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@@ -3,7 +3,7 @@
|
||||
|
||||
package:
|
||||
name: unilabos
|
||||
version: 0.10.19
|
||||
version: 0.11.3
|
||||
|
||||
source:
|
||||
path: ../../unilabos
|
||||
@@ -54,7 +54,7 @@ requirements:
|
||||
- pymodbus
|
||||
- matplotlib
|
||||
- pylibftdi
|
||||
- uni-lab::unilabos-env ==0.10.19
|
||||
- uni-lab::unilabos-env ==0.11.3
|
||||
|
||||
about:
|
||||
repository: https://github.com/deepmodeling/Uni-Lab-OS
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
package:
|
||||
name: unilabos-env
|
||||
version: 0.10.19
|
||||
version: 0.11.3
|
||||
|
||||
build:
|
||||
noarch: generic
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
|
||||
package:
|
||||
name: unilabos-full
|
||||
version: 0.10.19
|
||||
version: 0.11.3
|
||||
|
||||
build:
|
||||
noarch: generic
|
||||
@@ -11,7 +11,7 @@ build:
|
||||
requirements:
|
||||
run:
|
||||
# Base unilabos package (includes unilabos-env)
|
||||
- uni-lab::unilabos ==0.10.19
|
||||
- uni-lab::unilabos ==0.11.3
|
||||
# Documentation tools
|
||||
- sphinx
|
||||
- sphinx_rtd_theme
|
||||
|
||||
@@ -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 |
|
||||
|
||||
---
|
||||
|
||||
@@ -71,6 +160,45 @@ from unilabos.registry.decorators import action
|
||||
- `_` 开头的方法 → 不扫描
|
||||
- `@not_action` 标记的方法 → 排除
|
||||
|
||||
### 参数文档 → JSON Schema 元数据
|
||||
|
||||
在 `__init__` 和 action 方法 docstring 的 `Args:` 小节里，使用以下格式生成入参 schema 的显示信息：
|
||||
|
||||
```python
|
||||
"""
|
||||
Args:
|
||||
param[显示名称]: 参数说明，会写入 JSON Schema 的 description。
|
||||
"""
|
||||
```
|
||||
|
||||
- `param[显示名称]` 的显示名称会写入 goal property 的 `title`。
|
||||
- `:` 后面的说明会写入 goal property 的 `description`。
|
||||
- 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
|
||||
@@ -105,13 +233,27 @@ import logging
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
|
||||
from unilabos.registry.decorators import device, action, topic_config, not_action
|
||||
from unilabos.registry.decorators import action, device, not_action, topic_config
|
||||
|
||||
@device(id="my_device", category=["my_category"], description="设备描述")
|
||||
@device(
|
||||
id="my_device",
|
||||
category=["my_category"],
|
||||
description="设备描述",
|
||||
display_name="设备显示名",
|
||||
)
|
||||
class MyDevice:
|
||||
"""设备类说明。"""
|
||||
|
||||
_ros_node: BaseROS2DeviceNode
|
||||
|
||||
def __init__(self, device_id: Optional[str] = None, config: Optional[Dict[str, Any]] = None, **kwargs):
|
||||
"""
|
||||
初始化设备。
|
||||
|
||||
Args:
|
||||
device_id[设备ID]: 设备实例 ID，默认使用 my_device。
|
||||
config[设备配置]: 设备启动配置。
|
||||
"""
|
||||
self.device_id = device_id or "my_device"
|
||||
self.config = config or {}
|
||||
self.logger = logging.getLogger(f"MyDevice.{self.device_id}")
|
||||
@@ -133,7 +275,13 @@ class MyDevice:
|
||||
|
||||
@action(description="执行操作")
|
||||
def my_action(self, param: float = 0.0, name: str = "") -> Dict[str, Any]:
|
||||
"""带 @action 装饰器 → 注册为 'my_action' 动作"""
|
||||
"""
|
||||
带 @action 装饰器 → 注册为 'my_action' 动作。
|
||||
|
||||
Args:
|
||||
param[操作数值]: 操作使用的数值参数。
|
||||
name[操作名称]: 操作名称或备注。
|
||||
"""
|
||||
return {"success": True}
|
||||
|
||||
def get_info(self) -> Dict[str, Any]:
|
||||
@@ -158,3 +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。
|
||||
|
||||
@@ -28,13 +28,14 @@ python -c "import base64,sys; print('Authorization: Lab ' + base64.b64encode(f'{
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
|-------------|------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| ------------ | ----------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-lab.bohrium.com` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
|
||||
确认后设置：
|
||||
|
||||
```bash
|
||||
BASE="<根据 addr 确定的 URL>"
|
||||
AUTH="Authorization: Lab <gen_auth.py 输出的 token>"
|
||||
@@ -65,7 +66,7 @@ curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
返回：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
|
||||
{ "code": 0, "data": { "uuid": "xxx", "name": "实验室名称" } }
|
||||
```
|
||||
|
||||
记住 `data.uuid` 为 `lab_uuid`。
|
||||
@@ -90,6 +91,7 @@ curl -s -X POST "$BASE/api/v1/lab/reagent" \
|
||||
```
|
||||
|
||||
返回成功时包含试剂 UUID：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", ...}}
|
||||
```
|
||||
@@ -99,7 +101,7 @@ curl -s -X POST "$BASE/api/v1/lab/reagent" \
|
||||
## 试剂字段说明
|
||||
|
||||
| 字段 | 类型 | 必填 | 说明 | 示例 |
|
||||
|------|------|------|------|------|
|
||||
| ------------------- | ------ | ---- | ----------------------------- | ------------------------ |
|
||||
| `lab_uuid` | string | 是 | 实验室 UUID（从 API #1 获取） | `"8511c672-..."` |
|
||||
| `cas` | string | 是 | CAS 注册号 | `"7732-18-3"` |
|
||||
| `name` | string | 是 | 试剂中文/英文名称 | `"水"` |
|
||||
@@ -114,7 +116,7 @@ curl -s -X POST "$BASE/api/v1/lab/reagent" \
|
||||
### unit 单位值
|
||||
|
||||
| 值 | 单位 |
|
||||
|------|------|
|
||||
| ------ | ---- |
|
||||
| `"mL"` | 毫升 |
|
||||
| `"L"` | 升 |
|
||||
| `"g"` | 克 |
|
||||
@@ -133,8 +135,22 @@ curl -s -X POST "$BASE/api/v1/lab/reagent" \
|
||||
|
||||
```json
|
||||
[
|
||||
{"cas": "7732-18-3", "name": "水", "molecular_formula": "H2O", "smiles": "O", "stock_in_quantity": 10, "unit": "mL"},
|
||||
{"cas": "64-17-5", "name": "乙醇", "molecular_formula": "C2H6O", "smiles": "CCO", "stock_in_quantity": 5, "unit": "L"}
|
||||
{
|
||||
"cas": "7732-18-3",
|
||||
"name": "水",
|
||||
"molecular_formula": "H2O",
|
||||
"smiles": "O",
|
||||
"stock_in_quantity": 10,
|
||||
"unit": "mL"
|
||||
},
|
||||
{
|
||||
"cas": "64-17-5",
|
||||
"name": "乙醇",
|
||||
"molecular_formula": "C2H6O",
|
||||
"smiles": "CCO",
|
||||
"stock_in_quantity": 5,
|
||||
"unit": "L"
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
@@ -160,9 +176,20 @@ cas,name,molecular_formula,smiles,stock_in_quantity,unit,supplier,production_dat
|
||||
7732-18-3,水,H2O,O,10,mL,农夫山泉,2025-11-18T00:00:00Z,2026-11-18T00:00:00Z
|
||||
```
|
||||
|
||||
### 日期格式规则（重要）
|
||||
|
||||
所有日期字段（`production_date`、`expiry_date`）**必须**使用 ISO 8601 完整格式：`YYYY-MM-DDTHH:MM:SSZ`。
|
||||
|
||||
- 用户输入 `2025-03-01` → 转换为 `"2025-03-01T00:00:00Z"`
|
||||
- 用户输入 `2025/9/1` → 转换为 `"2025-09-01T00:00:00Z"`
|
||||
- 用户未提供日期 → 使用当天日期 + `T00:00:00Z`，有效期默认 +1 年
|
||||
|
||||
**禁止**发送不带时间部分的日期字符串（如 `"2025-03-01"`），API 会拒绝。
|
||||
|
||||
### 执行与汇报
|
||||
|
||||
每次 API 调用后：
|
||||
|
||||
1. 检查返回 `code`（0 = 成功）
|
||||
2. 记录成功/失败数量
|
||||
3. 全部完成后汇总：「共录入 N 条试剂，成功 X 条，失败 Y 条」
|
||||
@@ -173,9 +200,10 @@ cas,name,molecular_formula,smiles,stock_in_quantity,unit,supplier,production_dat
|
||||
## 常见试剂速查表
|
||||
|
||||
| 名称 | CAS | 分子式 | SMILES |
|
||||
|------|-----|--------|--------|
|
||||
| --------------------- | --------- | ---------- | ------------------------------------ |
|
||||
| 水 | 7732-18-3 | H2O | O |
|
||||
| 乙醇 | 64-17-5 | C2H6O | CCO |
|
||||
| 乙酸 | 64-19-7 | C2H4O2 | CC(O)=O |
|
||||
| 甲醇 | 67-56-1 | CH4O | CO |
|
||||
| 丙酮 | 67-64-1 | C3H6O | CC(C)=O |
|
||||
| 二甲基亚砜(DMSO) | 67-68-5 | C2H6OS | CS(C)=O |
|
||||
|
||||
@@ -1,11 +1,13 @@
|
||||
---
|
||||
name: batch-submit-experiment
|
||||
description: Batch submit experiments (notebooks) to Uni-Lab platform — list workflows, generate node_params from registry schemas, submit multiple rounds, check notebook status. Use when the user wants to submit experiments, create notebooks, batch run workflows, check experiment status, or mentions 提交实验/批量实验/notebook/实验轮次/实验状态.
|
||||
description: Batch submit experiments (notebooks) to the Uni-Lab cloud platform (leap-lab) — list workflows, generate node_params from registry schemas, submit multiple rounds, check notebook status. Use when the user wants to submit experiments, create notebooks, batch run workflows, check experiment status, or mentions 提交实验/批量实验/notebook/实验轮次/实验状态.
|
||||
---
|
||||
|
||||
# 批量提交实验指南
|
||||
# Uni-Lab 批量提交实验指南
|
||||
|
||||
通过云端 API 批量提交实验（notebook），支持多轮实验参数配置。根据 workflow 模板详情和本地设备注册表自动生成 `node_params` 模板。
|
||||
通过 Uni-Lab 云端 API 批量提交实验（notebook），支持多轮实验参数配置。根据 workflow 模板详情和本地设备注册表自动生成 `node_params` 模板。
|
||||
|
||||
> **重要**：本指南中的 `Authorization: Lab <token>` 是 **Uni-Lab 平台专用的认证方式**，`Lab` 是 Uni-Lab 的 auth scheme 关键字，**不是** HTTP Basic 认证。请勿将其替换为 `Basic`。
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
@@ -18,25 +20,28 @@ description: Batch submit experiments (notebooks) to Uni-Lab platform — list w
|
||||
生成 AUTH token（任选一种方式）：
|
||||
|
||||
```bash
|
||||
# 方式一：Python 一行生成
|
||||
# 方式一：Python 一行生成（注意：scheme 是 "Lab" 不是 "Basic"）
|
||||
python -c "import base64,sys; print('Authorization: Lab ' + base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
|
||||
|
||||
# 方式二：手动计算
|
||||
# base64(ak:sk) → Authorization: Lab <token>
|
||||
# ⚠️ 这里的 "Lab" 是 Uni-Lab 平台的 auth scheme，绝对不能用 "Basic" 替代
|
||||
```
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
|-------------|------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| ------------ | ----------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-lab.bohrium.com` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
|
||||
确认后设置：
|
||||
|
||||
```bash
|
||||
BASE="<根据 addr 确定的 URL>"
|
||||
# ⚠️ Auth scheme 必须是 "Lab"（Uni-Lab 专用），不是 "Basic"
|
||||
AUTH="Authorization: Lab <上面命令输出的 token>"
|
||||
```
|
||||
|
||||
@@ -44,18 +49,19 @@ AUTH="Authorization: Lab <上面命令输出的 token>"
|
||||
|
||||
**批量提交实验时需要本地注册表来解析 workflow 节点的参数 schema。**
|
||||
|
||||
按优先级搜索：
|
||||
**必须先用 Glob 工具搜索文件**，不要直接猜测路径：
|
||||
|
||||
```
|
||||
<workspace 根目录>/unilabos_data/req_device_registry_upload.json
|
||||
<workspace 根目录>/req_device_registry_upload.json
|
||||
Glob: **/req_device_registry_upload.json
|
||||
```
|
||||
|
||||
也可直接 Glob 搜索：`**/req_device_registry_upload.json`
|
||||
常见位置（仅供参考，以 Glob 实际结果为准）：
|
||||
- `<workspace>/unilabos_data/req_device_registry_upload.json`
|
||||
- `<workspace>/req_device_registry_upload.json`
|
||||
|
||||
找到后**检查文件修改时间**并告知用户。超过 1 天提醒用户是否需要重新启动 `unilab`。
|
||||
|
||||
**如果文件不存在** → 告知用户先运行 `unilab` 启动命令，等注册表生成后再执行。可跳过此步，但将无法自动生成参数模板，需要用户手动填写 `param`。
|
||||
**如果 Glob 搜索无结果** → 告知用户先运行 `unilab` 启动命令，等注册表生成后再执行。可跳过此步，但将无法自动生成参数模板，需要用户手动填写 `param`。
|
||||
|
||||
### 4. workflow_uuid（目标工作流）
|
||||
|
||||
@@ -93,7 +99,7 @@ curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
返回：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
|
||||
{ "code": 0, "data": { "uuid": "xxx", "name": "实验室名称" } }
|
||||
```
|
||||
|
||||
记住 `data.uuid` 为 `lab_uuid`。
|
||||
@@ -104,9 +110,33 @@ curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
curl -s -X GET "$BASE/api/v1/lab/project/list?lab_uuid=$lab_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回项目列表，展示给用户选择。列出每个项目的 `uuid` 和 `name`。
|
||||
返回：
|
||||
|
||||
用户**必须**选择一个项目，记住 `project_uuid`，后续创建 notebook 时需要提供。
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"data": {
|
||||
"items": [
|
||||
{
|
||||
"uuid": "1b3f249a-...",
|
||||
"name": "bt",
|
||||
"description": null,
|
||||
"status": "active",
|
||||
"created_at": "2026-04-09T14:31:28+08:00"
|
||||
},
|
||||
{
|
||||
"uuid": "b6366243-...",
|
||||
"name": "default",
|
||||
"description": "默认项目",
|
||||
"status": "active",
|
||||
"created_at": "2026-03-26T11:13:36+08:00"
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
展示 `data.items[]` 中每个项目的 `name` 和 `uuid`，让用户选择。用户**必须**选择一个项目，记住 `project_uuid`（即选中项目的 `uuid`），后续创建 notebook 时需要提供。
|
||||
|
||||
### 3. 列出可用 workflow
|
||||
|
||||
@@ -123,6 +153,7 @@ curl -s -X GET "$BASE/api/v1/lab/workflow/template/detail/$workflow_uuid" -H "$A
|
||||
```
|
||||
|
||||
返回 workflow 的完整结构，包含所有 action 节点信息。需要从响应中提取：
|
||||
|
||||
- 每个 action 节点的 `node_uuid`
|
||||
- 每个节点对应的设备 ID（`resource_template_name`）
|
||||
- 每个节点的动作名（`node_template_name`）
|
||||
@@ -195,14 +226,14 @@ curl -s -X GET "$BASE/api/v1/lab/notebook/status?uuid=$notebook_uuid" -H "$AUTH"
|
||||
### 每轮的字段
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| -------------- | ------------- | ----------------------------------------- |
|
||||
| `sample_uuids` | array\<uuid\> | 该轮实验的样品 UUID 数组，无样品时传 `[]` |
|
||||
| `datas` | array | 该轮中每个 workflow 节点的参数配置 |
|
||||
|
||||
### datas 中每个节点
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| --------------- | ------ | -------------------------------------------- |
|
||||
| `node_uuid` | string | workflow 模板中的节点 UUID（从 API #4 获取） |
|
||||
| `param` | object | 动作参数（根据本地注册表 schema 填写） |
|
||||
| `sample_params` | array | 样品相关参数（液体名、体积等） |
|
||||
@@ -210,7 +241,7 @@ curl -s -X GET "$BASE/api/v1/lab/notebook/status?uuid=$notebook_uuid" -H "$AUTH"
|
||||
### sample_params 中每条
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| ---------------- | ------ | ---------------------------------------------------- |
|
||||
| `container_uuid` | string | 容器 UUID |
|
||||
| `sample_value` | object | 样品值，如 `{"liquid_names": "水", "volumes": 1000}` |
|
||||
|
||||
@@ -233,6 +264,7 @@ python scripts/gen_notebook_params.py \
|
||||
> 脚本位于本文档同级目录下的 `scripts/gen_notebook_params.py`。
|
||||
|
||||
脚本会：
|
||||
|
||||
1. 调用 workflow detail API 获取所有 action 节点
|
||||
2. 读取本地注册表，为每个节点查找对应的 action schema
|
||||
3. 生成 `notebook_template.json`，包含：
|
||||
@@ -270,8 +302,11 @@ python scripts/gen_notebook_params.py \
|
||||
"properties": {
|
||||
"goal": {
|
||||
"properties": {
|
||||
"asp_vols": {"type": "array", "items": {"type": "number"}},
|
||||
"sources": {"type": "array"}
|
||||
"asp_vols": {
|
||||
"type": "array",
|
||||
"items": { "type": "number" }
|
||||
},
|
||||
"sources": { "type": "array" }
|
||||
},
|
||||
"required": ["asp_vols", "sources"]
|
||||
}
|
||||
|
||||
@@ -7,7 +7,7 @@
|
||||
|
||||
选项:
|
||||
--auth <token> Lab token（base64(ak:sk) 的结果，不含 "Lab " 前缀）
|
||||
--base <url> API 基础 URL（如 https://uni-lab.test.bohrium.com）
|
||||
--base <url> API 基础 URL（如 https://leap-lab.test.bohrium.com）
|
||||
--workflow-uuid <uuid> 目标 workflow 的 UUID
|
||||
--registry <path> 本地注册表文件路径（默认自动搜索）
|
||||
--rounds <n> 实验轮次数（默认 1）
|
||||
@@ -17,7 +17,7 @@
|
||||
示例:
|
||||
python gen_notebook_params.py \\
|
||||
--auth YTFmZDlkNGUtxxxx \\
|
||||
--base https://uni-lab.test.bohrium.com \\
|
||||
--base https://leap-lab.test.bohrium.com \\
|
||||
--workflow-uuid abc-123-def \\
|
||||
--rounds 2
|
||||
"""
|
||||
|
||||
@@ -41,11 +41,11 @@ python ./scripts/gen_auth.py --config <config.py>
|
||||
决定 API 请求发往哪个服务器。从启动命令的 `--addr` 参数获取：
|
||||
|
||||
| `--addr` 值 | BASE URL |
|
||||
|-------------|----------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| -------------- | ----------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-lab.bohrium.com` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
| 其他自定义 URL | 直接使用该 URL |
|
||||
|
||||
#### 必备项 ③：req_device_registry_upload.json（设备注册表）
|
||||
@@ -55,7 +55,7 @@ python ./scripts/gen_auth.py --config <config.py>
|
||||
**推断 working_dir**（即 `unilabos_data` 所在目录）：
|
||||
|
||||
| 条件 | working_dir 取值 |
|
||||
|------|------------------|
|
||||
| -------------------- | -------------------------------------------------------- |
|
||||
| 传了 `--working_dir` | `<working_dir>/unilabos_data/`（若子目录已存在则直接用） |
|
||||
| 仅传了 `--config` | `<config 文件所在目录>/unilabos_data/` |
|
||||
| 都没传 | `<当前工作目录>/unilabos_data/` |
|
||||
@@ -84,24 +84,6 @@ python ./scripts/gen_auth.py --config <config.py>
|
||||
python ./scripts/extract_device_actions.py --registry <找到的文件路径>
|
||||
```
|
||||
|
||||
#### 完整示例
|
||||
|
||||
用户提供：
|
||||
|
||||
```
|
||||
--ak a1fd9d4e-xxxx-xxxx-xxxx-d9a69c09f0fd
|
||||
--sk 136ff5c6-xxxx-xxxx-xxxx-a03e301f827b
|
||||
--addr test
|
||||
--port 8003
|
||||
--disable_browser
|
||||
```
|
||||
|
||||
从中提取：
|
||||
- ✅ ak/sk → 运行 `gen_auth.py` 得到 `AUTH="Authorization: Lab YTFmZDlk..."`
|
||||
- ✅ addr=test → `BASE=https://uni-lab.test.bohrium.com`
|
||||
- ✅ 搜索 `unilabos_data/req_device_registry_upload.json` → 找到并确认时间
|
||||
- ✅ 用户指明目标设备 → 如 `liquid_handler.prcxi`
|
||||
|
||||
**四项全部就绪后才进入 Step 1。**
|
||||
|
||||
### Step 1 — 列出可用设备
|
||||
@@ -129,6 +111,7 @@ python ./scripts/extract_device_actions.py [--registry <path>] <device_id> ./ski
|
||||
脚本会显示设备的 Python 源码路径和类名，方便阅读源码了解参数含义。
|
||||
|
||||
每个 action 生成一个 JSON 文件，包含：
|
||||
|
||||
- `type` — 作为 API 调用的 `action_type`
|
||||
- `schema` — 完整 JSON Schema（含 `properties.goal.properties` 参数定义）
|
||||
- `goal` — goal 字段映射（含占位符 `$placeholder`）
|
||||
@@ -136,13 +119,14 @@ python ./scripts/extract_device_actions.py [--registry <path>] <device_id> ./ski
|
||||
|
||||
### Step 3 — 写 action-index.md
|
||||
|
||||
按模板为每个 action 写条目：
|
||||
按模板为每个 action 写条目（**必须包含 `action_type`**）：
|
||||
|
||||
```markdown
|
||||
### `<action_name>`
|
||||
|
||||
<用途描述（一句话）>
|
||||
|
||||
- **action_type**: `<从 actions/<name>.json 的 type 字段获取>`
|
||||
- **Schema**: [`actions/<filename>.json`](actions/<filename>.json)
|
||||
- **核心参数**: `param1`, `param2`（从 schema.required 获取）
|
||||
- **可选参数**: `param3`, `param4`
|
||||
@@ -150,6 +134,8 @@ python ./scripts/extract_device_actions.py [--registry <path>] <device_id> ./ski
|
||||
```
|
||||
|
||||
描述规则：
|
||||
|
||||
- **每个 action 必须标注 `action_type`**（从 JSON 的 `type` 字段读取），这是 API #9 调用时的必填参数，传错会导致任务永远卡住
|
||||
- 从 `schema.properties` 读参数列表（schema 已提升为 goal 内容）
|
||||
- 从 `schema.required` 区分核心/可选参数
|
||||
- 按功能分类（移液、枪头、外设等）
|
||||
@@ -165,6 +151,7 @@ python ./scripts/extract_device_actions.py [--registry <path>] <device_id> ./ski
|
||||
### Step 4 — 写 SKILL.md
|
||||
|
||||
直接复用 `unilab-device-api` 的 API 模板，修改：
|
||||
|
||||
- 设备名称
|
||||
- Action 数量
|
||||
- 目录列表
|
||||
@@ -172,42 +159,77 @@ python ./scripts/extract_device_actions.py [--registry <path>] <device_id> ./ski
|
||||
- **AUTH 头** — 使用 Step 0 中 `gen_auth.py` 生成的 `Authorization: Lab <token>`（不要硬编码 `Api` 类型的 key）
|
||||
- **Python 源码路径** — 在 SKILL.md 开头注明设备对应的源码文件，方便参考参数含义
|
||||
- **Slot 字段表** — 列出本设备哪些 action 的哪些字段需要填入 Slot（物料/设备/节点/类名）
|
||||
- **action_type 速查表** — 在 API #9 说明后面紧跟一个表格，列出每个 action 对应的 `action_type` 值（从 JSON `type` 字段提取），方便 agent 快速查找而无需打开 JSON 文件
|
||||
|
||||
API 模板结构：
|
||||
|
||||
```markdown
|
||||
## 设备信息
|
||||
|
||||
- device_id, Python 源码路径, 设备类名
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
- ak/sk → AUTH, --addr → BASE URL
|
||||
|
||||
## 请求约定
|
||||
|
||||
- Windows 平台必须用 curl.exe（非 PowerShell 的 curl 别名）
|
||||
|
||||
## Session State
|
||||
|
||||
- lab_uuid（通过 GET /edge/lab/info 直接获取，不要问用户）, device_name
|
||||
|
||||
## API Endpoints
|
||||
|
||||
# - #1 GET /edge/lab/info → 直接拿到 lab_uuid
|
||||
|
||||
# - #2 创建工作流 POST /lab/workflow/owner → 拼 URL 告知用户
|
||||
|
||||
# - #3 创建节点 POST /edge/workflow/node
|
||||
|
||||
# body: {workflow_uuid, resource_template_name: "<device_id>", node_template_name: "<action_name>"}
|
||||
|
||||
# - #4 删除节点 DELETE /lab/workflow/nodes
|
||||
|
||||
# - #5 更新节点参数 PATCH /lab/workflow/node
|
||||
|
||||
# - #6 查询节点 handles POST /lab/workflow/node-handles
|
||||
|
||||
# body: {node_uuids: ["uuid1","uuid2"]} → 返回各节点的 handle_uuid
|
||||
|
||||
# - #7 批量创建边 POST /lab/workflow/edges
|
||||
|
||||
# body: {edges: [{source_node_uuid, target_node_uuid, source_handle_uuid, target_handle_uuid}]}
|
||||
|
||||
# - #8 启动工作流 POST /lab/workflow/{uuid}/run
|
||||
# - #9 运行设备单动作 POST /lab/mcp/run/action
|
||||
|
||||
# - #9 运行设备单动作 POST /lab/mcp/run/action（⚠️ action_type 必须从 action-index.md 或 actions/<name>.json 的 type 字段获取，传错会导致任务永远卡住）
|
||||
|
||||
# - #10 查询任务状态 GET /lab/mcp/task/{task_uuid}
|
||||
|
||||
# - #11 运行工作流单节点 POST /lab/mcp/run/workflow/action
|
||||
|
||||
# - #12 获取资源树 GET /lab/material/download/{lab_uuid}
|
||||
|
||||
# - #13 获取工作流模板详情 GET /lab/workflow/template/detail/{workflow_uuid}
|
||||
|
||||
# 返回 workflow 完整结构：data.nodes[] 含每个节点的 uuid、name、param、device_name、handles
|
||||
|
||||
# - #14 按名称查询物料模板 GET /lab/material/template/by-name?lab_uuid=&name=
|
||||
|
||||
# 返回 res_template_uuid，用于 #15 创建物料时的必填字段
|
||||
|
||||
# - #15 创建物料节点 POST /edge/material/node
|
||||
|
||||
# body: {res_template_uuid(从#14获取), name(自定义), display_name, parent_uuid?(从#12获取), ...}
|
||||
|
||||
# - #16 更新物料节点 PUT /edge/material/node
|
||||
|
||||
# body: {uuid(从#12获取), display_name?, description?, init_param_data?, data?, ...}
|
||||
|
||||
## Placeholder Slot 填写规则
|
||||
|
||||
- unilabos_resources → ResourceSlot → {"id":"/path/name","name":"name","uuid":"xxx"}
|
||||
- unilabos_devices → DeviceSlot → "/parent/device" 路径字符串
|
||||
- unilabos_nodes → NodeSlot → "/parent/node" 路径字符串
|
||||
@@ -217,13 +239,15 @@ API 模板结构：
|
||||
- 列出本设备所有 Slot 字段、类型及含义
|
||||
|
||||
## 渐进加载策略
|
||||
|
||||
## 完整工作流 Checklist
|
||||
```
|
||||
|
||||
### Step 5 — 验证
|
||||
|
||||
检查文件完整性：
|
||||
- [ ] `SKILL.md` 包含 API endpoint（#1 获取 lab_uuid、#2-#7 工作流/节点/边、#8-#11 运行/查询、#12 资源树、#13 工作流模板详情）
|
||||
|
||||
- [ ] `SKILL.md` 包含 API endpoint（#1 获取 lab_uuid、#2-#7 工作流/节点/边、#8-#11 运行/查询、#12 资源树、#13 工作流模板详情、#14-#16 物料管理）
|
||||
- [ ] `SKILL.md` 包含 Placeholder Slot 填写规则（ResourceSlot / DeviceSlot / NodeSlot / ClassSlot / FormulationSlot + create_resource 特例）和本设备的 Slot 字段表
|
||||
- [ ] `action-index.md` 列出所有 action 并有描述
|
||||
- [ ] `actions/` 目录中每个 action 有对应 JSON 文件
|
||||
@@ -273,7 +297,7 @@ API 模板结构：
|
||||
`placeholder_keys` / `_unilabos_placeholder_info` 中有 5 种值，对应不同的填写方式：
|
||||
|
||||
| placeholder 值 | Slot 类型 | 填写格式 | 选取范围 |
|
||||
|---------------|-----------|---------|---------|
|
||||
| ---------------------- | --------------- | ----------------------------------------------------- | ----------------------------------------- |
|
||||
| `unilabos_resources` | ResourceSlot | `{"id": "/path/name", "name": "name", "uuid": "xxx"}` | 仅**物料**节点（不含设备） |
|
||||
| `unilabos_devices` | DeviceSlot | `"/parent/device_name"` | 仅**设备**节点（type=device），路径字符串 |
|
||||
| `unilabos_nodes` | NodeSlot | `"/parent/node_name"` | **设备 + 物料**，即所有节点，路径字符串 |
|
||||
@@ -284,80 +308,36 @@ API 模板结构：
|
||||
|
||||
最常见的类型。从资源树中选取**物料**节点（孔板、枪头盒、试剂槽等）：
|
||||
|
||||
```json
|
||||
{"id": "/workstation/container1", "name": "container1", "uuid": "ff149a9a-2cb8-419d-8db5-d3ba056fb3c2"}
|
||||
```
|
||||
- 单个：`{"id": "/workstation/container1", "name": "container1", "uuid": "ff149a9a-..."}`
|
||||
- 数组：`[{"id": "/path/a", "name": "a", "uuid": "xxx"}, ...]`
|
||||
- `id` 从 parent 计算的路径格式，根据 action 语义选择正确的物料
|
||||
|
||||
- 单个（schema type=object）：`{"id": "/path/name", "name": "name", "uuid": "xxx"}`
|
||||
- 数组（schema type=array）：`[{"id": "/path/a", "name": "a", "uuid": "xxx"}, ...]`
|
||||
- `id` 本身是从 parent 计算的路径格式
|
||||
- 根据 action 语义选择正确的物料（如 `sources` = 液体来源，`targets` = 目标位置）
|
||||
> **特例**：`create_resource` 的 `res_id`，目标物料可能尚不存在，直接填期望路径，不需要 uuid。
|
||||
|
||||
> **特例**：`create_resource` 的 `res_id` 字段，目标物料可能**尚不存在**，此时直接填写期望的路径（如 `"/workstation/container1"`），不需要 uuid。
|
||||
### DeviceSlot / NodeSlot / ClassSlot
|
||||
|
||||
### DeviceSlot（`unilabos_devices`）
|
||||
|
||||
填写**设备路径字符串**。从资源树中筛选 type=device 的节点，从 parent 计算路径：
|
||||
|
||||
```
|
||||
"/host_node"
|
||||
"/bioyond_cell/reaction_station"
|
||||
```
|
||||
|
||||
- 只填路径字符串，不需要 `{id, uuid}` 对象
|
||||
- 根据 action 语义选择正确的设备（如 `target_device_id` = 目标设备）
|
||||
|
||||
### NodeSlot（`unilabos_nodes`）
|
||||
|
||||
范围 = 设备 + 物料。即资源树中**所有节点**都可以选，填写**路径字符串**：
|
||||
|
||||
```
|
||||
"/PRCXI/PRCXI_Deck"
|
||||
```
|
||||
|
||||
- 使用场景：当参数既可能指向物料也可能指向设备时（如 `PumpTransferProtocol` 的 `from_vessel`/`to_vessel`，`create_resource` 的 `parent`）
|
||||
|
||||
### ClassSlot（`unilabos_class`）
|
||||
|
||||
填写注册表中已上报的**资源类 name**。从本地 `req_resource_registry_upload.json` 中查找：
|
||||
|
||||
```
|
||||
"container"
|
||||
```
|
||||
- **DeviceSlot**（`unilabos_devices`）：路径字符串如 `"/host_node"`，仅 type=device 的节点
|
||||
- **NodeSlot**（`unilabos_nodes`）：路径字符串如 `"/PRCXI/PRCXI_Deck"`，设备 + 物料均可选
|
||||
- **ClassSlot**（`unilabos_class`）：类名字符串如 `"container"`，从 `req_resource_registry_upload.json` 查找
|
||||
|
||||
### FormulationSlot（`unilabos_formulation`）
|
||||
|
||||
描述**液体配方**：向哪些物料容器中加入哪些液体及体积。填写为**对象数组**：
|
||||
描述**液体配方**：向哪些容器中加入哪些液体及体积。
|
||||
|
||||
```json
|
||||
[
|
||||
{
|
||||
"sample_uuid": "",
|
||||
"well_name": "YB_PrepBottle_15mL_Carrier_bottle_A1",
|
||||
"liquids": [
|
||||
{ "name": "LiPF6", "volume": 0.6 },
|
||||
{ "name": "DMC", "volume": 1.2 }
|
||||
]
|
||||
"well_name": "bottle_A1",
|
||||
"liquids": [{ "name": "LiPF6", "volume": 0.6 }]
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
#### 字段说明
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| `sample_uuid` | string | 样品 UUID，无样品时传空字符串 `""` |
|
||||
| `well_name` | string | 目标物料容器的 **name**（从资源树中取物料节点的 `name` 字段，如瓶子、孔位名称） |
|
||||
| `liquids` | array | 要加入的液体列表 |
|
||||
| `liquids[].name` | string | 液体名称（如试剂名、溶剂名） |
|
||||
| `liquids[].volume` | number | 液体体积（单位由设备决定，通常为 mL） |
|
||||
|
||||
#### 填写规则
|
||||
|
||||
- `well_name` 必须是资源树中已存在的物料节点 `name`（不是 `id` 路径），通过 API #12 获取资源树后筛选
|
||||
- 每个数组元素代表一个目标容器的配方
|
||||
- 一个容器可以加入多种液体（`liquids` 数组多条记录）
|
||||
- 与 ResourceSlot 的区别：ResourceSlot 填 `{id, name, uuid}` 指向物料本身；FormulationSlot 用 `well_name` 引用物料，并附带液体配方信息
|
||||
- `well_name` — 目标物料的 **name**（从资源树取，不是 `id` 路径）
|
||||
- `liquids[]` — 液体列表，每条含 `name`（试剂名）和 `volume`（体积，单位由上下文决定；pylabrobot 内部统一 uL）
|
||||
- `sample_uuid` — 样品 UUID，无样品传 `""`
|
||||
- 与 ResourceSlot 的区别：ResourceSlot 指向物料本身，FormulationSlot 引用物料名并附带配方信息
|
||||
|
||||
### 通过 API #12 获取资源树
|
||||
|
||||
@@ -365,7 +345,147 @@ API 模板结构：
|
||||
curl -s -X GET "$BASE/api/v1/lab/material/download/$lab_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
注意 `lab_uuid` 在路径中（不是查询参数）。资源树返回所有节点，每个节点包含 `id`（路径格式）、`name`、`uuid`、`type`、`parent` 等字段。填写 Slot 时需根据 placeholder 类型筛选正确的节点。
|
||||
注意 `lab_uuid` 在路径中（不是查询参数）。返回结构：
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"data": {
|
||||
"nodes": [
|
||||
{"name": "host_node", "uuid": "c3ec1e68-...", "type": "device", "parent": ""},
|
||||
{"name": "PRCXI", "uuid": "e249c9a6-...", "type": "device", "parent": ""},
|
||||
{"name": "PRCXI_Deck", "uuid": "fb6a8b71-...", "type": "deck", "parent": "PRCXI"}
|
||||
],
|
||||
"edges": [...]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
- `data.nodes[]` — 所有节点（设备 + 物料），每个节点含 `name`、`uuid`、`type`、`parent`
|
||||
- `type` 区分设备（`device`）和物料（`deck`、`container`、`resource` 等）
|
||||
- `parent` 为父节点名称（空字符串表示顶级）
|
||||
- 填写 Slot 时根据 placeholder 类型筛选：ResourceSlot 取非 device 节点，DeviceSlot 取 device 节点
|
||||
- 创建/更新物料时：`parent_uuid` 取父节点的 `uuid`，更新目标的 `uuid` 取节点自身的 `uuid`
|
||||
|
||||
## 物料管理 API
|
||||
|
||||
设备 Skill 除了设备动作外，还需支持物料节点的创建和参数设定，用于在资源树中动态管理物料。
|
||||
|
||||
典型流程：先通过 **#14 按名称查询模板** 获取 `res_template_uuid` → 再通过 **#15 创建物料** → 之后可通过 **#16 更新物料** 修改属性。更新时需要的 `uuid` 和 `parent_uuid` 均从 **#12 资源树下载** 获取。
|
||||
|
||||
### API #14 — 按名称查询物料模板
|
||||
|
||||
创建物料前，需要先获取物料模板的 UUID。通过模板名称查询：
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/material/template/by-name?lab_uuid=$lab_uuid&name=<template_name>" -H "$AUTH"
|
||||
```
|
||||
|
||||
| 参数 | 必填 | 说明 |
|
||||
| ---------- | ------ | -------------------------------- |
|
||||
| `lab_uuid` | **是** | 实验室 UUID（从 API #1 获取） |
|
||||
| `name` | **是** | 物料模板名称（如 `"container"`） |
|
||||
|
||||
返回 `code: 0` 时，**`data.uuid`** 即为 `res_template_uuid`，用于 API #15 创建物料。返回还包含 `name`、`resource_type`、`handles`、`config_infos` 等模板元信息。
|
||||
|
||||
模板不存在时返回 `code: 10002`，`data` 为空对象。模板名称来自资源注册表中已注册的资源类型。
|
||||
|
||||
### API #15 — 创建物料节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/edge/material/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '<request_body>'
|
||||
```
|
||||
|
||||
请求体：
|
||||
|
||||
```json
|
||||
{
|
||||
"res_template_uuid": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
|
||||
"name": "my_custom_bottle",
|
||||
"display_name": "自定义瓶子",
|
||||
"parent_uuid": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
|
||||
"type": "",
|
||||
"init_param_data": {},
|
||||
"schema": {},
|
||||
"data": {
|
||||
"liquids": [["water", 1000, "uL"]],
|
||||
"max_volume": 50000
|
||||
},
|
||||
"plate_well_datas": {},
|
||||
"plate_reagent_datas": {},
|
||||
"pose": {},
|
||||
"model": {}
|
||||
}
|
||||
```
|
||||
|
||||
| 字段 | 必填 | 类型 | 数据来源 | 说明 |
|
||||
| --------------------- | ------ | ------------- | ----------------------------------- | -------------------------------------- |
|
||||
| `res_template_uuid` | **是** | string (UUID) | **API #14** 按名称查询获取 | 物料模板 UUID |
|
||||
| `name` | 否 | string | **用户自定义** | 节点名称（标识符），可自由命名 |
|
||||
| `display_name` | 否 | string | 用户自定义 | 显示名称（UI 展示用） |
|
||||
| `parent_uuid` | 否 | string (UUID) | **API #12** 资源树中父节点的 `uuid` | 父节点，为空则创建顶级节点 |
|
||||
| `type` | 否 | string | 从模板继承 | 节点类型 |
|
||||
| `init_param_data` | 否 | object | 用户指定 | 初始化参数，覆盖模板默认值 |
|
||||
| `data` | 否 | object | 用户指定 | 节点数据，container 见下方 data 格式 |
|
||||
| `plate_well_datas` | 否 | object | 用户指定 | 孔板子节点数据（创建带孔位的板时使用） |
|
||||
| `plate_reagent_datas` | 否 | object | 用户指定 | 试剂关联数据 |
|
||||
| `schema` | 否 | object | 从模板继承 | 自定义 schema，不传则从模板继承 |
|
||||
| `pose` | 否 | object | 用户指定 | 位姿信息 |
|
||||
| `model` | 否 | object | 用户指定 | 3D 模型信息 |
|
||||
|
||||
#### container 的 `data` 格式
|
||||
|
||||
> **体积单位统一为 uL（微升）**。pylabrobot 体系中所有体积值（`max_volume`、`liquids` 中的 volume）均为 uL。外部如果是 mL 需乘 1000 转换。
|
||||
|
||||
```json
|
||||
{
|
||||
"liquids": [["water", 1000, "uL"], ["ethanol", 500, "uL"]],
|
||||
"max_volume": 50000
|
||||
}
|
||||
```
|
||||
|
||||
- `liquids` — 液体列表，每条为 `[液体名称, 体积(uL), 单位字符串]`
|
||||
- `max_volume` — 容器最大容量（uL），如 50 mL = 50000 uL
|
||||
|
||||
### API #16 — 更新物料节点
|
||||
|
||||
```bash
|
||||
curl -s -X PUT "$BASE/api/v1/edge/material/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '<request_body>'
|
||||
```
|
||||
|
||||
请求体：
|
||||
|
||||
```json
|
||||
{
|
||||
"uuid": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
|
||||
"parent_uuid": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
|
||||
"display_name": "新显示名称",
|
||||
"description": "新描述",
|
||||
"init_param_data": {},
|
||||
"data": {},
|
||||
"pose": {},
|
||||
"schema": {},
|
||||
"extra": {}
|
||||
}
|
||||
```
|
||||
|
||||
| 字段 | 必填 | 类型 | 数据来源 | 说明 |
|
||||
| ----------------- | ------ | ------------- | ------------------------------------- | ---------------- |
|
||||
| `uuid` | **是** | string (UUID) | **API #12** 资源树中目标节点的 `uuid` | 要更新的物料节点 |
|
||||
| `parent_uuid` | 否 | string (UUID) | API #12 资源树 | 移动到新父节点 |
|
||||
| `display_name` | 否 | string | 用户指定 | 更新显示名称 |
|
||||
| `description` | 否 | string | 用户指定 | 更新描述 |
|
||||
| `init_param_data` | 否 | object | 用户指定 | 更新初始化参数 |
|
||||
| `data` | 否 | object | 用户指定 | 更新节点数据 |
|
||||
| `pose` | 否 | object | 用户指定 | 更新位姿 |
|
||||
| `schema` | 否 | object | 用户指定 | 更新 schema |
|
||||
| `extra` | 否 | object | 用户指定 | 更新扩展数据 |
|
||||
|
||||
> 只传需要更新的字段，未传的字段保持不变。
|
||||
|
||||
## 最终目录结构
|
||||
|
||||
|
||||
450
.cursor/skills/filter-workflow-by-tags/SKILL.md
Normal file
450
.cursor/skills/filter-workflow-by-tags/SKILL.md
Normal file
@@ -0,0 +1,450 @@
|
||||
---
|
||||
name: filter-workflow-by-tags
|
||||
description: Query backend workflow list, aggregate all tags, and filter workflows by domain/scenario requirements using tags. Use when the user wants to search workflows, find workflows by tags, list available workflow tags, filter workflows by category/domain/scenario, or mentions 工作流筛选/标签查询/workflow tags/按领域查找工作流.
|
||||
---
|
||||
# Uni-Lab 工作流标签筛选指南
|
||||
|
||||
通过 Uni-Lab 云端 API 查询工作流列表，汇总所有可用标签（tags），并根据领域和场景要求筛选工作流。
|
||||
|
||||
> **重要**：本指南中的 `Authorization: Lab <token>` 是 **Uni-Lab 平台专用的认证方式**，`Lab` 是 Uni-Lab 的 auth scheme 关键字，**不是** HTTP Basic 认证。请勿将其替换为 `Basic`。
|
||||
|
||||
## 使用模式识别
|
||||
|
||||
**用户可能一开始就给出场景目标**（如"我要做有机合成实验"、"找柱层析相关的 protocol"）。此时：
|
||||
|
||||
1. **识别场景关键词** → 映射到可能的 tags（如 synthesis、organic、chromatography、purification）
|
||||
2. **直接执行完整流程**（获取 ak/sk/addr → 拉取所有工作流 → 汇总 tags → 按场景筛选）
|
||||
3. **展示筛选结果** → 引导用户从候选 workflow 中**选择明确的实验 protocol**
|
||||
4. **如果用户确认某个 workflow** → 记录 `workflow_uuid`，准备对接“与其他 Skill 的协作”
|
||||
|
||||
**如果用户未给场景目标**，则按标准 checklist 询问筛选条件。
|
||||
|
||||
---
|
||||
|
||||
## 前置条件
|
||||
|
||||
使用本指南前，**必须**先确认以下信息。如果缺少任何一项，**立即向用户询问并终止**，等补齐后再继续。
|
||||
|
||||
### 1. ak / sk → AUTH
|
||||
|
||||
询问用户的启动参数，从 `--ak` `--sk` 或 config.py 中获取。
|
||||
|
||||
生成 AUTH token：
|
||||
|
||||
```bash
|
||||
python -c "import base64,sys; print('Authorization: Lab ' + base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
|
||||
```
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
| ------------- | ------------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
|
||||
确认后设置：
|
||||
|
||||
```bash
|
||||
BASE="<根据 addr 确定的 URL>"
|
||||
AUTH="Authorization: Lab <上面命令输出的 token>"
|
||||
```
|
||||
|
||||
### 3. lab_uuid（实验室 UUID）
|
||||
|
||||
如果用户未提供 `lab_uuid`，通过以下 API 自动获取：
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回 `data.uuid` 即为 `lab_uuid`。
|
||||
|
||||
**三项全部就绪后才可开始。**
|
||||
|
||||
## Session State
|
||||
|
||||
在整个对话过程中，agent 需要记住以下状态：
|
||||
|
||||
- `lab_uuid` — 实验室 UUID
|
||||
- `all_workflows` — 完整工作流列表（分页获取后缓存到内存或临时文件）
|
||||
- `all_tags` — 所有工作流的标签汇总
|
||||
|
||||
---
|
||||
|
||||
## API 端点
|
||||
|
||||
### 查询工作流列表（支持分页）
|
||||
|
||||
```
|
||||
GET $BASE/api/v1/lab/workflow/owner/list?page=<page>&page_size=<page_size>&lab_uuid=$lab_uuid
|
||||
```
|
||||
|
||||
**参数：**
|
||||
|
||||
- `page` — 页码，从 1 开始
|
||||
- `page_size` — 每页数量，建议 1000
|
||||
- `lab_uuid` — 实验室 UUID
|
||||
|
||||
**返回结构：**
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"data": {
|
||||
"has_more": true,
|
||||
"data": [
|
||||
{
|
||||
"uuid": "9661bba2-1b9f-4687-a63d-910245df174b",
|
||||
"name": "Untitled",
|
||||
"description": "",
|
||||
"user_id": "114211",
|
||||
"published": false,
|
||||
"tags": null
|
||||
},
|
||||
{
|
||||
"uuid": "e0436638-190b-46bc-b1a1-2711d9602f6a",
|
||||
"name": "Synthesis v2",
|
||||
"user_id": "114211",
|
||||
"published": true,
|
||||
"tags": ["synthesis", "organic"]
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**字段说明：**
|
||||
|
||||
- `has_more` — 若为 `true`，需要继续请求 `page+1`
|
||||
- `tags` — 可能为 `null`、空数组或字符串数组；聚合时必须容忍 `null`
|
||||
|
||||
### 启动工作流（直接运行）
|
||||
|
||||
```
|
||||
POST $BASE/api/v1/lab/workflow/<workflow_uuid>/run
|
||||
```
|
||||
|
||||
**用途：** 直接启动一个 workflow 的默认执行（使用模板中预设的参数），无需创建 notebook。适用于快速测试或无参数变化的重复执行。
|
||||
|
||||
**请求体：** 空 JSON `{}` 或省略
|
||||
|
||||
**返回：**
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"data": "<run_uuid>"
|
||||
}
|
||||
```
|
||||
|
||||
- `run_uuid` — 本次执行的唯一标识（不是 notebook UUID）
|
||||
|
||||
**注意：**
|
||||
|
||||
- 该接口会使用 workflow 模板中保存的默认参数直接执行
|
||||
- 如果 workflow 需要动态参数（如 CSV 路径、样品 UUID），应使用 `POST /lab/notebook` 创建 notebook 并传入 `node_params`
|
||||
- 返回的 `run_uuid` 可直接传入下方「查询任务状态」接口查询实时进度
|
||||
|
||||
### 查询任务状态
|
||||
|
||||
```
|
||||
GET $BASE/api/v1/lab/mcp/task/<task_uuid>
|
||||
```
|
||||
|
||||
**用途：** 查询由 `POST /lab/workflow/<uuid>/run` 返回的 `run_uuid`（即 task_uuid）的实时执行状态，包括整体状态和每个节点（JOS：Job On Station）的执行详情。
|
||||
|
||||
**路径参数：**
|
||||
|
||||
- `task_uuid` — 等同于启动工作流接口返回的 `run_uuid`
|
||||
|
||||
**返回：**
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"data": {
|
||||
"status": "running",
|
||||
"jos_status": [
|
||||
{
|
||||
"uuid": "d0e24bfe-8d99-450e-b19d-f25849dfbaad",
|
||||
"node_name": "PRCXI_BioER_96_wellplate_slot_1",
|
||||
"action_name": "create_resource",
|
||||
"status": "success",
|
||||
"return_info": {
|
||||
"suc": true,
|
||||
"error": "",
|
||||
"return_value": { ... }
|
||||
}
|
||||
},
|
||||
{
|
||||
"uuid": "...",
|
||||
"node_name": "...",
|
||||
"action_name": "transfer_liquid",
|
||||
"status": "pending",
|
||||
"return_info": null
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**字段说明：**
|
||||
|
||||
- `data.status` — 整体任务状态
|
||||
- `running` — 正在执行（至少一个节点 pending 或 running）
|
||||
- `success` — 全部节点成功
|
||||
- `failed` — 有节点失败
|
||||
- `data.jos_status[]` — 节点级执行列表（按执行顺序）
|
||||
- `uuid` — 节点执行实例 UUID
|
||||
- `node_name` — 节点名称（资源/设备名或工位名）
|
||||
- `action_name` — 动作类型（`create_resource`、`transfer_liquid`、`centrifuge`、等）
|
||||
- `status` — 节点状态：`success`、`pending`、`running`、`failed`
|
||||
- `return_info` — 执行返回，失败时 `suc=false` 且 `error` 有错误信息
|
||||
|
||||
**注意：**
|
||||
|
||||
- 此接口的 `task_uuid` **是** `POST /lab/workflow/<uuid>/run` 返回的 `run_uuid`，二者为同一个 ID 的不同称呼
|
||||
- **不要**把 notebook UUID（`POST /lab/notebook` 返回）传进来——那条路径用 `GET /lab/notebook/status` 查询
|
||||
- `jos_status` 数组按节点执行顺序给出；从 pending 数量可以估算剩余进度
|
||||
- 返回体可能较大（`return_info.return_value` 中可能包含完整 resource tree），可在脚本中只提取 `status` + `node_name` + `action_name` 做摘要
|
||||
|
||||
**状态轮询示例：**
|
||||
|
||||
```bash
|
||||
# 每 5 秒轮询一次直至完成
|
||||
TASK="b183d97e-d2b5-4b24-b14b-820df04d87c0"
|
||||
while :; do
|
||||
st=$(curl -s -X GET "$BASE/api/v1/lab/mcp/task/$TASK" -H "$AUTH" \
|
||||
| python3 -c "import json,sys; d=json.load(sys.stdin)['data']; \
|
||||
print(d['status'], '|', sum(1 for j in d['jos_status'] if j['status']=='success'), '/', len(d['jos_status']))")
|
||||
echo "$(date +%H:%M:%S) $st"
|
||||
[[ "$st" == success* || "$st" == failed* ]] && break
|
||||
sleep 5
|
||||
done
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 完整工作流 Checklist
|
||||
|
||||
```
|
||||
Task Progress:
|
||||
- [ ] Step 0: 识别用户是否已给出场景目标（如"有机合成"、"柱层析"）
|
||||
- 若已给出 → 记录场景关键词，自动进入后续步骤
|
||||
- 若未给出 → 在 Step 6 询问用户
|
||||
- [ ] Step 1: 确认 ak/sk → 生成 AUTH token
|
||||
- [ ] Step 2: 确认 --addr → 设置 BASE URL
|
||||
- [ ] Step 3: GET /edge/lab/info → 获取 lab_uuid（如用户未提供）
|
||||
- [ ] Step 4: 分页获取所有工作流（从 page=1 开始直到 has_more=false）
|
||||
- [ ] Step 5: 汇总所有非空 tags → 生成 all_tags（去重、排序、附出现次数）
|
||||
- [ ] Step 6: 根据场景关键词（Step 0 或新询问）在 all_tags 中做语义映射 → 确定候选 tags
|
||||
- 若语义映射不唯一，列出候选 tags 让用户确认
|
||||
- [ ] Step 7: 按候选 tags 筛选工作流（默认 any 模式，召回优先）
|
||||
- [ ] Step 8: 展示筛选结果（uuid、name、description、tags、published）
|
||||
- [ ] Step 9: 引导用户从结果中选择**明确的实验 protocol**
|
||||
- 若结果只有 1 条 → 直接确认该 workflow_uuid
|
||||
- 若结果 2–10 条 → 让用户按编号选择
|
||||
- 若结果过多 → 提示收紧条件（加 tag、切换 all 模式、仅 published）
|
||||
- 若结果为空 → 放宽条件（去掉最稀有 tag）或提示用户换关键词
|
||||
- [ ] Step 10: 记录用户选中的 workflow_uuid，并提示提交实验或查看详情
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 推荐路径：使用脚本
|
||||
|
||||
同目录下提供 `scripts/filter_workflows.py`，一次完成分页抓取、标签聚合与筛选：
|
||||
|
||||
```bash
|
||||
# 1. 仅汇总标签（不筛选）
|
||||
python scripts/filter_workflows.py \
|
||||
--auth "<Lab base64token>" \
|
||||
--base "$BASE" \
|
||||
--lab-uuid "$lab_uuid" \
|
||||
--summary-only
|
||||
|
||||
# 2. 按标签筛选（ANY 模式：包含任一）
|
||||
python scripts/filter_workflows.py \
|
||||
--auth "<Lab base64token>" \
|
||||
--base "$BASE" \
|
||||
--lab-uuid "$lab_uuid" \
|
||||
--tags synthesis organic \
|
||||
--mode any
|
||||
|
||||
# 3. 按标签筛选（ALL 模式：必须同时包含）
|
||||
python scripts/filter_workflows.py \
|
||||
--auth "<Lab base64token>" \
|
||||
--base "$BASE" \
|
||||
--lab-uuid "$lab_uuid" \
|
||||
--tags synthesis organic \
|
||||
--mode all \
|
||||
--output filtered.json
|
||||
|
||||
# 4. 仅筛选已发布
|
||||
python scripts/filter_workflows.py \
|
||||
--auth "<Lab base64token>" \
|
||||
--base "$BASE" \
|
||||
--lab-uuid "$lab_uuid" \
|
||||
--tags synthesis \
|
||||
--published-only
|
||||
```
|
||||
|
||||
**`--auth` 参数说明**：传入 `Authorization` 头中 `Lab` 之后的 base64 token（不带 `Lab ` 前缀），脚本内部会自动补上 scheme。
|
||||
|
||||
**输出结构：**
|
||||
|
||||
```json
|
||||
{
|
||||
"total_workflows": 150,
|
||||
"tag_counts": {"synthesis": 12, "organic": 8, "analysis": 5},
|
||||
"all_tags": ["analysis", "organic", "synthesis"],
|
||||
"filter": {"tags": ["synthesis", "organic"], "mode": "any"},
|
||||
"filtered_workflows": [
|
||||
{"uuid": "...", "name": "...", "description": "...", "tags": [...], "published": true}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 手动路径：curl + jq
|
||||
|
||||
如果脚本不可用或环境缺少 Python，可用 shell 实现。
|
||||
|
||||
### 1. 分页抓取（写入 `all_workflows.json`）
|
||||
|
||||
```bash
|
||||
page=1
|
||||
echo "[]" > all_workflows.json
|
||||
|
||||
while :; do
|
||||
resp=$(curl -s -X GET \
|
||||
"$BASE/api/v1/lab/workflow/owner/list?page=$page&page_size=1000&lab_uuid=$lab_uuid" \
|
||||
-H "$AUTH")
|
||||
|
||||
page_data=$(echo "$resp" | jq -c '.data.data // []')
|
||||
jq -c --argjson p "$page_data" '. + $p' all_workflows.json > _tmp.json && mv _tmp.json all_workflows.json
|
||||
|
||||
has_more=$(echo "$resp" | jq -r '.data.has_more')
|
||||
[ "$has_more" != "true" ] && break
|
||||
page=$((page + 1))
|
||||
done
|
||||
|
||||
echo "Total: $(jq 'length' all_workflows.json)"
|
||||
```
|
||||
|
||||
### 2. 汇总所有标签（含出现次数）
|
||||
|
||||
```bash
|
||||
jq '[.[].tags // [] | .[]] | group_by(.) | map({tag: .[0], count: length}) | sort_by(-.count)' \
|
||||
all_workflows.json
|
||||
```
|
||||
|
||||
### 3. 按标签筛选
|
||||
|
||||
```bash
|
||||
# ANY：包含任一指定标签
|
||||
jq --argjson want '["synthesis","organic"]' \
|
||||
'[.[] | select((.tags // []) | any(. as $t | $want | index($t)))]' \
|
||||
all_workflows.json
|
||||
|
||||
# ALL：同时包含所有指定标签
|
||||
jq --argjson want '["synthesis","organic"]' \
|
||||
'[.[] | select(($want | all(. as $w | (.tags // []) | index($w))))]' \
|
||||
all_workflows.json
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 筛选策略
|
||||
|
||||
agent 拿到用户的「领域 + 场景」自然语言描述时，按如下顺序选择 tag：
|
||||
|
||||
1. **优先用户显式指定的 tags**：若用户明确给出标签词，直接精确匹配。
|
||||
2. **从 all_tags 中做语义映射**：若用户描述是自然语言（如"有机合成、柱层析"），在 all_tags 中找语义相关项（如 `synthesis`、`organic`、`chromatography`）。必要时展示候选 tag 让用户确认。
|
||||
3. **模式选择**：
|
||||
- 默认 `any`（更多召回），给出 tag 集合的并集匹配
|
||||
- 用户强调"必须同时满足"时用 `all`
|
||||
4. **空结果兜底**：如果筛选为空，放宽条件（去掉最稀有 tag、切换 any 模式），并提醒用户。
|
||||
|
||||
---
|
||||
|
||||
## 引导到明确的 Protocol
|
||||
|
||||
筛选完成后，**最终目标是让用户确认一个具体的 workflow_uuid**，而不是停留在"一堆候选"上。按结果数量采取不同策略：
|
||||
|
||||
| 结果数量 | 策略 |
|
||||
| --------- | ---------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| 0 条 | 放宽筛选（去掉最稀有 tag → 切换 any 模式 → 去掉 `--published-only`）。仍为空则提示换关键词，或列出 `all_tags` 让用户重新选。 |
|
||||
| 1 条 | 直接确认："找到唯一匹配：`<name>` (uuid `<uuid>`)，是否用它？"用户确认后记录 `workflow_uuid`。 |
|
||||
| 2–10 条 | 编号列表展示，让用户选编号。每项给出 name、tags、description 摘要、published 状态。 |
|
||||
| 10–30 条 | 先展示 tag 分布帮助用户进一步收紧：列出匹配结果中最常见的子标签，提示"加一个 tag 可将结果缩小到 N 条"。 |
|
||||
| >30 条 | 强制要求用户补充条件：仅 published、指定具体 tag 组合、或按名称关键词过滤。 |
|
||||
|
||||
**确认 workflow 后**：
|
||||
|
||||
1. 将 `workflow_uuid` 写入 session state
|
||||
2. 提示用户下一步可用的 skill：
|
||||
- 提交实验 → 引导到“与其他 Skill 的协作”
|
||||
- 查看 workflow 详细节点 → `GET /api/v1/lab/workflow/template/detail/<workflow_uuid>`
|
||||
3. 若用户想换一个，回到筛选步骤。
|
||||
|
||||
---
|
||||
|
||||
## 展示结果
|
||||
|
||||
推荐格式（表格 + 汇总统计）：
|
||||
|
||||
```
|
||||
共 150 个工作流，其中 32 个匹配筛选条件 [tags: synthesis OR organic]
|
||||
|
||||
| UUID (短) | 名称 | Tags | 已发布 |
|
||||
|-----------|--------------------------|------------------------------|--------|
|
||||
| e0436638 | Synthesis v2 | synthesis, organic | ✓ |
|
||||
| 5b60dbb8 | Grignard Protocol | synthesis, organometallic | ✓ |
|
||||
| ... | ... | ... | ... |
|
||||
|
||||
所有可用标签（按频次）：
|
||||
synthesis (12), organic (8), analysis (5), purification (4), ...
|
||||
```
|
||||
|
||||
如果用户下一步想执行某工作流 → 引导到“与其他 Skill 的协作”。
|
||||
|
||||
---
|
||||
|
||||
## 常见问题
|
||||
|
||||
### Q: tags 为 null 的工作流要不要展示？
|
||||
|
||||
默认**不展示**在筛选结果中（因为无法按 tag 匹配）。但在 `--summary-only` 或无筛选条件时，这些工作流仍会计入总数，并在输出中单独列出"未打标签"计数。
|
||||
|
||||
### Q: 如何按名称/描述做模糊匹配？
|
||||
|
||||
脚本未内置，但可在 jq 中组合：
|
||||
|
||||
```bash
|
||||
jq '[.[] | select((.name + " " + (.description // "")) | test("organic"; "i"))]' all_workflows.json
|
||||
```
|
||||
|
||||
### Q: `page_size=1000` 是否会被服务端限制？
|
||||
|
||||
接口通常允许最大 1000；如果返回量少于 1000 且 `has_more=false`，说明已到末页。极端情况下若服务端返回错误，可降到 200 或 500 再试。
|
||||
|
||||
### Q: 工作流数量极大（>10k）怎么办？
|
||||
|
||||
1. 先跑 `--summary-only` 了解 tag 分布
|
||||
2. 提示用户先限定 `--published-only` 或指定 tag
|
||||
3. 考虑将 `all_workflows.json` 缓存到本地，下次直接复用
|
||||
|
||||
---
|
||||
|
||||
## 与其他 Skill 的协作
|
||||
|
||||
- 正常情况下，找到 workflow 之后可以直接用它提交实验（启动工作流的 api 端点 POST $BASE/api/v1/lab/workflow/<workflow_uuid>/run，不用别的 skill）
|
||||
- **仅当需要进行多次实验时，使用 batch-submit-experiment** — 筛选到目标工作流后，`workflow_uuid` 直接用于实验提交
|
||||
|
||||
## 脚本依赖
|
||||
|
||||
`scripts/filter_workflows.py` 仅使用 Python 标准库（`urllib`、`json`、`argparse`），无需额外安装。
|
||||
191
.cursor/skills/filter-workflow-by-tags/scripts/filter_workflows.py
Executable file
191
.cursor/skills/filter-workflow-by-tags/scripts/filter_workflows.py
Executable file
@@ -0,0 +1,191 @@
|
||||
#!/usr/bin/env python3
|
||||
"""分页拉取 Uni-Lab 工作流列表，汇总 tags 并按 tag 筛选。
|
||||
|
||||
使用示例:
|
||||
python filter_workflows.py \
|
||||
--auth <base64token> \
|
||||
--base https://leap-lab.test.bohrium.com \
|
||||
--lab-uuid a9059772-... \
|
||||
--tags synthesis organic --mode any
|
||||
|
||||
仅依赖 Python 标准库。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.parse
|
||||
import urllib.request
|
||||
from collections import Counter
|
||||
|
||||
|
||||
def fetch_all_workflows(base: str, auth_token: str, lab_uuid: str, page_size: int = 1000) -> list[dict]:
|
||||
"""分页拉取所有 owner 工作流，直到 has_more=false。"""
|
||||
workflows: list[dict] = []
|
||||
page = 1
|
||||
while True:
|
||||
query = urllib.parse.urlencode(
|
||||
{"page": page, "page_size": page_size, "lab_uuid": lab_uuid}
|
||||
)
|
||||
url = f"{base.rstrip('/')}/api/v1/lab/workflow/owner/list?{query}"
|
||||
req = urllib.request.Request(
|
||||
url,
|
||||
headers={
|
||||
"Authorization": f"Lab {auth_token}",
|
||||
"Accept": "application/json",
|
||||
},
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=30) as resp:
|
||||
payload = json.loads(resp.read().decode("utf-8"))
|
||||
except urllib.error.HTTPError as e:
|
||||
sys.exit(f"[ERROR] HTTP {e.code} on page {page}: {e.read().decode('utf-8', 'ignore')}")
|
||||
except urllib.error.URLError as e:
|
||||
sys.exit(f"[ERROR] URL error on page {page}: {e.reason}")
|
||||
|
||||
if payload.get("code") != 0:
|
||||
sys.exit(f"[ERROR] API returned non-zero code: {payload}")
|
||||
|
||||
data = payload.get("data") or {}
|
||||
page_items = data.get("data") or []
|
||||
workflows.extend(page_items)
|
||||
|
||||
if not data.get("has_more"):
|
||||
break
|
||||
page += 1
|
||||
# 防御性兜底，避免接口异常导致无限循环
|
||||
if page > 1000:
|
||||
print(f"[WARN] page count exceeded 1000, stopping early", file=sys.stderr)
|
||||
break
|
||||
|
||||
return workflows
|
||||
|
||||
|
||||
def aggregate_tags(workflows: list[dict]) -> tuple[list[str], dict[str, int], int]:
|
||||
"""返回 (sorted_tags, tag_counts, untagged_count)。"""
|
||||
counter: Counter[str] = Counter()
|
||||
untagged = 0
|
||||
for wf in workflows:
|
||||
tags = wf.get("tags")
|
||||
if not tags:
|
||||
untagged += 1
|
||||
continue
|
||||
for t in tags:
|
||||
if isinstance(t, str) and t.strip():
|
||||
counter[t.strip()] += 1
|
||||
return sorted(counter.keys()), dict(counter), untagged
|
||||
|
||||
|
||||
def filter_workflows(
|
||||
workflows: list[dict],
|
||||
want_tags: list[str],
|
||||
mode: str,
|
||||
published_only: bool,
|
||||
) -> list[dict]:
|
||||
"""按 tag 筛选。mode 取值 any / all。"""
|
||||
want_set = {t.strip() for t in want_tags if t.strip()}
|
||||
out: list[dict] = []
|
||||
for wf in workflows:
|
||||
if published_only and not wf.get("published"):
|
||||
continue
|
||||
if not want_set:
|
||||
out.append(wf)
|
||||
continue
|
||||
tags = wf.get("tags") or []
|
||||
tag_set = {t for t in tags if isinstance(t, str)}
|
||||
if mode == "all":
|
||||
if want_set.issubset(tag_set):
|
||||
out.append(wf)
|
||||
else: # any
|
||||
if want_set & tag_set:
|
||||
out.append(wf)
|
||||
return out
|
||||
|
||||
|
||||
def project_workflow(wf: dict) -> dict:
|
||||
"""精简输出字段。"""
|
||||
return {
|
||||
"uuid": wf.get("uuid"),
|
||||
"name": wf.get("name"),
|
||||
"description": wf.get("description", ""),
|
||||
"tags": wf.get("tags") or [],
|
||||
"published": bool(wf.get("published")),
|
||||
"user_id": wf.get("user_id"),
|
||||
}
|
||||
|
||||
|
||||
def parse_args() -> argparse.Namespace:
|
||||
p = argparse.ArgumentParser(description="Fetch & filter Uni-Lab workflows by tags.")
|
||||
p.add_argument("--auth", required=True, help="Base64 token (the part after `Lab `).")
|
||||
p.add_argument("--base", required=True, help="Base URL, e.g. https://leap-lab.test.bohrium.com")
|
||||
p.add_argument("--lab-uuid", required=True, help="Lab UUID.")
|
||||
p.add_argument("--tags", nargs="*", default=[], help="Tags to filter by (space separated).")
|
||||
p.add_argument(
|
||||
"--mode",
|
||||
choices=["any", "all"],
|
||||
default="any",
|
||||
help="any: workflow contains at least one tag; all: workflow contains every tag.",
|
||||
)
|
||||
p.add_argument("--published-only", action="store_true", help="Only include published workflows.")
|
||||
p.add_argument("--page-size", type=int, default=1000, help="Page size, default 1000.")
|
||||
p.add_argument(
|
||||
"--summary-only",
|
||||
action="store_true",
|
||||
help="Print tag summary without applying filter (still fetches everything).",
|
||||
)
|
||||
p.add_argument("--output", help="Write JSON result to this path. If omitted, print to stdout.")
|
||||
return p.parse_args()
|
||||
|
||||
|
||||
def main() -> None:
|
||||
args = parse_args()
|
||||
workflows = fetch_all_workflows(
|
||||
base=args.base,
|
||||
auth_token=args.auth,
|
||||
lab_uuid=args.lab_uuid,
|
||||
page_size=args.page_size,
|
||||
)
|
||||
sorted_tags, tag_counts, untagged = aggregate_tags(workflows)
|
||||
|
||||
if args.summary_only:
|
||||
result = {
|
||||
"total_workflows": len(workflows),
|
||||
"untagged_count": untagged,
|
||||
"tag_counts": tag_counts,
|
||||
"all_tags": sorted_tags,
|
||||
}
|
||||
else:
|
||||
filtered = filter_workflows(
|
||||
workflows,
|
||||
want_tags=args.tags,
|
||||
mode=args.mode,
|
||||
published_only=args.published_only,
|
||||
)
|
||||
result = {
|
||||
"total_workflows": len(workflows),
|
||||
"untagged_count": untagged,
|
||||
"tag_counts": tag_counts,
|
||||
"all_tags": sorted_tags,
|
||||
"filter": {
|
||||
"tags": args.tags,
|
||||
"mode": args.mode,
|
||||
"published_only": args.published_only,
|
||||
},
|
||||
"matched_count": len(filtered),
|
||||
"filtered_workflows": [project_workflow(wf) for wf in filtered],
|
||||
}
|
||||
|
||||
payload = json.dumps(result, ensure_ascii=False, indent=2)
|
||||
if args.output:
|
||||
with open(args.output, "w", encoding="utf-8") as f:
|
||||
f.write(payload)
|
||||
print(f"Wrote {len(workflows)} workflows summary → {args.output}", file=sys.stderr)
|
||||
else:
|
||||
print(payload)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
251
.cursor/skills/host-node/SKILL.md
Normal file
251
.cursor/skills/host-node/SKILL.md
Normal file
@@ -0,0 +1,251 @@
|
||||
---
|
||||
name: host-node
|
||||
description: Operate Uni-Lab host node via REST API — create resources, test latency, test resource tree, manual confirm. Use when the user mentions host_node, creating resources, resource management, testing latency, or any host node operation.
