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233
.cursor/skills/batch-insert-reagent/SKILL.md
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233
.cursor/skills/batch-insert-reagent/SKILL.md
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@@ -0,0 +1,233 @@
|
||||
---
|
||||
name: batch-insert-reagent
|
||||
description: Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info. Use when the user wants to add reagents, insert chemicals, batch register reagents, or mentions 录入试剂/添加试剂/试剂入库/reagent.
|
||||
---
|
||||
|
||||
# 批量录入试剂 Skill
|
||||
|
||||
通过云端 API 批量录入试剂信息，支持逐条或批量操作。
|
||||
|
||||
## 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
|
||||
|
||||
询问用户的启动参数，从 `--ak` `--sk` 或 config.py 中获取。
|
||||
|
||||
生成 AUTH token（任选一种方式）：
|
||||
|
||||
```bash
|
||||
# 方式一：Python 一行生成
|
||||
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>
|
||||
```
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
|-------------|------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-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>"
|
||||
```
|
||||
|
||||
**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**）
|
||||
|
||||
## 请求约定
|
||||
|
||||
所有请求使用 `curl -s`，POST 需加 `Content-Type: application/json`。
|
||||
|
||||
> **Windows 平台**必须使用 `curl.exe`（而非 PowerShell 的 `curl` 别名），示例中的 `curl` 均指 `curl.exe`。
|
||||
|
||||
---
|
||||
|
||||
## 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：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
|
||||
```
|
||||
|
||||
记住 `data.uuid` 为 `lab_uuid`。
|
||||
|
||||
### 2. 录入试剂
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/reagent" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"lab_uuid": "<lab_uuid>",
|
||||
"cas": "<CAS号>",
|
||||
"name": "<试剂名称>",
|
||||
"molecular_formula": "<分子式>",
|
||||
"smiles": "<SMILES>",
|
||||
"stock_in_quantity": <入库数量>,
|
||||
"unit": "<单位字符串>",
|
||||
"supplier": "<供应商>",
|
||||
"production_date": "<生产日期 ISO 8601>",
|
||||
"expiry_date": "<过期日期 ISO 8601>"
|
||||
}'
|
||||
```
|
||||
|
||||
返回成功时包含试剂 UUID：
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", ...}}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 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"` |
|
||||
| `molecular_formula` | string | 是 | 分子式 | `"H2O"` |
|
||||
| `smiles` | string | 是 | SMILES 表示 | `"O"` |
|
||||
| `stock_in_quantity` | number | 是 | 入库数量 | `10` |
|
||||
| `unit` | string | 是 | 单位（字符串，见下表） | `"mL"` |
|
||||
| `supplier` | string | 否 | 供应商名称 | `"国药集团"` |
|
||||
| `production_date` | string | 否 | 生产日期（ISO 8601） | `"2025-11-18T00:00:00Z"` |
|
||||
| `expiry_date` | string | 否 | 过期日期（ISO 8601） | `"2026-11-18T00:00:00Z"` |
|
||||
|
||||
### unit 单位值
|
||||
|
||||
| 值 | 单位 |
|
||||
|------|------|
|
||||
| `"mL"` | 毫升 |
|
||||
| `"L"` | 升 |
|
||||
| `"g"` | 克 |
|
||||
| `"kg"` | 千克 |
|
||||
| `"瓶"` | 瓶 |
|
||||
|
||||
> 根据试剂状态选择：液体用 `"mL"` / `"L"`，固体用 `"g"` / `"kg"`。
|
||||
|
||||
---
|
||||
|
||||
## 批量录入策略
|
||||
|
||||
### 方式一：用户提供 JSON 数组
|
||||
|
||||
用户一次性给出多条试剂数据：
|
||||
|
||||
```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"}
|
||||
]
|
||||
```
|
||||
|
||||
Agent 自动为每条补充 `lab_uuid`、`production_date`、`expiry_date` 等字段后逐条提交。
|
||||
|
||||
Agent 循环调用 API #2 逐条录入，每条记录一次 API 调用。
|
||||
|
||||
### 方式二：用户逐个描述
|
||||
|
||||
用户口头描述试剂（如「帮我录入 500mL 的无水乙醇，Sigma 的」），agent 自行补全字段：
|
||||
|
||||
1. 根据名称查找 CAS 号、分子式、SMILES（参考下方速查表或自行推断）
|
||||
2. 构建完整的请求体
|
||||
3. 向用户确认后提交
|
||||
|
||||
### 方式三：从 CSV/表格批量导入
|
||||
|
||||
用户提供 CSV 或表格文件路径，agent 读取并解析：
|
||||
|
||||
```bash
|
||||
# 期望的 CSV 格式（首行为表头）
|
||||
cas,name,molecular_formula,smiles,stock_in_quantity,unit,supplier,production_date,expiry_date
|
||||
7732-18-3,水,H2O,O,10,mL,农夫山泉,2025-11-18T00:00:00Z,2026-11-18T00:00:00Z
|
||||
```
|
||||
|
||||
### 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」
|
||||
4. 如有失败，列出失败的试剂名称和错误信息
|
||||
|
||||
---
|
||||
|
||||
## 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 |
|
||||
| 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 |
|
||||
| 乙酸乙酯 | 141-78-6 | C4H8O2 | CCOC(C)=O |
|
||||
| 二氯甲烷 | 75-09-2 | CH2Cl2 | ClCCl |
|
||||
| 四氢呋喃(THF) | 109-99-9 | C4H8O | C1CCOC1 |
|
||||
| N,N-二甲基甲酰胺(DMF) | 68-12-2 | C3H7NO | CN(C)C=O |
|
||||
| 氯仿 | 67-66-3 | CHCl3 | ClC(Cl)Cl |
|
||||
| 乙腈 | 75-05-8 | C2H3N | CC#N |
|
||||
| 甲苯 | 108-88-3 | C7H8 | Cc1ccccc1 |
|
||||
| 正己烷 | 110-54-3 | C6H14 | CCCCCC |
|
||||
| 异丙醇 | 67-63-0 | C3H8O | CC(C)O |
|
||||
| 盐酸 | 7647-01-0 | HCl | Cl |
|
||||
| 硫酸 | 7664-93-9 | H2SO4 | OS(O)(=O)=O |
|
||||
| 氢氧化钠 | 1310-73-2 | NaOH | [Na]O |
|
||||
| 碳酸钠 | 497-19-8 | Na2CO3 | [Na]OC([O-])=O.[Na+] |
|
||||
| 氯化钠 | 7647-14-5 | NaCl | [Na]Cl |
|
||||
| 乙二胺四乙酸(EDTA) | 60-00-4 | C10H16N2O8 | OC(=O)CN(CCN(CC(O)=O)CC(O)=O)CC(O)=O |
|
||||
|
||||
> 此表仅供快速参考。对于不在表中的试剂，agent 应根据化学知识推断或提示用户补充。
|
||||
|
||||
---
|
||||
|
||||
## 完整工作流 Checklist
|
||||
|
||||
```
|
||||
Task Progress:
|
||||
