id: str,
+        typ: str,
+        free: bool,
+        need_more: int,
+        notebook_id: str = "",
     ):
         """发送动作状态响应"""
         message = {
@@ -1112,6 +1160,7 @@ class MessageProcessor:
                 "action_name": action_name,
                 "task_id": task_id,
                 "job_id": job_id,
+                "notebook_id": notebook_id,
                 "free": free,
                 "need_more": need_more + 1,
             },
@@ -1194,6 +1243,7 @@ class QueueProcessor:
                             action_name=timeout_job.action_name,
                             task_id=timeout_job.task_id,
                             job_id=timeout_job.job_id,
+                            notebook_id=timeout_job.notebook_id,
                             device_action_key=timeout_job.device_action_key,
                         )
                         # 发布超时失败状态，这会触发正常的job完成流程
@@ -1252,6 +1302,7 @@ class QueueProcessor:
                     "action_name": job_info.action_name,
                     "task_id": job_info.task_id,
                     "job_id": job_info.job_id,
+                    "notebook_id": job_info.notebook_id,
                     "free": False,
                     "need_more": 10 + 1,
                 },
@@ -1291,6 +1342,7 @@ class QueueProcessor:
                     "action_name": job_info.action_name,
                     "task_id": job_info.task_id,
                     "job_id": job_info.job_id,
+                    "notebook_id": job_info.notebook_id,
                     "free": False,
                     "need_more": 10 + 1,
                 },
@@ -1336,12 +1388,15 @@ class QueueProcessor:
                     "action_name": next_job.action_name,
                     "task_id": next_job.task_id,
                     "job_id": next_job.job_id,
+                    "notebook_id": next_job.notebook_id,
                     "free": True,
                     "need_more": 0,
                 },
             }
             self.message_processor.send_message(message)
-            # next_job_log = format_job_log(next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name)
+            # next_job_log = format_job_log(
+            #     next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name
+            # )
             # logger.debug(f"[QueueProcessor] Notified next job {next_job_log} can start")
 
             # 立即触发下一轮状态检查
@@ -1510,6 +1565,7 @@ class WebSocketClient(BaseCommunicationClient):
                 "job_id": item.job_id,
                 "task_id": item.task_id,
                 "device_id": item.device_id,
+                "notebook_id": item.notebook_id,
                 "action_name": item.action_name,
                 "status": status,
                 "feedback_data": feedback_data,

unilabos/resources/graphio.py

@@ -42,7 +42,7 @@ def canonicalize_nodes_data(
     Returns:
         ResourceTreeSet: 标准化后的资源树集合
     """
-    print_status(f"{len(nodes)} Resources loaded:", "info")
+    print_status(f"{len(nodes)} Resources loaded", "info")
 
     # 第一步：基本预处理（处理graphml的label字段）
     outer_host_node_id = None

unilabos/ros/nodes/base_device_node.py

@@ -45,6 +45,7 @@ from unilabos.resources.graphio import (
 )
 from unilabos.resources.plr_additional_res_reg import register
 from unilabos.ros.msgs.message_converter import (
+    String,
     convert_to_ros_msg,
     convert_from_ros_msg_with_mapping,
     convert_to_ros_msg_with_mapping,
@@ -250,7 +251,8 @@ class PropertyPublisher:
     ):
         self.node = node
         self.name = name
-        self.msg_type = msg_type
+        self.msg_type = self._normalize_msg_type(msg_type)
+        self.original_msg_type = msg_type
         self.get_method = get_method
         self.timer_period = initial_period
         self.print_publish = print_publish
@@ -258,16 +260,36 @@ class PropertyPublisher:
 
         self._value = None
         try:
-            self.publisher_ = node.create_publisher(msg_type, f"{name}", qos)
+            self.publisher_ = node.create_publisher(self.msg_type, f"{name}", qos)
         except Exception as e:
             self.node.lab_logger().error(
-                f"StatusError, DeviceId: {self.node.device_id} 创建发布者 {name} 失败，可能由于注册表有误，类型: {msg_type}，错误: {e}"
+                f"StatusError, DeviceId: {self.node.device_id} 创建发布者 {name} 失败，"
+                f"可能由于注册表有误，类型: {msg_type}，错误: {e}"
             )
+            self.msg_type = String
+            try:
+                self.publisher_ = node.create_publisher(self.msg_type, f"{name}", qos)
+                self.node.lab_logger().warning(
+                    f"属性 {name} 的发布类型已降级为 String，原始类型: {msg_type}"
+                )
+            except Exception:
+                self.publisher_ = None
         self.timer = node.create_timer(self.timer_period, self.publish_property)
         self.__loop = ROS2DeviceNode.get_asyncio_loop()
-        str_msg_type = str(msg_type)[8:-2]
+        str_msg_type = str(self.msg_type)[8:-2]
         self.node.lab_logger().trace(f"发布属性: {name}, 类型: {str_msg_type}, 周期: {initial_period}秒, QoS: {qos}")
 
