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AGENTS.md
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AGENTS.md
@ -125,18 +125,6 @@ System: [...] Feishu[xiaobian] group oc_xxx | 发送者 (ou_xxx) [msg:om_xxx]
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2. **无 `GroupSystemPrompt` 或无特殊任务时：** 不执行任何操作
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3. ⚠️ **最终必须回复 `NO_REPLY`：** 无论是否执行了静默任务，未被 @ 的群聊消息**一律以 `NO_REPLY` 结束**，禁止输出任何对话内容
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**简言之：群聊中未被 @ → 可以做事（静默任务），但绝不说话。**
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#### 何时发言（仅在被 @ 的前提下）
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即使被 @，以下情况仍应保持沉默（NO_REPLY）：
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- 同事之间的闲聊，@ 你只是无意的
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- 已经有人回答了问题
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- 你的回复只是"是的"或"收到"，没有实质价值
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- 对话在没有你的情况下进展顺利
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参与，而非主导。质量 > 数量。
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## 工作区目录规范（强制执行）
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business_knowledge/unit_challenge_all_types.md
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business_knowledge/unit_challenge_all_types.md
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# 单元挑战全部题型 · 生产工作流总览
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> 数据源：飞书 Wiki [【最新】单元挑战全部题型JSON结构说明](https://makee-interactive.feishu.cn/wiki/UUKtwRWQRiPw1Gko3R8cLVfUnCe)
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> Bitable App Token: `CMHSbUUjka3TrUsaxxEc297ongf`
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## 一、全部题型映射（20种）
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### 听力类（6种）
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| # | 题型 | type | 阶段 | Bitable表 | table_id | 技能文件 |
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|---|------|------|------|-----------|----------|---------|
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| 1 | 图片选择题 | `listening_choicePic` | L2 | 听力-P1-图片选择题 | `tbliZAhcc9C43B23` | `L2/listening-choicePic/SKILL.md` |
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| 2 | 表格填空题 | `listening_tableCloze` | L2 | 听力-P2-表格填空题 | `tblzTLNH7f13uWQN` | `L2/listening_form_fill/SKILL.md` |
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| 3 | 长对话选择 | `listening_choiceLong` | L2 | 听力-P3-长对话选择 | `tblgxsDn25oSq7WS` | `L2/listening_long_conversation/SKILL.md` |
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| 4 | 短对话选择题 | `listening_choiceShort` | L2 | 听力-P4-短对话选择题 | `tblVmeDtBDKsAEfz` | `L2/listening_short_conversation/SKILL.md` |
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| 5 | 信息匹配题 | `listening_matchInfo` | L2 | 听力-P5-信息匹配题 | `tblDssVmhGzc3UKd` | `L1+L2/listening_info_match/SKILL.md` |
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| 6 | 听力拖拽 | `listening_drag` | L1 | 听力-P7-听力拖拽 | `tbly9SvPEa44k3yX` | `L1/listening-drag/SKILL.md` |
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### 阅读类（7种）
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| # | 题型 | type | 阶段 | Bitable表 | table_id | 技能文件 |
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|---|------|------|------|-----------|----------|---------|
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| 7 | 信息匹配题 | `reading_matchInfo` | L2 | 阅读-P1-信息匹配题 | `tblCgfYDnnqwLfgH` | `reading_info_match/SKILL.md` |
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| 8 | 段落匹配题 | `reading_matchPara` | L2 | 阅读-P2-段落匹配题 | `tblEp820dnatNYbb` | `reading_paragraph_match/SKILL.md` |
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| 9 | 长文选择题 | `reading_choiceLong` | L2 | 阅读-P3-长文选择题 | `tbl4q0ZUV3HB54t1` | `reading_long_passage/SKILL.md` |
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| 10 | 完形填空题 | `reading_cloze` | L2 | 阅读-P4-完形填空题 | `tblzKVm1FEukPgnN` | `reading_cloze/SKILL.md` |
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| 11 | 开放填空题 | `reading_openCloze` | L2 | 阅读-P5-开放填空题 | `tblLmUxzzUDe0QAJ` | `reading_open_fill/SKILL.md` |
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| 12 | 看图判断题 | `reading_pic_judge` | L1&L2 | 阅读-P6-看图判断题 | `tblJc60aO0T163MJ` | `common/reading_pic_judge/SKILL.md` |