- [ ] 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
|
||||
- [ ] Step 4: 收集试剂信息（用户提供列表/逐个描述/CSV文件）
|
||||
- [ ] Step 5: 补全缺失字段（CAS、分子式、SMILES 等）
|
||||
- [ ] Step 6: 向用户确认待录入的试剂列表
|
||||
- [ ] Step 7: 循环调用 POST /lab/reagent 逐条录入（每条需含 lab_uuid）
|
||||
- [ ] Step 8: 汇总结果（成功/失败数量及详情）
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 完整示例
|
||||
|
||||
用户说：「帮我录入 3 种试剂：500mL 无水乙醇、1kg 氯化钠、2L 去离子水」
|
||||
|
||||
Agent 构建的请求序列：
|
||||
|
||||
```json
|
||||
// 第 1 条
|
||||
{"lab_uuid": "8511c672-...", "cas": "64-17-5", "name": "无水乙醇", "molecular_formula": "C2H6O", "smiles": "CCO", "stock_in_quantity": 500, "unit": "mL", "supplier": "国药集团", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
|
||||
|
||||
// 第 2 条
|
||||
{"lab_uuid": "8511c672-...", "cas": "7647-14-5", "name": "氯化钠", "molecular_formula": "NaCl", "smiles": "[Na]Cl", "stock_in_quantity": 1, "unit": "kg", "supplier": "", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
|
||||
|
||||
// 第 3 条
|
||||
{"lab_uuid": "8511c672-...", "cas": "7732-18-3", "name": "去离子水", "molecular_formula": "H2O", "smiles": "O", "stock_in_quantity": 2, "unit": "L", "supplier": "", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
|
||||
```
|
||||
301
.cursor/skills/batch-submit-experiment/SKILL.md
Normal file
301
.cursor/skills/batch-submit-experiment/SKILL.md
Normal file
@@ -0,0 +1,301 @@
|
||||
---
|
||||
name: batch-submit-experiment
|
||||
description: Batch submit experiments (notebooks) to Uni-Lab platform — list workflows, generate node_params from registry schemas, submit multiple rounds. Use when the user wants to submit experiments, create notebooks, batch run workflows, or mentions 提交实验/批量实验/notebook/实验轮次.
|
||||
---
|
||||
|
||||
# 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。
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
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（任选一种方式）：
|
||||
|
||||
```bash
|
||||
# 方式一：Python 一行生成
|
||||
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>
|
||||
```
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
|-------------|------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-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. req_device_registry_upload.json（设备注册表）
|
||||
|
||||
**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：
|
||||
|
||||
```
|
||||
<workspace 根目录>/unilabos_data/req_device_registry_upload.json
|
||||
<workspace 根目录>/req_device_registry_upload.json
|
||||
```
|
||||
|
||||
也可直接 Glob 搜索：`**/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`。
|
||||
|
||||
### 4. workflow_uuid（目标工作流）
|
||||
|
||||
用户需要提供要提交的 workflow UUID。如果用户不确定，通过 API #2 列出可用 workflow 供选择。
|
||||
|
||||
**四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，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**）
|
||||
- `workflow_uuid` — 工作流 UUID（用户提供或从列表选择）
|
||||
- `workflow_nodes` — workflow 中各 action 节点的 uuid、设备 ID、动作名（从 API #3 获取）
|
||||
|
||||
## 请求约定
|
||||
|
||||
所有请求使用 `curl -s`，POST 需加 `Content-Type: application/json`。
|
||||
|
||||
> **Windows 平台**必须使用 `curl.exe`（而非 PowerShell 的 `curl` 别名），示例中的 `curl` 均指 `curl.exe`。
|
||||
>
|
||||
> **PowerShell JSON 传参**：PowerShell 中 `-d '{"key":"value"}'` 会因引号转义失败。请将 JSON 写入临时文件，用 `-d '@tmp_body.json'`（单引号包裹 `@`，否则会被解析为 splatting 运算符）。
|
||||
|
||||
---
|
||||
|
||||
## 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：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
|
||||
```
|
||||
|
||||
记住 `data.uuid` 为 `lab_uuid`。
|
||||
|
||||
### 2. 列出可用 workflow
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/workflow/workflows?page=1&page_size=20&lab_uuid=$lab_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
返回 workflow 列表，展示给用户选择。列出每个 workflow 的 `uuid` 和 `name`。
|
||||
|
||||
### 3. 获取 workflow 模板详情
|
||||
|
||||
```bash
|
||||
curl -s -X GET "$BASE/api/v1/lab/workflow/template/detail/$workflow_uuid" -H "$AUTH"
|
||||
```
|
||||
|
||||
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`）
|
||||
- 每个节点的现有参数（`param`）
|
||||
|
||||
> **注意**：此 API 返回格式可能因版本不同而有差异。首次调用时，先打印完整响应分析结构，再提取节点信息。常见的节点字段路径为 `data.nodes[]` 或 `data.workflow_nodes[]`。
|
||||
|
||||
### 4. 提交实验（创建 notebook）
|
||||
|
||||
```bash
|
||||
curl -s -X POST "$BASE/api/v1/lab/notebook" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '<request_body>'
|
||||
```
|
||||
|
||||
请求体结构：
|
||||
|
||||
```json
|
||||
{
|
||||
"lab_uuid": "<lab_uuid>",
|
||||
"workflow_uuid": "<workflow_uuid>",
|
||||
"name": "<实验名称>",
|
||||
"node_params": [
|
||||
{
|
||||
"sample_uuids": ["<样品UUID1>", "<样品UUID2>"],
|
||||
"datas": [
|
||||
{
|
||||
"node_uuid": "<workflow中的节点UUID>",
|
||||
"param": {},
|
||||
"sample_params": [
|
||||
{
|
||||
"container_uuid": "<容器UUID>",
|
||||
"sample_value": {
|
||||
"liquid_names": "<液体名称>",
|
||||
"volumes": 1000
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
> **注意**：`sample_uuids` 必须是 **UUID 数组**（`[]uuid.UUID`），不是字符串。无样品时传空数组 `[]`。