+    @staticmethod
+    def _normalize_msg_type(msg_type):
+        if msg_type in (dict, list, tuple, set) or msg_type in ("dict", "list", "tuple", "set"):
+            return String
+        return msg_type
+
+    def _normalize_value(self, value):
+        if self.msg_type is String and isinstance(value, (dict, list, tuple, set)):
+            return json.dumps(value, ensure_ascii=False, cls=TypeEncoder)
+        return value
+
     def get_property(self):
         if asyncio.iscoroutinefunction(self.get_method):
             # 如果是异步函数，运行事件循环并等待结果
@@ -302,12 +324,16 @@ class PropertyPublisher:
                 pass
                 # self.node.lab_logger().trace(f"【.publish_property】发布 {self.msg_type}: {value}")
             if value is not None:
+                if self.publisher_ is None:
+                    return
+                value = self._normalize_value(value)
                 msg = convert_to_ros_msg(self.msg_type, value)
                 self.publisher_.publish(msg)
                 # self.node.lab_logger().trace(f"【.publish_property】属性 {self.name} 发布成功")
         except Exception as e:
+            topic = getattr(self.publisher_, "topic", self.name)
             self.node.lab_logger().error(
-                f"【.publish_property】发布属性 {self.publisher_.topic} 出错: {str(e)}\n{traceback.format_exc()}"
+                f"【.publish_property】发布属性 {topic} 出错: {str(e)}\n{traceback.format_exc()}"
             )
 
     def change_frequency(self, period):

unilabos/ros/nodes/presets/host_node.py

@@ -1691,7 +1691,9 @@ class HostNode(BaseROS2DeviceNode):
         else:
             self.lab_logger().warning("⚠️ 收到无效的Pong响应（缺少ping_id）")
 
-    def notify_resource_tree_update(self, device_id: str, action: str, resource_uuid_list: List[str]) -> bool:
+    def notify_resource_tree_update(
+        self, device_id: str, action: str, resource_uuid_list: List[str]
+    ) -> Optional[bool]:
         """
         通知设备节点更新资源树
 
@@ -1701,13 +1703,14 @@ class HostNode(BaseROS2DeviceNode):
             resource_uuid_list: 资源UUIDs
 
         Returns:
-            bool: 操作是否成功
+            True if the update completed, False if it failed, None if it was intentionally skipped.
         """
         try:
-            # 检查设备是否存在
             if device_id not in self.devices_names:
-                self.lab_logger().error(f"[Host Node-Resource] Device {device_id} not found in devices_names")
+                self.lab_logger().info(
-                return False
+                    f"[Host Node-Resource] 在线增加设备暂不支持，跳过设备 {device_id} 的资源树 {action} 更新"
+                )
+                return None
 
             namespace = self.devices_names[device_id]
             device_key = f"{namespace}/{device_id}"