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| 13 | 看图回答题 | `reading_pic_qa` | L1&L2 | 阅读-P7-看图回答题 | `tblweY65jGBiwSdt` | `common/reading_pic_qa/SKILL.md` |
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### 写作类（3种）
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| # | 题型 | type | 阶段 | Bitable表 | table_id | 技能文件 |
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|---|------|------|------|-----------|----------|---------|
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| 14 | 邮件回复 | `writing_email` | L2 | 写作-P1-邮件回复 | `tblszuk1TeToofBF` | `writing_email_reply/SKILL.md` |
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| 15 | 看图写作 | `writing_picWrite` | L2 | 写作-P2-看图写作 | `tblSAwlMumKoyjws` | `writing_picture_writing/SKILL.md` |
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| 16 | 看图回答 | `writing_pic_qa` | L1&L2 | 写作-P3-看图回答题 | `tblFc9TVl2PeM2tg` | `common/writing_pic_qa/SKILL.md` |
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### 口语类（4种）
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| # | 题型 | type | 阶段 | Bitable表 | table_id | 技能文件 |
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|---|------|------|------|-----------|----------|---------|
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| 17 | 日常问答 | `speaking_qa` | L1&L2 | 口语-P1-日常回答 | `tblRGv7k4WH58Jgq` | `common/speaking_daily_qa/SKILL.md` |
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| 18 | 看图回答 | `speaking_pic_qa` | L1 | 口语-P3-看图回答 | `tblOHgNkNer2hGEp` | `L1/speaking_pic_qa/SKILL.md` |
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| 19 | 话题讨论 | `speaking_topic` | L2 | 口语-P2-话题讨论 | `tblGoWYBmVI0IrvQ` | `L1+L2/speaking_topic/SKILL.md` |
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| 20 | 看图识物 | `speaking_pic_recognize` | L1 | 口语-P4-看图识物 | `tblsD2dxaRpLmkXD` | `L1/speaking_pic_recognize/SKILL.md` |
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## 二、通用生产流程
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每类题型遵循统一流程：
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```
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用户输入（含触发关键词）→ 解析（题型type/知识点/难度/ID/题量/能力标签）
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→ 读取对应 SKILL.md 确认JSON结构和规范
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→ 设计题目（校核词汇大纲/句型库/难度匹配）
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→ LLM生成完整jsonData
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→ 写入多维表格（两阶段延迟策略：先空记录等30s → 再PUT jsonData）
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→ 回读验证（题数+抽样Q1内容）
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→ 生成图片描述（如题型需要）→ 回填 图片描述 列
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→ 汇总交付
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```
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## 三、触发关键词体系
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### 按题型 type 触发（精确匹配）
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| type | 关键词 |
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|------|--------|
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| `listening_choicePic` | 听力图片选择 / listening choicePic / 听力P1 |
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| `listening_tableCloze` | 听力表格填空 / listening tableCloze / 听力P2 |
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| `listening_choiceLong` | 听力长对话 / listening choiceLong / 听力P3 |
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| `listening_choiceShort` | 听力短对话 / listening choiceShort / 听力P4 |
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| `listening_matchInfo` | 听力信息匹配 / listening matchInfo / 听力P5 |
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| `listening_drag` | 听力拖拽 / listening drag / 听力P7 |
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| `reading_matchInfo` | 阅读信息匹配 / reading matchInfo / 阅读P1 |
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| `reading_matchPara` | 阅读段落匹配 / reading matchPara / 阅读P2 |
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| `reading_choiceLong` | 阅读长文选择 / reading choiceLong / 阅读P3 |
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| `reading_cloze` | 阅读完形填空 / reading cloze / 阅读P4 |
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| `reading_openCloze` | 阅读开放填空 / reading openCloze / 阅读P5 |