|
||||
|
||||
---
|
||||
|
||||
## Notebook 请求体详解
|
||||
|
||||
### node_params 结构
|
||||
|
||||
`node_params` 是一个数组，**每个元素代表一轮实验**：
|
||||
|
||||
- 要跑 2 轮 → `node_params` 有 2 个元素
|
||||
- 要跑 N 轮 → `node_params` 有 N 个元素
|
||||
|
||||
### 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 #3 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） |
|
||||
|
||||
### 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}` |
|
||||
|
||||
---
|
||||
|
||||
## 从本地注册表生成 param 模板
|
||||
|
||||
### 自动方式 — 运行脚本
|
||||
|
||||
```bash
|
||||
python scripts/gen_notebook_params.py \
|
||||
--auth <token> \
|
||||
--base <BASE_URL> \
|
||||
--workflow-uuid <workflow_uuid> \
|
||||
[--registry <path/to/req_device_registry_upload.json>] \
|
||||
[--rounds <轮次数>] \
|
||||
[--output <输出文件路径>]
|
||||
```
|
||||
|
||||
> 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：
|
||||
- 完整 `node_params` 骨架
|
||||
- 每个节点的 param 字段及类型说明
|
||||
- `_schema_info` 辅助信息（不提交，仅供参考）
|
||||
|
||||
### 手动方式
|
||||
|
||||
如果脚本不可用或注册表不存在：
|
||||
|
||||
1. 调用 API #3 获取 workflow 详情
|
||||
2. 找到每个 action 节点的 `node_uuid`
|
||||
3. 在本地注册表中查找对应设备的 `action_value_mappings`：
|
||||
```
|
||||
resources[].id == <device_id>
|
||||
→ resources[].class.action_value_mappings.<action_name>.schema.properties.goal.properties
|
||||
```
|
||||
4. 将 schema 中的 properties 作为 `param` 的字段模板
|
||||
5. 按轮次复制 `node_params` 元素，让用户填写每轮的具体值
|
||||
|
||||
### 注册表结构参考
|
||||
|
||||
```json
|
||||
{
|
||||
"resources": [
|
||||
{
|
||||
"id": "liquid_handler.prcxi",
|
||||
"class": {
|
||||
"module": "unilabos.devices.xxx:ClassName",
|
||||
"action_value_mappings": {
|
||||
"transfer_liquid": {
|
||||
"type": "LiquidHandlerTransfer",
|
||||
"schema": {
|
||||
"properties": {
|
||||
"goal": {
|
||||
"properties": {
|
||||
"asp_vols": {"type": "array", "items": {"type": "number"}},
|
||||
"sources": {"type": "array"}
|
||||
},
|
||||
"required": ["asp_vols", "sources"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"goal_default": {}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
`param` 填写时，使用 `goal.properties` 中的字段名和类型。
|
||||
|
||||
---
|
||||
|
||||
## 完整工作流 Checklist
|
||||
|
||||
```
|
||||
Task Progress:
|
||||
- [ ] 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
|
||||
- [ ] Step 4: 确认 workflow_uuid（用户提供或从 GET #2 列表选择）
|
||||
- [ ] Step 5: GET workflow detail (#3) → 提取各节点 uuid、设备ID、动作名
|
||||
- [ ] Step 6: 定位本地注册表 req_device_registry_upload.json
|
||||
- [ ] Step 7: 运行 gen_notebook_params.py 或手动匹配 → 生成 node_params 模板
|
||||
- [ ] Step 8: 引导用户填写每轮的参数（sample_uuids、param、sample_params）
|
||||
- [ ] Step 9: 构建完整请求体 → POST /lab/notebook 提交
|
||||
- [ ] Step 10: 检查返回结果，确认提交成功
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 常见问题
|
||||
|
||||
### Q: workflow 中有多个节点，每轮都要填所有节点的参数吗？
|
||||
|
||||
是的。`datas` 数组中需要包含该轮实验涉及的每个 workflow 节点的参数。通常每个 action 节点都需要一条 `datas` 记录。
|
||||
|
||||
### Q: 多轮实验的参数完全不同吗？
|
||||
|
||||
通常每轮的 `param`（设备动作参数）可能相同或相似，但 `sample_uuids` 和 `sample_params`（样品信息）每轮不同。脚本生成模板时会按轮次复制骨架，用户只需修改差异部分。
|
||||
|
||||
### Q: 如何获取 sample_uuids 和 container_uuid？
|
||||
|
||||
这些 UUID 通常来自实验室的样品管理系统。向用户询问，或从资源树（API `GET /lab/material/download/$lab_uuid`）中查找。
|
||||
@@ -0,0 +1,394 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
从 workflow 模板详情 + 本地设备注册表生成 notebook 提交用的 node_params 模板。
|
||||
|
||||
用法:
|
||||
python gen_notebook_params.py --auth <token> --base <url> --workflow-uuid <uuid> [选项]
|
||||
|
||||
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）
|
||||
--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）
|
||||
--output <path> 输出模板文件路径（默认 notebook_template.json）
|
||||
--dump-response 打印 workflow detail API 的原始响应（调试用）
|
||||
|
||||
示例:
|
||||
python gen_notebook_params.py \\
|
||||
--auth YTFmZDlkNGUtxxxx \\
|
||||
--base https://uni-lab.test.bohrium.com \\
|
||||
--workflow-uuid abc-123-def \\
|
||||
--rounds 2
|
||||
"""
|
||||
import copy
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
from urllib.request import Request, urlopen
|
||||
from urllib.error import HTTPError, URLError
|
||||
|
||||
REGISTRY_FILENAME = "req_device_registry_upload.json"
|
||||
|
||||
|
||||
def find_registry(explicit_path=None):
|
||||
"""查找本地注册表文件，逻辑同 extract_device_actions.py"""
|
||||
if explicit_path:
|
||||
if os.path.isfile(explicit_path):
|
||||
return explicit_path
|
||||
if os.path.isdir(explicit_path):
|
||||
fp = os.path.join(explicit_path, REGISTRY_FILENAME)
|
||||
if os.path.isfile(fp):
|
||||
return fp
|
||||
print(f"警告: 指定的注册表路径不存在: {explicit_path}")
|
||||
return None
|
||||
|
||||
candidates = [
|
||||
os.path.join("unilabos_data", REGISTRY_FILENAME),
|
||||
REGISTRY_FILENAME,
|
||||
]
|
||||
for c in candidates:
|
||||
if os.path.isfile(c):
|
||||
return c
|
||||
|
||||
script_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
workspace_root = os.path.normpath(os.path.join(script_dir, "..", "..", ".."))