|
||||
---
|
||||
|
||||
# Host Node API Skill
|
||||
|
||||
## 设备信息
|
||||
|
||||
- **device_id**: `host_node`
|
||||
- **Python 源码**: `unilabos/ros/nodes/presets/host_node.py`
|
||||
- **设备类**: `HostNode`
|
||||
- **动作数**: 4（`create_resource`, `test_latency`, `auto-test_resource`, `manual_confirm`）
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
使用本 skill 前，**必须**先确认以下信息。如果缺少任何一项，**立即向用户询问并终止**，等补齐后再继续。
|
||||
|
||||
### 1. ak / sk → AUTH
|
||||
|
||||
从启动参数 `--ak` `--sk` 或 config.py 中获取，生成 token：`base64(ak:sk)` → `Authorization: Lab <token>`
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
| ------------ | ----------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
|
||||
确认后设置：
|
||||
|
||||
```bash
|
||||
BASE="<根据 addr 确定的 URL>"
|
||||
AUTH="Authorization: Lab <token>"
|
||||
```
|
||||
|
||||
**两项全部就绪后才可发起 API 请求。**
|
||||
|
||||
## Session State
|
||||
|
||||
在整个对话过程中，agent 需要记住以下状态，避免重复询问用户：
|
||||
|
||||
- `lab_uuid` — 实验室 UUID（首次通过 API #1 自动获取，**不需要问用户**）
|
||||
- `device_name` — `host_node`
|
||||
|
||||
## 请求约定
|
||||
|
||||
所有请求使用 `curl -s`，POST/PATCH/DELETE 需加 `Content-Type: application/json`。
|
||||
|
||||
> **Windows 平台**必须使用 `curl.exe`（而非 PowerShell 的 `curl` 别名）。
|
||||
|
||||
---
|
||||
|
||||
## API Endpoints
|
||||
|
||||
### 1. 获取实验室信息（自动获取 lab_uuid）
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回 `data.uuid` 为 `lab_uuid`，`data.name` 为 `lab_name`。
|
||||
|
||||
### 2. 创建工作流
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/owner" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"name":"<名称>","lab_uuid":"<lab_uuid>","description":"<描述>"}'
|
||||
```
|
||||
|
||||
返回 `data.uuid` 为 `workflow_uuid`。创建成功后告知用户链接：`$BASE/laboratory/$lab_uuid/workflow/$workflow_uuid`
|
||||
|
||||
### 3. 创建节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/edge/workflow/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"workflow_uuid":"<workflow_uuid>","resource_template_name":"host_node","node_template_name":"<action_name>"}'
|
||||
```
|
||||
|
||||
- `resource_template_name` 固定为 `host_node`
|
||||
- `node_template_name` — action 名称（如 `create_resource`, `test_latency`）
|
||||
|
||||
### 4. 删除节点
|
||||
|
||||
```bash
|
||||
curl -s -X DELETE "$BASE/api/v1/lab/workflow/nodes" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"node_uuids":["<uuid1>"],"workflow_uuid":"<workflow_uuid>"}'
|
||||
```
|
||||
|
||||
### 5. 更新节点参数
|
||||
|
||||
```bash
|
||||
curl -s -X PATCH "$BASE/api/v1/lab/workflow/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"workflow_uuid":"<wf_uuid>","uuid":"<node_uuid>","param":{...}}'
|
||||
```
|
||||
|
||||
`param` 直接使用创建节点返回的 `data.param` 结构，修改需要填入的字段值。参考 [action-index.md](action-index.md) 确定哪些字段是 Slot。
|
||||
|
||||
### 6. 查询节点 handles
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/node-handles" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"node_uuids":["<node_uuid_1>","<node_uuid_2>"]}'
|
||||
```
|
||||
|
||||
### 7. 批量创建边
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/edges" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"edges":[{"source_node_uuid":"<uuid>","target_node_uuid":"<uuid>","source_handle_uuid":"<uuid>","target_handle_uuid":"<uuid>"}]}'
|
||||
```
|
||||
|
||||
### 8. 启动工作流
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/<workflow_uuid>/run" -H "$AUTH"
|
||||
```
|
||||
|
||||
### 9. 运行设备单动作
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/mcp/run/action" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"lab_uuid":"<lab_uuid>","device_id":"host_node","action":"<action_name>","action_type":"<type>","param":{...}}'
|
||||
```
|
||||
|
||||
`param` 直接放 goal 里的属性，**不要**再包一层 `{"goal": {...}}`。
|
||||
|
||||
> **WARNING: `action_type` 必须正确，传错会导致任务永远卡住无法完成。** 从下表或 `actions/<name>.json` 的 `type` 字段获取。
|
||||
|
||||
#### action_type 速查表
|
||||
|
||||
| action | action_type |
|
||||
|--------|-------------|
|
||||
| `test_latency` | `UniLabJsonCommand` |
|
||||
| `create_resource` | `ResourceCreateFromOuterEasy` |
|
||||
| `auto-test_resource` | `UniLabJsonCommand` |
|
||||
| `manual_confirm` | `UniLabJsonCommand` |
|
||||
|
||||
### 10. 查询任务状态
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/mcp/task/<task_uuid>" -H "$AUTH"
|
||||
```
|
||||
|
||||
### 11. 运行工作流单节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/mcp/run/workflow/action" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"node_uuid":"<node_uuid>"}'
|
||||
```
|
||||
|
||||
### 12. 获取资源树（物料信息）
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/material/download/$lab_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
注意 `lab_uuid` 在路径中。返回 `data.nodes[]` 含所有节点（设备 + 物料），每个节点含 `name`、`uuid`、`type`、`parent`。
|
||||
|
||||
### 13. 获取工作流模板详情
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/workflow/template/detail/$workflow_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
> 必须使用 `/lab/workflow/template/detail/{uuid}`，其他路径会返回 404。
|
||||
|
||||
### 14. 按名称查询物料模板
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/material/template/by-name?lab_uuid=$lab_uuid&name=<template_name>" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回 `data.uuid` 为 `res_template_uuid`，用于 API #15。
|
||||
|
||||
### 15. 创建物料节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/edge/material/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"res_template_uuid":"<uuid>","name":"<名称>","display_name":"<显示名>","parent_uuid":"<父节点uuid>","data":{...}}'
|
||||
```
|
||||
|
||||
### 16. 更新物料节点
|
||||
|
||||
```bash
|
||||
curl -s -X PUT "$BASE/api/v1/edge/material/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"uuid":"<节点uuid>","display_name":"<新名称>","data":{...}}'
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Placeholder Slot 填写规则
|
||||
|
||||
| `placeholder_keys` 值 | Slot 类型 | 填写格式 | 选取范围 |
|
||||
| --------------------- | ------------ | ----------------------------------------------------- | ---------------------- |
|
||||
| `unilabos_resources` | ResourceSlot | `{"id": "/path/name", "name": "name", "uuid": "xxx"}` | 仅物料节点（非设备） |
|
||||
| `unilabos_devices` | DeviceSlot | `"/parent/device_name"` | 仅设备节点（type=device） |
|
||||
| `unilabos_nodes` | NodeSlot | `"/parent/node_name"` | 所有节点（设备 + 物料） |
|
||||
| `unilabos_class` | ClassSlot | `"class_name"` | 注册表中已注册的资源类 |
|
||||
|
||||
### host_node 设备的 Slot 字段表
|
||||
|
||||
| Action | 字段 | Slot 类型 | 说明 |
|
||||
| ----------------- | ----------- | ------------ | ------------------------------ |
|
||||
| `create_resource` | `res_id` | ResourceSlot | 新资源路径（可填不存在的路径） |
|
||||
| `create_resource` | `device_id` | DeviceSlot | 归属设备 |
|
||||
| `create_resource` | `parent` | NodeSlot | 父节点路径 |
|
||||
| `create_resource` | `class_name`| ClassSlot | 资源类名如 `"container"` |
|
||||
| `auto-test_resource` | `resource` | ResourceSlot | 单个测试物料 |
|
||||
| `auto-test_resource` | `resources` | ResourceSlot | 测试物料数组 |
|
||||
| `auto-test_resource` | `device` | DeviceSlot | 测试设备 |
|
||||
| `auto-test_resource` | `devices` | DeviceSlot | 测试设备 |
|
||||
|
||||
---
|
||||
|
||||
## 渐进加载策略
|
||||
|
||||
1. **SKILL.md**（本文件）— API 端点 + session state 管理
|
||||
2. **[action-index.md](action-index.md)** — 按分类浏览 4 个动作的描述和核心参数
|
||||
3. **[actions/\<name\>.json](actions/)** — 仅在需要构建具体请求时，加载对应 action 的完整 JSON Schema
|
||||
|
||||
---
|
||||
|
||||
## 完整工作流 Checklist
|
||||
|
||||
```
|
||||
Task Progress:
|
||||
- [ ] Step 1: GET /edge/lab/info 获取 lab_uuid
|
||||
- [ ] Step 2: 获取资源树 (GET #12) → 记住可用物料
|
||||
- [ ] Step 3: 读 action-index.md 确定要用的 action 名
|
||||
- [ ] Step 4: 创建工作流 (POST #2) → 记住 workflow_uuid，告知用户链接
|
||||
- [ ] Step 5: 创建节点 (POST #3, resource_template_name=host_node) → 记住 node_uuid + data.param
|
||||
- [ ] Step 6: 根据 _unilabos_placeholder_info 和资源树，填写 data.param 中的 Slot 字段
|
||||
- [ ] Step 7: 更新节点参数 (PATCH #5)
|
||||
- [ ] Step 8: 查询节点 handles (POST #6) → 获取各节点的 handle_uuid
|
||||
- [ ] Step 9: 批量创建边 (POST #7) → 用 handle_uuid 连接节点
|
||||
- [ ] Step 10: 启动工作流 (POST #8) 或运行单节点 (POST #11)
|
||||
- [ ] Step 11: 查询任务状态 (GET #10) 确认完成
|
||||
```
|
||||
58
.cursor/skills/host-node/action-index.md
Normal file
58
.cursor/skills/host-node/action-index.md
Normal file
@@ -0,0 +1,58 @@
|
||||
# Action Index — host_node
|
||||
|
||||
4 个动作，按功能分类。每个动作的完整 JSON Schema 在 `actions/<name>.json`。
|
||||
|
||||
---
|
||||
|
||||
## 资源管理
|
||||
|
||||
### `create_resource`
|
||||
|
||||
在资源树中创建新资源（容器、物料等），支持指定位置、类型和初始液体
|
||||
|
||||
- **action_type**: `ResourceCreateFromOuterEasy`
|
||||
- **Schema**: [`actions/create_resource.json`](actions/create_resource.json)
|
||||
- **可选参数**: `res_id`, `device_id`, `class_name`, `parent`, `bind_locations`, `liquid_input_slot`, `liquid_type`, `liquid_volume`, `slot_on_deck`
|
||||
- **占位符字段**:
|
||||
- `res_id` — **ResourceSlot**（特例：目标物料可能尚不存在，直接填期望路径）
|
||||
- `device_id` — **DeviceSlot**，填路径字符串如 `"/host_node"`
|
||||
- `parent` — **NodeSlot**，填路径字符串如 `"/workstation/deck"`
|
||||
- `class_name` — **ClassSlot**，填类名如 `"container"`
|
||||
|
||||
### `auto-test_resource`
|
||||
|
||||
测试资源系统，返回当前资源树和设备列表
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/test_resource.json`](actions/test_resource.json)
|
||||
- **可选参数**: `resource`, `resources`, `device`, `devices`
|
||||
- **占位符字段**:
|
||||
- `resource` — **ResourceSlot**，单个物料节点 `{id, name, uuid}`
|
||||
- `resources` — **ResourceSlot**，物料节点数组 `[{id, name, uuid}, ...]`
|
||||
- `device` — **DeviceSlot**，设备路径字符串
|
||||
- `devices` — **DeviceSlot**，设备路径字符串
|
||||
|
||||
---
|
||||
|
||||
## 系统工具
|
||||
|
||||
### `test_latency`
|
||||
|
||||
测试设备通信延迟，返回 RTT、时间差、任务延迟等指标
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/test_latency.json`](actions/test_latency.json)
|
||||
- **参数**: 无（零参数调用）
|
||||
|
||||
---
|
||||
|
||||
## 人工确认
|
||||
|
||||
### `manual_confirm`
|
||||
|
||||
创建人工确认节点，等待用户手动确认后继续
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/manual_confirm.json`](actions/manual_confirm.json)
|
||||
- **核心参数**: `timeout_seconds`（超时时间，秒）, `assignee_user_ids`（指派用户 ID 列表）
|
||||
- **占位符字段**: `assignee_user_ids` — `unilabos_manual_confirm` 类型
|
||||
93
.cursor/skills/host-node/actions/create_resource.json
Normal file
93
.cursor/skills/host-node/actions/create_resource.json
Normal file
@@ -0,0 +1,93 @@
|
||||
{
|
||||
"type": "ResourceCreateFromOuterEasy",
|
||||
"goal": {
|
||||
"res_id": "res_id",
|
||||
"class_name": "class_name",
|
||||
"parent": "parent",
|
||||
"device_id": "device_id",
|
||||
"bind_locations": "bind_locations",
|
||||
"liquid_input_slot": "liquid_input_slot[]",
|
||||
"liquid_type": "liquid_type[]",
|
||||
"liquid_volume": "liquid_volume[]",
|
||||
"slot_on_deck": "slot_on_deck"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"res_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"device_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"class_name": {
|
||||
"type": "string"
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"bind_locations": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "bind_locations",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"liquid_input_slot": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "integer"
|
||||
}
|
||||
},
|
||||
"liquid_type": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"liquid_volume": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "number"
|
||||
}
|
||||
},
|
||||
"slot_on_deck": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"required": [],
|
||||
"_unilabos_placeholder_info": {
|
||||
"res_id": "unilabos_resources",
|
||||
"device_id": "unilabos_devices",
|
||||
"parent": "unilabos_nodes",
|
||||
"class_name": "unilabos_class"
|
||||
}
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {
|
||||
"res_id": "unilabos_resources",
|
||||
"device_id": "unilabos_devices",
|
||||
"parent": "unilabos_nodes",
|
||||
"class_name": "unilabos_class"
|
||||
}
|
||||
}
|
||||
32
.cursor/skills/host-node/actions/manual_confirm.json
Normal file
32
.cursor/skills/host-node/actions/manual_confirm.json
Normal file
@@ -0,0 +1,32 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"timeout_seconds": "timeout_seconds",
|
||||
"assignee_user_ids": "assignee_user_ids"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"timeout_seconds": {
|
||||
"type": "integer"
|
||||
},
|
||||
"assignee_user_ids": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"timeout_seconds",
|
||||
"assignee_user_ids"
|
||||
],
|
||||
"_unilabos_placeholder_info": {
|
||||
"assignee_user_ids": "unilabos_manual_confirm"
|
||||
}
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {
|
||||
"assignee_user_ids": "unilabos_manual_confirm"
|
||||
}
|
||||
}
|
||||
11
.cursor/skills/host-node/actions/test_latency.json
Normal file
11
.cursor/skills/host-node/actions/test_latency.json
Normal file
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {},
|
||||
"required": []
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {}
|
||||
}
|
||||
255
.cursor/skills/host-node/actions/test_resource.json
Normal file
255
.cursor/skills/host-node/actions/test_resource.json
Normal file
@@ -0,0 +1,255 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"resource": "resource",
|
||||
"resources": "resources",
|
||||
"device": "device",
|
||||
"devices": "devices"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"resource": {
|
||||
"type": "object",
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string"
|
||||
},
|
||||
"name": {
|
||||
"type": "string"
|
||||
},
|
||||
"sample_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"children": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
},
|
||||
"category": {
|
||||
"type": "string"
|
||||
},
|
||||
"pose": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"position": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "position",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"orientation": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"w": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z",
|
||||
"w"
|
||||
],
|
||||
"title": "orientation",
|
||||
"additionalProperties": false
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"position",
|
||||
"orientation"
|
||||
],
|
||||
"title": "pose",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"config": {
|
||||
"type": "string"
|
||||
},
|
||||
"data": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"title": "resource"
|
||||
},
|
||||
"resources": {
|
||||
"items": {
|
||||
"type": "object",
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string"
|
||||
},
|
||||
"name": {
|
||||
"type": "string"
|
||||
},
|
||||
"sample_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"children": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
},
|
||||
"category": {
|
||||
"type": "string"
|
||||
},
|
||||
"pose": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"position": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "position",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"orientation": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"w": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z",
|
||||
"w"
|
||||
],
|
||||
"title": "orientation",
|
||||
"additionalProperties": false
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"position",
|
||||
"orientation"
|
||||
],
|
||||
"title": "pose",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"config": {
|
||||
"type": "string"
|
||||
},
|
||||
"data": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"title": "resources"
|
||||
},
|
||||
"type": "array"
|
||||
},
|
||||
"device": {
|
||||
"type": "string",
|
||||
"description": "device reference"
|
||||
},
|
||||
"devices": {
|
||||
"type": "string",
|
||||
"description": "device reference"
|
||||
}
|
||||
},
|
||||
"required": [],
|
||||
"_unilabos_placeholder_info": {
|
||||
"resource": "unilabos_resources",
|
||||
"resources": "unilabos_resources",
|
||||
"device": "unilabos_devices",
|
||||
"devices": "unilabos_devices"
|
||||
}
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {
|
||||
"resource": "unilabos_resources",
|
||||
"resources": "unilabos_resources",
|
||||
"device": "unilabos_devices",
|
||||
"devices": "unilabos_devices"
|
||||
}
|
||||
}
|
||||
@@ -1,11 +1,13 @@
|
||||
---
|
||||
name: submit-agent-result
|
||||
description: Submit historical experiment results (agent_result) to Uni-Lab notebook — read data files, assemble JSON payload, PUT to cloud API. Use when the user wants to submit experiment results, upload agent results, report experiment data, or mentions agent_result/实验结果/历史记录/notebook结果.
|
||||
description: Submit historical experiment results (agent_result) to Uni-Lab cloud platform (leap-lab) notebook — read data files, assemble JSON payload, PUT to cloud API. Use when the user wants to submit experiment results, upload agent results, report experiment data, or mentions agent_result/实验结果/历史记录/notebook结果.
|
||||
---
|
||||
|
||||
# 提交历史实验记录指南
|
||||
# Uni-Lab 提交历史实验记录指南
|
||||
|
||||
通过云端 API 向已创建的 notebook 提交实验结果数据（agent_result）。支持从 JSON / CSV 文件读取数据，整合后提交。
|
||||
通过 Uni-Lab 云端 API 向已创建的 notebook 提交实验结果数据（agent_result）。支持从 JSON / CSV 文件读取数据，整合后提交。
|
||||
|
||||
> **重要**：本指南中的 `Authorization: Lab <token>` 是 **Uni-Lab 平台专用的认证方式**，`Lab` 是 Uni-Lab 的 auth scheme 关键字，**不是** HTTP Basic 认证。请勿将其替换为 `Basic`。
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
@@ -18,23 +20,26 @@ description: Submit historical experiment results (agent_result) to Uni-Lab note
|
||||
生成 AUTH token：
|
||||
|
||||
```bash
|
||||
# ⚠️ 注意：scheme 是 "Lab"（Uni-Lab 专用），不是 "Basic"
|
||||
python -c "import base64,sys; print(base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
|
||||
```
|
||||
|
||||
输出即为 token 值，拼接为 `Authorization: Lab <token>`。
|
||||
输出即为 token 值，拼接为 `Authorization: Lab <token>`（`Lab` 是 Uni-Lab 平台 auth scheme，不可替换为 `Basic`）。
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
|-------------|------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| ------------ | ----------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-lab.bohrium.com` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
|
||||
确认后设置：
|
||||
|
||||
```bash
|
||||
BASE="<根据 addr 确定的 URL>"
|
||||
# ⚠️ Auth scheme 必须是 "Lab"（Uni-Lab 专用），不是 "Basic"
|
||||
AUTH="Authorization: Lab <上面命令输出的 token>"
|
||||
```
|
||||
|
||||
@@ -45,6 +50,7 @@ AUTH="Authorization: Lab <上面命令输出的 token>"
|
||||
notebook_uuid 来自之前通过「批量提交实验」创建的实验批次，即 `POST /api/v1/lab/notebook` 返回的 `data.uuid`。
|
||||
|
||||
如果用户不记得，可提示：
|
||||
|
||||
- 查看之前的对话记录中创建 notebook 时返回的 UUID
|
||||
- 或通过平台页面查找对应的 notebook
|
||||
|
||||
@@ -55,7 +61,7 @@ notebook_uuid 来自之前通过「批量提交实验」创建的实验批次，
|
||||
用户需要提供实验结果数据，支持以下方式：
|
||||
|
||||
| 方式 | 说明 |
|
||||
|------|------|
|
||||
| --------- | ----------------------------------------------- |
|
||||
| JSON 文件 | 直接作为 `agent_result` 的内容合并 |
|
||||
| CSV 文件 | 转为 `{"文件名": [行数据...]}` 格式 |
|
||||
| 手动指定 | 用户直接告知 key-value 数据，由 agent 构建 JSON |
|
||||
@@ -90,7 +96,7 @@ curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
返回：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
|
||||
{ "code": 0, "data": { "uuid": "xxx", "name": "实验室名称" } }
|
||||
```
|
||||
|
||||
记住 `data.uuid` 为 `lab_uuid`。
|
||||
@@ -122,7 +128,7 @@ curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
|
||||
#### 必要字段
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| --------------- | ------------- | ------------------------------------------- |
|
||||
| `notebook_uuid` | string (UUID) | 目标 notebook 的 UUID，从批量提交实验时获取 |
|
||||
| `agent_result` | object | 实验结果数据，任意 JSON 对象 |
|
||||
|
||||
@@ -131,6 +137,7 @@ curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
|
||||
`agent_result` 接受**任意 JSON 对象**，常见格式：
|
||||
|
||||
**简单键值对**：
|
||||
|
||||
```json
|
||||
{
|
||||
"avg_rtt_ms": 12.5,
|
||||
@@ -140,22 +147,24 @@ curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
|
||||
```
|
||||
|
||||
**包含嵌套结构**：
|
||||
|
||||
```json
|
||||
{
|
||||
"summary": {"total": 100, "passed": 98, "failed": 2},
|
||||
"summary": { "total": 100, "passed": 98, "failed": 2 },
|
||||
"measurements": [
|
||||
{"sample_id": "S001", "value": 3.14, "unit": "mg/mL"},
|
||||
{"sample_id": "S002", "value": 2.71, "unit": "mg/mL"}
|
||||
{ "sample_id": "S001", "value": 3.14, "unit": "mg/mL" },
|
||||
{ "sample_id": "S002", "value": 2.71, "unit": "mg/mL" }
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**从 CSV 文件导入**（脚本自动转换）：
|
||||
|
||||
```json
|
||||
{
|
||||
"experiment_data": [
|
||||
{"温度": 25, "压力": 101.3, "产率": 0.85},
|
||||
{"温度": 30, "压力": 101.3, "产率": 0.91}
|
||||
{ "温度": 25, "压力": 101.3, "产率": 0.85 },
|
||||
{ "温度": 30, "压力": 101.3, "产率": 0.91 }
|
||||
]
|
||||
}
|
||||
```
|
||||
@@ -179,7 +188,7 @@ python scripts/prepare_agent_result.py \
|
||||
```
|
||||
|
||||
| 参数 | 必选 | 说明 |
|
||||
|------|------|------|
|
||||
| ----------------- | ---------- | ----------------------------------------------- |
|
||||
| `--notebook-uuid` | 是 | 目标 notebook UUID |
|
||||
| `--files` | 是 | 输入文件路径（支持多个，JSON / CSV） |
|
||||
| `--auth` | 提交时必选 | Lab token（base64(ak:sk)） |
|
||||
@@ -190,7 +199,7 @@ python scripts/prepare_agent_result.py \
|
||||
### 文件合并规则
|
||||
|
||||
| 文件类型 | 合并方式 |
|
||||
|----------|----------|
|
||||
| --------------------- | -------------------------------------------- |
|
||||
| `.json`（dict） | 字段直接合并到 `agent_result` 顶层 |
|
||||
| `.json`（list/other） | 以文件名为 key 放入 `agent_result` |
|
||||
| `.csv` | 以文件名（不含扩展名）为 key，值为行对象数组 |
|
||||
@@ -210,7 +219,7 @@ python scripts/prepare_agent_result.py \
|
||||
--notebook-uuid 73c67dca-c8cc-4936-85a0-329106aa7cca \
|
||||
--files results.json \
|
||||
--auth YTFmZDlkNGUt... \
|
||||
--base https://uni-lab.test.bohrium.com \
|
||||
--base https://leap-lab.test.bohrium.com \
|
||||
--submit
|
||||
```
|
||||
|
||||
@@ -272,4 +281,4 @@ Task Progress:
|
||||
|
||||
### Q: 认证方式是 Lab 还是 Api？
|
||||
|
||||
本指南统一使用 `Authorization: Lab <base64(ak:sk)>` 方式。如果用户有独立的 API Key，也可用 `Authorization: Api <key>` 替代。
|
||||
本指南统一使用 `Authorization: Lab <base64(ak:sk)>` 方式（`Lab` 是 Uni-Lab 平台的 auth scheme，**绝不能用 `Basic` 替代**）。如果用户有独立的 API Key，也可用 `Authorization: Api <key>` 替代。
|
||||
|
||||
282
.cursor/skills/virtual-workbench/SKILL.md
Normal file
282
.cursor/skills/virtual-workbench/SKILL.md
Normal file
@@ -0,0 +1,282 @@
|
||||
---
|
||||
name: virtual-workbench
|
||||
description: Operate Virtual Workbench via REST API — prepare materials, move to heating stations, start heating, move to output, transfer resources. Use when the user mentions virtual workbench, virtual_workbench, 虚拟工作台, heating stations, material processing, or workbench operations.
|
||||
---
|
||||
|
||||
# Virtual Workbench API Skill
|
||||
|
||||
## 设备信息
|
||||
|
||||
- **device_id**: `virtual_workbench`
|
||||
- **Python 源码**: `unilabos/devices/virtual/workbench.py`
|
||||
- **设备类**: `VirtualWorkbench`
|
||||
- **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
|
||||
|
||||
1. `prepare_materials` — 生成 A1-A5 物料（5 个 output handle）
|
||||
2. `move_to_heating_station` — 物料并发竞争机械臂，移动到空闲加热台
|
||||
3. `start_heating` — 启动加热（3 个加热台可并行）
|
||||
4. `move_to_output` — 加热完成后移到输出位置 Cn
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
使用本 skill 前，**必须**先确认以下信息。如果缺少任何一项，**立即向用户询问并终止**，等补齐后再继续。
|
||||
|
||||
### 1. ak / sk → AUTH
|
||||
|
||||
从启动参数 `--ak` `--sk` 或 config.py 中获取，生成 token：`base64(ak:sk)` → `Authorization: Lab <token>`
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
| ------------ | ----------------------------------- |
|
||||
| `test` | `https://leap-lab.test.bohrium.com` |
|
||||
| `uat` | `https://leap-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://leap-lab.bohrium.com` |
|
||||
|
||||
确认后设置：
|
||||
|
||||
```bash
|
||||
BASE="<根据 addr 确定的 URL>"
|
||||
AUTH="Authorization: Lab <token>"
|
||||
```
|
||||
|
||||
**两项全部就绪后才可发起 API 请求。**
|
||||
|
||||
## Session State
|
||||
|
||||
- `lab_uuid` — 实验室 UUID（首次通过 API #1 自动获取，**不需要问用户**）
|
||||
- `device_name` — `virtual_workbench`
|
||||
|
||||
## 请求约定
|
||||
|
||||
所有请求使用 `curl -s`，POST/PATCH/DELETE 需加 `Content-Type: application/json`。
|
||||
|
||||
> **Windows 平台**必须使用 `curl.exe`（而非 PowerShell 的 `curl` 别名）。
|
||||
|
||||
---
|
||||
|
||||
## API Endpoints
|
||||
|
||||
### 1. 获取实验室信息（自动获取 lab_uuid）
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回 `data.uuid` 为 `lab_uuid`，`data.name` 为 `lab_name`。
|
||||
|
||||
### 2. 创建工作流
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/owner" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"name":"<名称>","lab_uuid":"<lab_uuid>","description":"<描述>"}'
|
||||
```
|
||||
|
||||
返回 `data.uuid` 为 `workflow_uuid`。创建成功后告知用户链接：`$BASE/laboratory/$lab_uuid/workflow/$workflow_uuid`
|
||||
|
||||
### 3. 创建节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/edge/workflow/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"workflow_uuid":"<workflow_uuid>","resource_template_name":"virtual_workbench","node_template_name":"<action_name>"}'
|
||||
```
|
||||
|
||||
- `resource_template_name` 固定为 `virtual_workbench`
|
||||
- `node_template_name` — action 名称（如 `auto-prepare_materials`, `auto-move_to_heating_station`）
|
||||
|
||||
### 4. 删除节点
|
||||
|
||||
```bash
|
||||
curl -s -X DELETE "$BASE/api/v1/lab/workflow/nodes" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"node_uuids":["<uuid1>"],"workflow_uuid":"<workflow_uuid>"}'
|
||||
```
|
||||
|
||||
### 5. 更新节点参数
|
||||
|
||||
```bash
|
||||
curl -s -X PATCH "$BASE/api/v1/lab/workflow/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"workflow_uuid":"<wf_uuid>","uuid":"<node_uuid>","param":{...}}'
|
||||
```
|
||||
|
||||
参考 [action-index.md](action-index.md) 确定哪些字段是 Slot。
|
||||
|
||||
### 6. 查询节点 handles
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/node-handles" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"node_uuids":["<node_uuid_1>","<node_uuid_2>"]}'
|
||||
```
|
||||
|
||||
### 7. 批量创建边
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/edges" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"edges":[{"source_node_uuid":"<uuid>","target_node_uuid":"<uuid>","source_handle_uuid":"<uuid>","target_handle_uuid":"<uuid>"}]}'
|
||||
```
|
||||
|
||||
### 8. 启动工作流
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/workflow/<workflow_uuid>/run" -H "$AUTH"
|
||||
```
|
||||
|
||||
### 9. 运行设备单动作
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/mcp/run/action" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"lab_uuid":"<lab_uuid>","device_id":"virtual_workbench","action":"<action_name>","action_type":"<type>","param":{...}}'
|
||||
```
|
||||
|
||||
`param` 直接放 goal 里的属性，**不要**再包一层 `{"goal": {...}}`。
|
||||
|
||||
> **WARNING: `action_type` 必须正确，传错会导致任务永远卡住无法完成。** 从下表或 `actions/<name>.json` 的 `type` 字段获取。
|
||||
|
||||
#### action_type 速查表
|
||||
|
||||
| action | action_type |
|
||||
|--------|-------------|
|
||||
| `auto-prepare_materials` | `UniLabJsonCommand` |
|
||||
| `auto-move_to_heating_station` | `UniLabJsonCommand` |
|
||||
| `auto-start_heating` | `UniLabJsonCommand` |
|
||||
| `auto-move_to_output` | `UniLabJsonCommand` |
|
||||
| `transfer` | `UniLabJsonCommandAsync` |
|
||||
|
||||
> `manual_confirm` 和扣电测试 `test` 当前不纳入本 skill 的推荐操作范围；不要基于历史 JSON 直接调用，需先重新生成并校验 schema。
|
||||
|
||||
### 10. 查询任务状态
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/mcp/task/<task_uuid>" -H "$AUTH"
|
||||
```
|
||||
|
||||
### 11. 运行工作流单节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/mcp/run/workflow/action" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"node_uuid":"<node_uuid>"}'
|
||||
```
|
||||
|
||||
### 12. 获取资源树（物料信息）
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/material/download/$lab_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
注意 `lab_uuid` 在路径中。返回 `data.nodes[]` 含所有节点（设备 + 物料），每个节点含 `name`、`uuid`、`type`、`parent`。
|
||||
|
||||
### 13. 获取工作流模板详情
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/workflow/template/detail/$workflow_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
> 必须使用 `/lab/workflow/template/detail/{uuid}`，其他路径会返回 404。
|
||||
|
||||
### 14. 按名称查询物料模板
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/material/template/by-name?lab_uuid=$lab_uuid&name=<template_name>" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回 `data.uuid` 为 `res_template_uuid`，用于 API #15。
|
||||
|
||||
### 15. 创建物料节点
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/edge/material/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"res_template_uuid":"<uuid>","name":"<名称>","display_name":"<显示名>","parent_uuid":"<父节点uuid>","data":{...}}'
|
||||
```
|
||||
|
||||
### 16. 更新物料节点
|
||||
|
||||
```bash
|
||||
curl -s -X PUT "$BASE/api/v1/edge/material/node" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{"uuid":"<节点uuid>","display_name":"<新名称>","data":{...}}'
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Placeholder Slot 填写规则
|
||||
|
||||
| `placeholder_keys` 值 | Slot 类型 | 填写格式 | 选取范围 |
|
||||
| --------------------- | ------------ | ----------------------------------------------------- | ---------------------- |
|
||||
| `unilabos_resources` | ResourceSlot | `{"id": "/path/name", "name": "name", "uuid": "xxx"}` | 仅物料节点（非设备） |
|
||||
| `unilabos_devices` | DeviceSlot | `"/parent/device_name"` | 仅设备节点（type=device） |
|
||||
| `unilabos_nodes` | NodeSlot | `"/parent/node_name"` | 所有节点（设备 + 物料） |
|
||||
| `unilabos_class` | ClassSlot | `"class_name"` | 注册表中已注册的资源类 |
|
||||
|
||||
### virtual_workbench 设备的 Slot 字段表
|
||||
|
||||
| Action | 字段 | Slot 类型 | 说明 |
|
||||
| ----------------- | ---------------- | ------------ | -------------------- |
|
||||
| `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 |
|
||||
|
||||
> `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。
|
||||
|
||||
---
|
||||
|
||||
## 渐进加载策略
|
||||
|
||||
1. **SKILL.md**（本文件）— API 端点 + session state 管理 + 设备工作流概览
|
||||
2. **[action-index.md](action-index.md)** — 按分类浏览 6 个动作的描述和核心参数
|
||||
3. **[actions/\<name\>.json](actions/)** — 仅在需要构建具体请求时，加载对应 action 的完整 JSON Schema
|
||||
|
||||
---
|
||||
|
||||
## 完整工作流 Checklist
|
||||
|
||||
```
|
||||
Task Progress:
|
||||
- [ ] Step 1: GET /edge/lab/info 获取 lab_uuid
|
||||
- [ ] Step 2: 获取资源树 (GET #12) → 记住可用物料
|
||||
- [ ] Step 3: 读 action-index.md 确定要用的 action 名
|
||||
- [ ] Step 4: 创建工作流 (POST #2) → 记住 workflow_uuid，告知用户链接
|
||||
- [ ] Step 5: 创建节点 (POST #3, resource_template_name=virtual_workbench) → 记住 node_uuid + data.param
|
||||
- [ ] Step 6: 根据 _unilabos_placeholder_info 和资源树，填写 data.param 中的 Slot 字段
|
||||
- [ ] Step 7: 更新节点参数 (PATCH #5)
|
||||
- [ ] Step 8: 查询节点 handles (POST #6) → 获取各节点的 handle_uuid
|
||||
- [ ] Step 9: 批量创建边 (POST #7) → 用 handle_uuid 连接节点
|
||||
- [ ] Step 10: 启动工作流 (POST #8) 或运行单节点 (POST #11)
|
||||
- [ ] Step 11: 查询任务状态 (GET #10) 确认完成
|
||||
```
|
||||
|
||||
### 典型 5 物料并发加热工作流示例
|
||||
|
||||
```
|
||||
prepare_materials (count=5)
|
||||
├─ channel_1 → move_to_heating_station (material_number=1) → start_heating → move_to_output
|
||||
├─ channel_2 → move_to_heating_station (material_number=2) → start_heating → move_to_output
|
||||
├─ channel_3 → move_to_heating_station (material_number=3) → start_heating → move_to_output
|
||||
├─ channel_4 → move_to_heating_station (material_number=4) → start_heating → move_to_output
|
||||
└─ channel_5 → move_to_heating_station (material_number=5) → start_heating → move_to_output
|
||||
```
|
||||
|
||||
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` |
|
||||
79
.cursor/skills/virtual-workbench/action-index.md
Normal file
79
.cursor/skills/virtual-workbench/action-index.md
Normal file
@@ -0,0 +1,79 @@
|
||||
# Action Index — virtual_workbench
|
||||
|
||||
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。
|
||||
|
||||
---
|
||||
|
||||
## 物料准备
|
||||
|
||||
### `auto-prepare_materials`
|
||||
|
||||
批量准备物料（虚拟起始节点），生成 A1-A5 物料编号，输出 5 个 handle 供后续节点使用
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/prepare_materials.json`](actions/prepare_materials.json)
|
||||
- **可选参数**: `count`（物料数量，默认 5）
|
||||
|
||||
---
|
||||
|
||||
## 机械臂 & 加热台操作
|
||||
|
||||
### `auto-move_to_heating_station`
|
||||
|
||||
将物料从 An 位置移动到空闲加热台（竞争机械臂，自动查找空闲加热台）
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/move_to_heating_station.json`](actions/move_to_heating_station.json)
|
||||
- **核心参数**: `material_number`（物料编号，integer）
|
||||
|
||||
### `auto-start_heating`
|
||||
|
||||
启动指定加热台的加热程序（可并行，3 个加热台同时工作）
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/start_heating.json`](actions/start_heating.json)
|
||||
- **核心参数**: `station_id`（加热台 ID），`material_number`（物料编号）
|
||||
|
||||
### `auto-move_to_output`
|
||||
|
||||
将加热完成的物料从加热台移动到输出位置 Cn
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/move_to_output.json`](actions/move_to_output.json)
|
||||
- **核心参数**: `station_id`（加热台 ID），`material_number`（物料编号）
|
||||
|
||||
---
|
||||
|
||||
## 物料转移
|
||||
|
||||
### `transfer`
|
||||
|
||||
异步转移物料到目标设备（通过 ROS 资源转移）
|
||||
|
||||
- **action_type**: `UniLabJsonCommandAsync`
|
||||
- **Schema**: [`actions/transfer.json`](actions/transfer.json)
|
||||
- **核心参数**: `resource`, `target_device`, `mount_resource`
|
||||
- **占位符字段**:
|
||||
- `resource` — **ResourceSlot**，待转移的物料数组 `[{id, name, uuid}, ...]`
|
||||
- `target_device` — **DeviceSlot**，目标设备路径字符串
|
||||
- `mount_resource` — **ResourceSlot**，目标孔位数组 `[{id, name, uuid}, ...]`
|
||||
|
||||
---
|
||||
|
||||
## 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）。当前先不纳入推荐操作范围。
|
||||
|
||||
- **action_type**: `UniLabJsonCommand`
|
||||
- **Schema**: [`actions/manual_confirm.json`](actions/manual_confirm.json)
|
||||
- **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。
|
||||
|
||||
### `test`
|
||||
|
||||
启动扣电测试。当前先不纳入本 skill。
|
||||
|
||||
- **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。
|
||||
270
.cursor/skills/virtual-workbench/actions/manual_confirm.json
Normal file
270
.cursor/skills/virtual-workbench/actions/manual_confirm.json
Normal file
@@ -0,0 +1,270 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"resource": "resource",
|
||||
"target_device": "target_device",
|
||||
"mount_resource": "mount_resource",
|
||||
"timeout_seconds": "timeout_seconds",
|
||||
"assignee_user_ids": "assignee_user_ids"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"resource": {
|
||||
"items": {
|
||||
"type": "object",
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string"
|
||||
},
|
||||
"name": {
|
||||
"type": "string"
|
||||
},
|
||||
"sample_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"children": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
},
|
||||
"category": {
|
||||
"type": "string"
|
||||
},
|
||||
"pose": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"position": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "position",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"orientation": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"w": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z",
|
||||
"w"
|
||||
],
|
||||
"title": "orientation",
|
||||
"additionalProperties": false
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"position",
|
||||
"orientation"
|
||||
],
|
||||
"title": "pose",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"config": {
|
||||
"type": "string"
|
||||
},
|
||||
"data": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"title": "resource"
|
||||
},
|
||||
"type": "array"
|
||||
},
|
||||
"target_device": {
|
||||
"type": "string",
|
||||
"description": "device reference"
|
||||
},
|
||||
"mount_resource": {
|
||||
"items": {
|
||||
"type": "object",
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string"
|
||||
},
|
||||
"name": {
|
||||
"type": "string"
|
||||
},
|
||||
"sample_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"children": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
},
|
||||
"category": {
|
||||
"type": "string"
|
||||
},
|
||||
"pose": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"position": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "position",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"orientation": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"w": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z",
|
||||
"w"
|
||||
],
|
||||
"title": "orientation",
|
||||
"additionalProperties": false
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"position",
|
||||
"orientation"
|
||||
],
|
||||
"title": "pose",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"config": {
|
||||
"type": "string"
|
||||
},
|
||||
"data": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"title": "mount_resource"
|
||||
},
|
||||
"type": "array"
|
||||
},
|
||||
"timeout_seconds": {
|
||||
"type": "integer"
|
||||
},
|
||||
"assignee_user_ids": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"resource",
|
||||
"target_device",
|
||||
"mount_resource",
|
||||
"timeout_seconds",
|
||||
"assignee_user_ids"
|
||||
],
|
||||
"_unilabos_placeholder_info": {
|
||||
"resource": "unilabos_resources",
|
||||
"target_device": "unilabos_devices",
|
||||
"mount_resource": "unilabos_resources",
|
||||
"assignee_user_ids": "unilabos_manual_confirm"
|
||||
}
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {
|
||||
"resource": "unilabos_resources",
|
||||
"target_device": "unilabos_devices",
|
||||
"mount_resource": "unilabos_resources",
|
||||
"assignee_user_ids": "unilabos_manual_confirm"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,19 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"material_number": "material_number"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"material_number": {
|
||||
"type": "integer"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"material_number"
|
||||
]
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {}
|
||||
}
|
||||
24
.cursor/skills/virtual-workbench/actions/move_to_output.json
Normal file
24
.cursor/skills/virtual-workbench/actions/move_to_output.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"station_id": "station_id",
|
||||
"material_number": "material_number"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"station_id": {
|
||||
"type": "integer"
|
||||
},
|
||||
"material_number": {
|
||||
"type": "integer"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"station_id",
|
||||
"material_number"
|
||||
]
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {}
|
||||
}
|
||||
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"count": "count"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"count": {
|
||||
"type": "integer",
|
||||
"default": 5
|
||||
}
|
||||
},
|
||||
"required": []
|
||||
},
|
||||
"goal_default": {
|
||||
"count": 5
|
||||
},
|
||||
"placeholder_keys": {}
|
||||
}
|
||||
24
.cursor/skills/virtual-workbench/actions/start_heating.json
Normal file
24
.cursor/skills/virtual-workbench/actions/start_heating.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"type": "UniLabJsonCommand",
|
||||
"goal": {
|
||||
"station_id": "station_id",
|
||||
"material_number": "material_number"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"station_id": {
|
||||
"type": "integer"
|
||||
},
|
||||
"material_number": {
|
||||
"type": "integer"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"station_id",
|
||||
"material_number"
|
||||
]
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {}
|
||||
}
|
||||
255
.cursor/skills/virtual-workbench/actions/transfer.json
Normal file
255
.cursor/skills/virtual-workbench/actions/transfer.json
Normal file
@@ -0,0 +1,255 @@
|
||||
{
|
||||
"type": "UniLabJsonCommandAsync",
|
||||
"goal": {
|
||||
"resource": "resource",
|
||||
"target_device": "target_device",
|
||||
"mount_resource": "mount_resource"
|
||||
},
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"resource": {
|
||||
"items": {
|
||||
"type": "object",
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string"
|
||||
},
|
||||
"name": {
|
||||
"type": "string"
|
||||
},
|
||||
"sample_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"children": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
},
|
||||
"category": {
|
||||
"type": "string"
|
||||
},
|
||||
"pose": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"position": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "position",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"orientation": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"w": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z",
|
||||
"w"
|
||||
],
|
||||
"title": "orientation",
|
||||
"additionalProperties": false
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"position",
|
||||
"orientation"
|
||||
],
|
||||
"title": "pose",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"config": {
|
||||
"type": "string"
|
||||
},
|
||||
"data": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"title": "resource"
|
||||
},
|
||||
"type": "array"
|
||||
},
|
||||
"target_device": {
|
||||
"type": "string",
|
||||
"description": "device reference"
|
||||
},
|
||||
"mount_resource": {
|
||||
"items": {
|
||||
"type": "object",
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string"
|
||||
},
|
||||
"name": {
|
||||
"type": "string"
|
||||
},
|
||||
"sample_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"children": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"parent": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
},
|
||||
"category": {
|
||||
"type": "string"
|
||||
},
|
||||
"pose": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"position": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z"
|
||||
],
|
||||
"title": "position",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"orientation": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"x": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"y": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"z": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
},
|
||||
"w": {
|
||||
"type": "number",
|
||||
"minimum": -1.7976931348623157e+308,
|
||||
"maximum": 1.7976931348623157e+308
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"x",
|
||||
"y",
|
||||
"z",
|
||||
"w"
|
||||
],
|
||||
"title": "orientation",
|
||||
"additionalProperties": false
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"position",
|
||||
"orientation"
|
||||
],
|
||||
"title": "pose",
|
||||
"additionalProperties": false
|
||||
},
|
||||
"config": {
|
||||
"type": "string"
|
||||
},
|
||||
"data": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"title": "mount_resource"
|
||||
},
|
||||
"type": "array"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"resource",
|
||||
"target_device",
|
||||
"mount_resource"
|
||||
],
|
||||
"_unilabos_placeholder_info": {
|
||||
"resource": "unilabos_resources",
|
||||
"target_device": "unilabos_devices",
|
||||
"mount_resource": "unilabos_resources"
|
||||
}
|
||||
},
|
||||
"goal_default": {},
|
||||
"placeholder_keys": {
|
||||
"resource": "unilabos_resources",
|
||||
"target_device": "unilabos_devices",
|
||||
"mount_resource": "unilabos_resources"
|
||||
}
|
||||
}
|
||||
4
.github/workflows/ci-check.yml
vendored
4
.github/workflows/ci-check.yml
vendored
@@ -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
|
||||
@@ -38,7 +38,7 @@ jobs:
|
||||
- name: Install ROS dependencies, uv and unilabos-msgs
|
||||
run: |
|
||||
echo Installing ROS dependencies...
|
||||
mamba install -n check-env conda-forge::uv conda-forge::opencv robostack-staging::ros-humble-ros-core robostack-staging::ros-humble-action-msgs robostack-staging::ros-humble-std-msgs robostack-staging::ros-humble-geometry-msgs robostack-staging::ros-humble-control-msgs robostack-staging::ros-humble-nav2-msgs uni-lab::ros-humble-unilabos-msgs robostack-staging::ros-humble-cv-bridge robostack-staging::ros-humble-vision-opencv robostack-staging::ros-humble-tf-transformations robostack-staging::ros-humble-moveit-msgs robostack-staging::ros-humble-tf2-ros robostack-staging::ros-humble-tf2-ros-py conda-forge::transforms3d -c robostack-staging -c conda-forge -c uni-lab -y
|
||||
mamba install -n check-env --override-channels -c robostack-staging -c conda-forge -c uni-lab conda-forge::uv conda-forge::opencv robostack-staging::ros-humble-ros-core robostack-staging::ros-humble-action-msgs robostack-staging::ros-humble-std-msgs robostack-staging::ros-humble-geometry-msgs robostack-staging::ros-humble-control-msgs robostack-staging::ros-humble-nav2-msgs uni-lab::ros-humble-unilabos-msgs robostack-staging::ros-humble-cv-bridge robostack-staging::ros-humble-vision-opencv robostack-staging::ros-humble-tf-transformations robostack-staging::ros-humble-moveit-msgs robostack-staging::ros-humble-tf2-ros robostack-staging::ros-humble-tf2-ros-py conda-forge::transforms3d -y
|
||||
|
||||
- name: Install pip dependencies and unilabos
|
||||
run: |
|
||||
|
||||
81
.github/workflows/conda-pack-build.yml
vendored
81
.github/workflows/conda-pack-build.yml
vendored
@@ -1,6 +1,10 @@
|
||||
name: Build Conda-Pack Environment
|
||||
|
||||
on:
|
||||
# 在 UniLabOS Conda Build 成功上传后自动构建非全量 conda-pack
|
||||
workflow_run:
|
||||
workflows: ["UniLabOS Conda Build"]
|
||||
types: [completed]
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
branch:
|
||||
@@ -21,6 +25,16 @@ on:
|
||||
|
||||
jobs:
|
||||
build-conda-pack:
|
||||
if: |
|
||||
github.event_name == 'workflow_dispatch' ||
|
||||
(
|
||||
github.event_name == 'workflow_run' &&
|
||||
github.event.workflow_run.conclusion == 'success' &&
|
||||
github.event.workflow_run.event == 'workflow_run'
|
||||
)
|
||||
env:
|
||||
BUILD_FULL: ${{ github.event_name == 'workflow_dispatch' && github.event.inputs.build_full == 'true' }}
|
||||
PACKAGE_REF: ${{ github.event.inputs.branch || github.event.workflow_run.head_sha || github.ref_name }}
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
@@ -29,7 +43,7 @@ jobs:
|
||||
platform: linux-64
|
||||
env_file: unilabos-linux-64.yaml
|
||||
script_ext: sh
|
||||
- os: macos-15 # Intel (via Rosetta)
|
||||
- os: macos-15-intel # Intel x86_64
|
||||
platform: osx-64
|
||||
env_file: unilabos-osx-64.yaml
|
||||
script_ext: sh
|
||||
@@ -54,7 +68,9 @@ jobs:
|
||||
id: should_build
|
||||
shell: bash
|
||||
run: |
|
||||
if [[ -z "${{ github.event.inputs.platforms }}" ]]; then
|
||||
if [[ "${{ github.event_name }}" != "workflow_dispatch" ]]; then
|
||||
echo "should_build=true" >> $GITHUB_OUTPUT
|
||||
elif [[ -z "${{ github.event.inputs.platforms }}" ]]; then
|
||||
echo "should_build=true" >> $GITHUB_OUTPUT
|
||||
elif [[ "${{ github.event.inputs.platforms }}" == *"${{ matrix.platform }}"* ]]; then
|
||||
echo "should_build=true" >> $GITHUB_OUTPUT
|
||||
@@ -65,17 +81,17 @@ jobs:
|
||||
- uses: actions/checkout@v6
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
with:
|
||||
ref: ${{ github.event.inputs.branch }}
|
||||
ref: ${{ github.event.inputs.branch || github.event.workflow_run.head_sha || github.ref }}
|
||||
fetch-depth: 0
|
||||
|
||||
- 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
|
||||
python-version: '3.11.14'
|
||||
channels: conda-forge,robostack-staging,uni-lab,defaults
|
||||
channels: conda-forge,robostack-staging,uni-lab
|
||||
channel-priority: flexible
|
||||
activate-environment: unilab
|
||||
auto-update-conda: false
|
||||
@@ -86,13 +102,13 @@ jobs:
|
||||
run: |
|
||||
echo Installing unilabos and dependencies to unilab environment...
|
||||
echo Using mamba for faster and more reliable dependency resolution...
|
||||
echo Build full: ${{ github.event.inputs.build_full }}
|
||||
if "${{ github.event.inputs.build_full }}"=="true" (
|
||||
echo Build full: ${{ env.BUILD_FULL }}
|
||||
if "${{ env.BUILD_FULL }}"=="true" (
|
||||
echo Installing unilabos-full ^(complete package^)...
|
||||
mamba install -n unilab uni-lab::unilabos-full conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
|
||||
mamba install -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge uni-lab::unilabos-full conda-pack zstandard -y
|
||||
) else (
|
||||
echo Installing unilabos ^(minimal package^)...
|
||||
mamba install -n unilab uni-lab::unilabos conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
|
||||
mamba install -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge uni-lab::unilabos conda-pack zstandard -y
|
||||
)
|
||||
|
||||
- name: Install conda-pack, unilabos and dependencies (Unix)
|
||||
@@ -101,13 +117,13 @@ jobs:
|
||||
run: |
|
||||
echo "Installing unilabos and dependencies to unilab environment..."
|
||||
echo "Using mamba for faster and more reliable dependency resolution..."
|
||||
echo "Build full: ${{ github.event.inputs.build_full }}"
|
||||
if [[ "${{ github.event.inputs.build_full }}" == "true" ]]; then
|
||||
echo "Build full: ${{ env.BUILD_FULL }}"
|
||||
if [[ "${{ env.BUILD_FULL }}" == "true" ]]; then
|
||||
echo "Installing unilabos-full (complete package)..."
|
||||
mamba install -n unilab uni-lab::unilabos-full conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
|
||||
mamba install -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge uni-lab::unilabos-full conda-pack zstandard -y
|
||||
else
|
||||
echo "Installing unilabos (minimal package)..."
|
||||
mamba install -n unilab uni-lab::unilabos conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
|
||||
mamba install -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge uni-lab::unilabos conda-pack zstandard -y
|
||||
fi
|
||||
|
||||
- name: Get latest ros-humble-unilabos-msgs version (Windows)
|
||||
@@ -134,27 +150,27 @@ jobs:
|
||||
if: steps.should_build.outputs.should_build == 'true' && matrix.platform == 'win-64'
|
||||
run: |
|
||||
echo Checking for available ros-humble-unilabos-msgs versions...
|
||||
mamba search ros-humble-unilabos-msgs -c uni-lab -c robostack-staging -c conda-forge || echo Search completed
|
||||
mamba search --override-channels -c uni-lab -c robostack-staging -c conda-forge ros-humble-unilabos-msgs || echo Search completed
|
||||
echo.
|
||||
echo Updating ros-humble-unilabos-msgs to latest version...
|
||||
mamba update -n unilab ros-humble-unilabos-msgs -c uni-lab -c robostack-staging -c conda-forge -y || echo Already at latest version
|
||||
mamba update -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge ros-humble-unilabos-msgs -y || echo Already at latest version
|
||||
|
||||
- name: Check for newer ros-humble-unilabos-msgs (Unix)
|
||||
if: steps.should_build.outputs.should_build == 'true' && matrix.platform != 'win-64'
|
||||
shell: bash
|
||||
run: |
|
||||
echo "Checking for available ros-humble-unilabos-msgs versions..."
|
||||
mamba search ros-humble-unilabos-msgs -c uni-lab -c robostack-staging -c conda-forge || echo "Search completed"
|
||||
mamba search --override-channels -c uni-lab -c robostack-staging -c conda-forge ros-humble-unilabos-msgs || echo "Search completed"
|
||||
echo ""
|
||||
echo "Updating ros-humble-unilabos-msgs to latest version..."
|
||||
mamba update -n unilab ros-humble-unilabos-msgs -c uni-lab -c robostack-staging -c conda-forge -y || echo "Already at latest version"
|
||||
mamba update -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge ros-humble-unilabos-msgs -y || echo "Already at latest version"
|
||||
|
||||
- name: Install latest unilabos from source (Windows)
|
||||
if: steps.should_build.outputs.should_build == 'true' && matrix.platform == 'win-64'
|
||||
run: |
|
||||
echo Uninstalling existing unilabos...
|
||||
mamba run -n unilab pip uninstall unilabos -y || echo unilabos not installed via pip
|
||||
echo Installing unilabos from source (branch: ${{ github.event.inputs.branch }})...
|
||||
echo Installing unilabos from source (ref: ${{ env.PACKAGE_REF }})...
|
||||
mamba run -n unilab pip install .
|
||||
echo Verifying installation...
|
||||
mamba run -n unilab pip show unilabos
|
||||
@@ -165,7 +181,7 @@ jobs:
|
||||
run: |
|
||||
echo "Uninstalling existing unilabos..."
|
||||
mamba run -n unilab pip uninstall unilabos -y || echo "unilabos not installed via pip"
|
||||
echo "Installing unilabos from source (branch: ${{ github.event.inputs.branch }})..."
|
||||
echo "Installing unilabos from source (ref: ${{ env.PACKAGE_REF }})..."
|
||||
mamba run -n unilab pip install .
|
||||
echo "Verifying installation..."
|
||||
mamba run -n unilab pip show unilabos
|
||||
@@ -226,7 +242,9 @@ jobs:
|
||||
if: steps.should_build.outputs.should_build == 'true' && matrix.platform == 'win-64'
|
||||
run: |
|
||||
echo Packing unilab environment with conda-pack...
|
||||
mamba activate unilab && conda pack -n unilab -o unilab-env-${{ matrix.platform }}.tar.gz --ignore-missing-files
|
||||
for /f "delims=" %%i in ('mamba run -n unilab python -c "import os; print(os.environ['CONDA_PREFIX'])"') do set "UNILAB_PREFIX=%%i"
|
||||
echo Packing environment at: %UNILAB_PREFIX%
|
||||
mamba run -n unilab conda-pack -p "%UNILAB_PREFIX%" -o unilab-env-${{ matrix.platform }}.tar.gz --ignore-missing-files
|
||||
echo Pack file created:
|
||||
dir unilab-env-${{ matrix.platform }}.tar.gz
|
||||
|
||||
@@ -235,8 +253,9 @@ jobs:
|
||||
shell: bash
|
||||
run: |
|
||||
echo "Packing unilab environment with conda-pack..."
|
||||
mamba install conda-pack -c conda-forge -y
|
||||
conda pack -n unilab -o unilab-env-${{ matrix.platform }}.tar.gz --ignore-missing-files
|
||||
UNILAB_PREFIX="$(mamba run -n unilab python -c 'import os; print(os.environ["CONDA_PREFIX"])')"
|
||||
echo "Packing environment at: $UNILAB_PREFIX"
|
||||
mamba run -n unilab conda-pack -p "$UNILAB_PREFIX" -o unilab-env-${{ matrix.platform }}.tar.gz --ignore-missing-files
|
||||
echo "Pack file created:"
|
||||
ls -lh unilab-env-${{ matrix.platform }}.tar.gz
|
||||
|
||||
@@ -267,7 +286,7 @@ jobs:
|
||||
|
||||
rem Create README using Python script
|
||||
echo Creating: README.txt
|
||||
python scripts\create_readme.py ${{ matrix.platform }} ${{ github.event.inputs.branch }} dist-package\README.txt
|
||||
python scripts\create_readme.py ${{ matrix.platform }} ${{ env.PACKAGE_REF }} dist-package\README.txt
|
||||
|
||||
echo.
|
||||
echo Distribution package contents:
|
||||
@@ -303,7 +322,7 @@ jobs:
|
||||
|
||||
# Create README using Python script
|
||||
echo "Creating: README.txt"
|
||||
python scripts/create_readme.py ${{ matrix.platform }} ${{ github.event.inputs.branch }} dist-package/README.txt
|
||||
python scripts/create_readme.py ${{ matrix.platform }} ${{ env.PACKAGE_REF }} dist-package/README.txt
|
||||
|
||||
echo ""
|
||||
echo "Distribution package contents:"
|
||||
@@ -314,7 +333,7 @@ jobs:
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
name: unilab-pack-${{ matrix.platform }}-${{ github.event.inputs.branch }}
|
||||
name: unilab-pack-${{ matrix.platform }}-${{ env.PACKAGE_REF }}
|
||||
path: dist-package/
|
||||
retention-days: 90
|
||||
if-no-files-found: error
|
||||
@@ -326,9 +345,9 @@ jobs:
|
||||
echo Build Summary
|
||||
echo ==========================================
|
||||
echo Platform: ${{ matrix.platform }}
|
||||
echo Branch: ${{ github.event.inputs.branch }}
|
||||
echo Branch: ${{ env.PACKAGE_REF }}
|
||||
echo Python version: 3.11.14
|
||||
if "${{ github.event.inputs.build_full }}"=="true" (
|
||||
if "${{ env.BUILD_FULL }}"=="true" (
|
||||
echo Package: unilabos-full ^(complete^)
|
||||
) else (
|
||||
echo Package: unilabos ^(minimal^)
|
||||
@@ -337,7 +356,7 @@ jobs:
|
||||
echo Distribution package contents:
|
||||
dir dist-package
|
||||
echo.
|
||||
echo Artifact name: unilab-pack-${{ matrix.platform }}-${{ github.event.inputs.branch }}
|
||||
echo Artifact name: unilab-pack-${{ matrix.platform }}-${{ env.PACKAGE_REF }}
|
||||
echo.
|
||||
echo After download, extract the ZIP and run:
|
||||
echo install_unilab.bat
|
||||
@@ -351,9 +370,9 @@ jobs:
|
||||
echo "Build Summary"
|
||||
echo "=========================================="
|
||||
echo "Platform: ${{ matrix.platform }}"
|
||||
echo "Branch: ${{ github.event.inputs.branch }}"
|
||||
echo "Branch: ${{ env.PACKAGE_REF }}"
|
||||
echo "Python version: 3.11.14"
|
||||
if [[ "${{ github.event.inputs.build_full }}" == "true" ]]; then
|
||||
if [[ "${{ env.BUILD_FULL }}" == "true" ]]; then
|
||||
echo "Package: unilabos-full (complete)"
|
||||
else
|
||||
echo "Package: unilabos (minimal)"
|
||||
@@ -362,7 +381,7 @@ jobs:
|
||||
echo "Distribution package contents:"
|
||||
ls -lh dist-package/
|
||||
echo ""
|
||||
echo "Artifact name: unilab-pack-${{ matrix.platform }}-${{ github.event.inputs.branch }}"
|
||||
echo "Artifact name: unilab-pack-${{ matrix.platform }}-${{ env.PACKAGE_REF }}"
|
||||
echo ""
|
||||
echo "After download:"
|
||||
echo " install_unilab.sh"
|
||||
|
||||
12
.github/workflows/deploy-docs.yml
vendored
12
.github/workflows/deploy-docs.yml
vendored
@@ -51,12 +51,12 @@ 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
|
||||
python-version: '3.11.14'
|
||||
channels: conda-forge,robostack-staging,uni-lab,defaults
|
||||
channels: conda-forge,robostack-staging,uni-lab
|
||||
channel-priority: flexible
|
||||
activate-environment: unilab
|
||||
auto-update-conda: false
|
||||
@@ -66,7 +66,7 @@ jobs:
|
||||
run: |
|
||||
echo "Installing unilabos and dependencies to unilab environment..."
|
||||
echo "Using mamba for faster and more reliable dependency resolution..."
|
||||
mamba install -n unilab uni-lab::unilabos -c uni-lab -c robostack-staging -c conda-forge -y
|
||||
mamba install -n unilab --override-channels -c uni-lab -c robostack-staging -c conda-forge uni-lab::unilabos -y
|
||||
|
||||
- name: Install latest unilabos from source
|
||||
run: |
|
||||
@@ -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
|
||||
|
||||
39
.github/workflows/multi-platform-build.yml
vendored
39
.github/workflows/multi-platform-build.yml
vendored
@@ -10,6 +10,9 @@ on:
|
||||
# 支持 tag 推送（不依赖 CI Check）
|
||||
push:
|
||||
tags: ['v*']
|
||||
# GitHub Release 发布时自动构建并上传
|
||||
release:
|
||||
types: [published]
|
||||
# 手动触发
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
@@ -60,7 +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
|
||||
@@ -80,7 +83,7 @@ jobs:
|
||||
- uses: actions/checkout@v6
|
||||
with:
|
||||
# 如果是 workflow_run 触发，使用触发 CI Check 的 commit
|
||||
ref: ${{ github.event.workflow_run.head_sha || github.ref }}
|
||||
ref: ${{ github.event.workflow_run.head_sha || github.event.release.tag_name || github.ref }}
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Check if platform should be built
|
||||
@@ -96,12 +99,14 @@ jobs:
|
||||
echo "should_build=false" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
|
||||
- name: Setup Miniconda
|
||||
- name: Setup Miniforge
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
uses: conda-incubator/setup-miniconda@v3
|
||||
uses: conda-incubator/setup-miniconda@v4
|
||||
with:
|
||||
miniconda-version: 'latest'
|
||||
channels: conda-forge,robostack-staging,defaults
|
||||
miniforge-version: latest
|
||||
use-mamba: true
|
||||
python-version: '3.11.14'
|
||||
channels: conda-forge,robostack-staging
|
||||
channel-priority: strict
|
||||
activate-environment: build-env
|
||||
auto-update-conda: false
|
||||
@@ -110,24 +115,22 @@ jobs:
|
||||
- name: Install rattler-build and anaconda-client
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
run: |
|
||||
conda install -c conda-forge rattler-build anaconda-client
|
||||
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
|
||||
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
|
||||
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
|
||||
|
||||
- name: List built packages
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
@@ -157,9 +160,15 @@ jobs:
|
||||
retention-days: 30
|
||||
|
||||
- name: Upload to Anaconda.org (unilab organization)
|
||||
if: steps.should_build.outputs.should_build == 'true' && github.event.inputs.upload_to_anaconda == 'true'
|
||||
if: |
|
||||
steps.should_build.outputs.should_build == 'true' &&
|
||||
(
|
||||
github.event_name == 'release' ||
|
||||
startsWith(github.ref, 'refs/tags/') ||
|
||||
github.event.inputs.upload_to_anaconda == 'true'
|
||||
)
|
||||
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
|
||||
|
||||
78
.github/workflows/unilabos-conda-build.yml
vendored
78
.github/workflows/unilabos-conda-build.yml
vendored
@@ -1,14 +1,10 @@
|
||||
name: UniLabOS Conda Build
|
||||
|
||||
on:
|
||||
# 在 CI Check 成功后自动触发
|
||||
# 在 Multi-Platform Conda Build 成功上传 msgs 后自动触发
|
||||
workflow_run:
|
||||
workflows: ["CI Check"]
|
||||
workflows: ["Multi-Platform Conda Build"]
|
||||
types: [completed]
|
||||
branches: [main, dev]
|
||||
# 标签推送时直接触发（发布版本）
|
||||
push:
|
||||
tags: ['v*']
|
||||
# 手动触发
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
@@ -33,37 +29,37 @@ on:
|
||||
type: boolean
|
||||
|
||||
jobs:
|
||||
# 等待 CI Check 完成的 job (仅用于 workflow_run 触发)
|
||||
wait-for-ci:
|
||||
# 等待上游 msgs 构建完成的 job (仅用于 workflow_run 触发)
|
||||
wait-for-upstream:
|
||||
runs-on: ubuntu-latest
|
||||
if: github.event_name == 'workflow_run'
|
||||
outputs:
|
||||
should_continue: ${{ steps.check.outputs.should_continue }}
|
||||
steps:
|
||||
- name: Check CI status
|
||||
- name: Check upstream workflow status
|
||||
id: check
|
||||
run: |
|
||||
if [[ "${{ github.event.workflow_run.conclusion }}" == "success" ]]; then
|
||||
if [[ "${{ github.event.workflow_run.conclusion }}" == "success" && ( "${{ github.event.workflow_run.event }}" == "release" || "${{ github.event.workflow_run.event }}" == "push" ) ]]; then
|
||||
echo "should_continue=true" >> $GITHUB_OUTPUT
|
||||
echo "CI Check passed, proceeding with build"
|
||||
echo "Multi-Platform Conda Build passed for release/tag, proceeding with UniLabOS build"
|
||||
else
|
||||
echo "should_continue=false" >> $GITHUB_OUTPUT
|
||||
echo "CI Check did not succeed (status: ${{ github.event.workflow_run.conclusion }}), skipping build"
|
||||
echo "Upstream workflow is not a successful release/tag build (status: ${{ github.event.workflow_run.conclusion }}, event: ${{ github.event.workflow_run.event }}), skipping build"
|
||||
fi
|
||||
|
||||
build:
|
||||
needs: [wait-for-ci]
|
||||
# 运行条件：workflow_run 触发且 CI 成功，或者其他触发方式
|
||||
needs: [wait-for-upstream]
|
||||
# 运行条件：workflow_run 触发且上游成功，或者手动触发
|
||||
if: |
|
||||
always() &&
|
||||
(needs.wait-for-ci.result == 'skipped' || needs.wait-for-ci.outputs.should_continue == 'true')
|
||||
(needs.wait-for-upstream.result == 'skipped' || needs.wait-for-upstream.outputs.should_continue == 'true')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
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
|
||||
@@ -79,7 +75,7 @@ jobs:
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
with:
|
||||
# 如果是 workflow_run 触发，使用触发 CI Check 的 commit
|
||||
# 如果是 workflow_run 触发，使用上游 conda 包构建的 commit
|
||||
ref: ${{ github.event.workflow_run.head_sha || github.ref }}
|
||||
fetch-depth: 0
|
||||
|
||||
@@ -96,12 +92,14 @@ jobs:
|
||||
echo "should_build=false" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
|
||||
- name: Setup Miniconda
|
||||
- name: Setup Miniforge
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
uses: conda-incubator/setup-miniconda@v3
|
||||
uses: conda-incubator/setup-miniconda@v4
|
||||
with:
|
||||
miniconda-version: 'latest'
|
||||
channels: conda-forge,robostack-staging,uni-lab,defaults
|
||||
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
|
||||
auto-update-conda: false
|
||||
@@ -110,20 +108,22 @@ jobs:
|
||||
- name: Install rattler-build and anaconda-client
|
||||
if: steps.should_build.outputs.should_build == 'true'
|
||||
run: |
|
||||
conda install -c conda-forge rattler-build anaconda-client
|
||||
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.inputs.build_full || 'false' }}"
|
||||
echo "Build full package: ${{ github.event_name == 'workflow_dispatch' && github.event.inputs.build_full == 'true' }}"
|
||||
echo "Building packages:"
|
||||
echo " - unilabos-env (environment dependencies)"
|
||||
echo " - unilabos (with pip package)"
|
||||
if [[ "${{ github.event.inputs.build_full }}" == "true" ]]; then
|
||||
if [[ "${{ github.event_name == 'workflow_dispatch' && github.event.inputs.build_full == 'true' }}" == "true" ]]; then
|
||||
echo " - unilabos-full (complete package)"
|
||||
fi
|
||||
|
||||
@@ -131,14 +131,19 @@ 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: steps.should_build.outputs.should_build == 'true' && github.event.inputs.upload_to_anaconda == 'true'
|
||||
if: |
|
||||
steps.should_build.outputs.should_build == 'true' &&
|
||||
(
|
||||
github.event_name == 'workflow_run' ||
|
||||
github.event.inputs.upload_to_anaconda == 'true'
|
||||
)
|
||||
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)
|
||||
@@ -146,33 +151,40 @@ 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: steps.should_build.outputs.should_build == 'true' && github.event.inputs.upload_to_anaconda == 'true'
|
||||
if: |
|
||||
steps.should_build.outputs.should_build == 'true' &&
|
||||
(
|
||||
github.event_name == 'workflow_run' ||
|
||||
github.event.inputs.upload_to_anaconda == 'true'
|
||||
)
|
||||
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
|
||||
if: |
|
||||
steps.should_build.outputs.should_build == 'true' &&
|
||||
github.event_name == 'workflow_dispatch' &&
|
||||
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: |
|
||||
steps.should_build.outputs.should_build == 'true' &&
|
||||
github.event_name == 'workflow_dispatch' &&
|
||||
github.event.inputs.build_full == 'true' &&
|
||||
github.event.inputs.upload_to_anaconda == 'true'
|
||||
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
|
||||
|
||||
@@ -12,7 +12,7 @@ Uni-Lab 使用 Python 格式的配置文件（`.py`），默认为 `unilabos_dat
|
||||
|
||||
**获取方式：**
|
||||
|
||||
进入 [Uni-Lab 实验室](https://uni-lab.bohrium.com)，点击左下角的头像，在实验室详情中获取所在实验室的 ak 和 sk：
|
||||
进入 [Uni-Lab 实验室](https://leap-lab.bohrium.com)，点击左下角的头像，在实验室详情中获取所在实验室的 ak 和 sk：
|
||||
|
||||
|
||||
|
||||
@@ -69,7 +69,7 @@ class WSConfig:
|
||||
|
||||
# HTTP配置
|
||||
class HTTPConfig:
|
||||
remote_addr = "https://uni-lab.bohrium.com/api/v1" # 远程服务器地址
|
||||
remote_addr = "https://leap-lab.bohrium.com/api/v1" # 远程服务器地址
|
||||
|
||||
# ROS配置
|
||||
class ROSConfig:
|
||||
@@ -209,8 +209,8 @@ unilab --ak "key" --sk "secret" --addr "test" --upload_registry --2d_vis -g grap
|
||||
|
||||
`--addr` 参数支持以下预设值，会自动转换为对应的完整 URL：
|
||||
|
||||
- `test` → `https://uni-lab.test.bohrium.com/api/v1`
|
||||
- `uat` → `https://uni-lab.uat.bohrium.com/api/v1`
|
||||
- `test` → `https://leap-lab.test.bohrium.com/api/v1`
|
||||
- `uat` → `https://leap-lab.uat.bohrium.com/api/v1`
|
||||
- `local` → `http://127.0.0.1:48197/api/v1`
|
||||
- 其他值 → 直接使用作为完整 URL
|
||||
|
||||
@@ -248,7 +248,7 @@ unilab --ak "key" --sk "secret" --addr "test" --upload_registry --2d_vis -g grap
|
||||
|
||||
`ak` 和 `sk` 是必需的认证参数：
|
||||
|
||||
1. **获取方式**：在 [Uni-Lab 官网](https://uni-lab.bohrium.com) 注册实验室后获得
|
||||
1. **获取方式**：在 [Uni-Lab 官网](https://leap-lab.bohrium.com) 注册实验室后获得
|
||||
2. **配置方式**：
|
||||
- **命令行参数**：`--ak "your_key" --sk "your_secret"`（最高优先级，推荐）
|
||||
- **环境变量**：`UNILABOS_BASICCONFIG_AK` 和 `UNILABOS_BASICCONFIG_SK`
|
||||
@@ -276,14 +276,14 @@ WebSocket 是 Uni-Lab 的主要通信方式：
|
||||
HTTP 客户端配置用于与云端服务通信：
|
||||
|
||||
| 参数 | 类型 | 默认值 | 说明 |
|
||||
| ------------- | ---- | -------------------------------------- | ------------ |
|
||||
| `remote_addr` | str | `"https://uni-lab.bohrium.com/api/v1"` | 远程服务地址 |
|
||||
| ------------- | ---- | --------------------------------------- | ------------ |
|
||||
| `remote_addr` | str | `"https://leap-lab.bohrium.com/api/v1"` | 远程服务地址 |
|
||||
|
||||
**预设环境地址**：
|
||||
|
||||
- 生产环境：`https://uni-lab.bohrium.com/api/v1`（默认）
|
||||
- 测试环境：`https://uni-lab.test.bohrium.com/api/v1`
|
||||
- UAT 环境：`https://uni-lab.uat.bohrium.com/api/v1`
|
||||
- 生产环境：`https://leap-lab.bohrium.com/api/v1`（默认）
|
||||
- 测试环境：`https://leap-lab.test.bohrium.com/api/v1`
|
||||
- UAT 环境：`https://leap-lab.uat.bohrium.com/api/v1`
|
||||
- 本地环境：`http://127.0.0.1:48197/api/v1`
|
||||
|
||||
### 4. ROSConfig - ROS 配置
|
||||
@@ -401,7 +401,7 @@ export UNILABOS_WSCONFIG_RECONNECT_INTERVAL="10"
|
||||
export UNILABOS_WSCONFIG_MAX_RECONNECT_ATTEMPTS="500"
|
||||
|
||||
# 设置HTTP配置
|
||||
export UNILABOS_HTTPCONFIG_REMOTE_ADDR="https://uni-lab.test.bohrium.com/api/v1"
|
||||
export UNILABOS_HTTPCONFIG_REMOTE_ADDR="https://leap-lab.test.bohrium.com/api/v1"
|
||||
```
|
||||
|
||||
## 配置文件使用方法
|
||||
@@ -484,13 +484,13 @@ export UNILABOS_WSCONFIG_MAX_RECONNECT_ATTEMPTS=100
|
||||
|
||||
```python
|
||||
class HTTPConfig:
|
||||
remote_addr = "https://uni-lab.test.bohrium.com/api/v1"
|
||||
remote_addr = "https://leap-lab.test.bohrium.com/api/v1"
|
||||
```
|
||||
|
||||
**环境变量方式：**
|
||||
|
||||
```bash
|
||||
export UNILABOS_HTTPCONFIG_REMOTE_ADDR=https://uni-lab.test.bohrium.com/api/v1
|
||||
export UNILABOS_HTTPCONFIG_REMOTE_ADDR=https://leap-lab.test.bohrium.com/api/v1
|
||||
```
|
||||
|
||||
**命令行方式（推荐）：**
|
||||
|
||||
611
docs/developer_guide/add_PLC.md
Normal file
611
docs/developer_guide/add_PLC.md
Normal file
@@ -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` |
|
||||
@@ -23,7 +23,7 @@ Uni-Lab-OS 支持多种部署模式：
|
||||
```
|
||||
┌──────────────────────────────────────────────┐
|
||||
│ Cloud Platform/Self-hosted Platform │
|
||||
│ uni-lab.bohrium.com │
|
||||
│ leap-lab.bohrium.com │
|
||||
│ (Resource Management, Task Scheduling, │
|
||||
│ Monitoring) │
|
||||
└────────────────────┬─────────────────────────┘
|
||||
@@ -444,7 +444,7 @@ ros2 daemon stop && ros2 daemon start
|
||||
|
||||
```bash
|
||||
# 测试云端连接
|
||||
curl https://uni-lab.bohrium.com/api/v1/health
|
||||
curl https://leap-lab.bohrium.com/api/v1/health
|
||||
|
||||
# 测试WebSocket
|
||||
# 启动Uni-Lab后查看日志
|
||||
|
||||
@@ -34,7 +34,7 @@
|
||||
**选择合适的安装包：**
|
||||
|
||||
| 安装包 | 适用场景 | 包含组件 |
|
||||
|--------|----------|----------|
|
||||
| --------------- | ---------------------------- | --------------------------------------------- |
|
||||
| `unilabos` | **推荐大多数用户**，生产部署 | 完整安装包，开箱即用 |
|
||||
| `unilabos-env` | 开发者（可编辑安装） | 仅环境依赖，通过 pip 安装 unilabos |
|
||||
| `unilabos-full` | 仿真/可视化 | unilabos + 完整 ROS2 桌面版 + Gazebo + MoveIt |
|
||||
@@ -66,6 +66,7 @@ mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
|
||||
```
|
||||
|
||||
**选择建议：**
|
||||
|
||||
- **日常使用/生产部署**：使用 `unilabos`（推荐），完整功能，开箱即用
|
||||
- **开发者**：使用 `unilabos-env` + `pip install -e .` + `uv pip install -r unilabos/utils/requirements.txt`，代码修改立即生效
|
||||
- **仿真/可视化**：使用 `unilabos-full`，含 Gazebo、rviz2、MoveIt
|
||||
@@ -88,7 +89,7 @@ python -c "from unilabos_msgs.msg import Resource; print('ROS msgs OK')"
|
||||
|
||||
#### 2.1 注册实验室账号
|
||||
|
||||
1. 访问 [https://uni-lab.bohrium.com](https://uni-lab.bohrium.com)
|
||||
1. 访问 [https://leap-lab.bohrium.com](https://leap-lab.bohrium.com)
|
||||
2. 注册账号并登录
|
||||
3. 创建新实验室
|
||||
|
||||
@@ -297,7 +298,7 @@ unilab --ak your_ak --sk your_sk -g test/experiments/mock_devices/mock_all.json
|
||||
|
||||
#### 5.2 访问 Web 界面
|
||||
|
||||
启动系统后，访问[https://uni-lab.bohrium.com](https://uni-lab.bohrium.com)
|
||||
启动系统后，访问[https://leap-lab.bohrium.com](https://leap-lab.bohrium.com)
|
||||
|
||||
#### 5.3 添加设备和物料
|
||||
|
||||
@@ -306,12 +307,10 @@ unilab --ak your_ak --sk your_sk -g test/experiments/mock_devices/mock_all.json
|
||||
**示例场景：** 创建一个简单的液体转移实验
|
||||
|
||||
1. **添加工作站（必需）：**
|
||||
|
||||
- 在"仪器设备"中找到 `work_station`
|
||||
- 添加 `workstation` x1
|
||||
|
||||
2. **添加虚拟转移泵：**
|
||||
|
||||
- 在"仪器设备"中找到 `virtual_device`
|
||||
- 添加 `virtual_transfer_pump` x1
|
||||
|
||||
@@ -818,6 +817,7 @@ uv pip install -r unilabos/utils/requirements.txt
|
||||
```
|
||||
|
||||
**为什么使用这种方式？**
|
||||
|
||||
- `unilabos-env` 提供 ROS2 核心组件和 uv（通过 conda 安装，避免编译）
|
||||
- `unilabos/utils/requirements.txt` 包含所有运行时需要的 pip 依赖
|
||||
- `dev_install.py` 自动检测中文环境，中文系统自动使用清华镜像
|
||||
@@ -1796,32 +1796,27 @@ unilab --ak your_ak --sk your_sk -g graph.json \
|
||||
**详细步骤：**
|
||||
|
||||
1. **需求分析**：
|
||||
|
||||
- 明确实验流程
|
||||
- 列出所需设备和物料
|
||||
- 设计工作流程图
|
||||
|
||||
2. **环境搭建**：
|
||||
|
||||
- 安装 Uni-Lab-OS
|
||||
- 创建实验室账号
|
||||
- 准备开发工具（IDE、Git）
|
||||
|
||||
3. **原型验证**：
|
||||
|
||||
- 使用虚拟设备测试流程
|
||||
- 验证工作流逻辑
|
||||
- 调整参数
|
||||
|
||||
4. **迭代开发**：
|
||||
|
||||
- 实现自定义设备驱动（同时撰写单点函数测试）
|
||||
- 编写注册表
|
||||
- 单元测试
|
||||
- 集成测试
|
||||
|
||||
5. **测试部署**：
|
||||
|
||||
- 连接真实硬件
|
||||
- 空跑测试
|
||||
- 小规模试验
|
||||
@@ -1871,7 +1866,7 @@ unilab --ak your_ak --sk your_sk -g graph.json \
|
||||
#### 14.5 社区支持
|
||||
|
||||
- **GitHub Issues**：[https://github.com/deepmodeling/Uni-Lab-OS/issues](https://github.com/deepmodeling/Uni-Lab-OS/issues)
|
||||
- **官方网站**：[https://uni-lab.bohrium.com](https://uni-lab.bohrium.com)
|
||||
- **官方网站**：[https://leap-lab.bohrium.com](https://leap-lab.bohrium.com)
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -626,7 +626,7 @@ unilab
|
||||
|
||||
**云端图文件管理**:
|
||||
|
||||
1. 登录 https://uni-lab.bohrium.com
|
||||
1. 登录 https://leap-lab.bohrium.com
|
||||
2. 进入"设备配置"
|
||||
3. 创建或编辑配置
|
||||
4. 保存到云端
|
||||
|
||||
@@ -54,7 +54,6 @@ Uni-Lab 的启动过程分为以下几个阶段：
|
||||
您可以直接跟随 unilabos 的提示进行，无需查阅本节
|
||||
|
||||
- **工作目录设置**：
|
||||
|
||||
- 如果当前目录以 `unilabos_data` 结尾，则使用当前目录
|
||||
- 否则使用 `当前目录/unilabos_data` 作为工作目录
|
||||
- 可通过 `--working_dir` 指定自定义工作目录
|
||||
@@ -68,8 +67,8 @@ Uni-Lab 的启动过程分为以下几个阶段：
|
||||
|
||||
支持多种后端环境：
|
||||
|
||||
- `--addr test`：测试环境 (`https://uni-lab.test.bohrium.com/api/v1`)
|
||||
- `--addr uat`：UAT 环境 (`https://uni-lab.uat.bohrium.com/api/v1`)
|
||||
- `--addr test`：测试环境 (`https://leap-lab.test.bohrium.com/api/v1`)
|
||||
- `--addr uat`：UAT 环境 (`https://leap-lab.uat.bohrium.com/api/v1`)
|
||||
- `--addr local`：本地环境 (`http://127.0.0.1:48197/api/v1`)
|
||||
- 自定义地址：直接指定完整 URL
|
||||
|
||||
@@ -176,7 +175,7 @@ unilab --config path/to/your/config.py
|
||||
|
||||
如果是首次使用，系统会：
|
||||
|
||||
1. 提示前往 https://uni-lab.bohrium.com 注册实验室
|
||||
1. 提示前往 https://leap-lab.bohrium.com 注册实验室
|
||||
2. 引导创建配置文件
|
||||
3. 设置工作目录
|
||||
|
||||
@@ -216,7 +215,7 @@ unilab --ak your_ak --sk your_sk --port 8080 --disable_browser
|
||||
|
||||
如果提示 "后续运行必须拥有一个实验室"，请确保：
|
||||
|
||||
- 已在 https://uni-lab.bohrium.com 注册实验室
|
||||
- 已在 https://leap-lab.bohrium.com 注册实验室
|
||||
- 正确设置了 `--ak` 和 `--sk` 参数
|
||||
- 配置文件中包含正确的认证信息
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
channel_sources:
|
||||
- robostack,robostack-staging,conda-forge,defaults
|
||||
- robostack,robostack-staging,conda-forge
|
||||
|
||||
gazebo:
|
||||
- '11'
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
package:
|
||||
name: ros-humble-unilabos-msgs
|
||||
version: 0.10.19
|
||||
version: 0.11.3
|
||||
source:
|
||||
path: ../../unilabos_msgs
|
||||
target_directory: src
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
package:
|
||||
name: unilabos
|
||||
version: "0.10.19"
|
||||
version: "0.11.3"
|
||||
|
||||
source:
|
||||
path: ../..