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| `reading_pic_judge` | 阅读看图判断 / reading pic judge / 看图判断题 / 阅读P6 |
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| `reading_pic_qa` | 阅读看图回答 / reading pic qa / 看图回答题 / 阅读P7 |
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| `writing_email` | 写作邮件 / writing email / 邮件回复 / 写作P1 |
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| `writing_picWrite` | 写作看图写作 / writing picWrite / 看图写作 / 写作P2 |
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| `writing_pic_qa` | 写作看图回答 / writing pic qa / 写作P3 |
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| `speaking_qa` | 口语日常问答 / speaking qa / 口语P1 |
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| `speaking_pic_qa` | 口语看图回答 / speaking pic qa / 口语P3 |
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| `speaking_topic` | 口语话题讨论 / speaking topic / 口语P2 |
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| `speaking_pic_recognize` | 口语看图识物 / speaking pic recognize / 口语P4 |
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## 四、生产请求标准格式
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用户提供以下信息即可触发自动生产：
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```
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题型：{type 或 中文名}
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ID：{questionSetID}
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级别：L1/L2
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难度：A/B/C/D
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能力标签：{逗号分隔}
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题组1知识点：{逗号分隔}
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题组2知识点：{逗号分隔}（如适用）
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```
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## 五、Bitable 写入策略（通用）
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所有表均存在自动化覆盖问题，统一使用两阶段延迟写入：
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1. **删除旧记录** → 清理同ID的损坏记录
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2. **创建空记录** → 仅写入 `题目集合ID` + `dataStatus`
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3. **等待30秒** → 让自动化完成模板覆写
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4. **PUT jsonData** → 写入完整 JSON
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5. **等待 >10秒** → 最终回读验证
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6. **抽样检查** → Q1 内容是否匹配（确认未被自动化替换为空壳）
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## 六、参考：各题型JSON结构特点
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### 听力类
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- **choicePic**: questionSet[].question + questionAudio + optionsImage[] + answer[]
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- **tableCloze**: textTitle + textBody(含[0][1]占位) + textDesc + textAudio + questionSet[].options[] + answer[]
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- **choiceLong**: textDesc + textAudio + questionSet[].question + options[] + answer[]
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- **choiceShort**: questionSet[].question + questionAudio + questionDesc + options[] + answer[]
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- **matchInfo**: textTitle + textBody(含[0][1]占位) + textDesc + textAudio + optionSetTitle + optionSetList[] + answerSet[]
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- **drag**: textDesc + textAudio + questionSet[].answer[] + imageInfo + optionList[]
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### 阅读类
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- **matchInfo**: questionSet[].questionImage + question + options[] + answer[]
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- **matchPara**: textTitle + textBody + questionSet[].question + options[] + answer[]
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- **choiceLong**: textTitle + textSubtitle + textBody + questionSet[].question + options[] + answer[]
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- **cloze**: textTitle + textBody(含[0][1]占位) + questionSet[].options[] + answer[]
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- **openCloze**: textTitle + textBody(含[0][1]占位) + questionSet[].options[] + answer[]