unilabos/workflow/from_python_script.py

@@ -0,0 +1,241 @@
+import ast
+import json
+from typing import Dict, List, Any, Tuple, Optional
+
+from .common import WorkflowGraph, RegistryAdapter
+
+Json = Dict[str, Any]
+
+# ---------------- Converter ----------------
+
+class DeviceMethodConverter:
+    """
+    - 字段统一：resource_name（原 device_class）、template_name（原 action_key）
+    - params 单层；inputs 使用 'params.' 前缀
+    - SimpleGraph.add_workflow_node 负责变量连线与边
+    """
+    def __init__(self, device_registry: Optional[Dict[str, Any]] = None):
+        self.graph = WorkflowGraph()
+        self.variable_sources: Dict[str, Dict[str, Any]] = {}        # var -> {node_id, output_name}
+        self.instance_to_resource: Dict[str, Optional[str]] = {}     # 实例名 -> resource_name
+        self.node_id_counter: int = 0
+        self.registry = RegistryAdapter(device_registry or {})
+
+    # ---- helpers ----
+    def _new_node_id(self) -> int:
+        nid = self.node_id_counter
+        self.node_id_counter += 1
+        return nid
+
+    def _assign_targets(self, targets) -> List[str]:
+        names: List[str] = []
+        import ast
+        if isinstance(targets, ast.Tuple):
+            for elt in targets.elts:
+                if isinstance(elt, ast.Name):
+                    names.append(elt.id)
+        elif isinstance(targets, ast.Name):
+            names.append(targets.id)
+        return names
+
+    def _extract_device_instantiation(self, node) -> Optional[Tuple[str, str]]:
+        import ast
+        if not isinstance(node.value, ast.Call):
+            return None
+        callee = node.value.func
+        if isinstance(callee, ast.Name):
+            class_name = callee.id
+        elif isinstance(callee, ast.Attribute) and isinstance(callee.value, ast.Name):
+            class_name = callee.attr
+        else:
+            return None
+        if isinstance(node.targets[0], ast.Name):
+            instance = node.targets[0].id
+            return instance, class_name
+        return None
+
+    def _extract_call(self, call) -> Tuple[str, str, Dict[str, Any], str]:
+        import ast
+        owner_name, method_name, call_kind = "", "", "func"
+        if isinstance(call.func, ast.Attribute):
+            method_name = call.func.attr
+            if isinstance(call.func.value, ast.Name):
+                owner_name = call.func.value.id
+                call_kind = "instance" if owner_name in self.instance_to_resource else "class_or_module"
+            elif isinstance(call.func.value, ast.Attribute) and isinstance(call.func.value.value, ast.Name):
+                owner_name = call.func.value.attr
+                call_kind = "class_or_module"
+        elif isinstance(call.func, ast.Name):
+            method_name = call.func.id
+            call_kind = "func"
+
+        def pack(node):
+            if isinstance(node, ast.Name):
+                return {"type": "variable", "value": node.id}
+            if isinstance(node, ast.Constant):
+                return {"type": "constant", "value": node.value}
+            if isinstance(node, ast.Dict):
+                return {"type": "dict", "value": self._parse_dict(node)}
+            if isinstance(node, ast.List):
+                return {"type": "list", "value": self._parse_list(node)}
+            return {"type": "raw", "value": ast.unparse(node) if hasattr(ast, "unparse") else str(node)}
+
+        args: Dict[str, Any] = {}
+        pos: List[Any] = []
+        for a in call.args:
+            pos.append(pack(a))
+        for kw in call.keywords:
+            args[kw.arg] = pack(kw.value)
+        if pos:
+            args["_positional"] = pos
+        return owner_name, method_name, args, call_kind
+
+    def _parse_dict(self, node) -> Dict[str, Any]:
+        import ast
+        out: Dict[str, Any] = {}
+        for k, v in zip(node.keys, node.values):
+            if isinstance(k, ast.Constant):
+                key = str(k.value)
+                if isinstance(v, ast.Name):
+                    out[key] = f"var:{v.id}"
+                elif isinstance(v, ast.Constant):
+                    out[key] = v.value
+                elif isinstance(v, ast.Dict):
+                    out[key] = self._parse_dict(v)
+                elif isinstance(v, ast.List):
+                    out[key] = self._parse_list(v)
+        return out
+
+    def _parse_list(self, node) -> List[Any]:
+        import ast
+        out: List[Any] = []
+        for elt in node.elts:
+            if isinstance(elt, ast.Name):
+                out.append(f"var:{elt.id}")
+            elif isinstance(elt, ast.Constant):
+                out.append(elt.value)
+            elif isinstance(elt, ast.Dict):
+                out.append(self._parse_dict(elt))
+            elif isinstance(elt, ast.List):