|
||||
|
||||
2
setup.py
2
setup.py
@@ -4,7 +4,7 @@ package_name = 'unilabos'
|
||||
|
||||
setup(
|
||||
name=package_name,
|
||||
version='0.10.19',
|
||||
version='0.11.3',
|
||||
packages=find_packages(),
|
||||
include_package_data=True,
|
||||
install_requires=['setuptools'],
|
||||
|
||||
@@ -1 +1 @@
|
||||
__version__ = "0.10.19"
|
||||
__version__ = "0.11.3"
|
||||
|
||||
@@ -12,6 +12,15 @@ from typing import Dict, Any, List
|
||||
import networkx as nx
|
||||
import yaml
|
||||
|
||||
# Windows 中文系统 stdout 默认 GBK，无法编码 banner / emoji 日志中的 Unicode 字符
|
||||
# 强制 stdout/stderr 用 UTF-8，避免 print 触发 UnicodeEncodeError 导致进程崩溃
|
||||
if sys.platform == "win32":
|
||||
for _stream in (sys.stdout, sys.stderr):
|
||||
try:
|
||||
_stream.reconfigure(encoding="utf-8", errors="replace") # type: ignore[attr-defined]
|
||||
except (AttributeError, OSError):
|
||||
pass
|
||||
|
||||
# 首先添加项目根目录到路径
|
||||
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
unilabos_dir = os.path.dirname(os.path.dirname(current_dir))
|
||||
@@ -233,7 +242,7 @@ def parse_args():
|
||||
parser.add_argument(
|
||||
"--addr",
|
||||
type=str,
|
||||
default="https://uni-lab.bohrium.com/api/v1",
|
||||
default="https://leap-lab.bohrium.com/api/v1",
|
||||
help="Laboratory backend address",
|
||||
)
|
||||
parser.add_argument(
|
||||
@@ -438,10 +447,10 @@ def main():
|
||||
if args.addr != parser.get_default("addr"):
|
||||
if args.addr == "test":
|
||||
print_status("使用测试环境地址", "info")
|
||||
HTTPConfig.remote_addr = "https://uni-lab.test.bohrium.com/api/v1"
|
||||
HTTPConfig.remote_addr = "https://leap-lab.test.bohrium.com/api/v1"
|
||||
elif args.addr == "uat":
|
||||
print_status("使用uat环境地址", "info")
|
||||
HTTPConfig.remote_addr = "https://uni-lab.uat.bohrium.com/api/v1"
|
||||
HTTPConfig.remote_addr = "https://leap-lab.uat.bohrium.com/api/v1"
|
||||
elif args.addr == "local":
|
||||
print_status("使用本地环境地址", "info")
|
||||
HTTPConfig.remote_addr = "http://127.0.0.1:48197/api/v1"
|
||||
@@ -553,7 +562,7 @@ def main():
|
||||
os._exit(0)
|
||||
|
||||
if not BasicConfig.ak or not BasicConfig.sk:
|
||||
print_status("后续运行必须拥有一个实验室，请前往 https://uni-lab.bohrium.com 注册实验室！", "warning")
|
||||
print_status("后续运行必须拥有一个实验室，请前往 https://leap-lab.bohrium.com 注册实验室！", "warning")
|
||||
os._exit(1)
|
||||
graph: nx.Graph
|
||||
resource_tree_set: ResourceTreeSet
|
||||
|
||||
@@ -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)",
|
||||
|
||||
@@ -10,29 +10,170 @@ import shutil
|
||||
import sys
|
||||
|
||||
|
||||
_PATCH_MARKER = "# UniLabOS DLL Patch"
|
||||
_PATCH_END_MARKER = "# End UniLabOS DLL Patch"
|
||||
|
||||
# 75 = EX_TEMPFAIL: 临时失败、重试即可，避免与业务退出码冲突
|
||||
_RESTART_EXIT_CODE = 75
|
||||
|
||||
|
||||
def _build_dll_patch(lib_bin: str, preload_pyd: str = "") -> str:
|
||||
"""生成一段加在目标文件顶部的 DLL 加载补丁源码。
|
||||
|
||||
- 始终把 ``lib_bin`` 加入 DLL 搜索路径，并把 handle 挂在模块属性上，
|
||||
防止 GC 清掉搜索路径（``os.add_dll_directory`` 的句柄被回收时
|
||||
目录会被移除）。
|
||||
- 可选地用 ``ctypes.CDLL`` 预加载一个 .pyd，把它的依赖 DLL 提前装入
|
||||
进程内存，作为 ``rclpy._rclpy_pybind11`` 这类首次加载点的兜底。
|
||||
"""
|
||||
# 用 repr() 序列化路径：Python 解析 repr 的结果会还原成原始字符串，
|
||||
# 不需要也不能再叠加 raw-string 前缀（叠了反而会让 \\ 变成两个反斜杠）。
|
||||
lines = [
|
||||
_PATCH_MARKER,
|
||||
"import os as _ulab_os",
|
||||
f"_ulab_p = {lib_bin!r}",
|
||||
'if hasattr(_ulab_os, "add_dll_directory") and _ulab_os.path.isdir(_ulab_p):',
|
||||
" try: _UNILAB_DLL_HANDLE = _ulab_os.add_dll_directory(_ulab_p)",
|
||||
" except Exception: _UNILAB_DLL_HANDLE = None",
|
||||
]
|
||||
if preload_pyd:
|
||||
lines.extend(
|
||||
[
|
||||
"import ctypes as _ulab_ctypes",
|
||||
f"try: _ulab_ctypes.CDLL({preload_pyd!r})",
|
||||
"except Exception: pass",
|
||||
]
|
||||
)
|
||||
lines.append(_PATCH_END_MARKER)
|
||||
return "\n".join(lines) + "\n"
|
||||
|
||||
|
||||
def _apply_dll_patch(file_path: str, lib_bin: str, preload_pyd: str = "") -> bool:
|
||||
"""把 DLL 补丁前置到 ``file_path``。文件不存在或已打过补丁则返回 False。"""
|
||||
if not os.path.isfile(file_path):
|
||||
return False
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
if _PATCH_MARKER in content:
|
||||
return False
|
||||
shutil.copy2(file_path, file_path + ".bak")
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
f.write(_build_dll_patch(lib_bin, preload_pyd) + content)
|
||||
return True
|
||||
|
||||
|
||||
def _print_restart_banner(patched_files):
|
||||
"""打印重启提示并以 EX_TEMPFAIL 退出。
|
||||
|
||||
- 不使用 ANSI 颜色码：Windows 旧版 cmd / PowerShell 5 默认不开 VT 处理，
|
||||
会把 ``\\033[1;33m`` 当做字面字符显示，反而让用户看不到正文。
|
||||
- 同时写入 stderr 与 stdout：某些上层 launcher / supervisor 只重定向
|
||||
其中一路，写两遍能保证用户至少看到一份。
|
||||
- 写入前防御性把流切到 UTF-8 with replace：``main.py`` 里已经做过一次，
|
||||
但本模块也可能被绕过 ``main.py`` 的代码路径直接 import；reconfigure
|
||||
失败也只是退回 errors=replace，不影响整体流程。
|
||||
"""
|
||||
if sys.platform == "win32":
|
||||
for _stream in (sys.stdout, sys.stderr):
|
||||
try:
|
||||
_stream.reconfigure(encoding="utf-8", errors="replace") # type: ignore[attr-defined]
|
||||
except (AttributeError, OSError):
|
||||
pass
|
||||
|
||||
bar = "#" * 78
|
||||
files_lines = [f"[UniLabOS] - {p}" for p in patched_files]
|
||||
body = "\n".join(
|
||||
[
|
||||
"",
|
||||
bar,
|
||||
bar,
|
||||
"##",
|
||||
"## [UniLabOS] Windows + conda 下检测到 DLL 加载失败，已自动打补丁。",
|
||||
"## [UniLabOS] DLL load failure detected on Windows + conda;",
|
||||
"## [UniLabOS] the following files have been auto-patched:",
|
||||
"##",
|
||||
*[f"## {line}" for line in files_lines],
|
||||
"##",
|
||||
"## [UniLabOS] 当前进程的 rclpy 状态已损坏，补丁需要在新进程才生效。",
|
||||
"## [UniLabOS] The current process is unusable; the patch only takes",
|
||||
"## [UniLabOS] effect on a fresh process.",
|
||||
"##",
|
||||
"## >>> 请重新运行刚才的命令 / Please re-run the same command. <<<",
|
||||
"##",
|
||||
bar,
|
||||
bar,
|
||||
"",
|
||||
]
|
||||
)
|
||||
|
||||
for stream in (sys.stderr, sys.stdout):
|
||||
try:
|
||||
stream.write(body)
|
||||
stream.flush()
|
||||
except Exception:
|
||||
try:
|
||||
print(body, file=stream)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
sys.exit(_RESTART_EXIT_CODE)
|
||||
|
||||
|
||||
def patch_rclpy_dll_windows():
|
||||
"""在 Windows + conda 环境下为 rclpy 打 DLL 加载补丁"""
|
||||
"""在 Windows + conda 环境下修复 rclpy / rosidl typesupport 的 DLL 加载。
|
||||
|
||||
背景：conda 安装的 ros 系列包，其原生扩展依赖 ``$CONDA_PREFIX/Library/bin``
|
||||
下的 DLL；只有 conda 环境被正确激活、且 PATH 中含 ``Library/bin`` 时，
|
||||
``os.add_dll_directory`` 才能找到它们。当从快捷方式 / IDE / 子进程 /
|
||||
没激活的 shell 启动 ``unilab`` 时，会出现 ``DLL load failed``。
|
||||
|
||||
本函数会:
|
||||
1) 修补 ``rclpy/impl/implementation_singleton.py`` —— rclpy 自身的 C 扩展入口；
|
||||
2) 修补 ``rpyutils/add_dll_directories.py`` —— 所有 ``*_s__rosidl_typesupport_c.pyd``
|
||||
（``geometry_msgs`` / ``std_msgs`` / ``sensor_msgs`` 等）的统一加载入口。
|
||||
|
||||
打完补丁后**必须重启进程**才能生效（当前进程的 rclpy 已经发生过
|
||||
``ImportError``，子模块仍处于损坏状态）。因此函数会主动退出，并在
|
||||
stdout/stderr 同时打印明显的重启提示，避免用户被后续报错淹没。
|
||||
"""
|
||||
if sys.platform != "win32" or not os.environ.get("CONDA_PREFIX"):
|
||||
return
|
||||
|
||||
try:
|
||||
import rclpy
|
||||
import rclpy # noqa: F401
|
||||
|
||||
return
|
||||
except ImportError as e:
|
||||
if not str(e).startswith("DLL load failed"):
|
||||
return
|
||||
|
||||
cp = os.environ["CONDA_PREFIX"]
|
||||
impl = os.path.join(cp, "Lib", "site-packages", "rclpy", "impl", "implementation_singleton.py")
|
||||
pyd = glob.glob(os.path.join(cp, "Lib", "site-packages", "rclpy", "_rclpy_pybind11*.pyd"))
|
||||
if not os.path.exists(impl) or not pyd:
|
||||
lib_bin = os.path.join(cp, "Library", "bin")
|
||||
site_packages = os.path.join(cp, "Lib", "site-packages")
|
||||
if not os.path.isdir(lib_bin):
|
||||
return
|
||||
with open(impl, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
lib_bin = os.path.join(cp, "Library", "bin").replace("\\", "/")
|
||||
patch = f'# UniLabOS DLL Patch\nimport os,ctypes\nos.add_dll_directory("{lib_bin}") if hasattr(os,"add_dll_directory") else None\ntry: ctypes.CDLL("{pyd[0].replace(chr(92),"/")}")\nexcept: pass\n# End Patch\n'
|
||||
shutil.copy2(impl, impl + ".bak")
|
||||
with open(impl, "w", encoding="utf-8") as f:
|
||||
f.write(patch + content)
|
||||
|
||||
patched = []
|
||||
|
||||
# 1) rclpy 自身的入口
|
||||
rclpy_impl = os.path.join(site_packages, "rclpy", "impl", "implementation_singleton.py")
|
||||
rclpy_pyd_matches = glob.glob(os.path.join(site_packages, "rclpy", "_rclpy_pybind11*.pyd"))
|
||||
rclpy_pyd = rclpy_pyd_matches[0] if rclpy_pyd_matches else ""
|
||||
if rclpy_pyd and _apply_dll_patch(rclpy_impl, lib_bin, preload_pyd=rclpy_pyd):
|
||||
patched.append(rclpy_impl)
|
||||
|
||||
# 2) rpyutils —— 所有 rosidl typesupport pyd 的加载点；放在 rclpy 之后
|
||||
# 例：geometry_msgs/geometry_msgs_s__rosidl_typesupport_c.pyd
|
||||
rpyutils_dll = os.path.join(site_packages, "rpyutils", "add_dll_directories.py")
|
||||
if _apply_dll_patch(rpyutils_dll, lib_bin):
|
||||
patched.append(rpyutils_dll)
|
||||
|
||||
if not patched:
|
||||
# 已经打过补丁但 rclpy 仍然加载失败：原因不是缺 DLL 搜索路径，
|
||||
# 不要再次打补丁污染文件，让上层看到真实的 ImportError。
|
||||
return
|
||||
|
||||
_print_restart_banner(patched)
|
||||
|
||||
|
||||
patch_rclpy_dll_windows()
|
||||
|
||||
@@ -36,6 +36,9 @@ class HTTPClient:
|
||||
auth_secret = BasicConfig.auth_secret()
|
||||
self.auth = auth_secret
|
||||
info(f"正在使用ak sk作为授权信息：[{auth_secret}]")
|
||||
# 复用 TCP/TLS 连接，避免每次请求重新握手
|
||||
self._session = requests.Session()
|
||||
self._session.headers.update({"Authorization": f"Lab {self.auth}"})
|
||||
info(f"HTTPClient 初始化完成: remote_addr={self.remote_addr}")
|
||||
|
||||
def resource_edge_add(self, resources: List[Dict[str, Any]]) -> requests.Response:
|
||||
@@ -48,7 +51,7 @@ class HTTPClient:
|
||||
Returns:
|
||||
Response: API响应对象
|
||||
"""
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/edge/material/edge",
|
||||
json={
|
||||
"edges": resources,
|
||||
@@ -75,26 +78,28 @@ class HTTPClient:
|
||||
Returns:
|
||||
Dict[str, str]: 旧UUID到新UUID的映射关系 {old_uuid: new_uuid}
|
||||
"""
|
||||
with open(os.path.join(BasicConfig.working_dir, "req_resource_tree_add.json"), "w", encoding="utf-8") as f:
|
||||
payload = {"nodes": [x for xs in resources.dump() for x in xs], "mount_uuid": mount_uuid}
|
||||
f.write(json.dumps(payload, indent=4))
|
||||
# 从序列化数据中提取所有节点的UUID（保存旧UUID）
|
||||
old_uuids = {n.res_content.uuid: n for n in resources.all_nodes}
|
||||
# dump() 只调用一次，复用给文件保存和 HTTP 请求
|
||||
nodes_info = [x for xs in resources.dump() for x in xs]
|
||||
old_uuids = {n.res_content.uuid: n for n in resources.all_nodes}
|
||||
payload = {"nodes": nodes_info, "mount_uuid": mount_uuid}
|
||||
body_bytes = _fast_dumps(payload)
|
||||
with open(os.path.join(BasicConfig.working_dir, "req_resource_tree_add.json"), "wb") as f:
|
||||
f.write(_fast_dumps_pretty(payload))
|
||||
http_headers = {"Content-Type": "application/json"}
|
||||
if not self.initialized or first_add:
|
||||
self.initialized = True
|
||||
info(f"首次添加资源，当前远程地址: {self.remote_addr}")
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/edge/material",
|
||||
json={"nodes": nodes_info, "mount_uuid": mount_uuid},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
data=body_bytes,
|
||||
headers=http_headers,
|
||||
timeout=60,
|
||||
)
|
||||
else:
|
||||
response = requests.put(
|
||||
response = self._session.put(
|
||||
f"{self.remote_addr}/edge/material",
|
||||
json={"nodes": nodes_info, "mount_uuid": mount_uuid},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
data=body_bytes,
|
||||
headers=http_headers,
|
||||
timeout=10,
|
||||
)
|
||||
|
||||
@@ -133,7 +138,7 @@ class HTTPClient:
|
||||
"""
|
||||
with open(os.path.join(BasicConfig.working_dir, "req_resource_tree_get.json"), "w", encoding="utf-8") as f:
|
||||
f.write(json.dumps({"uuids": uuid_list, "with_children": with_children}, indent=4))
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/edge/material/query",
|
||||
json={"uuids": uuid_list, "with_children": with_children},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
@@ -147,6 +152,7 @@ class HTTPClient:
|
||||
logger.error(f"查询物料失败: {response.text}")
|
||||
else:
|
||||
data = res["data"]["nodes"]
|
||||
logger.trace(f"resource_tree_get查询到物料: {data}")
|
||||
return data
|
||||
else:
|
||||
logger.error(f"查询物料失败: {response.text}")
|
||||
@@ -164,14 +170,14 @@ class HTTPClient:
|
||||
if not self.initialized:
|
||||
self.initialized = True
|
||||
info(f"首次添加资源，当前远程地址: {self.remote_addr}")
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/lab/material",
|
||||
json={"nodes": resources},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
timeout=100,
|
||||
)
|
||||
else:
|
||||
response = requests.put(
|
||||
response = self._session.put(
|
||||
f"{self.remote_addr}/lab/material",
|
||||
json={"nodes": resources},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
@@ -198,7 +204,7 @@ class HTTPClient:
|
||||
"""
|
||||
with open(os.path.join(BasicConfig.working_dir, "req_resource_get.json"), "w", encoding="utf-8") as f:
|
||||
f.write(json.dumps({"id": id, "with_children": with_children}, indent=4))
|
||||
response = requests.get(
|
||||
response = self._session.get(
|
||||
f"{self.remote_addr}/lab/material",
|
||||
params={"id": id, "with_children": with_children},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
@@ -239,14 +245,14 @@ class HTTPClient:
|
||||
if not self.initialized:
|
||||
self.initialized = True
|
||||
info(f"首次添加资源，当前远程地址: {self.remote_addr}")
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/lab/material",
|
||||
json={"nodes": resources},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
timeout=100,
|
||||
)
|
||||
else:
|
||||
response = requests.put(
|
||||
response = self._session.put(
|
||||
f"{self.remote_addr}/lab/material",
|
||||
json={"nodes": resources},
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
@@ -276,7 +282,7 @@ class HTTPClient:
|
||||
with open(file_path, "rb") as file:
|
||||
files = {"files": file}
|
||||
logger.info(f"上传文件: {file_path} 到 {scene}")
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/api/account/file_upload/{scene}",
|
||||
files=files,
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
@@ -316,7 +322,7 @@ class HTTPClient:
|
||||
"Content-Type": "application/json",
|
||||
"Content-Encoding": "gzip",
|
||||
}
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/lab/resource",
|
||||
data=compressed_body,
|
||||
headers=headers,
|
||||
@@ -350,7 +356,7 @@ class HTTPClient:
|
||||
Returns:
|
||||
Response: API响应对象
|
||||
"""
|
||||
response = requests.get(
|
||||
response = self._session.get(
|
||||
f"{self.remote_addr}/edge/material/download",
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
timeout=(3, 30),
|
||||
@@ -411,7 +417,7 @@ class HTTPClient:
|
||||
with open(os.path.join(BasicConfig.working_dir, "req_workflow_upload.json"), "w", encoding="utf-8") as f:
|
||||
f.write(json.dumps(payload, indent=4, ensure_ascii=False))
|
||||
|
||||
response = requests.post(
|
||||
response = self._session.post(
|
||||
f"{self.remote_addr}/lab/workflow/owner/import",
|
||||
json=payload,
|
||||
headers={"Authorization": f"Lab {self.auth}"},
|
||||
|
||||
@@ -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,
|
||||
)
|
||||
|
||||
|
||||
@@ -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,
|
||||
},
|
||||
@@ -1269,7 +1320,13 @@ class QueueProcessor:
|
||||
if not queued_jobs:
|
||||
return
|
||||
|
||||
logger.debug(f"[QueueProcessor] Sending busy status for {len(queued_jobs)} queued jobs")
|
||||
queue_summary = {}
|
||||
for j in queued_jobs:
|
||||
key = f"{j.device_id}/{j.action_name}"
|
||||
queue_summary[key] = queue_summary.get(key, 0) + 1
|
||||
logger.debug(
|
||||
f"[QueueProcessor] Sending busy status for {len(queued_jobs)} queued jobs: {queue_summary}"
|
||||
)
|
||||
|
||||
for job_info in queued_jobs:
|
||||
# 快照可能已过期：在遍历过程中 end_job() 可能已将此 job 移至 READY，
|
||||
@@ -1285,6 +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,
|
||||
},
|
||||
@@ -1330,12 +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
|
||||
@@ -1504,6 +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,
|
||||
|
||||
@@ -46,7 +46,7 @@ class WSConfig:
|
||||
|
||||
# HTTP配置
|
||||
class HTTPConfig:
|
||||
remote_addr = "https://uni-lab.bohrium.com/api/v1"
|
||||
remote_addr = "https://leap-lab.bohrium.com/api/v1"
|
||||
|
||||
|
||||
# ROS配置
|
||||
|
||||
@@ -2,6 +2,8 @@ import time
|
||||
import logging
|
||||
from typing import Union, Dict, Optional
|
||||
|
||||
from unilabos.registry.decorators import topic_config
|
||||
|
||||
|
||||
class VirtualMultiwayValve:
|
||||
"""
|
||||
@@ -41,13 +43,11 @@ class VirtualMultiwayValve:
|
||||
def target_position(self) -> int:
|
||||
return self._target_position
|
||||
|
||||
def get_current_position(self) -> int:
|
||||
"""获取当前阀门位置 📍"""
|
||||
return self._current_position
|
||||
|
||||
def get_current_port(self) -> str:
|
||||
"""获取当前连接的端口名称 🔌"""
|
||||
return self._current_position
|
||||
@property
|
||||
@topic_config()
|
||||
def current_port(self) -> str:
|
||||
"""当前连接的端口名称 🔌"""
|
||||
return self.port
|
||||
|
||||
def set_position(self, command: Union[int, str]):
|
||||
"""
|
||||
@@ -169,12 +169,14 @@ class VirtualMultiwayValve:
|
||||
self._status = "Idle"
|
||||
self._valve_state = "Closed"
|
||||
|
||||
close_msg = f"🔒 阀门已关闭，保持在位置 {self._current_position} ({self.get_current_port()})"
|
||||
close_msg = f"🔒 阀门已关闭，保持在位置 {self._current_position} ({self.port})"
|
||||
self.logger.info(close_msg)
|
||||
return close_msg
|
||||
|
||||
def get_valve_position(self) -> int:
|
||||
"""获取阀门位置 - 兼容性方法 📍"""
|
||||
@property
|
||||
@topic_config()
|
||||
def valve_position(self) -> int:
|
||||
"""阀门位置 📍"""
|
||||
return self._current_position
|
||||
|
||||
def set_valve_position(self, command: Union[int, str]):
|
||||
@@ -229,19 +231,16 @@ class VirtualMultiwayValve:
|
||||
self.logger.info(f"🔄 从端口 {self._current_position} 切换到泵位置...")
|
||||
return self.set_to_pump_position()
|
||||
|
||||
def get_flow_path(self) -> str:
|
||||
"""获取当前流路路径描述 🌊"""
|
||||
current_port = self.get_current_port()
|
||||
@property
|
||||
@topic_config()
|
||||
def flow_path(self) -> str:
|
||||
"""当前流路路径描述 🌊"""
|
||||
if self._current_position == 0:
|
||||
flow_path = f"🚰 转移泵已连接 (位置 {self._current_position})"
|
||||
else:
|
||||
flow_path = f"🔌 端口 {self._current_position} 已连接 ({current_port})"
|
||||
|
||||
# 删除debug日志：self.logger.debug(f"🌊 当前流路: {flow_path}")
|
||||
return flow_path
|
||||
return f"🚰 转移泵已连接 (位置 {self._current_position})"
|
||||
return f"🔌 端口 {self._current_position} 已连接 ({self.current_port})"
|
||||
|
||||
def __str__(self):
|
||||
current_port = self.get_current_port()
|
||||
current_port = self.current_port
|
||||
status_emoji = "✅" if self._status == "Idle" else "🔄" if self._status == "Busy" else "❌"
|
||||
|
||||
return f"🔄 VirtualMultiwayValve({status_emoji} 位置: {self._current_position}/{self.max_positions}, 端口: {current_port}, 状态: {self._status})"
|
||||
@@ -253,7 +252,7 @@ if __name__ == "__main__":
|
||||
|
||||
print("🔄 === 虚拟九通阀门测试 === ✨")
|
||||
print(f"🏠 初始状态: {valve}")
|
||||
print(f"🌊 当前流路: {valve.get_flow_path()}")
|
||||
print(f"🌊 当前流路: {valve.flow_path}")
|
||||
|
||||
# 切换到试剂瓶1（1号位）
|
||||
print(f"\n🔌 切换到1号位: {valve.set_position(1)}")
|
||||
|
||||
@@ -3,6 +3,7 @@ import logging
|
||||
import time as time_module
|
||||
from typing import Dict, Any
|
||||
|
||||
from unilabos.registry.decorators import topic_config
|
||||
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
|
||||
|
||||
class VirtualStirrer:
|
||||
@@ -314,9 +315,11 @@ class VirtualStirrer:
|
||||
def min_speed(self) -> float:
|
||||
return self._min_speed
|
||||
|
||||
def get_device_info(self) -> Dict[str, Any]:
|
||||
"""获取设备状态信息 📊"""
|
||||
info = {
|
||||
@property
|
||||
@topic_config()
|
||||
def device_info(self) -> Dict[str, Any]:
|
||||
"""设备状态快照信息 📊"""
|
||||
return {
|
||||
"device_id": self.device_id,
|
||||
"status": self.status,
|
||||
"operation_mode": self.operation_mode,
|
||||
@@ -325,12 +328,9 @@ class VirtualStirrer:
|
||||
"is_stirring": self.is_stirring,
|
||||
"remaining_time": self.remaining_time,
|
||||
"max_speed": self._max_speed,
|
||||
"min_speed": self._min_speed
|
||||
"min_speed": self._min_speed,
|
||||
}
|
||||
|
||||
# self.logger.debug(f"📊 设备信息: 模式={self.operation_mode}, 速度={self.current_speed} RPM, 搅拌={self.is_stirring}")
|
||||
return info
|
||||
|
||||
def __str__(self):
|
||||
status_emoji = "✅" if self.operation_mode == "Idle" else "🌪️" if self.operation_mode == "Stirring" else "🛑" if self.operation_mode == "Settling" else "❌"
|
||||
return f"🌪️ VirtualStirrer({status_emoji} {self.device_id}: {self.operation_mode}, {self.current_speed} RPM)"
|
||||
@@ -4,6 +4,7 @@ from enum import Enum
|
||||
from typing import Union, Optional
|
||||
import logging
|
||||
|
||||
from unilabos.registry.decorators import topic_config
|
||||
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
|
||||
|
||||
|
||||
@@ -385,8 +386,10 @@ class VirtualTransferPump:
|
||||
"""获取当前体积"""
|
||||
return self._current_volume
|
||||
|
||||
def get_remaining_capacity(self) -> float:
|
||||
"""获取剩余容量"""
|
||||
@property
|
||||
@topic_config()
|
||||
def remaining_capacity(self) -> float:
|
||||
"""剩余容量 (ml)"""
|
||||
return self.max_volume - self._current_volume
|
||||
|
||||
def is_empty(self) -> bool:
|
||||
|
||||
@@ -14,19 +14,30 @@ Virtual Workbench Device - 模拟工作台设备
|
||||
|
||||
import logging
|
||||
import time
|
||||
from typing import Dict, Any, Optional, List
|
||||
from dataclasses import dataclass
|
||||
from enum import Enum
|
||||
from threading import Lock, RLock
|
||||
from typing import Any, Dict, List, Optional, cast
|
||||
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from unilabos.registry.decorators import (
|
||||
device, action, ActionInputHandle, ActionOutputHandle, DataSource, topic_config, not_action
|
||||
ActionInputHandle,
|
||||
ActionOutputHandle,
|
||||
DataSource,
|
||||
NodeType,
|
||||
action,
|
||||
device,
|
||||
not_action,
|
||||
topic_config,
|
||||
)
|
||||
from unilabos.registry.placeholder_type import ResourceSlot, DeviceSlot
|
||||
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode, ROS2DeviceNode
|
||||
from unilabos.resources.resource_tracker import (
|
||||
SampleUUIDsType,
|
||||
LabSample,
|
||||
ResourceTreeSet,
|
||||
)
|
||||
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
|
||||
from unilabos.resources.resource_tracker import SampleUUIDsType, LabSample
|
||||
|
||||
|
||||
# ============ TypedDict 返回类型定义 ============
|
||||
|
||||
@@ -111,6 +122,7 @@ class HeatingStation:
|
||||
|
||||
@device(
|
||||
id="virtual_workbench",
|
||||
display_name="虚拟工作台",
|
||||
category=["virtual_device"],
|
||||
description="Virtual Workbench with 1 robotic arm and 3 heating stations for concurrent material processing",
|
||||
)
|
||||
@@ -136,7 +148,19 @@ class VirtualWorkbench:
|
||||
HEATING_TIME: float = 60.0 # 加热时间(秒)
|
||||
NUM_HEATING_STATIONS: int = 3 # 加热台数量
|
||||
|
||||
def __init__(self, device_id: Optional[str] = None, config: Optional[Dict[str, Any]] = None, **kwargs):
|
||||
def __init__(
|
||||
self,
|
||||
device_id: Optional[str] = None,
|
||||
config: Optional[Dict[str, Any]] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""
|
||||
初始化虚拟工作台。
|
||||
|
||||
Args:
|
||||
device_id[设备ID]: 工作台设备实例 ID，默认使用 virtual_workbench。
|
||||
config[设备配置]: 可包含 arm_operation_time、heating_time、num_heating_stations。
|
||||
"""
|
||||
# 处理可能的不同调用方式
|
||||
if device_id is None and "id" in kwargs:
|
||||
device_id = kwargs.pop("id")
|
||||
@@ -150,9 +174,13 @@ class VirtualWorkbench:
|
||||
self.data: Dict[str, Any] = {}
|
||||
|
||||
# 从config中获取可配置参数
|
||||
self.ARM_OPERATION_TIME = float(self.config.get("arm_operation_time", self.ARM_OPERATION_TIME))
|
||||
self.ARM_OPERATION_TIME = float(
|
||||
self.config.get("arm_operation_time", self.ARM_OPERATION_TIME)
|
||||
)
|
||||
self.HEATING_TIME = float(self.config.get("heating_time", self.HEATING_TIME))
|
||||
self.NUM_HEATING_STATIONS = int(self.config.get("num_heating_stations", self.NUM_HEATING_STATIONS))
|
||||
self.NUM_HEATING_STATIONS = int(
|
||||
self.config.get("num_heating_stations", self.NUM_HEATING_STATIONS)
|
||||
)
|
||||
|
||||
# 机械臂状态和锁
|
||||
self._arm_lock = Lock()
|
||||
@@ -161,7 +189,8 @@ class VirtualWorkbench:
|
||||
|
||||
# 加热台状态
|
||||
self._heating_stations: Dict[int, HeatingStation] = {
|
||||
i: HeatingStation(station_id=i) for i in range(1, self.NUM_HEATING_STATIONS + 1)
|
||||
i: HeatingStation(station_id=i)
|
||||
for i in range(1, self.NUM_HEATING_STATIONS + 1)
|
||||
}
|
||||
self._stations_lock = RLock()
|
||||
|
||||
@@ -290,20 +319,292 @@ class VirtualWorkbench:
|
||||
self._update_data_status(f"机械臂已释放 (完成: {task})")
|
||||
self.logger.info(f"机械臂已释放 (完成: {task})")
|
||||
|
||||
@action(
|
||||
always_free=True,
|
||||
node_type=NodeType.MANUAL_CONFIRM,
|
||||
placeholder_keys={"assignee_user_ids": "unilabos_manual_confirm"},
|
||||
goal_default={"timeout_seconds": 3600, "assignee_user_ids": []},
|
||||
feedback_interval=300,
|
||||
handles=[
|
||||
ActionInputHandle(
|
||||
key="target_device",
|
||||
data_type="device_id",
|
||||
label="目标设备",
|
||||
data_key="target_device",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="resource",
|
||||
data_type="resource",
|
||||
label="待转移资源",
|
||||
data_key="resource",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="mount_resource",
|
||||
data_type="resource",
|
||||
label="目标孔位",
|
||||
data_key="mount_resource",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="collector_mass",
|
||||
data_type="collector_mass",
|
||||
label="极流体质量",
|
||||
data_key="collector_mass",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="active_material",
|
||||
data_type="active_material",
|
||||
label="活性物质含量",
|
||||
data_key="active_material",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="capacity",
|
||||
data_type="capacity",
|
||||
label="克容量",
|
||||
data_key="capacity",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="battery_system",
|
||||
data_type="battery_system",
|
||||
label="电池体系",
|
||||
data_key="battery_system",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
# transfer使用
|
||||
ActionOutputHandle(
|
||||
key="target_device",
|
||||
data_type="device_id",
|
||||
label="目标设备",
|
||||
data_key="target_device",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="resource",
|
||||
data_type="resource",
|
||||
label="待转移资源",
|
||||
data_key="resource.@flatten",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="mount_resource",
|
||||
data_type="resource",
|
||||
label="目标孔位",
|
||||
data_key="mount_resource.@flatten",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
# test使用
|
||||
ActionOutputHandle(
|
||||
key="collector_mass",
|
||||
data_type="collector_mass",
|
||||
label="极流体质量",
|
||||
data_key="collector_mass",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="active_material",
|
||||
data_type="active_material",
|
||||
label="活性物质含量",
|
||||
data_key="active_material",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="capacity",
|
||||
data_type="capacity",
|
||||
label="克容量",
|
||||
data_key="capacity",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="battery_system",
|
||||
data_type="battery_system",
|
||||
label="电池体系",
|
||||
data_key="battery_system",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
],
|
||||
)
|
||||
def manual_confirm(
|
||||
self,
|
||||
resource: List[ResourceSlot],
|
||||
target_device: DeviceSlot,
|
||||
mount_resource: List[ResourceSlot],
|
||||
collector_mass: List[float],
|
||||
active_material: List[float],
|
||||
capacity: List[float],
|
||||
battery_system: List[str],
|
||||
timeout_seconds: int,
|
||||
assignee_user_ids: list[str],
|
||||
**kwargs,
|
||||
) -> dict:
|
||||
"""
|
||||
人工确认资源转移和扣电测试参数。
|
||||
|
||||
Args:
|
||||
resource[待转移资源]: 需要人工确认的资源列表。
|
||||
target_device[目标设备]: 资源要转移到的目标设备 ID。
|
||||
mount_resource[目标孔位]: 资源要挂载到的目标孔位列表。
|
||||
collector_mass[极流体质量]: 每个样品对应的极流体质量。
|
||||
active_material[活性物质含量]: 每个样品对应的活性物质含量。
|
||||
capacity[克容量]: 每个样品对应的克容量，单位 mAh/g。
|
||||
battery_system[电池体系]: 每个样品对应的电池体系名称。
|
||||
timeout_seconds[超时时间]: 人工确认超时时间，单位秒。
|
||||
assignee_user_ids[确认人]: 指定处理人工确认任务的用户 ID 列表。
|
||||
|
||||
Note:
|
||||
修改的结果无效，是只读的。
|
||||
"""
|
||||
resource_tree = ResourceTreeSet.from_plr_resources(cast(Any, resource)).dump()
|
||||
mount_resource_tree = ResourceTreeSet.from_plr_resources(cast(Any, mount_resource)).dump()
|
||||
kwargs.update(locals())
|
||||
kwargs.pop("kwargs")
|
||||
kwargs.pop("self")
|
||||
kwargs["resource"] = resource_tree
|
||||
kwargs["mount_resource"] = mount_resource_tree
|
||||
kwargs.pop("resource_tree")
|
||||
kwargs.pop("mount_resource_tree")
|
||||
return kwargs
|
||||
|
||||
@action(
|
||||
description="转移物料",
|
||||
handles=[
|
||||
ActionInputHandle(
|
||||
key="target_device",
|
||||
data_type="device_id",
|
||||
label="目标设备",
|
||||
data_key="target_device",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="resource",
|
||||
data_type="resource",
|
||||
label="待转移资源",
|
||||
data_key="resource",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="mount_resource",
|
||||
data_type="resource",
|
||||
label="目标孔位",
|
||||
data_key="mount_resource",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
],
|
||||
)
|
||||
async def transfer(
|
||||
self,
|
||||
resource: List[ResourceSlot],
|
||||
target_device: DeviceSlot,
|
||||
mount_resource: List[ResourceSlot],
|
||||
):
|
||||
"""
|
||||
转移资源到目标设备。
|
||||
|
||||
Args:
|
||||
resource[待转移资源]: 待转移的资源列表。
|
||||
target_device[目标设备]: 接收资源的目标设备 ID。
|
||||
mount_resource[目标孔位]: 目标设备上的挂载孔位列表。
|
||||
"""
|
||||
future = ROS2DeviceNode.run_async_func(
|
||||
self._ros_node.transfer_resource_to_another,
|
||||
True,
|
||||
**{
|
||||
"plr_resources": resource,
|
||||
"target_device_id": target_device,
|
||||
"target_resources": mount_resource,
|
||||
"sites": [None] * len(mount_resource),
|
||||
},
|
||||
)
|
||||
result = await future
|
||||
return result
|
||||
|
||||
@action(
|
||||
description="扣电测试启动",
|
||||
handles=[
|
||||
ActionInputHandle(
|
||||
key="resource",
|
||||
data_type="resource",
|
||||
label="待转移资源",
|
||||
data_key="resource",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="mount_resource",
|
||||
data_type="resource",
|
||||
label="目标孔位",
|
||||
data_key="mount_resource",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="collector_mass",
|
||||
data_type="collector_mass",
|
||||
label="极流体质量",
|
||||
data_key="collector_mass",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="active_material",
|
||||
data_type="active_material",
|
||||
label="活性物质含量",
|
||||
data_key="active_material",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="capacity",
|
||||
data_type="capacity",
|
||||
label="克容量",
|
||||
data_key="capacity",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="battery_system",
|
||||
data_type="battery_system",
|
||||
label="电池体系",
|
||||
data_key="battery_system",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
],
|
||||
)
|
||||
async def test(
|
||||
self,
|
||||
resource: List[ResourceSlot],
|
||||
mount_resource: List[ResourceSlot],
|
||||
collector_mass: List[float],
|
||||
active_material: List[float],
|
||||
capacity: List[float],
|
||||
battery_system: list[str],
|
||||
):
|
||||
"""
|
||||
启动扣电测试。
|
||||
|
||||
Args:
|
||||
resource[待测试资源]: 需要进行扣电测试的资源列表。
|
||||
mount_resource[测试孔位]: 扣电测试使用的目标孔位列表。
|
||||
collector_mass[极流体质量]: 每个样品对应的极流体质量。
|
||||
active_material[活性物质含量]: 每个样品对应的活性物质含量。
|
||||
capacity[克容量]: 每个样品对应的克容量，单位 mAh/g。
|
||||
battery_system[电池体系]: 每个样品对应的电池体系名称。
|
||||
"""
|
||||
print(resource)
|
||||
print(mount_resource)
|
||||
print(collector_mass)
|
||||
print(active_material)
|
||||
print(capacity)
|
||||
print(battery_system)
|
||||
|
||||
@action(
|
||||
auto_prefix=True,
|
||||
description="批量准备物料 - 虚拟起始节点, 生成A1-A5物料, 输出5个handle供后续节点使用",
|
||||
handles=[
|
||||
ActionOutputHandle(key="channel_1", data_type="workbench_material",
|
||||
label="实验1", data_key="material_1", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="channel_2", data_type="workbench_material",
|
||||
label="实验2", data_key="material_2", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="channel_3", data_type="workbench_material",
|
||||
label="实验3", data_key="material_3", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="channel_4", data_type="workbench_material",
|
||||
label="实验4", data_key="material_4", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="channel_5", data_type="workbench_material",
|
||||
label="实验5", data_key="material_5", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="channel_1", data_type="workbench_material", label="实验1", data_key="material_1", data_source=DataSource.EXECUTOR), # noqa: E501
|
||||
ActionOutputHandle(key="channel_2", data_type="workbench_material", label="实验2", data_key="material_2", data_source=DataSource.EXECUTOR), # noqa: E501
|
||||
ActionOutputHandle(key="channel_3", data_type="workbench_material", label="实验3", data_key="material_3", data_source=DataSource.EXECUTOR), # noqa: E501
|
||||
ActionOutputHandle(key="channel_4", data_type="workbench_material", label="实验4", data_key="material_4", data_source=DataSource.EXECUTOR), # noqa: E501
|
||||
ActionOutputHandle(key="channel_5", data_type="workbench_material", label="实验5", data_key="material_5", data_source=DataSource.EXECUTOR), # noqa: E501
|
||||
],
|
||||
)
|
||||
def prepare_materials(
|
||||
@@ -316,6 +617,9 @@ class VirtualWorkbench:
|
||||
|
||||
作为工作流的起始节点, 生成指定数量的物料编号供后续节点使用。
|
||||
输出5个handle (material_1 ~ material_5), 分别对应实验1~5。
|
||||
|
||||
Args:
|
||||
count[物料数量]: 要生成的物料数量，默认生成 5 个。
|
||||
"""
|
||||
materials = [i for i in range(1, count + 1)]
|
||||
|
||||
@@ -336,7 +640,11 @@ class VirtualWorkbench:
|
||||
LabSample(
|
||||
sample_uuid=sample_uuid,
|
||||
oss_path="",
|
||||
extra={"material_uuid": content} if isinstance(content, str) else (content.serialize() if content else {}),
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
],
|
||||
@@ -346,12 +654,27 @@ class VirtualWorkbench:
|
||||
auto_prefix=True,
|
||||
description="将物料从An位置移动到空闲加热台, 返回分配的加热台ID",
|
||||
handles=[
|
||||
ActionInputHandle(key="material_input", data_type="workbench_material",
|
||||
label="物料编号", data_key="material_number", data_source=DataSource.HANDLE),
|
||||
ActionOutputHandle(key="heating_station_output", data_type="workbench_station",
|
||||
label="加热台ID", data_key="station_id", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="material_number_output", data_type="workbench_material",
|
||||
label="物料编号", data_key="material_number", data_source=DataSource.EXECUTOR),
|
||||
ActionInputHandle(
|
||||
key="material_input",
|
||||
data_type="workbench_material",
|
||||
label="物料编号",
|
||||
data_key="material_number",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="heating_station_output",
|
||||
data_type="workbench_station",
|
||||
label="加热台ID",
|
||||
data_key="station_id",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="material_number_output",
|
||||
data_type="workbench_material",
|
||||
label="物料编号",
|
||||
data_key="material_number",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
],
|
||||
)
|
||||
def move_to_heating_station(
|
||||
@@ -363,6 +686,9 @@ class VirtualWorkbench:
|
||||
将物料从An位置移动到加热台
|
||||
|
||||
多线程并发调用时, 会竞争机械臂使用权, 并自动查找空闲加热台
|
||||
|
||||
Args:
|
||||
material_number[物料编号]: 要移动的物料编号，对应 A1、A2 等起始位置。
|
||||
"""
|
||||
material_id = f"A{material_number}"
|
||||
task_desc = f"移动{material_id}到加热台"
|
||||
@@ -425,7 +751,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -448,7 +775,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -460,14 +788,34 @@ class VirtualWorkbench:
|
||||
always_free=True,
|
||||
description="启动指定加热台的加热程序",
|
||||
handles=[
|
||||
ActionInputHandle(key="station_id_input", data_type="workbench_station",
|
||||
label="加热台ID", data_key="station_id", data_source=DataSource.HANDLE),
|
||||
ActionInputHandle(key="material_number_input", data_type="workbench_material",
|
||||
label="物料编号", data_key="material_number", data_source=DataSource.HANDLE),
|
||||
ActionOutputHandle(key="heating_done_station", data_type="workbench_station",
|
||||
label="加热完成-加热台ID", data_key="station_id", data_source=DataSource.EXECUTOR),
|
||||
ActionOutputHandle(key="heating_done_material", data_type="workbench_material",
|
||||
label="加热完成-物料编号", data_key="material_number", data_source=DataSource.EXECUTOR),
|
||||
ActionInputHandle(
|
||||
key="station_id_input",
|
||||
data_type="workbench_station",
|
||||
label="加热台ID",
|
||||
data_key="station_id",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="material_number_input",
|
||||
data_type="workbench_material",
|
||||
label="物料编号",
|
||||
data_key="material_number",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="heating_done_station",
|
||||
data_type="workbench_station",
|
||||
label="加热完成-加热台ID",
|
||||
data_key="station_id",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
ActionOutputHandle(
|
||||
key="heating_done_material",
|
||||
data_type="workbench_material",
|
||||
label="加热完成-物料编号",
|
||||
data_key="material_number",
|
||||
data_source=DataSource.EXECUTOR,
|
||||
),
|
||||
],
|
||||
)
|
||||
def start_heating(
|
||||
@@ -478,6 +826,10 @@ class VirtualWorkbench:
|
||||
) -> StartHeatingResult:
|
||||
"""
|
||||
启动指定加热台的加热程序
|
||||
|
||||
Args:
|
||||
station_id[加热台ID]: 要启动加热的加热台编号。
|
||||
material_number[物料编号]: 当前加热台上的物料编号。
|
||||
"""
|
||||
self.logger.info(f"[加热台{station_id}] 开始加热")
|
||||
|
||||
@@ -494,7 +846,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -517,7 +870,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -537,7 +891,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -577,7 +932,9 @@ class VirtualWorkbench:
|
||||
self._update_data_status(f"加热台{station_id}加热中: {progress:.1f}%")
|
||||
|
||||
if time.time() - last_countdown_log >= 5.0:
|
||||
self.logger.info(f"[加热台{station_id}] {material_id} 剩余 {remaining:.1f}s")
|
||||
self.logger.info(
|
||||
f"[加热台{station_id}] {material_id} 剩余 {remaining:.1f}s"
|
||||
)
|
||||
last_countdown_log = time.time()
|
||||
|
||||
if elapsed >= self.HEATING_TIME:
|
||||
@@ -594,7 +951,9 @@ class VirtualWorkbench:
|
||||
self._active_tasks[material_id]["status"] = "heating_completed"
|
||||
|
||||
self._update_data_status(f"加热台{station_id}加热完成")
|
||||
self.logger.info(f"[加热台{station_id}] {material_id}加热完成 (用时{self.HEATING_TIME}s)")
|
||||
self.logger.info(
|
||||
f"[加热台{station_id}] {material_id}加热完成 (用时{self.HEATING_TIME}s)"
|
||||
)
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
@@ -608,7 +967,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -619,10 +979,20 @@ class VirtualWorkbench:
|
||||
auto_prefix=True,
|
||||
description="将物料从加热台移动到输出位置Cn",
|
||||
handles=[
|
||||
ActionInputHandle(key="output_station_input", data_type="workbench_station",
|
||||
label="加热台ID", data_key="station_id", data_source=DataSource.HANDLE),
|
||||
ActionInputHandle(key="output_material_input", data_type="workbench_material",
|
||||
label="物料编号", data_key="material_number", data_source=DataSource.HANDLE),
|
||||
ActionInputHandle(
|
||||
key="output_station_input",
|
||||
data_type="workbench_station",
|
||||
label="加热台ID",
|
||||
data_key="station_id",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
ActionInputHandle(
|
||||
key="output_material_input",
|
||||
data_type="workbench_material",
|
||||
label="物料编号",
|
||||
data_key="material_number",
|
||||
data_source=DataSource.HANDLE,
|
||||
),
|
||||
],
|
||||
)
|
||||
def move_to_output(
|
||||
@@ -633,6 +1003,10 @@ class VirtualWorkbench:
|
||||
) -> MoveToOutputResult:
|
||||
"""
|
||||
将物料从加热台移动到输出位置Cn
|
||||
|
||||
Args:
|
||||
station_id[加热台ID]: 已完成加热的加热台编号。
|
||||
material_number[物料编号]: 要移动到输出位置的物料编号，对应 Cn。
|
||||
"""
|
||||
output_number = material_number
|
||||
|
||||
@@ -649,7 +1023,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -673,7 +1048,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -693,7 +1069,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
@@ -775,7 +1152,8 @@ class VirtualWorkbench:
|
||||
oss_path="",
|
||||
extra=(
|
||||
{"material_uuid": content}
|
||||
if isinstance(content, str) else (content.serialize() if content else {})
|
||||
if isinstance(content, str)
|
||||
else (content.serialize() if content else {})
|
||||
),
|
||||
)
|
||||
for sample_uuid, content in sample_uuids.items()
|
||||
|
||||
@@ -1,634 +0,0 @@
|
||||
# Layout Optimizer Handover
|
||||
|
||||
**Date**: 2026-04-10 | **Branch**: `feat/3d_layout_and_visualize` | **Commit**: `99dc821a` | **Tests**: 270 (260 pass + 10 LLM skip w/o API key)
|
||||
|
||||
This package is a standalone lab layout optimizer. It takes a device list + constraints and returns optimized placements. Your integration points are the HTTP API and the LLM skill document.
|
||||
|
||||
---
|
||||
|
||||
## 1. Full Pipeline Overview
|
||||
|
||||
```
|
||||
User NL request
|
||||
│
|
||||
▼
|
||||
┌─────────────────┐ skill doc: llm_skill/layout_intent_translator.md
|
||||
│ LLM Agent │◄── + device list from scene (GET /devices)
|
||||
│ (your side) │ + schema discovery (GET /interpret/schema)
|
||||
└────────┬────────┘
|
||||
│ structured intents JSON
|
||||
▼
|
||||
POST /interpret ← intent_interpreter.py (pure translation)
|
||||
│
|
||||
│ { constraints, translations, workflow_edges, errors }
|
||||
▼
|
||||
User confirms ← translations have human-readable explanations
|
||||
│
|
||||
▼
|
||||
POST /optimize ← full pipeline below
|
||||
│
|
||||
┌────┴─────────────────────────────────────────┐
|
||||
│ 1. Device catalog (device_catalog.py) │
|
||||
│ footprints.json → Device objects │
|
||||
│ bbox, height, openings per device │
|
||||
│ │
|
||||
│ 2. Seeder (seeders.py) │
|
||||
│ Force-directed initial placement │
|
||||
│ Presets: compact_outward, spread_inward, │
|
||||
│ workflow_cluster, row_fallback │
|
||||
│ Accounts for openings, workflow edges │
|
||||
│ │
|
||||
│ 3. DE Optimizer (optimizer.py) │
|
||||
│ Custom DE loop (best1bin/currenttobest1bin│
|
||||
│ /rand1bin strategies) │
|
||||
│ 3N-dim: [x0, y0, θ0, x1, y1, θ1, ...] │
|
||||
│ Broad-phase AABB sweep (broad_phase.py) │
|
||||
│ θ lattice snap in joint discrete mode │
|
||||
│ Cost = hard_penalties + soft_penalties │
|
||||
│ Graduated collision penalties (not binary) │
|
||||
│ │
|
||||
│ 4. θ snap (optimizer.snap_theta) │
|
||||
│ Snap near-cardinal angles to 0/90/180/270 │
|
||||
│ (opt-in via snap_cardinal=True) │
|
||||
│ │
|
||||
│ 5. Final eval (constraints.py) │
|
||||
│ Binary pass/fail for response.success │
|
||||
└──────────────────────────────────────────────┘
|
||||
│
|
||||
▼
|
||||
{ placements, cost, success }
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 2. API Reference
|
||||
|
||||
### `POST /interpret` — LLM intent → constraints
|
||||
|
||||
Translates semantic intents into optimizer constraints. The LLM agent calls this after translating user NL.
|
||||
|
||||
**Request:**
|
||||
```json
|
||||
{
|
||||
"intents": [
|
||||
{
|
||||
"intent": "reachable_by",
|
||||
"params": {"arm": "arm_slider", "targets": ["opentrons_liquid_handler", "inheco_odtc_96xl"]},
|
||||
"description": "Robot arm must reach these devices"
|
||||
},
|
||||
{
|
||||
"intent": "workflow_hint",
|
||||
"params": {"workflow": "pcr", "devices": ["device_a", "device_b", "device_c"]},
|
||||
"description": "PCR workflow order"
|
||||
},
|
||||
{
|
||||
"intent": "close_together",
|
||||
"params": {"devices": ["device_a", "device_b"], "priority": "high"},
|
||||
"description": "Keep these close"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**Response:**
|
||||
```json
|
||||
{
|
||||
"constraints": [
|
||||
{"type": "hard", "rule_name": "reachability", "params": {"arm_id": "arm_slider", "target_device_id": "opentrons_liquid_handler"}, "weight": 1.0},
|
||||
...
|
||||
],
|
||||
"translations": [
|
||||
{
|
||||
"source_intent": "reachable_by",
|
||||
"source_description": "Robot arm must reach these devices",
|
||||
"source_params": {"arm": "arm_slider", "targets": ["..."]},
|
||||
"generated_constraints": [...],
|
||||
"explanation": "机械臂 'arm_slider' 需要能够到达 2 个目标设备",
|
||||
"confidence": "high"
|
||||
}
|
||||
],
|
||||
"workflow_edges": [["device_a", "device_b"], ["device_b", "device_c"]],
|
||||
"errors": []
|
||||
}
|
||||
```
|
||||
|
||||
The `constraints` and `workflow_edges` arrays pass directly to `/optimize` — no transformation needed.
|
||||
|
||||
### `GET /interpret/schema` — LLM discovery
|
||||
|
||||
Returns all 11 intent types with parameter specs. LLM agent should call this before translating.
|
||||
|
||||
### `POST /optimize` — Run layout optimization
|
||||
|
||||
**Request:**
|
||||
```json
|
||||
{
|
||||
"devices": [
|
||||
{"id": "thermo_orbitor_rs2_hotel", "name": "Plate Hotel", "device_type": "static"},
|
||||
{"id": "arm_slider", "name": "Robot Arm", "device_type": "articulation"},
|
||||
...
|
||||
],
|
||||
"lab": {"width": 6.0, "depth": 4.0},
|
||||
"constraints": [...],
|
||||
"workflow_edges": [["device_a", "device_b"]],
|
||||
"seeder": "compact_outward",
|
||||
"run_de": true,
|
||||
"maxiter": 200,
|
||||
"seed": 42,
|
||||
"angle_granularity": 4,
|
||||
"snap_cardinal": false,
|
||||
"strategy": "currenttobest1bin",
|
||||
"mutation": [0.5, 1.0],
|
||||
"theta_mutation": null,
|
||||
"recombination": 0.7,
|
||||
"crossover_mode": "device"
|
||||
}
|
||||
```
|
||||
|
||||
**Response:**
|
||||
```json
|
||||
{
|
||||
"placements": [
|
||||
{
|
||||
"device_id": "thermo_orbitor_rs2_hotel",
|
||||
"uuid": "thermo_orbitor_rs2_hotel",
|
||||
"position": {"x": 1.33, "y": 2.35, "z": 0.0},
|
||||
"rotation": {"x": 0.0, "y": 0.0, "z": 1.5708}
|
||||
},
|
||||
...
|
||||
],
|
||||
"cost": 0.0,
|
||||
"success": true,
|
||||
"seeder_used": "compact_outward",
|
||||
"de_ran": true
|
||||
}
|
||||
```
|
||||
|
||||
`position`/`rotation` format matches Cloud's `CommonPositionType`. `rotation.z` is θ in radians.
|
||||
|
||||
**DE hyperparameters:**
|
||||
| Param | Default | Description |
|
||||
|-------|---------|-------------|
|
||||
| `strategy` | `"currenttobest1bin"` | DE mutation strategy (`best1bin`, `currenttobest1bin`, `rand1bin`) |
|
||||
| `mutation` | `[0.5, 1.0]` | Dithered F range for position dimensions |
|
||||
| `theta_mutation` | `null` (same as `mutation`) | Separate F range for θ dimensions (decoupled mutation) |
|
||||
| `recombination` | `0.7` | Crossover probability |
|
||||
| `crossover_mode` | `"device"` | `"device"` = per-device CR, `"dimension"` = per-dimension CR |
|
||||
| `angle_granularity` | `null` | `4`/`8`/`12`/`24` — snaps θ to a discrete lattice during DE (joint mode). `4` = axis-aligned (0/90/180/270). `null` = continuous θ |
|
||||
| `snap_cardinal` | `false` | Post-DE snap to nearest cardinal angle with collision rollback |
|
||||
|
||||
### Scene State API
|
||||
|
||||
Shared scene state between the LLM agent and the frontend. The agent pushes layout results here; the frontend polls for updates.
|
||||
|
||||
#### `GET /scene/lab` / `POST /scene/lab` — Lab dimensions
|
||||
|
||||
**GET** returns current lab dimensions. **POST** sets them (frontend sends this when user changes lab size).
|
||||
|
||||
```json
|
||||
{"width": 6.0, "depth": 4.0}
|
||||
```
|
||||
|
||||
#### `GET /scene/placements` / `POST /scene/placements` / `DELETE /scene/placements`
|
||||
|
||||
**GET** returns current placements + a version counter. Frontend polls this every 1s and re-renders when version changes.
|
||||
|
||||
```json
|
||||
{"version": 3, "placements": [...]}
|
||||
```
|
||||
|
||||
**POST** pushes new placements (from `/optimize` result or agent). Bumps version.
|
||||
|
||||
**DELETE** clears all placements (resets scene).
|
||||
|
||||
### `GET /devices` — Device catalog
|
||||
|
||||
Returns all known devices with bbox, openings, model paths. The LLM agent should receive this list as context so it can resolve fuzzy device names.
|
||||
|
||||
### `GET /health`
|
||||
|
||||
Returns `{"status": "ok"}`.
|
||||
|
||||
---
|
||||
|
||||
## 3. Intent Types (11 total)
|
||||
|
||||
| Intent | Params | Generates | Type |
|
||||
|--------|--------|-----------|------|
|
||||
| `reachable_by` | `arm` (str), `targets` (list[str]) | `reachability` per target | hard |
|
||||
| `close_together` | `devices` (list[str]), `priority` (low/medium/high) | `minimize_distance` per pair | soft |
|
||||
| `far_apart` | `devices` (list[str]), `priority` | `maximize_distance` per pair | soft |
|
||||
| `keep_adjacent` | `devices` (list[str]), `priority` | `minimize_distance` per pair | soft |
|
||||
| `max_distance` | `device_a`, `device_b`, `distance` (float m) | `distance_less_than` | hard |
|
||||
| `min_distance` | `device_a`, `device_b`, `distance` (float m) | `distance_greater_than` | hard |
|
||||
| `min_spacing` | `min_gap` (float m, default 0.3) | `min_spacing` | hard |
|
||||
| `workflow_hint` | `workflow` (str), `devices` (ordered list[str]) | `minimize_distance` consecutive + `workflow_edges` | soft |
|
||||
| `face_outward` | (none) | `prefer_orientation_mode` outward | soft |
|
||||
| `face_inward` | (none) | `prefer_orientation_mode` inward | soft |
|
||||
| `align_cardinal` | (none) | `prefer_aligned` | soft |
|
||||
|
||||
Intent priorities are baked into the final emitted constraint `weight` during interpretation. The caller only sees the resulting weight, not a separate constraint-level priority field.
|
||||
|
||||
---
|
||||
|
||||
## 4. LLM Integration Guide
|
||||
|
||||
### What You Need to Build (Your Side)
|
||||
|
||||
The LLM agent that converts user natural language → structured intents JSON. We provide:
|
||||
|
||||
1. **Skill document** (`llm_skill/layout_intent_translator.md`) — system prompt for the LLM. Contains intent schema, device name resolution rules, translation rules, and PCR workflow examples.
|
||||
|
||||
2. **Runtime schema** (`GET /interpret/schema`) — machine-readable intent specs. LLM agent should call this for discovery.
|
||||
|
||||
3. **Device context** — before translating, feed the LLM the scene's device list (from `GET /devices` or your scene state). The LLM uses this to resolve fuzzy names like "PCR machine" → `inheco_odtc_96xl`.
|
||||
|
||||
### Integration Flow
|
||||
|
||||
```
|
||||
1. User enters NL request in Cloud UI
|
||||
2. Your LLM agent receives:
|
||||
- User message
|
||||
- Scene device list (id, name, type, bbox)
|
||||
- Skill doc as system prompt
|
||||
- Optional: GET /interpret/schema for discovery
|
||||
3. LLM outputs: {"intents": [...]}
|
||||
4. POST /interpret with LLM output
|
||||
5. Show user the translations for confirmation
|
||||
6. POST /optimize with confirmed constraints + workflow_edges
|
||||
7. Apply placements to scene
|
||||
```
|
||||
|
||||
### Device Name Resolution (handled by LLM, not by optimizer)
|
||||
|
||||
The skill doc teaches the LLM to match fuzzy names:
|
||||
- "PCR machine" / "thermal cycler" → `inheco_odtc_96xl`
|
||||
- "liquid handler" / "pipetting robot" → `opentrons_liquid_handler`
|
||||
- "plate hotel" / "storage" → `thermo_orbitor_rs2_hotel`
|
||||
- "robot arm" / "the arm" → device with `type: articulation`
|
||||
- "plate sealer" → `agilent_plateloc`
|
||||
|
||||
No search endpoint needed — the device list is already in context.
|
||||
|
||||
### Tested LLM Outputs
|
||||
|
||||
We tested with Claude Sonnet (via subagent, no API key required). Examples:
|
||||
|
||||
**Input**: "Take plate from hotel, prepare sample in the pipetting robot, seal it, then run thermal cycling. The arm handles all transfers. Keep liquid handler and sealer close, minimum 15cm gap."
|
||||
|
||||
**LLM produced**: `reachable_by` (arm→4 devices), `workflow_hint` (correct PCR order), `close_together` (high, LH+sealer), `min_distance` (0.15m, LH+sealer)
|
||||
|
||||
**Input**: "I want an automatic PCR lab, make it compact and neat"
|
||||
|
||||
**LLM produced**: `reachable_by`, `workflow_hint`, `close_together` (all devices), `min_spacing` (0.05m), `align_cardinal`
|
||||
|
||||
All outputs pass through `/interpret` → `/optimize` successfully.
|
||||
|
||||
---
|
||||
|
||||
## 5. Constraint System Details
|
||||
|
||||
### Hard Constraints (cost = ∞ on violation)
|
||||
|
||||
| Rule Name | Params | What it checks |
|
||||
|-----------|--------|---------------|
|
||||
| `no_collision` | (default, always on) | OBB-SAT pairwise collision between all devices |
|
||||
| `within_bounds` | (default, always on) | All devices within lab boundary |
|
||||
| `reachability` | `arm_id`, `target_device_id` | Target center within arm reach radius |
|
||||
| `distance_less_than` | `device_a`, `device_b`, `distance` | OBB edge-to-edge distance ≤ threshold |
|
||||
| `distance_greater_than` | `device_a`, `device_b`, `distance` | OBB edge-to-edge distance ≥ threshold |
|
||||
| `min_spacing` | `min_gap` | All device pairs have ≥ min_gap edge-to-edge |
|
||||
|
||||
### Soft Constraints (weighted penalty)
|
||||
|
||||
| Rule Name | Params | What it minimizes |
|
||||
|-----------|--------|------------------|
|
||||
| `minimize_distance` | `device_a`, `device_b` | OBB edge-to-edge distance × weight |
|
||||
| `maximize_distance` | `device_a`, `device_b` | 1/(distance+ε) × weight |
|
||||
| `prefer_orientation_mode` | `mode` (outward/inward) | Angle between opening direction and ideal direction |
|
||||
| `prefer_aligned` | (none) | Deviation from nearest 90° angle |
|
||||
| `prefer_seeder_orientation` | (none) | Deviation from seeder-assigned θ |
|
||||
| `crossing_penalty` | (auto, part of `reachability` eval) | Segment-OBB intersection length of opening-to-arm path blocked by other devices (Cyrus-Beck clipping via `obb.segment_obb_intersection_length`) |
|
||||
|
||||
### Weight Normalization
|
||||
|
||||
| Constant | Value | Meaning |
|
||||
|----------|-------|---------|
|
||||
| `DEFAULT_WEIGHT_DISTANCE` | 100.0 | 1 cm → penalty 1.0 |
|
||||
| `DEFAULT_WEIGHT_ANGLE` | 60.0 | 5° → penalty ~1.0 |
|
||||
| `HARD_MULTIPLIER` | 5.0 | Hard constraint penalty multiplier during graduated DE |
|
||||
|
||||
Constraints support a `priority` field (`critical` / `high` / `normal` / `low`) with multipliers 5× / 2× / 1× / 0.5×.
|
||||
|
||||
### Graduated Penalties (DE internals)
|
||||
|
||||
Default hard constraints (collision, boundary) use **graduated penalties** during DE optimization — proportional to penetration depth / overshoot distance. This gives DE a smooth gradient instead of binary inf. Final evaluation uses binary mode for pass/fail reporting.
|
||||
|
||||
---
|
||||
|
||||
## 6. Checker Architecture (Mock → Real)
|
||||
|
||||
```
|
||||
interfaces.py (Protocol definitions)
|
||||
├── CollisionChecker.check(placements) → collisions
|
||||
├── CollisionChecker.check_bounds(placements, w, d) → out_of_bounds
|
||||
└── ReachabilityChecker.is_reachable(arm_id, arm_pose, target) → bool
|
||||
|
||||
mock_checkers.py (current, no ROS)
|
||||
├── MockCollisionChecker — OBB SAT
|
||||
└── MockReachabilityChecker — Euclidean distance, 100m fallback for unknown arms
|
||||
|
||||
ros_checkers.py (for ROS2/MoveIt2 integration)
|
||||
├── MoveItCollisionChecker — python-fcl direct + OBB fallback
|
||||
└── IKFastReachabilityChecker — precomputed voxel O(1) + live IK fallback
|
||||
└── create_checkers(mode) — factory, controlled by LAYOUT_CHECKER_MODE env var
|
||||
```
|
||||
|
||||
To switch to real checkers: `LAYOUT_CHECKER_MODE=moveit` + pass MoveIt2 instance.
|
||||
|
||||
---
|
||||
|
||||
## 7. File Inventory
|
||||
|
||||
### Core Pipeline
|
||||
| File | Lines | Purpose |
|
||||
|------|-------|---------|
|
||||
| `models.py` | 97 | Dataclasses: Device, Lab, Placement, Constraint, Intent, Opening |
|
||||
| `device_catalog.py` | 303 | Loads devices from footprints.json + uni-lab-assets + registry |
|
||||
| `footprints.json` | 183KB | 499 device bounding boxes, heights, openings (offline extracted) |
|
||||
| `seeders.py` | 331 | Force-directed initial layout with presets |
|
||||
| `optimizer.py` | 1056 | Custom DE loop: per-device crossover, θ wrapping, discrete angle lattice, multi-strategy |
|
||||
| `broad_phase.py` | 66 | 2-axis sweep-and-prune AABB broad phase for collision pair pruning |
|
||||
| `constraints.py` | 627 | Unified constraint evaluation (hard + soft + graduated + crossing penalty) |
|
||||
| `obb.py` | 257 | OBB geometry: corners, overlap SAT, min_distance, penetration_depth, segment intersection |
|
||||
| `intent_interpreter.py` | 366 | 11 intent handlers, pure translation, no side effects |
|
||||
| `server.py` | 743 | FastAPI: /interpret, /optimize, /devices, /scene/* endpoints |
|
||||
| `lab_parser.py` | 50 | Parse lab floor plan JSON to Lab dataclass |
|
||||
|
||||
### Reference / Utilities
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `extract_footprints.py` | How footprints.json was generated (offline STL/GLB → 2D bbox extraction via trimesh) |
|
||||
| `generate_asset_registry.py` | Generate YAML registry entries for uni-lab-assets devices not already registered |
|
||||
|
||||
### Integration Layer
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `interfaces.py` | Protocol definitions for CollisionChecker / ReachabilityChecker |
|
||||
| `mock_checkers.py` | Dev-mode checkers (OBB collision, Euclidean reachability) |
|
||||
| `ros_checkers.py` | MoveIt2/IKFast adapters for real collision + reachability |
|
||||
|
||||
### LLM
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `llm_skill/layout_intent_translator.md` | System prompt for LLM: intent schema, device resolution, translation rules, examples |
|
||||
| `llm_skill/demo_agent.md` | LLM agent orchestration instructions for demo (GET /devices → intents → /interpret → /optimize → /scene/placements) |
|
||||
|
||||
### Demo / Frontend
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `static/lab3d.html` | Three.js 3D visualization frontend (1227 lines): device library, drag-to-add, auto layout, scene polling |
|
||||
|
||||
### Configuration
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `pyproject.toml` | Package deps: scipy, numpy, fastapi, uvicorn, pydantic |
|
||||
|
||||
### Tests (270 total: 260 pass + 10 skip without API key)
|
||||
| File | Tests | Coverage |
|
||||
|------|-------|----------|
|
||||
| `test_intent_interpreter.py` | 19 | All 11 handlers, validation, priority, multi-intent |
|
||||
| `test_interpret_api.py` | 6 | /interpret and /interpret/schema endpoints |
|
||||
| `test_e2e_pcr_pipeline.py` | 12 | Full pipeline: interpret → optimize → verify placements |
|
||||
| `test_llm_skill.py` | 10 | Real LLM fuzzy input → structured output (needs ANTHROPIC_API_KEY) |
|
||||
| `test_constraints.py` | 30 | Constraint evaluation, hard/soft, graduated penalties, crossing penalty |
|
||||
| `test_optimizer.py` | 50 | DE optimizer, vector encoding, bounds, discrete angles, strategies |
|
||||
| `test_mock_checkers.py` | 15 | MockCollisionChecker, MockReachabilityChecker |
|
||||
| `test_ros_checkers.py` | 40 | MoveIt2/IKFast adapter tests |
|
||||
| `test_seeders.py` | 12 | Force-directed seeder presets |
|
||||
| `test_device_catalog.py` | 25 | Device loading, footprint merging |
|
||||
| `test_obb.py` | 18 | OBB geometry functions, segment intersection |
|
||||
| `test_bugfixes_v2.py` | 28 | Regression: duplicate IDs, orientation, min_spacing, cardinal snap defaults |
|
||||
| `test_broad_phase.py` | 5 | Sweep-and-prune AABB broad phase |
|
||||
|
||||
---
|
||||
|
||||
## 8. How to Run
|
||||
|
||||
### Quick Start
|
||||
```bash
|
||||
# Install
|
||||
pip install -e ".[dev]"
|
||||
|
||||
# Run server
|
||||
uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
|
||||
|
||||
# Run server with debug logging (shows DE cost breakdown per generation)
|
||||
LAYOUT_DEBUG=1 uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
|
||||
|
||||
# Run tests
|
||||
pytest unilabos/layout_optimizer/tests/ -v
|
||||
|
||||
# Run LLM skill tests (needs API key)
|
||||
ANTHROPIC_API_KEY=sk-... pytest unilabos/layout_optimizer/tests/test_llm_skill.py -v
|
||||
```
|
||||
|
||||
**Log files**: All requests are logged to `unilabos/layout_optimizer/logs/{YYYYMMDD_HHMMSS}.log` at DEBUG level (frontend polling GET /scene/placements excluded).