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- **pic_judge**: 使用 first/second 包裹，每组含 textTitle + textImage + questionSet[].question + answerText(Yes/No)
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- **pic_qa**: 使用 first/second 包裹，每组含 textTitle + textImage + questionSet[].question + answerText(Yes/No)
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### 写作类
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- **email**: textDesc + optionSetList[] + answerSet[]
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- **picWrite**: textDesc + textImage + optionSetList[] + answerSet[]
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- **pic_qa**: questionSet[].questionImage + questionList[].question + questionDesc + answerText
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### 口语类
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- **qa**: asrPrompt + textDesc + questionSet[].content
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- **pic_qa**: asrPrompt + textDesc + textImage + imageDesc + questionSet[].content
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- **topic**: asrPrompt + textDesc + textImage + imageDesc + questionSet[].content
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- **pic_recognize**: asrPrompt + textTitle + questionSet[].question + questionImage + imageDesc
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## 七、已生产记录
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### reading_pic_qa（2026-05-11）
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- 000001, 010101, 010201, 010301, 010401, 010501, 010601（7套 L2 A级）
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- 含图片描述
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- 脚本：`scripts/batch_reading_pic_qa.py`、`scripts/batch_create_delayed.py`、`scripts/update_image_descriptions.py`
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@ -6,12 +6,11 @@ description: K12英语听力三选一图片选择题标准化设计、生产、
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## 题型说明
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本技能对应官方题型：**L2 - Movers - 听力 Part3 三选一图片选择【阶段归属：L2专属】**，考察核心能力为**显性事实理解（单句信息点抓取）**：学生听单句听力内容，从3张图片选项中选出与听力内容匹配的正确答案。
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## 难度对应关系（与教研标准对齐）
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| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
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|----------|------------|------------------|----------|
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| A级 | L1 第1-2阶段 | Starters 1-2 | 选项差异极大（类别完全不同），听力为3-5词简单句，关键词后置 |
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| B级 | L1 第3-4阶段 | Starters 3 | 选项为同类物品差异（颜色/大小不同），听力为5-8词简单句 |
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| C级 | L1 第5-6阶段 | Movers 1 | 选项为动作/状态差异，听力为8-12词带介词短语的句子 |
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| D级 | L2 第1-2阶段 | Movers 2-3 | 选项为场景/逻辑差异，听力为12-15词带简单从句的句子 |
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| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
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| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 选项差异极大（类别完全不同），听力为3-5词简单句，关键词后置 |
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| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 选项为同类物品差异（颜色/大小不同），听力为5-8词简单句 |
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| C级 | U25-U36（阶段5-6） | KET基础→强化 | 选项为动作/状态差异，听力为8-12词带介词短语的句子 |
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| D级 | U37-U48（阶段7-8） | KET高位→达标 | 选项为场景/逻辑差异，听力为12-15词带简单从句的句子 |
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## 能力标签绑定规则
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1. 题型固定绑定通用能力标签：听力理解、图片信息识别、单句信息抓取
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2. 每道题专属能力标签（与官方45个能力tag对齐）：
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@ -30,7 +29,7 @@ description: K12英语听力三选一图片选择题标准化设计、生产、
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| 参数 | 必填 | 格式示例 | 说明 |
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|------|------|----------|------|
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| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
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| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