+                out.append(self._parse_list(elt))
+        return out
+
+    def _normalize_var_tokens(self, x: Any) -> Any:
+        if isinstance(x, str) and x.startswith("var:"):
+            return {"__var__": x[4:]}
+        if isinstance(x, list):
+            return [self._normalize_var_tokens(i) for i in x]
+        if isinstance(x, dict):
+            return {k: self._normalize_var_tokens(v) for k, v in x.items()}
+        return x
+
+    def _make_params_payload(self, resource_name: Optional[str], template_name: str, call_args: Dict[str, Any]) -> Dict[str, Any]:
+        input_keys = self.registry.get_action_input_keys(resource_name, template_name) if resource_name else []
+        defaults = self.registry.get_action_goal_default(resource_name, template_name) if resource_name else {}
+        params: Dict[str, Any] = dict(defaults)
+
+        def unpack(p):
+            t, v = p.get("type"), p.get("value")
+            if t == "variable":
+                return {"__var__": v}
+            if t == "dict":
+                return self._normalize_var_tokens(v)
+            if t == "list":
+                return self._normalize_var_tokens(v)
+            return v
+
+        for k, p in call_args.items():
+            if k == "_positional":
+                continue
+            params[k] = unpack(p)
+
+        pos = call_args.get("_positional", [])
+        if pos:
+            if input_keys:
+                for i, p in enumerate(pos):
+                    if i >= len(input_keys):
+                        break
+                    name = input_keys[i]
+                    if name in params:
+                        continue
+                    params[name] = unpack(p)
+            else:
+                for i, p in enumerate(pos):
+                    params[f"arg_{i}"] = unpack(p)
+        return params
+
+    # ---- handlers ----
+    def _on_assign(self, stmt):
+        import ast
+        inst = self._extract_device_instantiation(stmt)
+        if inst:
+            instance, code_class = inst
+            resource_name = self.registry.resolve_resource_by_classname(code_class)
+            self.instance_to_resource[instance] = resource_name
+            return
+
+        if isinstance(stmt.value, ast.Call):
+            owner, method, call_args, kind = self._extract_call(stmt.value)
+            if kind == "instance":
+                device_key = owner
+                resource_name = self.instance_to_resource.get(owner)
+            else:
+                device_key = owner
+                resource_name = self.registry.resolve_resource_by_classname(owner)
+
+            module = self.registry.get_device_module(resource_name)
+            params = self._make_params_payload(resource_name, method, call_args)
+
+            nid = self._new_node_id()
+            self.graph.add_workflow_node(
+                nid,
+                device_key=device_key,
+                resource_name=resource_name,      # ✅
+                module=module,
+                template_name=method,             # ✅
+                params=params,
+                variable_sources=self.variable_sources,
+                add_ready_if_no_vars=True,
+                prev_node_id=(nid - 1) if nid > 0 else None,
+            )
+
+            out_vars = self._assign_targets(stmt.targets[0])
+            for var in out_vars:
+                self.variable_sources[var] = {"node_id": nid, "output_name": "result"}
+
+    def _on_expr(self, stmt):
+        import ast
+        if not isinstance(stmt.value, ast.Call):
+            return
+        owner, method, call_args, kind = self._extract_call(stmt.value)
+        if kind == "instance":
+            device_key = owner
+            resource_name = self.instance_to_resource.get(owner)
+        else:
+            device_key = owner
+            resource_name = self.registry.resolve_resource_by_classname(owner)
+
+        module = self.registry.get_device_module(resource_name)
+        params = self._make_params_payload(resource_name, method, call_args)
+
+        nid = self._new_node_id()
+        self.graph.add_workflow_node(
+            nid,
+            device_key=device_key,
+            resource_name=resource_name,      # ✅
+            module=module,
+            template_name=method,             # ✅
+            params=params,
+            variable_sources=self.variable_sources,
+            add_ready_if_no_vars=True,
+            prev_node_id=(nid - 1) if nid > 0 else None,
+        )
+
+    def convert(self, python_code: str):
+        tree = ast.parse(python_code)
+        for stmt in tree.body:
+            if isinstance(stmt, ast.Assign):
+                self._on_assign(stmt)
+            elif isinstance(stmt, ast.Expr):
+                self._on_expr(stmt)
+        return self