|
||||
|
||||
### Dependencies
|
||||
- Python ≥ 3.10
|
||||
- scipy, numpy, fastapi, uvicorn, pydantic
|
||||
- Optional: anthropic (for LLM skill tests)
|
||||
- Optional: python-fcl (for real collision checking, not needed for mock mode)
|
||||
|
||||
### Environment Variables
|
||||
| Variable | Default | Purpose |
|
||||
|----------|---------|---------|
|
||||
| `UNI_LAB_ASSETS_DIR` | `../uni-lab-assets` | Path to device 3D models |
|
||||
| `UNI_LAB_OS_DEVICE_MESH_DIR` | `Uni-Lab-OS/unilabos/device_mesh/devices` | Registry device meshes |
|
||||
| `LAYOUT_CHECKER_MODE` | `mock` | `mock` or `moveit` for checker selection |
|
||||
| `LAYOUT_DEBUG` | (unset) | Set to `1` for DEBUG-level console logging (DE cost breakdown per generation) |
|
||||
| `ANTHROPIC_API_KEY` | (none) | For LLM skill tests |
|
||||
|
||||
---
|
||||
|
||||
## 9. Known Limitations
|
||||
|
||||
1. **Mock reachability**: `MockReachabilityChecker` uses 100m fallback for unknown arm IDs — effectively "always reachable" for mock mode. Real arm reach requires `ros_checkers.py` with MoveIt2.
|
||||
|
||||
2. **No real LLM in tests**: `test_llm_skill.py` tests are skipped without `ANTHROPIC_API_KEY`. We verified with Claude Sonnet subagent that the skill doc produces correct output for PCR workflow scenarios.
|
||||
|
||||
3. **Opening data coverage**: 289/499 devices have opening direction annotations. Devices without openings default to local -Y as front with no alignment penalty.
|
||||
|
||||
4. **Single lab room**: No multi-room or corridor support yet. Lab is a single rectangle with optional rectangular obstacles.
|
||||
|
||||
5. **Intent interpreter is stateless**: It translates intents one-by-one with no cross-referencing between them. Duplicate/conflicting constraints are the LLM's responsibility to avoid.
|
||||
|
||||
6. **`align_weight` and `snap_cardinal` default to off**: `prefer_aligned` weight defaults to 0 (was `DEFAULT_WEIGHT_ANGLE=60`) and `snap_theta_safe` is opt-in via `snap_cardinal=True`. Both remain available when explicitly requested via `align_cardinal` intent or API param.
|
||||
|
||||
7. **Hybrid angle mode deprecated**: The angle-first hybrid mode (separate angle sweep + position-only DE) has been replaced by joint discrete mode as the default when `angle_granularity` is set. Joint mode snaps θ to the discrete lattice within the normal 3N DE loop.
|
||||
|
||||
---
|
||||
|
||||
## 10. Quick Verification (curl)
|
||||
|
||||
```bash
|
||||
# 1. Health check
|
||||
curl http://localhost:8000/health
|
||||
|
||||
# 2. Schema discovery
|
||||
curl http://localhost:8000/interpret/schema | python3 -m json.tool
|
||||
|
||||
# 3. Interpret PCR workflow
|
||||
curl -X POST http://localhost:8000/interpret \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"intents": [
|
||||
{"intent": "reachable_by", "params": {"arm": "arm_slider", "targets": ["opentrons_liquid_handler", "inheco_odtc_96xl"]}, "description": "arm reaches targets"},
|
||||
{"intent": "workflow_hint", "params": {"workflow": "pcr", "devices": ["thermo_orbitor_rs2_hotel", "opentrons_liquid_handler", "agilent_plateloc", "inheco_odtc_96xl"]}, "description": "PCR order"}
|
||||
]
|
||||
}' | python3 -m json.tool
|
||||
|
||||
# 4. Optimize (use constraints from step 3)
|
||||
curl -X POST http://localhost:8000/optimize \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"devices": [
|
||||
{"id": "thermo_orbitor_rs2_hotel", "name": "Plate Hotel"},
|
||||
{"id": "arm_slider", "name": "Robot Arm", "device_type": "articulation"},
|
||||
{"id": "opentrons_liquid_handler", "name": "Liquid Handler"},
|
||||
{"id": "agilent_plateloc", "name": "Plate Sealer"},
|
||||
{"id": "inheco_odtc_96xl", "name": "Thermal Cycler"}
|
||||
],
|
||||
"lab": {"width": 6.0, "depth": 4.0},
|
||||
"constraints": [
|
||||
{"type": "hard", "rule_name": "reachability", "params": {"arm_id": "arm_slider", "target_device_id": "opentrons_liquid_handler"}, "weight": 1.0},
|
||||
{"type": "hard", "rule_name": "reachability", "params": {"arm_id": "arm_slider", "target_device_id": "inheco_odtc_96xl"}, "weight": 1.0},
|
||||
{"type": "soft", "rule_name": "minimize_distance", "params": {"device_a": "thermo_orbitor_rs2_hotel", "device_b": "opentrons_liquid_handler"}, "weight": 3.0},
|
||||
{"type": "soft", "rule_name": "minimize_distance", "params": {"device_a": "opentrons_liquid_handler", "device_b": "agilent_plateloc"}, "weight": 3.0},
|
||||
{"type": "soft", "rule_name": "minimize_distance", "params": {"device_a": "agilent_plateloc", "device_b": "inheco_odtc_96xl"}, "weight": 3.0}
|
||||
],
|
||||
"workflow_edges": [
|
||||
["thermo_orbitor_rs2_hotel", "opentrons_liquid_handler"],
|
||||
["opentrons_liquid_handler", "agilent_plateloc"],
|
||||
["agilent_plateloc", "inheco_odtc_96xl"]
|
||||
],
|
||||
"run_de": true,
|
||||
"angle_granularity": 4,
|
||||
"maxiter": 100,
|
||||
"seed": 42
|
||||
}' | python3 -m json.tool
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 11. Demo Setup
|
||||
|
||||
This section documents the device processing pipeline, test frontend, and LLM agent demo for the layout optimizer.
|
||||
|
||||
### 11.1 Device Processing Pipeline
|
||||
|
||||
How devices go from 3D meshes to collision footprints:
|
||||
|
||||
1. **Source data**:
|
||||
- `uni-lab-assets/` repository: GLB/STL 3D models + XACRO robot descriptions
|
||||
- `Uni-Lab-OS/device_mesh/devices/` registry: device metadata directories
|
||||
|
||||
2. **Extraction** (`extract_footprints.py`):
|
||||
- Load meshes via `trimesh` (STL for geometry, GLB for display)
|
||||
- Compute oriented bounding box (OBB): width, depth, height
|
||||
- Apply GLB root node rotation to align with world frame
|
||||
- Detect openings from XACRO `<joint type="fixed">` elements containing "socket" in name
|
||||
- Compute opening direction: centroid of socket origins → cardinal direction mapping
|
||||
- Manual overrides for devices with non-standard opening patterns (`MANUAL_OPENINGS` dict)
|
||||
- Write results to `footprints.json` (499 devices, 183KB)
|
||||
|
||||
3. **Catalog merging** (`device_catalog.py`):
|
||||
- Load `footprints.json` (OBB + openings)
|
||||
- Load `uni-lab-assets/data.json` (asset tree structure)
|
||||
- Load `Uni-Lab-OS/device_mesh/devices/` (registry devices)
|
||||
- Merge: registry devices get priority for metadata, but assets' 3D model paths preferred
|
||||
- Fallback sizes: `KNOWN_SIZES` dict provides manual dimensions when trimesh extraction fails
|
||||
|
||||
4. **Standalone filtering** (`server.py:_is_standalone_device`):
|
||||
- Bbox >30cm = device (standalone equipment)
|
||||
- Bbox <5cm = consumable (plates, tubes, tips)
|
||||
- 5-30cm = keyword heuristic (check name for "plate", "tube", "tip", "rack")
|
||||
|
||||
### 11.2 Test Frontend (`static/lab3d.html`)
|
||||
|
||||
Interactive 3D lab layout visualization and design tool (1227 lines).
|
||||
|
||||
**Technology stack**:
|
||||
- Three.js v0.169.0 (ES modules from esm.sh CDN)
|
||||
- WebGL renderer with PCF soft shadow maps, ACES filmic tone mapping
|
||||
- OrbitControls for camera interaction
|
||||
|
||||
**Features**:
|
||||
- **Device library**: Left sidebar with search/filter, toggle between devices and consumables
|
||||
- **Drag-to-add**: Click device in library → adds to scene with random position
|
||||
- **Selected devices panel**: Right panel lists all placed devices, click to remove
|
||||
- **Lab dimensions**: Width × Depth inputs (meters), collision margin slider
|
||||
- **View modes**: 3D perspective (default) and top-down orthographic
|
||||
- **Grid system**: 0.5m grid with lab boundary highlighting
|
||||
- **Device visualization**: Box geometry with emissive materials, edge highlights, CSS2D labels
|
||||
- **Opening markers**: Orange arrows and semi-transparent strips showing device access directions
|
||||
- **Auto Layout button**: Calls `POST /optimize` with current devices + constraints
|
||||
- **Scene polling**: 1-second polling of `GET /scene/placements` for agent-pushed updates (version-based change detection)
|
||||
- **Smooth animation**: Lerp interpolation for device placement changes
|
||||
|
||||
**Backend integration**:
|
||||
- `GET /devices` — Load device catalog on startup
|
||||
- `POST /optimize` — Send devices + constraints, receive placements
|
||||
- `POST /scene/lab` — Push lab dimensions when changed
|
||||
- `GET /scene/placements` — Poll every 1s for agent-pushed updates
|
||||
|
||||
**Key JavaScript functions**:
|
||||
- `loadDeviceCatalog()` — Fetch device list, build catalog with color pool
|
||||
- `createDeviceMesh(deviceId, uuid)` — Create Three.js Group with body, edges, opening markers
|
||||
- `addDevice(deviceId)` / `removeDevice(uuid)` — Manage selected devices
|
||||
- `runLayout()` — Call backend `/optimize` or local bin packing fallback
|
||||
- `animatePlacement(uuid, tx, tz, theta)` — Smooth lerp to target position
|
||||
- `setView('3d' | 'top')` — Switch camera perspective
|
||||
|
||||
### 11.3 LLM Agent Demo (`llm_skill/demo_agent.md`)
|
||||
|
||||
LLM agent orchestration instructions for natural language lab layout design.
|
||||
|
||||
**Agent workflow**:
|
||||
1. `GET /devices` — Fetch device catalog for context
|
||||
2. Parse user natural language request
|
||||
3. Build structured intents JSON (using `layout_intent_translator.md` skill)
|
||||
4. `POST /interpret` — Translate intents to constraints
|
||||
5. `POST /optimize` — Run layout optimization
|
||||
6. `POST /scene/placements` — Push results to shared scene state
|
||||
7. Frontend auto-updates via polling (no manual refresh needed)
|
||||
|
||||
**Example user requests**:
|
||||
- "Design a PCR lab with robot arm automation, keep it compact"
|
||||
- "Place liquid handler, thermal cycler, and plate sealer. Arm must reach all devices."
|
||||
- "Add a plate hotel, make sure it's close to the liquid handler"
|
||||
|
||||
### 11.4 Running the Demo
|
||||
|
||||
```bash
|
||||
# Start the server
|
||||
uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
|
||||
|
||||
# Open in browser
|
||||
# http://localhost:8000/
|
||||
|
||||
# Use Claude Code with demo_agent.md skill to orchestrate via natural language
|
||||
# The agent will call the API endpoints and push results to /scene/placements
|
||||
# The frontend will automatically update via polling
|
||||
```
|
||||
|
||||
**Demo flow**:
|
||||
1. Open `http://localhost:8000/` in browser
|
||||
2. Frontend loads device catalog and displays 3D scene
|
||||
3. Use Claude Code with `demo_agent.md` skill to send natural language requests
|
||||
4. Agent translates request → intents → constraints → optimization → scene update
|
||||
5. Frontend polls `/scene/placements` every 1s and animates changes
|
||||
6. User can manually add/remove devices or adjust lab size in the UI
|
||||
7. Click "Auto Layout" to re-optimize with current devices
|
||||
|
||||
@@ -1,9 +0,0 @@
|
||||
"""Layout Optimizer — AI 实验室布局自动排布。
|
||||
|
||||
独立开发包，无 ROS 依赖。集成阶段合并到 Uni-Lab-OS。
|
||||
"""
|
||||
|
||||
from .models import Constraint, Device, Lab, Opening, Placement
|
||||
from .optimizer import optimize
|
||||
|
||||
__all__ = ["Device", "Lab", "Opening", "Placement", "Constraint", "optimize"]
|
||||
@@ -1,66 +0,0 @@
|
||||
"""2 轴 sweep-and-prune 宽相碰撞检测。
|
||||
|
||||
对每个设备计算旋转后的 AABB，先沿 x 轴排序并剪枝，
|
||||
再用 y 轴交叠过滤。返回候选碰撞对（索引对列表），
|
||||
供后续 OBB SAT 精确检测使用。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from .models import Device, Placement
|
||||
|
||||
|
||||
def sweep_and_prune_pairs(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
) -> list[tuple[int, int]]:
|
||||
"""2 轴 sweep-and-prune，返回 AABB 交叠的索引对。
|
||||
|
||||
Args:
|
||||
devices: 设备列表，与 placements 一一对应。
|
||||
placements: 布局位姿列表。
|
||||
|
||||
Returns:
|
||||
候选碰撞对列表，每个元素为 (i, j)，
|
||||
i < j，索引对应 placements 原始顺序。
|
||||
"""
|
||||
n = len(devices)
|
||||
if n < 2:
|
||||
return []
|
||||
|
||||
# --- 计算每个设备旋转后的 AABB ---
|
||||
aabbs: list[tuple[float, float, float, float]] = []
|
||||
for dev, pl in zip(devices, placements):
|
||||
hw, hd = pl.rotated_bbox(dev)
|
||||
aabbs.append((pl.x - hw, pl.x + hw, pl.y - hd, pl.y + hd))
|
||||
|
||||
# --- 按 xmin 排序，保留原始索引映射 ---
|
||||
sorted_indices = sorted(range(n), key=lambda k: aabbs[k][0])
|
||||
|
||||
# --- 扫描 x 轴，y 轴过滤 ---
|
||||
candidates: list[tuple[int, int]] = []
|
||||
for si in range(len(sorted_indices)):
|
||||
i = sorted_indices[si]
|
||||
x_min_i, x_max_i, y_min_i, y_max_i = aabbs[i]
|
||||
for sj in range(si + 1, len(sorted_indices)):
|
||||
j = sorted_indices[sj]
|
||||
x_min_j, _x_max_j, y_min_j, y_max_j = aabbs[j]
|
||||
# 由于按 xmin 排序，x_min_j >= x_min_i
|
||||
if x_min_j > x_max_i:
|
||||
break # 后续设备 xmin 更大，不可能与 i 在 x 轴交叠
|
||||
# x 轴交叠确认，检查 y 轴
|
||||
if y_min_i <= y_max_j and y_min_j <= y_max_i:
|
||||
# 保证输出 (min_idx, max_idx) 方便去重和测试
|
||||
pair = (min(i, j), max(i, j))
|
||||
candidates.append(pair)
|
||||
|
||||
return candidates
|
||||
|
||||
|
||||
def broad_phase_device_pairs(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
) -> list[tuple[str, str]]:
|
||||
"""返回候选碰撞对的 device_id 字符串元组列表。"""
|
||||
index_pairs = sweep_and_prune_pairs(devices, placements)
|
||||
return [(placements[i].device_id, placements[j].device_id) for i, j in index_pairs]
|
||||
@@ -1,626 +0,0 @@
|
||||
"""约束体系：硬约束 / 软约束定义与统一评估。
|
||||
|
||||
硬约束违反 → cost = inf（方案直接淘汰）
|
||||
软约束违反 → 加权 penalty 累加到 cost
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import math
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from .broad_phase import sweep_and_prune_pairs
|
||||
from .models import Constraint, Device, Lab, Placement
|
||||
from .obb import (
|
||||
nearest_point_on_obb,
|
||||
obb_corners,
|
||||
obb_min_distance,
|
||||
obb_penetration_depth,
|
||||
segment_obb_intersection_length,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from typing import Any
|
||||
|
||||
from .interfaces import CollisionChecker, ReachabilityChecker
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 归一化默认权重 — 1cm距离违规 ≈ 5°角度违规 的惩罚量级
|
||||
DEFAULT_WEIGHT_DISTANCE: float = 100.0 # 1cm → penalty 1.0
|
||||
DEFAULT_WEIGHT_ANGLE: float = 60.0 # 5° → penalty ~1.0
|
||||
|
||||
# 硬约束graduated模式下的惩罚倍数
|
||||
HARD_MULTIPLIER: float = 5.0
|
||||
|
||||
# 优先级等级对应的权重乘数
|
||||
PRIORITY_MULTIPLIERS: dict[str, float] = {
|
||||
"critical": 5.0,
|
||||
"high": 2.0,
|
||||
"normal": 1.0,
|
||||
"low": 0.5,
|
||||
}
|
||||
|
||||
|
||||
def evaluate_constraints(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
lab: Lab,
|
||||
constraints: list[Constraint],
|
||||
collision_checker: CollisionChecker,
|
||||
reachability_checker: ReachabilityChecker | None = None,
|
||||
*,
|
||||
graduated: bool = True,
|
||||
) -> float:
|
||||
"""统一评估所有约束，返回总 cost。
|
||||
|
||||
Args:
|
||||
devices: 设备列表（与 placements 一一对应）
|
||||
placements: 当前布局方案
|
||||
lab: 实验室平面图
|
||||
constraints: 约束规则列表
|
||||
collision_checker: 碰撞检测实例
|
||||
reachability_checker: 可达性检测实例（可选）
|
||||
graduated: True=比例惩罚（DE优化用），False=二值inf（最终pass/fail用）
|
||||
|
||||
Returns:
|
||||
总 cost。硬约束违反在非graduated模式返回 inf，否则为加权 penalty 之和。
|
||||
"""
|
||||
device_map = {d.id: d for d in devices}
|
||||
placement_map = {p.device_id: p for p in placements}
|
||||
|
||||
total_cost = 0.0
|
||||
|
||||
for c in constraints:
|
||||
cost = _evaluate_single(
|
||||
c, device_map, placement_map, lab, collision_checker, reachability_checker,
|
||||
graduated=graduated,
|
||||
)
|
||||
if math.isinf(cost):
|
||||
return math.inf
|
||||
total_cost += cost
|
||||
|
||||
return total_cost
|
||||
|
||||
|
||||
def evaluate_default_hard_constraints(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
lab: Lab,
|
||||
collision_checker: CollisionChecker,
|
||||
*,
|
||||
graduated: bool = True,
|
||||
collision_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER, # 500
|
||||
boundary_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER, # 500
|
||||
) -> float:
|
||||
"""评估默认硬约束（碰撞 + 边界），无需显式声明约束列表。
|
||||
|
||||
始终生效，用于 cost function 的基础检查。
|
||||
|
||||
When graduated=True (default), returns a penalty proportional to the
|
||||
severity of each violation instead of binary inf. This gives DE a
|
||||
smooth gradient so it can fix specific collision pairs instead of
|
||||
discarding near-optimal layouts entirely.
|
||||
|
||||
When graduated=False, uses the legacy binary inf behaviour.
|
||||
"""
|
||||
if not graduated:
|
||||
return _evaluate_hard_binary(devices, placements, lab, collision_checker)
|
||||
|
||||
device_map = {d.id: d for d in devices}
|
||||
cost = 0.0
|
||||
|
||||
# Graduated collision penalty: 2 轴 sweep-and-prune 宽相 + OBB SAT 精确检测
|
||||
candidate_pairs = sweep_and_prune_pairs(devices, placements)
|
||||
for i, j in candidate_pairs:
|
||||
di, dj = device_map[placements[i].device_id], device_map[placements[j].device_id]
|
||||
ci = obb_corners(placements[i].x, placements[i].y,
|
||||
di.bbox[0], di.bbox[1], placements[i].theta)
|
||||
cj = obb_corners(placements[j].x, placements[j].y,
|
||||
dj.bbox[0], dj.bbox[1], placements[j].theta)
|
||||
depth = obb_penetration_depth(ci, cj)
|
||||
if depth > 0:
|
||||
cost += collision_weight * depth
|
||||
|
||||
# Graduated boundary penalty: sum of overshoot distances (rotation-aware)
|
||||
for p in placements:
|
||||
dev = device_map[p.device_id]
|
||||
hw, hd = p.rotated_bbox(dev)
|
||||
# How far each edge exceeds the lab boundary
|
||||
overshoot = 0.0
|
||||
overshoot += max(0.0, hw - p.x) # left wall
|
||||
overshoot += max(0.0, (p.x + hw) - lab.width) # right wall
|
||||
overshoot += max(0.0, hd - p.y) # bottom wall
|
||||
overshoot += max(0.0, (p.y + hd) - lab.depth) # top wall
|
||||
cost += boundary_weight * overshoot
|
||||
|
||||
return cost
|
||||
|
||||
|
||||
def _evaluate_hard_binary(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
lab: Lab,
|
||||
collision_checker: CollisionChecker,
|
||||
) -> float:
|
||||
"""Legacy binary hard-constraint evaluation (inf or 0)."""
|
||||
checker_placements = _to_checker_format(devices, placements)
|
||||
|
||||
collisions = collision_checker.check(checker_placements)
|
||||
if collisions:
|
||||
return math.inf
|
||||
|
||||
if hasattr(collision_checker, "check_bounds"):
|
||||
oob = collision_checker.check_bounds(checker_placements, lab.width, lab.depth)
|
||||
if oob:
|
||||
return math.inf
|
||||
|
||||
return 0.0
|
||||
|
||||
|
||||
def _evaluate_single(
|
||||
constraint: Constraint,
|
||||
device_map: dict[str, Device],
|
||||
placement_map: dict[str, Placement],
|
||||
lab: Lab,
|
||||
collision_checker: CollisionChecker,
|
||||
reachability_checker: ReachabilityChecker | None,
|
||||
*,
|
||||
graduated: bool = True,
|
||||
) -> float:
|
||||
"""评估单条约束规则。
|
||||
|
||||
graduated=True 时硬约束返回比例惩罚（DE用），
|
||||
graduated=False 时硬约束返回 inf（最终 pass/fail）。
|
||||
"""
|
||||
rule = constraint.rule_name
|
||||
params = constraint.params
|
||||
is_hard = constraint.type == "hard"
|
||||
|
||||
effective_weight = constraint.weight
|
||||
|
||||
if rule == "no_collision":
|
||||
checker_placements = _to_checker_format_from_maps(device_map, placement_map)
|
||||
collisions = collision_checker.check(checker_placements)
|
||||
if collisions:
|
||||
if is_hard and not graduated:
|
||||
return math.inf
|
||||
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
|
||||
return w * len(collisions)
|
||||
return 0.0
|
||||
|
||||
if rule == "within_bounds":
|
||||
checker_placements = _to_checker_format_from_maps(device_map, placement_map)
|
||||
if hasattr(collision_checker, "check_bounds"):
|
||||
oob = collision_checker.check_bounds(
|
||||
checker_placements, lab.width, lab.depth
|
||||
)
|
||||
if oob:
|
||||
if is_hard and not graduated:
|
||||
return math.inf
|
||||
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
|
||||
return w * len(oob)
|
||||
return 0.0
|
||||
|
||||
if rule == "distance_less_than":
|
||||
a_id, b_id = params["device_a"], params["device_b"]
|
||||
max_dist = params["distance"]
|
||||
da, db = device_map.get(a_id), device_map.get(b_id)
|
||||
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
|
||||
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
|
||||
if missing_cost is not None:
|
||||
return missing_cost
|
||||
if da and db:
|
||||
dist = _device_distance_obb(da, pa, db, pb)
|
||||
else:
|
||||
dist = _device_distance_center(pa, pb) or 0.0
|
||||
if dist > max_dist:
|
||||
if is_hard and not graduated:
|
||||
return math.inf
|
||||
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
|
||||
return w * (dist - max_dist)
|
||||
return 0.0
|
||||
|
||||
if rule == "distance_greater_than":
|
||||
a_id, b_id = params["device_a"], params["device_b"]
|
||||
min_dist = params["distance"]
|
||||
da, db = device_map.get(a_id), device_map.get(b_id)
|
||||
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
|
||||
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
|
||||
if missing_cost is not None:
|
||||
return missing_cost
|
||||
if da and db:
|
||||
dist = _device_distance_obb(da, pa, db, pb)
|
||||
else:
|
||||
dist = _device_distance_center(pa, pb) or 0.0
|
||||
if dist < min_dist:
|
||||
if is_hard and not graduated:
|
||||
return math.inf
|
||||
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
|
||||
return w * (min_dist - dist)
|
||||
return 0.0
|
||||
|
||||
if rule == "minimize_distance":
|
||||
a_id, b_id = params["device_a"], params["device_b"]
|
||||
da, db = device_map.get(a_id), device_map.get(b_id)
|
||||
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
|
||||
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
|
||||
if missing_cost is not None:
|
||||
return missing_cost
|
||||
if da and db:
|
||||
dist = _device_distance_obb(da, pa, db, pb)
|
||||
else:
|
||||
dist = _device_distance_center(pa, pb) or 0.0
|
||||
return effective_weight * dist
|
||||
|
||||
if rule == "maximize_distance":
|
||||
a_id, b_id = params["device_a"], params["device_b"]
|
||||
da, db = device_map.get(a_id), device_map.get(b_id)
|
||||
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
|
||||
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
|
||||
if missing_cost is not None:
|
||||
return missing_cost
|
||||
if da and db:
|
||||
dist = _device_distance_obb(da, pa, db, pb)
|
||||
else:
|
||||
dist = _device_distance_center(pa, pb) or 0.0
|
||||
max_possible = math.sqrt(lab.width**2 + lab.depth**2)
|
||||
return effective_weight * (max_possible - dist)
|
||||
|
||||
if rule == "min_spacing":
|
||||
min_gap = params.get("min_gap", 0.0)
|
||||
all_placements = list(placement_map.values())
|
||||
total_penalty = 0.0
|
||||
for i in range(len(all_placements)):
|
||||
for j in range(i + 1, len(all_placements)):
|
||||
pi, pj = all_placements[i], all_placements[j]
|
||||
di = device_map.get(pi.device_id)
|
||||
dj = device_map.get(pj.device_id)
|
||||
if di and dj:
|
||||
dist = _device_distance_obb(di, pi, dj, pj)
|
||||
else:
|
||||
dist = _device_distance_center(pi, pj) or 0.0
|
||||
if dist < min_gap:
|
||||
total_penalty += (min_gap - dist)
|
||||
if total_penalty > 0:
|
||||
if is_hard and not graduated:
|
||||
return math.inf
|
||||
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
|
||||
return w * total_penalty
|
||||
return 0.0
|
||||
|
||||
if rule == "reachability":
|
||||
if reachability_checker is None:
|
||||
return 0.0
|
||||
arm_id = params["arm_id"]
|
||||
target_device_id = params["target_device_id"]
|
||||
arm_p = placement_map.get(arm_id)
|
||||
target_p = placement_map.get(target_device_id)
|
||||
missing_cost = _missing_reference_cost(
|
||||
constraint, placement_map, arm_id, target_device_id,
|
||||
)
|
||||
if missing_cost is not None:
|
||||
return missing_cost
|
||||
arm_dev = device_map.get(arm_id)
|
||||
target_dev = device_map.get(target_device_id)
|
||||
|
||||
# opening surface center → nearest point on arm OBB
|
||||
if arm_dev and target_dev:
|
||||
opening_pt = _opening_surface_center(target_dev, target_p)
|
||||
arm_corners = obb_corners(
|
||||
arm_p.x, arm_p.y, arm_dev.bbox[0], arm_dev.bbox[1], arm_p.theta,
|
||||
)
|
||||
nearest = nearest_point_on_obb(opening_pt[0], opening_pt[1], arm_corners)
|
||||
dist = math.sqrt((opening_pt[0] - nearest[0])**2 + (opening_pt[1] - nearest[1])**2)
|
||||
else:
|
||||
opening_pt = (target_p.x, target_p.y)
|
||||
nearest = (arm_p.x, arm_p.y)
|
||||
dist = _device_distance_center(arm_p, target_p) or 0.0
|
||||
|
||||
# 交叉惩罚始终计算（soft, 不依赖可达性结果）
|
||||
crossing_cost = _crossing_penalty(
|
||||
opening_pt, nearest,
|
||||
arm_id, target_device_id,
|
||||
device_map, placement_map,
|
||||
)
|
||||
|
||||
arm_pose = {"x": arm_p.x, "y": arm_p.y, "theta": arm_p.theta}
|
||||
target_point = {"x": target_p.x, "y": target_p.y, "z": 0.0}
|
||||
target_point["_obb_dist"] = dist
|
||||
if not reachability_checker.is_reachable(arm_id, arm_pose, target_point):
|
||||
if is_hard and not graduated:
|
||||
return math.inf
|
||||
# Graduated: overshoot penalty + crossing cost
|
||||
max_reach = reachability_checker.arm_reach.get(arm_id, 2.0)
|
||||
overshoot = max(0.0, dist - max_reach)
|
||||
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
|
||||
return w * overshoot * 10.0 + crossing_cost
|
||||
|
||||
return crossing_cost
|
||||
|
||||
if rule == "prefer_aligned":
|
||||
alignment_cost = sum(
|
||||
(1 - math.cos(4 * p.theta)) / 2 for p in placement_map.values()
|
||||
)
|
||||
if is_hard:
|
||||
if not graduated:
|
||||
return math.inf if alignment_cost > 1e-6 else 0.0
|
||||
return HARD_MULTIPLIER * effective_weight * alignment_cost
|
||||
return effective_weight * alignment_cost
|
||||
|
||||
if rule == "prefer_seeder_orientation":
|
||||
target_thetas = params.get("target_thetas", {})
|
||||
cost = 0.0
|
||||
for dev_id, target in target_thetas.items():
|
||||
p = placement_map.get(dev_id)
|
||||
if p is None:
|
||||
continue
|
||||
# Circular distance: (1 - cos(diff)) / 2 gives 0..1 range
|
||||
diff = p.theta - target
|
||||
cost += (1 - math.cos(diff)) / 2
|
||||
return effective_weight * cost
|
||||
|
||||
if rule == "prefer_orientation_mode":
|
||||
mode = params.get("mode", "outward")
|
||||
center_x = lab.width / 2
|
||||
center_y = lab.depth / 2
|
||||
cost = 0.0
|
||||
for dev_id, p in placement_map.items():
|
||||
dev = device_map.get(dev_id)
|
||||
if dev is None:
|
||||
continue
|
||||
target = _desired_theta(
|
||||
p.x, p.y, center_x, center_y, dev, mode,
|
||||
)
|
||||
if target is None:
|
||||
continue
|
||||
diff = p.theta - target
|
||||
cost += (1 - math.cos(diff)) / 2
|
||||
return effective_weight * cost
|
||||
|
||||
# 未知约束类型，忽略
|
||||
return 0.0
|
||||
|
||||
|
||||
def _desired_theta(
|
||||
x: float, y: float,
|
||||
center_x: float, center_y: float,
|
||||
device: Device, mode: str,
|
||||
) -> float | None:
|
||||
"""Compute desired theta for outward/inward facing at the given position."""
|
||||
dx = x - center_x
|
||||
dy = y - center_y
|
||||
if abs(dx) < 1e-9 and abs(dy) < 1e-9:
|
||||
return None # At center, no preferred direction
|
||||
angle_to_device = math.atan2(dy, dx)
|
||||
front = device.openings[0].direction if device.openings else (0.0, -1.0)
|
||||
front_angle = math.atan2(front[1], front[0])
|
||||
if mode == "outward":
|
||||
target = angle_to_device
|
||||
elif mode == "inward":
|
||||
target = angle_to_device + math.pi
|
||||
else:
|
||||
return None
|
||||
return (target - front_angle) % (2 * math.pi)
|
||||
|
||||
|
||||
def _device_distance_center(a: Placement | None, b: Placement | None) -> float | None:
|
||||
"""计算两设备中心的欧几里得距离（后备方法）。"""
|
||||
if a is None or b is None:
|
||||
return None
|
||||
return math.sqrt((a.x - b.x) ** 2 + (a.y - b.y) ** 2)
|
||||
|
||||
|
||||
def _device_distance_obb(
|
||||
device_a: Device, placement_a: Placement,
|
||||
device_b: Device, placement_b: Placement,
|
||||
) -> float:
|
||||
"""Minimum edge-to-edge distance between two devices using OBB."""
|
||||
corners_a = obb_corners(
|
||||
placement_a.x, placement_a.y,
|
||||
device_a.bbox[0], device_a.bbox[1],
|
||||
placement_a.theta,
|
||||
)
|
||||
corners_b = obb_corners(
|
||||
placement_b.x, placement_b.y,
|
||||
device_b.bbox[0], device_b.bbox[1],
|
||||
placement_b.theta,
|
||||
)
|
||||
return obb_min_distance(corners_a, corners_b)
|
||||
|
||||
|
||||
def _to_checker_format(
|
||||
devices: list[Device], placements: list[Placement]
|
||||
) -> list[dict]:
|
||||
"""转换为 CollisionChecker.check() 接受的格式。"""
|
||||
device_map = {d.id: d for d in devices}
|
||||
result = []
|
||||
for p in placements:
|
||||
dev = device_map.get(p.device_id)
|
||||
if dev is None:
|
||||
continue
|
||||
result.append({"id": p.device_id, "bbox": dev.bbox, "pos": (p.x, p.y, p.theta)})
|
||||
return result
|
||||
|
||||
|
||||
def _to_checker_format_from_maps(
|
||||
device_map: dict[str, Device], placement_map: dict[str, Placement]
|
||||
) -> list[dict]:
|
||||
"""从 map 转换为 CollisionChecker.check() 接受的格式。"""
|
||||
result = []
|
||||
for dev_id, p in placement_map.items():
|
||||
dev = device_map.get(dev_id)
|
||||
if dev is None:
|
||||
continue
|
||||
result.append({"id": dev_id, "bbox": dev.bbox, "pos": (p.x, p.y, p.theta)})
|
||||
return result
|
||||
|
||||
|
||||
def _opening_surface_center(
|
||||
device: Device, placement: Placement,
|
||||
) -> tuple[float, float]:
|
||||
"""Return the world-space center of the device's opening surface.
|
||||
|
||||
Computes where the opening direction intersects the device's bbox boundary,
|
||||
then transforms to world coordinates. For a device facing away from the arm,
|
||||
this point is on the far side — making the distance to the arm larger,
|
||||
which naturally penalizes wrong orientation.
|
||||
"""
|
||||
front = device.openings[0].direction if device.openings else (0.0, -1.0)
|
||||
dx, dy = front
|
||||
w, h = device.bbox
|
||||
|
||||
# Scale factor to reach bbox edge in the opening direction
|
||||
scales = []
|
||||
if abs(dx) > 1e-9:
|
||||
scales.append((w / 2) / abs(dx))
|
||||
if abs(dy) > 1e-9:
|
||||
scales.append((h / 2) / abs(dy))
|
||||
scale = min(scales) if scales else 0.0
|
||||
|
||||
# Opening center in local frame
|
||||
local_x = dx * scale
|
||||
local_y = dy * scale
|
||||
|
||||
# Rotate to world frame and translate
|
||||
cos_t = math.cos(placement.theta)
|
||||
sin_t = math.sin(placement.theta)
|
||||
world_x = placement.x + local_x * cos_t - local_y * sin_t
|
||||
world_y = placement.y + local_x * sin_t + local_y * cos_t
|
||||
return (world_x, world_y)
|
||||
|
||||
|
||||
def evaluate_default_hard_constraints_breakdown(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
lab: Lab,
|
||||
collision_checker: CollisionChecker,
|
||||
*,
|
||||
collision_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER,
|
||||
boundary_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER,
|
||||
) -> dict[str, float]:
|
||||
"""与 evaluate_default_hard_constraints 逻辑相同，但返回分项明细。"""
|
||||
device_map = {d.id: d for d in devices}
|
||||
collision_cost = 0.0
|
||||
boundary_cost = 0.0
|
||||
|
||||
candidate_pairs = sweep_and_prune_pairs(devices, placements)
|
||||
for i, j in candidate_pairs:
|
||||
di, dj = device_map[placements[i].device_id], device_map[placements[j].device_id]
|
||||
ci = obb_corners(placements[i].x, placements[i].y,
|
||||
di.bbox[0], di.bbox[1], placements[i].theta)
|
||||
cj = obb_corners(placements[j].x, placements[j].y,
|
||||
dj.bbox[0], dj.bbox[1], placements[j].theta)
|
||||
depth = obb_penetration_depth(ci, cj)
|
||||
if depth > 0:
|
||||
collision_cost += collision_weight * depth
|
||||
|
||||
for p in placements:
|
||||
dev = device_map[p.device_id]
|
||||
hw, hd = p.rotated_bbox(dev)
|
||||
overshoot = 0.0
|
||||
overshoot += max(0.0, hw - p.x)
|
||||
overshoot += max(0.0, (p.x + hw) - lab.width)
|
||||
overshoot += max(0.0, hd - p.y)
|
||||
overshoot += max(0.0, (p.y + hd) - lab.depth)
|
||||
boundary_cost += boundary_weight * overshoot
|
||||
|
||||
return {
|
||||
"collision": collision_cost,
|
||||
"boundary": boundary_cost,
|
||||
"total": collision_cost + boundary_cost,
|
||||
"collision_weight": collision_weight,
|
||||
"boundary_weight": boundary_weight,
|
||||
}
|
||||
|
||||
|
||||
def evaluate_constraints_breakdown(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
lab: Lab,
|
||||
constraints: list[Constraint],
|
||||
collision_checker: CollisionChecker,
|
||||
reachability_checker: ReachabilityChecker | None = None,
|
||||
) -> list[dict[str, Any]]:
|
||||
"""与 evaluate_constraints 逻辑相同，但返回每条约束的分项明细。"""
|
||||
device_map = {d.id: d for d in devices}
|
||||
placement_map = {p.device_id: p for p in placements}
|
||||
|
||||
results = []
|
||||
for c in constraints:
|
||||
cost = _evaluate_single(
|
||||
c, device_map, placement_map, lab, collision_checker, reachability_checker,
|
||||
graduated=True,
|
||||
)
|
||||
results.append({
|
||||
"name": _constraint_display_name(c),
|
||||
"rule": c.rule_name,
|
||||
"type": c.type,
|
||||
"cost": cost,
|
||||
"weight": c.weight,
|
||||
})
|
||||
return results
|
||||
|
||||
|
||||
def _missing_reference_cost(
|
||||
constraint: Constraint,
|
||||
placement_map: dict[str, Placement],
|
||||
*device_ids: str,
|
||||
) -> float | None:
|
||||
"""当约束引用不存在的设备时返回对应 cost。"""
|
||||
missing = sorted({device_id for device_id in device_ids if device_id not in placement_map})
|
||||
if not missing:
|
||||
return None
|
||||
|
||||
logger.warning(
|
||||
"Constraint %s references missing device IDs: %s",
|
||||
constraint.rule_name,
|
||||
", ".join(missing),
|
||||
)
|
||||
if constraint.type == "hard":
|
||||
return math.inf
|
||||
return 0.0
|
||||
|
||||
|
||||
def _constraint_display_name(c: Constraint) -> str:
|
||||
"""为约束生成可读的显示名称。"""
|
||||
params = c.params
|
||||
if c.rule_name in (
|
||||
"distance_less_than", "distance_greater_than",
|
||||
"minimize_distance", "maximize_distance",
|
||||
):
|
||||
return f"{c.rule_name}({params.get('device_a', '?')}, {params.get('device_b', '?')})"
|
||||
if c.rule_name == "reachability":
|
||||
return f"reachability({params.get('arm_id', '?')}, {params.get('target_device_id', '?')})"
|
||||
if c.rule_name == "min_spacing":
|
||||
return f"min_spacing(gap={params.get('min_gap', '?')})"
|
||||
if c.rule_name == "prefer_orientation_mode":
|
||||
return f"prefer_orientation_mode({params.get('mode', '?')})"
|
||||
return c.rule_name
|
||||
|
||||
|
||||
def _crossing_penalty(
|
||||
opening_pt: tuple[float, float],
|
||||
arm_nearest_pt: tuple[float, float],
|
||||
arm_id: str,
|
||||
target_id: str,
|
||||
device_map: dict[str, Device],
|
||||
placement_map: dict[str, Placement],
|
||||
) -> float:
|
||||
"""交叉惩罚：其他设备 OBB 遮挡 opening→arm 路径的长度加权 penalty。
|
||||
|
||||
Soft penalty，权重 = DEFAULT_WEIGHT_DISTANCE * 穿过各遮挡设备 OBB 的线段长度之和。
|
||||
始终生效（不论可达性是否通过），为 DE 提供清晰的梯度信号。
|
||||
"""
|
||||
cost = 0.0
|
||||
for dev_id, p in placement_map.items():
|
||||
if dev_id == arm_id or dev_id == target_id:
|
||||
continue
|
||||
dev = device_map.get(dev_id)
|
||||
if dev is None:
|
||||
continue
|
||||
corners = obb_corners(p.x, p.y, dev.bbox[0], dev.bbox[1], p.theta)
|
||||
crossing_len = segment_obb_intersection_length(opening_pt, arm_nearest_pt, corners)
|
||||
cost += DEFAULT_WEIGHT_DISTANCE * crossing_len
|
||||
return cost
|
||||
@@ -1,302 +0,0 @@
|
||||
"""双源设备目录：从 uni-lab-assets 和 Uni-Lab-OS registry 加载设备。
|
||||
|
||||
数据流：
|
||||
footprints.json (离线提取) + data.json (资产树) + registry device_mesh dirs
|
||||
→ merge → Device 列表
|
||||
|
||||
footprints.json 由 extract_footprints.py 生成，包含碰撞包围盒、开口方向等。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from collections import Counter
|
||||
import json
|
||||
import logging
|
||||
from pathlib import Path
|
||||
|
||||
from .models import Device, Opening
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 默认路径（相对于本文件）
|
||||
_THIS_DIR = Path(__file__).resolve().parent
|
||||
_DEFAULT_FOOTPRINTS = _THIS_DIR / "footprints.json"
|
||||
|
||||
# 手动后备尺寸（trimesh 不可用时）
|
||||
KNOWN_SIZES: dict[str, tuple[float, float]] = {
|
||||
"elite_cs66_arm": (0.20, 0.20),
|
||||
"elite_cs612_arm": (0.20, 0.20),
|
||||
"ot2": (0.62, 0.50),
|
||||
"agilent_bravo": (0.80, 0.65),
|
||||
"thermo_orbitor_rs2": (0.45, 0.55),
|
||||
"hplc_station": (0.60, 0.50),
|
||||
"1_3m_hamilton_table": (1.30, 0.75),
|
||||
}
|
||||
|
||||
DEFAULT_BBOX: tuple[float, float] = (0.6, 0.4)
|
||||
|
||||
# ---------- footprints.json 加载 ----------
|
||||
|
||||
_footprints_cache: dict[str, dict] | None = None
|
||||
|
||||
|
||||
def load_footprints(path: str | Path = _DEFAULT_FOOTPRINTS) -> dict[str, dict]:
|
||||
"""加载 footprints.json 并缓存。"""
|
||||
global _footprints_cache
|
||||
if _footprints_cache is not None:
|
||||
return _footprints_cache
|
||||
|
||||
p = Path(path)
|
||||
if not p.exists():
|
||||
logger.warning("footprints.json not found at %s", p)
|
||||
_footprints_cache = {}
|
||||
return _footprints_cache
|
||||
|
||||
with open(p) as f:
|
||||
_footprints_cache = json.load(f)
|
||||
logger.info("Loaded %d footprints from %s", len(_footprints_cache), p)
|
||||
return _footprints_cache
|
||||
|
||||
|
||||
def reset_footprints_cache() -> None:
|
||||
"""清除缓存（测试用）。"""
|
||||
global _footprints_cache
|
||||
_footprints_cache = None
|
||||
|
||||
|
||||
# ---------- 从 footprints 构建 Device ----------
|
||||
|
||||
|
||||
def _footprint_to_device(
|
||||
device_id: str,
|
||||
fp: dict,
|
||||
name: str = "",
|
||||
models_url_prefix: str = "/models",
|
||||
) -> Device:
|
||||
"""从 footprints.json 条目创建 Device。"""
|
||||
bbox = tuple(fp.get("bbox", DEFAULT_BBOX))
|
||||
openings = [
|
||||
Opening(direction=tuple(o["direction"]), label=o.get("label", ""))
|
||||
for o in fp.get("openings", [])
|
||||
]
|
||||
|
||||
model_file = fp.get("model_file", "")
|
||||
model_path = f"{models_url_prefix}/{device_id}/{model_file}" if model_file else ""
|
||||
model_type = fp.get("model_type", "")
|
||||
|
||||
thumb_file = fp.get("thumbnail_file", "")
|
||||
thumbnail_url = f"{models_url_prefix}/{device_id}/{thumb_file}" if thumb_file else ""
|
||||
|
||||
return Device(
|
||||
id=device_id,
|
||||
name=name or device_id.replace("_", " ").title(),
|
||||
bbox=bbox,
|
||||
device_type="articulation" if "robot" in device_id or "arm" in device_id or "flex" in device_id else "static",
|
||||
height=fp.get("height", 0.4),
|
||||
origin_offset=tuple(fp.get("origin_offset", [0.0, 0.0])),
|
||||
openings=openings,
|
||||
source=fp.get("source", "manual"),
|
||||
model_path=model_path,
|
||||
model_type=model_type,
|
||||
thumbnail_url=thumbnail_url,
|
||||
)
|
||||
|
||||
|
||||
# ---------- 从 data.json 加载 ----------
|
||||
|
||||
|
||||
def load_devices_from_assets(
|
||||
data_json_path: str | Path,
|
||||
footprints: dict[str, dict] | None = None,
|
||||
models_url_prefix: str = "/models",
|
||||
) -> list[Device]:
|
||||
"""从 uni-lab-assets 的 data.json 加载设备列表。
|
||||
|
||||
如果设备在 footprints 中有条目，使用真实尺寸；否则使用默认值。
|
||||
"""
|
||||
path = Path(data_json_path)
|
||||
if not path.exists():
|
||||
logger.warning("data.json not found at %s, returning empty list", path)
|
||||
return []
|
||||
|
||||
if footprints is None:
|
||||
footprints = load_footprints()
|
||||
|
||||
with open(path) as f:
|
||||
data = json.load(f)
|
||||
|
||||
devices: list[Device] = []
|
||||
_flatten_tree(data, devices, footprints, models_url_prefix)
|
||||
return devices
|
||||
|
||||
|
||||
def _flatten_tree(
|
||||
nodes: list[dict],
|
||||
result: list[Device],
|
||||
footprints: dict[str, dict],
|
||||
models_url_prefix: str,
|
||||
) -> None:
|
||||
"""递归遍历树形结构，提取叶节点为 Device。"""
|
||||
for node in nodes:
|
||||
if "children" in node:
|
||||
_flatten_tree(node["children"], result, footprints, models_url_prefix)
|
||||
elif "id" in node:
|
||||
device_id = node["id"]
|
||||
name = node.get("label", device_id)
|
||||
|
||||
if device_id in footprints:
|
||||
dev = _footprint_to_device(
|
||||
device_id, footprints[device_id], name, models_url_prefix
|
||||
)
|
||||
else:
|
||||
bbox = KNOWN_SIZES.get(device_id, DEFAULT_BBOX)
|
||||
dev = Device(id=device_id, name=name, bbox=bbox, source="assets")
|
||||
|
||||
result.append(dev)
|
||||
|
||||
|
||||
# ---------- 从 registry 加载 ----------
|
||||
|
||||
|
||||
def load_devices_from_registry(
|
||||
device_mesh_dir: str | Path,
|
||||
footprints: dict[str, dict] | None = None,
|
||||
models_url_prefix: str = "/models",
|
||||
) -> list[Device]:
|
||||
"""从 Uni-Lab-OS device_mesh/devices/ 加载 registry 设备。"""
|
||||
d = Path(device_mesh_dir)
|
||||
if not d.exists():
|
||||
logger.warning("Registry dir not found at %s", d)
|
||||
return []
|
||||
|
||||
if footprints is None:
|
||||
footprints = load_footprints()
|
||||
|
||||
devices: list[Device] = []
|
||||
for entry in sorted(d.iterdir()):
|
||||
if not entry.is_dir():
|
||||
continue
|
||||
device_id = entry.name
|
||||
if device_id in footprints:
|
||||
dev = _footprint_to_device(
|
||||
device_id, footprints[device_id], models_url_prefix=models_url_prefix
|
||||
)
|
||||
dev.source = "registry"
|
||||
else:
|
||||
bbox = KNOWN_SIZES.get(device_id, DEFAULT_BBOX)
|
||||
dev = Device(id=device_id, name=device_id.replace("_", " ").title(), bbox=bbox, source="registry")
|
||||
devices.append(dev)
|
||||
|
||||
return devices
|
||||
|
||||
|
||||
# ---------- 合并与去重 ----------
|
||||
|
||||
|
||||
def merge_device_lists(
|
||||
registry_devices: list[Device],
|
||||
asset_devices: list[Device],
|
||||
) -> list[Device]:
|
||||
"""合并双源设备列表，registry 优先。
|
||||
|
||||
对于同时存在于两个源的设备，使用 registry 条目的元数据，
|
||||
但优先使用 assets 的 3D 模型路径和缩略图。
|
||||
"""
|
||||
merged: dict[str, Device] = {}
|
||||
|
||||
for dev in asset_devices:
|
||||
merged[dev.id] = dev
|
||||
|
||||
for dev in registry_devices:
|
||||
if dev.id in merged:
|
||||
# registry 元数据优先，但保留 assets 的模型/缩略图
|
||||
asset_dev = merged[dev.id]
|
||||
dev.model_path = dev.model_path or asset_dev.model_path
|
||||
dev.model_type = dev.model_type or asset_dev.model_type
|
||||
dev.thumbnail_url = dev.thumbnail_url or asset_dev.thumbnail_url
|
||||
if dev.bbox == DEFAULT_BBOX and asset_dev.bbox != DEFAULT_BBOX:
|
||||
dev.bbox = asset_dev.bbox
|
||||
dev.height = asset_dev.height
|
||||
dev.origin_offset = asset_dev.origin_offset
|
||||
dev.openings = asset_dev.openings
|
||||
dev.source = "registry"
|
||||
merged[dev.id] = dev
|
||||
|
||||
return list(merged.values())
|
||||
|
||||
|
||||
# ---------- 统一解析器 ----------
|
||||
|
||||
|
||||
def resolve_device(
|
||||
device_id: str,
|
||||
footprints: dict[str, dict] | None = None,
|
||||
models_url_prefix: str = "/models",
|
||||
) -> Device | None:
|
||||
"""按 ID 查找单个设备。先查 footprints，再查 KNOWN_SIZES。"""
|
||||
if footprints is None:
|
||||
footprints = load_footprints()
|
||||
|
||||
if device_id in footprints:
|
||||
return _footprint_to_device(
|
||||
device_id, footprints[device_id], models_url_prefix=models_url_prefix
|
||||
)
|
||||
|
||||
if device_id in KNOWN_SIZES:
|
||||
bbox = KNOWN_SIZES[device_id]
|
||||
return Device(id=device_id, name=device_id.replace("_", " ").title(), bbox=bbox, source="manual")
|
||||
|
||||
return None
|
||||
|
||||
|
||||
# ---------- 向后兼容 ----------
|
||||
|
||||
|
||||
def create_devices_from_list(
|
||||
device_specs: list[dict],
|
||||
) -> list[Device]:
|
||||
"""从 API 请求中的设备列表创建 Device 对象（向后兼容）。
|
||||
|
||||
Args:
|
||||
device_specs: [{"id": str, "name": str, "size": [w, d], "uuid": str}, ...]
|
||||
size 可选，缺失时使用 footprints 或默认值。
|
||||
"""
|
||||
footprints = load_footprints()
|
||||
devices = []
|
||||
catalog_counts = Counter(spec["id"] for spec in device_specs)
|
||||
catalog_seen: Counter[str] = Counter()
|
||||
|
||||
for spec in device_specs:
|
||||
catalog_id = spec["id"]
|
||||
catalog_seen[catalog_id] += 1
|
||||
instance_idx = catalog_seen[catalog_id]
|
||||
if catalog_counts[catalog_id] > 1 and instance_idx > 1:
|
||||
dev_id = f"{catalog_id}#{instance_idx}"
|
||||
else:
|
||||
dev_id = catalog_id
|
||||
size = spec.get("size")
|
||||
if size:
|
||||
bbox = (float(size[0]), float(size[1]))
|
||||
elif catalog_id in footprints:
|
||||
bbox = tuple(footprints[catalog_id].get("bbox", DEFAULT_BBOX))
|
||||
else:
|
||||
bbox = KNOWN_SIZES.get(catalog_id, DEFAULT_BBOX)
|
||||
|
||||
openings = []
|
||||
if catalog_id in footprints:
|
||||
openings = [
|
||||
Opening(direction=tuple(o["direction"]), label=o.get("label", ""))
|
||||
for o in footprints[catalog_id].get("openings", [])
|
||||
]
|
||||
|
||||
devices.append(
|
||||
Device(
|
||||
id=dev_id,
|
||||
name=spec.get("name", catalog_id),
|
||||
bbox=bbox,
|
||||
device_type=spec.get("device_type", "static"),
|
||||
openings=openings,
|
||||
uuid=spec.get("uuid", ""),
|
||||
)
|
||||
)
|
||||
return devices
|
||||
@@ -1,559 +0,0 @@
|
||||
"""从 STL/GLB 网格提取设备足迹（碰撞包围盒）。
|
||||
|
||||
运行方式:
|
||||
conda activate phase3
|
||||
python -m layout_optimizer.extract_footprints
|
||||
|
||||
输出 footprints.json 供 device_catalog.py 和 2D 规划器使用。
|
||||
|
||||
GLB root node rotation:
|
||||
每个设备的 GLB 文件包含根节点旋转四元数，定义 STL 原生坐标到 glTF Y-up
|
||||
约定的轴映射。extract_one_device() 读取 GLB JSON，提取旋转矩阵，
|
||||
应用到 STL 包围盒后按 glTF 约定提取 2D 足迹 (X=width, Z=depth, Y=height)。
|
||||
GLB scale 不应用——STL 文件已是米制坐标。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import logging
|
||||
import math
|
||||
import os
|
||||
import re
|
||||
import struct
|
||||
import xml.etree.ElementTree as ET
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 测试设备的开口方向（手动标注）
|
||||
# direction 为设备局部坐标系中的单位向量，[0, -1] 表示设备正前方
|
||||
MANUAL_OPENINGS: dict[str, list[dict]] = {
|
||||
"agilent_bravo": [{"direction": [0, -1], "label": "front_plate_slot"}],
|
||||
"opentrons_liquid_handler": [{"direction": [0, -1], "label": "front_deck"}],
|
||||
"opentrons_flex": [{"direction": [0, -1], "label": "front_deck"}],
|
||||
"thermo_orbitor_rs2_hotel": [{"direction": [0, -1], "label": "front_door"}],
|
||||
"hamilton_star": [{"direction": [0, -1], "label": "front_deck"}],
|
||||
"tecan_spark_plate_reader": [{"direction": [0, -1], "label": "front_slot"}],
|
||||
"highres_bio_plate_hotel_12": [{"direction": [0, -1], "label": "front_shelf"}],
|
||||
"beckman_coulter_orbital_shaker_alp": [],
|
||||
"liconic_str44_incubator": [{"direction": [0, -1], "label": "front_door"}],
|
||||
"elite_robot": [], # 机械臂，无开口
|
||||
}
|
||||
|
||||
# 手动尺寸后备（trimesh 提取失败时使用）
|
||||
FALLBACK_SIZES: dict[str, tuple[float, float, float]] = {
|
||||
"elite_robot": (0.20, 0.20, 0.10),
|
||||
"elite_cs66_arm": (0.20, 0.20, 0.10),
|
||||
"elite_cs612_arm": (0.20, 0.20, 0.10),
|
||||
}
|
||||
|
||||
|
||||
def extract_openings_from_xacro(
|
||||
xacro_path: Path,
|
||||
bbox_center_xy: tuple[float, float],
|
||||
bbox_size_xy: tuple[float, float],
|
||||
) -> list[dict]:
|
||||
"""从 XACRO 文件自动提取设备开口方向。
|
||||
|
||||
解析 fixed joint 中包含 "socket" 的关节，计算其 XY 质心，与包围盒中心比较，
|
||||
映射到最近的基本方向。
|
||||
|
||||
Args:
|
||||
xacro_path: modal.xacro 文件路径
|
||||
bbox_center_xy: 包围盒 XY 中心 (cx, cy)
|
||||
bbox_size_xy: 包围盒 XY 尺寸 (w, d)
|
||||
|
||||
Returns:
|
||||
[{"direction": [dx, dy], "label": "auto_xacro"}] 或 []
|
||||
"""
|
||||
# --- 方法1: ElementTree 解析（忽略 xacro 命名空间） ---
|
||||
socket_positions: list[tuple[float, float]] = []
|
||||
|
||||
try:
|
||||
xacro_text = xacro_path.read_text(encoding="utf-8", errors="replace")
|
||||
|
||||
# 去掉 xacro 命名空间前缀，避免 ElementTree 解析失败
|
||||
xacro_text_clean = re.sub(r'\bxacro:', '', xacro_text)
|
||||
|
||||
root = ET.fromstring(xacro_text_clean)
|
||||
|
||||
for joint in root.iter("joint"):
|
||||
joint_name = joint.get("name", "")
|
||||
joint_type = joint.get("type", "")
|
||||
if "socket" not in joint_name.lower():
|
||||
continue
|
||||
if joint_type != "fixed":
|
||||
continue
|
||||
origin = joint.find("origin")
|
||||
if origin is None:
|
||||
continue
|
||||
xyz_str = origin.get("xyz", "")
|
||||
if not xyz_str:
|
||||
continue
|
||||
parts = xyz_str.split()
|
||||
if len(parts) < 2:
|
||||
continue
|
||||
try:
|
||||
x = float(parts[0])
|
||||
y = float(parts[1])
|
||||
socket_positions.append((x, y))
|
||||
except ValueError:
|
||||
continue
|
||||
|
||||
except ET.ParseError as e:
|
||||
logger.debug("ElementTree parse error for %s: %s — falling back to regex", xacro_path, e)
|
||||
|
||||
# --- 方法2: 正则表达式后备（当 ElementTree 失败或无结果时） ---
|
||||
if not socket_positions:
|
||||
try:
|
||||
xacro_text = xacro_path.read_text(encoding="utf-8", errors="replace")
|
||||
# 匹配包含 "socket" 的 joint 块，提取 origin xyz
|
||||
joint_blocks = re.findall(
|
||||
r'<joint\s[^>]*name=["\'][^"\']*socket[^"\']*["\'][^>]*>.*?</joint>',
|
||||
xacro_text,
|
||||
flags=re.IGNORECASE | re.DOTALL,
|
||||
)
|
||||
for block in joint_blocks:
|
||||
# 只处理 fixed 类型
|
||||
if 'type="fixed"' not in block and "type='fixed'" not in block:
|
||||
continue
|
||||
xyz_match = re.search(r'<origin[^>]*xyz=["\']([^"\']+)["\']', block)
|
||||
if not xyz_match:
|
||||
continue
|
||||
parts = xyz_match.group(1).split()
|
||||
if len(parts) < 2:
|
||||
continue
|
||||
try:
|
||||
x = float(parts[0])
|
||||
y = float(parts[1])
|
||||
socket_positions.append((x, y))
|
||||
except ValueError:
|
||||
continue
|
||||
except Exception as e:
|
||||
logger.debug("Regex fallback also failed for %s: %s", xacro_path, e)
|
||||
|
||||
if not socket_positions:
|
||||
return []
|
||||
|
||||
# 计算 socket XY 质心
|
||||
cx_sock = sum(p[0] for p in socket_positions) / len(socket_positions)
|
||||
cy_sock = sum(p[1] for p in socket_positions) / len(socket_positions)
|
||||
|
||||
# 方向向量：从包围盒中心指向 socket 质心
|
||||
dx = cx_sock - bbox_center_xy[0]
|
||||
dy = cy_sock - bbox_center_xy[1]
|
||||
|
||||
# 如果 socket 质心非常靠近包围盒中心（<5% 尺寸），判断为顶部装载
|
||||
threshold = 0.05 * max(bbox_size_xy[0], bbox_size_xy[1], 1e-6)
|
||||
if math.hypot(dx, dy) < threshold:
|
||||
logger.debug(
|
||||
"%s: socket centroid too close to bbox center (dist=%.4f, threshold=%.4f) → top-loading",
|
||||
xacro_path.parent.name,
|
||||
math.hypot(dx, dy),
|
||||
threshold,
|
||||
)
|
||||
return []
|
||||
|
||||
# 映射到最近基本方向
|
||||
# socket 质心指示交互区在设备哪一侧，而 opening direction 是从该面
|
||||
# 向外的法线方向（与质心偏移同向），这里的 dx/dy 已经是从包围盒中心
|
||||
# 指向 socket 区域的方向，即 opening 朝外的方向
|
||||
# 注意：在 uni-lab-assets 中，大多数设备 front 在 Y=0 而 body 在 -Y，
|
||||
# 所以 socket 集中在 +Y 侧（靠近 Y=0 前端），bbox 中心在 -Y/2。
|
||||
# 方向 center→socket = +Y，但 "opening faces front" 在手动标注中
|
||||
# 写作 [0, -1]（法线向外=向操作者方向）。
|
||||
# 因此需要取反：opening direction = -(center→socket)
|
||||
if abs(dx) >= abs(dy):
|
||||
cardinal = [-1, 0] if dx > 0 else [1, 0]
|
||||
else:
|
||||
cardinal = [0, -1] if dy > 0 else [0, 1]
|
||||
|
||||
logger.debug(
|
||||
"%s: %d socket joints → centroid=(%.3f, %.3f) dir=%s",
|
||||
xacro_path.parent.name,
|
||||
len(socket_positions),
|
||||
cx_sock,
|
||||
cy_sock,
|
||||
cardinal,
|
||||
)
|
||||
return [{"direction": cardinal, "label": "auto_xacro"}]
|
||||
|
||||
|
||||
def _find_mesh_files(device_dir: Path) -> list[Path]:
|
||||
"""查找设备目录中的所有 STL/GLB 网格文件。"""
|
||||
mesh_files: list[Path] = []
|
||||
meshes_dir = device_dir / "meshes"
|
||||
if not meshes_dir.exists():
|
||||
return mesh_files
|
||||
|
||||
# uni-lab-assets 结构: meshes/*.stl, meshes/*.glb
|
||||
for f in meshes_dir.iterdir():
|
||||
if f.suffix.lower() in (".stl", ".glb"):
|
||||
mesh_files.append(f)
|
||||
|
||||
# registry 结构: meshes/<variant>/collision/*.stl
|
||||
if not mesh_files:
|
||||
for variant_dir in meshes_dir.iterdir():
|
||||
if variant_dir.is_dir():
|
||||
collision_dir = variant_dir / "collision"
|
||||
if collision_dir.exists():
|
||||
for f in collision_dir.iterdir():
|
||||
if f.suffix.lower() == ".stl":
|
||||
mesh_files.append(f)
|
||||
if mesh_files:
|
||||
break # 使用找到的第一个变体
|
||||
|
||||
return sorted(mesh_files)
|
||||
|
||||
|
||||
def _find_best_model_file(device_dir: Path) -> tuple[str, str]:
|
||||
"""找到最佳可展示的模型文件。优先 GLB > STL。
|
||||
|
||||
Returns:
|
||||
(relative_path, model_type) e.g. ("meshes/0_base.glb", "gltf")
|
||||
"""
|
||||
meshes_dir = device_dir / "meshes"
|
||||
if not meshes_dir.exists():
|
||||
return "", ""
|
||||
|
||||
glbs = sorted(meshes_dir.glob("*.glb"))
|
||||
if glbs:
|
||||
return f"meshes/{glbs[0].name}", "gltf"
|
||||
|
||||
stls = sorted(f for f in meshes_dir.glob("*.stl") if f.suffix == ".stl")
|
||||
if not stls:
|
||||
stls = sorted(f for f in meshes_dir.glob("*.STL"))
|
||||
if stls:
|
||||
return f"meshes/{stls[0].name}", "stl"
|
||||
|
||||
return "", ""
|
||||
|
||||
|
||||
def _find_thumbnail(device_dir: Path) -> str:
|
||||
"""查找设备目录中的第一个 PNG 缩略图。"""
|
||||
pngs = sorted(device_dir.glob("*.png"))
|
||||
if pngs:
|
||||
return pngs[0].name
|
||||
return ""
|
||||
|
||||
|
||||
def _read_glb_json(glb_path: Path) -> dict | None:
|
||||
"""Read the JSON chunk from a GLB (Binary glTF) file.
|
||||
|
||||
GLB structure: 12-byte header + chunks. Chunk 0 is JSON.
|
||||
Returns parsed dict or None on failure.
|
||||
"""
|
||||
try:
|
||||
with open(glb_path, "rb") as f:
|
||||
header = f.read(12)
|
||||
if len(header) < 12:
|
||||
return None
|
||||
magic, version, length = struct.unpack("<III", header)
|
||||
if magic != 0x46546C67: # 'glTF'
|
||||
return None
|
||||
chunk_header = f.read(8)
|
||||
if len(chunk_header) < 8:
|
||||
return None
|
||||
chunk_length, chunk_type = struct.unpack("<II", chunk_header)
|
||||
if chunk_type != 0x4E4F534A: # 'JSON'
|
||||
return None
|
||||
json_bytes = f.read(chunk_length)
|
||||
return json.loads(json_bytes)
|
||||
except Exception as e:
|
||||
logger.debug("Failed to read GLB JSON from %s: %s", glb_path, e)
|
||||
return None
|
||||
|
||||
|
||||
def _quat_to_matrix(q: list[float]) -> list[list[float]]:
|
||||
"""Convert quaternion [x, y, z, w] to 3×3 rotation matrix."""
|
||||
x, y, z, w = q
|
||||
return [
|
||||
[1 - 2*(y*y + z*z), 2*(x*y - z*w), 2*(x*z + y*w)],
|
||||
[ 2*(x*y + z*w), 1 - 2*(x*x + z*z), 2*(y*z - x*w)],
|
||||
[ 2*(x*z - y*w), 2*(y*z + x*w), 1 - 2*(x*x + y*y)],
|
||||
]
|
||||
|
||||
|
||||
def _get_glb_root_rotation(device_dir: Path) -> list[list[float]] | None:
|
||||
"""Extract root node rotation matrix from the first GLB in device_dir/meshes/.
|
||||
|
||||
Only rotation is extracted — GLB scale is NOT applied because STL files
|
||||
are already in meters while GLB scale converts GLB mesh units (often mm)
|
||||
to scene units. Since we read STL directly, scale is irrelevant.
|
||||
|
||||
Returns 3×3 rotation matrix or None if no GLB or no rotation found.
|
||||
"""
|
||||
meshes_dir = device_dir / "meshes"
|
||||
if not meshes_dir.exists():
|
||||
return None
|
||||
glbs = sorted(meshes_dir.glob("*.glb"))
|
||||
if not glbs:
|
||||
return None
|
||||
|
||||
gltf = _read_glb_json(glbs[0])
|
||||
if gltf is None:
|
||||
return None
|
||||
|
||||
nodes = gltf.get("nodes", [])
|
||||
if not nodes:
|
||||
return None
|
||||
|
||||
root = nodes[0]
|
||||
rotation = root.get("rotation")
|
||||
if rotation is None:
|
||||
return None
|
||||
|
||||
# Skip identity quaternion [0,0,0,1]
|
||||
x, y, z, w = rotation
|
||||
if abs(x) < 1e-9 and abs(y) < 1e-9 and abs(z) < 1e-9 and abs(w - 1.0) < 1e-9:
|
||||
return None
|
||||
|
||||
return _quat_to_matrix(rotation)
|
||||
|
||||
|
||||
def _apply_rotation_to_bbox(
|
||||
stl_min: list[float], stl_max: list[float],
|
||||
rot: list[list[float]],
|
||||
) -> tuple[list[float], list[float]]:
|
||||
"""Apply rotation to an axis-aligned bounding box.
|
||||
|
||||
Transforms all 8 corners of the STL AABB through rotation,
|
||||
then computes the new AABB in glTF space.
|
||||
"""
|
||||
corners = []
|
||||
for x in (stl_min[0], stl_max[0]):
|
||||
for y in (stl_min[1], stl_max[1]):
|
||||
for z in (stl_min[2], stl_max[2]):
|
||||
tx = rot[0][0]*x + rot[0][1]*y + rot[0][2]*z
|
||||
ty = rot[1][0]*x + rot[1][1]*y + rot[1][2]*z
|
||||
tz = rot[2][0]*x + rot[2][1]*y + rot[2][2]*z
|
||||
corners.append((tx, ty, tz))
|
||||
|
||||
xs = [c[0] for c in corners]
|
||||
ys = [c[1] for c in corners]
|
||||
zs = [c[2] for c in corners]
|
||||
return [min(xs), min(ys), min(zs)], [max(xs), max(ys), max(zs)]
|
||||
|
||||
|
||||
def extract_one_device(device_dir: Path) -> dict | None:
|
||||
"""提取单个设备的足迹信息。"""
|
||||
try:
|
||||
import trimesh
|
||||
except ImportError:
|
||||
logger.error("trimesh not installed. Run: pip install trimesh")
|
||||
return None
|
||||
|
||||
mesh_files = _find_mesh_files(device_dir)
|
||||
if not mesh_files:
|
||||
return None
|
||||
|
||||
# 加载所有网格部件并计算联合包围盒
|
||||
meshes = []
|
||||
for f in mesh_files:
|
||||
try:
|
||||
m = trimesh.load(str(f), force="mesh")
|
||||
if hasattr(m, "bounds") and m.bounds is not None:
|
||||
meshes.append(m)
|
||||
except Exception as e:
|
||||
logger.warning("Failed to load %s: %s", f, e)
|
||||
|
||||
if not meshes:
|
||||
return None
|
||||
|
||||
if len(meshes) == 1:
|
||||
combined = meshes[0]
|
||||
else:
|
||||
combined = trimesh.util.concatenate(meshes)
|
||||
|
||||
bounds = combined.bounds
|
||||
stl_min = [float(bounds[0][i]) for i in range(3)]
|
||||
stl_max = [float(bounds[1][i]) for i in range(3)]
|
||||
|
||||
# 应用 GLB 根节点旋转到 STL 包围盒（scale 不应用 — STL 已是米制）
|
||||
# glTF 约定: X=right, Y=up, Z=forward → 2D 足迹取 X 和 Z, 高度取 Y
|
||||
rot = _get_glb_root_rotation(device_dir)
|
||||
if rot is not None:
|
||||
t_min, t_max = _apply_rotation_to_bbox(stl_min, stl_max, rot)
|
||||
t_size = [t_max[i] - t_min[i] for i in range(3)]
|
||||
t_center = [(t_min[i] + t_max[i]) / 2 for i in range(3)]
|
||||
# glTF Y-up: X=width, Z=depth, Y=height
|
||||
bbox_w = round(t_size[0], 4)
|
||||
bbox_d = round(t_size[2], 4)
|
||||
height = round(t_size[1], 4)
|
||||
origin_offset = [round(t_center[0], 4), round(t_center[2], 4)]
|
||||
logger.debug(
|
||||
"%s: GLB rotation applied → bbox=[%.3f, %.3f] height=%.3f",
|
||||
device_dir.name, bbox_w, bbox_d, height,
|
||||
)
|
||||
else:
|
||||
# 无 GLB 或 identity rotation → 沿用原始 STL 坐标 (X=width, Y=depth, Z=height)
|
||||
size = [stl_max[i] - stl_min[i] for i in range(3)]
|
||||
center = [(stl_min[i] + stl_max[i]) / 2 for i in range(3)]
|
||||
bbox_w = round(size[0], 4)
|
||||
bbox_d = round(size[1], 4)
|
||||
height = round(size[2], 4)
|
||||
origin_offset = [round(center[0], 4), round(center[1], 4)]
|
||||
|
||||
model_file, model_type = _find_best_model_file(device_dir)
|
||||
thumbnail_file = _find_thumbnail(device_dir)
|
||||
|
||||
device_id = device_dir.name
|
||||
|
||||
# 确定 openings：手动标注优先，否则尝试从 XACRO 自动提取
|
||||
# 注意：XACRO socket 坐标是 STL 原生坐标系，这里传入变换后的 bbox
|
||||
if device_id in MANUAL_OPENINGS:
|
||||
openings = MANUAL_OPENINGS[device_id]
|
||||
else:
|
||||
xacro_path = device_dir / "modal.xacro"
|
||||
if xacro_path.exists():
|
||||
openings = extract_openings_from_xacro(
|
||||
xacro_path,
|
||||
bbox_center_xy=(origin_offset[0], origin_offset[1]),
|
||||
bbox_size_xy=(bbox_w, bbox_d),
|
||||
)
|
||||
else:
|
||||
openings = []
|
||||
|
||||
result: dict = {
|
||||
"bbox": [bbox_w, bbox_d],
|
||||
"height": height,
|
||||
"origin_offset": origin_offset,
|
||||
"model_file": model_file,
|
||||
"model_type": model_type,
|
||||
"thumbnail_file": thumbnail_file,
|
||||
"openings": openings,
|
||||
}
|
||||
return result
|
||||
|
||||
|
||||
def extract_all(
|
||||
assets_dir: Path | None = None,
|
||||
registry_dir: Path | None = None,
|
||||
device_ids: list[str] | None = None,
|
||||
) -> dict[str, dict]:
|
||||
"""提取所有（或指定）设备的足迹。
|
||||
|
||||
Args:
|
||||
assets_dir: uni-lab-assets/device_models/ 路径
|
||||
registry_dir: Uni-Lab-OS/unilabos/device_mesh/devices/ 路径
|
||||
device_ids: 仅提取指定设备（None = 全部扫描）
|
||||
|
||||
Returns:
|
||||
{device_id: footprint_dict}
|
||||
"""
|
||||
results: dict[str, dict] = {}
|
||||
|
||||
dirs_to_scan: list[tuple[Path, str]] = []
|
||||
|
||||
if assets_dir and assets_dir.exists():
|
||||
for d in sorted(assets_dir.iterdir()):
|
||||
if d.is_dir() and (device_ids is None or d.name in device_ids):
|
||||
dirs_to_scan.append((d, "assets"))
|
||||
|
||||
if registry_dir and registry_dir.exists():
|
||||
for d in sorted(registry_dir.iterdir()):
|
||||
if d.is_dir() and (device_ids is None or d.name in device_ids):
|
||||
if d.name not in results: # assets 已有的不重复扫描
|
||||
dirs_to_scan.append((d, "registry"))
|
||||
|
||||
for device_dir, source in dirs_to_scan:
|
||||
device_id = device_dir.name
|
||||
if device_id in results:
|
||||
continue
|
||||
|
||||
footprint = extract_one_device(device_dir)
|
||||
if footprint:
|
||||
footprint["source"] = source
|
||||
results[device_id] = footprint
|
||||
logger.info(
|
||||
"Extracted %s: bbox=%s height=%.3f source=%s",
|
||||
device_id,
|
||||
footprint["bbox"],
|
||||
footprint["height"],
|
||||
source,
|
||||
)
|
||||
|
||||
# 统计自动提取的 openings 数量
|
||||
auto_xacro_count = sum(
|
||||
1
|
||||
for fp in results.values()
|
||||
if any(o.get("label") == "auto_xacro" for o in fp.get("openings", []))
|
||||
)
|
||||
logger.info(
|
||||
"Auto-extracted openings from XACRO for %d / %d devices",
|
||||
auto_xacro_count,
|
||||
len(results),
|
||||
)
|
||||
|
||||
# 手动后备
|
||||
for dev_id, (w, d, h) in FALLBACK_SIZES.items():
|
||||
if dev_id not in results:
|
||||
results[dev_id] = {
|
||||
"bbox": [w, d],
|
||||
"height": h,
|
||||
"origin_offset": [0.0, 0.0],
|
||||
"model_file": "",
|
||||
"model_type": "",
|
||||
"thumbnail_file": "",
|
||||
"openings": MANUAL_OPENINGS.get(dev_id, []),
|
||||
"source": "manual",
|
||||
}
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def main() -> None:
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Extract device footprints from STL/GLB meshes"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--assets-dir",
|
||||
type=Path,
|
||||
default=Path(__file__).resolve().parent.parent / "uni-lab-assets" / "device_models",
|
||||
help="Path to uni-lab-assets/device_models/",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--registry-dir",
|
||||
type=Path,
|
||||
default=Path(__file__).resolve().parent / "Uni-Lab-OS" / "unilabos" / "device_mesh" / "devices",
|
||||
help="Path to Uni-Lab-OS device_mesh/devices/",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--output",
|
||||
type=Path,
|
||||
default=Path(__file__).resolve().parent / "footprints.json",
|
||||
help="Output JSON path",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--devices",
|
||||
nargs="*",
|
||||
default=None,
|
||||
help="Only extract these device IDs (default: all)",
|
||||
)
|
||||
parser.add_argument("-v", "--verbose", action="store_true")
|
||||
args = parser.parse_args()
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.DEBUG if args.verbose else logging.INFO,
|
||||
format="%(levelname)s: %(message)s",
|
||||
)
|
||||
|
||||
logger.info("Assets dir: %s (exists=%s)", args.assets_dir, args.assets_dir.exists())
|
||||
logger.info("Registry dir: %s (exists=%s)", args.registry_dir, args.registry_dir.exists())
|
||||
|
||||
results = extract_all(
|
||||
assets_dir=args.assets_dir,
|
||||
registry_dir=args.registry_dir,
|
||||
device_ids=args.devices,
|
||||
)
|
||||
|
||||
with open(args.output, "w") as f:
|
||||
json.dump(results, f, indent=2, ensure_ascii=False)
|
||||
|
||||
logger.info("Wrote %d devices to %s", len(results), args.output)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,187 +0,0 @@
|
||||
"""
|
||||
Generate a YAML registry file for all devices in uni-lab-assets that don't
|
||||
already have a registry entry (identified by model.mesh value).