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| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
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| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
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| 场景要求 | 🟢 | `场景为家庭厨房` | 指定题目场景，不指定则自动匹配知识点 |
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## 输出格式规范
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@ -6,12 +6,11 @@ description: K12英语听力表格填空题标准化设计、生产、审校工
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## 题型说明
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本技能对应官方题型：**L2 - Movers - 听力 Part2 表格填空【阶段归属：L2专属】**，考察核心能力为**信息抓取（关键词识别+拼写准确性）**：学生听1-2段短对话/独白，提取关键信息填写表格中空缺的内容，考察词汇拼写、数字识别、信息匹配能力。
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## 难度对应关系（与教研标准对齐）
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| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
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|----------|------------|------------------|----------|
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| A级 | L1 第1-2阶段 | Starters 1-2 | 表格仅2-3个空缺，答案为1-2个字母/数字，听力直接念出答案 |
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| B级 | L1 第3-4阶段 | Starters 3 | 表格3-4个空缺，答案为3-5个字母的单词，听力直接念出答案 |
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| C级 | L1 第5-6阶段 | Movers 1 | 表格4-5个空缺，答案为单词/短语，听力包含简单干扰信息 |
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| D级 | L2 第1-2阶段 | Movers 2-3 | 表格5-6个空缺，答案为短语/短句，听力包含较多干扰信息 |
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| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
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| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 表格仅2-3个空缺，答案为1-2个字母/数字，听力直接念出答案 |
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| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 表格3-4个空缺，答案为3-5个字母的单词，听力直接念出答案 |
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| C级 | U25-U36（阶段5-6） | KET基础→强化 | 表格4-5个空缺，答案为单词/短语，听力包含简单干扰信息 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 表格5-6个空缺，答案为短语/短句，听力包含较多干扰信息 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：听力理解、信息抓取、拼写准确性
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语听力表格填空题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为学校报名` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语听力信息匹配题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 听力 Part5 信息匹配【阶段归属：L2专属】**，考察核心能力为**信息关联（多任务处理+干扰抑制）**：学生听1段长对话/独白，将左右两栏的相关信息进行匹配，考察对多个信息点的关联、记忆和区分能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 匹配项5组，信息直接对应，无干扰 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 匹配项5-6组，信息需要简单关联，1个干扰项 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 匹配项6组，信息需要整合关联，2个干扰项 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 匹配项6-7组，信息需要推断关联，3个干扰项 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 匹配项5组，信息直接对应，无干扰 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 匹配项5-6组，信息需要简单关联，1个干扰项 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 匹配项6组，信息需要整合关联，2个干扰项 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 匹配项6-7组，信息需要推断关联，3个干扰项 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：听力理解、信息关联、干扰抑制
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语听力信息匹配题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为生日派对` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语听力长对话选择题标准化设计、生产、审校
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 听力 Part3 长对话选择【阶段归属：L2专属】**，考察核心能力为**逻辑理解（信息整合+干扰抑制）**：学生听1段3-5轮的长对话，回答3-4道选择题，考察对对话整体逻辑、隐含信息、因果关系的理解能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 对话3轮，3道题，答案直接对应对话内容，无干扰 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 对话4轮，3道题，答案需要简单推理，1个干扰项 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 对话5轮，4道题，答案需要逻辑整合，2个干扰项 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 对话6轮，4道题，答案需要隐含信息推断，3个干扰项 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 对话3轮，3道题，答案直接对应对话内容，无干扰 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 对话4轮，3道题，答案需要简单推理，1个干扰项 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 对话5轮，4道题，答案需要逻辑整合，2个干扰项 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 对话6轮，4道题，答案需要隐含信息推断，3个干扰项 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：听力理解、逻辑推理、信息整合
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语听力长对话选择题标准化设计、生产、审校