|
||||
for c in candidates:
|
||||
path = os.path.join(workspace_root, c)
|
||||
if os.path.isfile(path):
|
||||
return path
|
||||
|
||||
cwd = os.getcwd()
|
||||
for _ in range(5):
|
||||
parent = os.path.dirname(cwd)
|
||||
if parent == cwd:
|
||||
break
|
||||
cwd = parent
|
||||
for c in candidates:
|
||||
path = os.path.join(cwd, c)
|
||||
if os.path.isfile(path):
|
||||
return path
|
||||
return None
|
||||
|
||||
|
||||
def load_registry(path):
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return json.load(f)
|
||||
|
||||
|
||||
def build_registry_index(registry_data):
|
||||
"""构建 device_id → action_value_mappings 的索引"""
|
||||
index = {}
|
||||
for res in registry_data.get("resources", []):
|
||||
rid = res.get("id", "")
|
||||
avm = res.get("class", {}).get("action_value_mappings", {})
|
||||
if rid and avm:
|
||||
index[rid] = avm
|
||||
return index
|
||||
|
||||
|
||||
def flatten_goal_schema(action_data):
|
||||
"""从 action_value_mappings 条目中提取 goal 层的 schema"""
|
||||
schema = action_data.get("schema", {})
|
||||
goal_schema = schema.get("properties", {}).get("goal", {})
|
||||
return goal_schema if goal_schema else schema
|
||||
|
||||
|
||||
def build_param_template(goal_schema):
|
||||
"""根据 goal schema 生成 param 模板，含类型标注"""
|
||||
properties = goal_schema.get("properties", {})
|
||||
required = set(goal_schema.get("required", []))
|
||||
template = {}
|
||||
for field_name, field_def in properties.items():
|
||||
if field_name == "unilabos_device_id":
|
||||
continue
|
||||
ftype = field_def.get("type", "any")
|
||||
default = field_def.get("default")
|
||||
if default is not None:
|
||||
template[field_name] = default
|
||||
elif ftype == "string":
|
||||
template[field_name] = f"$TODO ({ftype}, {'required' if field_name in required else 'optional'})"
|
||||
elif ftype == "number" or ftype == "integer":
|
||||
template[field_name] = 0
|
||||
elif ftype == "boolean":
|
||||
template[field_name] = False
|
||||
elif ftype == "array":
|
||||
template[field_name] = []
|
||||
elif ftype == "object":
|
||||
template[field_name] = {}
|
||||
else:
|
||||
template[field_name] = f"$TODO ({ftype})"
|
||||
return template
|
||||
|
||||
|
||||
def fetch_workflow_detail(base_url, auth_token, workflow_uuid):
|
||||
"""调用 workflow detail API"""
|
||||
url = f"{base_url}/api/v1/lab/workflow/template/detail/{workflow_uuid}"
|
||||
req = Request(url, method="GET")
|
||||
req.add_header("Authorization", f"Lab {auth_token}")
|
||||
try:
|
||||
with urlopen(req, timeout=30) as resp:
|
||||
return json.loads(resp.read().decode("utf-8"))
|
||||
except HTTPError as e:
|
||||
body = e.read().decode("utf-8", errors="replace")
|
||||
print(f"API 错误 {e.code}: {body}")
|
||||
return None
|
||||
except URLError as e:
|
||||
print(f"网络错误: {e.reason}")
|
||||
return None
|
||||
|
||||
|
||||
def extract_nodes_from_response(response):
|
||||
"""
|
||||
从 workflow detail 响应中提取 action 节点列表。
|
||||
适配多种可能的响应格式。
|
||||
|
||||
返回: [(node_uuid, resource_template_name, node_template_name, existing_param), ...]
|
||||
"""
|
||||
data = response.get("data", response)
|
||||
|
||||
search_keys = ["nodes", "workflow_nodes", "node_list", "steps"]
|
||||
nodes_raw = None
|
||||
for key in search_keys:
|
||||
if key in data and isinstance(data[key], list):
|
||||
nodes_raw = data[key]
|
||||
break
|
||||
|
||||
if nodes_raw is None:
|
||||
if isinstance(data, list):
|
||||
nodes_raw = data
|
||||
else:
|
||||
for v in data.values():
|
||||
if isinstance(v, list) and len(v) > 0 and isinstance(v[0], dict):
|
||||
nodes_raw = v
|
||||
break
|
||||
|
||||
if not nodes_raw:
|
||||
print("警告: 未能从响应中提取节点列表")
|
||||
print("响应顶层 keys:", list(data.keys()) if isinstance(data, dict) else type(data).__name__)
|
||||
return []
|
||||
|
||||
result = []
|
||||
for node in nodes_raw:
|
||||
if not isinstance(node, dict):
|
||||
continue
|
||||
|
||||
node_uuid = (
|
||||
node.get("uuid")
|
||||
or node.get("node_uuid")
|
||||
or node.get("id")
|
||||
or ""
|
||||
)
|
||||
resource_name = (
|
||||
node.get("resource_template_name")
|
||||
or node.get("device_id")
|
||||
or node.get("resource_name")
|
||||
or node.get("device_name")
|
||||
or ""
|
||||
)
|
||||
template_name = (
|
||||
node.get("node_template_name")
|
||||
or node.get("action_name")
|
||||
or node.get("template_name")
|
||||
or node.get("action")
|
||||
or node.get("name")
|
||||
or ""
|
||||
)
|
||||
existing_param = node.get("param", {}) or {}
|
||||
|
||||
if node_uuid:
|
||||
result.append((node_uuid, resource_name, template_name, existing_param))
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def generate_template(nodes, registry_index, rounds):
|
||||
"""生成 notebook 提交模板"""
|
||||
node_params = []
|
||||
schema_info = {}
|
||||
|
||||
datas_template = []
|
||||
for node_uuid, resource_name, template_name, existing_param in nodes:
|
||||
param_template = {}
|
||||
matched = False
|
||||
|
||||
if resource_name and template_name and resource_name in registry_index:
|
||||
avm = registry_index[resource_name]
|
||||
if template_name in avm:
|
||||
goal_schema = flatten_goal_schema(avm[template_name])
|
||||
param_template = build_param_template(goal_schema)
|
||||
goal_default = avm[template_name].get("goal_default", {})
|
||||
if goal_default:
|
||||
for k, v in goal_default.items():
|
||||
if k in param_template and v is not None:
|
||||
param_template[k] = v
|
||||
matched = True
|
||||
|
||||
schema_info[node_uuid] = {
|
||||
"device_id": resource_name,
|
||||
"action_name": template_name,