|
||||
|
||||
Output: Uni-Lab-OS/unilabos/registry/devices/asset_models.yaml
|
||||
"""
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
import yaml
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Paths (resolved relative to this script's location)
|
||||
# ---------------------------------------------------------------------------
|
||||
REPO_ROOT = Path(__file__).parent.parent
|
||||
|
||||
ASSETS_DIR = REPO_ROOT.parent / "uni-lab-assets" / "device_models"
|
||||
REGISTRY_DIR = REPO_ROOT / "Uni-Lab-OS" / "unilabos" / "registry" / "devices"
|
||||
OUTPUT_FILE = REGISTRY_DIR / "asset_models.yaml"
|
||||
|
||||
OSS_BASE = (
|
||||
"https://uni-lab.oss-cn-zhangjiakou.aliyuncs.com/uni-lab/devices"
|
||||
)
|
||||
CONTAINER_CLASS = (
|
||||
"unilabos.devices.resource_container.container:HotelContainer"
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Step 1 — collect mesh names already present in the registry
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def collect_registered_meshes() -> set[str]:
|
||||
"""Return the set of mesh values found in all existing registry YAML files."""
|
||||
registered: set[str] = set()
|
||||
for yaml_file in REGISTRY_DIR.glob("*.yaml"):
|
||||
# Skip the output file itself so the script is idempotent
|
||||
if yaml_file == OUTPUT_FILE:
|
||||
continue
|
||||
try:
|
||||
with yaml_file.open("r", encoding="utf-8") as fh:
|
||||
data = yaml.safe_load(fh)
|
||||
except Exception as exc:
|
||||
print(f" [warn] Could not parse {yaml_file.name}: {exc}")
|
||||
continue
|
||||
if not isinstance(data, dict):
|
||||
continue
|
||||
for _key, entry in data.items():
|
||||
if not isinstance(entry, dict):
|
||||
continue
|
||||
model = entry.get("model")
|
||||
if isinstance(model, dict):
|
||||
mesh = model.get("mesh")
|
||||
if mesh:
|
||||
registered.add(str(mesh))
|
||||
return registered
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Step 2 — scan uni-lab-assets/device_models/
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def scan_asset_devices() -> list[dict]:
|
||||
"""
|
||||
Return a list of device dicts for every subfolder that has a modal.xacro.
|
||||
Each dict has keys: folder_name, description.
|
||||
"""
|
||||
devices = []
|
||||
if not ASSETS_DIR.is_dir():
|
||||
raise FileNotFoundError(f"Assets directory not found: {ASSETS_DIR}")
|
||||
|
||||
for device_dir in sorted(ASSETS_DIR.iterdir()):
|
||||
if not device_dir.is_dir():
|
||||
continue
|
||||
|
||||
folder_name = device_dir.name
|
||||
|
||||
# modal.xacro is required
|
||||
if not (device_dir / "modal.xacro").exists():
|
||||
continue
|
||||
|
||||
# Read optional meta.json
|
||||
description = folder_name
|
||||
meta_path = device_dir / "meta.json"
|
||||
if meta_path.exists():
|
||||
try:
|
||||
with meta_path.open("r", encoding="utf-8") as fh:
|
||||
meta = json.load(fh)
|
||||
# Use name field if present; otherwise fall back to folder name
|
||||
description = meta.get("name", folder_name)
|
||||
except Exception as exc:
|
||||
print(f" [warn] Could not parse {meta_path}: {exc}")
|
||||
|
||||
devices.append(
|
||||
{
|
||||
"folder_name": folder_name,
|
||||
"description": description,
|
||||
}
|
||||
)
|
||||
|
||||
return devices
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Step 3 — build registry entry for a single device
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def build_entry(folder_name: str, description: str) -> dict:
|
||||
return {
|
||||
"category": ["asset_model"],
|
||||
"class": {
|
||||
"action_value_mappings": {},
|
||||
"module": CONTAINER_CLASS,
|
||||
"status_types": {},
|
||||
"type": "python",
|
||||
},
|
||||
"config_info": [],
|
||||
"description": description,
|
||||
"handles": [],
|
||||
"icon": "",
|
||||
"init_param_schema": {
|
||||
"config": {
|
||||
"properties": {},
|
||||
"required": [],
|
||||
"type": "object",
|
||||
},
|
||||
"data": {
|
||||
"properties": {},
|
||||
"required": [],
|
||||
"type": "object",
|
||||
},
|
||||
},
|
||||
"model": {
|
||||
"mesh": folder_name,
|
||||
"path": f"{OSS_BASE}/{folder_name}/macro_device.xacro",
|
||||
"type": "device",
|
||||
},
|
||||
"version": "1.0.0",
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Main
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> None:
|
||||
print("Scanning existing registry for registered meshes...")
|
||||
registered_meshes = collect_registered_meshes()
|
||||
print(f" Found {len(registered_meshes)} already-registered mesh(es).")
|
||||
|
||||
print(f"\nScanning asset devices in: {ASSETS_DIR}")
|
||||
all_devices = scan_asset_devices()
|
||||
print(f" Found {len(all_devices)} device folder(s) with modal.xacro.")
|
||||
|
||||
registry: dict[str, dict] = {}
|
||||
skipped = 0
|
||||
generated = 0
|
||||
|
||||
for device in all_devices:
|
||||
folder_name = device["folder_name"]
|
||||
if folder_name in registered_meshes:
|
||||
skipped += 1
|
||||
continue
|
||||
key = f"asset_model.{folder_name}"
|
||||
registry[key] = build_entry(folder_name, device["description"])
|
||||
generated += 1
|
||||
|
||||
print(f"\nWriting {generated} new entr(ies) to: {OUTPUT_FILE}")
|
||||
OUTPUT_FILE.parent.mkdir(parents=True, exist_ok=True)
|
||||
with OUTPUT_FILE.open("w", encoding="utf-8") as fh:
|
||||
yaml.dump(
|
||||
registry,
|
||||
fh,
|
||||
default_flow_style=False,
|
||||
allow_unicode=True,
|
||||
sort_keys=False,
|
||||
)
|
||||
|
||||
print("\n--- Summary ---")
|
||||
print(f" Total devices found (with modal.xacro): {len(all_devices)}")
|
||||
print(f" Already registered (skipped): {skipped}")
|
||||
print(f" Newly generated: {generated}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -1,373 +0,0 @@
|
||||
"""意图解释器：将语义化意图翻译为 Constraint 列表。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import itertools
|
||||
from collections.abc import Callable
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
from .constraints import PRIORITY_MULTIPLIERS
|
||||
from .models import Constraint, Intent
|
||||
|
||||
# 优先级权重映射
|
||||
_PRIORITY_WEIGHTS: dict[str, float] = {"low": 1.0, "medium": 3.0, "high": 8.0}
|
||||
_DEFAULT_WEIGHT = _PRIORITY_WEIGHTS["medium"]
|
||||
|
||||
|
||||
def _priority_key(priority: str) -> str:
|
||||
"""将 intent priority 映射到 constraint 权重等级。"""
|
||||
return "normal" if priority == "medium" else priority
|
||||
|
||||
|
||||
def _final_weight(base_weight: float, priority: str) -> float:
|
||||
"""在解释阶段直接烘焙优先级乘数。"""
|
||||
return base_weight * PRIORITY_MULTIPLIERS.get(priority, 1.0)
|
||||
|
||||
|
||||
@dataclass
|
||||
class InterpretResult:
|
||||
"""意图解释结果。"""
|
||||
|
||||
constraints: list[Constraint] = field(default_factory=list)
|
||||
translations: list[dict] = field(default_factory=list)
|
||||
errors: list[str] = field(default_factory=list)
|
||||
workflow_edges: list[list[str]] = field(default_factory=list)
|
||||
|
||||
|
||||
def _handle_reachable_by(intent: Intent, result: InterpretResult) -> None:
|
||||
"""reachable_by：机械臂必须能到达指定设备列表。"""
|
||||
arm = intent.params.get("arm")
|
||||
targets = intent.params.get("targets", [])
|
||||
|
||||
if arm is None:
|
||||
result.errors.append(f"reachable_by: 缺少必要参数 'arm'")
|
||||
return
|
||||
if not targets:
|
||||
result.errors.append(f"reachable_by: 参数 'targets' 不能为空")
|
||||
return
|
||||
|
||||
generated: list[dict] = []
|
||||
for target in targets:
|
||||
c = Constraint(
|
||||
type="hard",
|
||||
rule_name="reachability",
|
||||
params={"arm_id": arm, "target_device_id": target},
|
||||
weight=_final_weight(1.0, "critical"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": generated,
|
||||
"explanation": f"机械臂 '{arm}' 需要能够到达 {len(targets)} 个目标设备",
|
||||
})
|
||||
|
||||
|
||||
def _handle_close_together(intent: Intent, result: InterpretResult) -> None:
|
||||
"""close_together：设备组内两两最小化距离。"""
|
||||
devices: list[str] = intent.params.get("devices", [])
|
||||
priority: str = intent.params.get("priority", "medium")
|
||||
|
||||
if len(devices) < 2:
|
||||
result.errors.append(f"close_together: 参数 'devices' 至少需要 2 个设备，当前 {len(devices)} 个")
|
||||
return
|
||||
|
||||
weight = _final_weight(
|
||||
_PRIORITY_WEIGHTS.get(priority, _DEFAULT_WEIGHT),
|
||||
_priority_key(priority),
|
||||
)
|
||||
generated: list[dict] = []
|
||||
for dev_a, dev_b in itertools.combinations(devices, 2):
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="minimize_distance",
|
||||
params={"device_a": dev_a, "device_b": dev_b},
|
||||
weight=weight,
|
||||
)
|
||||
result.constraints.append(c)
|
||||
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": generated,
|
||||
"explanation": f"设备组 {devices} 应尽量靠近（优先级: {priority}）",
|
||||
})
|
||||
|
||||
|
||||
def _handle_far_apart(intent: Intent, result: InterpretResult) -> None:
|
||||
"""far_apart：设备组内两两最大化距离。"""
|
||||
devices: list[str] = intent.params.get("devices", [])
|
||||
priority: str = intent.params.get("priority", "medium")
|
||||
|
||||
if len(devices) < 2:
|
||||
result.errors.append(f"far_apart: 参数 'devices' 至少需要 2 个设备，当前 {len(devices)} 个")
|
||||
return
|
||||
|
||||
weight = _final_weight(
|
||||
_PRIORITY_WEIGHTS.get(priority, _DEFAULT_WEIGHT),
|
||||
_priority_key(priority),
|
||||
)
|
||||
generated: list[dict] = []
|
||||
for dev_a, dev_b in itertools.combinations(devices, 2):
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="maximize_distance",
|
||||
params={"device_a": dev_a, "device_b": dev_b},
|
||||
weight=weight,
|
||||
)
|
||||
result.constraints.append(c)
|
||||
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": generated,
|
||||
"explanation": f"设备组 {devices} 应尽量分散（优先级: {priority}）",
|
||||
})
|
||||
|
||||
|
||||
def _handle_max_distance(intent: Intent, result: InterpretResult) -> None:
|
||||
"""max_distance：两设备间距不超过指定值。"""
|
||||
device_a = intent.params.get("device_a")
|
||||
device_b = intent.params.get("device_b")
|
||||
distance = intent.params.get("distance")
|
||||
|
||||
if device_a is None or device_b is None or distance is None:
|
||||
result.errors.append(
|
||||
f"max_distance: 缺少必要参数，需要 'device_a'、'device_b' 和 'distance'，"
|
||||
f"当前: device_a={device_a}, device_b={device_b}, distance={distance}"
|
||||
)
|
||||
return
|
||||
|
||||
c = Constraint(
|
||||
type="hard",
|
||||
rule_name="distance_less_than",
|
||||
params={"device_a": device_a, "device_b": device_b, "distance": distance},
|
||||
weight=_final_weight(1.0, "normal"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
|
||||
"explanation": f"设备 '{device_a}' 与 '{device_b}' 之间的距离不得超过 {distance} 米",
|
||||
})
|
||||
|
||||
|
||||
def _handle_min_distance(intent: Intent, result: InterpretResult) -> None:
|
||||
"""min_distance：两设备间距不小于指定值。"""
|
||||
device_a = intent.params.get("device_a")
|
||||
device_b = intent.params.get("device_b")
|
||||
distance = intent.params.get("distance")
|
||||
|
||||
if device_a is None or device_b is None or distance is None:
|
||||
result.errors.append(
|
||||
f"min_distance: 缺少必要参数，需要 'device_a'、'device_b' 和 'distance'，"
|
||||
f"当前: device_a={device_a}, device_b={device_b}, distance={distance}"
|
||||
)
|
||||
return
|
||||
|
||||
c = Constraint(
|
||||
type="hard",
|
||||
rule_name="distance_greater_than",
|
||||
params={"device_a": device_a, "device_b": device_b, "distance": distance},
|
||||
weight=_final_weight(1.0, "normal"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
|
||||
"explanation": f"设备 '{device_a}' 与 '{device_b}' 之间的距离不得小于 {distance} 米",
|
||||
})
|
||||
|
||||
|
||||
def _handle_min_spacing(intent: Intent, result: InterpretResult) -> None:
|
||||
"""min_spacing：所有设备之间的最小间隙。"""
|
||||
min_gap: float = intent.params.get("min_gap", 0.3)
|
||||
|
||||
c = Constraint(
|
||||
type="hard",
|
||||
rule_name="min_spacing",
|
||||
params={"min_gap": min_gap},
|
||||
weight=_final_weight(1.0, "high"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
|
||||
"explanation": f"所有设备之间至少保持 {min_gap} 米的间隙",
|
||||
})
|
||||
|
||||
|
||||
def _handle_face_outward(intent: Intent, result: InterpretResult) -> None:
|
||||
"""face_outward：设备朝向偏好为向外。"""
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="prefer_orientation_mode",
|
||||
params={"mode": "outward"},
|
||||
weight=_final_weight(1.0, "low"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
|
||||
"explanation": "设备开口偏好朝向实验室外侧",
|
||||
})
|
||||
|
||||
|
||||
def _handle_face_inward(intent: Intent, result: InterpretResult) -> None:
|
||||
"""face_inward：设备朝向偏好为向内。"""
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="prefer_orientation_mode",
|
||||
params={"mode": "inward"},
|
||||
weight=_final_weight(1.0, "low"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
|
||||
"explanation": "设备开口偏好朝向实验室内侧",
|
||||
})
|
||||
|
||||
|
||||
def _handle_align_cardinal(intent: Intent, result: InterpretResult) -> None:
|
||||
"""align_cardinal：设备偏好对齐到主轴方向。"""
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="prefer_aligned",
|
||||
params={},
|
||||
weight=_final_weight(1.0, "low"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
|
||||
"explanation": "设备偏好与实验室主轴对齐（0°/90°/180°/270°）",
|
||||
})
|
||||
|
||||
|
||||
def _handle_keep_adjacent(intent: Intent, result: InterpretResult) -> None:
|
||||
"""keep_adjacent：两个设备保持相邻（同 close_together 逻辑，支持 priority 映射）。"""
|
||||
devices: list[str] = intent.params.get("devices", [])
|
||||
priority: str = intent.params.get("priority", "medium")
|
||||
|
||||
if len(devices) < 2:
|
||||
result.errors.append(f"keep_adjacent: 参数 'devices' 至少需要 2 个设备，当前 {len(devices)} 个")
|
||||
return
|
||||
|
||||
weight = _final_weight(
|
||||
_PRIORITY_WEIGHTS.get(priority, _DEFAULT_WEIGHT),
|
||||
_priority_key(priority),
|
||||
)
|
||||
generated: list[dict] = []
|
||||
for dev_a, dev_b in itertools.combinations(devices, 2):
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="minimize_distance",
|
||||
params={"device_a": dev_a, "device_b": dev_b},
|
||||
weight=weight,
|
||||
)
|
||||
result.constraints.append(c)
|
||||
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": generated,
|
||||
"explanation": f"设备组 {devices} 应保持相邻（优先级: {priority}）",
|
||||
})
|
||||
|
||||
|
||||
def _handle_workflow_hint(intent: Intent, result: InterpretResult) -> None:
|
||||
"""workflow_hint：工作流顺序暗示，相邻步骤设备靠近。"""
|
||||
workflow: str = intent.params.get("workflow", "")
|
||||
devices: list[str] = intent.params.get("devices", [])
|
||||
|
||||
if len(devices) < 2:
|
||||
result.errors.append(
|
||||
f"workflow_hint: 参数 'devices' 至少需要 2 个设备，当前 {len(devices)} 个"
|
||||
)
|
||||
return
|
||||
|
||||
generated: list[dict] = []
|
||||
for dev_a, dev_b in zip(devices[:-1], devices[1:]):
|
||||
c = Constraint(
|
||||
type="soft",
|
||||
rule_name="minimize_distance",
|
||||
params={"device_a": dev_a, "device_b": dev_b},
|
||||
weight=_final_weight(1.0, "normal"),
|
||||
)
|
||||
result.constraints.append(c)
|
||||
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
|
||||
result.workflow_edges.append([dev_a, dev_b])
|
||||
|
||||
result.translations.append({
|
||||
"source_intent": intent.intent,
|
||||
"source_description": intent.description,
|
||||
"source_params": intent.params,
|
||||
"generated_constraints": generated,
|
||||
"explanation": f"工作流 '{workflow}' 中相邻步骤设备应靠近",
|
||||
"confidence": "low",
|
||||
})
|
||||
|
||||
|
||||
# 意图处理器分发表
|
||||
_HANDLERS: dict[str, Callable[[Intent, InterpretResult], None]] = {
|
||||
"reachable_by": _handle_reachable_by,
|
||||
"close_together": _handle_close_together,
|
||||
"far_apart": _handle_far_apart,
|
||||
"max_distance": _handle_max_distance,
|
||||
"min_distance": _handle_min_distance,
|
||||
"min_spacing": _handle_min_spacing,
|
||||
"face_outward": _handle_face_outward,
|
||||
"face_inward": _handle_face_inward,
|
||||
"align_cardinal": _handle_align_cardinal,
|
||||
"keep_adjacent": _handle_keep_adjacent,
|
||||
"workflow_hint": _handle_workflow_hint,
|
||||
}
|
||||
|
||||
|
||||
def interpret_intents(intents: list[Intent]) -> InterpretResult:
|
||||
"""将意图列表翻译为约束列表。
|
||||
|
||||
Args:
|
||||
intents: 语义化意图列表（通常由 LLM 生成）
|
||||
|
||||
Returns:
|
||||
InterpretResult，包含约束、翻译记录、错误信息和工作流边
|
||||
"""
|
||||
result = InterpretResult()
|
||||
|
||||
for intent in intents:
|
||||
handler = _HANDLERS.get(intent.intent)
|
||||
if handler is None:
|
||||
result.errors.append(f"未知意图类型: '{intent.intent}'，跳过处理")
|
||||
continue
|
||||
handler(intent, result)
|
||||
|
||||
return result
|
||||
@@ -1,41 +0,0 @@
|
||||
"""Protocol 接口定义，隔离 ROS 依赖。
|
||||
|
||||
开发阶段使用 mock_checkers.py 中的 Mock 实现，
|
||||
集成阶段替换为 ros_checkers.py 中的 MoveIt2 / IKFast 实现。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Protocol
|
||||
|
||||
|
||||
class CollisionChecker(Protocol):
|
||||
"""碰撞检测接口。"""
|
||||
|
||||
def check(self, placements: list[dict]) -> list[tuple[str, str]]:
|
||||
"""返回碰撞设备对列表。
|
||||
|
||||
Args:
|
||||
placements: [{"id": str, "bbox": (w, d), "pos": (x, y, θ)}, ...]
|
||||
|
||||
Returns:
|
||||
[("device_a", "device_b"), ...] 存在碰撞的设备对
|
||||
"""
|
||||
...
|
||||
|
||||
|
||||
class ReachabilityChecker(Protocol):
|
||||
"""可达性检测接口。"""
|
||||
|
||||
def is_reachable(self, arm_id: str, arm_pose: dict, target: dict) -> bool:
|
||||
"""判断机械臂在给定位姿下能否到达目标点。
|
||||
|
||||
Args:
|
||||
arm_id: 机械臂设备 ID
|
||||
arm_pose: {"x": float, "y": float, "theta": float}
|
||||
target: {"x": float, "y": float, "z": float}
|
||||
|
||||
Returns:
|
||||
True 如果可达
|
||||
"""
|
||||
...
|
||||
@@ -1,49 +0,0 @@
|
||||
"""解析实验室平面图 JSON。
|
||||
|
||||
简单格式：
|
||||
{
|
||||
"width": 6.0,
|
||||
"depth": 4.0,
|
||||
"obstacles": [
|
||||
{"x": 2.0, "y": 0.0, "width": 0.1, "depth": 1.0}
|
||||
]
|
||||
}
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
from .models import Lab, Obstacle
|
||||
|
||||
|
||||
def parse_lab(data: dict) -> Lab:
|
||||
"""从字典解析实验室平面图。"""
|
||||
obstacles = []
|
||||
for obs in data.get("obstacles", []):
|
||||
obstacles.append(
|
||||
Obstacle(
|
||||
x=float(obs["x"]),
|
||||
y=float(obs["y"]),
|
||||
width=float(obs["width"]),
|
||||
depth=float(obs["depth"]),
|
||||
)
|
||||
)
|
||||
return Lab(
|
||||
width=float(data["width"]),
|
||||
depth=float(data["depth"]),
|
||||
obstacles=obstacles,
|
||||
)
|
||||
|
||||
|
||||
def load_lab_from_file(path: str | Path) -> Lab:
|
||||
"""从 JSON 文件加载实验室平面图。"""
|
||||
with open(path) as f:
|
||||
data = json.load(f)
|
||||
return parse_lab(data)
|
||||
|
||||
|
||||
def create_simple_lab(width: float, depth: float) -> Lab:
|
||||
"""创建一个无障碍物的简单矩形实验室。"""
|
||||
return Lab(width=width, depth=depth)
|
||||
@@ -1,187 +0,0 @@
|
||||
# Demo Agent — Lab Layout Orchestrator
|
||||
|
||||
You are a lab layout agent for a recorded demo. Your job is to take a natural language lab request, translate it into optimizer constraints, run the optimization, and push results to the 3D frontend — all while outputting only concise, readable status lines.
|
||||
|
||||
## CRITICAL OUTPUT RULES
|
||||
|
||||
- Output ONLY short status lines. No markdown fences. No raw JSON. No explanations.
|
||||
- Every HTTP call uses `curl -s` (silent). Never show curl output to the user.
|
||||
- Parse responses internally. Extract only the fields needed for your status lines.
|
||||
- Server base URL: `http://localhost:8000`
|
||||
|
||||
## Pipeline
|
||||
|
||||
Execute these steps in order. Print the status line shown after each step.
|
||||
|
||||
### Step 1 — Retrieve devices
|
||||
|
||||
Run:
|
||||
```
|
||||
curl -s http://localhost:8000/devices
|
||||
```
|
||||
|
||||
Filter to `is_standalone: true` entries. Count them. Build an id→name lookup.
|
||||
|
||||
Print:
|
||||
```
|
||||
retrieving devices... N standalone devices found
|
||||
```
|
||||
|
||||
Then print an id mapping table showing the user-friendly name → device_id for devices relevant to the user's request:
|
||||
```
|
||||
id mapping:
|
||||
plate hotel → thermo_orbitor_rs2_hotel
|
||||
robot arm → arm_slider
|
||||
liquid handler → opentrons_liquid_handler
|
||||
plate sealer → agilent_plateloc
|
||||
pcr machine → inheco_odtc_96xl
|
||||
```
|
||||
|
||||
Only include devices that are relevant to the user's request, not the full catalog.
|
||||
|
||||
### Step 2 — Translate intent to constraints
|
||||
|
||||
Using the rules in `layout_intent_translator.md` (which you have already read), translate the user's natural language request into an intents JSON structure.
|
||||
|
||||
Do NOT print the JSON. Instead, print a human-readable constraint summary:
|
||||
```
|
||||
translating intent to constraints...
|
||||
constraints:
|
||||
hard: arm_slider must reach 4 devices
|
||||
hard: min spacing 0.05m between all devices
|
||||
soft: workflow order hotel → liquid handler → sealer → pcr
|
||||
soft: all devices close together (high priority)
|
||||
soft: align to cardinal directions
|
||||
```
|
||||
|
||||
### Step 3 — Interpret intents
|
||||
|
||||
Send the intents JSON to the interpret endpoint:
|
||||
```
|
||||
curl -s -X POST http://localhost:8000/interpret \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{ "intents": [...] }'
|
||||
```
|
||||
|
||||
Capture the `constraints` and `workflow_edges` arrays from the response. Do NOT print anything for this step — it's a silent validation.
|
||||
|
||||
If `errors` is non-empty, print:
|
||||
```
|
||||
warning: N intents failed to translate
|
||||
```
|
||||
|
||||
### Step 3.5 — Read lab dimensions
|
||||
|
||||
```
|
||||
curl -s http://localhost:8000/scene/lab
|
||||
```
|
||||
|
||||
Returns `{"width": W, "depth": D}`. Use these values for the optimize request. Do NOT print anything for this step.
|
||||
|
||||
### Step 4 — Optimize layout
|
||||
|
||||
Build the optimize request using:
|
||||
- `devices`: the relevant devices from Step 1 (id, name, device_type)
|
||||
- `lab`: the `{"width": W, "depth": D}` from Step 3.5
|
||||
- `constraints`: from Step 3 interpret response
|
||||
- `workflow_edges`: from Step 3 interpret response
|
||||
- `seeder`: `"compact_outward"` (default)
|
||||
- `seeder_overrides`: generally not needed. Cardinal alignment is handled by the `align_cardinal` intent (generates `prefer_aligned` constraint). Do NOT use `align_weight` in seeder_overrides — it is deprecated.
|
||||
- `snap_cardinal`: `false` (default). Set `true` only if user explicitly requests snapping to 0/90/180/270.
|
||||
- `run_de`: `true`
|
||||
- `maxiter`: `200`
|
||||
- `seed`: `42`
|
||||
|
||||
Run:
|
||||
```
|
||||
curl -s -X POST http://localhost:8000/optimize \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{ ... }'
|
||||
```
|
||||
|
||||
Print:
|
||||
```
|
||||
optimizing layout (DE, 200 iterations)...
|
||||
optimization complete — cost: X.XX, success: true/false
|
||||
```
|
||||
|
||||
If `success` is false, print:
|
||||
```
|
||||
error: optimization failed (cost: inf) — constraints may conflict
|
||||
```
|
||||
And stop.
|
||||
|
||||
### Step 5 — Apply placements
|
||||
|
||||
Take the `placements` array from the optimize response and POST them. Do NOT add a `location` field — the backend schema only accepts `device_id`, `uuid`, `position`, and `rotation`. Extra fields will cause validation errors.
|
||||
|
||||
```
|
||||
curl -s -X POST http://localhost:8000/scene/placements \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{ "placements": [
|
||||
{
|
||||
"device_id": "...",
|
||||
"uuid": "...",
|
||||
"position": {"x": ..., "y": ..., "z": ...},
|
||||
"rotation": {"x": ..., "y": ..., "z": ...}
|
||||
}
|
||||
] }'
|
||||
```
|
||||
|
||||
**Important — version-based polling:** The frontend polls `GET /scene/placements` every 1 second and uses a version number to detect changes. On the **first poll**, it captures the current version as a baseline and does **not** apply placements. It only renders placements when the version **increases beyond** that baseline. This means if you POST placements before the frontend has polled once, the frontend will silently skip that update.
|
||||
|
||||
**Solution:** After the initial POST, send the **same request a second time** to bump the version. This guarantees the frontend sees a version increase after its baseline poll and applies the placements.
|
||||
|
||||
Print:
|
||||
```
|
||||
applying placements to scene...
|
||||
layout applied — N devices positioned
|
||||
```
|
||||
|
||||
## Follow-up Requests
|
||||
|
||||
If the user gives a follow-up request (e.g., "now move the sealer farther from the thermal cycler"):
|
||||
|
||||
1. Print a `---` separator
|
||||
2. Keep the same device list (no need to re-fetch)
|
||||
3. Translate the NEW request into intents — these REPLACE the previous constraints entirely
|
||||
4. Run Steps 3–5 again with the new constraints
|
||||
5. Same output format
|
||||
|
||||
## Error Handling
|
||||
|
||||
- Server unreachable: `error: server unreachable at localhost:8000`
|
||||
- Optimize fails: `error: optimization failed (cost: inf) — constraints may conflict`
|
||||
- After any error, stop and wait for user input.
|
||||
|
||||
## Device Name Resolution
|
||||
|
||||
You have `layout_intent_translator.md` loaded as context. Use its device name resolution rules to match user's informal names (e.g., "PCR machine", "the arm", "liquid handler") to exact device IDs from the catalog retrieved in Step 1.
|
||||
|
||||
## Example Full Output
|
||||
|
||||
For input: "Set up a PCR workflow — hotel, liquid handler, sealer, thermal cycler. The arm handles all transfers. Keep it compact."
|
||||
|
||||
```
|
||||
retrieving devices... 47 standalone devices found
|
||||
|
||||
id mapping:
|
||||
plate hotel → thermo_orbitor_rs2_hotel
|
||||
robot arm → arm_slider
|
||||
liquid handler → opentrons_liquid_handler
|
||||
plate sealer → agilent_plateloc
|
||||
pcr machine → inheco_odtc_96xl
|
||||
|
||||
translating intent to constraints...
|
||||
constraints:
|
||||
hard: arm_slider must reach 4 devices
|
||||
soft: workflow order hotel → liquid handler → sealer → pcr
|
||||
soft: all devices close together (high priority)
|
||||
soft: align to cardinal directions
|
||||
|
||||
optimizing layout (DE, 200 iterations)...
|
||||
optimization complete — cost: 0.00, success: true
|
||||
|
||||
applying placements to scene...
|
||||
layout applied — 5 devices positioned
|
||||
```
|
||||
@@ -1,312 +0,0 @@
|
||||
# Layout Intent Translator — LLM Skill
|
||||
|
||||
You are a lab layout intent translator. Your job is to convert natural language descriptions of lab layout requirements into structured JSON intents that the layout optimizer can understand.
|
||||
|
||||
## Your Role
|
||||
|
||||
Users describe their lab needs in natural language. You must:
|
||||
1. Identify devices by their IDs from the provided device list
|
||||
2. Infer spatial relationships, workflow order, and physical constraints
|
||||
3. Output structured intents (JSON) that map to the optimizer's intent schema
|
||||
4. Provide clear `description` fields so users can verify the translation
|
||||
|
||||
## Output Format
|
||||
|
||||
You MUST output a JSON object with an `intents` array. Each intent has:
|
||||
|
||||
```json
|
||||
{
|
||||
"intents": [
|
||||
{
|
||||
"intent": "<intent_type>",
|
||||
"params": { ... },
|
||||
"description": "Human-readable explanation of what this intent means"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## Available Intent Types
|
||||
|
||||
### `reachable_by` — Robot arm must reach devices
|
||||
```json
|
||||
{
|
||||
"intent": "reachable_by",
|
||||
"params": {
|
||||
"arm": "arm_device_id",
|
||||
"targets": ["device_a", "device_b"]
|
||||
},
|
||||
"description": "Robot arm must be able to reach device A and device B"
|
||||
}
|
||||
```
|
||||
**When to use:** Any time a robot arm transfers items between devices, all those devices must be reachable.
|
||||
|
||||
### `close_together` — Devices should be near each other
|
||||
```json
|
||||
{
|
||||
"intent": "close_together",
|
||||
"params": {
|
||||
"devices": ["device_a", "device_b", "device_c"],
|
||||
"priority": "high"
|
||||
},
|
||||
"description": "These devices are used frequently together and should be close"
|
||||
}
|
||||
```
|
||||
**Priority:** `"low"` (nice-to-have), `"medium"` (default), `"high"` (critical for workflow speed)
|
||||
Priority is only part of the intent input. The interpreter automatically bakes it into the emitted constraint `weight`; there is no separate constraint-level `priority` field in `/interpret` output or `/optimize` input.
|
||||
|
||||
### `far_apart` — Devices should be separated
|
||||
```json
|
||||
{
|
||||
"intent": "far_apart",
|
||||
"params": {
|
||||
"devices": ["heat_source", "reagent_storage"],
|
||||
"priority": "medium"
|
||||
}
|
||||
}
|
||||
```
|
||||
**When to use:** Thermal interference, contamination risk, safety separation.
|
||||
|
||||
### `keep_adjacent` — Devices should stay adjacent
|
||||
```json
|
||||
{
|
||||
"intent": "keep_adjacent",
|
||||
"params": {
|
||||
"devices": ["device_a", "device_b"],
|
||||
"priority": "high"
|
||||
}
|
||||
}
|
||||
```
|
||||
**When to use:** User explicitly asks for a pair or group to stay side-by-side / adjacent. This currently maps to the same optimizer behavior as `close_together`, but is semantically more precise.
|
||||
|
||||
### `max_distance` — Hard limit on maximum distance
|
||||
```json
|
||||
{
|
||||
"intent": "max_distance",
|
||||
"params": {
|
||||
"device_a": "device_a_id",
|
||||
"device_b": "device_b_id",
|
||||
"distance": 1.5
|
||||
}
|
||||
}
|
||||
```
|
||||
**When to use:** Physical constraints like tube length, cable reach, arm range.
|
||||
|
||||
### `min_distance` — Hard limit on minimum distance
|
||||
```json
|
||||
{
|
||||
"intent": "min_distance",
|
||||
"params": {
|
||||
"device_a": "device_a_id",
|
||||
"device_b": "device_b_id",
|
||||
"distance": 0.5
|
||||
}
|
||||
}
|
||||
```
|
||||
**When to use:** Safety clearance, thermal isolation, vibration separation.
|
||||
|
||||
### `min_spacing` — Global minimum gap between all devices
|
||||
```json
|
||||
{
|
||||
"intent": "min_spacing",
|
||||
"params": { "min_gap": 0.3 }
|
||||
}
|
||||
```
|
||||
**When to use:** General accessibility, maintenance clearance.
|
||||
|
||||
### `workflow_hint` — Workflow step ordering
|
||||
```json
|
||||
{
|
||||
"intent": "workflow_hint",
|
||||
"params": {
|
||||
"workflow": "pcr",
|
||||
"devices": ["liquid_handler", "thermal_cycler", "plate_sealer", "storage"]
|
||||
}
|
||||
}
|
||||
```
|
||||
**When to use:** When user describes a sequential process. Devices are listed in workflow order. Consecutive devices will be placed near each other.
|
||||
|
||||
### `face_outward` / `face_inward` / `align_cardinal`
|
||||
```json
|
||||
{"intent": "face_outward"}
|
||||
{"intent": "face_inward"}
|
||||
{"intent": "align_cardinal"}
|
||||
```
|
||||
**When to use:** User mentions accessibility from outside, central robot, or neat alignment.
|
||||
|
||||
## Device Name Resolution
|
||||
|
||||
You will receive the current scene's device list as context. This is the **only** source of valid device IDs. Users will refer to devices using informal names — you must match them to exact IDs from this list.
|
||||
|
||||
### Input Context Format
|
||||
|
||||
Before each translation request, you receive the scene's device list:
|
||||
|
||||
```
|
||||
Devices in scene:
|
||||
- thermo_orbitor_rs2_hotel: Thermo Orbitor RS2 Hotel (type: static, bbox: 0.68×0.52m)
|
||||
- arm_slider: Arm Slider (type: articulation, bbox: 1.20×0.30m)
|
||||
- opentrons_liquid_handler: Opentrons Liquid Handler (type: static, bbox: 0.65×0.60m)
|
||||
- agilent_plateloc: Agilent PlateLoc (type: static, bbox: 0.35×0.40m)
|
||||
- inheco_odtc_96xl: Inheco ODTC 96XL (type: static, bbox: 0.30×0.35m)
|
||||
```
|
||||
|
||||
### Matching Rules
|
||||
|
||||
1. **Exact match first**: If user says "arm_slider", match directly
|
||||
2. **Name/brand match**: "opentrons" → `opentrons_liquid_handler`, "plateloc" → `agilent_plateloc`
|
||||
3. **Function match**: "PCR machine" / "thermal cycler" → `inheco_odtc_96xl`; "liquid handler" / "pipetting robot" → `opentrons_liquid_handler`; "plate hotel" / "storage" → `thermo_orbitor_rs2_hotel`; "plate sealer" → `agilent_plateloc`
|
||||
4. **Type match**: "robot arm" / "the arm" → look for `device_type: articulation`
|
||||
5. **Ambiguous**: If multiple devices could match, list candidates in the `description` field and pick the most likely one. If truly ambiguous, return an error intent asking the user to clarify.
|
||||
|
||||
### Duplicate Device Convention
|
||||
|
||||
When the same catalog device appears multiple times in the scene:
|
||||
|
||||
- first instance keeps the bare catalog ID, e.g. `plate_reader`
|
||||
- second and later instances use `#N`, e.g. `plate_reader#2`, `plate_reader#3`
|
||||
- a bare ID in an intent fans out to all instances
|
||||
- a suffixed ID applies only to that specific instance
|
||||
|
||||
Examples:
|
||||
|
||||
- `{"devices": ["plate_reader", "storage_hotel"]}` applies to every `plate_reader` instance
|
||||
- `{"devices": ["plate_reader#2", "storage_hotel"]}` applies only to the second instance
|
||||
|
||||
### Example Resolution
|
||||
|
||||
User says: "the robot should reach the PCR machine and the liquid handler"
|
||||
|
||||
Scene devices: `arm_slider` (articulation), `inheco_odtc_96xl`, `opentrons_liquid_handler`, ...
|
||||
|
||||
Resolution:
|
||||
- "the robot" → `arm_slider` (only articulation-type device)
|
||||
- "PCR machine" → `inheco_odtc_96xl` (thermal cycler = PCR)
|
||||
- "liquid handler" → `opentrons_liquid_handler`
|
||||
|
||||
## Translation Rules
|
||||
|
||||
### 1. Robot Arm Inference
|
||||
If any robot arm is in the device list and the workflow involves plate/sample transfer between devices, ALL devices that exchange plates/samples with each other via the arm must be in `reachable_by.targets`.
|
||||
|
||||
### 2. Workflow Order
|
||||
When a user describes a process (e.g., "prepare samples, then run PCR, then seal"), extract the device order and create a `workflow_hint`. The device order follows the sample processing path.
|
||||
|
||||
### 3. Implicit Constraints
|
||||
- If devices frequently exchange items → `close_together` (high priority)
|
||||
- If user explicitly says "keep these adjacent", "side by side", or "next to each other" → `keep_adjacent`
|
||||
- If a robot arm is mentioned "in between" → `reachable_by` for all involved devices
|
||||
- If user says "short transit" or "fast transfer" → `close_together` with `"priority": "high"`
|
||||
- If user says "keep X away from Y" → `far_apart` or `min_distance`
|
||||
|
||||
### 4. Don't Over-Constrain
|
||||
- Only add constraints the user's description implies
|
||||
- When unsure about priority, use `"medium"`
|
||||
- For workflow_hint, confidence is inherently `"low"` — the optimizer notes this
|
||||
|
||||
## Example: PCR Workflow
|
||||
|
||||
**User input:**
|
||||
> "Take plate from hotel, prepare sample in opentrons, seal plate then pcr cycle, arm_slider handles all transfers"
|
||||
|
||||
**Device list provided:**
|
||||
- `thermo_orbitor_rs2_hotel` (plate hotel/storage)
|
||||
- `arm_slider` (robot arm on linear rail)
|
||||
- `opentrons_liquid_handler` (liquid handling/pipetting)
|
||||
- `agilent_plateloc` (plate sealer)
|
||||
- `inheco_odtc_96xl` (thermal cycler for PCR)
|
||||
|
||||
**Your output:**
|
||||
```json
|
||||
{
|
||||
"intents": [
|
||||
{
|
||||
"intent": "reachable_by",
|
||||
"params": {
|
||||
"arm": "arm_slider",
|
||||
"targets": [
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
"opentrons_liquid_handler",
|
||||
"agilent_plateloc",
|
||||
"inheco_odtc_96xl"
|
||||
]
|
||||
},
|
||||
"description": "arm_slider must reach all devices since it handles all plate transfers"
|
||||
},
|
||||
{
|
||||
"intent": "workflow_hint",
|
||||
"params": {
|
||||
"workflow": "pcr",
|
||||
"devices": [
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
"opentrons_liquid_handler",
|
||||
"agilent_plateloc",
|
||||
"inheco_odtc_96xl"
|
||||
]
|
||||
},
|
||||
"description": "PCR workflow order: hotel → liquid handler → plate sealer → thermal cycler"
|
||||
},
|
||||
{
|
||||
"intent": "close_together",
|
||||
"params": {
|
||||
"devices": ["opentrons_liquid_handler", "agilent_plateloc"],
|
||||
"priority": "high"
|
||||
},
|
||||
"description": "Sealing happens immediately after sample prep — minimize transit time"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**Reasoning:**
|
||||
- The arm handles ALL transfers → all 4 devices in reachable_by targets
|
||||
- User described a clear sequence → workflow_hint in that order
|
||||
- "seal plate then pcr" implies sealing is immediately after prep → close_together for the pair with high priority
|
||||
|
||||
## Example: Simple Proximity Request
|
||||
|
||||
**User input:**
|
||||
> "Keep the thermal cycler close to the plate sealer, at most 1 meter apart"
|
||||
|
||||
**Your output:**
|
||||
```json
|
||||
{
|
||||
"intents": [
|
||||
{
|
||||
"intent": "max_distance",
|
||||
"params": {
|
||||
"device_a": "inheco_odtc_96xl",
|
||||
"device_b": "agilent_plateloc",
|
||||
"distance": 1.0
|
||||
},
|
||||
"description": "Thermal cycler and plate sealer must be within 1 meter"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## API Integration
|
||||
|
||||
### Discovery
|
||||
Call `GET /interpret/schema` to get the current list of available intent types and their parameter specifications. Always check this before translating, as new intent types may be added.
|
||||
|
||||
### Translation
|
||||
Send your output to `POST /interpret`:
|
||||
```
|
||||
POST /interpret
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"intents": [ ... your translated intents ... ]
|
||||
}
|
||||
```
|
||||
|
||||
### Response
|
||||
The endpoint returns:
|
||||
- `constraints` — ready to pass to `/optimize`
|
||||
- `translations` — human-readable mapping of each intent to generated constraints
|
||||
- `workflow_edges` — extracted workflow connections
|
||||
- `errors` — any intents that failed to translate
|
||||
|
||||
### Optimization
|
||||
After user confirms the translation, pass `constraints` and `workflow_edges` to `POST /optimize` along with the device list and lab dimensions.
|
||||
@@ -1,110 +0,0 @@
|
||||
"""Mock 检测器：无 ROS 依赖的简化碰撞与可达性检测。
|
||||
|
||||
碰撞检测基于 OBB SAT（O(n²) 两两比较）。
|
||||
可达性检测基于最大臂展半径的欧几里得距离判断。
|
||||
|
||||
集成阶段由 ros_checkers.py 中的 MoveItCollisionChecker / IKFastReachabilityChecker 替代。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
|
||||
from .obb import obb_corners, obb_overlap
|
||||
|
||||
|
||||
class MockCollisionChecker:
|
||||
"""基于 OBB SAT 的碰撞检测。
|
||||
|
||||
输入格式与 CollisionChecker Protocol 一致：
|
||||
placements: [{"id": str, "bbox": (w, d), "pos": (x, y, θ)}, ...]
|
||||
"""
|
||||
|
||||
def check(self, placements: list[dict]) -> list[tuple[str, str]]:
|
||||
"""返回所有碰撞的设备对。"""
|
||||
collisions: list[tuple[str, str]] = []
|
||||
n = len(placements)
|
||||
for i in range(n):
|
||||
for j in range(i + 1, n):
|
||||
a, b = placements[i], placements[j]
|
||||
corners_a = obb_corners(
|
||||
a["pos"][0], a["pos"][1],
|
||||
a["bbox"][0], a["bbox"][1],
|
||||
a["pos"][2] if len(a["pos"]) > 2 else 0.0,
|
||||
)
|
||||
corners_b = obb_corners(
|
||||
b["pos"][0], b["pos"][1],
|
||||
b["bbox"][0], b["bbox"][1],
|
||||
b["pos"][2] if len(b["pos"]) > 2 else 0.0,
|
||||
)
|
||||
if obb_overlap(corners_a, corners_b):
|
||||
collisions.append((a["id"], b["id"]))
|
||||
return collisions
|
||||
|
||||
def check_bounds(
|
||||
self, placements: list[dict], lab_width: float, lab_depth: float
|
||||
) -> list[str]:
|
||||
"""返回超出实验室边界的设备 ID 列表。"""
|
||||
out_of_bounds: list[str] = []
|
||||
for p in placements:
|
||||
hw, hd = self._rotated_half_extents(p)
|
||||
x, y = p["pos"][:2]
|
||||
if x - hw < 0 or x + hw > lab_width or y - hd < 0 or y + hd > lab_depth:
|
||||
out_of_bounds.append(p["id"])
|
||||
return out_of_bounds
|
||||
|
||||
@staticmethod
|
||||
def _rotated_half_extents(p: dict) -> tuple[float, float]:
|
||||
"""计算旋转后 AABB 的半宽和半深。"""
|
||||
w, d = p["bbox"]
|
||||
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
|
||||
cos_t = abs(math.cos(theta))
|
||||
sin_t = abs(math.sin(theta))
|
||||
half_w = (w * cos_t + d * sin_t) / 2
|
||||
half_d = (w * sin_t + d * cos_t) / 2
|
||||
return half_w, half_d
|
||||
|
||||
|
||||
class MockReachabilityChecker:
|
||||
"""基于最大臂展半径的简化可达性判断。
|
||||
|
||||
内置常见 Elite CS 系列机械臂的臂展参数。
|
||||
自定义臂展可通过构造参数传入。
|
||||
"""
|
||||
|
||||
# 默认臂展参数（单位：米）
|
||||
DEFAULT_ARM_REACH: dict[str, float] = {
|
||||
"elite_cs63": 0.624,
|
||||
"elite_cs66": 0.914,
|
||||
"elite_cs612": 1.304,
|
||||
"elite_cs620": 1.800,
|
||||
"arm_slider": 0.3, # 线性导轨臂：1.07 body 2.14m × 0.35m，reach ≈ half length
|
||||
}
|
||||
|
||||
# 未知型号回退臂展：realistic default for lab-scale arms
|
||||
DEFAULT_FALLBACK_REACH: float = 0.4
|
||||
|
||||
def __init__(self, arm_reach: dict[str, float] | None = None):
|
||||
self.arm_reach = {**self.DEFAULT_ARM_REACH, **(arm_reach or {})}
|
||||
|
||||
def is_reachable(self, arm_id: str, arm_pose: dict, target: dict) -> bool:
|
||||
"""判断目标点是否在机械臂最大臂展半径内。
|
||||
|
||||
Uses OBB edge-to-edge distance when available (passed as _obb_dist),
|
||||
otherwise falls back to center-to-center Euclidean distance.
|
||||
|
||||
Args:
|
||||
arm_id: 机械臂型号 ID（用于查臂展）
|
||||
arm_pose: {"x": float, "y": float, "theta": float}
|
||||
target: {"x": float, "y": float, "z": float, "_obb_dist": float (optional)}
|
||||
|
||||
Returns:
|
||||
True 如果目标在臂展半径内
|
||||
"""
|
||||
max_reach = self.arm_reach.get(arm_id, self.DEFAULT_FALLBACK_REACH)
|
||||
if "_obb_dist" in target:
|
||||
return target["_obb_dist"] <= max_reach
|
||||
dx = target["x"] - arm_pose["x"]
|
||||
dy = target["y"] - arm_pose["y"]
|
||||
dist_sq = dx**2 + dy**2
|
||||
return dist_sq <= max_reach**2
|
||||
@@ -1,96 +0,0 @@
|
||||
"""数据模型定义：Device, Lab, Placement, Constraint 及 API 请求/响应。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Literal
|
||||
|
||||
|
||||
@dataclass
|
||||
class Opening:
|
||||
"""设备的访问开口（用于方向约束）。"""
|
||||
|
||||
# 设备局部坐标系中的方向单位向量，如 (0, -1) = 正前方
|
||||
direction: tuple[float, float] = (0.0, -1.0)
|
||||
label: str = ""
|
||||
|
||||
|
||||
@dataclass
|
||||
class Device:
|
||||
"""设备描述。"""
|
||||
|
||||
id: str
|
||||
name: str
|
||||
# 碰撞包围盒 (width along X, depth along Y)，单位：米
|
||||
bbox: tuple[float, float] = (0.6, 0.4)
|
||||
device_type: Literal["static", "articulation", "rigid"] = "static"
|
||||
# 以下为可选扩展字段（向后兼容）
|
||||
height: float = 0.4
|
||||
origin_offset: tuple[float, float] = (0.0, 0.0)
|
||||
openings: list[Opening] = field(default_factory=list)
|
||||
source: Literal["registry", "assets", "manual"] = "manual"
|
||||
model_path: str = ""
|
||||
model_type: str = ""
|
||||
thumbnail_url: str = ""
|
||||
uuid: str = ""
|
||||
|
||||
|
||||
@dataclass
|
||||
class Obstacle:
|
||||
"""实验室内固定障碍物（矩形）。"""
|
||||
|
||||
x: float
|
||||
y: float
|
||||
width: float
|
||||
depth: float
|
||||
|
||||
|
||||
@dataclass
|
||||
class Lab:
|
||||
"""实验室平面图。"""
|
||||
|
||||
width: float # X 方向，单位：米
|
||||
depth: float # Y 方向，单位：米
|
||||
obstacles: list[Obstacle] = field(default_factory=list)
|
||||
|
||||
|
||||
@dataclass
|
||||
class Placement:
|
||||
"""单个设备的布局位姿。"""
|
||||
|
||||
device_id: str
|
||||
x: float
|
||||
y: float
|
||||
theta: float # 旋转角，弧度
|
||||
uuid: str = "" # 前端分配的唯一标识，透传不生成
|
||||
|
||||
def rotated_bbox(self, device: Device) -> tuple[float, float]:
|
||||
"""返回旋转后的 AABB 尺寸 (half_w, half_h)。"""
|
||||
w, d = device.bbox
|
||||
cos_t = abs(math.cos(self.theta))
|
||||
sin_t = abs(math.sin(self.theta))
|
||||
half_w = (w * cos_t + d * sin_t) / 2
|
||||
half_h = (w * sin_t + d * cos_t) / 2
|
||||
return half_w, half_h
|
||||
|
||||
|
||||
@dataclass
|
||||
class Constraint:
|
||||
"""约束规则。"""
|
||||
|
||||
type: Literal["hard", "soft"]
|
||||
rule_name: str
|
||||
# 规则参数，含义因 rule_name 而异
|
||||
params: dict = field(default_factory=dict)
|
||||
# 仅 soft 约束使用
|
||||
weight: float = 1.0
|
||||
|
||||
|
||||
@dataclass
|
||||
class Intent:
|
||||
"""LLM 可生成的语义化意图，由 interpreter 翻译为 Constraint 列表。"""
|
||||
|
||||
intent: str # 意图类型，如 "reachable_by", "close_together"
|
||||
params: dict = field(default_factory=dict)
|
||||
description: str = "" # 可选的自然语言描述（用于审计/调试）
|
||||
@@ -1,257 +0,0 @@
|
||||
"""OBB (Oriented Bounding Box) geometry: corners, overlap (SAT), minimum distance."""
|
||||
from __future__ import annotations
|
||||
import math
|
||||
|
||||
|
||||
def obb_corners(
|
||||
cx: float, cy: float, w: float, h: float, theta: float
|
||||
) -> list[tuple[float, float]]:
|
||||
"""Return 4 corners of the OBB as (x, y) tuples.
|
||||
|
||||
Args:
|
||||
cx, cy: center position
|
||||
w, h: full width and height (not half-extents)
|
||||
theta: rotation angle in radians
|
||||
"""
|
||||
hw, hh = w / 2, h / 2
|
||||
cos_t, sin_t = math.cos(theta), math.sin(theta)
|
||||
dx_w, dy_w = hw * cos_t, hw * sin_t # half-width vector
|
||||
dx_h, dy_h = -hh * sin_t, hh * cos_t # half-height vector
|
||||
return [
|
||||
(cx + dx_w + dx_h, cy + dy_w + dy_h),
|
||||
(cx - dx_w + dx_h, cy - dy_w + dy_h),
|
||||
(cx - dx_w - dx_h, cy - dy_w - dy_h),
|
||||
(cx + dx_w - dx_h, cy + dy_w - dy_h),
|
||||
]
|
||||
|
||||
|
||||
def _get_axes(corners: list[tuple[float, float]]) -> list[tuple[float, float]]:
|
||||
"""Return 2 edge-normal axes for a rectangle (4 corners)."""
|
||||
axes = []
|
||||
for i in range(2): # Only need 2 axes for a rectangle
|
||||
edge_x = corners[i + 1][0] - corners[i][0]
|
||||
edge_y = corners[i + 1][1] - corners[i][1]
|
||||
length = math.sqrt(edge_x**2 + edge_y**2)
|
||||
if length > 0:
|
||||
axes.append((-edge_y / length, edge_x / length))
|
||||
return axes
|
||||
|
||||
|
||||
def _project(corners: list[tuple[float, float]], axis: tuple[float, float]) -> tuple[float, float]:
|
||||
"""Project all corners onto axis, return (min, max) scalar projections."""
|
||||
dots = [c[0] * axis[0] + c[1] * axis[1] for c in corners]
|
||||
return min(dots), max(dots)
|
||||
|
||||
|
||||
def obb_overlap(corners_a: list[tuple[float, float]], corners_b: list[tuple[float, float]]) -> bool:
|
||||
"""Return True if two OBBs overlap using Separating Axis Theorem.
|
||||
|
||||
Uses strict inequality (touching edges = no overlap).
|
||||
"""
|
||||
for axis in _get_axes(corners_a) + _get_axes(corners_b):
|
||||
min_a, max_a = _project(corners_a, axis)
|
||||
min_b, max_b = _project(corners_b, axis)
|
||||
if max_a <= min_b or max_b <= min_a:
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def _point_to_segment_dist_sq(
|
||||
px: float, py: float,
|
||||
ax: float, ay: float,
|
||||
bx: float, by: float,
|
||||
) -> float:
|
||||
"""Squared distance from point (px,py) to line segment (ax,ay)-(bx,by)."""
|
||||
dx, dy = bx - ax, by - ay
|
||||
len_sq = dx * dx + dy * dy
|
||||
if len_sq == 0:
|
||||
return (px - ax) ** 2 + (py - ay) ** 2
|
||||
t = max(0.0, min(1.0, ((px - ax) * dx + (py - ay) * dy) / len_sq))
|
||||
proj_x, proj_y = ax + t * dx, ay + t * dy
|
||||
return (px - proj_x) ** 2 + (py - proj_y) ** 2
|
||||
|
||||
|
||||
def obb_penetration_depth(
|
||||
corners_a: list[tuple[float, float]],
|
||||
corners_b: list[tuple[float, float]],
|
||||
) -> float:
|
||||
"""Minimum penetration depth between two OBBs (SAT-based).
|
||||
|
||||
Returns 0.0 if not overlapping. Otherwise returns the minimum overlap
|
||||
along any separating axis — the smallest push needed to separate them.
|
||||
"""
|
||||
min_overlap = float("inf")
|
||||
for axis in _get_axes(corners_a) + _get_axes(corners_b):
|
||||
min_a, max_a = _project(corners_a, axis)
|
||||
min_b, max_b = _project(corners_b, axis)
|
||||
overlap = min(max_a - min_b, max_b - min_a)
|
||||
if overlap <= 0:
|
||||
return 0.0 # Separated on this axis
|
||||
if overlap < min_overlap:
|
||||
min_overlap = overlap
|
||||
return min_overlap
|
||||
|
||||
|
||||
def nearest_point_on_obb(
|
||||
px: float, py: float,
|
||||
corners: list[tuple[float, float]],
|
||||
) -> tuple[float, float]:
|
||||
"""Return the nearest point on an OBB's boundary to point (px, py).
|
||||
|
||||
If the point is inside the OBB, returns the nearest edge point.
|
||||
"""
|
||||
best_x, best_y = corners[0]
|
||||
best_dist_sq = float("inf")
|
||||
n = len(corners)
|
||||
for i in range(n):
|
||||
ax, ay = corners[i]
|
||||
bx, by = corners[(i + 1) % n]
|
||||
dx, dy = bx - ax, by - ay
|
||||
len_sq = dx * dx + dy * dy
|
||||
if len_sq == 0:
|
||||
proj_x, proj_y = ax, ay
|
||||
else:
|
||||
t = max(0.0, min(1.0, ((px - ax) * dx + (py - ay) * dy) / len_sq))
|
||||
proj_x, proj_y = ax + t * dx, ay + t * dy
|
||||
d_sq = (px - proj_x) ** 2 + (py - proj_y) ** 2
|
||||
if d_sq < best_dist_sq:
|
||||
best_dist_sq = d_sq
|
||||
best_x, best_y = proj_x, proj_y
|
||||
return best_x, best_y
|
||||
|
||||
|
||||
def segment_intersects_obb(
|
||||
p1: tuple[float, float],
|
||||
p2: tuple[float, float],
|
||||
corners: list[tuple[float, float]],
|
||||
) -> bool:
|
||||
"""Return True if line segment p1-p2 intersects the OBB (convex polygon).
|
||||
|
||||
Uses separating axis theorem on the Minkowski difference:
|
||||
test segment against each edge of the polygon + segment normal.
|
||||
"""
|
||||
# Quick: test each edge of the OBB against the segment
|
||||
n = len(corners)
|
||||
for i in range(n):
|
||||
ax, ay = corners[i]
|
||||
bx, by = corners[(i + 1) % n]
|
||||
if _segments_intersect(p1[0], p1[1], p2[0], p2[1], ax, ay, bx, by):
|
||||
return True
|
||||
# Also check if segment is fully inside the OBB
|
||||
if _point_in_convex(p1, corners) or _point_in_convex(p2, corners):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _segments_intersect(
|
||||
ax: float, ay: float, bx: float, by: float,
|
||||
cx: float, cy: float, dx: float, dy: float,
|
||||
) -> bool:
|
||||
"""Return True if segment AB intersects segment CD (proper or endpoint)."""
|
||||
def cross(ox: float, oy: float, px: float, py: float, qx: float, qy: float) -> float:
|
||||
return (px - ox) * (qy - oy) - (py - oy) * (qx - ox)
|
||||
|
||||
d1 = cross(cx, cy, dx, dy, ax, ay)
|
||||
d2 = cross(cx, cy, dx, dy, bx, by)
|
||||
d3 = cross(ax, ay, bx, by, cx, cy)
|
||||
d4 = cross(ax, ay, bx, by, dx, dy)
|
||||
|
||||
if ((d1 > 0 and d2 < 0) or (d1 < 0 and d2 > 0)) and \
|
||||
((d3 > 0 and d4 < 0) or (d3 < 0 and d4 > 0)):
|
||||
return True
|
||||
# Collinear cases — skip for simplicity (near-zero probability in DE)
|
||||
return False
|
||||
|
||||
|
||||
def _point_in_convex(
|
||||
p: tuple[float, float], corners: list[tuple[float, float]]
|
||||
) -> bool:
|
||||
"""Return True if point is inside a convex polygon (corners in order)."""
|
||||
n = len(corners)
|
||||
sign = None
|
||||
for i in range(n):
|
||||
ax, ay = corners[i]
|
||||
bx, by = corners[(i + 1) % n]
|
||||
cross = (bx - ax) * (p[1] - ay) - (by - ay) * (p[0] - ax)
|
||||
if abs(cross) < 1e-12:
|
||||
continue
|
||||
s = cross > 0
|
||||
if sign is None:
|
||||
sign = s
|
||||
elif s != sign:
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def segment_obb_intersection_length(
|
||||
p1: tuple[float, float],
|
||||
p2: tuple[float, float],
|
||||
corners: list[tuple[float, float]],
|
||||
) -> float:
|
||||
"""线段 p1-p2 与 OBB（凸多边形）的交集长度。
|
||||
|
||||
Cyrus-Beck 线段裁剪算法。corners 假定为 CCW 顺序（obb_corners 生成）。
|
||||
无交集返回 0.0。
|
||||
"""
|
||||
dx = p2[0] - p1[0]
|
||||
dy = p2[1] - p1[1]
|
||||
seg_len_sq = dx * dx + dy * dy
|
||||
if seg_len_sq < 1e-24:
|
||||
return 0.0
|
||||
|
||||
t_enter = 0.0
|
||||
t_exit = 1.0
|
||||
n = len(corners)
|
||||
|
||||
for i in range(n):
|
||||
ax, ay = corners[i]
|
||||
bx, by = corners[(i + 1) % n]
|
||||
# CCW 多边形边的外法线: (ey, -ex), e = b - a
|
||||
ex, ey = bx - ax, by - ay
|
||||
nx, ny = ey, -ex
|
||||
|
||||
denom = nx * dx + ny * dy
|
||||
numer = nx * (p1[0] - ax) + ny * (p1[1] - ay)
|
||||
|
||||
if abs(denom) < 1e-12:
|
||||
if numer > 0:
|
||||
return 0.0 # 在此边外侧且平行
|
||||
continue
|
||||
|
||||
t = -numer / denom
|
||||
if denom < 0:
|
||||
t_enter = max(t_enter, t) # 进入
|
||||
else:
|
||||
t_exit = min(t_exit, t) # 退出
|
||||
|
||||
if t_enter > t_exit:
|
||||
return 0.0
|
||||
|
||||
if t_enter >= t_exit:
|
||||
return 0.0
|
||||
|
||||
return (t_exit - t_enter) * math.sqrt(seg_len_sq)
|
||||
|
||||
|
||||
def obb_min_distance(
|
||||
corners_a: list[tuple[float, float]],
|
||||
corners_b: list[tuple[float, float]],
|
||||
) -> float:
|
||||
"""Minimum distance between two OBBs (convex polygons).
|
||||
|
||||
Returns 0.0 if overlapping or touching.
|
||||
"""
|
||||
if obb_overlap(corners_a, corners_b):
|
||||
return 0.0
|
||||
|
||||
min_dist_sq = float("inf")
|
||||
for poly, other in [(corners_a, corners_b), (corners_b, corners_a)]:
|
||||
n = len(other)
|
||||
for px, py in poly:
|
||||
for i in range(n):
|
||||
ax, ay = other[i]
|
||||
bx, by = other[(i + 1) % n]
|
||||
d_sq = _point_to_segment_dist_sq(px, py, ax, ay, bx, by)
|
||||
if d_sq < min_dist_sq:
|
||||
min_dist_sq = d_sq
|
||||
return math.sqrt(min_dist_sq)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,144 +0,0 @@
|
||||
"""初始布局生成：Pencil MCP 接口 + 行列式回退。
|
||||
|
||||
策略：
|
||||
1. 尝试调用 Pencil AI MCP 生成初始布局
|
||||
2. 若 Pencil 不可用或失败，回退到行列式放置算法
|
||||
|
||||
行列式回退逻辑：
|
||||
- 设备按面积从大到小排序
|
||||
- 沿 X 轴逐个放置，行满（超出 lab.width）则换行
|
||||
- 设备间保留 margin 间距
|
||||
- 所有设备 θ=0（朝向不变）
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
|
||||
from .models import Device, Lab, Placement
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 设备间最小间距（米）
|
||||
DEFAULT_MARGIN = 0.3
|
||||
|
||||
|
||||
def generate_initial_layout(
|
||||
devices: list[Device],
|
||||
lab: Lab,
|
||||
margin: float = DEFAULT_MARGIN,
|
||||
) -> list[Placement]:
|
||||
"""生成初始布局方案。
|
||||
|
||||
优先尝试 Pencil MCP，失败则回退到行列式放置。
|
||||
|
||||
Args:
|
||||
devices: 待放置的设备列表
|
||||
lab: 实验室平面图
|
||||
margin: 设备间最小间距
|
||||
|
||||
Returns:
|
||||
初始布局 Placement 列表
|
||||
"""
|
||||
# 尝试 Pencil MCP
|
||||
pencil_result = _try_pencil(devices, lab)
|
||||
if pencil_result is not None:
|
||||
logger.info("Using Pencil AI generated layout")
|
||||
return pencil_result
|
||||
|
||||
# 回退到行列式
|
||||
logger.info("Pencil unavailable, using row-based fallback layout")
|
||||
return generate_fallback(devices, lab, margin)
|
||||
|
||||
|
||||
def _try_pencil(
|
||||
devices: list[Device],
|
||||
lab: Lab,
|
||||
) -> list[Placement] | None:
|
||||
"""尝试通过 Pencil AI MCP 生成布局。
|
||||
|
||||
当前 Pencil MCP 不可用，返回 None 触发回退。
|
||||
未来集成时，此函数应：
|
||||
1. 将设备 2D 投影 + 实验室平面图序列化为 Pencil 输入格式
|
||||
2. 调用 mcp__pencil_* 工具
|
||||
3. 解析返回的布局方案为 Placement 列表
|
||||
|
||||
预留接口参数：
|
||||
- devices: 设备列表（id, bbox）
|
||||
- lab: 实验室尺寸
|
||||
"""
|
||||
# TODO: 当 Pencil MCP 可用时实现
|
||||
# 预期调用方式：
|
||||
# pencil_input = {
|
||||
# "floor_plan": {"width": lab.width, "depth": lab.depth},
|
||||
# "items": [{"id": d.id, "width": d.bbox[0], "depth": d.bbox[1]} for d in devices],
|
||||
# }
|
||||
# result = mcp__pencil_layout(pencil_input)
|
||||
# return [Placement(device_id=r["id"], x=r["x"], y=r["y"], theta=r["theta"]) for r in result]
|
||||
return None
|
||||
|
||||
|
||||
def generate_fallback(
|
||||
devices: list[Device],
|
||||
lab: Lab,
|
||||
margin: float = DEFAULT_MARGIN,
|
||||
) -> list[Placement]:
|
||||
"""行列式回退布局：按面积从大到小排序，逐行放置。
|
||||
|
||||
放置规则：
|
||||
- 设备中心坐标，从左上角开始
|
||||
- 每行从 margin + half_width 开始
|
||||
- 行满（下一个设备右边缘超出 lab.width - margin）则换行
|
||||
- 行高取该行最大设备深度
|
||||
|
||||
Args:
|
||||
devices: 待放置的设备列表
|
||||
lab: 实验室平面图
|
||||
margin: 设备间最小间距
|
||||
|
||||
Returns:
|
||||
Placement 列表。若实验室空间不足，剩余设备堆叠在右下角并记录警告。
|
||||
"""
|
||||
if not devices:
|
||||
return []
|
||||
|
||||
# 按面积从大到小排序
|
||||
sorted_devices = sorted(devices, key=lambda d: d.bbox[0] * d.bbox[1], reverse=True)
|
||||
|
||||
placements: list[Placement] = []
|
||||
cursor_x = margin
|
||||
cursor_y = margin
|
||||
row_height = 0.0
|
||||
|
||||
for dev in sorted_devices:
|
||||
w, d = dev.bbox
|
||||
half_w = w / 2
|
||||
half_d = d / 2
|
||||
|
||||
# 检查当前行是否放得下
|
||||
if cursor_x + half_w + margin > lab.width and placements:
|
||||
# 换行
|
||||
cursor_x = margin
|
||||
cursor_y += row_height + margin
|
||||
row_height = 0.0
|
||||
|
||||
# 设备中心位置
|
||||
cx = cursor_x + half_w
|
||||
cy = cursor_y + half_d
|
||||
|
||||
# 检查是否超出实验室深度
|
||||
if cy + half_d + margin > lab.depth:
|
||||
logger.warning(
|
||||
"Lab space insufficient for device '%s' (%s), "
|
||||
"placing at overflow position",
|
||||
dev.id,
|
||||
dev.bbox,
|
||||
)
|
||||
|
||||
placements.append(Placement(device_id=dev.id, x=cx, y=cy, theta=0.0))
|
||||
|
||||
# 更新游标
|
||||
cursor_x = cx + half_w + margin
|
||||
row_height = max(row_height, d)
|
||||
|
||||
return placements
|
||||
@@ -1,29 +0,0 @@
|
||||
[build-system]
|
||||
requires = ["setuptools>=68.0", "wheel"]
|
||||
build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "layout-optimizer"
|
||||
version = "0.1.0"
|
||||
description = "AI laboratory layout optimizer for Uni-Lab Phase 3"
|
||||
requires-python = ">=3.10"
|
||||
dependencies = [
|
||||
"scipy>=1.10",
|
||||
"numpy>=1.24",
|
||||
"fastapi>=0.100",
|
||||
"uvicorn>=0.20",
|
||||
"pydantic>=2.0",
|
||||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
dev = [
|
||||
"pytest>=7.0",
|
||||
"httpx>=0.24",
|
||||
]
|
||||
|
||||
[tool.setuptools.packages.find]
|
||||
where = ["."]