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为周末购物` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语听力短对话选择题标准化设计、生产、审校
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 听力 Part4 短对话选择【阶段归属：L2专属】**，考察核心能力为**场景理解（快速信息抓取+反应）**：学生听多段1-2轮的短对话，每段对话对应1道选择题，考察对常见场景、日常用语的理解能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第1-2阶段 | Starters 1-2 | 每段对话1轮，问题直接问物品/场景，答案直接明确 |
|
||||
| B级 | L1 第3-4阶段 | Starters 3 | 每段对话1-2轮，问题问物品属性/人物动作，答案简单明确 |
|
||||
| C级 | L1 第5-6阶段 | Movers 1 | 每段对话2轮，问题问人物意图/事件结果，需要简单推理 |
|
||||
| D级 | L2 第1-2阶段 | Movers 2-3 | 每段对话2轮，问题问隐含观点/未来计划，需要推理 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 每段对话1轮，问题直接问物品/场景，答案直接明确 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 每段对话1-2轮，问题问物品属性/人物动作，答案简单明确 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 每段对话2轮，问题问人物意图/事件结果，需要简单推理 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 每段对话2轮，问题问隐含观点/未来计划，需要推理 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：听力理解、场景识别、快速反应
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语听力短对话选择题标准化设计、生产、审校
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1套（5段对话） |
|
||||
| 场景要求 | 🟢 | `场景为家庭日常` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -11,6 +11,12 @@ description: K12英语阅读看图判断题标准化设计、生产、审校工
|
||||
- 答案统一为"Yes"或"No"
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|
||||
> **L2 难度维度（对标 Flyers/KET，每2阶段为1个难度等级）：**
|
||||
> - A级 = U1-U12（阶段1-2）：Flyers入门→Flyers基础
|
||||
> - B级 = U13-U24（阶段3-4）：Flyers达标→KET入门
|
||||
> - C级 = U25-U36（阶段5-6）：KET基础→KET强化
|
||||
> - D级 = U37-U48（阶段7-8）：KET高位→KET达标
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第1-2阶段 | Starters 1-2 | 句子为1-3词极简陈述句（如"These are grapes."），图片为单一物品，判断直接 |
|
||||
| B级 | L1 第3-4阶段 | Starters 3 | 句子为4-6词简单陈述句，图片为单一物品+简单背景，需辨识颜色/数量属性 |
|
||||
@ -37,7 +43,7 @@ description: K12英语阅读看图判断题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `grape n.葡萄;house n.房子;helicopter n.直升机` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级（L1用Starters/Movers，L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认5道 |
|
||||
| 场景要求 | 🟢 | `场景为日常物品` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范（JSON）
|
||||
|
||||
@ -11,6 +11,12 @@ description: K12英语阅读看图回答题标准化设计、生产、审校工
|
||||
- 答案统一为"Yes"或"No"
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|
||||
> **L2 难度维度（对标 Flyers/KET，每2阶段为1个难度等级）：**
|
||||
> - A级 = U1-U12（阶段1-2）：Flyers入门→Flyers基础
|
||||
> - B级 = U13-U24（阶段3-4）：Flyers达标→KET入门
|
||||
> - C级 = U25-U36（阶段5-6）：KET基础→KET强化
|
||||
> - D级 = U37-U48（阶段7-8）：KET高位→KET达标
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第1-2阶段 | Starters 1-2 | 句子为3-5词简单陈述句，考察单个名词/属性匹配，图片元素差异明显 |
|
||||
| B级 | L1 第3-4阶段 | Starters 3 | 句子为5-8词简单陈述句，考察多个名词/属性匹配，图片包含多人/多物但干扰少 |
|
||||
@ -37,7 +43,7 @@ description: K12英语阅读看图回答题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `hat n.帽子;beach n.海滩;book n.书;shell n.贝壳` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级（L1用Starters/Movers，L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量（小题数），默认5道 |
|
||||
| 场景要求 | 🟢 | `场景为阳光海滩` | 指定场景内容，不指定则自动匹配知识点 |
|
||||
## 输出格式规范（JSON）
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语阅读完形填空题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 阅读 Part4 完形填空【阶段归属：L2专属】**，考察核心能力为**词汇运用（语法判断+上下文逻辑理解）**：学生阅读1篇80-150词的短文，文中有3-5个空缺，每个空缺从3个选项中选择正确的单词填入，考察词汇、语法和上下文理解能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 短文80词左右，3个空，考察名词/形容词等实词，上下文提示明显 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 短文100词左右，4个空，考察实词+简单介词/动词，上下文有提示 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 短文120词左右，5个空，考察实词+虚词，需要简单逻辑判断 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 短文150词左右，5个空，考察词汇+语法+逻辑，需要上下文推断 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 短文80词左右，3个空，考察名词/形容词等实词，上下文提示明显 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 短文100词左右，4个空，考察实词+简单介词/动词，上下文有提示 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 短文120词左右，5个空，考察实词+虚词，需要简单逻辑判断 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 短文150词左右，5个空，考察词汇+语法+逻辑，需要上下文推断 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：阅读理解、词汇运用、逻辑推理