|
||||
"action_type": avm[template_name].get("type", ""),
|
||||
"schema_properties": list(goal_schema.get("properties", {}).keys()),
|
||||
"required": goal_schema.get("required", []),
|
||||
}
|
||||
|
||||
if not matched and existing_param:
|
||||
param_template = existing_param
|
||||
|
||||
if not matched and not existing_param:
|
||||
schema_info[node_uuid] = {
|
||||
"device_id": resource_name,
|
||||
"action_name": template_name,
|
||||
"warning": "未在本地注册表中找到匹配的 action schema",
|
||||
}
|
||||
|
||||
datas_template.append({
|
||||
"node_uuid": node_uuid,
|
||||
"param": param_template,
|
||||
"sample_params": [
|
||||
{
|
||||
"container_uuid": "$TODO_CONTAINER_UUID",
|
||||
"sample_value": {
|
||||
"liquid_names": "$TODO_LIQUID_NAME",
|
||||
"volumes": 0,
|
||||
},
|
||||
}
|
||||
],
|
||||
})
|
||||
|
||||
for i in range(rounds):
|
||||
node_params.append({
|
||||
"sample_uuids": f"$TODO_SAMPLE_UUID_ROUND_{i + 1}",
|
||||
"datas": copy.deepcopy(datas_template),
|
||||
})
|
||||
|
||||
return {
|
||||
"lab_uuid": "$TODO_LAB_UUID",
|
||||
"workflow_uuid": "$TODO_WORKFLOW_UUID",
|
||||
"name": "$TODO_EXPERIMENT_NAME",
|
||||
"node_params": node_params,
|
||||
"_schema_info（仅参考，提交时删除）": schema_info,
|
||||
}
|
||||
|
||||
|
||||
def parse_args(argv):
|
||||
"""简单的参数解析"""
|
||||
opts = {
|
||||
"auth": None,
|
||||
"base": None,
|
||||
"workflow_uuid": None,
|
||||
"registry": None,
|
||||
"rounds": 1,
|
||||
"output": "notebook_template.json",
|
||||
"dump_response": False,
|
||||
}
|
||||
i = 0
|
||||
while i < len(argv):
|
||||
arg = argv[i]
|
||||
if arg == "--auth" and i + 1 < len(argv):
|
||||
opts["auth"] = argv[i + 1]
|
||||
i += 2
|
||||
elif arg == "--base" and i + 1 < len(argv):
|
||||
opts["base"] = argv[i + 1].rstrip("/")
|
||||
i += 2
|
||||
elif arg == "--workflow-uuid" and i + 1 < len(argv):
|
||||
opts["workflow_uuid"] = argv[i + 1]
|
||||
i += 2
|
||||
elif arg == "--registry" and i + 1 < len(argv):
|
||||
opts["registry"] = argv[i + 1]
|
||||
i += 2
|
||||
elif arg == "--rounds" and i + 1 < len(argv):
|
||||
opts["rounds"] = int(argv[i + 1])
|
||||
i += 2
|
||||
elif arg == "--output" and i + 1 < len(argv):
|
||||
opts["output"] = argv[i + 1]
|
||||
i += 2
|
||||
elif arg == "--dump-response":
|
||||
opts["dump_response"] = True
|
||||
i += 1
|
||||
else:
|
||||
print(f"未知参数: {arg}")
|
||||
i += 1
|
||||
return opts
|
||||
|
||||
|
||||
def main():
|
||||
opts = parse_args(sys.argv[1:])
|
||||
|
||||
if not opts["auth"] or not opts["base"] or not opts["workflow_uuid"]:
|
||||
print("用法:")
|
||||
print(" python gen_notebook_params.py --auth <token> --base <url> --workflow-uuid <uuid> [选项]")
|
||||
print()
|
||||
print("必需参数:")
|
||||
print(" --auth <token> Lab token（base64(ak:sk)）")
|
||||
print(" --base <url> API 基础 URL")
|
||||
print(" --workflow-uuid <uuid> 目标 workflow UUID")
|
||||
print()
|
||||
print("可选参数:")
|
||||
print(" --registry <path> 注册表文件路径（默认自动搜索）")
|
||||
print(" --rounds <n> 实验轮次数（默认 1）")
|
||||
print(" --output <path> 输出文件路径（默认 notebook_template.json）")
|
||||
print(" --dump-response 打印 API 原始响应")
|
||||
sys.exit(1)
|
||||
|
||||
# 1. 查找并加载本地注册表
|
||||
registry_path = find_registry(opts["registry"])
|
||||
registry_index = {}
|
||||
if registry_path:
|
||||
mtime = os.path.getmtime(registry_path)
|
||||
gen_time = datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
|
||||
print(f"注册表: {registry_path} (生成时间: {gen_time})")
|
||||
registry_data = load_registry(registry_path)
|
||||
registry_index = build_registry_index(registry_data)
|
||||
print(f"已索引 {len(registry_index)} 个设备的 action schemas")
|
||||
else:
|
||||
print("警告: 未找到本地注册表，将跳过 param 模板生成")
|
||||
print(" 提交时需要手动填写各节点的 param 字段")
|
||||
|
||||
# 2. 获取 workflow 详情
|
||||
print(f"\n正在获取 workflow 详情: {opts['workflow_uuid']}")
|
||||
response = fetch_workflow_detail(opts["base"], opts["auth"], opts["workflow_uuid"])
|
||||
if not response:
|
||||
print("错误: 无法获取 workflow 详情")
|
||||
sys.exit(1)
|
||||
|
||||
if opts["dump_response"]:
|
||||
print("\n=== API 原始响应 ===")
|
||||
print(json.dumps(response, indent=2, ensure_ascii=False)[:5000])
|
||||
print("=== 响应结束（截断至 5000 字符） ===\n")
|
||||
|
||||
# 3. 提取节点
|
||||
nodes = extract_nodes_from_response(response)
|
||||
if not nodes:
|
||||
print("错误: 未能从 workflow 中提取任何 action 节点")
|
||||
print("请使用 --dump-response 查看原始响应结构")
|
||||
sys.exit(1)
|
||||
|
||||
print(f"\n找到 {len(nodes)} 个 action 节点:")
|
||||
print(f" {'节点 UUID':<40} {'设备 ID':<30} {'动作名':<25} {'Schema'}")
|
||||
print(" " + "-" * 110)
|
||||
for node_uuid, resource_name, template_name, _ in nodes:
|
||||
matched = "✓" if (resource_name in registry_index and
|
||||
template_name in registry_index.get(resource_name, {})) else "✗"
|
||||
print(f" {node_uuid:<40} {resource_name:<30} {template_name:<25} {matched}")
|
||||
|
||||
# 4. 生成模板
|
||||
template = generate_template(nodes, registry_index, opts["rounds"])
|
||||
template["workflow_uuid"] = opts["workflow_uuid"]
|
||||
|
||||
output_path = opts["output"]
|
||||
with open(output_path, "w", encoding="utf-8") as f:
|
||||
json.dump(template, f, indent=2, ensure_ascii=False)
|
||||
print(f"\n模板已写入: {output_path}")
|
||||
print(f" 轮次数: {opts['rounds']}")
|
||||
print(f" 节点数/轮: {len(nodes)}")
|
||||
print()
|
||||
print("下一步:")
|
||||
print(" 1. 打开模板文件，将 $TODO 占位符替换为实际值")
|
||||
print(" 2. 删除 _schema_info 字段（仅供参考）")
|
||||
print(" 3. 使用 POST /api/v1/lab/notebook 提交")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -163,7 +163,7 @@ 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（10 个 endpoint），修改：