|
||||
include = ["layout_optimizer*"]
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
testpaths = ["tests"]
|
||||
@@ -1,433 +0,0 @@
|
||||
"""ROS2/MoveIt2 碰撞检测与 IKFast 可达性检测适配器。
|
||||
|
||||
集成阶段替换 mock_checkers.py 中的 Mock 实现，
|
||||
依赖 Uni-Lab-OS 的 moveit2.py 提供的 MoveIt2 Python 接口。
|
||||
|
||||
用法：
|
||||
from .ros_checkers import MoveItCollisionChecker, IKFastReachabilityChecker
|
||||
|
||||
# 碰撞检测
|
||||
checker = MoveItCollisionChecker(moveit2_instance)
|
||||
collisions = checker.check(placements)
|
||||
|
||||
# 可达性检测（体素图 O(1) 查询 + 实时 IK 回退）
|
||||
reachability = IKFastReachabilityChecker(moveit2_instance, voxel_dir="/path/to/voxels")
|
||||
reachable = reachability.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
环境变量：
|
||||
LAYOUT_CHECKER_MODE: "mock" | "moveit" — 选择检测器实现（默认 "mock"）
|
||||
LAYOUT_VOXEL_DIR: 预计算体素图目录路径（.npz 文件）
|
||||
|
||||
前置条件：
|
||||
- ROS2 + MoveIt2 运行中
|
||||
- moveit2.py 中的 MoveIt2 实例已初始化
|
||||
- 命名规范：碰撞对象使用 {device_id}_ 前缀
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import math
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
import numpy as np
|
||||
|
||||
from .obb import obb_corners, obb_overlap
|
||||
|
||||
if TYPE_CHECKING:
|
||||
pass
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# ---------- 坐标变换辅助 ----------
|
||||
|
||||
|
||||
def _yaw_to_quat(theta: float) -> tuple[float, float, float, float]:
|
||||
"""将 2D 旋转角（绕 Z 轴弧度）转换为四元数 (x, y, z, w)。"""
|
||||
return (0.0, 0.0, math.sin(theta / 2), math.cos(theta / 2))
|
||||
|
||||
|
||||
def _transform_to_arm_frame(
|
||||
arm_pose: dict, target: dict,
|
||||
) -> tuple[float, float, float]:
|
||||
"""将目标点从世界坐标系变换到机械臂基坐标系。
|
||||
|
||||
Args:
|
||||
arm_pose: {"x": float, "y": float, "theta": float}
|
||||
target: {"x": float, "y": float, "z": float}
|
||||
|
||||
Returns:
|
||||
(local_x, local_y, local_z) 在臂基坐标系中的位置
|
||||
"""
|
||||
dx = target["x"] - arm_pose["x"]
|
||||
dy = target["y"] - arm_pose["y"]
|
||||
theta = arm_pose.get("theta", 0.0)
|
||||
cos_t = math.cos(-theta)
|
||||
sin_t = math.sin(-theta)
|
||||
local_x = dx * cos_t - dy * sin_t
|
||||
local_y = dx * sin_t + dy * cos_t
|
||||
local_z = target.get("z", 0.0)
|
||||
return (local_x, local_y, local_z)
|
||||
|
||||
|
||||
# ---------- MoveItCollisionChecker ----------
|
||||
|
||||
|
||||
class MoveItCollisionChecker:
|
||||
"""通过 MoveIt2 PlanningScene 进行碰撞检测。
|
||||
|
||||
工作流程：
|
||||
1. 将所有设备同步为 MoveIt2 碰撞盒（{device_id}_ 前缀）
|
||||
2. 使用 python-fcl 进行精确两两碰撞检测（若可用）
|
||||
3. 若 FCL 不可用，回退到 OBB SAT 检测
|
||||
|
||||
同步到 MoveIt2 确保机器人运动规划也能感知设备布局。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
moveit2: Any,
|
||||
*,
|
||||
default_height: float = 0.4,
|
||||
sync_to_scene: bool = True,
|
||||
):
|
||||
"""
|
||||
Args:
|
||||
moveit2: Uni-Lab-OS moveit2.py 中的 MoveIt2 实例
|
||||
default_height: 碰撞盒默认高度（米）
|
||||
sync_to_scene: 是否同步碰撞对象到 MoveIt2 规划场景
|
||||
"""
|
||||
self._moveit2 = moveit2
|
||||
self._default_height = default_height
|
||||
self._sync_to_scene = sync_to_scene
|
||||
self._fcl_available = self._check_fcl()
|
||||
|
||||
@staticmethod
|
||||
def _check_fcl() -> bool:
|
||||
"""检查 python-fcl 是否可用。"""
|
||||
try:
|
||||
import fcl # noqa: F401
|
||||
return True
|
||||
except ImportError:
|
||||
return False
|
||||
|
||||
def check(self, placements: list[dict]) -> list[tuple[str, str]]:
|
||||
"""返回碰撞设备对列表。
|
||||
|
||||
Args:
|
||||
placements: [{"id": str, "bbox": (w, d), "pos": (x, y, θ)}, ...]
|
||||
|
||||
Returns:
|
||||
[("device_a", "device_b"), ...] 存在碰撞的设备对
|
||||
"""
|
||||
# 同步到 MoveIt2 规划场景
|
||||
if self._sync_to_scene:
|
||||
self._sync_collision_objects(placements)
|
||||
|
||||
# 碰撞检测
|
||||
if self._fcl_available:
|
||||
return self._check_with_fcl(placements)
|
||||
return self._check_with_obb(placements)
|
||||
|
||||
def check_bounds(
|
||||
self, placements: list[dict], lab_width: float, lab_depth: float,
|
||||
) -> list[str]:
|
||||
"""返回超出实验室边界的设备 ID 列表。"""
|
||||
out_of_bounds: list[str] = []
|
||||
for p in placements:
|
||||
hw, hd = self._rotated_half_extents(p)
|
||||
x, y = p["pos"][:2]
|
||||
if x - hw < 0 or x + hw > lab_width or y - hd < 0 or y + hd > lab_depth:
|
||||
out_of_bounds.append(p["id"])
|
||||
return out_of_bounds
|
||||
|
||||
def _sync_collision_objects(self, placements: list[dict]) -> None:
|
||||
"""将设备布局同步到 MoveIt2 规划场景。
|
||||
|
||||
使用 {device_id}_ 前缀命名碰撞对象。
|
||||
"""
|
||||
for p in placements:
|
||||
obj_id = f"{p['id']}_"
|
||||
w, d = p["bbox"]
|
||||
x, y = p["pos"][:2]
|
||||
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
|
||||
h = self._default_height
|
||||
|
||||
try:
|
||||
self._moveit2.add_collision_box(
|
||||
id=obj_id,
|
||||
size=(w, d, h),
|
||||
position=(x, y, h / 2),
|
||||
quat_xyzw=_yaw_to_quat(theta),
|
||||
)
|
||||
except Exception:
|
||||
logger.warning("Failed to sync collision object %s", obj_id, exc_info=True)
|
||||
|
||||
def _check_with_fcl(self, placements: list[dict]) -> list[tuple[str, str]]:
|
||||
"""使用 python-fcl 进行精确碰撞检测。"""
|
||||
import fcl
|
||||
|
||||
objects: list[tuple[str, Any]] = []
|
||||
for p in placements:
|
||||
w, d = p["bbox"]
|
||||
h = self._default_height
|
||||
x, y = p["pos"][:2]
|
||||
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
|
||||
|
||||
geom = fcl.Box(w, d, h)
|
||||
tf = fcl.Transform(
|
||||
_yaw_to_rotation_matrix(theta),
|
||||
np.array([x, y, h / 2]),
|
||||
)
|
||||
obj = fcl.CollisionObject(geom, tf)
|
||||
objects.append((p["id"], obj))
|
||||
|
||||
collisions: list[tuple[str, str]] = []
|
||||
n = len(objects)
|
||||
for i in range(n):
|
||||
for j in range(i + 1, n):
|
||||
id_a, obj_a = objects[i]
|
||||
id_b, obj_b = objects[j]
|
||||
request = fcl.CollisionRequest()
|
||||
result = fcl.CollisionResult()
|
||||
ret = fcl.collide(obj_a, obj_b, request, result)
|
||||
if ret > 0:
|
||||
collisions.append((id_a, id_b))
|
||||
|
||||
return collisions
|
||||
|
||||
def _check_with_obb(self, placements: list[dict]) -> list[tuple[str, str]]:
|
||||
"""OBB SAT 回退检测（与 MockCollisionChecker 相同算法）。"""
|
||||
collisions: list[tuple[str, str]] = []
|
||||
n = len(placements)
|
||||
for i in range(n):
|
||||
for j in range(i + 1, n):
|
||||
a, b = placements[i], placements[j]
|
||||
corners_a = obb_corners(
|
||||
a["pos"][0], a["pos"][1],
|
||||
a["bbox"][0], a["bbox"][1],
|
||||
a["pos"][2] if len(a["pos"]) > 2 else 0.0,
|
||||
)
|
||||
corners_b = obb_corners(
|
||||
b["pos"][0], b["pos"][1],
|
||||
b["bbox"][0], b["bbox"][1],
|
||||
b["pos"][2] if len(b["pos"]) > 2 else 0.0,
|
||||
)
|
||||
if obb_overlap(corners_a, corners_b):
|
||||
collisions.append((a["id"], b["id"]))
|
||||
return collisions
|
||||
|
||||
@staticmethod
|
||||
def _rotated_half_extents(p: dict) -> tuple[float, float]:
|
||||
"""计算旋转后 AABB 的半宽和半深。"""
|
||||
w, d = p["bbox"]
|
||||
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
|
||||
cos_t = abs(math.cos(theta))
|
||||
sin_t = abs(math.sin(theta))
|
||||
half_w = (w * cos_t + d * sin_t) / 2
|
||||
half_d = (w * sin_t + d * cos_t) / 2
|
||||
return half_w, half_d
|
||||
|
||||
|
||||
# ---------- IKFastReachabilityChecker ----------
|
||||
|
||||
|
||||
class IKFastReachabilityChecker:
|
||||
"""基于 MoveIt2 compute_ik 和预计算体素图的可达性检测。
|
||||
|
||||
双模式：
|
||||
1. 体素图模式（O(1)）：从 .npz 文件加载预计算可达性网格，
|
||||
将目标点变换到臂基坐标系后直接查表。
|
||||
2. 实时 IK 模式（~5ms/call）：调用 MoveIt2.compute_ik()，
|
||||
支持约束感知的精确可达性判断。
|
||||
|
||||
优先使用体素图，无匹配时回退到实时 IK。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
moveit2: Any = None,
|
||||
*,
|
||||
voxel_dir: str | Path | None = None,
|
||||
voxel_resolution: float = 0.01,
|
||||
):
|
||||
"""
|
||||
Args:
|
||||
moveit2: MoveIt2 实例（用于实时 IK 回退）
|
||||
voxel_dir: 预计算体素图目录（.npz 文件，文件名 = arm_id）
|
||||
voxel_resolution: 体素分辨率（米），用于坐标 → 索引转换
|
||||
"""
|
||||
self._moveit2 = moveit2
|
||||
self._voxel_resolution = voxel_resolution
|
||||
self._voxel_maps: dict[str, _VoxelMap] = {}
|
||||
|
||||
if voxel_dir is not None:
|
||||
self._load_voxel_maps(Path(voxel_dir))
|
||||
|
||||
def is_reachable(self, arm_id: str, arm_pose: dict, target: dict) -> bool:
|
||||
"""判断机械臂在给定位姿下能否到达目标点。
|
||||
|
||||
Args:
|
||||
arm_id: 机械臂设备 ID
|
||||
arm_pose: {"x": float, "y": float, "theta": float}
|
||||
target: {"x": float, "y": float, "z": float}
|
||||
|
||||
Returns:
|
||||
True 如果可达
|
||||
"""
|
||||
local = _transform_to_arm_frame(arm_pose, target)
|
||||
|
||||
# 1. 体素图查询（O(1)）
|
||||
if arm_id in self._voxel_maps:
|
||||
return self._check_voxel(arm_id, local)
|
||||
|
||||
# 2. 实时 IK 回退
|
||||
if self._moveit2 is not None:
|
||||
return self._check_live_ik(local)
|
||||
|
||||
# 无可用检测方式，乐观返回（记录警告）
|
||||
logger.warning(
|
||||
"No reachability checker available for arm %s, returning True", arm_id,
|
||||
)
|
||||
return True
|
||||
|
||||
def _load_voxel_maps(self, voxel_dir: Path) -> None:
|
||||
"""加载目录下所有 .npz 体素图文件。
|
||||
|
||||
文件格式：{arm_id}.npz，包含：
|
||||
- "grid": bool ndarray (nx, ny, nz) — True 表示可达
|
||||
- "origin": float ndarray (3,) — 网格原点（臂基坐标系）
|
||||
- "resolution": float — 体素分辨率（米）
|
||||
"""
|
||||
if not voxel_dir.exists():
|
||||
logger.warning("Voxel directory does not exist: %s", voxel_dir)
|
||||
return
|
||||
|
||||
for npz_file in voxel_dir.glob("*.npz"):
|
||||
arm_id = npz_file.stem
|
||||
try:
|
||||
data = np.load(str(npz_file))
|
||||
grid = data["grid"].astype(bool)
|
||||
origin = data["origin"].astype(float)
|
||||
resolution = float(data.get("resolution", self._voxel_resolution))
|
||||
self._voxel_maps[arm_id] = _VoxelMap(
|
||||
grid=grid, origin=origin, resolution=resolution,
|
||||
)
|
||||
logger.info(
|
||||
"Loaded voxel map for %s: shape=%s, resolution=%.3f",
|
||||
arm_id, grid.shape, resolution,
|
||||
)
|
||||
except Exception:
|
||||
logger.warning("Failed to load voxel map %s", npz_file, exc_info=True)
|
||||
|
||||
def _check_voxel(self, arm_id: str, local: tuple[float, float, float]) -> bool:
|
||||
"""通过体素网格查询可达性。"""
|
||||
vm = self._voxel_maps[arm_id]
|
||||
ix = int(round((local[0] - vm.origin[0]) / vm.resolution))
|
||||
iy = int(round((local[1] - vm.origin[1]) / vm.resolution))
|
||||
iz = int(round((local[2] - vm.origin[2]) / vm.resolution))
|
||||
|
||||
if (
|
||||
0 <= ix < vm.grid.shape[0]
|
||||
and 0 <= iy < vm.grid.shape[1]
|
||||
and 0 <= iz < vm.grid.shape[2]
|
||||
):
|
||||
return bool(vm.grid[ix, iy, iz])
|
||||
|
||||
# 超出体素图范围 → 不可达
|
||||
return False
|
||||
|
||||
def _check_live_ik(self, local: tuple[float, float, float]) -> bool:
|
||||
"""调用 MoveIt2.compute_ik() 进行实时可达性检测。
|
||||
|
||||
compute_ik 返回 JointState（成功）或 None（不可达）。
|
||||
使用默认朝下姿态（四元数 0, 1, 0, 0 即绕 X 轴旋转 180°）。
|
||||
"""
|
||||
# 目标姿态：末端执行器朝下
|
||||
quat_xyzw = (0.0, 1.0, 0.0, 0.0)
|
||||
try:
|
||||
result = self._moveit2.compute_ik(
|
||||
position=local,
|
||||
quat_xyzw=quat_xyzw,
|
||||
)
|
||||
return result is not None
|
||||
except Exception:
|
||||
logger.warning("compute_ik call failed", exc_info=True)
|
||||
return False
|
||||
|
||||
|
||||
# ---------- 体素图数据类 ----------
|
||||
|
||||
|
||||
class _VoxelMap:
|
||||
"""预计算可达性体素网格。"""
|
||||
|
||||
__slots__ = ("grid", "origin", "resolution")
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
grid: np.ndarray,
|
||||
origin: np.ndarray,
|
||||
resolution: float,
|
||||
):
|
||||
self.grid = grid
|
||||
self.origin = origin
|
||||
self.resolution = resolution
|
||||
|
||||
|
||||
# ---------- FCL 辅助 ----------
|
||||
|
||||
|
||||
def _yaw_to_rotation_matrix(theta: float) -> np.ndarray:
|
||||
"""绕 Z 轴旋转矩阵（3×3）。"""
|
||||
c, s = math.cos(theta), math.sin(theta)
|
||||
return np.array([
|
||||
[c, -s, 0.0],
|
||||
[s, c, 0.0],
|
||||
[0.0, 0.0, 1.0],
|
||||
])
|
||||
|
||||
|
||||
# ---------- 工厂函数 ----------
|
||||
|
||||
|
||||
def create_checkers(
|
||||
moveit2: Any = None,
|
||||
*,
|
||||
mode: str | None = None,
|
||||
voxel_dir: str | None = None,
|
||||
) -> tuple[Any, Any]:
|
||||
"""根据环境变量或参数创建检测器实例。
|
||||
|
||||
Args:
|
||||
moveit2: MoveIt2 实例（moveit 模式必需）
|
||||
mode: "mock" | "moveit"（默认从 LAYOUT_CHECKER_MODE 环境变量读取）
|
||||
voxel_dir: 体素图目录（默认从 LAYOUT_VOXEL_DIR 环境变量读取）
|
||||
|
||||
Returns:
|
||||
(collision_checker, reachability_checker)
|
||||
"""
|
||||
if mode is None:
|
||||
mode = os.getenv("LAYOUT_CHECKER_MODE", "mock")
|
||||
|
||||
if mode == "moveit":
|
||||
if moveit2 is None:
|
||||
raise ValueError("MoveIt2 instance required for 'moveit' checker mode")
|
||||
|
||||
if voxel_dir is None:
|
||||
voxel_dir = os.getenv("LAYOUT_VOXEL_DIR")
|
||||
|
||||
collision = MoveItCollisionChecker(moveit2)
|
||||
reachability = IKFastReachabilityChecker(
|
||||
moveit2, voxel_dir=voxel_dir,
|
||||
)
|
||||
logger.info("Using MoveIt2 checkers (voxel_dir=%s)", voxel_dir)
|
||||
return collision, reachability
|
||||
|
||||
# 默认：mock 模式
|
||||
from .mock_checkers import MockCollisionChecker, MockReachabilityChecker
|
||||
|
||||
logger.info("Using mock checkers")
|
||||
return MockCollisionChecker(), MockReachabilityChecker()
|
||||
@@ -1,331 +0,0 @@
|
||||
"""Force-directed seeder engine with named parameter presets.
|
||||
|
||||
Produces initial device placements for the layout optimizer.
|
||||
Different layout strategies (compact, spread, workflow-aware) are
|
||||
parameter configurations of the same force-directed simulation engine.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import math
|
||||
from dataclasses import dataclass, replace
|
||||
|
||||
from .models import Device, Lab, Placement
|
||||
from .obb import obb_corners, obb_overlap, obb_min_distance
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class SeederParams:
|
||||
"""Parameters for the force-directed seeder engine."""
|
||||
boundary_attraction: float = 0.0 # >0 push to walls, <0 push to center
|
||||
mutual_repulsion: float = 1.0 # inter-device repulsion strength
|
||||
edge_attraction: float = 0.0 # workflow edge attraction (Stage 2)
|
||||
orientation_mode: str = "none" # "outward" | "inward" | "none"
|
||||
|
||||
|
||||
PRESETS: dict[str, SeederParams | None] = {
|
||||
"compact_outward": SeederParams(
|
||||
boundary_attraction=-1.0, mutual_repulsion=0.5, orientation_mode="outward",
|
||||
),
|
||||
"spread_inward": SeederParams(
|
||||
boundary_attraction=1.0, mutual_repulsion=1.0, orientation_mode="inward",
|
||||
),
|
||||
"workflow_cluster": SeederParams(
|
||||
boundary_attraction=-0.5, mutual_repulsion=0.5,
|
||||
edge_attraction=1.0, orientation_mode="outward",
|
||||
),
|
||||
"row_fallback": None, # Delegates to generate_fallback()
|
||||
}
|
||||
|
||||
|
||||
def resolve_seeder_params(
|
||||
preset_name: str, overrides: dict | None = None,
|
||||
) -> SeederParams | None:
|
||||
"""Look up preset by name and apply overrides."""
|
||||
if preset_name not in PRESETS:
|
||||
raise ValueError(
|
||||
f"Unknown seeder preset '{preset_name}'. "
|
||||
f"Available: {list(PRESETS.keys())}"
|
||||
)
|
||||
params = PRESETS[preset_name]
|
||||
if params is None or not overrides:
|
||||
return params
|
||||
return replace(params, **{k: v for k, v in overrides.items() if hasattr(params, k)})
|
||||
|
||||
|
||||
def seed_layout(
|
||||
devices: list[Device],
|
||||
lab: Lab,
|
||||
params: SeederParams | None,
|
||||
edges: list[list[str]] | None = None,
|
||||
) -> list[Placement]:
|
||||
"""Generate initial device placements using force-directed simulation.
|
||||
|
||||
Args:
|
||||
devices: devices to place
|
||||
lab: lab dimensions
|
||||
params: seeder parameters (None = row_fallback)
|
||||
edges: workflow edges as [device_a_id, device_b_id] pairs (Stage 2)
|
||||
|
||||
Returns:
|
||||
list of Placement objects, one per device
|
||||
"""
|
||||
if not devices:
|
||||
return []
|
||||
|
||||
if params is None:
|
||||
from .pencil_integration import generate_fallback
|
||||
return generate_fallback(devices, lab)
|
||||
|
||||
return _force_simulation(devices, lab, params, edges)
|
||||
|
||||
|
||||
def _force_simulation(
|
||||
devices: list[Device],
|
||||
lab: Lab,
|
||||
params: SeederParams,
|
||||
edges: list[list[str]] | None = None,
|
||||
max_iter: int = 80,
|
||||
dt: float = 0.05,
|
||||
damping: float = 0.8,
|
||||
) -> list[Placement]:
|
||||
"""Run force-directed simulation to produce initial placements."""
|
||||
n = len(devices)
|
||||
center_x, center_y = lab.width / 2, lab.depth / 2
|
||||
|
||||
# Initialize positions: grid layout within lab bounds
|
||||
cols = max(1, int(math.ceil(math.sqrt(n))))
|
||||
rows_count = max(1, math.ceil(n / cols))
|
||||
positions = [] # (x, y) per device
|
||||
for i, dev in enumerate(devices):
|
||||
row, col = divmod(i, cols)
|
||||
margin = 0.3
|
||||
x = margin + (col + 0.5) * (lab.width - 2 * margin) / cols
|
||||
y = margin + (row + 0.5) * (lab.depth - 2 * margin) / rows_count
|
||||
x = min(max(x, dev.bbox[0] / 2), lab.width - dev.bbox[0] / 2)
|
||||
y = min(max(y, dev.bbox[1] / 2), lab.depth - dev.bbox[1] / 2)
|
||||
positions.append([x, y])
|
||||
|
||||
# Initialize orientations
|
||||
thetas = [0.0] * n
|
||||
|
||||
# Build edge lookup for Stage 2
|
||||
edge_set: set[tuple[int, int]] = set()
|
||||
if edges and params.edge_attraction > 0:
|
||||
id_to_idx = {d.id: i for i, d in enumerate(devices)}
|
||||
for e in edges:
|
||||
if len(e) == 2 and e[0] in id_to_idx and e[1] in id_to_idx:
|
||||
edge_set.add((id_to_idx[e[0]], id_to_idx[e[1]]))
|
||||
|
||||
converged = False
|
||||
for iteration in range(max_iter):
|
||||
forces = [[0.0, 0.0] for _ in range(n)]
|
||||
total_force = 0.0
|
||||
|
||||
# 1. Boundary force
|
||||
for i in range(n):
|
||||
dx = positions[i][0] - center_x
|
||||
dy = positions[i][1] - center_y
|
||||
dist_to_center = math.sqrt(dx * dx + dy * dy) + 1e-9
|
||||
f = params.boundary_attraction
|
||||
forces[i][0] += f * dx / dist_to_center
|
||||
forces[i][1] += f * dy / dist_to_center
|
||||
|
||||
# 2. Mutual repulsion (OBB edge-to-edge)
|
||||
for i in range(n):
|
||||
for j in range(i + 1, n):
|
||||
ci = obb_corners(
|
||||
positions[i][0], positions[i][1],
|
||||
devices[i].bbox[0], devices[i].bbox[1], thetas[i],
|
||||
)
|
||||
cj = obb_corners(
|
||||
positions[j][0], positions[j][1],
|
||||
devices[j].bbox[0], devices[j].bbox[1], thetas[j],
|
||||
)
|
||||
dist = obb_min_distance(ci, cj)
|
||||
if dist < 1e-9:
|
||||
dist = 0.01 # Prevent division by zero for overlapping
|
||||
dx = positions[i][0] - positions[j][0]
|
||||
dy = positions[i][1] - positions[j][1]
|
||||
d_center = math.sqrt(dx * dx + dy * dy) + 1e-9
|
||||
repulsion = params.mutual_repulsion / (dist * dist + 0.1)
|
||||
fx = repulsion * dx / d_center
|
||||
fy = repulsion * dy / d_center
|
||||
forces[i][0] += fx
|
||||
forces[i][1] += fy
|
||||
forces[j][0] -= fx
|
||||
forces[j][1] -= fy
|
||||
|
||||
# 3. Edge attraction (Stage 2)
|
||||
if params.edge_attraction > 0:
|
||||
for i_idx, j_idx in edge_set:
|
||||
dx = positions[j_idx][0] - positions[i_idx][0]
|
||||
dy = positions[j_idx][1] - positions[i_idx][1]
|
||||
dist = math.sqrt(dx * dx + dy * dy) + 1e-9
|
||||
f = params.edge_attraction * dist * 0.1
|
||||
forces[i_idx][0] += f * dx / dist
|
||||
forces[i_idx][1] += f * dy / dist
|
||||
forces[j_idx][0] -= f * dx / dist
|
||||
forces[j_idx][1] -= f * dy / dist
|
||||
|
||||
# 4. Update positions (Euler + damping)
|
||||
for i in range(n):
|
||||
positions[i][0] += forces[i][0] * dt * damping
|
||||
positions[i][1] += forces[i][1] * dt * damping
|
||||
total_force += math.sqrt(forces[i][0]**2 + forces[i][1]**2)
|
||||
|
||||
# 5. Update orientations
|
||||
if params.orientation_mode != "none":
|
||||
for i in range(n):
|
||||
thetas[i] = _compute_orientation(
|
||||
positions[i][0], positions[i][1],
|
||||
center_x, center_y,
|
||||
devices[i], params.orientation_mode,
|
||||
)
|
||||
|
||||
# 6. Clamp to lab bounds
|
||||
for i in range(n):
|
||||
hw, hh = devices[i].bbox[0] / 2, devices[i].bbox[1] / 2
|
||||
positions[i][0] = max(hw, min(lab.width - hw, positions[i][0]))
|
||||
positions[i][1] = max(hh, min(lab.depth - hh, positions[i][1]))
|
||||
|
||||
if total_force < 0.01 * n:
|
||||
converged = True
|
||||
logger.info("Force simulation converged at iteration %d", iteration)
|
||||
break
|
||||
|
||||
if not converged:
|
||||
logger.info("Force simulation reached max iterations (%d)", max_iter)
|
||||
|
||||
placements = [
|
||||
Placement(device_id=devices[i].id, x=positions[i][0], y=positions[i][1], theta=thetas[i])
|
||||
for i in range(n)
|
||||
]
|
||||
|
||||
# Log initial collision count
|
||||
initial_collisions = _count_collisions(devices, placements)
|
||||
logger.info("Seeder: %d initial collision pairs before resolution", initial_collisions)
|
||||
|
||||
# Collision resolution pass
|
||||
placements = _resolve_collisions(devices, placements, lab, max_passes=5)
|
||||
|
||||
# Log diagnostics
|
||||
final_collisions = _count_collisions(devices, placements)
|
||||
no_openings = sum(1 for d in devices if not d.openings)
|
||||
logger.info(
|
||||
"Seeder complete: %d devices, %d without openings, %d collision pairs remaining",
|
||||
n, no_openings, final_collisions,
|
||||
)
|
||||
|
||||
return placements
|
||||
|
||||
|
||||
def _compute_orientation(
|
||||
x: float, y: float,
|
||||
center_x: float, center_y: float,
|
||||
device: Device,
|
||||
mode: str,
|
||||
) -> float:
|
||||
"""Compute theta so the device's front faces outward or inward."""
|
||||
dx = x - center_x
|
||||
dy = y - center_y
|
||||
if abs(dx) < 1e-9 and abs(dy) < 1e-9:
|
||||
return 0.0
|
||||
|
||||
angle_to_device = math.atan2(dy, dx)
|
||||
|
||||
if device.openings:
|
||||
front = device.openings[0].direction
|
||||
else:
|
||||
front = (0.0, -1.0) # Default: -Y is front
|
||||
|
||||
front_angle = math.atan2(front[1], front[0])
|
||||
|
||||
if mode == "outward":
|
||||
target = angle_to_device
|
||||
elif mode == "inward":
|
||||
target = angle_to_device + math.pi
|
||||
else:
|
||||
return 0.0
|
||||
|
||||
return (target - front_angle) % (2 * math.pi)
|
||||
|
||||
|
||||
def _count_collisions(devices: list[Device], placements: list[Placement]) -> int:
|
||||
"""Count OBB collision pairs (for diagnostics logging)."""
|
||||
n = len(devices)
|
||||
count = 0
|
||||
for i in range(n):
|
||||
for j in range(i + 1, n):
|
||||
ci = obb_corners(placements[i].x, placements[i].y,
|
||||
devices[i].bbox[0], devices[i].bbox[1], placements[i].theta)
|
||||
cj = obb_corners(placements[j].x, placements[j].y,
|
||||
devices[j].bbox[0], devices[j].bbox[1], placements[j].theta)
|
||||
if obb_overlap(ci, cj):
|
||||
count += 1
|
||||
return count
|
||||
|
||||
|
||||
def _resolve_collisions(
|
||||
devices: list[Device],
|
||||
placements: list[Placement],
|
||||
lab: Lab,
|
||||
max_passes: int = 5,
|
||||
) -> list[Placement]:
|
||||
"""Push overlapping devices apart. Returns new placement list."""
|
||||
positions = [[p.x, p.y] for p in placements]
|
||||
thetas = [p.theta for p in placements]
|
||||
n = len(devices)
|
||||
|
||||
for pass_num in range(max_passes):
|
||||
has_collision = False
|
||||
for i in range(n):
|
||||
for j in range(i + 1, n):
|
||||
ci = obb_corners(
|
||||
positions[i][0], positions[i][1],
|
||||
devices[i].bbox[0], devices[i].bbox[1], thetas[i],
|
||||
)
|
||||
cj = obb_corners(
|
||||
positions[j][0], positions[j][1],
|
||||
devices[j].bbox[0], devices[j].bbox[1], thetas[j],
|
||||
)
|
||||
if obb_overlap(ci, cj):
|
||||
has_collision = True
|
||||
dx = positions[i][0] - positions[j][0]
|
||||
dy = positions[i][1] - positions[j][1]
|
||||
dist = math.sqrt(dx * dx + dy * dy) + 1e-9
|
||||
push = 0.5 * (
|
||||
max(devices[i].bbox[0], devices[i].bbox[1])
|
||||
+ max(devices[j].bbox[0], devices[j].bbox[1])
|
||||
) / 4
|
||||
positions[i][0] += push * dx / dist
|
||||
positions[i][1] += push * dy / dist
|
||||
positions[j][0] -= push * dx / dist
|
||||
positions[j][1] -= push * dy / dist
|
||||
|
||||
# Clamp to bounds (rotation-aware AABB half-extents)
|
||||
for i in range(n):
|
||||
cos_t = abs(math.cos(thetas[i]))
|
||||
sin_t = abs(math.sin(thetas[i]))
|
||||
hw = (devices[i].bbox[0] * cos_t + devices[i].bbox[1] * sin_t) / 2
|
||||
hh = (devices[i].bbox[0] * sin_t + devices[i].bbox[1] * cos_t) / 2
|
||||
positions[i][0] = max(hw, min(lab.width - hw, positions[i][0]))
|
||||
positions[i][1] = max(hh, min(lab.depth - hh, positions[i][1]))
|
||||
|
||||
if not has_collision:
|
||||
logger.info("Collision resolution complete after %d passes", pass_num + 1)
|
||||
break
|
||||
else:
|
||||
logger.warning(
|
||||
"Collision resolution: %d passes exhausted, collisions may remain",
|
||||
max_passes,
|
||||
)
|
||||
|
||||
return [
|
||||
Placement(device_id=placements[i].device_id,
|
||||
x=positions[i][0], y=positions[i][1],
|
||||
theta=thetas[i], uuid=placements[i].uuid)
|
||||
for i in range(n)
|
||||
]
|
||||
@@ -1,742 +0,0 @@
|
||||
"""FastAPI 开发服务器。
|
||||
|
||||
开发阶段独立运行于 localhost:8000，前端通过 CORS 调用。
|
||||
集成阶段合并到 Uni-Lab-OS 的 FastAPI 服务中。
|
||||
|
||||
运行方式：
|
||||
uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
|
||||
|
||||
调试模式（启用 DEBUG 日志，含优化器逐代 cost 明细）：
|
||||
LAYOUT_DEBUG=1 uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
|
||||
|
||||
日志文件：
|
||||
自动写入 layout_optimizer/logs/{YYYYMMDD_HHMMSS}.log（始终 DEBUG 级别）。
|
||||
前端 1s 轮询的 GET /scene/placements 200 行不写入日志文件。
|
||||
|
||||
前端访问：
|
||||
http://localhost:8000/
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from collections import defaultdict
|
||||
import itertools
|
||||
import logging
|
||||
import logging.handlers
|
||||
import math
|
||||
import os
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
from fastapi import FastAPI
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import FileResponse, RedirectResponse
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
from pydantic import BaseModel
|
||||
|
||||
from .constraints import DEFAULT_WEIGHT_ANGLE # noqa: F401 — kept for external use
|
||||
from .device_catalog import (
|
||||
create_devices_from_list,
|
||||
load_devices_from_assets,
|
||||
load_devices_from_registry,
|
||||
load_footprints,
|
||||
merge_device_lists,
|
||||
)
|
||||
from .lab_parser import parse_lab
|
||||
from .intent_interpreter import InterpretResult, interpret_intents
|
||||
from .models import Constraint, Intent
|
||||
from .optimizer import optimize
|
||||
|
||||
_console_level = logging.DEBUG if os.getenv("LAYOUT_DEBUG") else logging.INFO
|
||||
# root logger must be DEBUG so the file handler receives all records;
|
||||
# console output level is controlled separately via its handler.
|
||||
logging.basicConfig(level=logging.DEBUG)
|
||||
# basicConfig creates a default StreamHandler — set its level to the console level
|
||||
for _h in logging.getLogger().handlers:
|
||||
if isinstance(_h, logging.StreamHandler):
|
||||
_h.setLevel(_console_level)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# --- 文件日志：实时写入 logs/ 目录，按启动时间命名 ---
|
||||
_LOG_DIR = Path(__file__).parent / "logs"
|
||||
_LOG_DIR.mkdir(exist_ok=True)
|
||||
_log_file = _LOG_DIR / f"{datetime.now():%Y%m%d_%H%M%S}.log"
|
||||
|
||||
|
||||
class _PollingFilter(logging.Filter):
|
||||
"""过滤掉前端 1s 轮询产生的 GET /scene/placements 日志行。"""
|
||||
|
||||
def filter(self, record: logging.LogRecord) -> bool:
|
||||
msg = record.getMessage()
|
||||
if "GET /scene/placements" in msg and "200" in msg:
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
_file_handler = logging.FileHandler(_log_file, encoding="utf-8")
|
||||
_file_handler.setLevel(logging.DEBUG)
|
||||
_file_handler.setFormatter(
|
||||
logging.Formatter("%(asctime)s %(levelname)-5s [%(name)s] %(message)s")
|
||||
)
|
||||
_file_handler.addFilter(_PollingFilter())
|
||||
logging.getLogger().addHandler(_file_handler)
|
||||
|
||||
STATIC_DIR = Path(__file__).parent / "static"
|
||||
|
||||
# 可配置路径
|
||||
# __file__ -> Uni-Lab-OS/unilabos/layout_optimizer/server.py
|
||||
_UNILABOS_DIR = Path(__file__).resolve().parent.parent # .../Uni-Lab-OS/unilabos/
|
||||
|
||||
UNI_LAB_ASSETS_DIR = Path(
|
||||
os.getenv("UNI_LAB_ASSETS_DIR", str(_UNILABOS_DIR.parent.parent.parent / "uni-lab-assets"))
|
||||
)
|
||||
UNI_LAB_ASSETS_MODELS_DIR = UNI_LAB_ASSETS_DIR / "device_models"
|
||||
UNI_LAB_ASSETS_DATA_JSON = UNI_LAB_ASSETS_DIR / "data.json"
|
||||
UNI_LAB_OS_DEVICE_MESH_DIR = Path(
|
||||
os.getenv(
|
||||
"UNI_LAB_OS_DEVICE_MESH_DIR",
|
||||
str(_UNILABOS_DIR / "device_mesh" / "devices"),
|
||||
)
|
||||
)
|
||||
|
||||
app = FastAPI(title="Layout Optimizer", version="0.2.0")
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"], # 开发阶段允许所有来源
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
# 挂载静态文件目录
|
||||
app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static")
|
||||
|
||||
# 挂载 3D 模型和缩略图
|
||||
if UNI_LAB_ASSETS_MODELS_DIR.exists():
|
||||
app.mount("/models", StaticFiles(directory=str(UNI_LAB_ASSETS_MODELS_DIR)), name="models")
|
||||
logger.info("Mounted /models from %s", UNI_LAB_ASSETS_MODELS_DIR)
|
||||
else:
|
||||
logger.warning("uni-lab-assets models dir not found: %s", UNI_LAB_ASSETS_MODELS_DIR)
|
||||
|
||||
|
||||
# ---------- 设备目录缓存 ----------
|
||||
|
||||
_device_cache: list[dict] | None = None
|
||||
_DEVICE_PARAM_KEYS = {"device_a", "device_b", "arm_id", "target_device_id", "device"}
|
||||
|
||||
|
||||
# 消耗品/配件关键词（不独立放置于实验台）
|
||||
_CONSUMABLE_KEYWORDS = {
|
||||
"plate", "well", "tube", "tip", "reservoir", "carrier", "nest",
|
||||
"adapter", "trough", "magnet_module", "magnet_plate", "rack", "lid",
|
||||
"seal", "cap", "vial", "flask", "dish", "block", "strip", "insert",
|
||||
"gasket", "pad", "grid_segment", "spacer", "diti_tray",
|
||||
}
|
||||
# 但包含这些关键词的是独立设备，不是消耗品
|
||||
_DEVICE_KEYWORDS = {
|
||||
"reader", "handler", "hotel", "washer", "stacker", "sealer", "labeler",
|
||||
"centrifuge", "incubator", "shaker", "robot", "arm", "flex", "dispenser",
|
||||
"printer", "scanner", "analyzer", "fluorometer", "spectrophotometer",
|
||||
"thermocycler", "module",
|
||||
}
|
||||
|
||||
|
||||
def _is_standalone_device(device_id: str, bbox: tuple[float, float]) -> bool:
|
||||
"""判断设备是否独立放置于实验台（非消耗品/配件）。"""
|
||||
mx = max(bbox[0], bbox[1])
|
||||
mn = min(bbox[0], bbox[1])
|
||||
if mx >= 0.30:
|
||||
return True # 大于 30cm 一定是独立设备
|
||||
if mx < 0.05:
|
||||
return False # 小于 5cm 一定是消耗品
|
||||
lower = device_id.lower()
|
||||
# 非常扁平（一维 < 3cm）的几乎都是配件/载具，即使名称匹配设备关键词
|
||||
if mn < 0.03:
|
||||
return False
|
||||
# 先检查消耗品关键词（如果匹配，再看是否有设备关键词覆盖）
|
||||
is_consumable_name = any(kw in lower for kw in _CONSUMABLE_KEYWORDS)
|
||||
is_device_name = any(kw in lower for kw in _DEVICE_KEYWORDS)
|
||||
if is_consumable_name and not is_device_name:
|
||||
return False
|
||||
if is_device_name:
|
||||
return True
|
||||
# 默认：>= 15cm 视为设备
|
||||
return mx >= 0.15
|
||||
|
||||
|
||||
def _build_device_list() -> list[dict]:
|
||||
"""构建合并后的设备列表（缓存）。"""
|
||||
global _device_cache
|
||||
if _device_cache is not None:
|
||||
return _device_cache
|
||||
|
||||
footprints = load_footprints()
|
||||
|
||||
registry = load_devices_from_registry(UNI_LAB_OS_DEVICE_MESH_DIR, footprints)
|
||||
assets = load_devices_from_assets(UNI_LAB_ASSETS_DATA_JSON, footprints)
|
||||
|
||||
merged = merge_device_lists(registry, assets)
|
||||
|
||||
_device_cache = [
|
||||
{
|
||||
"id": d.id,
|
||||
"name": d.name,
|
||||
"device_type": d.device_type,
|
||||
"source": d.source,
|
||||
"bbox": list(d.bbox),
|
||||
"height": d.height,
|
||||
"origin_offset": list(d.origin_offset),
|
||||
"openings": [
|
||||
{"direction": list(o.direction), "label": o.label}
|
||||
for o in d.openings
|
||||
],
|
||||
"model_path": d.model_path,
|
||||
"model_type": d.model_type,
|
||||
"thumbnail_url": d.thumbnail_url,
|
||||
"is_standalone": _is_standalone_device(d.id, d.bbox),
|
||||
}
|
||||
for d in merged
|
||||
]
|
||||
standalone = sum(1 for d in _device_cache if d["is_standalone"])
|
||||
logger.info("Built device catalog: %d devices (%d standalone)", len(_device_cache), standalone)
|
||||
return _device_cache
|
||||
|
||||
|
||||
def _catalog_id_from_internal(device_id: str) -> str:
|
||||
"""内部实例 ID → catalog ID。"""
|
||||
return device_id.split("#", 1)[0]
|
||||
|
||||
|
||||
def _expand_constraints_for_duplicates(
|
||||
constraints: list[Constraint], devices: list,
|
||||
) -> list[Constraint]:
|
||||
"""将引用 bare catalog ID 的约束扩展到所有重复实例。"""
|
||||
catalog_instances: dict[str, list[str]] = defaultdict(list)
|
||||
for dev in devices:
|
||||
catalog_instances[_catalog_id_from_internal(dev.id)].append(dev.id)
|
||||
|
||||
expanded_constraints: list[Constraint] = []
|
||||
for constraint in constraints:
|
||||
fan_out_keys: list[str] = []
|
||||
fan_out_values: list[list[str]] = []
|
||||
|
||||
for key in _DEVICE_PARAM_KEYS:
|
||||
if key not in constraint.params:
|
||||
continue
|
||||
ref_id = constraint.params[key]
|
||||
if "#" in ref_id:
|
||||
continue
|
||||
instances = catalog_instances.get(ref_id, [])
|
||||
if len(instances) > 1:
|
||||
fan_out_keys.append(key)
|
||||
fan_out_values.append(instances)
|
||||
logger.info(
|
||||
"Fan-out: %s %s=%s -> %d instances",
|
||||
constraint.rule_name, key, ref_id, len(instances),
|
||||
)
|
||||
|
||||
if not fan_out_keys:
|
||||
expanded_constraints.append(constraint)
|
||||
continue
|
||||
|
||||
for combo in itertools.product(*fan_out_values):
|
||||
new_params = dict(constraint.params)
|
||||
for key, internal_id in zip(fan_out_keys, combo):
|
||||
new_params[key] = internal_id
|
||||
expanded_constraints.append(
|
||||
Constraint(
|
||||
type=constraint.type,
|
||||
rule_name=constraint.rule_name,
|
||||
params=new_params,
|
||||
weight=constraint.weight,
|
||||
)
|
||||
)
|
||||
|
||||
return expanded_constraints
|
||||
|
||||
|
||||
def _maybe_add_prefer_aligned_constraint(
|
||||
constraints: list[Constraint], align_weight: float,
|
||||
) -> list[Constraint]:
|
||||
"""仅在用户未显式提供 prefer_aligned 时注入对齐约束。"""
|
||||
if align_weight <= 0:
|
||||
return constraints
|
||||
|
||||
if any(c.rule_name == "prefer_aligned" for c in constraints):
|
||||
logger.info("Skipping auto-injected prefer_aligned because one already exists")
|
||||
return constraints
|
||||
|
||||
constraints.append(
|
||||
Constraint(
|
||||
type="soft",
|
||||
rule_name="prefer_aligned",
|
||||
weight=align_weight,
|
||||
)
|
||||
)
|
||||
return constraints
|
||||
|
||||
|
||||
# ---------- 路由 ----------
|
||||
|
||||
|
||||
@app.get("/", include_in_schema=False)
|
||||
async def root():
|
||||
return RedirectResponse(url="/lab3d")
|
||||
|
||||
|
||||
@app.get("/lab3d", include_in_schema=False)
|
||||
async def lab3d_ui():
|
||||
return FileResponse(STATIC_DIR / "lab3d.html")
|
||||
|
||||
|
||||
@app.get("/devices")
|
||||
async def list_devices(source: str = "all"):
|
||||
"""返回合并后的设备目录。?source=registry|assets|all"""
|
||||
devices = _build_device_list()
|
||||
if source != "all":
|
||||
devices = [d for d in devices if d["source"] == source]
|
||||
return devices
|
||||
|
||||
|
||||
@app.get("/health")
|
||||
async def health():
|
||||
return {"status": "ok"}
|
||||
|
||||
|
||||
# ---------- 意图解释 API ----------
|
||||
|
||||
|
||||
class IntentSpec(BaseModel):
|
||||
intent: str
|
||||
params: dict = {}
|
||||
description: str = ""
|
||||
|
||||
|
||||
class TranslationEntry(BaseModel):
|
||||
source_intent: str
|
||||
source_description: str
|
||||
source_params: dict
|
||||
generated_constraints: list[dict]
|
||||
explanation: str
|
||||
confidence: str = "high"
|
||||
|
||||
|
||||
class InterpretRequest(BaseModel):
|
||||
intents: list[IntentSpec]
|
||||
|
||||
|
||||
class InterpretResponse(BaseModel):
|
||||
constraints: list[dict]
|
||||
translations: list[TranslationEntry]
|
||||
workflow_edges: list[list[str]]
|
||||
errors: list[str]
|
||||
|
||||
|
||||
@app.post("/interpret", response_model=InterpretResponse)
|
||||
async def run_interpret(request: InterpretRequest):
|
||||
"""将语义化意图翻译为约束列表，供用户确认后传入 /optimize。"""
|
||||
logger.info("Interpret request: %d intents", len(request.intents))
|
||||
|
||||
intents = [
|
||||
Intent(
|
||||
intent=i.intent,
|
||||
params=i.params,
|
||||
description=i.description,
|
||||
)
|
||||
for i in request.intents
|
||||
]
|
||||
|
||||
result: InterpretResult = interpret_intents(intents)
|
||||
|
||||
return InterpretResponse(
|
||||
constraints=[
|
||||
{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}
|
||||
for c in result.constraints
|
||||
],
|
||||
translations=[
|
||||
TranslationEntry(
|
||||
source_intent=t["source_intent"],
|
||||
source_description=t.get("source_description", ""),
|
||||
source_params=t.get("source_params", {}),
|
||||
generated_constraints=t["generated_constraints"],
|
||||
explanation=t["explanation"],
|
||||
confidence=t.get("confidence", "high"),
|
||||
)
|
||||
for t in result.translations
|
||||
],
|
||||
workflow_edges=result.workflow_edges,
|
||||
errors=result.errors,
|
||||
)
|
||||
|
||||
|
||||
@app.get("/interpret/schema")
|
||||
async def interpret_schema():
|
||||
"""返回可用意图类型及其参数规范，供 LLM agent 发现和使用。"""
|
||||
return {
|
||||
"description": "Layout optimizer intent schema. LLM agents should translate user requests into these intents.",
|
||||
"intents": {
|
||||
"reachable_by": {
|
||||
"description": "Robot arm must be able to reach all target devices",
|
||||
"params": {
|
||||
"arm": {"type": "string", "required": True, "description": "Device ID of robot arm"},
|
||||
"targets": {"type": "list[string]", "required": True, "description": "Device IDs the arm must reach"},
|
||||
},
|
||||
"generates": "hard reachability constraint per target",
|
||||
},
|
||||
"close_together": {
|
||||
"description": "Group of devices should be placed near each other",
|
||||
"params": {
|
||||
"devices": {"type": "list[string]", "required": True, "description": "Device IDs (min 2)"},
|
||||
"priority": {"type": "string", "required": False, "default": "medium", "enum": ["low", "medium", "high"]},
|
||||
},
|
||||
"generates": "soft minimize_distance for each pair",
|
||||
},
|
||||
"far_apart": {
|
||||
"description": "Devices should be placed far from each other",
|
||||
"params": {
|
||||
"devices": {"type": "list[string]", "required": True, "description": "Device IDs (min 2)"},
|
||||
"priority": {"type": "string", "required": False, "default": "medium", "enum": ["low", "medium", "high"]},
|
||||
},
|
||||
"generates": "soft maximize_distance for each pair",
|
||||
},
|
||||
"keep_adjacent": {
|
||||
"description": "Devices should stay adjacent, similar to close_together",
|
||||
"params": {
|
||||
"devices": {"type": "list[string]", "required": True, "description": "Device IDs (min 2)"},
|
||||
"priority": {"type": "string", "required": False, "default": "medium", "enum": ["low", "medium", "high"]},
|
||||
},
|
||||
"generates": "soft minimize_distance for each pair",
|
||||
},
|
||||
"max_distance": {
|
||||
"description": "Two devices must be within a maximum distance",
|
||||
"params": {
|
||||
"device_a": {"type": "string", "required": True},
|
||||
"device_b": {"type": "string", "required": True},
|
||||
"distance": {"type": "float", "required": True, "description": "Max edge-to-edge distance in meters"},
|
||||
},
|
||||
"generates": "hard distance_less_than",
|
||||
},
|
||||
"min_distance": {
|
||||
"description": "Two devices must be at least a minimum distance apart",
|
||||
"params": {
|
||||
"device_a": {"type": "string", "required": True},
|
||||
"device_b": {"type": "string", "required": True},
|
||||
"distance": {"type": "float", "required": True, "description": "Min edge-to-edge distance in meters"},
|
||||
},
|
||||
"generates": "hard distance_greater_than",
|
||||
},
|
||||
"min_spacing": {
|
||||
"description": "Minimum gap between all device pairs",
|
||||
"params": {
|
||||
"min_gap": {"type": "float", "required": False, "default": 0.3, "description": "Minimum gap in meters"},
|
||||
},
|
||||
"generates": "hard min_spacing",
|
||||
},
|
||||
"workflow_hint": {
|
||||
"description": "Workflow step order — consecutive devices should be near each other",
|
||||
"params": {
|
||||
"workflow": {"type": "string", "required": False, "description": "Workflow name (e.g. 'pcr')"},
|
||||
"devices": {"type": "list[string]", "required": True, "description": "Ordered device IDs following workflow steps"},
|
||||
},
|
||||
"generates": "soft minimize_distance for consecutive pairs + workflow_edges",
|
||||
},
|
||||
"face_outward": {
|
||||
"description": "Devices should face outward from lab center",
|
||||
"params": {},
|
||||
"generates": "soft prefer_orientation_mode outward",
|
||||
},
|
||||
"face_inward": {
|
||||
"description": "Devices should face inward toward lab center",
|
||||
"params": {},
|
||||
"generates": "soft prefer_orientation_mode inward",
|
||||
},
|
||||
"align_cardinal": {
|
||||
"description": "Devices should align to cardinal directions (0/90/180/270 degrees)",
|
||||
"params": {},
|
||||
"generates": "soft prefer_aligned",
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# ---------- 优化 API ----------
|
||||
|
||||
|
||||
class DeviceSpec(BaseModel):
|
||||
id: str
|
||||
name: str = ""
|
||||
size: list[float] | None = None
|
||||
device_type: str = "static"
|
||||
uuid: str = ""
|
||||
|
||||
|
||||
class ConstraintSpec(BaseModel):
|
||||
type: str # "hard" or "soft"
|
||||
rule_name: str
|
||||
params: dict = {}
|
||||
weight: float = 1.0
|
||||
|
||||
|
||||
class LabSpec(BaseModel):
|
||||
width: float
|
||||
depth: float
|
||||
obstacles: list[dict] = []
|
||||
|
||||
|
||||
class OptimizeRequest(BaseModel):
|
||||
devices: list[DeviceSpec]
|
||||
lab: LabSpec
|
||||
constraints: list[ConstraintSpec] = []
|
||||
seeder: str = "compact_outward"
|
||||
seeder_overrides: dict = {}
|
||||
run_de: bool = True
|
||||
workflow_edges: list[list[str]] = []
|
||||
maxiter: int = 200
|
||||
seed: int | None = None
|
||||
snap_cardinal: bool = False
|
||||
angle_granularity: int | None = None
|
||||
arm_reach: dict[str, float] = {}
|
||||
# DE 超参数
|
||||
strategy: str = "currenttobest1bin"
|
||||
angle_mode: str = "joint"
|
||||
mutation: list[float] = [0.5, 1.0]
|
||||
theta_mutation: list[float] | None = None
|
||||
recombination: float = 0.7
|
||||
crossover_mode: str = "device"
|
||||
|
||||
|
||||
class PositionXYZ(BaseModel):
|
||||
x: float
|
||||
y: float
|
||||
z: float
|
||||
|
||||
|
||||
class PlacementResult(BaseModel):
|
||||
device_id: str
|
||||
uuid: str
|
||||
position: PositionXYZ
|
||||
rotation: PositionXYZ
|
||||
|
||||
|
||||
class OptimizeResponse(BaseModel):
|
||||
placements: list[PlacementResult]
|
||||
cost: float
|
||||
success: bool
|
||||
seeder_used: str = ""
|
||||
de_ran: bool = True
|
||||
|
||||
|
||||
@app.post("/optimize", response_model=OptimizeResponse)
|
||||
async def run_optimize(request: OptimizeRequest):
|
||||
"""接收设备列表+约束，返回最优布局方案。"""
|
||||
from fastapi import HTTPException
|
||||
|
||||
from .constraints import evaluate_default_hard_constraints, evaluate_constraints
|
||||
from .mock_checkers import MockCollisionChecker, MockReachabilityChecker
|
||||
from .optimizer import optimize, snap_theta, snap_theta_safe
|
||||
from .seeders import resolve_seeder_params, seed_layout
|
||||
|
||||
logger.info(
|
||||
"Optimize request: %d devices, lab %.1f×%.1f, %d constraints, seeder=%s, run_de=%s, angle_granularity=%s",
|
||||
len(request.devices),
|
||||
request.lab.width,
|
||||
request.lab.depth,
|
||||
len(request.constraints),
|
||||
request.seeder,
|
||||
request.run_de,
|
||||
request.angle_granularity,
|
||||
)
|
||||
|
||||
if request.angle_granularity not in (None, 4, 8, 12, 24):
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="angle_granularity must be one of: 4, 8, 12, 24",
|
||||
)
|
||||
|
||||
# 转换输入
|
||||
devices = create_devices_from_list(
|
||||
[d.model_dump() for d in request.devices]
|
||||
)
|
||||
id_to_catalog = {dev.id: _catalog_id_from_internal(dev.id) for dev in devices}
|
||||
id_to_uuid = {dev.id: (dev.uuid or dev.id) for dev in devices}
|
||||
lab = parse_lab(request.lab.model_dump())
|
||||
constraints = [
|
||||
Constraint(
|
||||
type=c.type,
|
||||
rule_name=c.rule_name,
|
||||
params=c.params,
|
||||
weight=c.weight,
|
||||
)
|
||||
for c in request.constraints
|
||||
]
|
||||
constraints = _expand_constraints_for_duplicates(constraints, devices)
|
||||
|
||||
# 1. Resolve seeder
|
||||
try:
|
||||
params = resolve_seeder_params(request.seeder, request.seeder_overrides or None)
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
|
||||
# 2. Seed
|
||||
seed_placements = seed_layout(
|
||||
devices, lab, params,
|
||||
request.workflow_edges or None,
|
||||
)
|
||||
|
||||
# 3. Auto-inject alignment soft constraint (opt-in via seeder_overrides)
|
||||
if request.run_de and seed_placements:
|
||||
# prefer_aligned: penalize non-cardinal angles（默认关闭，用户可通过 align_cardinal intent 或 seeder_overrides 开启）
|
||||
constraints = _maybe_add_prefer_aligned_constraint(
|
||||
constraints,
|
||||
request.seeder_overrides.get("align_weight", 0),
|
||||
)
|
||||
|
||||
# 4. Validate DE hyperparameters
|
||||
if request.strategy not in {"currenttobest1bin", "best1bin", "rand1bin"}:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"strategy must be one of: currenttobest1bin, best1bin, rand1bin (got {request.strategy!r})",
|
||||
)
|
||||
if request.angle_mode not in {"joint", "hybrid"}:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"angle_mode must be one of: joint, hybrid (got {request.angle_mode!r})",
|
||||
)
|
||||
if request.crossover_mode not in {"device", "dimension"}:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"crossover_mode must be one of: device, dimension (got {request.crossover_mode!r})",
|
||||
)
|
||||
if len(request.mutation) != 2 or request.mutation[0] > request.mutation[1]:
|
||||
raise HTTPException(status_code=400, detail="mutation must be [F_min, F_max] with F_min <= F_max")
|
||||
if request.mutation[0] < 0 or request.mutation[1] > 2.0:
|
||||
raise HTTPException(status_code=400, detail="mutation values must be in [0, 2.0]")
|
||||
if request.theta_mutation is not None:
|
||||
if len(request.theta_mutation) != 2 or request.theta_mutation[0] > request.theta_mutation[1]:
|
||||
raise HTTPException(status_code=400, detail="theta_mutation must be [F_min, F_max] with F_min <= F_max")
|
||||
if request.theta_mutation[0] < 0 or request.theta_mutation[1] > 2.0:
|
||||
raise HTTPException(status_code=400, detail="theta_mutation values must be in [0, 2.0]")
|
||||
if not (0 <= request.recombination <= 1.0):
|
||||
raise HTTPException(status_code=400, detail="recombination must be in [0, 1.0]")
|
||||
|
||||
# 5. Conditional Differential Evolution
|
||||
de_ran = False
|
||||
checker = MockCollisionChecker()
|
||||
reachability_checker = MockReachabilityChecker(request.arm_reach or None)
|
||||
if request.run_de:
|
||||
result_placements = optimize(
|
||||
devices=devices,
|
||||
lab=lab,
|
||||
constraints=constraints,
|
||||
collision_checker=checker,
|
||||
reachability_checker=reachability_checker,
|
||||
seed_placements=seed_placements,
|
||||
maxiter=request.maxiter,
|
||||
seed=request.seed,
|
||||
strategy=request.strategy,
|
||||
workflow_edges=request.workflow_edges or None,
|
||||
angle_granularity=request.angle_granularity,
|
||||
angle_mode=request.angle_mode,
|
||||
mutation=tuple(request.mutation),
|
||||
theta_mutation=tuple(request.theta_mutation) if request.theta_mutation else None,
|
||||
recombination=request.recombination,
|
||||
crossover_mode=request.crossover_mode,
|
||||
)
|
||||
de_ran = True
|
||||
else:
|
||||
result_placements = seed_placements
|
||||
|
||||
# 5. θ snap post-processing（opt-in，默认关闭）
|
||||
if request.snap_cardinal and request.angle_granularity is None:
|
||||
result_placements = snap_theta_safe(result_placements, devices, lab, checker)
|
||||
elif request.snap_cardinal and request.angle_granularity is not None:
|
||||
logger.info(
|
||||
"snap_cardinal ignored because angle_granularity=%s already constrains theta",
|
||||
request.angle_granularity,
|
||||
)
|
||||
|
||||
# 6. Evaluate final cost (binary mode for pass/fail reporting)
|
||||
final_cost = evaluate_default_hard_constraints(
|
||||
devices, result_placements, lab, checker, graduated=False,
|
||||
)
|
||||
# 也检查用户硬约束（binary 模式）
|
||||
if constraints and not math.isinf(final_cost):
|
||||
user_hard_cost = evaluate_constraints(
|
||||
devices, result_placements, lab, constraints, checker, reachability_checker,
|
||||
graduated=False,
|
||||
)
|
||||
if math.isinf(user_hard_cost):
|
||||
final_cost = math.inf
|
||||
|
||||
return OptimizeResponse(
|
||||
placements=[
|
||||
PlacementResult(
|
||||
device_id=id_to_catalog.get(p.device_id, p.device_id),
|
||||
uuid=id_to_uuid.get(p.device_id, p.device_id),
|
||||
position=PositionXYZ(x=round(p.x, 4), y=round(p.y, 4), z=0.0),
|
||||
rotation=PositionXYZ(x=0.0, y=0.0, z=round(p.theta, 4)),
|
||||
)
|
||||
for p in result_placements
|
||||
],
|
||||
cost=final_cost,
|
||||
success=not math.isinf(final_cost),
|
||||
seeder_used=request.seeder,
|
||||
de_ran=de_ran,
|
||||
)
|
||||
|
||||
|
||||
# ---------- 场景状态 API（演示用） ----------
|
||||
|
||||
|
||||
_scene_state: dict = {"version": 0, "placements": []}
|
||||
_lab_state: dict = {"width": 4.0, "depth": 4.0}
|
||||
|
||||
|
||||
class LabDimensions(BaseModel):
|
||||
width: float
|
||||
depth: float
|
||||
|
||||
|
||||
@app.get("/scene/lab")
|
||||
async def get_lab_dimensions():
|
||||
"""返回当前实验室尺寸（前端推送，agent 读取）。"""
|
||||
return _lab_state
|
||||
|
||||
|
||||
@app.post("/scene/lab")
|
||||
async def set_lab_dimensions(dims: LabDimensions):
|
||||
"""前端在加载和尺寸变更时推送。"""
|
||||
_lab_state["width"] = dims.width
|
||||
_lab_state["depth"] = dims.depth
|
||||
return _lab_state
|
||||
|
||||
|
||||
class ScenePlacementsRequest(BaseModel):
|
||||
placements: list[PlacementResult]
|
||||
|
||||
|
||||
@app.post("/scene/placements")
|
||||
async def set_scene_placements(request: ScenePlacementsRequest):
|
||||
"""Agent 写入布局结果，前端轮询读取。"""
|
||||
_scene_state["version"] += 1
|
||||
_scene_state["placements"] = [p.model_dump() for p in request.placements]
|
||||
logger.info(
|
||||
"Scene placements updated: version=%d, count=%d",
|
||||
_scene_state["version"],
|
||||
len(request.placements),
|
||||
)
|
||||
return {"version": _scene_state["version"], "count": len(request.placements)}
|
||||
|
||||
|
||||
@app.get("/scene/placements")
|
||||
async def get_scene_placements():
|
||||
"""前端轮询此端点，检测 version 变化后应用布局。"""
|
||||
return _scene_state
|
||||
|
||||
|
||||
@app.delete("/scene/placements")
|
||||
async def clear_scene_placements():
|
||||
"""重置场景状态（重录时使用）。"""
|
||||
_scene_state["version"] = 0
|
||||
_scene_state["placements"] = []
|
||||
return {"version": 0, "placements": []}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,7 +0,0 @@
|
||||
[
|
||||
{"id": "arm_1", "name": "Elite CS66 Arm", "size": [0.20, 0.20], "device_type": "articulation"},
|
||||
{"id": "liquid_handler", "name": "Agilent Bravo", "size": [0.80, 0.65], "device_type": "static"},
|
||||
{"id": "centrifuge", "name": "Centrifuge", "size": [0.50, 0.50], "device_type": "static"},
|
||||
{"id": "plate_hotel", "name": "Thermo Orbitor RS2", "size": [0.45, 0.55], "device_type": "static"},
|
||||
{"id": "hplc", "name": "HPLC Station", "size": [0.60, 0.50], "device_type": "static"}
|
||||
]
|
||||
@@ -1,7 +0,0 @@
|
||||
{
|
||||
"width": 5.0,
|
||||
"depth": 4.0,
|
||||
"obstacles": [
|
||||
{"x": 2.5, "y": 0.0, "width": 0.1, "depth": 0.5}
|
||||
]
|
||||
}
|
||||
@@ -1,241 +0,0 @@
|
||||
"""Tests for broad_phase.py — 2 轴 sweep-and-prune 宽相碰撞检测。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
import random
|
||||
|
||||
import pytest
|
||||
|
||||
from ..broad_phase import broad_phase_device_pairs, sweep_and_prune_pairs
|
||||
from ..models import Device, Placement
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 测试用辅助函数
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _make_device(device_id: str, w: float = 0.6, d: float = 0.4) -> Device:
|
||||
"""创建简单测试设备。"""
|
||||
return Device(id=device_id, name=device_id, bbox=(w, d))
|
||||
|
||||
|
||||
def _make_placement(
|
||||
device_id: str, x: float, y: float, theta: float = 0.0
|
||||
) -> Placement:
|
||||
"""创建简单测试放置。"""
|
||||
return Placement(device_id=device_id, x=x, y=y, theta=theta)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 测试类
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestNoOverlap:
|
||||
"""两台设备距离足够远，宽相不返回候选对。"""
|
||||
|
||||
def test_no_overlap_returns_empty(self):
|
||||
"""水平方向间距远大于 AABB 尺寸 → 0 候选对。"""
|
||||
devices = [_make_device("A", 1.0, 1.0), _make_device("B", 1.0, 1.0)]
|
||||
placements = [
|
||||
_make_placement("A", 0.0, 0.0),
|
||||
_make_placement("B", 10.0, 0.0),
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
assert pairs == []
|
||||
|
||||
|
||||
class TestOverlapping:
|
||||
"""两台设备 AABB 明显重叠。"""
|
||||
|
||||
def test_overlapping_devices_returned(self):
|
||||
"""两台 1×1 设备中心距 0.5m → 1 候选对。"""
|
||||
devices = [_make_device("A", 1.0, 1.0), _make_device("B", 1.0, 1.0)]
|
||||
placements = [
|
||||
_make_placement("A", 0.0, 0.0),
|
||||
_make_placement("B", 0.5, 0.0),
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
assert len(pairs) == 1
|
||||
assert pairs[0] == (0, 1)
|
||||
|
||||
|
||||
class TestXOverlapYNoOverlap:
|
||||
"""x 轴投影交叠但 y 轴不交叠，应被 y 轴检查剪枝。"""
|
||||
|
||||
def test_x_overlap_y_no_overlap(self):
|
||||
"""水平接近但垂直方向偏移足够大 → 0 候选对。"""
|
||||
devices = [_make_device("A", 2.0, 1.0), _make_device("B", 2.0, 1.0)]
|
||||
placements = [
|
||||
_make_placement("A", 0.0, 0.0),
|
||||
_make_placement("B", 0.5, 5.0), # x 轴交叠但 y 轴相距很远
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
assert pairs == []
|
||||
|
||||
|
||||
class TestTouchingDevices:
|
||||
"""AABB 恰好接触（边缘距离 = 0）应作为候选对返回。"""
|
||||
|
||||
def test_touching_devices_included(self):
|
||||
"""两个 1×1 设备中心距恰好为 1.0（半宽 0.5 + 0.5 = 1.0），
|
||||
AABB 边界接触 → 应包含在候选对中（<= 判定）。"""
|
||||
devices = [_make_device("A", 1.0, 1.0), _make_device("B", 1.0, 1.0)]
|
||||
placements = [
|
||||
_make_placement("A", 0.0, 0.0),
|
||||
_make_placement("B", 1.0, 0.0), # xmax_A = 0.5, xmin_B = 0.5 → 接触
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
# 接触算作潜在碰撞，安全起见需保留
|
||||
assert len(pairs) == 1
|
||||
assert pairs[0] == (0, 1)
|
||||
|
||||
|
||||
class TestMultipleDevices:
|
||||
"""4 台设备验证精确的候选对列表。"""
|
||||
|
||||
def test_multiple_devices_correct_pairs(self):
|
||||
"""排列 4 台设备，只有特定配对 AABB 交叠。
|
||||
|
||||
布局（1×1 设备）：
|
||||
A(0,0) B(0.8,0) — A-B 交叠（中心距 0.8 < 1.0）
|
||||
C(0,5) — 远离 A、B
|
||||
D(0.9,5) — C-D 交叠（中心距 0.9 < 1.0）
|
||||
|
||||
期望候选对: (A,B) 和 (C,D)。
|
||||
"""
|
||||
devices = [
|
||||
_make_device("A", 1.0, 1.0),
|
||||
_make_device("B", 1.0, 1.0),
|
||||
_make_device("C", 1.0, 1.0),
|
||||
_make_device("D", 1.0, 1.0),
|
||||
]
|
||||
placements = [
|
||||
_make_placement("A", 0.0, 0.0),
|
||||
_make_placement("B", 0.8, 0.0),
|
||||
_make_placement("C", 0.0, 5.0),
|
||||
_make_placement("D", 0.9, 5.0),
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
pair_set = set(pairs)
|
||||
assert (0, 1) in pair_set # A-B
|
||||
assert (2, 3) in pair_set # C-D
|
||||
assert len(pair_set) == 2
|
||||
|
||||
|
||||
class TestRotatedDeviceAabb:
|
||||
"""旋转设备导致 AABB 变大，命中候选对。"""
|
||||
|
||||
def test_rotated_device_aabb(self):
|
||||
"""一台窄长设备 (2.0×0.2)：
|
||||
- 未旋转时 AABB 半宽 = 1.0，两设备中心距 2.5 → 不交叠
|
||||
- 旋转 90° 后 AABB 半宽 = 0.1，半深 = 1.0 → 仍不交叠
|
||||
- 旋转 45° 后 AABB 半宽 ≈ (2*cos45 + 0.2*sin45)/2 ≈ 0.778
|
||||
但另一台放在 x=1.6，半宽 = 1.0
|
||||
所以 xmax_A = 0 + 0.778 = 0.778 < 1.6 - 1.0 = 0.6 → 不够
|
||||
|
||||
更好的方案：用中心距 1.5，未旋转时不交叠，旋转后交叠。
|
||||
未旋转: half_w_A = 0.3 (bbox 0.6x2.0), half_w_B = 0.3
|
||||
A: xmax = 0 + 0.3 = 0.3, B: xmin = 1.5 - 0.3 = 1.2 → 不交叠
|
||||
旋转 90°: A 的 bbox (0.6, 2.0) → half_w = (0.6*0 + 2.0*1)/2 = 1.0
|
||||
A: xmax = 0 + 1.0 = 1.0, B: xmin = 1.5 - 0.3 = 1.2 → 仍不交叠
|
||||
|
||||
用 bbox (0.4, 2.0)，间距 1.2：
|
||||
未旋转: half_w = 0.2, xmax_A = 0.2, xmin_B = 1.2 - 0.2 = 1.0 → 不交叠
|
||||
旋转 45°: half_w = (0.4*cos45 + 2.0*sin45)/2 = (0.283+1.414)/2 = 0.849
|
||||
xmax_A = 0.849, xmin_B = 1.2 - 0.2 = 1.0 → 不交叠
|
||||
|
||||
间距 0.8：
|
||||
未旋转: xmax_A = 0.2, xmin_B = 0.8 - 0.2 = 0.6 → 不交叠 ✓
|
||||
旋转 45°: xmax_A = 0.849, xmin_B = 0.6 → 交叠 ✓ (0.849 > 0.6)
|
||||
y 轴: half_d_A_rot = (0.4*sin45 + 2.0*cos45)/2 = 0.849, half_d_B = 1.0
|
||||
ymax_A = 0.849, ymin_B = -1.0 → 交叠 ✓
|
||||
"""
|
||||
dev_narrow = _make_device("narrow", 0.4, 2.0)
|
||||
dev_normal = _make_device("normal", 0.4, 2.0)
|
||||
# 未旋转：不交叠
|
||||
placements_no_rot = [
|
||||
_make_placement("narrow", 0.0, 0.0, theta=0.0),
|
||||
_make_placement("normal", 0.8, 0.0, theta=0.0),
|
||||
]
|
||||
assert sweep_and_prune_pairs([dev_narrow, dev_normal], placements_no_rot) == []
|
||||
|
||||
# narrow 旋转 45° → AABB 变大 → 交叠
|
||||
placements_rot = [
|
||||
_make_placement("narrow", 0.0, 0.0, theta=math.pi / 4),
|
||||
_make_placement("normal", 0.8, 0.0, theta=0.0),
|
||||
]
|
||||
pairs = sweep_and_prune_pairs([dev_narrow, dev_normal], placements_rot)
|
||||
assert len(pairs) == 1
|
||||
|
||||
|
||||
class TestOriginalIndices:
|
||||
"""验证返回的索引对应 placements 原始顺序而非排序后顺序。"""
|
||||
|
||||
def test_sorted_output_preserves_original_indices(self):
|
||||
"""故意让 placements 按 x 坐标逆序排列，
|
||||
验证返回的索引仍是原始顺序。"""
|
||||
devices = [
|
||||
_make_device("A", 1.0, 1.0),
|
||||
_make_device("B", 1.0, 1.0),
|
||||
_make_device("C", 1.0, 1.0),
|
||||
]
|
||||
# 逆序排列：C 在最左，A 在最右
|
||||
placements = [
|
||||
_make_placement("A", 5.0, 0.0), # idx 0, 最右
|
||||
_make_placement("B", 4.5, 0.0), # idx 1, 中间（与 A 交叠）
|
||||
_make_placement("C", 0.0, 0.0), # idx 2, 最左（独立）
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
# A(idx=0) 和 B(idx=1) AABB 交叠，索引应为 (0, 1)
|
||||
assert len(pairs) == 1
|
||||
assert pairs[0] == (0, 1)
|
||||
|
||||
# 同时验证 broad_phase_device_pairs 返回正确 device_id
|
||||
id_pairs = broad_phase_device_pairs(devices, placements)
|
||||
assert id_pairs == [("A", "B")]
|
||||
|
||||
|
||||
class TestPairCountReduction:
|
||||
"""大规模随机测试：宽相候选对数应远小于 N*(N-1)/2。"""
|
||||
|
||||
def test_pair_count_reduction(self):
|
||||
"""N=15 台设备随机放置在 10×10 实验室 → 候选对数显著少于全量。"""
|
||||
random.seed(42)
|
||||
n = 15
|
||||
devices = [_make_device(f"D{i}", 0.5, 0.5) for i in range(n)]
|
||||
placements = [
|
||||
_make_placement(f"D{i}", random.uniform(0, 10), random.uniform(0, 10))
|
||||
for i in range(n)
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
full_pairs = n * (n - 1) // 2 # = 105
|
||||
# 在 10×10 区域放 15 台 0.5×0.5 设备，交叠率应很低
|
||||
assert len(pairs) < full_pairs
|
||||
# 额外断言：候选对数不超过全量的一半（保守判定）
|
||||
assert len(pairs) < full_pairs * 0.5
|
||||
|
||||
|
||||
class TestEdgeCases:
|
||||
"""边界情况。"""
|
||||
|
||||
def test_empty_input(self):
|
||||
"""空列表 → 空结果。"""
|
||||
assert sweep_and_prune_pairs([], []) == []
|
||||
|
||||
def test_single_device(self):
|
||||
"""单台设备 → 无候选对。"""
|
||||
devices = [_make_device("A")]
|
||||
placements = [_make_placement("A", 0.0, 0.0)]
|
||||
assert sweep_and_prune_pairs(devices, placements) == []
|
||||
|
||||
def test_identical_positions(self):
|
||||
"""两台设备完全重叠 → 1 候选对。"""
|
||||
devices = [_make_device("A", 1.0, 1.0), _make_device("B", 1.0, 1.0)]
|
||||
placements = [
|
||||
_make_placement("A", 0.0, 0.0),
|
||||
_make_placement("B", 0.0, 0.0),
|
||||
]
|
||||
pairs = sweep_and_prune_pairs(devices, placements)
|
||||
assert len(pairs) == 1
|
||||
@@ -1,435 +0,0 @@
|
||||
"""Regression tests for V2 Stage 1 bugfixes.
|
||||
|
||||
Covers:
|
||||
- Duplicate device ID stacking (catalog ID + #N internal IDs)
|
||||
- DE orientation preservation (prefer_orientation_mode constraint)
|
||||
- prefer_aligned auto-injection and adjustability
|
||||
- Preset switch reorientation
|
||||
- min_spacing with duplicate catalog IDs
|
||||
"""
|
||||
|
||||
import math
|
||||
|
||||
import pytest
|
||||
|
||||
from ..constraints import evaluate_constraints
|
||||
from ..mock_checkers import MockCollisionChecker
|
||||
from ..models import Constraint, Device, Lab, Opening, Placement
|
||||
from ..obb import obb_corners, obb_overlap
|
||||
from ..optimizer import (
|
||||
_placements_to_vector,
|
||||
_vector_to_placements,
|
||||
optimize,
|
||||
snap_theta,
|
||||
)
|
||||
from ..seeders import resolve_seeder_params, seed_layout
|
||||
|
||||
|
||||
# ── Helpers ─────────────────────────────────────────────
|
||||
|
||||
def _ot(uid: str) -> Device:
|
||||
return Device(
|
||||
id=uid, name="Opentrons Liquid Handler",
|
||||
bbox=(0.6243, 0.5672), openings=[Opening(direction=(0.0, -1.0))],
|
||||
)
|
||||
|
||||
def _tecan(uid: str) -> Device:
|
||||
return Device(
|
||||
id=uid, name="Tecan EVO 100",
|
||||
bbox=(0.8121, 0.8574), openings=[Opening(direction=(0.0, -1.0))],
|
||||
)
|
||||
|
||||
def _facing_dot(p: Placement, device: Device, lab: Lab) -> float:
|
||||
"""Dot product of rotated front vector with vector from center to device.
|
||||
Positive = outward, negative = inward."""