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语阅读完形填空题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为生日派对` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语阅读信息匹配题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 阅读 Part1 信息匹配【阶段归属：L2专属】**，考察核心能力为**信息抓取（快速阅读+图文匹配）**：学生阅读5-6个简短文本（标识/告示/短句），与对应的图片/标题进行匹配，考察快速抓取关键信息和图文匹配能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第1-2阶段 | Starters 1-2 | 文本为1-2个单词，图片差异极大，直接对应 |
|
||||
| B级 | L1 第3-4阶段 | Starters 3 | 文本为3-5词短句，图片为同类差异，简单对应 |
|
||||
| C级 | L1 第5-6阶段 | Movers 1 | 文本为5-8词短句，需要提取关键词匹配 |
|
||||
| D级 | L2 第1-2阶段 | Movers 2-3 | 文本为8-10词短句，包含干扰信息，需要筛选匹配 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 文本为1-2个单词，图片差异极大，直接对应 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 文本为3-5词短句，图片为同类差异，简单对应 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 文本为5-8词短句，需要提取关键词匹配 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 文本为8-10词短句，包含干扰信息，需要筛选匹配 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：阅读理解、信息抓取、快速阅读
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语阅读信息匹配题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1套（6小题） |
|
||||
| 场景要求 | 🟢 | `场景为公共场所标识` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语阅读长文选择题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 阅读 Part3 长文选择【阶段归属：L2专属】**，考察核心能力为**篇章理解（细节定位+推理判断）**：学生阅读1篇100-200词的短文，回答3-4道选择题，考察对篇章整体内容、细节信息、推理判断的能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 短文100词左右，3道题，答案直接在原文中出现 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 短文120-150词，3道题，答案需要简单定位 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 短文150-180词，4道题，答案需要简单推理 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 短文180-200词，4道题，答案需要逻辑推断 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 短文100词左右，3道题，答案直接在原文中出现 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 短文120-150词，3道题，答案需要简单定位 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 短文150-180词，4道题，答案需要简单推理 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 短文180-200词，4道题，答案需要逻辑推断 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：阅读理解、细节定位、推理判断
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语阅读长文选择题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为周末活动` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语阅读开放填空题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 阅读 Part5 开放填空【阶段归属：L2专属】**，考察核心能力为**信息提取（词汇拼写+语法正确性）**：学生阅读1篇短文/通知/表格，根据要求填写3-5个空缺的单词，无选项提示，考察信息提取、词汇拼写和语法正确性。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 空缺3个，答案为1-4个字母的简单名词，原文直接给出 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 空缺4个，答案为名词/形容词，原文直接给出，需要简单变形 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 空缺5个，答案为动词/短语，需要从原文提取后变形 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 空缺5个，答案需要根据原文信息归纳总结，符合语法要求 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 空缺3个，答案为1-4个字母的简单名词，原文直接给出 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 空缺4个，答案为名词/形容词，原文直接给出，需要简单变形 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 空缺5个，答案为动词/短语，需要从原文提取后变形 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 空缺5个，答案需要根据原文信息归纳总结，符合语法要求 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：阅读理解、信息提取、词汇拼写
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语阅读开放填空题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为活动通知` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语阅读段落匹配题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 阅读 Part2 段落匹配【阶段归属：L2专属】**，考察核心能力为**主旨理解（信息归纳+快速阅读）**：学生阅读4-5个简短段落，与对应的段落标题/主旨句进行匹配，考察归纳段落主旨和抓取核心信息的能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 段落3-4句话，主旨直接明确，无干扰 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 段落4-5句话，主旨需要简单归纳，1个干扰项 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 段落5-6句话，主旨需要整合信息，2个干扰项 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 段落6-7句话，主旨需要隐含推断，3个干扰项 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 段落3-4句话，主旨直接明确，无干扰 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 段落4-5句话，主旨需要简单归纳，1个干扰项 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 段落5-6句话，主旨需要整合信息，2个干扰项 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 段落6-7句话，主旨需要隐含推断，3个干扰项 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：阅读理解、主旨归纳、快速阅读