|
||||
直接复用 `unilab-device-api` 的 API 模板，修改：
|
||||
- 设备名称
|
||||
- Action 数量
|
||||
- 目录列表
|
||||
@@ -181,15 +181,18 @@ API 模板结构：
|
||||
## 前置条件（缺一不可）
|
||||
- ak/sk → AUTH, --addr → BASE URL
|
||||
|
||||
## Session State
|
||||
- lab_uuid（通过 API #1 自动匹配，不要问用户）, device_name
|
||||
## 请求约定
|
||||
- Windows 平台必须用 curl.exe（非 PowerShell 的 curl 别名）
|
||||
|
||||
## API Endpoints (10 个)
|
||||
# 注意：
|
||||
# - #1 获取 lab 列表 + 自动匹配 lab_uuid（遍历 is_admin 的 lab，
|
||||
# 调用 /lab/info/{uuid} 比对 access_key == ak）
|
||||
# - #2 创建工作流用 POST /lab/workflow
|
||||
# - #10 获取资源树路径含 lab_uuid: /lab/material/download/{lab_uuid}
|
||||
## 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>"}
|
||||
# - #10 获取资源树 GET /lab/material/download/{lab_uuid}
|
||||
|
||||
## Placeholder Slot 填写规则
|
||||
- unilabos_resources → ResourceSlot → {"id":"/path/name","name":"name","uuid":"xxx"}
|
||||
@@ -206,7 +209,7 @@ API 模板结构：
|
||||
### Step 5 — 验证
|
||||
|
||||
检查文件完整性：
|
||||
- [ ] `SKILL.md` 包含 10 个 API endpoint
|
||||
- [ ] `SKILL.md` 包含 API endpoint（#1 获取 lab_uuid、#2-#9 工作流/动作、#10 资源树）
|
||||
- [ ] `SKILL.md` 包含 Placeholder Slot 填写规则（ResourceSlot / DeviceSlot / NodeSlot / ClassSlot + 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
|
||||
@@ -249,7 +252,7 @@ API 模板结构：
|
||||
```
|
||||
|
||||
> **注意**：`schema` 已由脚本从原始 `schema.properties.goal` 提升为顶层，直接包含参数定义。
|
||||
> `schema.properties` 中的字段即为 API 请求 `param.goal` 中的字段。
|
||||
> `schema.properties` 中的字段即为 API 创建节点返回的 `data.param` 中的字段，PATCH 更新时直接修改 `param` 即可。
|
||||
|
||||
## Placeholder Slot 类型体系
|
||||
|
||||
|
||||
275
.cursor/skills/submit-agent-result/SKILL.md
Normal file
275
.cursor/skills/submit-agent-result/SKILL.md
Normal file
@@ -0,0 +1,275 @@
|
||||
---
|
||||
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.
|
||||
---
|
||||
|
||||
# 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。
|
||||
|
||||
## 前置条件（缺一不可）
|
||||
|
||||
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(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>`。
|
||||
|
||||
### 2. --addr → BASE URL
|
||||
|
||||
| `--addr` 值 | BASE |
|
||||
|-------------|------|
|
||||
| `test` | `https://uni-lab.test.bohrium.com` |
|
||||
| `uat` | `https://uni-lab.uat.bohrium.com` |
|
||||
| `local` | `http://127.0.0.1:48197` |
|
||||
| 不传（默认） | `https://uni-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. notebook_uuid（**必须询问用户**）
|
||||
|
||||
**必须主动询问用户**：「请提供要提交结果的 notebook UUID。」
|
||||
|
||||
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
|
||||
|
||||
**绝不能跳过此步骤，没有 notebook_uuid 无法提交。**
|
||||
|
||||
### 4. 实验结果数据
|
||||
|
||||
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 |
|
||||
|
||||
**四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（通过 API #1 自动获取，**不需要问用户**）
|
||||
- `notebook_uuid` — 目标 notebook UUID（**必须询问用户**）
|
||||
|
||||
## 请求约定
|
||||
|
||||
所有请求使用 `curl -s`，PUT 需加 `Content-Type: application/json`。
|
||||
|
||||
> **Windows 平台**必须使用 `curl.exe`（而非 PowerShell 的 `curl` 别名），示例中的 `curl` 均指 `curl.exe`。
|
||||
>
|
||||
> **PowerShell JSON 传参**：PowerShell 中 `-d '{"key":"value"}'` 会因引号转义失败。请将 JSON 写入临时文件，用 `-d '@tmp_body.json'`（单引号包裹 `@`，否则 `@` 会被 PowerShell 解析为 splatting 运算符导致报错）。
|
||||
|
||||
---
|
||||
|
||||
## 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 "$AUTH"
|
||||
```
|
||||
|
||||
返回：
|
||||
|
||||
```json
|
||||
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
|
||||
```
|
||||
|
||||
记住 `data.uuid` 为 `lab_uuid`。
|
||||
|
||||
### 2. 提交实验结果（agent_result）
|
||||
|
||||
```bash
|
||||
curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '<request_body>'
|
||||
```
|
||||
|
||||
请求体结构：
|
||||
|
||||
```json
|
||||
{
|
||||
"notebook_uuid": "<notebook_uuid>",
|
||||
"agent_result": {
|
||||
"<key1>": "<value1>",
|
||||
"<key2>": 123,
|
||||
"<nested_key>": {"a": 1, "b": 2},
|
||||
"<array_key>": [{"col1": "v1", "col2": "v2"}, ...]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
> **注意**：HTTP 方法是 **PUT**（不是 POST）。
|
||||
|
||||
#### 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 |
|
||||
|
||||
#### agent_result 内容格式
|
||||
|
||||
`agent_result` 接受**任意 JSON 对象**，常见格式：
|
||||
|
||||
**简单键值对**：
|
||||
```json
|
||||
{
|
||||
"avg_rtt_ms": 12.5,
|
||||
"status": "success",
|
||||
"test_count": 5
|
||||
}
|
||||
```
|
||||
|
||||
**包含嵌套结构**：
|
||||
```json
|
||||
{
|
||||
"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"}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**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}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 整合脚本
|
||||
|
||||
本文档同级目录下的 `scripts/prepare_agent_result.py` 可自动读取文件并构建请求体。
|
||||
|
||||
### 用法
|
||||
|
||||
```bash
|
||||
python scripts/prepare_agent_result.py \
|
||||
--notebook-uuid <uuid> \
|
||||
--files data1.json data2.csv \
|
||||
[--auth <token>] \
|
||||
[--base <BASE_URL>] \
|
||||
[--submit] \
|
||||
[--output <output.json>]
|
||||
```
|
||||
|
||||
| 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)） |
|
||||
| `--base` | 提交时必选 | API base URL |
|
||||
| `--submit` | 否 | 加上此标志则直接提交到云端 |
|
||||
| `--output` | 否 | 输出 JSON 路径（默认 `agent_result_body.json`） |
|
||||
|
||||
### 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 |
|
||||
|
||||
多个文件的字段会合并。JSON dict 中的重复 key 后者覆盖前者。
|
||||
|
||||
### 示例
|
||||
|
||||
```bash
|
||||
# 仅生成请求体文件（不提交）
|
||||
python scripts/prepare_agent_result.py \
|
||||
--notebook-uuid 73c67dca-c8cc-4936-85a0-329106aa7cca \
|
||||
--files results.json measurements.csv
|
||||
|
||||