|
||||
cx, cy = lab.width / 2, lab.depth / 2
|
||||
dx, dy = p.x - cx, p.y - cy
|
||||
front = device.openings[0].direction if device.openings else (0.0, -1.0)
|
||||
rf_x = math.cos(p.theta) * front[0] - math.sin(p.theta) * front[1]
|
||||
rf_y = math.sin(p.theta) * front[0] + math.cos(p.theta) * front[1]
|
||||
return rf_x * dx + rf_y * dy
|
||||
|
||||
def _has_collision(devices, placements):
|
||||
for i in range(len(devices)):
|
||||
for j in range(i + 1, len(devices)):
|
||||
ci = obb_corners(placements[i].x, placements[i].y,
|
||||
devices[i].bbox[0], devices[i].bbox[1], placements[i].theta)
|
||||
cj = obb_corners(placements[j].x, placements[j].y,
|
||||
devices[j].bbox[0], devices[j].bbox[1], placements[j].theta)
|
||||
if obb_overlap(ci, cj):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
# ── Bug 1: Duplicate device ID stacking ────────────────
|
||||
|
||||
class TestDuplicateDeviceIDs:
|
||||
"""When two instances of the same catalog device are placed,
|
||||
unique uuid-based IDs must prevent dict-key collisions."""
|
||||
|
||||
def test_vector_roundtrip_preserves_unique_positions(self):
|
||||
"""_placements_to_vector → _vector_to_placements with unique IDs."""
|
||||
devices = [_ot("uuid-a"), _ot("uuid-b")]
|
||||
placements = [
|
||||
Placement(device_id="uuid-a", x=0.5, y=0.5, theta=0.0),
|
||||
Placement(device_id="uuid-b", x=1.5, y=1.5, theta=1.0),
|
||||
]
|
||||
vec = _placements_to_vector(placements, devices)
|
||||
decoded = _vector_to_placements(vec, devices)
|
||||
assert decoded[0].x == pytest.approx(0.5)
|
||||
assert decoded[1].x == pytest.approx(1.5)
|
||||
|
||||
def test_min_spacing_detects_stacked_unique_ids(self):
|
||||
"""min_spacing should detect two devices at the same position
|
||||
when they have unique IDs."""
|
||||
devices = [_ot("uuid-a"), _ot("uuid-b")]
|
||||
stacked = [
|
||||
Placement(device_id="uuid-a", x=1.0, y=1.0, theta=0.0),
|
||||
Placement(device_id="uuid-b", x=1.0, y=1.0, theta=0.0),
|
||||
]
|
||||
lab = Lab(width=5, depth=5)
|
||||
constraints = [Constraint(type="hard", rule_name="min_spacing",
|
||||
params={"min_gap": 0.05})]
|
||||
# graduated=True (default): 返回有限惩罚
|
||||
cost = evaluate_constraints(devices, stacked, lab, constraints,
|
||||
MockCollisionChecker())
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
# graduated=False: binary inf
|
||||
cost_binary = evaluate_constraints(devices, stacked, lab, constraints,
|
||||
MockCollisionChecker(),
|
||||
graduated=False)
|
||||
assert math.isinf(cost_binary)
|
||||
|
||||
def test_create_devices_uses_catalog_id_with_suffixes(self):
|
||||
"""create_devices_from_list should keep catalog IDs and suffix duplicates."""
|
||||
from ..device_catalog import create_devices_from_list
|
||||
specs = [
|
||||
{"id": "opentrons_liquid_handler", "uuid": "abc-123"},
|
||||
{"id": "opentrons_liquid_handler", "uuid": "def-456"},
|
||||
]
|
||||
devices = create_devices_from_list(specs)
|
||||
assert devices[0].id == "opentrons_liquid_handler"
|
||||
assert devices[1].id == "opentrons_liquid_handler#2"
|
||||
assert devices[0].uuid == "abc-123"
|
||||
assert devices[1].uuid == "def-456"
|
||||
# Both should have the same bbox from footprints
|
||||
assert devices[0].bbox == devices[1].bbox
|
||||
|
||||
def test_create_devices_fallback_no_uuid(self):
|
||||
"""Without uuid, Device.id falls back to catalog id."""
|
||||
from ..device_catalog import create_devices_from_list
|
||||
specs = [{"id": "opentrons_liquid_handler"}]
|
||||
devices = create_devices_from_list(specs)
|
||||
assert devices[0].id == "opentrons_liquid_handler"
|
||||
|
||||
|
||||
# ── Bug 2 & 4: DE orientation preservation ─────────────
|
||||
|
||||
class TestOrientationWithDE:
|
||||
"""DE must preserve seeder orientation direction (outward/inward)
|
||||
via the prefer_orientation_mode constraint."""
|
||||
|
||||
def _run_de_with_orientation(self, mode, seed_val=42):
|
||||
devices = [_ot("ot1"), _ot("ot2"), _tecan("tecan")]
|
||||
lab = Lab(width=2.0, depth=2.0)
|
||||
params = resolve_seeder_params(
|
||||
"compact_outward" if mode == "outward" else "spread_inward"
|
||||
)
|
||||
seed = seed_layout(devices, lab, params)
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="min_spacing",
|
||||
params={"min_gap": 0.05}),
|
||||
Constraint(type="soft", rule_name="prefer_orientation_mode",
|
||||
params={"mode": mode}, weight=5.0),
|
||||
Constraint(type="soft", rule_name="prefer_aligned", weight=2.0),
|
||||
]
|
||||
result = optimize(devices, lab, constraints, seed_placements=seed,
|
||||
maxiter=200, seed=seed_val)
|
||||
result = snap_theta(result)
|
||||
return devices, lab, result
|
||||
|
||||
def test_compact_outward_de_faces_outward(self):
|
||||
devices, lab, result = self._run_de_with_orientation("outward")
|
||||
for i, p in enumerate(result):
|
||||
dot = _facing_dot(p, devices[i], lab)
|
||||
assert dot > 0, (
|
||||
f"{p.device_id} faces inward (dot={dot:.3f}) "
|
||||
f"at ({p.x:.2f},{p.y:.2f}) theta={math.degrees(p.theta):.0f}°"
|
||||
)
|
||||
|
||||
def test_spread_inward_de_faces_inward(self):
|
||||
devices, lab, result = self._run_de_with_orientation("inward")
|
||||
for i, p in enumerate(result):
|
||||
dot = _facing_dot(p, devices[i], lab)
|
||||
assert dot < 0, (
|
||||
f"{p.device_id} faces outward (dot={dot:.3f}) "
|
||||
f"at ({p.x:.2f},{p.y:.2f}) theta={math.degrees(p.theta):.0f}°"
|
||||
)
|
||||
|
||||
def test_switching_preset_changes_orientation(self):
|
||||
"""Switching from outward to inward should produce opposite facing."""
|
||||
_, lab, out_result = self._run_de_with_orientation("outward")
|
||||
devices_in, _, in_result = self._run_de_with_orientation("inward")
|
||||
# At least one device should have different facing
|
||||
out_dots = [_facing_dot(p, devices_in[i], lab) for i, p in enumerate(out_result)]
|
||||
in_dots = [_facing_dot(p, devices_in[i], lab) for i, p in enumerate(in_result)]
|
||||
# Outward: all positive; inward: all negative
|
||||
assert all(d > 0 for d in out_dots), f"outward dots: {out_dots}"
|
||||
assert all(d < 0 for d in in_dots), f"inward dots: {in_dots}"
|
||||
|
||||
def test_no_collision_after_de(self):
|
||||
devices, lab, result = self._run_de_with_orientation("outward")
|
||||
assert not _has_collision(devices, result)
|
||||
|
||||
|
||||
# ── Bug 3: prefer_aligned & prefer_orientation_mode ────
|
||||
|
||||
class TestOrientationConstraints:
|
||||
"""Test the new constraint rules directly."""
|
||||
|
||||
def test_prefer_orientation_mode_outward_zero_at_correct(self):
|
||||
"""Zero cost when device faces outward from center."""
|
||||
device = _ot("a")
|
||||
# Device to the right of center, front pointing right
|
||||
# front=(0,-1), theta=pi/2 → rotated front = (1, 0) = rightward
|
||||
lab = Lab(width=4, depth=4)
|
||||
placements = [Placement("a", 3.0, 2.0, math.pi / 2)]
|
||||
constraint = Constraint(
|
||||
type="soft", rule_name="prefer_orientation_mode",
|
||||
params={"mode": "outward"}, weight=1.0,
|
||||
)
|
||||
cost = evaluate_constraints(
|
||||
[device], placements, lab, [constraint], MockCollisionChecker(),
|
||||
)
|
||||
assert cost == pytest.approx(0.0, abs=0.01)
|
||||
|
||||
def test_prefer_orientation_mode_outward_penalty_at_inward(self):
|
||||
"""High cost when device faces inward (opposite of outward)."""
|
||||
device = _ot("a")
|
||||
# Device to the right of center, front pointing left (inward)
|
||||
# front=(0,-1), theta=3*pi/2 → rotated front = (-1, 0) = leftward
|
||||
lab = Lab(width=4, depth=4)
|
||||
placements = [Placement("a", 3.0, 2.0, 3 * math.pi / 2)]
|
||||
constraint = Constraint(
|
||||
type="soft", rule_name="prefer_orientation_mode",
|
||||
params={"mode": "outward"}, weight=1.0,
|
||||
)
|
||||
cost = evaluate_constraints(
|
||||
[device], placements, lab, [constraint], MockCollisionChecker(),
|
||||
)
|
||||
# 180° off → (1 - cos(pi)) / 2 = 1.0
|
||||
assert cost == pytest.approx(1.0, abs=0.05)
|
||||
|
||||
def test_prefer_orientation_mode_inward(self):
|
||||
"""Zero cost when device faces inward."""
|
||||
device = _ot("a")
|
||||
# Device to the right of center, front pointing left (inward)
|
||||
lab = Lab(width=4, depth=4)
|
||||
placements = [Placement("a", 3.0, 2.0, 3 * math.pi / 2)]
|
||||
constraint = Constraint(
|
||||
type="soft", rule_name="prefer_orientation_mode",
|
||||
params={"mode": "inward"}, weight=1.0,
|
||||
)
|
||||
cost = evaluate_constraints(
|
||||
[device], placements, lab, [constraint], MockCollisionChecker(),
|
||||
)
|
||||
assert cost == pytest.approx(0.0, abs=0.01)
|
||||
|
||||
def test_prefer_seeder_orientation_zero_at_target(self):
|
||||
"""Zero cost when theta matches target."""
|
||||
device = Device(id="a", name="A", bbox=(0.5, 0.5))
|
||||
lab = Lab(width=4, depth=4)
|
||||
placements = [Placement("a", 2, 2, 1.5)]
|
||||
constraint = Constraint(
|
||||
type="soft", rule_name="prefer_seeder_orientation",
|
||||
params={"target_thetas": {"a": 1.5}}, weight=1.0,
|
||||
)
|
||||
cost = evaluate_constraints(
|
||||
[device], placements, lab, [constraint], MockCollisionChecker(),
|
||||
)
|
||||
assert cost == pytest.approx(0.0, abs=1e-9)
|
||||
|
||||
def test_prefer_seeder_orientation_penalty_at_deviation(self):
|
||||
"""Non-zero cost when theta deviates from target."""
|
||||
device = Device(id="a", name="A", bbox=(0.5, 0.5))
|
||||
lab = Lab(width=4, depth=4)
|
||||
placements = [Placement("a", 2, 2, math.pi)] # pi away from 0
|
||||
constraint = Constraint(
|
||||
type="soft", rule_name="prefer_seeder_orientation",
|
||||
params={"target_thetas": {"a": 0.0}}, weight=1.0,
|
||||
)
|
||||
cost = evaluate_constraints(
|
||||
[device], placements, lab, [constraint], MockCollisionChecker(),
|
||||
)
|
||||
# (1 - cos(pi)) / 2 = 1.0
|
||||
assert cost == pytest.approx(1.0)
|
||||
|
||||
|
||||
# ── API endpoint regression ────────────────────────────
|
||||
|
||||
class TestEndpointOrientation:
|
||||
"""Test that /optimize injects orientation constraints."""
|
||||
|
||||
def test_endpoint_with_de_injects_orientation(self):
|
||||
from fastapi.testclient import TestClient
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": [
|
||||
{"id": "opentrons_liquid_handler", "uuid": "u1"},
|
||||
{"id": "opentrons_liquid_handler", "uuid": "u2"},
|
||||
],
|
||||
"lab": {"width": 3, "depth": 3},
|
||||
"seeder": "compact_outward",
|
||||
"run_de": True,
|
||||
"maxiter": 50,
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
# Both devices should have unique uuids in response
|
||||
uuids = [p["uuid"] for p in data["placements"]]
|
||||
assert len(set(uuids)) == 2, f"Expected 2 unique uuids, got {uuids}"
|
||||
|
||||
def test_endpoint_orientation_weight_override(self):
|
||||
from fastapi.testclient import TestClient
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": [{"id": "opentrons_liquid_handler", "uuid": "u1"}],
|
||||
"lab": {"width": 3, "depth": 3},
|
||||
"seeder": "compact_outward",
|
||||
"seeder_overrides": {"orientation_weight": 10, "align_weight": 0},
|
||||
"run_de": True,
|
||||
"maxiter": 50,
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
|
||||
def test_endpoint_align_weight_zero_disables(self):
|
||||
"""Setting align_weight=0 should not inject prefer_aligned."""
|
||||
from fastapi.testclient import TestClient
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": [{"id": "opentrons_liquid_handler", "uuid": "u1"}],
|
||||
"lab": {"width": 3, "depth": 3},
|
||||
"seeder": "compact_outward",
|
||||
"seeder_overrides": {"align_weight": 0},
|
||||
"run_de": True,
|
||||
"maxiter": 50,
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
|
||||
|
||||
# ── Broader scenario tests ─────────────────────────────
|
||||
|
||||
class TestScenarios:
|
||||
"""End-to-end scenarios similar to user's real usage."""
|
||||
|
||||
def test_user_scenario_2ot_1tecan_compact_outward(self):
|
||||
"""User's exact scenario: 2 OT + 1 Tecan in 2m×2m, compact outward."""
|
||||
devices = [_ot("ot1"), _ot("ot2"), _tecan("tecan")]
|
||||
lab = Lab(width=2.0, depth=2.0)
|
||||
params = resolve_seeder_params("compact_outward")
|
||||
seed = seed_layout(devices, lab, params)
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="min_spacing",
|
||||
params={"min_gap": 0.05}),
|
||||
Constraint(type="soft", rule_name="prefer_orientation_mode",
|
||||
params={"mode": "outward"}, weight=5.0),
|
||||
Constraint(type="soft", rule_name="prefer_aligned", weight=2.0),
|
||||
]
|
||||
result = optimize(devices, lab, constraints, seed_placements=seed,
|
||||
maxiter=200, seed=42)
|
||||
result = snap_theta(result)
|
||||
# No stacking
|
||||
assert not _has_collision(devices, result)
|
||||
# All outward
|
||||
for i, p in enumerate(result):
|
||||
assert _facing_dot(p, devices[i], lab) > 0
|
||||
|
||||
def test_4_medium_devices_mixed_openings(self):
|
||||
"""4 devices with different opening directions."""
|
||||
devices = [
|
||||
Device(id="d0", name="D0", bbox=(0.5, 0.3), openings=[Opening((1, 0))]),
|
||||
Device(id="d1", name="D1", bbox=(0.5, 0.3), openings=[Opening((-1, 0))]),
|
||||
Device(id="d2", name="D2", bbox=(0.5, 0.3), openings=[Opening((0, -1))]),
|
||||
Device(id="d3", name="D3", bbox=(0.5, 0.3), openings=[Opening((0, 1))]),
|
||||
]
|
||||
lab = Lab(width=3.0, depth=3.0)
|
||||
params = resolve_seeder_params("compact_outward")
|
||||
seed = seed_layout(devices, lab, params)
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="min_spacing",
|
||||
params={"min_gap": 0.05}),
|
||||
Constraint(type="soft", rule_name="prefer_orientation_mode",
|
||||
params={"mode": "outward"}, weight=5.0),
|
||||
Constraint(type="soft", rule_name="prefer_aligned", weight=2.0),
|
||||
]
|
||||
result = optimize(devices, lab, constraints, seed_placements=seed,
|
||||
maxiter=200, seed=42)
|
||||
result = snap_theta(result)
|
||||
assert not _has_collision(devices, result)
|
||||
for i, p in enumerate(result):
|
||||
assert _facing_dot(p, devices[i], lab) > 0
|
||||
|
||||
|
||||
# ── V2 Stage 1: 默认关闭 cardinal snap/alignment ────────
|
||||
|
||||
class TestV2Stage1Bugfixes:
|
||||
"""align_weight 默认为 0，snap_cardinal 默认关闭。"""
|
||||
|
||||
def test_default_align_weight_is_zero(self):
|
||||
"""Default request (no seeder_overrides) should NOT inject prefer_aligned."""
|
||||
from fastapi.testclient import TestClient
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": [{"id": "opentrons_liquid_handler", "uuid": "u1"}],
|
||||
"lab": {"width": 3, "depth": 3},
|
||||
"seeder": "compact_outward",
|
||||
"run_de": True,
|
||||
"maxiter": 50,
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
|
||||
def test_snap_cardinal_off_by_default(self):
|
||||
"""Default request should NOT snap theta to cardinal."""
|
||||
from fastapi.testclient import TestClient
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": [{"id": "opentrons_liquid_handler", "uuid": "u1"}],
|
||||
"lab": {"width": 3, "depth": 3},
|
||||
"seeder": "compact_outward",
|
||||
"run_de": True,
|
||||
"maxiter": 10,
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
|
||||
def test_snap_cardinal_opt_in(self):
|
||||
"""snap_cardinal=True should be accepted and snap angles."""
|
||||
from fastapi.testclient import TestClient
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": [{"id": "opentrons_liquid_handler", "uuid": "u1"}],
|
||||
"lab": {"width": 3, "depth": 3},
|
||||
"seeder": "compact_outward",
|
||||
"snap_cardinal": True,
|
||||
"run_de": True,
|
||||
"maxiter": 10,
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
@@ -1,505 +0,0 @@
|
||||
"""约束体系测试。"""
|
||||
|
||||
import math
|
||||
|
||||
import pytest
|
||||
|
||||
from ..constraints import (
|
||||
_crossing_penalty,
|
||||
_opening_surface_center,
|
||||
DEFAULT_WEIGHT_DISTANCE,
|
||||
evaluate_constraints,
|
||||
evaluate_default_hard_constraints,
|
||||
)
|
||||
from ..mock_checkers import MockCollisionChecker, MockReachabilityChecker
|
||||
from ..models import Constraint, Device, Opening, Placement, Lab
|
||||
from ..obb import nearest_point_on_obb, obb_corners
|
||||
|
||||
|
||||
def _make_devices():
|
||||
return [
|
||||
Device(id="a", name="Device A", bbox=(0.5, 0.5)),
|
||||
Device(id="b", name="Device B", bbox=(0.5, 0.5)),
|
||||
]
|
||||
|
||||
|
||||
def _make_lab():
|
||||
return Lab(width=5.0, depth=4.0)
|
||||
|
||||
|
||||
class TestDefaultHardConstraints:
|
||||
def test_no_collision_passes(self):
|
||||
"""无碰撞的布局应返回 0。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 1.0, 0.0),
|
||||
Placement("b", 3.0, 3.0, 0.0),
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_default_hard_constraints(devices, placements, _make_lab(), checker)
|
||||
assert cost == 0.0
|
||||
|
||||
def test_collision_returns_graduated_penalty(self):
|
||||
"""碰撞布局应返回正的graduated penalty（非inf）。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 1.0, 0.0),
|
||||
Placement("b", 1.2, 1.0, 0.0),
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_default_hard_constraints(devices, placements, _make_lab(), checker)
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
|
||||
def test_collision_returns_inf_binary_mode(self):
|
||||
"""Binary mode: 碰撞布局应返回 inf。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 1.0, 0.0),
|
||||
Placement("b", 1.2, 1.0, 0.0),
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_default_hard_constraints(
|
||||
devices, placements, _make_lab(), checker, graduated=False,
|
||||
)
|
||||
assert math.isinf(cost)
|
||||
|
||||
def test_out_of_bounds_returns_graduated_penalty(self):
|
||||
"""越界布局应返回正的graduated penalty（非inf）。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 0.1, 0.1, 0.0), # 左下角越界
|
||||
Placement("b", 3.0, 3.0, 0.0),
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_default_hard_constraints(devices, placements, _make_lab(), checker)
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
|
||||
def test_out_of_bounds_returns_inf_binary_mode(self):
|
||||
"""Binary mode: 越界布局应返回 inf。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 0.1, 0.1, 0.0),
|
||||
Placement("b", 3.0, 3.0, 0.0),
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_default_hard_constraints(
|
||||
devices, placements, _make_lab(), checker, graduated=False,
|
||||
)
|
||||
assert math.isinf(cost)
|
||||
|
||||
def test_worse_collision_higher_cost(self):
|
||||
"""Deeper penetration should produce higher cost."""
|
||||
devices = _make_devices()
|
||||
checker = MockCollisionChecker()
|
||||
lab = _make_lab()
|
||||
# Small overlap
|
||||
cost_small = evaluate_default_hard_constraints(
|
||||
devices, [Placement("a", 1.0, 1.0, 0.0), Placement("b", 1.4, 1.0, 0.0)],
|
||||
lab, checker,
|
||||
)
|
||||
# Large overlap
|
||||
cost_large = evaluate_default_hard_constraints(
|
||||
devices, [Placement("a", 1.0, 1.0, 0.0), Placement("b", 1.1, 1.0, 0.0)],
|
||||
lab, checker,
|
||||
)
|
||||
assert cost_large > cost_small > 0
|
||||
|
||||
|
||||
class TestUserConstraints:
|
||||
def test_distance_less_than_satisfied(self):
|
||||
"""距离约束满足时 cost=0。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 1.0, 0.0),
|
||||
Placement("b", 1.5, 1.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="distance_less_than",
|
||||
params={"device_a": "a", "device_b": "b", "distance": 1.0})
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
reachability = MockReachabilityChecker()
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker, reachability
|
||||
)
|
||||
assert cost == 0.0
|
||||
|
||||
def test_distance_less_than_violated_hard(self):
|
||||
"""硬距离约束违反：graduated模式返回有限惩罚，binary模式返回inf。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 1.0, 0.0),
|
||||
Placement("b", 4.0, 3.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="distance_less_than",
|
||||
params={"device_a": "a", "device_b": "b", "distance": 1.0})
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
# graduated=True (default): 有限惩罚
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker
|
||||
)
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
# graduated=False: binary inf
|
||||
cost_binary = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker,
|
||||
graduated=False,
|
||||
)
|
||||
assert math.isinf(cost_binary)
|
||||
|
||||
def test_minimize_distance_cost(self):
|
||||
"""minimize_distance 约束应返回正比于距离的 cost。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 1.0, 0.0),
|
||||
Placement("b", 3.0, 1.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="soft", rule_name="minimize_distance",
|
||||
params={"device_a": "a", "device_b": "b"}, weight=2.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker
|
||||
)
|
||||
# edge-to-edge distance = 2.0 - 0.25 - 0.25 = 1.5, weight = 2.0 → cost = 3.0
|
||||
assert abs(cost - 3.0) < 0.01
|
||||
|
||||
def test_reachability_constraint(self):
|
||||
"""可达性约束：目标在臂展内应通过（不返回 inf）。
|
||||
|
||||
Opening-faces-arm penalty may add a small soft cost when the
|
||||
target's opening doesn't face the arm, but it must not cause
|
||||
hard failure (inf).
|
||||
"""
|
||||
devices = [
|
||||
Device(id="arm", name="Arm", bbox=(0.2, 0.2), device_type="articulation"),
|
||||
Device(id="target", name="Target", bbox=(0.5, 0.5)),
|
||||
]
|
||||
placements = [
|
||||
Placement("arm", 1.0, 1.0, 0.0),
|
||||
Placement("target", 1.5, 1.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="reachability",
|
||||
params={"arm_id": "arm", "target_device_id": "target"})
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
reachability = MockReachabilityChecker(arm_reach={"arm": 1.0})
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker, reachability
|
||||
)
|
||||
assert not math.isinf(cost) # reachable → no hard failure
|
||||
|
||||
def test_reachability_constraint_violated(self):
|
||||
"""可达性约束：目标超出臂展 — graduated返回有限惩罚，binary返回inf。"""
|
||||
devices = [
|
||||
Device(id="arm", name="Arm", bbox=(0.2, 0.2), device_type="articulation"),
|
||||
Device(id="target", name="Target", bbox=(0.5, 0.5)),
|
||||
]
|
||||
placements = [
|
||||
Placement("arm", 1.0, 1.0, 0.0),
|
||||
Placement("target", 4.0, 3.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="reachability",
|
||||
params={"arm_id": "arm", "target_device_id": "target"})
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
reachability = MockReachabilityChecker(arm_reach={"arm": 1.0})
|
||||
# graduated=True (default): 有限惩罚
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker, reachability
|
||||
)
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
# graduated=False: binary inf
|
||||
cost_binary = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker, reachability,
|
||||
graduated=False,
|
||||
)
|
||||
assert math.isinf(cost_binary)
|
||||
|
||||
|
||||
def test_distance_less_than_uses_edge_to_edge():
|
||||
"""distance_less_than should measure edge-to-edge, not center-to-center.
|
||||
|
||||
Two devices: centers 3m apart, each 2m wide → edge gap = 1m.
|
||||
Constraint: distance_less_than 1.5m (edge-to-edge).
|
||||
Old center-to-center: 3m > 1.5m → violation.
|
||||
New edge-to-edge: 1m < 1.5m → satisfied.
|
||||
"""
|
||||
devices = [
|
||||
Device(id="a", name="A", bbox=(2.0, 1.0)),
|
||||
Device(id="b", name="B", bbox=(2.0, 1.0)),
|
||||
]
|
||||
placements = [
|
||||
Placement(device_id="a", x=1.0, y=1.0, theta=0.0),
|
||||
Placement(device_id="b", x=4.0, y=1.0, theta=0.0),
|
||||
]
|
||||
lab = Lab(width=10, depth=10)
|
||||
constraint = Constraint(
|
||||
type="soft", rule_name="distance_less_than",
|
||||
params={"device_a": "a", "device_b": "b", "distance": 1.5},
|
||||
weight=1.0,
|
||||
)
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(devices, placements, lab, [constraint], checker)
|
||||
assert cost == pytest.approx(0.0)
|
||||
|
||||
|
||||
def test_prefer_aligned_zero_at_cardinal():
|
||||
"""prefer_aligned cost = 0 when all devices at 0/90/180/270°."""
|
||||
devices = [Device(id="a", name="A", bbox=(1.0, 1.0))]
|
||||
lab = Lab(width=10, depth=10)
|
||||
checker = MockCollisionChecker()
|
||||
for angle in [0, math.pi / 2, math.pi, 3 * math.pi / 2]:
|
||||
placements = [Placement(device_id="a", x=5, y=5, theta=angle)]
|
||||
constraint = Constraint(type="soft", rule_name="prefer_aligned", weight=1.0)
|
||||
cost = evaluate_constraints(devices, placements, lab, [constraint], checker)
|
||||
assert cost == pytest.approx(0.0, abs=1e-9)
|
||||
|
||||
|
||||
def test_prefer_aligned_max_at_45():
|
||||
"""prefer_aligned cost is maximum when device at 45°."""
|
||||
devices = [Device(id="a", name="A", bbox=(1.0, 1.0))]
|
||||
placements = [Placement(device_id="a", x=5, y=5, theta=math.pi / 4)]
|
||||
lab = Lab(width=10, depth=10)
|
||||
constraint = Constraint(type="soft", rule_name="prefer_aligned", weight=1.0)
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(devices, placements, lab, [constraint], checker)
|
||||
# (1 - cos(4 * pi/4)) / 2 = (1 - cos(pi)) / 2 = (1 - (-1)) / 2 = 1.0
|
||||
assert cost == pytest.approx(1.0)
|
||||
|
||||
|
||||
def test_prefer_aligned_sums_over_devices():
|
||||
"""Cost sums across all devices."""
|
||||
devices = [
|
||||
Device(id="a", name="A", bbox=(1.0, 1.0)),
|
||||
Device(id="b", name="B", bbox=(1.0, 1.0)),
|
||||
]
|
||||
placements = [
|
||||
Placement(device_id="a", x=2, y=2, theta=math.pi / 4), # cost = 1.0
|
||||
Placement(device_id="b", x=7, y=7, theta=math.pi / 4), # cost = 1.0
|
||||
]
|
||||
lab = Lab(width=10, depth=10)
|
||||
constraint = Constraint(type="soft", rule_name="prefer_aligned", weight=2.0)
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(devices, placements, lab, [constraint], checker)
|
||||
# 2 devices × 1.0 × weight 2.0 = 4.0
|
||||
assert cost == pytest.approx(4.0)
|
||||
|
||||
|
||||
class TestGraduatedHardConstraints:
|
||||
"""graduated 模式下硬约束返回比例惩罚而非 inf。"""
|
||||
|
||||
def test_hard_reachability_graduated_finite(self):
|
||||
"""graduated=True: 硬可达性返回有限惩罚。"""
|
||||
devices = [
|
||||
Device(id="arm", name="Arm", bbox=(0.2, 0.2), device_type="articulation"),
|
||||
Device(id="t", name="Target", bbox=(0.5, 0.5)),
|
||||
]
|
||||
placements = [
|
||||
Placement("arm", 1.0, 1.0, 0.0),
|
||||
Placement("t", 4.0, 3.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="reachability",
|
||||
params={"arm_id": "arm", "target_device_id": "t"}, weight=1.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
reach = MockReachabilityChecker(arm_reach={"arm": 1.0})
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker, reach,
|
||||
graduated=True,
|
||||
)
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
|
||||
def test_hard_reachability_binary_inf(self):
|
||||
"""graduated=False: 硬可达性返回 inf。"""
|
||||
devices = [
|
||||
Device(id="arm", name="Arm", bbox=(0.2, 0.2), device_type="articulation"),
|
||||
Device(id="t", name="Target", bbox=(0.5, 0.5)),
|
||||
]
|
||||
placements = [
|
||||
Placement("arm", 1.0, 1.0, 0.0),
|
||||
Placement("t", 4.0, 3.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="reachability",
|
||||
params={"arm_id": "arm", "target_device_id": "t"}, weight=1.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
reach = MockReachabilityChecker(arm_reach={"arm": 1.0})
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker, reach,
|
||||
graduated=False,
|
||||
)
|
||||
assert math.isinf(cost)
|
||||
|
||||
def test_hard_min_spacing_graduated_sums_all_pairs(self):
|
||||
"""graduated模式：min_spacing 对所有违规对求和（不只第一对）。"""
|
||||
devices = [
|
||||
Device(id="a", name="A", bbox=(0.5, 0.5)),
|
||||
Device(id="b", name="B", bbox=(0.5, 0.5)),
|
||||
Device(id="c", name="C", bbox=(0.5, 0.5)),
|
||||
]
|
||||
# 三个设备间距都小于 min_gap=1.0
|
||||
placements = [
|
||||
Placement("a", 1.0, 2.0, 0.0),
|
||||
Placement("b", 1.3, 2.0, 0.0), # OBB 边缘距 a 约 0.3
|
||||
Placement("c", 1.6, 2.0, 0.0), # OBB 边缘距 b 约 0.3, 距 a 约 0.6
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="min_spacing",
|
||||
params={"min_gap": 1.0}, weight=1.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker,
|
||||
graduated=True,
|
||||
)
|
||||
# 应大于 0 且有限（累加多对违规）
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
|
||||
def test_hard_min_spacing_binary_inf(self):
|
||||
"""graduated=False: min_spacing 违规返回 inf。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 2.0, 0.0),
|
||||
Placement("b", 1.3, 2.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="min_spacing",
|
||||
params={"min_gap": 1.0}, weight=1.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker,
|
||||
graduated=False,
|
||||
)
|
||||
assert math.isinf(cost)
|
||||
|
||||
def test_hard_distance_less_than_graduated(self):
|
||||
"""graduated模式：distance_less_than 硬约束返回比例惩罚。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 2.0, 0.0),
|
||||
Placement("b", 4.0, 2.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="distance_less_than",
|
||||
params={"device_a": "a", "device_b": "b", "distance": 0.5},
|
||||
weight=2.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker,
|
||||
graduated=True,
|
||||
)
|
||||
# HARD_MULTIPLIER(5) × weight(2) × overshoot > 0
|
||||
assert cost > 0
|
||||
assert not math.isinf(cost)
|
||||
|
||||
def test_graduated_default_is_true(self):
|
||||
"""不传 graduated 参数时默认使用 graduated 模式。"""
|
||||
devices = _make_devices()
|
||||
placements = [
|
||||
Placement("a", 1.0, 2.0, 0.0),
|
||||
Placement("b", 4.0, 2.0, 0.0),
|
||||
]
|
||||
constraints = [
|
||||
Constraint(type="hard", rule_name="distance_less_than",
|
||||
params={"device_a": "a", "device_b": "b", "distance": 0.5},
|
||||
weight=1.0)
|
||||
]
|
||||
checker = MockCollisionChecker()
|
||||
# 不指定 graduated — 默认应为 True → 有限惩罚
|
||||
cost = evaluate_constraints(
|
||||
devices, placements, _make_lab(), constraints, checker,
|
||||
)
|
||||
assert not math.isinf(cost)
|
||||
|
||||
|
||||
class TestCrossingPenalty:
|
||||
"""_crossing_penalty: 交叉长度加权的 soft penalty。"""
|
||||
|
||||
def _make_device(self, dev_id, bbox=(0.5, 0.5), direction=(0.0, -1.0)):
|
||||
return Device(
|
||||
id=dev_id, name=dev_id, device_type="static",
|
||||
bbox=bbox, height=0.3,
|
||||
openings=[Opening(direction=direction, label="front")],
|
||||
)
|
||||
|
||||
def test_no_blockers_returns_zero(self):
|
||||
"""arm 与 target 之间无遮挡设备 → 交叉代价为 0。"""
|
||||
arm = self._make_device("arm", bbox=(2.14, 0.35))
|
||||
target = self._make_device("target")
|
||||
arm_p = Placement(device_id="arm", x=2.0, y=1.0, theta=0.0)
|
||||
target_p = Placement(device_id="target", x=0.5, y=1.0, theta=3.14159)
|
||||
device_map = {"arm": arm, "target": target}
|
||||
placement_map = {"arm": arm_p, "target": target_p}
|
||||
|
||||
opening_pt = _opening_surface_center(target, target_p)
|
||||
arm_corners = obb_corners(arm_p.x, arm_p.y, arm.bbox[0], arm.bbox[1], arm_p.theta)
|
||||
nearest = nearest_point_on_obb(opening_pt[0], opening_pt[1], arm_corners)
|
||||
|
||||
cost = _crossing_penalty(
|
||||
opening_pt, nearest,
|
||||
"arm", "target",
|
||||
device_map, placement_map,
|
||||
)
|
||||
assert cost == 0.0
|
||||
|
||||
def test_one_blocker_proportional_to_length(self):
|
||||
"""一个遮挡设备 → cost = DEFAULT_WEIGHT_DISTANCE * 穿过长度。"""
|
||||
arm = self._make_device("arm", bbox=(2.14, 0.35))
|
||||
target = self._make_device("target")
|
||||
blocker = self._make_device("blocker", bbox=(0.5, 0.5))
|
||||
arm_p = Placement(device_id="arm", x=3.0, y=1.0, theta=0.0)
|
||||
target_p = Placement(device_id="target", x=0.0, y=1.0, theta=0.0)
|
||||
blocker_p = Placement(device_id="blocker", x=1.5, y=1.0, theta=0.0)
|
||||
device_map = {"arm": arm, "target": target, "blocker": blocker}
|
||||
placement_map = {"arm": arm_p, "target": target_p, "blocker": blocker_p}
|
||||
|
||||
opening_pt = _opening_surface_center(target, target_p)
|
||||
arm_corners = obb_corners(arm_p.x, arm_p.y, arm.bbox[0], arm.bbox[1], arm_p.theta)
|
||||
nearest = nearest_point_on_obb(opening_pt[0], opening_pt[1], arm_corners)
|
||||
|
||||
cost = _crossing_penalty(
|
||||
opening_pt, nearest,
|
||||
"arm", "target",
|
||||
device_map, placement_map,
|
||||
)
|
||||
# blocker 宽 0.5m，theta=0，路径水平 → 穿过长度 ≈ 0.5m
|
||||
# cost = DEFAULT_WEIGHT_DISTANCE * 0.5 = 100 * 0.5 = 50
|
||||
assert cost > 0
|
||||
assert abs(cost - DEFAULT_WEIGHT_DISTANCE * 0.5) < DEFAULT_WEIGHT_DISTANCE * 0.1
|
||||
|
||||
def test_blocker_off_path_returns_zero(self):
|
||||
"""不在路径上的设备 → 交叉代价为 0。"""
|
||||
arm = self._make_device("arm", bbox=(2.14, 0.35))
|
||||
target = self._make_device("target")
|
||||
bystander = self._make_device("bystander", bbox=(0.5, 0.5))
|
||||
arm_p = Placement(device_id="arm", x=3.0, y=1.0, theta=0.0)
|
||||
target_p = Placement(device_id="target", x=0.0, y=1.0, theta=0.0)
|
||||
bystander_p = Placement(device_id="bystander", x=1.5, y=3.0, theta=0.0)
|
||||
device_map = {"arm": arm, "target": target, "bystander": bystander}
|
||||
placement_map = {"arm": arm_p, "target": target_p, "bystander": bystander_p}
|
||||
|
||||
opening_pt = _opening_surface_center(target, target_p)
|
||||
arm_corners = obb_corners(arm_p.x, arm_p.y, arm.bbox[0], arm.bbox[1], arm_p.theta)
|
||||
nearest = nearest_point_on_obb(opening_pt[0], opening_pt[1], arm_corners)
|
||||
|
||||
cost = _crossing_penalty(
|
||||
opening_pt, nearest,
|
||||
"arm", "target",
|
||||
device_map, placement_map,
|
||||
)
|
||||
assert cost == 0.0
|
||||
@@ -1,234 +0,0 @@
|
||||
"""device_catalog 双源加载测试。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from ..device_catalog import (
|
||||
_DEFAULT_FOOTPRINTS,
|
||||
create_devices_from_list,
|
||||
load_devices_from_assets,
|
||||
load_devices_from_registry,
|
||||
load_footprints,
|
||||
merge_device_lists,
|
||||
reset_footprints_cache,
|
||||
resolve_device,
|
||||
)
|
||||
|
||||
# ---------- fixtures ----------
|
||||
|
||||
# LeapLab/layout_optimizer/tests/ → LeapLab/ → DPTech/
|
||||
_LEAPLAB = Path(__file__).resolve().parent.parent.parent
|
||||
_DPTECH = _LEAPLAB.parent
|
||||
DATA_JSON = _DPTECH / "uni-lab-assets" / "data.json"
|
||||
REGISTRY_DIR = _LEAPLAB / "Uni-Lab-OS" / "unilabos" / "device_mesh" / "devices"
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _clear_cache():
|
||||
"""每个测试前清除缓存。"""
|
||||
reset_footprints_cache()
|
||||
yield
|
||||
reset_footprints_cache()
|
||||
|
||||
|
||||
# ---------- footprints ----------
|
||||
|
||||
|
||||
class TestLoadFootprints:
|
||||
def test_load_footprints_exists(self):
|
||||
fp = load_footprints(_DEFAULT_FOOTPRINTS)
|
||||
assert isinstance(fp, dict)
|
||||
assert len(fp) > 0
|
||||
|
||||
def test_footprint_structure(self):
|
||||
fp = load_footprints()
|
||||
for dev_id, entry in fp.items():
|
||||
assert "bbox" in entry, f"{dev_id} missing bbox"
|
||||
assert len(entry["bbox"]) == 2
|
||||
assert "height" in entry
|
||||
assert "origin_offset" in entry
|
||||
assert "openings" in entry
|
||||
|
||||
def test_known_device_in_footprints(self):
|
||||
fp = load_footprints()
|
||||
assert "agilent_bravo" in fp
|
||||
bbox = fp["agilent_bravo"]["bbox"]
|
||||
assert 0.5 < bbox[0] < 1.0 # width ~0.65m
|
||||
assert 0.5 < bbox[1] < 1.0 # depth ~0.70m
|
||||
|
||||
def test_nonexistent_path_returns_empty(self):
|
||||
reset_footprints_cache()
|
||||
fp = load_footprints("/nonexistent/footprints.json")
|
||||
assert fp == {}
|
||||
|
||||
|
||||
# ---------- assets 加载 ----------
|
||||
|
||||
|
||||
class TestLoadFromAssets:
|
||||
@pytest.mark.skipif(not DATA_JSON.exists(), reason="data.json not found")
|
||||
def test_load_returns_devices(self):
|
||||
devices = load_devices_from_assets(DATA_JSON)
|
||||
assert len(devices) > 0
|
||||
|
||||
@pytest.mark.skipif(not DATA_JSON.exists(), reason="data.json not found")
|
||||
def test_known_device_has_real_bbox(self):
|
||||
devices = load_devices_from_assets(DATA_JSON)
|
||||
bravo = next((d for d in devices if d.id == "agilent_bravo"), None)
|
||||
assert bravo is not None
|
||||
assert bravo.bbox != (0.6, 0.4) # 不是默认值
|
||||
assert bravo.source == "assets"
|
||||
|
||||
def test_missing_data_json(self):
|
||||
devices = load_devices_from_assets("/nonexistent/data.json")
|
||||
assert devices == []
|
||||
|
||||
|
||||
# ---------- registry 加载 ----------
|
||||
|
||||
|
||||
class TestLoadFromRegistry:
|
||||
@pytest.mark.skipif(not REGISTRY_DIR.exists(), reason="registry dir not found")
|
||||
def test_load_returns_devices(self):
|
||||
devices = load_devices_from_registry(REGISTRY_DIR)
|
||||
assert len(devices) > 0
|
||||
|
||||
@pytest.mark.skipif(not REGISTRY_DIR.exists(), reason="registry dir not found")
|
||||
def test_elite_robot_present(self):
|
||||
devices = load_devices_from_registry(REGISTRY_DIR)
|
||||
elite = next((d for d in devices if d.id == "elite_robot"), None)
|
||||
assert elite is not None
|
||||
assert elite.source == "registry"
|
||||
|
||||
def test_missing_dir(self):
|
||||
devices = load_devices_from_registry("/nonexistent/")
|
||||
assert devices == []
|
||||
|
||||
|
||||
# ---------- 合并与去重 ----------
|
||||
|
||||
|
||||
class TestMergeDedup:
|
||||
def test_registry_wins_dedup(self):
|
||||
from ..models import Device
|
||||
|
||||
reg = [Device(id="ot2", name="OT-2 Registry", bbox=(0.62, 0.50), source="registry")]
|
||||
asset = [Device(id="ot2", name="OT-2 Assets", bbox=(0.62, 0.50), source="assets")]
|
||||
merged = merge_device_lists(reg, asset)
|
||||
ot2 = next(d for d in merged if d.id == "ot2")
|
||||
assert ot2.source == "registry"
|
||||
assert ot2.name == "OT-2 Registry"
|
||||
|
||||
def test_merge_preserves_unique(self):
|
||||
from ..models import Device
|
||||
|
||||
reg = [Device(id="elite", name="Elite", source="registry")]
|
||||
asset = [Device(id="bravo", name="Bravo", source="assets")]
|
||||
merged = merge_device_lists(reg, asset)
|
||||
ids = {d.id for d in merged}
|
||||
assert ids == {"elite", "bravo"}
|
||||
|
||||
def test_registry_inherits_asset_model(self):
|
||||
from ..models import Device
|
||||
|
||||
reg = [Device(id="ot2", name="OT-2", source="registry", model_path="")]
|
||||
asset = [Device(id="ot2", name="OT-2", source="assets", model_path="/models/ot2/mesh.glb")]
|
||||
merged = merge_device_lists(reg, asset)
|
||||
ot2 = next(d for d in merged if d.id == "ot2")
|
||||
assert ot2.model_path == "/models/ot2/mesh.glb"
|
||||
|
||||
|
||||
# ---------- resolve_device ----------
|
||||
|
||||
|
||||
class TestResolveDevice:
|
||||
def test_known_device(self):
|
||||
dev = resolve_device("agilent_bravo")
|
||||
assert dev is not None
|
||||
assert dev.id == "agilent_bravo"
|
||||
assert dev.bbox != (0.6, 0.4)
|
||||
|
||||
def test_fallback_known_sizes(self):
|
||||
dev = resolve_device("ot2")
|
||||
assert dev is not None
|
||||
assert dev.bbox == (0.62, 0.50)
|
||||
|
||||
def test_unknown_device_returns_none(self):
|
||||
dev = resolve_device("totally_unknown_device_xyz")
|
||||
assert dev is None
|
||||
|
||||
|
||||
# ---------- create_devices_from_list (向后兼容) ----------
|
||||
|
||||
|
||||
class TestCreateDevicesFromList:
|
||||
def test_basic(self):
|
||||
specs = [{"id": "test_dev", "name": "Test"}]
|
||||
devs = create_devices_from_list(specs)
|
||||
assert len(devs) == 1
|
||||
assert devs[0].id == "test_dev"
|
||||
|
||||
def test_with_explicit_size(self):
|
||||
specs = [{"id": "custom", "name": "Custom", "size": [1.0, 0.5]}]
|
||||
devs = create_devices_from_list(specs)
|
||||
assert devs[0].bbox == (1.0, 0.5)
|
||||
|
||||
def test_footprint_size_used_when_no_explicit(self):
|
||||
specs = [{"id": "agilent_bravo", "name": "Bravo"}]
|
||||
devs = create_devices_from_list(specs)
|
||||
assert devs[0].bbox != (0.6, 0.4) # 使用 footprints 中的真实尺寸
|
||||
|
||||
def test_duplicate_catalog_ids_use_suffixes_and_store_uuid(self):
|
||||
specs = [
|
||||
{"id": "opentrons_liquid_handler", "uuid": "u1"},
|
||||
{"id": "opentrons_liquid_handler", "uuid": "u2"},
|
||||
]
|
||||
devs = create_devices_from_list(specs)
|
||||
assert [dev.id for dev in devs] == [
|
||||
"opentrons_liquid_handler",
|
||||
"opentrons_liquid_handler#2",
|
||||
]
|
||||
assert [dev.uuid for dev in devs] == ["u1", "u2"]
|
||||
|
||||
|
||||
# ---------- server endpoint (需要 httpx) ----------
|
||||
|
||||
|
||||
class TestDevicesEndpoint:
|
||||
def test_get_devices(self):
|
||||
try:
|
||||
from fastapi.testclient import TestClient
|
||||
except ImportError:
|
||||
pytest.skip("fastapi testclient not available")
|
||||
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.get("/devices")
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert isinstance(data, list)
|
||||
# 可能为空（取决于 uni-lab-assets 是否在预期路径）
|
||||
if len(data) > 0:
|
||||
first = data[0]
|
||||
assert "id" in first
|
||||
assert "bbox" in first
|
||||
assert "source" in first
|
||||
|
||||
def test_filter_by_source(self):
|
||||
try:
|
||||
from fastapi.testclient import TestClient
|
||||
except ImportError:
|
||||
pytest.skip("fastapi testclient not available")
|
||||
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
resp = client.get("/devices?source=registry")
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
for d in data:
|
||||
assert d["source"] == "registry"
|
||||
@@ -1,263 +0,0 @@
|
||||
"""End-to-end pipeline test: intents → interpret → optimize → verify.
|
||||
|
||||
Tests each stage boundary independently so failures are easy to localize.
|
||||
Uses real PCR workflow devices with footprints from the catalog.
|
||||
"""
|
||||
import math
|
||||
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
# -- Scene: 5 PCR devices the user has already placed in the scene --
|
||||
|
||||
PCR_DEVICES = [
|
||||
{"id": "thermo_orbitor_rs2_hotel", "name": "Plate Hotel", "device_type": "static"},
|
||||
{"id": "arm_slider", "name": "Robot Arm", "device_type": "articulation"},
|
||||
{"id": "opentrons_liquid_handler", "name": "Liquid Handler", "device_type": "static"},
|
||||
{"id": "agilent_plateloc", "name": "Plate Sealer", "device_type": "static"},
|
||||
{"id": "inheco_odtc_96xl", "name": "Thermal Cycler", "device_type": "static"},
|
||||
]
|
||||
|
||||
PCR_LAB = {"width": 6.0, "depth": 4.0}
|
||||
|
||||
# -- Stage 1: simulated LLM output (what the LLM would produce from NL) --
|
||||
# User said: "take plate from hotel, prepare sample in opentrons,
|
||||
# seal plate then pcr cycle, arm_slider handles transfers"
|
||||
|
||||
LLM_INTENTS = [
|
||||
{
|
||||
"intent": "reachable_by",
|
||||
"params": {
|
||||
"arm": "arm_slider",
|
||||
"targets": [
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
"opentrons_liquid_handler",
|
||||
"agilent_plateloc",
|
||||
"inheco_odtc_96xl",
|
||||
],
|
||||
},
|
||||
"description": "arm_slider must reach all workflow devices",
|
||||
},
|
||||
{
|
||||
"intent": "workflow_hint",
|
||||
"params": {
|
||||
"workflow": "pcr",
|
||||
"devices": [
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
"opentrons_liquid_handler",
|
||||
"agilent_plateloc",
|
||||
"inheco_odtc_96xl",
|
||||
],
|
||||
},
|
||||
"description": "PCR order: hotel → liquid handler → sealer → thermal cycler",
|
||||
},
|
||||
{
|
||||
"intent": "close_together",
|
||||
"params": {
|
||||
"devices": ["opentrons_liquid_handler", "agilent_plateloc"],
|
||||
"priority": "high",
|
||||
},
|
||||
"description": "Seal immediately after sample prep",
|
||||
},
|
||||
{
|
||||
"intent": "min_spacing",
|
||||
"params": {"min_gap": 0.15},
|
||||
"description": "Minimum 15cm gap for accessibility",
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
class TestStage1Interpret:
|
||||
"""Stage 1: /interpret translates intents → constraints."""
|
||||
|
||||
def test_interpret_returns_correct_constraint_count(self):
|
||||
resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
# 4 reachability + 3 workflow minimize + 1 close minimize + 1 min_spacing = 9
|
||||
assert len(data["constraints"]) == 9
|
||||
assert len(data["errors"]) == 0
|
||||
|
||||
def test_interpret_has_translations_for_each_intent(self):
|
||||
resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
data = resp.json()
|
||||
assert len(data["translations"]) == len(LLM_INTENTS)
|
||||
# 每个 translation 都有 explanation
|
||||
for t in data["translations"]:
|
||||
assert t["explanation"] != ""
|
||||
|
||||
def test_interpret_extracts_workflow_edges(self):
|
||||
resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
data = resp.json()
|
||||
assert len(data["workflow_edges"]) == 3
|
||||
assert ["thermo_orbitor_rs2_hotel", "opentrons_liquid_handler"] in data["workflow_edges"]
|
||||
assert ["opentrons_liquid_handler", "agilent_plateloc"] in data["workflow_edges"]
|
||||
assert ["agilent_plateloc", "inheco_odtc_96xl"] in data["workflow_edges"]
|
||||
|
||||
def test_interpret_constraint_types_correct(self):
|
||||
resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
data = resp.json()
|
||||
constraints = data["constraints"]
|
||||
by_rule = {}
|
||||
for c in constraints:
|
||||
by_rule.setdefault(c["rule_name"], []).append(c)
|
||||
assert len(by_rule["reachability"]) == 4
|
||||
assert all(c["type"] == "hard" for c in by_rule["reachability"])
|
||||
assert len(by_rule["minimize_distance"]) == 4 # 3 workflow + 1 close
|
||||
assert all(c["type"] == "soft" for c in by_rule["minimize_distance"])
|
||||
assert len(by_rule["min_spacing"]) == 1
|
||||
assert by_rule["min_spacing"][0]["type"] == "hard"
|
||||
|
||||
|
||||
class TestStage2Optimize:
|
||||
"""Stage 2: pipe /interpret output into /optimize → placements."""
|
||||
|
||||
@pytest.fixture()
|
||||
def interpret_result(self):
|
||||
resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
return resp.json()
|
||||
|
||||
def test_optimize_accepts_interpret_output(self, interpret_result):
|
||||
"""Constraints + workflow_edges from /interpret are valid /optimize input."""
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": PCR_DEVICES,
|
||||
"lab": PCR_LAB,
|
||||
"constraints": interpret_result["constraints"],
|
||||
"workflow_edges": interpret_result["workflow_edges"],
|
||||
"run_de": False, # seeder only — fast
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert len(data["placements"]) == 5
|
||||
assert data["success"] is True
|
||||
|
||||
def test_optimize_with_de(self, interpret_result):
|
||||
"""Full DE optimization completes without error."""
|
||||
resp = client.post("/optimize", json={
|
||||
"devices": PCR_DEVICES,
|
||||
"lab": PCR_LAB,
|
||||
"constraints": interpret_result["constraints"],
|
||||
"workflow_edges": interpret_result["workflow_edges"],
|
||||
"run_de": True,
|
||||
"maxiter": 50, # reduced for test speed
|
||||
"seed": 42,
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert len(data["placements"]) == 5
|
||||
assert data["de_ran"] is True
|
||||
|
||||
|
||||
class TestStage3VerifyPlacements:
|
||||
"""Stage 3: verify optimized placements satisfy constraint intent."""
|
||||
|
||||
@pytest.fixture()
|
||||
def placements(self):
|
||||
# Full pipeline: interpret → optimize (with DE), all intents including reachability
|
||||
# MockReachabilityChecker uses large fallback reach for unknown arms like arm_slider
|
||||
interpret_resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
interpret_data = interpret_resp.json()
|
||||
|
||||
optimize_resp = client.post("/optimize", json={
|
||||
"devices": PCR_DEVICES,
|
||||
"lab": PCR_LAB,
|
||||
"constraints": interpret_data["constraints"],
|
||||
"workflow_edges": interpret_data["workflow_edges"],
|
||||
"run_de": True,
|
||||
"maxiter": 50,
|
||||
"seed": 42,
|
||||
})
|
||||
return {p["device_id"]: p for p in optimize_resp.json()["placements"]}
|
||||
|
||||
def test_all_devices_placed(self, placements):
|
||||
expected_ids = {d["id"] for d in PCR_DEVICES}
|
||||
assert set(placements.keys()) == expected_ids
|
||||
|
||||
def test_all_within_lab_bounds(self, placements):
|
||||
for dev_id, p in placements.items():
|
||||
assert 0 <= p["position"]["x"] <= PCR_LAB["width"], f"{dev_id} x out of bounds"
|
||||
assert 0 <= p["position"]["y"] <= PCR_LAB["depth"], f"{dev_id} y out of bounds"
|
||||
|
||||
def test_no_hard_constraint_violation(self):
|
||||
"""Full pipeline with all intents including reachability converges cleanly.
|
||||
|
||||
MockReachabilityChecker now includes arm_slider in the default reach table
|
||||
(1.07m). Binary final evaluation checks all hard constraints including
|
||||
user-defined reachability.
|
||||
"""
|
||||
interpret_data = client.post("/interpret", json={"intents": LLM_INTENTS}).json()
|
||||
|
||||
optimize_resp = client.post("/optimize", json={
|
||||
"devices": PCR_DEVICES,
|
||||
"lab": PCR_LAB,
|
||||
"constraints": interpret_data["constraints"],
|
||||
"workflow_edges": interpret_data["workflow_edges"],
|
||||
"run_de": True,
|
||||
"maxiter": 100,
|
||||
"seed": 42,
|
||||
"snap_cardinal": True,
|
||||
"seeder_overrides": {"align_weight": 60},
|
||||
})
|
||||
data = optimize_resp.json()
|
||||
assert data["success"] is True
|
||||
assert not math.isinf(data["cost"])
|
||||
|
||||
def test_workflow_neighbors_closer_than_diagonal(self, placements):
|
||||
"""Workflow-adjacent devices should be closer than lab diagonal (basic sanity)."""
|
||||
max_diagonal = math.sqrt(PCR_LAB["width"] ** 2 + PCR_LAB["depth"] ** 2)
|
||||
workflow_pairs = [
|
||||
("thermo_orbitor_rs2_hotel", "opentrons_liquid_handler"),
|
||||
("opentrons_liquid_handler", "agilent_plateloc"),
|
||||
("agilent_plateloc", "inheco_odtc_96xl"),
|
||||
]
|
||||
for a_id, b_id in workflow_pairs:
|
||||
a, b = placements[a_id], placements[b_id]
|
||||
dist = math.sqrt(
|
||||
(a["position"]["x"] - b["position"]["x"]) ** 2
|
||||
+ (a["position"]["y"] - b["position"]["y"]) ** 2
|
||||
)
|
||||
# 应该远小于对角线（workflow minimize_distance 约束）
|
||||
assert dist < max_diagonal * 0.8, (
|
||||
f"Workflow pair {a_id}↔{b_id} distance {dist:.2f}m "
|
||||
f"exceeds 80% of diagonal {max_diagonal:.2f}m"
|
||||
)
|
||||
|
||||
|
||||
class TestPipelineStageIsolation:
|
||||
"""Verify each stage's output format is valid input for the next stage."""
|
||||
|
||||
def test_interpret_output_schema_matches_optimize_input(self):
|
||||
"""constraints from /interpret have all fields /optimize expects."""
|
||||
resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
data = resp.json()
|
||||
|
||||
for c in data["constraints"]:
|
||||
assert "type" in c
|
||||
assert "rule_name" in c
|
||||
assert "params" in c
|
||||
assert "weight" in c
|
||||
assert c["type"] in ("hard", "soft")
|
||||
|
||||
for edge in data["workflow_edges"]:
|
||||
assert isinstance(edge, list)
|
||||
assert len(edge) == 2
|
||||
|
||||
def test_round_trip_no_data_loss(self):
|
||||
"""Interpret → optimize → check that all device IDs survive the pipeline."""
|
||||
interpret_resp = client.post("/interpret", json={"intents": LLM_INTENTS})
|
||||
interpret_data = interpret_resp.json()
|
||||
|
||||
optimize_resp = client.post("/optimize", json={
|
||||
"devices": PCR_DEVICES,
|
||||
"lab": PCR_LAB,
|
||||
"constraints": interpret_data["constraints"],
|
||||
"workflow_edges": interpret_data["workflow_edges"],
|
||||
"run_de": False,
|
||||
})
|
||||
result_ids = {p["device_id"] for p in optimize_resp.json()["placements"]}
|
||||
input_ids = {d["id"] for d in PCR_DEVICES}
|
||||
assert result_ids == input_ids
|
||||
@@ -1,210 +0,0 @@
|
||||
"""Intent interpreter tests — PCR workflow devices."""
|
||||
import pytest
|
||||
|
||||
from ..intent_interpreter import interpret_intents
|
||||
from ..models import Intent
|
||||
|
||||
|
||||
# --- reachable_by ---
|
||||
|
||||
def test_reachable_by_generates_hard_reachability():
|
||||
intents = [Intent(
|
||||
intent="reachable_by",
|
||||
params={"arm": "arm_slider", "targets": ["opentrons_liquid_handler", "inheco_odtc_96xl"]},
|
||||
description="Robot arm must reach liquid handler and thermal cycler",
|
||||
)]
|
||||
result = interpret_intents(intents)
|
||||
assert len(result.constraints) == 2
|
||||
assert all(c.rule_name == "reachability" for c in result.constraints)
|
||||
assert all(c.type == "hard" for c in result.constraints)
|
||||
assert result.constraints[0].params == {"arm_id": "arm_slider", "target_device_id": "opentrons_liquid_handler"}
|
||||
assert result.constraints[1].params == {"arm_id": "arm_slider", "target_device_id": "inheco_odtc_96xl"}
|
||||
assert len(result.translations) == 1
|
||||
assert len(result.translations[0]["generated_constraints"]) == 2
|
||||
|
||||
|
||||
def test_reachable_by_missing_arm():
|
||||
result = interpret_intents([Intent(intent="reachable_by", params={"targets": ["a"]})])
|
||||
assert len(result.constraints) == 0
|
||||
assert len(result.errors) == 1
|
||||
assert "arm" in result.errors[0].lower()
|
||||
|
||||
|
||||
def test_reachable_by_empty_targets():
|
||||
result = interpret_intents([Intent(intent="reachable_by", params={"arm": "arm_slider", "targets": []})])
|
||||
assert len(result.constraints) == 0
|
||||
assert len(result.errors) == 1
|
||||
assert "targets" in result.errors[0].lower()
|
||||
|
||||
|
||||
# --- close_together ---
|
||||
|
||||
def test_close_together_generates_minimize_distance():
|
||||
intents = [Intent(intent="close_together", params={
|
||||
"devices": ["opentrons_liquid_handler", "inheco_odtc_96xl", "agilent_plateloc"],
|
||||
})]
|
||||
result = interpret_intents(intents)
|
||||
assert len(result.constraints) == 3 # C(3,2) = 3 pairs
|
||||
assert all(c.rule_name == "minimize_distance" for c in result.constraints)
|
||||
assert all(c.type == "soft" for c in result.constraints)
|
||||
|
||||
|
||||
def test_close_together_priority_scales_weight():
|
||||
low = interpret_intents([Intent(intent="close_together", params={"devices": ["a", "b"], "priority": "low"})])
|
||||
high = interpret_intents([Intent(intent="close_together", params={"devices": ["a", "b"], "priority": "high"})])
|
||||
assert high.constraints[0].weight > low.constraints[0].weight
|
||||
assert high.constraints[0].weight == pytest.approx(16.0)
|
||||
assert low.constraints[0].weight == pytest.approx(0.5)
|
||||
|
||||
|
||||
def test_close_together_single_device_error():
|
||||
result = interpret_intents([Intent(intent="close_together", params={"devices": ["a"]})])
|
||||
assert len(result.errors) == 1
|
||||
|
||||
|
||||
# --- far_apart ---
|
||||
|
||||
def test_far_apart_generates_maximize_distance():
|
||||
result = interpret_intents([Intent(intent="far_apart", params={
|
||||
"devices": ["inheco_odtc_96xl", "thermo_orbitor_rs2_hotel"],
|
||||
})])
|
||||
assert len(result.constraints) == 1
|
||||
assert result.constraints[0].rule_name == "maximize_distance"
|
||||
|
||||
|
||||
# --- max_distance / min_distance ---
|
||||
|
||||
def test_max_distance_generates_distance_less_than():
|
||||
result = interpret_intents([Intent(intent="max_distance", params={
|
||||
"device_a": "opentrons_liquid_handler", "device_b": "inheco_odtc_96xl", "distance": 1.5,
|
||||
})])
|
||||
assert len(result.constraints) == 1
|
||||
c = result.constraints[0]
|
||||
assert c.rule_name == "distance_less_than"
|
||||
assert c.type == "hard"
|
||||
assert c.params["distance"] == 1.5
|
||||
|
||||
|
||||
def test_min_distance_generates_distance_greater_than():
|
||||
result = interpret_intents([Intent(intent="min_distance", params={
|
||||
"device_a": "inheco_odtc_96xl", "device_b": "thermo_orbitor_rs2_hotel", "distance": 2.0,
|
||||
})])
|
||||
c = result.constraints[0]
|
||||
assert c.rule_name == "distance_greater_than"
|
||||
assert c.type == "hard"
|
||||
assert c.params["distance"] == 2.0
|
||||
|
||||
|
||||
def test_max_distance_zero_is_valid():
|
||||
"""distance=0 is falsy but valid — must not be rejected."""
|
||||
result = interpret_intents([Intent(intent="max_distance", params={
|
||||
"device_a": "a", "device_b": "b", "distance": 0,
|
||||
})])
|
||||
assert len(result.constraints) == 1
|
||||
assert len(result.errors) == 0
|
||||
|
||||
|
||||
def test_max_distance_missing_param():
|
||||
result = interpret_intents([Intent(intent="max_distance", params={"device_a": "a"})])
|
||||
assert len(result.errors) == 1
|
||||
assert len(result.constraints) == 0
|
||||
|
||||
|
||||
# --- orientation ---
|
||||
|
||||
def test_face_outward():
|
||||
result = interpret_intents([Intent(intent="face_outward")])
|
||||
assert result.constraints[0].rule_name == "prefer_orientation_mode"
|
||||
assert result.constraints[0].params["mode"] == "outward"
|
||||
|
||||
|
||||
def test_face_inward():
|
||||
result = interpret_intents([Intent(intent="face_inward")])
|
||||
assert result.constraints[0].params["mode"] == "inward"
|
||||
|
||||
|
||||
def test_align_cardinal():
|
||||
result = interpret_intents([Intent(intent="align_cardinal")])
|
||||
assert result.constraints[0].rule_name == "prefer_aligned"
|
||||
assert result.constraints[0].weight == pytest.approx(0.5)
|
||||
|
||||
|
||||
def test_keep_adjacent_generates_minimize_distance():
|
||||
result = interpret_intents([Intent(intent="keep_adjacent", params={
|
||||
"devices": ["opentrons_liquid_handler", "agilent_plateloc"],
|
||||
"priority": "high",
|
||||
})])
|
||||
assert len(result.constraints) == 1
|
||||
assert result.constraints[0].rule_name == "minimize_distance"
|
||||
assert result.constraints[0].weight == pytest.approx(16.0)
|
||||
|
||||
|
||||
# --- min_spacing ---
|
||||
|
||||
def test_min_spacing():
|
||||
result = interpret_intents([Intent(intent="min_spacing", params={"min_gap": 0.3})])
|
||||
c = result.constraints[0]
|
||||
assert c.rule_name == "min_spacing"
|
||||
assert c.type == "hard"
|
||||
assert c.params["min_gap"] == 0.3
|
||||
|
||||
|
||||
# --- workflow_hint (PCR scenario) ---
|
||||
|
||||
def test_workflow_hint_pcr():
|
||||
"""PCR workflow: pipette → thermal cycler → plate sealer → storage."""
|
||||
intents = [Intent(
|
||||
intent="workflow_hint",
|
||||
params={
|
||||
"workflow": "pcr",
|
||||
"devices": [
|
||||
"opentrons_liquid_handler",
|
||||
"inheco_odtc_96xl",
|
||||
"agilent_plateloc",
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
],
|
||||
},
|
||||
)]
|
||||
result = interpret_intents(intents)
|
||||
assert len(result.constraints) == 3 # 4 devices → 3 consecutive pairs
|
||||
assert all(c.rule_name == "minimize_distance" for c in result.constraints)
|
||||
assert len(result.workflow_edges) == 3
|
||||
assert ["opentrons_liquid_handler", "inheco_odtc_96xl"] in result.workflow_edges
|
||||
assert result.translations[0]["confidence"] == "low"
|
||||
|
||||
|
||||
def test_workflow_hint_single_device_error():
|
||||
result = interpret_intents([Intent(intent="workflow_hint", params={"workflow": "test", "devices": ["a"]})])
|
||||
assert len(result.errors) == 1
|
||||
|
||||
|
||||
# --- unknown intent ---
|
||||
|
||||
def test_unknown_intent():
|
||||
result = interpret_intents([Intent(intent="nonexistent")])
|
||||
assert len(result.constraints) == 0
|
||||
assert len(result.errors) == 1
|
||||
assert "nonexistent" in result.errors[0]
|
||||
|
||||
|
||||
# --- multi-intent combination ---
|
||||
|
||||
def test_full_pcr_scenario():
|
||||
"""Arm reachability + close together for full PCR setup."""
|
||||
intents = [
|
||||
Intent(intent="reachable_by", params={
|
||||
"arm": "arm_slider",
|
||||
"targets": [
|
||||
"opentrons_liquid_handler", "inheco_odtc_96xl",
|
||||
"agilent_plateloc", "thermo_orbitor_rs2_hotel",
|
||||
],
|
||||
}),
|
||||
Intent(intent="close_together", params={
|
||||
"devices": ["opentrons_liquid_handler", "inheco_odtc_96xl"],
|
||||
"priority": "high",
|
||||
}),
|
||||
]
|
||||
result = interpret_intents(intents)
|
||||
assert len(result.constraints) == 5 # 4 reachability + 1 minimize_distance
|
||||
assert len(result.translations) == 2
|
||||
assert len(result.errors) == 0
|
||||
@@ -1,134 +0,0 @@
|
||||
"""Tests for /interpret and /interpret/schema API endpoints."""