unilabos/workflow/from_xdl.py

@@ -0,0 +1,131 @@
+from typing import List, Any, Dict
+import xml.etree.ElementTree as ET
+
+
+def convert_to_type(val: str) -> Any:
+    """将字符串值转换为适当的数据类型"""
+    if val == "True":
+        return True
+    if val == "False":
+        return False
+    if val == "?":
+        return None
+    if val.endswith(" g"):
+        return float(val.split(" ")[0])
+    if val.endswith("mg"):
+        return float(val.split("mg")[0])
+    elif val.endswith("mmol"):
+        return float(val.split("mmol")[0]) / 1000
+    elif val.endswith("mol"):
+        return float(val.split("mol")[0])
+    elif val.endswith("ml"):
+        return float(val.split("ml")[0])
+    elif val.endswith("RPM"):
+        return float(val.split("RPM")[0])
+    elif val.endswith(" °C"):
+        return float(val.split(" ")[0])
+    elif val.endswith(" %"):
+        return float(val.split(" ")[0])
+    return val
+
+
+def flatten_xdl_procedure(procedure_elem: ET.Element) -> List[ET.Element]:
+    """展平嵌套的XDL程序结构"""
+    flattened_operations = []
+    TEMP_UNSUPPORTED_PROTOCOL = ["Purge", "Wait", "Stir", "ResetHandling"]
+
+    def extract_operations(element: ET.Element):
+        if element.tag not in ["Prep", "Reaction", "Workup", "Purification", "Procedure"]:
+            if element.tag not in TEMP_UNSUPPORTED_PROTOCOL:
+                flattened_operations.append(element)
+
+        for child in element:
+            extract_operations(child)
+
+    for child in procedure_elem:
+        extract_operations(child)
+
+    return flattened_operations
+
+
+def parse_xdl_content(xdl_content: str) -> tuple:
+    """解析XDL内容"""
+    try:
+        xdl_content_cleaned = "".join(c for c in xdl_content if c.isprintable())
+        root = ET.fromstring(xdl_content_cleaned)
+
+        synthesis_elem = root.find("Synthesis")
+        if synthesis_elem is None:
+            return None, None, None
+
+        # 解析硬件组件
+        hardware_elem = synthesis_elem.find("Hardware")
+        hardware = []
+        if hardware_elem is not None:
+            hardware = [{"id": c.get("id"), "type": c.get("type")} for c in hardware_elem.findall("Component")]
+
+        # 解析试剂
+        reagents_elem = synthesis_elem.find("Reagents")
+        reagents = []
+        if reagents_elem is not None:
+            reagents = [{"name": r.get("name"), "role": r.get("role", "")} for r in reagents_elem.findall("Reagent")]
+
+        # 解析程序
+        procedure_elem = synthesis_elem.find("Procedure")
+        if procedure_elem is None:
+            return None, None, None
+
+        flattened_operations = flatten_xdl_procedure(procedure_elem)
+        return hardware, reagents, flattened_operations
+
+    except ET.ParseError as e:
+        raise ValueError(f"Invalid XDL format: {e}")
+
+
+def convert_xdl_to_dict(xdl_content: str) -> Dict[str, Any]:
+    """
+    将XDL XML格式转换为标准的字典格式
+
+    Args:
+        xdl_content: XDL XML内容
+
+    Returns:
+        转换结果，包含步骤和器材信息
+    """
+    try:
+        hardware, reagents, flattened_operations = parse_xdl_content(xdl_content)
+        if hardware is None:
+            return {"error": "Failed to parse XDL content", "success": False}
+
+        # 将XDL元素转换为字典格式
+        steps_data = []
+        for elem in flattened_operations:
+            # 转换参数类型
+            parameters = {}
+            for key, val in elem.attrib.items():
+                converted_val = convert_to_type(val)
+                if converted_val is not None:
+                    parameters[key] = converted_val
+
+            step_dict = {
+                "operation": elem.tag,
+                "parameters": parameters,
+                "description": elem.get("purpose", f"Operation: {elem.tag}"),
+            }
+            steps_data.append(step_dict)
+
+        # 合并硬件和试剂为统一的labware_info格式
+        labware_data = []
+        labware_data.extend({"id": hw["id"], "type": "hardware", **hw} for hw in hardware)
+        labware_data.extend({"name": reagent["name"], "type": "reagent", **reagent} for reagent in reagents)
+
+        return {
+            "success": True,
+            "steps": steps_data,
+            "labware": labware_data,
+            "message": f"Successfully converted XDL to dict format. Found {len(steps_data)} steps and {len(labware_data)} labware items.",
+        }
+
+    except Exception as e:
+        error_msg = f"XDL conversion failed: {str(e)}"
+        return {"error": error_msg, "success": False}

unilabos_msgs/package.xml

@@ -2,7 +2,7 @@
 <?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
 <package format="3">
   <name>unilabos_msgs</name>
-  <version>0.11.2</version>
+  <version>0.11.3</version>
   <description>ROS2 Messages package for unilabos devices</description>
   <maintainer email="changjh@pku.edu.cn">Junhan Chang</maintainer>
   <maintainer email="18435084+Xuwznln@users.noreply.github.com">Xuwznln</maintainer>