# 生成并直接提交
|
||||
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 \
|
||||
--submit
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 手动构建方式
|
||||
|
||||
如果不使用脚本，也可手动构建请求体：
|
||||
|
||||
1. 将实验结果数据组装为 JSON 对象
|
||||
2. 写入临时文件：
|
||||
|
||||
```json
|
||||
{
|
||||
"notebook_uuid": "<uuid>",
|
||||
"agent_result": { ... }
|
||||
}
|
||||
```
|
||||
|
||||
3. 用 curl 提交：
|
||||
|
||||
```bash
|
||||
curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
|
||||
-H "$AUTH" -H "Content-Type: application/json" \
|
||||
-d '@tmp_body.json'
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 完整工作流 Checklist
|
||||
|
||||
```
|
||||
Task Progress:
|
||||
- [ ] 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
|
||||
- [ ] Step 4: **询问用户** notebook_uuid（必须，不可跳过）
|
||||
- [ ] Step 5: 确认实验结果数据来源（文件路径或手动数据）
|
||||
- [ ] Step 6: 运行 prepare_agent_result.py 或手动构建请求体
|
||||
- [ ] Step 7: PUT /lab/notebook/agent-result 提交
|
||||
- [ ] Step 8: 检查返回结果，确认提交成功
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 常见问题
|
||||
|
||||
### Q: notebook_uuid 从哪里获取？
|
||||
|
||||
从之前「批量提交实验」时 `POST /api/v1/lab/notebook` 的返回值 `data.uuid` 获取。也可以在平台 UI 中查找对应的 notebook。
|
||||
|
||||
### Q: agent_result 有固定的 schema 吗？
|
||||
|
||||
没有严格 schema，接受任意 JSON 对象。但建议包含有意义的字段名和结构化数据，方便后续分析。
|
||||
|
||||
### Q: 可以多次提交同一个 notebook 的结果吗？
|
||||
|
||||
可以，后续提交会覆盖之前的 agent_result。
|
||||
|
||||
### 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。
|
||||
@@ -0,0 +1,133 @@
|
||||
"""
|
||||
读取实验结果文件（JSON / CSV），整合为 agent_result 请求体并可选提交。
|
||||
|
||||
用法:
|
||||
python prepare_agent_result.py \
|
||||
--notebook-uuid <uuid> \
|
||||
--files data1.json data2.csv \
|
||||
[--auth <Lab token>] \
|
||||
[--base <BASE_URL>] \
|
||||
[--submit] \
|
||||
[--output <output.json>]
|
||||
|
||||
支持的输入文件格式:
|
||||
- .json → 直接作为 dict 合并
|
||||
- .csv → 转为 {"filename": [row_dict, ...]} 格式
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import base64
|
||||
import csv
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List
|
||||
|
||||
|
||||
def read_json_file(filepath: str) -> Dict[str, Any]:
|
||||
with open(filepath, "r", encoding="utf-8") as f:
|
||||
return json.load(f)
|
||||
|
||||
|
||||
def read_csv_file(filepath: str) -> List[Dict[str, Any]]:
|
||||
rows = []
|
||||
with open(filepath, "r", encoding="utf-8-sig") as f:
|
||||
reader = csv.DictReader(f)
|
||||
for row in reader:
|
||||
converted = {}
|
||||
for k, v in row.items():
|
||||
try:
|
||||
converted[k] = int(v)
|
||||
except (ValueError, TypeError):
|
||||
try:
|
||||
converted[k] = float(v)
|
||||
except (ValueError, TypeError):
|
||||
converted[k] = v
|
||||
rows.append(converted)
|
||||
return rows
|
||||
|
||||
|
||||
def merge_files(filepaths: List[str]) -> Dict[str, Any]:
|
||||
"""将多个文件合并为一个 agent_result dict"""
|
||||
merged: Dict[str, Any] = {}
|
||||
for fp in filepaths:
|
||||
path = Path(fp)
|
||||
ext = path.suffix.lower()
|
||||
key = path.stem
|
||||
|
||||
if ext == ".json":
|
||||
data = read_json_file(fp)
|
||||
if isinstance(data, dict):
|
||||
merged.update(data)
|
||||
else:
|
||||
merged[key] = data
|
||||
elif ext == ".csv":
|
||||
merged[key] = read_csv_file(fp)
|
||||
else:
|
||||
print(f"[警告] 不支持的文件格式: {fp}，跳过", file=sys.stderr)
|
||||
|
||||
return merged
|
||||
|
||||
|
||||
def build_request_body(notebook_uuid: str, agent_result: Dict[str, Any]) -> Dict[str, Any]:
|
||||
return {
|
||||
"notebook_uuid": notebook_uuid,
|
||||
"agent_result": agent_result,
|
||||
}
|
||||
|
||||
|
||||
def submit(base: str, auth: str, body: Dict[str, Any]) -> Dict[str, Any]:
|
||||
try:
|
||||
import requests
|
||||
except ImportError:
|
||||
print("[错误] 提交需要 requests 库: pip install requests", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
url = f"{base}/api/v1/lab/notebook/agent-result"
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Lab {auth}",
|
||||
}
|
||||
resp = requests.put(url, json=body, headers=headers, timeout=30)
|
||||
return {"status_code": resp.status_code, "body": resp.json() if resp.headers.get("content-type", "").startswith("application/json") else resp.text}
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="整合实验结果文件并构建 agent_result 请求体")
|
||||
parser.add_argument("--notebook-uuid", required=True, help="目标 notebook UUID")
|
||||
parser.add_argument("--files", nargs="+", required=True, help="输入文件路径（JSON / CSV）")
|
||||
parser.add_argument("--auth", help="Lab token（base64(ak:sk)）")
|
||||
parser.add_argument("--base", help="API base URL")
|
||||
parser.add_argument("--submit", action="store_true", help="直接提交到云端")
|
||||
parser.add_argument("--output", default="agent_result_body.json", help="输出 JSON 文件路径")
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
for fp in args.files:
|
||||
if not os.path.exists(fp):
|
||||
print(f"[错误] 文件不存在: {fp}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
agent_result = merge_files(args.files)
|
||||
body = build_request_body(args.notebook_uuid, agent_result)
|
||||
|
||||
with open(args.output, "w", encoding="utf-8") as f:
|
||||
json.dump(body, f, ensure_ascii=False, indent=2)
|
||||
print(f"[完成] 请求体已保存: {args.output}")
|
||||
print(f" notebook_uuid: {args.notebook_uuid}")
|
||||
print(f" agent_result 字段数: {len(agent_result)}")
|
||||
print(f" 合并文件数: {len(args.files)}")
|
||||
|
||||
if args.submit:
|
||||
if not args.auth or not args.base:
|
||||
print("[错误] 提交需要 --auth 和 --base 参数", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
print(f"\n[提交] PUT {args.base}/api/v1/lab/notebook/agent-result ...")