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from ..server import app
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
|
||||
def test_interpret_reachable_by():
|
||||
resp = client.post("/interpret", json={
|
||||
"intents": [
|
||||
{
|
||||
"intent": "reachable_by",
|
||||
"params": {
|
||||
"arm": "arm_slider",
|
||||
"targets": ["opentrons_liquid_handler", "inheco_odtc_96xl"],
|
||||
},
|
||||
"description": "Arm must reach liquid handler and thermal cycler",
|
||||
}
|
||||
]
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert len(data["constraints"]) == 2
|
||||
assert all(c["rule_name"] == "reachability" for c in data["constraints"])
|
||||
assert len(data["translations"]) == 1
|
||||
assert data["translations"][0]["source_intent"] == "reachable_by"
|
||||
assert len(data["errors"]) == 0
|
||||
|
||||
|
||||
def test_interpret_pcr_workflow():
|
||||
"""Full PCR: reachability + workflow_hint + close_together."""
|
||||
resp = client.post("/interpret", json={
|
||||
"intents": [
|
||||
{
|
||||
"intent": "reachable_by",
|
||||
"params": {
|
||||
"arm": "arm_slider",
|
||||
"targets": [
|
||||
"opentrons_liquid_handler",
|
||||
"inheco_odtc_96xl",
|
||||
"agilent_plateloc",
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
],
|
||||
},
|
||||
},
|
||||
{
|
||||
"intent": "workflow_hint",
|
||||
"params": {
|
||||
"workflow": "pcr",
|
||||
"devices": [
|
||||
"opentrons_liquid_handler",
|
||||
"inheco_odtc_96xl",
|
||||
"agilent_plateloc",
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
],
|
||||
},
|
||||
},
|
||||
{
|
||||
"intent": "close_together",
|
||||
"params": {
|
||||
"devices": ["opentrons_liquid_handler", "inheco_odtc_96xl"],
|
||||
"priority": "high",
|
||||
},
|
||||
},
|
||||
]
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
# 4 reachability + 3 workflow + 1 close = 8
|
||||
assert len(data["constraints"]) == 8
|
||||
assert len(data["workflow_edges"]) == 3
|
||||
assert len(data["translations"]) == 3
|
||||
assert len(data["errors"]) == 0
|
||||
|
||||
|
||||
def test_interpret_returns_errors_for_bad_intents():
|
||||
resp = client.post("/interpret", json={
|
||||
"intents": [
|
||||
{"intent": "reachable_by", "params": {}},
|
||||
{"intent": "nonexistent_intent"},
|
||||
]
|
||||
})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert len(data["errors"]) == 2
|
||||
assert len(data["constraints"]) == 0
|
||||
|
||||
|
||||
def test_interpret_empty_intents():
|
||||
resp = client.post("/interpret", json={"intents": []})
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["constraints"] == []
|
||||
assert data["translations"] == []
|
||||
assert data["errors"] == []
|
||||
|
||||
|
||||
def test_interpret_schema_returns_all_intents():
|
||||
resp = client.get("/interpret/schema")
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
intents = data["intents"]
|
||||
expected = {
|
||||
"reachable_by", "close_together", "far_apart", "keep_adjacent",
|
||||
"max_distance", "min_distance", "min_spacing",
|
||||
"workflow_hint", "face_outward", "face_inward", "align_cardinal",
|
||||
}
|
||||
assert set(intents.keys()) == expected
|
||||
|
||||
|
||||
def test_interpret_constraints_passable_to_optimize():
|
||||
"""Constraints from /interpret should be directly usable in /optimize."""
|
||||
# Step 1: interpret
|
||||
interpret_resp = client.post("/interpret", json={
|
||||
"intents": [
|
||||
{"intent": "close_together", "params": {"devices": ["dev_a", "dev_b"]}},
|
||||
]
|
||||
})
|
||||
constraints = interpret_resp.json()["constraints"]
|
||||
|
||||
# Step 2: pass to optimize (verify it accepts the format)
|
||||
optimize_resp = client.post("/optimize", json={
|
||||
"devices": [
|
||||
{"id": "dev_a", "name": "Device A", "size": [0.5, 0.4]},
|
||||
{"id": "dev_b", "name": "Device B", "size": [0.5, 0.4]},
|
||||
],
|
||||
"lab": {"width": 4.0, "depth": 3.0},
|
||||
"constraints": constraints,
|
||||
"run_de": False,
|
||||
})
|
||||
assert optimize_resp.status_code == 200
|
||||
assert len(optimize_resp.json()["placements"]) == 2
|
||||
@@ -1,277 +0,0 @@
|
||||
"""LLM 技能文档测试：用真实 LLM 验证模糊用户输入 → 结构化意图的翻译质量。
|
||||
|
||||
需要 ANTHROPIC_API_KEY 环境变量。无 key 时自动跳过。
|
||||
测试覆盖：设备名模糊匹配、工作流顺序推理、约束类型选择、JSON 格式正确性。
|
||||
"""
|
||||
import json
|
||||
import os
|
||||
|
||||
import pytest
|
||||
|
||||
HAS_API_KEY = bool(os.environ.get("ANTHROPIC_API_KEY"))
|
||||
pytestmark = pytest.mark.skipif(not HAS_API_KEY, reason="ANTHROPIC_API_KEY not set")
|
||||
|
||||
# 读取技能文档
|
||||
_SKILL_DOC_PATH = os.path.join(
|
||||
os.path.dirname(__file__), "..", "llm_skill", "layout_intent_translator.md"
|
||||
)
|
||||
|
||||
# PCR 场景设备列表（模拟用户场景中已有的设备）
|
||||
SCENE_DEVICE_LIST = """\
|
||||
Devices in scene:
|
||||
- thermo_orbitor_rs2_hotel: Thermo Orbitor RS2 Hotel (type: static, bbox: 0.68×0.52m)
|
||||
- arm_slider: Arm Slider (type: articulation, bbox: 1.20×0.30m)
|
||||
- opentrons_liquid_handler: Opentrons Liquid Handler (type: static, bbox: 0.65×0.60m)
|
||||
- agilent_plateloc: Agilent PlateLoc (type: static, bbox: 0.35×0.40m)
|
||||
- inheco_odtc_96xl: Inheco ODTC 96XL (type: static, bbox: 0.30×0.35m)
|
||||
"""
|
||||
|
||||
VALID_DEVICE_IDS = {
|
||||
"thermo_orbitor_rs2_hotel",
|
||||
"arm_slider",
|
||||
"opentrons_liquid_handler",
|
||||
"agilent_plateloc",
|
||||
"inheco_odtc_96xl",
|
||||
}
|
||||
|
||||
VALID_INTENT_TYPES = {
|
||||
"reachable_by", "close_together", "far_apart", "max_distance",
|
||||
"min_distance", "min_spacing", "workflow_hint",
|
||||
"face_outward", "face_inward", "align_cardinal",
|
||||
}
|
||||
|
||||
|
||||
def _call_llm(user_message: str) -> dict:
|
||||
"""调用 LLM，使用技能文档作为 system prompt，返回解析后的 JSON。"""
|
||||
import anthropic
|
||||
|
||||
with open(_SKILL_DOC_PATH) as f:
|
||||
skill_doc = f.read()
|
||||
|
||||
client = anthropic.Anthropic()
|
||||
response = client.messages.create(
|
||||
model="claude-sonnet-4-20250514",
|
||||
max_tokens=2000,
|
||||
system=skill_doc,
|
||||
messages=[
|
||||
{"role": "user", "content": f"{SCENE_DEVICE_LIST}\n\n{user_message}"},
|
||||
],
|
||||
)
|
||||
|
||||
# 从 response 中提取 JSON
|
||||
text = response.content[0].text
|
||||
# LLM 可能返回 ```json ... ``` 包裹的 JSON
|
||||
if "```json" in text:
|
||||
text = text.split("```json")[1].split("```")[0]
|
||||
elif "```" in text:
|
||||
text = text.split("```")[1].split("```")[0]
|
||||
|
||||
return json.loads(text.strip())
|
||||
|
||||
|
||||
def _extract_all_device_ids(intents: list[dict]) -> set[str]:
|
||||
"""从意图列表中提取所有引用的设备 ID。"""
|
||||
ids = set()
|
||||
for intent in intents:
|
||||
params = intent.get("params", {})
|
||||
if "arm" in params:
|
||||
ids.add(params["arm"])
|
||||
for key in ("targets", "devices"):
|
||||
if key in params:
|
||||
ids.update(params[key])
|
||||
for key in ("device_a", "device_b"):
|
||||
if key in params:
|
||||
ids.add(params[key])
|
||||
return ids
|
||||
|
||||
|
||||
class TestLLMFuzzyDeviceResolution:
|
||||
"""测试 LLM 能否将模糊设备名映射到精确 ID。"""
|
||||
|
||||
def test_pcr_machine_resolves_to_inheco(self):
|
||||
"""'PCR machine' 应解析为 inheco_odtc_96xl。"""
|
||||
result = _call_llm(
|
||||
"Keep the PCR machine close to the plate sealer"
|
||||
)
|
||||
intents = result["intents"]
|
||||
all_ids = _extract_all_device_ids(intents)
|
||||
assert "inheco_odtc_96xl" in all_ids, f"Expected inheco_odtc_96xl in {all_ids}"
|
||||
assert "agilent_plateloc" in all_ids, f"Expected agilent_plateloc in {all_ids}"
|
||||
|
||||
def test_robot_resolves_to_articulation_type(self):
|
||||
"""'the robot' / 'robot arm' 应解析为 arm_slider（唯一 articulation 类型）。"""
|
||||
result = _call_llm(
|
||||
"The robot should be able to reach the liquid handler and the storage hotel"
|
||||
)
|
||||
intents = result["intents"]
|
||||
all_ids = _extract_all_device_ids(intents)
|
||||
assert "arm_slider" in all_ids, f"Expected arm_slider in {all_ids}"
|
||||
assert "opentrons_liquid_handler" in all_ids
|
||||
assert "thermo_orbitor_rs2_hotel" in all_ids
|
||||
|
||||
def test_all_resolved_ids_are_valid(self):
|
||||
"""LLM 输出的所有设备 ID 必须来自场景设备列表。"""
|
||||
result = _call_llm(
|
||||
"Take plate from hotel, prepare sample in the pipetting robot, "
|
||||
"seal it, then run thermal cycling. The arm handles all transfers."
|
||||
)
|
||||
intents = result["intents"]
|
||||
all_ids = _extract_all_device_ids(intents)
|
||||
invalid = all_ids - VALID_DEVICE_IDS
|
||||
assert not invalid, f"LLM produced invalid device IDs: {invalid}"
|
||||
|
||||
|
||||
class TestLLMWorkflowInterpretation:
|
||||
"""测试 LLM 对工作流描述的理解和翻译。"""
|
||||
|
||||
def test_pcr_workflow_full(self):
|
||||
"""完整 PCR 工作流描述应生成 reachable_by + workflow_hint + close_together。"""
|
||||
result = _call_llm(
|
||||
"I need to set up a PCR workflow: take plate from the hotel, "
|
||||
"prepare the sample in the liquid handler, seal the plate, "
|
||||
"then run the thermal cycler. The robot arm handles all plate transfers. "
|
||||
"Keep the liquid handler and sealer close together."
|
||||
)
|
||||
intents = result["intents"]
|
||||
intent_types = {i["intent"] for i in intents}
|
||||
|
||||
# 应包含核心意图类型
|
||||
assert "reachable_by" in intent_types, f"Missing reachable_by in {intent_types}"
|
||||
assert "workflow_hint" in intent_types, f"Missing workflow_hint in {intent_types}"
|
||||
|
||||
# reachable_by 应包含所有工作流设备作为 targets
|
||||
reach_intents = [i for i in intents if i["intent"] == "reachable_by"]
|
||||
assert len(reach_intents) >= 1
|
||||
reach_targets = set()
|
||||
for ri in reach_intents:
|
||||
reach_targets.update(ri["params"].get("targets", []))
|
||||
# 至少液体处理器和热循环仪应在可达范围内
|
||||
assert "opentrons_liquid_handler" in reach_targets
|
||||
assert "inheco_odtc_96xl" in reach_targets
|
||||
|
||||
def test_workflow_device_order(self):
|
||||
"""workflow_hint 的设备顺序应反映工作流步骤。"""
|
||||
result = _call_llm(
|
||||
"PCR process: first the hotel dispenses a plate, then the opentrons "
|
||||
"prepares the sample, next the plateloc seals it, finally the thermal "
|
||||
"cycler runs PCR. Generate a workflow hint."
|
||||
)
|
||||
intents = result["intents"]
|
||||
wf_intents = [i for i in intents if i["intent"] == "workflow_hint"]
|
||||
assert len(wf_intents) >= 1, f"No workflow_hint found in {[i['intent'] for i in intents]}"
|
||||
|
||||
devices = wf_intents[0]["params"]["devices"]
|
||||
# 验证顺序：hotel → liquid_handler → plateloc → thermal_cycler
|
||||
hotel_idx = devices.index("thermo_orbitor_rs2_hotel")
|
||||
lh_idx = devices.index("opentrons_liquid_handler")
|
||||
seal_idx = devices.index("agilent_plateloc")
|
||||
tc_idx = devices.index("inheco_odtc_96xl")
|
||||
assert hotel_idx < lh_idx < seal_idx < tc_idx, (
|
||||
f"Wrong workflow order: {devices}"
|
||||
)
|
||||
|
||||
|
||||
class TestLLMOutputFormat:
|
||||
"""测试 LLM 输出格式的正确性。"""
|
||||
|
||||
def test_output_has_intents_array(self):
|
||||
"""输出必须有 intents 数组。"""
|
||||
result = _call_llm("Keep all devices at least 30cm apart")
|
||||
assert "intents" in result
|
||||
assert isinstance(result["intents"], list)
|
||||
assert len(result["intents"]) > 0
|
||||
|
||||
def test_each_intent_has_required_fields(self):
|
||||
"""每个意图必须有 intent、params、description。"""
|
||||
result = _call_llm(
|
||||
"The robot arm should reach the liquid handler. "
|
||||
"Keep the thermal cycler away from the plate hotel."
|
||||
)
|
||||
for intent in result["intents"]:
|
||||
assert "intent" in intent, f"Missing 'intent' field: {intent}"
|
||||
assert "params" in intent, f"Missing 'params' field: {intent}"
|
||||
assert "description" in intent, f"Missing 'description' field: {intent}"
|
||||
|
||||
def test_intent_types_are_valid(self):
|
||||
"""所有意图类型必须是已知类型。"""
|
||||
result = _call_llm(
|
||||
"Set up a compact PCR line: hotel → liquid handler → sealer → thermal cycler. "
|
||||
"Robot arm handles transfers. Align everything neatly."
|
||||
)
|
||||
for intent in result["intents"]:
|
||||
assert intent["intent"] in VALID_INTENT_TYPES, (
|
||||
f"Unknown intent type: {intent['intent']}"
|
||||
)
|
||||
|
||||
|
||||
class TestLLMInterpretThenOptimize:
|
||||
"""端到端：LLM 翻译 → /interpret → /optimize → 验证布局。"""
|
||||
|
||||
def test_llm_output_accepted_by_interpret_endpoint(self):
|
||||
"""LLM 输出应能直接被 /interpret 端点接受。"""
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from ..server import app
|
||||
|
||||
test_client = TestClient(app)
|
||||
|
||||
llm_result = _call_llm(
|
||||
"Take plate from hotel, prepare sample in opentrons, "
|
||||
"seal plate then pcr cycle, arm_slider handles all transfers. "
|
||||
"Keep liquid handler and sealer close."
|
||||
)
|
||||
|
||||
# /interpret 应接受 LLM 输出
|
||||
resp = test_client.post("/interpret", json=llm_result)
|
||||
assert resp.status_code == 200, f"Interpret failed: {resp.text}"
|
||||
data = resp.json()
|
||||
assert len(data["constraints"]) > 0, "No constraints generated"
|
||||
assert len(data["errors"]) == 0, f"Interpretation errors: {data['errors']}"
|
||||
|
||||
def test_full_pipeline_llm_to_placement(self):
|
||||
"""LLM 翻译 → interpret → optimize → 所有设备有 placement。"""
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from ..server import app
|
||||
|
||||
test_client = TestClient(app)
|
||||
|
||||
# Stage 1: LLM 翻译
|
||||
llm_result = _call_llm(
|
||||
"I want a PCR workflow lab. Take plate from the hotel, pipette in the "
|
||||
"liquid handler, seal with the plateloc, then thermal cycle. "
|
||||
"The robot arm does all transfers between devices. "
|
||||
"Minimum 15cm gap between everything."
|
||||
)
|
||||
|
||||
# Stage 2: interpret
|
||||
interpret_resp = test_client.post("/interpret", json=llm_result)
|
||||
assert interpret_resp.status_code == 200
|
||||
interpret_data = interpret_resp.json()
|
||||
assert len(interpret_data["errors"]) == 0
|
||||
|
||||
# Stage 3: optimize
|
||||
pcr_devices = [
|
||||
{"id": "thermo_orbitor_rs2_hotel", "name": "Plate Hotel", "device_type": "static"},
|
||||
{"id": "arm_slider", "name": "Robot Arm", "device_type": "articulation"},
|
||||
{"id": "opentrons_liquid_handler", "name": "Liquid Handler", "device_type": "static"},
|
||||
{"id": "agilent_plateloc", "name": "Plate Sealer", "device_type": "static"},
|
||||
{"id": "inheco_odtc_96xl", "name": "Thermal Cycler", "device_type": "static"},
|
||||
]
|
||||
optimize_resp = test_client.post("/optimize", json={
|
||||
"devices": pcr_devices,
|
||||
"lab": {"width": 6.0, "depth": 4.0},
|
||||
"constraints": interpret_data["constraints"],
|
||||
"workflow_edges": interpret_data.get("workflow_edges", []),
|
||||
"run_de": True,
|
||||
"maxiter": 50,
|
||||
"seed": 42,
|
||||
})
|
||||
assert optimize_resp.status_code == 200
|
||||
data = optimize_resp.json()
|
||||
|
||||
# Stage 4: 验证所有设备都有 placement
|
||||
placed_ids = {p["device_id"] for p in data["placements"]}
|
||||
expected_ids = {d["id"] for d in pcr_devices}
|
||||
assert placed_ids == expected_ids
|
||||
assert data["success"] is True
|
||||
@@ -1,138 +0,0 @@
|
||||
"""MockCollisionChecker 和 MockReachabilityChecker 测试。"""
|
||||
|
||||
import math
|
||||
|
||||
from ..mock_checkers import MockCollisionChecker, MockReachabilityChecker
|
||||
|
||||
|
||||
class TestMockCollisionChecker:
|
||||
def setup_method(self):
|
||||
self.checker = MockCollisionChecker()
|
||||
|
||||
def test_no_collision_far_apart(self):
|
||||
"""两个设备距离足够远，不碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (0.5, 0.5), "pos": (3.0, 3.0, 0.0)},
|
||||
]
|
||||
assert self.checker.check(placements) == []
|
||||
|
||||
def test_collision_overlapping(self):
|
||||
"""两个设备重叠，应检测到碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (1.0, 1.0), "pos": (1.5, 1.0, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert ("a", "b") in collisions
|
||||
|
||||
def test_collision_touching_edges(self):
|
||||
"""两设备恰好边缘接触，不算碰撞（< 而非 <=）。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (0.5, 0.5, 0.0)},
|
||||
{"id": "b", "bbox": (1.0, 1.0), "pos": (1.5, 0.5, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert collisions == []
|
||||
|
||||
def test_collision_with_rotation(self):
|
||||
"""旋转后的设备 OBB 可能导致碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 0.2), "pos": (1.0, 1.0, math.pi / 4)},
|
||||
{"id": "b", "bbox": (0.5, 0.5), "pos": (1.4, 1.0, 0.0)}, # closer: OBB overlap
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert ("a", "b") in collisions
|
||||
|
||||
def test_no_collision_with_rotation(self):
|
||||
"""旋转后仍不碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 0.2), "pos": (1.0, 1.0, math.pi / 4)},
|
||||
{"id": "b", "bbox": (0.5, 0.5), "pos": (2.0, 1.0, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert collisions == []
|
||||
|
||||
def test_check_bounds_within(self):
|
||||
"""设备在边界内。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
]
|
||||
assert self.checker.check_bounds(placements, 5.0, 5.0) == []
|
||||
|
||||
def test_check_bounds_outside(self):
|
||||
"""设备超出边界。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (0.2, 0.2, 0.0)},
|
||||
]
|
||||
oob = self.checker.check_bounds(placements, 5.0, 5.0)
|
||||
assert "a" in oob
|
||||
|
||||
def test_three_devices_multiple_collisions(self):
|
||||
"""三个设备，两两碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (1.0, 1.0), "pos": (1.3, 1.0, 0.0)},
|
||||
{"id": "c", "bbox": (1.0, 1.0), "pos": (1.6, 1.0, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert ("a", "b") in collisions
|
||||
assert ("b", "c") in collisions
|
||||
|
||||
|
||||
def test_obb_collision_rotated_no_false_positive():
|
||||
"""A rotated narrow device should NOT collide with a nearby device
|
||||
that the old AABB method would have flagged as colliding.
|
||||
|
||||
Old AABB expands footprint; OBB is precise.
|
||||
"""
|
||||
checker = MockCollisionChecker()
|
||||
# Narrow device (2.0 x 0.5) rotated 45°:
|
||||
# AABB would be ~1.77 x 1.77, OBB is the actual narrow rectangle
|
||||
placements = [
|
||||
{"id": "narrow", "bbox": (2.0, 0.5), "pos": (3.0, 3.0, math.pi / 4)},
|
||||
{"id": "nearby", "bbox": (0.5, 0.5), "pos": (4.5, 3.0, 0.0)},
|
||||
]
|
||||
collisions = checker.check(placements)
|
||||
# With OBB: no collision (the narrow rotated box doesn't reach)
|
||||
assert ("narrow", "nearby") not in collisions and ("nearby", "narrow") not in collisions
|
||||
|
||||
|
||||
class TestMockReachabilityChecker:
|
||||
def setup_method(self):
|
||||
self.checker = MockReachabilityChecker()
|
||||
|
||||
def test_reachable_within_radius(self):
|
||||
"""目标在臂展半径内。"""
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 0.5, "y": 0.5, "z": 0.0}
|
||||
assert self.checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_not_reachable_outside_radius(self):
|
||||
"""目标超出臂展半径。"""
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 2.0, "y": 2.0, "z": 0.0}
|
||||
assert not self.checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_reachable_at_boundary(self):
|
||||
"""目标恰好在臂展边界上（应可达）。"""
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 0.914, "y": 0.0, "z": 0.0}
|
||||
assert self.checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_unknown_arm_uses_default(self):
|
||||
"""未知型号使用 1.0m 回退臂展（realistic lab-scale default）。"""
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
# Within 1.0m fallback reach
|
||||
target_near = {"x": 0.8, "y": 0.0, "z": 0.0}
|
||||
assert self.checker.is_reachable("unknown_arm", arm_pose, target_near)
|
||||
# Beyond 1.0m fallback reach
|
||||
target_far = {"x": 1.5, "y": 0.0, "z": 0.0}
|
||||
assert not self.checker.is_reachable("unknown_arm", arm_pose, target_far)
|
||||
|
||||
def test_custom_arm_reach(self):
|
||||
"""自定义臂展参数。"""
|
||||
checker = MockReachabilityChecker(arm_reach={"custom_arm": 1.5})
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 1.4, "y": 0.0, "z": 0.0}
|
||||
assert checker.is_reachable("custom_arm", arm_pose, target)
|
||||
@@ -1,156 +0,0 @@
|
||||
"""Tests for OBB (Oriented Bounding Box) geometry utilities."""
|
||||
import math
|
||||
import pytest
|
||||
from ..obb import obb_corners, obb_overlap, obb_min_distance, segment_obb_intersection_length
|
||||
|
||||
|
||||
class TestObbCorners:
|
||||
"""obb_corners(cx, cy, w, h, theta) → 4 corner points of the rotated rectangle."""
|
||||
|
||||
def test_no_rotation(self):
|
||||
"""Axis-aligned box at origin: corners at ±half extents."""
|
||||
corners = obb_corners(0, 0, 2.0, 1.0, 0.0)
|
||||
assert len(corners) == 4
|
||||
xs = sorted(c[0] for c in corners)
|
||||
ys = sorted(c[1] for c in corners)
|
||||
assert xs == pytest.approx([-1.0, -1.0, 1.0, 1.0])
|
||||
assert ys == pytest.approx([-0.5, -0.5, 0.5, 0.5])
|
||||
|
||||
def test_90_degree_rotation(self):
|
||||
"""90° rotation swaps width and height extents."""
|
||||
corners = obb_corners(0, 0, 2.0, 1.0, math.pi / 2)
|
||||
xs = sorted(c[0] for c in corners)
|
||||
ys = sorted(c[1] for c in corners)
|
||||
assert xs == pytest.approx([-0.5, -0.5, 0.5, 0.5])
|
||||
assert ys == pytest.approx([-1.0, -1.0, 1.0, 1.0])
|
||||
|
||||
def test_offset_center(self):
|
||||
"""Corners shift by (cx, cy)."""
|
||||
corners = obb_corners(3.0, 2.0, 2.0, 1.0, 0.0)
|
||||
xs = sorted(c[0] for c in corners)
|
||||
ys = sorted(c[1] for c in corners)
|
||||
assert xs == pytest.approx([2.0, 2.0, 4.0, 4.0])
|
||||
assert ys == pytest.approx([1.5, 1.5, 2.5, 2.5])
|
||||
|
||||
def test_45_degree_rotation(self):
|
||||
"""45° rotation: corners on diagonals."""
|
||||
corners = obb_corners(0, 0, 2.0, 2.0, math.pi / 4)
|
||||
for cx, cy in corners:
|
||||
dist = math.sqrt(cx**2 + cy**2)
|
||||
assert dist == pytest.approx(math.sqrt(2), abs=1e-9)
|
||||
|
||||
|
||||
class TestObbOverlap:
|
||||
"""obb_overlap(corners_a, corners_b) → True if the two OBBs overlap."""
|
||||
|
||||
def test_separated_boxes(self):
|
||||
"""Two boxes far apart: no overlap."""
|
||||
a = obb_corners(0, 0, 1.0, 1.0, 0.0)
|
||||
b = obb_corners(5, 0, 1.0, 1.0, 0.0)
|
||||
assert obb_overlap(a, b) is False
|
||||
|
||||
def test_overlapping_boxes(self):
|
||||
"""Two boxes sharing space: overlap."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0)
|
||||
b = obb_corners(1, 0, 2.0, 2.0, 0.0)
|
||||
assert obb_overlap(a, b) is True
|
||||
|
||||
def test_touching_edges_no_overlap(self):
|
||||
"""Boxes touching at edge: no overlap (strict <, not <=)."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0)
|
||||
b = obb_corners(2.0, 0, 2.0, 2.0, 0.0)
|
||||
assert obb_overlap(a, b) is False
|
||||
|
||||
def test_rotated_overlap(self):
|
||||
"""One box rotated 45°, overlapping the other."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0)
|
||||
b = obb_corners(1.0, 1.0, 2.0, 2.0, math.pi / 4)
|
||||
assert obb_overlap(a, b) is True
|
||||
|
||||
def test_rotated_no_overlap(self):
|
||||
"""One box rotated 45°, separated from the other."""
|
||||
a = obb_corners(0, 0, 1.0, 1.0, 0.0)
|
||||
b = obb_corners(3, 0, 1.0, 1.0, math.pi / 4)
|
||||
assert obb_overlap(a, b) is False
|
||||
|
||||
def test_identical_boxes(self):
|
||||
"""Same position and size: overlap."""
|
||||
a = obb_corners(1, 1, 1.0, 1.0, 0.0)
|
||||
b = obb_corners(1, 1, 1.0, 1.0, 0.0)
|
||||
assert obb_overlap(a, b) is True
|
||||
|
||||
|
||||
class TestObbMinDistance:
|
||||
"""obb_min_distance(corners_a, corners_b) → minimum edge-to-edge distance."""
|
||||
|
||||
def test_overlapping_returns_zero(self):
|
||||
"""Overlapping boxes: distance = 0."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0)
|
||||
b = obb_corners(1, 0, 2.0, 2.0, 0.0)
|
||||
assert obb_min_distance(a, b) == pytest.approx(0.0)
|
||||
|
||||
def test_separated_axis_aligned(self):
|
||||
"""Two axis-aligned boxes with 2m gap."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0) # edges at x=±1
|
||||
b = obb_corners(4, 0, 2.0, 2.0, 0.0) # edges at x=3,5
|
||||
# Gap = 3 - 1 = 2.0
|
||||
assert obb_min_distance(a, b) == pytest.approx(2.0)
|
||||
|
||||
def test_diagonal_separation(self):
|
||||
"""Boxes separated diagonally: distance to nearest corner."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0) # corners at (±1, ±1)
|
||||
b = obb_corners(4, 4, 2.0, 2.0, 0.0) # corners at (3..5, 3..5)
|
||||
# Nearest corners: (1,1) to (3,3) → sqrt(8) ≈ 2.828
|
||||
assert obb_min_distance(a, b) == pytest.approx(math.sqrt(8), abs=0.01)
|
||||
|
||||
def test_rotated_separation(self):
|
||||
"""One rotated box separated from axis-aligned box."""
|
||||
a = obb_corners(0, 0, 1.0, 1.0, 0.0)
|
||||
b = obb_corners(3, 0, 1.0, 1.0, math.pi / 4)
|
||||
dist = obb_min_distance(a, b)
|
||||
assert dist > 0
|
||||
|
||||
def test_touching_returns_zero(self):
|
||||
"""Touching edges: distance = 0."""
|
||||
a = obb_corners(0, 0, 2.0, 2.0, 0.0)
|
||||
b = obb_corners(2.0, 0, 2.0, 2.0, 0.0)
|
||||
assert obb_min_distance(a, b) == pytest.approx(0.0)
|
||||
|
||||
|
||||
class TestSegmentOBBIntersectionLength:
|
||||
"""segment_obb_intersection_length: Cyrus-Beck clipping."""
|
||||
|
||||
def test_segment_fully_outside(self):
|
||||
corners = obb_corners(0, 0, 2, 2, 0)
|
||||
length = segment_obb_intersection_length((-5, 3), (5, 3), corners)
|
||||
assert length == 0.0
|
||||
|
||||
def test_segment_fully_inside(self):
|
||||
corners = obb_corners(0, 0, 4, 4, 0)
|
||||
length = segment_obb_intersection_length((-0.5, 0), (0.5, 0), corners)
|
||||
assert abs(length - 1.0) < 1e-6
|
||||
|
||||
def test_segment_crosses_through(self):
|
||||
corners = obb_corners(0, 0, 2, 2, 0)
|
||||
length = segment_obb_intersection_length((-5, 0), (5, 0), corners)
|
||||
assert abs(length - 2.0) < 1e-6
|
||||
|
||||
def test_segment_partial_overlap(self):
|
||||
corners = obb_corners(0, 0, 2, 2, 0)
|
||||
length = segment_obb_intersection_length((0, 0), (5, 0), corners)
|
||||
assert abs(length - 1.0) < 1e-6
|
||||
|
||||
def test_rotated_obb(self):
|
||||
corners = obb_corners(0, 0, 2, 2, math.pi / 4)
|
||||
length = segment_obb_intersection_length((-3, 0), (3, 0), corners)
|
||||
expected = 2 * math.sqrt(2)
|
||||
assert abs(length - expected) < 1e-4
|
||||
|
||||
def test_zero_length_segment(self):
|
||||
corners = obb_corners(0, 0, 2, 2, 0)
|
||||
assert segment_obb_intersection_length((0, 0), (0, 0), corners) == 0.0
|
||||
|
||||
def test_parallel_outside(self):
|
||||
corners = obb_corners(0, 0, 2, 2, 0)
|
||||
length = segment_obb_intersection_length((-5, 2), (5, 2), corners)
|
||||
assert length == 0.0
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,430 +0,0 @@
|
||||
"""MoveItCollisionChecker 和 IKFastReachabilityChecker 测试。
|
||||
|
||||
使用 unittest.mock 模拟 MoveIt2 实例，验证适配器逻辑，
|
||||
无需 ROS2 / MoveIt2 运行环境。
|
||||
"""
|
||||
|
||||
import math
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from ..ros_checkers import (
|
||||
IKFastReachabilityChecker,
|
||||
MoveItCollisionChecker,
|
||||
_transform_to_arm_frame,
|
||||
_yaw_to_quat,
|
||||
_yaw_to_rotation_matrix,
|
||||
create_checkers,
|
||||
)
|
||||
|
||||
|
||||
# ---------- 辅助函数测试 ----------
|
||||
|
||||
|
||||
class TestYawToQuat:
|
||||
def test_zero_rotation(self):
|
||||
"""零旋转 → 单位四元数。"""
|
||||
q = _yaw_to_quat(0.0)
|
||||
assert q == pytest.approx((0.0, 0.0, 0.0, 1.0))
|
||||
|
||||
def test_90_degrees(self):
|
||||
"""90° → (0, 0, sin(π/4), cos(π/4))。"""
|
||||
q = _yaw_to_quat(math.pi / 2)
|
||||
expected = (0.0, 0.0, math.sin(math.pi / 4), math.cos(math.pi / 4))
|
||||
assert q == pytest.approx(expected)
|
||||
|
||||
def test_180_degrees(self):
|
||||
"""180° → (0, 0, 1, 0)。"""
|
||||
q = _yaw_to_quat(math.pi)
|
||||
assert q == pytest.approx((0.0, 0.0, 1.0, 0.0), abs=1e-10)
|
||||
|
||||
|
||||
class TestTransformToArmFrame:
|
||||
def test_identity_transform(self):
|
||||
"""臂在原点无旋转，目标在 (1, 0, 0.5)。"""
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 1.0, "y": 0.0, "z": 0.5}
|
||||
local = _transform_to_arm_frame(arm_pose, target)
|
||||
assert local == pytest.approx((1.0, 0.0, 0.5))
|
||||
|
||||
def test_translation_only(self):
|
||||
"""臂在 (2, 3) 无旋转，目标在 (3, 4, 0)。"""
|
||||
arm_pose = {"x": 2.0, "y": 3.0, "theta": 0.0}
|
||||
target = {"x": 3.0, "y": 4.0, "z": 0.0}
|
||||
local = _transform_to_arm_frame(arm_pose, target)
|
||||
assert local == pytest.approx((1.0, 1.0, 0.0))
|
||||
|
||||
def test_rotation_90(self):
|
||||
"""臂旋转 90°，目标在臂前方。"""
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": math.pi / 2}
|
||||
target = {"x": 0.0, "y": 1.0, "z": 0.0}
|
||||
local = _transform_to_arm_frame(arm_pose, target)
|
||||
# 世界 Y+ 在臂坐标系中变成 X+
|
||||
assert local[0] == pytest.approx(1.0, abs=1e-10)
|
||||
assert local[1] == pytest.approx(0.0, abs=1e-10)
|
||||
|
||||
|
||||
class TestYawToRotationMatrix:
|
||||
def test_identity(self):
|
||||
"""零旋转 → 单位矩阵。"""
|
||||
R = _yaw_to_rotation_matrix(0.0)
|
||||
np.testing.assert_allclose(R, np.eye(3), atol=1e-10)
|
||||
|
||||
def test_90_degrees(self):
|
||||
"""90° 旋转矩阵。"""
|
||||
R = _yaw_to_rotation_matrix(math.pi / 2)
|
||||
expected = np.array([
|
||||
[0.0, -1.0, 0.0],
|
||||
[1.0, 0.0, 0.0],
|
||||
[0.0, 0.0, 1.0],
|
||||
])
|
||||
np.testing.assert_allclose(R, expected, atol=1e-10)
|
||||
|
||||
|
||||
# ---------- MoveItCollisionChecker 测试 ----------
|
||||
|
||||
|
||||
class TestMoveItCollisionChecker:
|
||||
def setup_method(self):
|
||||
self.moveit2 = MagicMock()
|
||||
# 禁用 FCL，使用 OBB 回退（测试环境无需 python-fcl）
|
||||
self.checker = MoveItCollisionChecker(
|
||||
self.moveit2, sync_to_scene=True,
|
||||
)
|
||||
self.checker._fcl_available = False
|
||||
|
||||
def test_no_collision_far_apart(self):
|
||||
"""两个设备距离足够远，不碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (0.5, 0.5), "pos": (3.0, 3.0, 0.0)},
|
||||
]
|
||||
assert self.checker.check(placements) == []
|
||||
|
||||
def test_collision_overlapping(self):
|
||||
"""两个设备重叠，应检测到碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (1.0, 1.0), "pos": (1.5, 1.0, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert ("a", "b") in collisions
|
||||
|
||||
def test_collision_with_rotation(self):
|
||||
"""旋转后的碰撞检测。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 0.2), "pos": (1.0, 1.0, math.pi / 4)},
|
||||
{"id": "b", "bbox": (0.5, 0.5), "pos": (1.4, 1.0, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert ("a", "b") in collisions
|
||||
|
||||
def test_syncs_collision_objects(self):
|
||||
"""验证 check() 调用 add_collision_box 同步到 MoveIt2。"""
|
||||
placements = [
|
||||
{"id": "dev_a", "bbox": (0.6, 0.8), "pos": (1.0, 2.0, 0.5)},
|
||||
]
|
||||
self.checker.check(placements)
|
||||
|
||||
self.moveit2.add_collision_box.assert_called_once()
|
||||
call_kwargs = self.moveit2.add_collision_box.call_args
|
||||
# 验证使用 {device_id}_ 前缀
|
||||
assert call_kwargs.kwargs["id"] == "dev_a_"
|
||||
# 验证 size = (w, d, h)
|
||||
assert call_kwargs.kwargs["size"] == (0.6, 0.8, 0.4)
|
||||
|
||||
def test_device_id_prefix(self):
|
||||
"""碰撞对象名称使用 {device_id}_ 前缀。"""
|
||||
placements = [
|
||||
{"id": "robot_arm", "bbox": (0.3, 0.3), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "centrifuge", "bbox": (0.5, 0.5), "pos": (3.0, 3.0, 0.0)},
|
||||
]
|
||||
self.checker.check(placements)
|
||||
|
||||
calls = self.moveit2.add_collision_box.call_args_list
|
||||
ids = [c.kwargs["id"] for c in calls]
|
||||
assert "robot_arm_" in ids
|
||||
assert "centrifuge_" in ids
|
||||
|
||||
def test_sync_failure_does_not_crash(self):
|
||||
"""add_collision_box 异常不影响碰撞检测结果。"""
|
||||
self.moveit2.add_collision_box.side_effect = RuntimeError("service unavailable")
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (0.5, 0.5), "pos": (3.0, 3.0, 0.0)},
|
||||
]
|
||||
# 不应抛异常
|
||||
collisions = self.checker.check(placements)
|
||||
assert collisions == []
|
||||
|
||||
def test_check_bounds_within(self):
|
||||
"""设备在边界内。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
]
|
||||
assert self.checker.check_bounds(placements, 5.0, 5.0) == []
|
||||
|
||||
def test_check_bounds_outside(self):
|
||||
"""设备超出边界。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (0.2, 0.2, 0.0)},
|
||||
]
|
||||
oob = self.checker.check_bounds(placements, 5.0, 5.0)
|
||||
assert "a" in oob
|
||||
|
||||
def test_no_sync_mode(self):
|
||||
"""sync_to_scene=False 时不调用 add_collision_box。"""
|
||||
checker = MoveItCollisionChecker(
|
||||
self.moveit2, sync_to_scene=False,
|
||||
)
|
||||
checker._fcl_available = False
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
]
|
||||
checker.check(placements)
|
||||
self.moveit2.add_collision_box.assert_not_called()
|
||||
|
||||
def test_touching_edges_no_collision(self):
|
||||
"""恰好边缘接触，不算碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (0.5, 0.5, 0.0)},
|
||||
{"id": "b", "bbox": (1.0, 1.0), "pos": (1.5, 0.5, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert collisions == []
|
||||
|
||||
def test_three_devices_multiple_collisions(self):
|
||||
"""三个设备，相邻碰撞。"""
|
||||
placements = [
|
||||
{"id": "a", "bbox": (1.0, 1.0), "pos": (1.0, 1.0, 0.0)},
|
||||
{"id": "b", "bbox": (1.0, 1.0), "pos": (1.3, 1.0, 0.0)},
|
||||
{"id": "c", "bbox": (1.0, 1.0), "pos": (1.6, 1.0, 0.0)},
|
||||
]
|
||||
collisions = self.checker.check(placements)
|
||||
assert ("a", "b") in collisions
|
||||
assert ("b", "c") in collisions
|
||||
|
||||
|
||||
# ---------- IKFastReachabilityChecker 测试 ----------
|
||||
|
||||
|
||||
class TestIKFastReachabilityCheckerVoxel:
|
||||
"""体素图模式测试。"""
|
||||
|
||||
def _create_voxel_dir(self, tmp_path: Path, arm_id: str = "elite_cs66") -> Path:
|
||||
"""创建包含体素图的临时目录。"""
|
||||
# 创建一个简单的体素网格：中心区域可达
|
||||
grid = np.zeros((100, 100, 50), dtype=bool)
|
||||
# 标记中心 60x60x30 区域为可达
|
||||
grid[20:80, 20:80, 10:40] = True
|
||||
|
||||
origin = np.array([-0.5, -0.5, 0.0])
|
||||
resolution = 0.01
|
||||
|
||||
npz_path = tmp_path / f"{arm_id}.npz"
|
||||
np.savez(str(npz_path), grid=grid, origin=origin, resolution=resolution)
|
||||
return tmp_path
|
||||
|
||||
def test_reachable_in_voxel(self, tmp_path):
|
||||
"""目标在体素图可达区域内。"""
|
||||
voxel_dir = self._create_voxel_dir(tmp_path)
|
||||
checker = IKFastReachabilityChecker(voxel_dir=voxel_dir)
|
||||
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
# 中心区域：local = (0.0, 0.0, 0.2) → ix=50, iy=50, iz=20 → 可达
|
||||
target = {"x": 0.0, "y": 0.0, "z": 0.2}
|
||||
assert checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_not_reachable_outside_voxel(self, tmp_path):
|
||||
"""目标在体素图不可达区域。"""
|
||||
voxel_dir = self._create_voxel_dir(tmp_path)
|
||||
checker = IKFastReachabilityChecker(voxel_dir=voxel_dir)
|
||||
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
# 边缘区域：local = (-0.45, -0.45, 0.0) → ix=5, iy=5, iz=0 → 不可达
|
||||
target = {"x": -0.45, "y": -0.45, "z": 0.0}
|
||||
assert not checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_out_of_bounds_not_reachable(self, tmp_path):
|
||||
"""目标超出体素图范围。"""
|
||||
voxel_dir = self._create_voxel_dir(tmp_path)
|
||||
checker = IKFastReachabilityChecker(voxel_dir=voxel_dir)
|
||||
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 5.0, "y": 5.0, "z": 0.0}
|
||||
assert not checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_arm_rotation_transforms_target(self, tmp_path):
|
||||
"""臂旋转后目标变换到臂坐标系。"""
|
||||
voxel_dir = self._create_voxel_dir(tmp_path)
|
||||
checker = IKFastReachabilityChecker(voxel_dir=voxel_dir)
|
||||
|
||||
# 臂旋转 90°，目标在世界 Y+ 方向 → 臂坐标系 X+ 方向
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": math.pi / 2}
|
||||
# 世界 (0, 0.1, 0.2) → 臂坐标系 (0.1, 0, 0.2) → 在可达范围
|
||||
target = {"x": 0.0, "y": 0.1, "z": 0.2}
|
||||
assert checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_unknown_arm_no_voxel_no_moveit(self, tmp_path):
|
||||
"""未知臂型且无 MoveIt2，乐观返回 True。"""
|
||||
voxel_dir = self._create_voxel_dir(tmp_path)
|
||||
checker = IKFastReachabilityChecker(voxel_dir=voxel_dir)
|
||||
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 0.5, "y": 0.0, "z": 0.0}
|
||||
assert checker.is_reachable("unknown_arm", arm_pose, target)
|
||||
|
||||
def test_missing_voxel_dir(self):
|
||||
"""体素目录不存在不报错。"""
|
||||
checker = IKFastReachabilityChecker(voxel_dir="/nonexistent/path")
|
||||
assert len(checker._voxel_maps) == 0
|
||||
|
||||
|
||||
class TestIKFastReachabilityCheckerLiveIK:
|
||||
"""实时 IK 模式测试。"""
|
||||
|
||||
def test_reachable_via_ik(self):
|
||||
"""compute_ik 返回 JointState → 可达。"""
|
||||
moveit2 = MagicMock()
|
||||
moveit2.compute_ik.return_value = MagicMock() # 非 None → 成功
|
||||
|
||||
checker = IKFastReachabilityChecker(moveit2)
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 0.5, "y": 0.0, "z": 0.3}
|
||||
assert checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_not_reachable_via_ik(self):
|
||||
"""compute_ik 返回 None → 不可达。"""
|
||||
moveit2 = MagicMock()
|
||||
moveit2.compute_ik.return_value = None
|
||||
|
||||
checker = IKFastReachabilityChecker(moveit2)
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 5.0, "y": 5.0, "z": 0.0}
|
||||
assert not checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_ik_exception_returns_false(self):
|
||||
"""compute_ik 抛异常 → 不可达。"""
|
||||
moveit2 = MagicMock()
|
||||
moveit2.compute_ik.side_effect = RuntimeError("service timeout")
|
||||
|
||||
checker = IKFastReachabilityChecker(moveit2)
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 0.5, "y": 0.0, "z": 0.0}
|
||||
assert not checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
def test_ik_called_with_correct_position(self):
|
||||
"""验证 compute_ik 接收正确的臂坐标系位置。"""
|
||||
moveit2 = MagicMock()
|
||||
moveit2.compute_ik.return_value = MagicMock()
|
||||
|
||||
checker = IKFastReachabilityChecker(moveit2)
|
||||
arm_pose = {"x": 1.0, "y": 2.0, "theta": 0.0}
|
||||
target = {"x": 1.5, "y": 2.3, "z": 0.4}
|
||||
checker.is_reachable("elite_cs66", arm_pose, target)
|
||||
|
||||
call_kwargs = moveit2.compute_ik.call_args.kwargs
|
||||
assert call_kwargs["position"] == pytest.approx((0.5, 0.3, 0.4))
|
||||
|
||||
def test_voxel_takes_priority_over_live_ik(self, tmp_path):
|
||||
"""有体素图时优先使用体素查询，不调用 compute_ik。"""
|
||||
# 创建体素图
|
||||
grid = np.ones((10, 10, 10), dtype=bool)
|
||||
origin = np.array([-0.05, -0.05, 0.0])
|
||||
np.savez(
|
||||
str(tmp_path / "test_arm.npz"),
|
||||
grid=grid, origin=origin, resolution=0.01,
|
||||
)
|
||||
|
||||
moveit2 = MagicMock()
|
||||
checker = IKFastReachabilityChecker(moveit2, voxel_dir=tmp_path)
|
||||
|
||||
arm_pose = {"x": 0.0, "y": 0.0, "theta": 0.0}
|
||||
target = {"x": 0.0, "y": 0.0, "z": 0.05}
|
||||
checker.is_reachable("test_arm", arm_pose, target)
|
||||
|
||||
moveit2.compute_ik.assert_not_called()
|
||||
|
||||
|
||||
# ---------- create_checkers 工厂函数测试 ----------
|
||||
|
||||
|
||||
class TestCreateCheckers:
|
||||
def test_mock_mode(self):
|
||||
"""mock 模式返回 Mock 检测器。"""
|
||||
from ..mock_checkers import (
|
||||
MockCollisionChecker,
|
||||
MockReachabilityChecker,
|
||||
)
|
||||
|
||||
collision, reachability = create_checkers(mode="mock")
|
||||
assert isinstance(collision, MockCollisionChecker)
|
||||
assert isinstance(reachability, MockReachabilityChecker)
|
||||
|
||||
def test_moveit_mode(self):
|
||||
"""moveit 模式返回 MoveIt2 检测器。"""
|
||||
moveit2 = MagicMock()
|
||||
collision, reachability = create_checkers(moveit2, mode="moveit")
|
||||
assert isinstance(collision, MoveItCollisionChecker)
|
||||
assert isinstance(reachability, IKFastReachabilityChecker)
|
||||
|
||||
def test_moveit_mode_requires_instance(self):
|
||||
"""moveit 模式无实例时抛异常。"""
|
||||
with pytest.raises(ValueError, match="MoveIt2 instance required"):
|
||||
create_checkers(mode="moveit")
|
||||
|
||||
def test_default_mode_is_mock(self):
|
||||
"""默认使用 mock 模式。"""
|
||||
from ..mock_checkers import MockCollisionChecker
|
||||
|
||||
collision, _ = create_checkers()
|
||||
assert isinstance(collision, MockCollisionChecker)
|
||||
|
||||
def test_env_var_override(self, monkeypatch):
|
||||
"""LAYOUT_CHECKER_MODE 环境变量覆盖默认值。"""
|
||||
moveit2 = MagicMock()
|
||||
monkeypatch.setenv("LAYOUT_CHECKER_MODE", "moveit")
|
||||
collision, _ = create_checkers(moveit2)
|
||||
assert isinstance(collision, MoveItCollisionChecker)
|
||||
|
||||
|
||||
# ---------- Protocol 兼容性测试 ----------
|
||||
|
||||
|
||||
class TestProtocolConformance:
|
||||
"""验证适配器满足 Protocol 接口签名。"""
|
||||
|
||||
def test_collision_checker_has_check(self):
|
||||
"""MoveItCollisionChecker 实现 check(placements) 方法。"""
|
||||
moveit2 = MagicMock()
|
||||
checker = MoveItCollisionChecker(moveit2, sync_to_scene=False)
|
||||
checker._fcl_available = False
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
]
|
||||
result = checker.check(placements)
|
||||
assert isinstance(result, list)
|
||||
|
||||
def test_reachability_checker_has_is_reachable(self):
|
||||
"""IKFastReachabilityChecker 实现 is_reachable(arm_id, arm_pose, target) 方法。"""
|
||||
checker = IKFastReachabilityChecker()
|
||||
result = checker.is_reachable(
|
||||
"arm_id",
|
||||
{"x": 0.0, "y": 0.0, "theta": 0.0},
|
||||
{"x": 0.5, "y": 0.0, "z": 0.0},
|
||||
)
|
||||
assert isinstance(result, bool)
|
||||
|
||||
def test_collision_checker_has_check_bounds(self):
|
||||
"""MoveItCollisionChecker 实现 check_bounds 方法。"""
|
||||
moveit2 = MagicMock()
|
||||
checker = MoveItCollisionChecker(moveit2, sync_to_scene=False)
|
||||
placements = [
|
||||
{"id": "a", "bbox": (0.5, 0.5), "pos": (1.0, 1.0, 0.0)},
|
||||
]
|
||||
result = checker.check_bounds(placements, 5.0, 5.0)
|
||||
assert isinstance(result, list)
|
||||
@@ -1,113 +0,0 @@
|
||||
"""Tests for the force-directed seeder engine."""
|
||||
import math
|
||||
import pytest
|
||||
from ..seeders import SeederParams, PRESETS, seed_layout
|
||||
from ..models import Device, Lab, Placement
|
||||
|
||||
|
||||
class TestSeederParams:
|
||||
def test_presets_exist(self):
|
||||
assert "compact_outward" in PRESETS
|
||||
assert "spread_inward" in PRESETS
|
||||
assert "row_fallback" in PRESETS
|
||||
|
||||
def test_compact_has_negative_boundary(self):
|
||||
assert PRESETS["compact_outward"].boundary_attraction < 0
|
||||
|
||||
def test_spread_has_positive_boundary(self):
|
||||
assert PRESETS["spread_inward"].boundary_attraction > 0
|
||||
|
||||
|
||||
class TestSeedLayout:
|
||||
"""seed_layout must return valid placements: within bounds, one per device."""
|
||||
|
||||
def _make_devices(self, n: int) -> list[Device]:
|
||||
return [Device(id=f"d{i}", name=f"Device {i}", bbox=(0.6, 0.4)) for i in range(n)]
|
||||
|
||||
def test_returns_one_placement_per_device(self):
|
||||
devices = self._make_devices(5)
|
||||
lab = Lab(width=5.0, depth=4.0)
|
||||
result = seed_layout(devices, lab, PRESETS["compact_outward"])
|
||||
assert len(result) == 5
|
||||
ids = {p.device_id for p in result}
|
||||
assert ids == {f"d{i}" for i in range(5)}
|
||||
|
||||
def test_placements_within_bounds(self):
|
||||
devices = self._make_devices(5)
|
||||
lab = Lab(width=5.0, depth=4.0)
|
||||
for preset_name in ["compact_outward", "spread_inward"]:
|
||||
result = seed_layout(devices, lab, PRESETS[preset_name])
|
||||
for p in result:
|
||||
assert 0 <= p.x <= lab.width, f"{preset_name}: x={p.x} out of bounds"
|
||||
assert 0 <= p.y <= lab.depth, f"{preset_name}: y={p.y} out of bounds"
|
||||
|
||||
def test_empty_devices(self):
|
||||
result = seed_layout([], Lab(width=5, depth=4), PRESETS["compact_outward"])
|
||||
assert result == []
|
||||
|
||||
def test_single_device(self):
|
||||
devices = self._make_devices(1)
|
||||
lab = Lab(width=5.0, depth=4.0)
|
||||
result = seed_layout(devices, lab, PRESETS["compact_outward"])
|
||||
assert len(result) == 1
|
||||
assert 0 <= result[0].x <= lab.width
|
||||
assert 0 <= result[0].y <= lab.depth
|
||||
|
||||
def test_row_fallback_delegates(self):
|
||||
"""row_fallback preset uses generate_fallback, not force engine."""
|
||||
devices = self._make_devices(3)
|
||||
lab = Lab(width=5.0, depth=4.0)
|
||||
# row_fallback is None in PRESETS; seed_layout detects and delegates
|
||||
result = seed_layout(devices, lab, None) # None = row_fallback
|
||||
assert len(result) == 3
|
||||
|
||||
def test_lab_too_small_returns_results_not_crash(self):
|
||||
"""When space is insufficient, seeder still returns placements (may have collisions)."""
|
||||
devices = [Device(id=f"d{i}", name=f"D{i}", bbox=(1.0, 1.0)) for i in range(20)]
|
||||
lab = Lab(width=2.0, depth=2.0) # Way too small for 20 1m×1m devices
|
||||
result = seed_layout(devices, lab, PRESETS["compact_outward"])
|
||||
assert len(result) == 20 # All placed, even if overlapping
|
||||
for p in result:
|
||||
assert 0 <= p.x <= lab.width
|
||||
assert 0 <= p.y <= lab.depth
|
||||
|
||||
def test_compact_clusters_toward_center(self):
|
||||
"""compact_outward should place devices closer to center than spread_inward."""
|
||||
devices = self._make_devices(4)
|
||||
lab = Lab(width=8.0, depth=8.0)
|
||||
center_x, center_y = lab.width / 2, lab.depth / 2
|
||||
|
||||
compact = seed_layout(devices, lab, PRESETS["compact_outward"])
|
||||
spread = seed_layout(devices, lab, PRESETS["spread_inward"])
|
||||
|
||||
avg_dist_compact = sum(
|
||||
math.sqrt((p.x - center_x)**2 + (p.y - center_y)**2) for p in compact
|
||||
) / len(compact)
|
||||
avg_dist_spread = sum(
|
||||
math.sqrt((p.x - center_x)**2 + (p.y - center_y)**2) for p in spread
|
||||
) / len(spread)
|
||||
|
||||
assert avg_dist_compact < avg_dist_spread
|
||||
|
||||
|
||||
class TestOrientation:
|
||||
"""Orientation modes should set theta based on position relative to center."""
|
||||
|
||||
def test_outward_orientation_sets_theta(self):
|
||||
"""compact_outward: devices should have non-zero theta."""
|
||||
devices = [
|
||||
Device(id="a", name="A", bbox=(0.6, 0.4)),
|
||||
Device(id="b", name="B", bbox=(0.6, 0.4)),
|
||||
]
|
||||
lab = Lab(width=5.0, depth=4.0)
|
||||
result = seed_layout(devices, lab, PRESETS["compact_outward"])
|
||||
thetas = [p.theta for p in result]
|
||||
assert any(t != 0.0 for t in thetas) or len(devices) == 1
|
||||
|
||||
def test_none_orientation_keeps_zero(self):
|
||||
"""orientation_mode='none': all thetas stay 0."""
|
||||
devices = [Device(id="a", name="A", bbox=(0.6, 0.4))]
|
||||
lab = Lab(width=5.0, depth=4.0)
|
||||
params = SeederParams(boundary_attraction=0.0, orientation_mode="none")
|
||||
result = seed_layout(devices, lab, params)
|
||||
assert result[0].theta == 0.0
|
||||
@@ -32,7 +32,7 @@ from typing import Any, Dict, List, Optional, Tuple, Union
|
||||
|
||||
MAX_SCAN_DEPTH = 10 # 最大目录递归深度
|
||||
MAX_SCAN_FILES = 1000 # 最大扫描文件数量
|
||||
_CACHE_VERSION = 1 # 缓存格式版本号，格式变更时递增
|
||||
_CACHE_VERSION = 2 # 缓存格式版本号，格式变更时递增
|
||||
|
||||
# 合法的装饰器来源模块
|
||||
_REGISTRY_DECORATOR_MODULE = "unilabos.registry.decorators"
|
||||
@@ -258,8 +258,6 @@ def scan_directory(
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# File-level parsing
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -361,6 +359,7 @@ def _parse_file(
|
||||
"actions": class_body.get("actions", {}),
|
||||
"status_properties": class_body.get("status_properties", {}),
|
||||
"init_params": class_body.get("init_params", []),
|
||||
"init_docstring": class_body.get("init_docstring"),
|
||||
"auto_methods": class_body.get("auto_methods", {}),
|
||||
"import_map": import_map,
|
||||
}
|
||||
@@ -497,7 +496,6 @@ def _collect_imports(tree: ast.Module, module_path: str = "") -> Dict[str, str]:
|
||||
return import_map
|
||||
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Decorator finding & argument extraction
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -768,6 +766,7 @@ def _extract_class_body(
|
||||
"actions": {}, # method_name -> action_info
|
||||
"status_properties": {}, # prop_name -> status_info
|
||||
"init_params": [], # [{"name": ..., "type": ..., "default": ...}, ...]
|
||||
"init_docstring": None,
|
||||
"auto_methods": {}, # method_name -> method_info (no @action decorator)
|
||||
}
|
||||
|
||||
@@ -780,6 +779,7 @@ def _extract_class_body(
|
||||
# --- __init__ ---
|
||||
if method_name == "__init__":
|
||||
result["init_params"] = _extract_method_params(item, import_map)
|
||||
result["init_docstring"] = ast.get_docstring(item)
|
||||
continue
|
||||
|
||||
# --- Skip private/dunder ---
|
||||
@@ -825,6 +825,7 @@ def _extract_class_body(
|
||||
action_args.setdefault("placeholder_keys", {})
|
||||
action_args.setdefault("always_free", False)
|
||||
action_args.setdefault("is_protocol", False)
|
||||
action_args.setdefault("feedback_interval", 1.0)
|
||||
action_args.setdefault("description", "")
|
||||
action_args.setdefault("auto_prefix", False)
|
||||
action_args.setdefault("parent", False)
|
||||
|
||||
@@ -343,6 +343,7 @@ def action(
|
||||
auto_prefix: bool = False,
|
||||
parent: bool = False,
|
||||
node_type: Optional["NodeType"] = None,
|
||||
feedback_interval: Optional[float] = None,
|
||||
):
|
||||
"""
|
||||
动作方法装饰器
|
||||
@@ -378,6 +379,13 @@ def action(
|
||||
"""
|
||||
|
||||
def decorator(func: F) -> F:
|
||||
import asyncio as _asyncio
|
||||
|
||||
if _asyncio.iscoroutinefunction(func):
|
||||
@wraps(func)
|
||||
async def wrapper(*args, **kwargs):
|
||||
return await func(*args, **kwargs)
|
||||
else:
|
||||
@wraps(func)
|
||||
def wrapper(*args, **kwargs):
|
||||
return func(*args, **kwargs)
|
||||
@@ -399,6 +407,8 @@ def action(
|
||||
"auto_prefix": auto_prefix,
|
||||
"parent": parent,
|
||||
}
|
||||
if feedback_interval is not None:
|
||||
meta["feedback_interval"] = feedback_interval
|
||||
if node_type is not None:
|
||||
meta["node_type"] = node_type.value if isinstance(node_type, NodeType) else str(node_type)
|
||||
wrapper._action_registry_meta = meta # type: ignore[attr-defined]
|
||||
|
||||
@@ -51,14 +51,18 @@ Qone_nmr:
|
||||
properties:
|
||||
check_interval:
|
||||
default: 60
|
||||
description: 检查间隔时间（秒），默认60秒
|
||||
type: string
|
||||
expected_count:
|
||||
default: 1
|
||||
description: 期望生成的.nmr文件数量，默认1个
|
||||
type: string
|
||||
monitor_dir:
|
||||
description: 要监督的目录路径，如果未指定则使用self.monitor_directory
|
||||
type: string
|
||||
stability_checks:
|
||||
default: 3
|
||||
description: 文件大小稳定性检查次数，默认3次
|
||||
type: string
|
||||
required: []
|
||||
type: object
|
||||
@@ -85,11 +89,14 @@ Qone_nmr:
|
||||
goal:
|
||||
properties:
|
||||
output_dir:
|
||||
description: 输出目录（如果未指定，使用self.output_directory）
|
||||
type: string
|
||||
string_list:
|
||||
description: 字符串列表
|
||||
type: string
|
||||
txt_encoding:
|
||||
default: utf-8
|
||||
description: 文件编码
|
||||
type: string
|
||||
required:
|
||||
- string_list
|
||||
@@ -151,6 +158,13 @@ Qone_nmr:
|
||||
additionalProperties: false
|
||||
properties:
|
||||
string:
|
||||
description: '包含多个字符串的输入数据，支持两种格式：
|
||||
|
||||
1. 逗号分隔：如 "A 1 B 2 C 3, X 10 Y 20 Z 30"
|
||||
|
||||
2. 换行分隔：如 "A 1 B 2 C 3
|
||||
|
||||
X 10 Y 20 Z 30"'
|
||||
type: string
|
||||
title: StrSingleInput_Goal
|
||||
type: object
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -491,14 +491,17 @@ bioyond_cell:
|
||||
goal:
|
||||
properties:
|
||||
material_names:
|
||||
description: 物料名称列表；默认使用 [LiPF6, LiDFOB, DTD, LiFSI, LiPO2F2]
|
||||
items:
|
||||
type: string
|
||||
type: array
|
||||
type_id:
|
||||
default: 3a190ca0-b2f6-9aeb-8067-547e72c11469
|
||||
description: 物料类型ID
|
||||
type: string
|
||||
warehouse_name:
|
||||
default: 粉末加样头堆栈
|
||||
description: 目标仓库名（用于取位置信息）
|
||||
type: string
|
||||
required: []
|
||||
type: object
|
||||
@@ -527,12 +530,16 @@ bioyond_cell:
|
||||
goal:
|
||||
properties:
|
||||
location_name_or_id:
|
||||
description: 具体库位名称（如 A01）或库位 UUID，由用户指定。
|
||||
type: string
|
||||
material_name:
|
||||
description: 物料名称（会优先匹配配置模板）。
|
||||
type: string
|
||||
type_id:
|
||||
description: 物料类型 ID（若为空则尝试从配置推断）。
|
||||
type: string
|
||||
warehouse_name:
|
||||
description: 需要入库的仓库名称；若为空则仅创建不入库。
|
||||
type: string
|
||||
required:
|
||||
- material_name
|
||||
@@ -661,15 +668,20 @@ bioyond_cell:
|
||||
goal:
|
||||
properties:
|
||||
board_type:
|
||||
description: 板类型，如 "5ml分液瓶板"、"配液瓶(小)板"
|
||||
type: string
|
||||
bottle_type:
|
||||
description: 瓶类型，如 "5ml分液瓶"、"配液瓶(小)"
|
||||
type: string
|
||||
location_code:
|
||||
description: 库位编号，例如 "A01"
|
||||
type: string
|
||||
name:
|
||||
description: 物料名称
|
||||
type: string
|
||||
warehouse_name:
|
||||
default: 手动堆栈
|
||||
description: 仓库名称，默认为 "手动堆栈"，支持 "自动堆栈-左"、"自动堆栈-右" 等
|
||||
type: string
|
||||
required:
|
||||
- name
|
||||
@@ -1956,19 +1968,19 @@ bioyond_cell:
|
||||
properties:
|
||||
source_wh_id:
|
||||
default: 3a19debc-84b4-0359-e2d4-b3beea49348b
|
||||
description: 来源仓库ID
|
||||
description: 来源仓库 Id (默认为3号仓库)
|
||||
type: string
|
||||
source_x:
|
||||
default: 1
|
||||
description: 来源位置X坐标
|
||||
description: 来源位置 X 坐标
|
||||
type: integer
|
||||
source_y:
|
||||
default: 1
|
||||
description: 来源位置Y坐标
|
||||
description: 来源位置 Y 坐标
|
||||
type: integer
|
||||
source_z:
|
||||
default: 1
|
||||
description: 来源位置Z坐标
|
||||
description: 来源位置 Z 坐标
|
||||
type: integer
|
||||
required: []
|
||||
type: object
|
||||
@@ -2061,9 +2073,11 @@ bioyond_cell:
|
||||
goal:
|
||||
properties:
|
||||
order_code:
|
||||
description: 任务编号
|
||||
type: string
|
||||
timeout:
|
||||
default: 36000
|
||||
description: 超时时间（秒）
|
||||
type: integer
|
||||
required:
|
||||
- order_code
|
||||
@@ -2092,12 +2106,15 @@ bioyond_cell:
|
||||
goal:
|
||||
properties:
|
||||
order_code:
|
||||
description: 任务编号
|
||||
type: string
|
||||
poll_interval:
|
||||
default: 0.5
|
||||
description: 轮询间隔（秒），默认 0.5 秒
|
||||
type: number
|
||||
timeout:
|
||||
default: 36000
|
||||
description: 超时时间（秒）
|
||||
type: integer
|
||||
required:
|
||||
- order_code
|
||||
@@ -2154,10 +2171,15 @@ bioyond_cell:
|
||||
config:
|
||||
properties:
|
||||
bioyond_config:
|
||||
description: '从 JSON 文件加载的 bioyond 配置字典
|
||||
|
||||
包含 api_host, api_key, HTTP_host, HTTP_port 等配置'
|
||||
type: object
|
||||
deck:
|
||||
description: Deck 配置（可选，会从 JSON 中自动处理）
|
||||
type: string
|
||||
protocol_type:
|
||||
description: 协议类型（可选）
|
||||
type: string
|
||||
required: []
|
||||
type: object
|
||||
|
||||
@@ -47,8 +47,10 @@ bioyond_dispensing_station:
|
||||
goal:
|
||||
properties:
|
||||
report_request:
|
||||
description: WorkstationReportRequest 对象，包含任务完成信息
|
||||
type: string
|
||||
used_materials:
|
||||
description: 物料使用记录列表
|
||||
type: string
|
||||
required:
|
||||
- report_request
|
||||
@@ -102,6 +104,7 @@ bioyond_dispensing_station:
|
||||
goal:
|
||||
properties:
|
||||
material_name:
|
||||
description: 物料名称
|
||||
type: string
|
||||
required:
|
||||
- material_name
|
||||
@@ -611,10 +614,10 @@ bioyond_dispensing_station:
|
||||
goal:
|
||||
properties:
|
||||
target_device_id:
|
||||
description: 目标反应站设备ID（从设备列表中选择，所有转移组都使用同一个目标设备）
|
||||
description: 目标反应站设备ID(所有转移组使用同一个设备)
|
||||
type: string
|
||||
transfer_groups:
|
||||
description: 转移任务组列表，每组包含物料名称、目标堆栈和目标库位，可以添加多组
|
||||
description: '转移任务组列表,每组包含:'
|
||||
type: array
|
||||
required:
|
||||
- target_device_id
|
||||
@@ -694,10 +697,13 @@ bioyond_dispensing_station:
|
||||
config:
|
||||
properties:
|
||||
config:
|
||||
description: 配置字典,应包含material_type_mappings等配置
|
||||
type: object
|
||||
deck:
|
||||
description: Deck对象
|
||||
type: string
|
||||
protocol_type:
|
||||
description: 协议类型(由ROS系统传递,此处忽略)
|
||||
type: string
|
||||
required: []
|
||||
type: object
|
||||
|
||||
@@ -150,15 +150,15 @@ coincellassemblyworkstation_device:
|
||||
properties:
|
||||
assembly_pressure:
|
||||
default: 4200
|
||||
description: 电池压制力(N)
|
||||
description: 电池压制力 (N)
|
||||
type: integer
|
||||
assembly_type:
|
||||
default: 7
|
||||
description: 组装类型(7=不用铝箔垫, 8=使用铝箔垫)
|
||||
description: 组装类型 (7=不用铝箔垫, 8=使用铝箔垫)
|
||||
type: integer
|
||||
battery_clean_ignore:
|
||||
default: false
|
||||
description: 是否忽略电池清洁步骤
|
||||
description: 是否忽略电池清洁
|
||||
type: boolean
|
||||
battery_pressure_mode:
|
||||
default: true
|
||||
@@ -166,29 +166,29 @@ coincellassemblyworkstation_device:
|
||||
type: boolean
|
||||
dual_drop_first_volume:
|
||||
default: 25
|
||||
description: 二次滴液第一次排液体积(μL)
|
||||
description: 二次滴液第一次排液体积 (μL)
|
||||
type: integer
|
||||
dual_drop_mode:
|
||||
default: false
|
||||
description: 电解液添加模式(false=单次滴液, true=二次滴液)
|
||||
description: 电解液添加模式 (False=单次滴液, True=二次滴液)
|
||||
type: boolean
|
||||
dual_drop_start_timing:
|
||||
default: false
|
||||
description: 二次滴液开始滴液时机(false=正极片前, true=正极片后)
|
||||
description: 二次滴液开始滴液时机 (False=正极片前, True=正极片后)
|
||||
type: boolean
|
||||
dual_drop_suction_timing:
|
||||
default: false
|
||||
description: 二次滴液吸液时机(false=正常吸液, true=先吸液)
|
||||
description: 二次滴液吸液时机 (False=正常吸液, True=先吸液)
|
||||
type: boolean
|
||||
elec_num:
|
||||
description: 电解液瓶数
|
||||
type: string
|
||||
elec_use_num:
|
||||
description: 每瓶电解液组装电池数
|
||||
description: 每瓶电解液组装的电池数
|
||||
type: string
|
||||
elec_vol:
|
||||
default: 50
|
||||
description: 电解液吸液量(μL)
|
||||
description: 电解液吸液量 (μL)
|
||||
type: integer
|
||||
file_path:
|
||||
default: /Users/sml/work
|
||||
@@ -196,7 +196,7 @@ coincellassemblyworkstation_device:
|
||||
type: string
|
||||
fujipian_juzhendianwei:
|
||||
default: 0
|
||||
description: 负极片矩阵点位。盘位置从1开始计数，有效范围：1-8, 13-20 (写入值比实际位置少1，例如：写0取盘位1，写1取盘位2)
|
||||
description: 负极片矩阵点位
|
||||
type: integer
|
||||
fujipian_panshu:
|
||||
default: 0
|
||||
@@ -204,7 +204,7 @@ coincellassemblyworkstation_device:
|
||||
type: integer
|
||||
gemo_juzhendianwei:
|
||||
default: 0
|
||||
description: 隔膜矩阵点位。盘位置从1开始计数，有效范围：1-8, 13-20 (写入值比实际位置少1，例如：写0取盘位1，写1取盘位2)
|
||||
description: 隔膜矩阵点位
|
||||
type: integer
|
||||
gemopanshu:
|
||||
default: 0
|
||||
@@ -216,7 +216,7 @@ coincellassemblyworkstation_device:
|
||||
type: boolean
|
||||
qiangtou_juzhendianwei:
|
||||
default: 0
|
||||
description: 枪头盒矩阵点位。盘位置从1开始计数，有效范围：1-32, 64-96 (写入值比实际位置少1，例如：写0取盘位1，写1取盘位2)
|
||||
description: 枪头盒矩阵点位
|
||||
type: integer
|
||||
required:
|
||||
- elec_num
|
||||
@@ -308,7 +308,13 @@ coincellassemblyworkstation_device:
|
||||
properties:
|
||||
material_search_enable:
|
||||
default: false
|
||||
description: 是否启用物料搜寻功能。设备初始化后会弹出物料搜寻确认弹窗，此参数控制自动点击"是"(启用)或"否"(不启用)。默认为false(不启用物料搜寻)
|
||||
description: '是否启用物料搜寻功能。
|
||||
|
||||
设备初始化后会弹出物料搜寻确认弹窗，
|
||||
|
||||
此参数控制自动点击''是''（启用）或''否''（不启用）。
|
||||
|
||||
默认为False（不启用物料搜寻）。'
|
||||
type: boolean
|
||||
required: []
|
||||
type: object
|
||||
@@ -547,15 +553,15 @@ coincellassemblyworkstation_device:
|
||||
properties:
|
||||
assembly_pressure:
|
||||
default: 4200
|
||||
description: 电池压制力(N)
|
||||
description: 电池压制力 (N)
|
||||
type: integer
|
||||
assembly_type:
|
||||
default: 7
|
||||
description: 组装类型(7=不用铝箔垫, 8=使用铝箔垫)
|
||||
description: 组装类型 (7=不用铝箔垫, 8=使用铝箔垫)
|
||||
type: integer
|
||||
battery_clean_ignore:
|
||||
default: false
|
||||
description: 是否忽略电池清洁步骤
|
||||
description: 是否忽略电池清洁
|
||||
type: boolean
|
||||
battery_pressure_mode:
|
||||
default: true
|
||||
@@ -563,29 +569,29 @@ coincellassemblyworkstation_device:
|
||||
type: boolean
|
||||
dual_drop_first_volume:
|
||||
default: 25
|
||||
description: 二次滴液第一次排液体积(μL)
|
||||
description: 二次滴液第一次排液体积 (μL)
|
||||
type: integer
|
||||
dual_drop_mode:
|
||||
default: false
|
||||
description: 电解液添加模式(false=单次滴液, true=二次滴液)
|
||||
description: 电解液添加模式 (False=单次滴液, True=二次滴液)
|
||||
type: boolean
|
||||
dual_drop_start_timing:
|
||||
default: false
|
||||
description: 二次滴液开始滴液时机(false=正极片前, true=正极片后)
|
||||
description: 二次滴液开始滴液时机 (False=正极片前, True=正极片后)
|
||||
type: boolean
|
||||
dual_drop_suction_timing:
|
||||
default: false
|
||||
description: 二次滴液吸液时机(false=正常吸液, true=先吸液)
|
||||
description: 二次滴液吸液时机 (False=正常吸液, True=先吸液)
|
||||
type: boolean
|
||||
elec_num:
|
||||
description: 电解液瓶数，如果在workflow中已通过handles连接上游(create_orders的bottle_count输出)，则此参数会自动从上游获取，无需手动填写；如果单独使用此函数(没有上游连接)，则必须手动填写电解液瓶数
|
||||
description: 电解液瓶数
|
||||
type: string
|
||||
elec_use_num:
|
||||
description: 每瓶电解液组装电池数
|
||||
description: 每瓶电解液组装的电池数
|
||||
type: string
|
||||
elec_vol:
|
||||
default: 50
|
||||
description: 电解液吸液量(μL)
|
||||
description: 电解液吸液量 (μL)
|
||||
type: integer
|
||||
file_path:
|
||||
default: /Users/sml/work
|
||||
@@ -593,7 +599,7 @@ coincellassemblyworkstation_device:
|
||||
type: string
|
||||
fujipian_juzhendianwei:
|
||||
default: 0
|
||||
description: 负极片矩阵点位。盘位置从1开始计数，有效范围：1-8, 13-20 (写入值比实际位置少1，例如：写0取盘位1，写1取盘位2)
|
||||
description: 负极片矩阵点位
|
||||
type: integer
|
||||
fujipian_panshu:
|
||||
default: 0
|
||||
@@ -601,7 +607,7 @@ coincellassemblyworkstation_device:
|
||||
type: integer
|
||||
gemo_juzhendianwei:
|
||||
default: 0
|
||||
description: 隔膜矩阵点位。盘位置从1开始计数，有效范围：1-8, 13-20 (写入值比实际位置少1，例如：写0取盘位1，写1取盘位2)
|
||||
description: 隔膜矩阵点位
|
||||
type: integer
|
||||
gemopanshu:
|
||||
default: 0
|
||||
@@ -613,7 +619,7 @@ coincellassemblyworkstation_device:
|
||||
type: boolean
|
||||
qiangtou_juzhendianwei:
|
||||
default: 0
|
||||
description: 枪头盒矩阵点位。盘位置从1开始计数，有效范围：1-32, 64-96 (写入值比实际位置少1，例如：写0取盘位1，写1取盘位2)
|
||||
description: 枪头盒矩阵点位
|
||||
type: integer
|
||||
required:
|
||||
- elec_num
|
||||
|
||||
@@ -31,6 +31,6 @@ hotel.thermo_orbitor_rs2_hotel:
|
||||
type: object
|
||||
model:
|
||||
mesh: thermo_orbitor_rs2_hotel
|
||||
path: https://uni-lab.oss-cn-zhangjiakou.aliyuncs.com/uni-lab/devices/thermo_orbitor_rs2_hotel/macro_device.xacro
|
||||
path: https://leap-lab.oss-cn-zhangjiakou.aliyuncs.com/uni-lab/devices/thermo_orbitor_rs2_hotel/macro_device.xacro
|
||||
type: device
|
||||
version: 1.0.0
|
||||
|
||||
@@ -18,6 +18,7 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
degrees:
|
||||
description: 角度值
|
||||
type: number
|
||||
required:
|
||||
- degrees
|
||||
@@ -44,6 +45,7 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
required:
|
||||
- axis
|
||||
@@ -71,6 +73,7 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
enable:
|
||||
default: true
|
||||
description: True为使能，False为失能
|
||||
type: boolean
|
||||
required: []
|
||||
type: object
|
||||
@@ -99,9 +102,11 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
enable:
|
||||
default: true
|
||||
description: True为使能，False为失能
|
||||
type: boolean
|
||||
required:
|
||||
- axis
|
||||
@@ -152,6 +157,7 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
required:
|
||||
- axis
|
||||
@@ -183,16 +189,21 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度(rpm/s)
|
||||
type: integer
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
position:
|
||||
description: 目标位置(步数)
|
||||
type: integer
|
||||
precision:
|
||||
default: 100
|
||||
description: 到位精度
|
||||
type: integer
|
||||
speed:
|
||||
default: 5000
|
||||
description: 运行速度(rpm)
|
||||
type: integer
|
||||
required:
|
||||
- axis
|
||||
@@ -225,16 +236,21 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度
|
||||
type: integer
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
degrees:
|
||||
description: 目标角度（度）
|
||||
type: number
|
||||
precision:
|
||||
default: 100
|
||||
description: 精度
|
||||
type: integer
|
||||
speed:
|
||||
default: 5000
|
||||
description: 移动速度
|
||||
type: integer
|
||||
required:
|
||||
- axis
|
||||
@@ -267,16 +283,21 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度
|
||||
type: integer
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
precision:
|
||||
default: 100
|
||||
description: 精度
|
||||
type: integer
|
||||
revolutions:
|
||||
description: 目标圈数
|
||||
type: number
|
||||
speed:
|
||||
default: 5000
|
||||
description: 移动速度
|
||||
type: integer
|
||||
required:
|
||||
- axis
|
||||
@@ -309,15 +330,20 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度
|
||||
type: integer
|
||||
speed:
|
||||
default: 5000
|
||||
description: 运行速度
|
||||
type: integer
|
||||
x:
|
||||
description: X轴目标位置
|
||||
type: integer
|
||||
y:
|
||||
description: Y轴目标位置
|
||||
type: integer
|
||||
z:
|
||||
description: Z轴目标位置
|
||||
type: integer
|
||||
required: []
|
||||
type: object
|
||||
@@ -350,15 +376,20 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度
|
||||
type: integer
|
||||
speed:
|
||||
default: 5000
|
||||
description: 移动速度
|
||||
type: integer
|
||||
x_deg:
|
||||
description: X轴目标角度（度）
|
||||
type: number
|
||||
y_deg:
|
||||
description: Y轴目标角度（度）
|
||||
type: number
|
||||
z_deg:
|
||||
description: Z轴目标角度（度）
|
||||
type: number
|
||||
required: []
|
||||
type: object
|
||||
@@ -391,15 +422,20 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度
|
||||
type: integer
|
||||
speed:
|
||||
default: 5000
|
||||
description: 移动速度
|
||||
type: integer
|
||||
x_rev:
|
||||
description: X轴目标圈数
|
||||
type: number
|
||||
y_rev:
|
||||
description: Y轴目标圈数
|
||||
type: number
|
||||
z_rev:
|
||||
description: Z轴目标圈数
|
||||
type: number
|
||||
required: []
|
||||
type: object
|
||||
@@ -427,6 +463,7 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
revolutions:
|
||||
description: 圈数
|
||||
type: number
|
||||
required:
|
||||
- revolutions
|
||||
@@ -456,10 +493,13 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
acceleration:
|
||||
default: 1000
|
||||
description: 加速度(rpm/s)
|
||||
type: integer
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
speed:
|
||||
description: 运行速度(rpm)，正值正转，负值反转
|
||||
type: integer
|
||||
required:
|
||||
- axis
|
||||
@@ -487,6 +527,7 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
steps:
|
||||
description: 步数
|
||||
type: integer
|
||||
required:
|
||||
- steps
|
||||
@@ -513,6 +554,7 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
steps:
|
||||
description: 步数
|
||||
type: integer
|
||||
required:
|
||||
- steps
|
||||
@@ -564,9 +606,11 @@ xyz_stepper_controller:
|
||||
goal:
|
||||
properties:
|
||||
axis:
|
||||
description: 电机轴
|
||||
type: object
|
||||
timeout:
|
||||
default: 30.0
|
||||
description: 超时时间(秒)
|
||||
type: number
|
||||
required:
|
||||
- axis
|
||||
@@ -591,11 +635,14 @@ xyz_stepper_controller:
|
||||
properties:
|
||||
baudrate:
|
||||
default: 115200
|
||||
description: 波特率
|
||||
type: integer
|
||||
port:
|
||||
description: 串口端口名
|
||||
type: string
|
||||
timeout:
|
||||
default: 1.0
|
||||
description: 通信超时时间
|
||||
type: number
|
||||
required:
|
||||
- port
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user