|
||||
result = submit(args.base, args.auth, body)
|
||||
print(f" HTTP {result['status_code']}")
|
||||
print(f" 响应: {json.dumps(result['body'], ensure_ascii=False)}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
2
.github/workflows/deploy-docs.yml
vendored
2
.github/workflows/deploy-docs.yml
vendored
@@ -125,4 +125,4 @@ jobs:
|
||||
steps:
|
||||
- name: Deploy to GitHub Pages
|
||||
id: deployment
|
||||
uses: actions/deploy-pages@v4
|
||||
uses: actions/deploy-pages@v5
|
||||
|
||||
@@ -754,6 +754,32 @@ class MessageProcessor:
|
||||
req = JobAddReq(**data)
|
||||
|
||||
job_log = format_job_log(req.job_id, req.task_id, req.device_id, req.action)
|
||||
|
||||
# 服务端对always_free动作可能跳过query_action_state直接发job_start，
|
||||
# 此时job尚未注册，需要自动补注册
|
||||
existing_job = self.device_manager.get_job_info(req.job_id)
|
||||
if not existing_job:
|
||||
action_name = req.action
|
||||
device_action_key = f"/devices/{req.device_id}/{action_name}"
|
||||
action_always_free = self._check_action_always_free(req.device_id, action_name)
|
||||
|
||||
if action_always_free:
|
||||
job_info = JobInfo(
|
||||
job_id=req.job_id,
|
||||
task_id=req.task_id,
|
||||
device_id=req.device_id,
|
||||
action_name=action_name,
|
||||
device_action_key=device_action_key,
|
||||
status=JobStatus.QUEUE,
|
||||
start_time=time.time(),
|
||||
always_free=True,
|
||||
)
|
||||
self.device_manager.add_queue_request(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
|
||||
|
||||
success = self.device_manager.start_job(req.job_id)
|
||||
if not success:
|
||||
logger.error(f"[MessageProcessor] Failed to start job {job_log}")
|
||||
|
||||
@@ -57,7 +57,7 @@ class VirtualSampleDemo:
|
||||
readings.append(round(random.uniform(0.1, 1.0), 4))
|
||||
samples.append(idx)
|
||||
|
||||
return {"volumes": out_volumes, "readings": readings, "samples": samples}
|
||||
return {"volumes": out_volumes, "readings": readings, "unilabos_samples": samples}
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Action 3: 入参和出参都带 samples 列（不等长）
|
||||
@@ -78,7 +78,7 @@ class VirtualSampleDemo:
|
||||
scores.append(score)
|
||||
passed.append(r >= threshold)
|
||||
|
||||
return {"scores": scores, "passed": passed, "samples": samples}
|
||||
return {"scores": scores, "passed": passed, "unilabos_samples": samples}
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 状态属性
|
||||
|
||||
@@ -237,6 +237,7 @@ class Registry:
|
||||
"parent": "unilabos_nodes",
|
||||
"class_name": "unilabos_class",
|
||||
},
|
||||
"always_free": True,
|
||||
},
|
||||
"test_latency": test_latency_action,
|
||||
"auto-test_resource": test_resource_action,
|
||||
|
||||
@@ -313,7 +313,9 @@ class HostNode(BaseROS2DeviceNode):
|
||||
callback_group=self.callback_group,
|
||||
),
|
||||
} # 用来存储多个ActionClient实例
|
||||
self._action_value_mappings: Dict[str, Dict] = {} # device_id -> action_value_mappings(本地+远程设备统一存储)
|
||||
self._action_value_mappings: Dict[str, Dict] = {
|
||||
device_id: self._action_value_mappings
|
||||
} # device_id -> action_value_mappings(本地+远程设备统一存储)
|
||||
self._slave_registry_configs: Dict[str, Dict] = {} # registry_name -> registry_config(含action_value_mappings)
|
||||
self._goals: Dict[str, Any] = {} # 用来存储多个目标的状态
|
||||
self._online_devices: Set[str] = {f"{self.namespace}/{device_id}"} # 用于跟踪在线设备
|
||||
@@ -1621,8 +1623,16 @@ class HostNode(BaseROS2DeviceNode):
|
||||
}
|
||||
return res
|
||||
|
||||
@action(always_free=True, node_type=NodeType.MANUAL_CONFIRM)
|
||||
def manual_confirm(self, **kwargs) -> dict:
|
||||
@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": []
|
||||
})
|
||||
def manual_confirm(self, timeout_seconds: int, assignee_user_ids: list[str], **kwargs) -> dict:
|
||||
"""
|
||||
timeout_seconds: 超时时间（秒），默认3600秒
|
||||
"""
|
||||
return kwargs
|
||||
|
||||
def test_resource(
|
||||
|
||||
@@ -80,11 +80,12 @@ def get_result_info_str(error: str, suc: bool, return_value=None) -> str:
|
||||
Returns:
|
||||
JSON字符串格式的结果信息
|
||||
"""
|
||||
samples = None
|
||||
if isinstance(return_value, dict):
|
||||
if "samples" in return_value and type(return_value["samples"]) in [list, tuple] and type(return_value["samples"][0]) == dict:
|
||||
samples = return_value.pop("samples")
|
||||
result_info = {"error": error, "suc": suc, "return_value": return_value, "samples": samples}
|
||||
# 请在返回的字典中使用 unilabos_samples进行返回
|
||||
# samples = None
|
||||
# if isinstance(return_value, dict):
|
||||
# if "samples" in return_value and type(return_value["samples"]) in [list, tuple] and type(return_value["samples"][0]) == dict:
|
||||
# samples = return_value.pop("samples")
|
||||
result_info = {"error": error, "suc": suc, "return_value": return_value}
|
||||
|
||||
return json.dumps(result_info, ensure_ascii=False, cls=ResultInfoEncoder)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user