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语阅读段落匹配题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为校园生活` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语口语话题讨论题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 口语 Part2 话题讨论【阶段归属：L2专属】**，考察核心能力为**口语表达（逻辑组织+观点阐述）**：学生根据给定话题，进行1-2分钟的口头阐述，考察词汇运用、逻辑连贯、观点表达能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 话题为具体物品/活动，回答3-4句话即可，无需复杂逻辑 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 话题为喜好/习惯，回答4-5句话，有简单逻辑顺序 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 话题为观点/经历，回答5-6句话，有清晰逻辑层次 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 话题为抽象感受/计划，回答6-8句话，逻辑连贯有支撑 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 话题为具体物品/活动，回答3-4句话即可，无需复杂逻辑 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 话题为喜好/习惯，回答4-5句话，有简单逻辑顺序 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 话题为观点/经历，回答5-6句话，有清晰逻辑层次 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 话题为抽象感受/计划，回答6-8句话，逻辑连贯有支撑 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：口语表达、逻辑组织、观点阐述
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语口语话题讨论题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `话题为食物` | 指定话题范围，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -7,6 +7,12 @@ description: K12英语口语日常回答题标准化设计、生产、审校工
|
||||
本技能对应官方题型：**口语 Part1 日常回答【阶段归属：L1&L2共用，通过难度参数区分】**，考察核心能力为**口语表达（日常用语运用+快速反应）**：学生回答3-4个日常问题，每个问题回答1-3句话，考察日常词汇、句式的运用能力和表达流畅度。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|
||||
> **L2 难度维度（对标 Flyers/KET，每2阶段为1个难度等级）：**
|
||||
> - A级 = U1-U12（阶段1-2）：Flyers入门→Flyers基础
|
||||
> - B级 = U13-U24（阶段3-4）：Flyers达标→KET入门
|
||||
> - C级 = U25-U36（阶段5-6）：KET基础→KET强化
|
||||
> - D级 = U37-U48（阶段7-8）：KET高位→KET达标
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第1-2阶段 | Starters 1-2 | 问题为个人基本信息类，答案为1-2个单词/短语即可 |
|
||||
| B级 | L1 第3-4阶段 | Starters 3 | 问题为喜好/日常活动类，答案为1个简单句即可 |
|
||||
@ -31,7 +37,7 @@ description: K12英语口语日常回答题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `L1第2阶段` / `Starters 2` | 难度等级（L1用Starters/Movers，L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1套（4个问题） |
|
||||
| 场景要求 | 🟢 | `场景为个人介绍` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -73,20 +73,27 @@ description: K12英语写作看图回答题标准化设计、生产、审校工
|
||||
|
||||
### 3.3 语言难度 = 欧标 A1-A2
|
||||
|
||||
- 句型控制在 Starters/Movers 级别（A1-A2）
|
||||
- 句型控制在 Starters（L1）/ Flyers-KET（L2）级别
|
||||
- L1 对标 A1（Starters/Movers），L2 对标 A1-A2（Flyers/KET）
|
||||
- 题干用词优先使用 L1 词库词汇（`business_knowledge/L1_word_list.json`）
|
||||
- 基础功能词（代词、be动词、介词）当前 L1/L2 词库暂不收录，写题时绕过词汇校验硬性约束
|
||||
|
||||
### 3.4 阶段变化原则
|
||||
|
||||
当前规格适用 **L2 第一阶段（Unit0-6）**，后续阶段规则将随难度递增而变化：
|
||||
当前规格适用 **L2 U1-U6（阶段1，A级，Flyers入门）**，后续阶段规则将随难度递增而变化：
|
||||
|
||||
| 维度 | L2 Unit0-6（当前） | 后续阶段 |
|
||||
|------|-------------------|---------|
|
||||
| 维度 | L2 U1-U6（阶段1，A级） | 后续阶段 |
|
||||
|------|----------------------|---------|
|
||||
| 挖空单位 | 1 个单词 | 短语 / 完整句子 |
|
||||
| 题组小题数 | 2 小题 / 题组 | 4 小题 / 题组 |
|
||||
| 能力标签 | 简短作答 / 一词答案 | （待补充） |
|
||||
|
||||
> **L2 8阶段难度体系（每2阶段为1个难度等级）：**
|
||||
> - A级 = U1-U12（阶段1-2）：Flyers入门→Flyers基础
|
||||
> - B级 = U13-U24（阶段3-4）：Flyers达标→KET入门
|
||||
> - C级 = U25-U36（阶段5-6）：KET基础→KET强化
|
||||
> - D级 = U37-U48（阶段7-8）：KET高位→KET达标
|
||||
|
||||
### 3.5 题干多样化
|
||||
|
||||
同一题包内的 question 不能全部相同，应随语境微调：
|
||||
@ -239,7 +246,7 @@ description: K12英语写作看图回答题标准化设计、生产、审校工
|
||||
| questionList[].question | ✅ | string | 问题（问角色说了什么，口语化，各题微调） |
|
||||
| questionList[].questionDesc | ✅ | string | 提示答案开头，含字母数标记如 `(5)` |
|
||||
| questionList[].answerText | ✅ | string | 标准答案（1个单词） |
|
||||
| questionList[].ability | ✅ | array | L2 Unit0-6 阶段固定 `["简短作答", "一词答案"]` |
|
||||
| questionList[].ability | ✅ | array | L2 U1-U6（阶段1，A级）固定 `["简短作答", "一词答案"]` |
|
||||
| questionList[].explanation | ✅ | string | 解析：图片内容 + 考点 + 字母数 |
|
||||
|
||||
---
|
||||
@ -352,13 +359,19 @@ description: K12英语写作看图回答题标准化设计、生产、审校工
|
||||
|
||||
## 九、阶段与难度对应
|
||||
|
||||
当前首个阶段为 **L2 Unit0-6**，后续阶段规则将随难度递增：
|
||||
当前首个阶段为 **L2 U1-U6（阶段1，A级，Flyers入门）**，后续阶段规则将随难度递增：
|
||||
|
||||
| 阶段 | 难度 | 剑桥对标 | 挖空单位 | 小题/题组 | 能力标签 |
|
||||
|------|------|---------|---------|----------|---------|
|
||||
| L2 Unit0-6（当前） | A级 | Starters 1-2 | 1个核心词 | 2 小题 | 简短作答 / 一词答案 |
|
||||
| 阶段 | 难度 | 对标 | 挖空单位 | 小题/题组 | 能力标签 |
|
||||
|------|------|------|---------|----------|---------|
|
||||
| L2 U1-U6（阶段1） | A级 | Flyers入门 | 1个核心词 | 2 小题 | 简短作答 / 一词答案 |
|
||||
| L2 后续阶段 | B/C/D | (待补充) | 短语 / 句子 | 4 小题 | (待补充) |
|
||||
|
||||
> **L2 完整 8 阶段难度体系（每2阶段为1个难度等级）：**
|
||||
> - A级 = U1-U12（阶段1-2）：Flyers入门→Flyers基础
|
||||
> - B级 = U13-U24（阶段3-4）：Flyers达标→KET入门
|
||||
> - C级 = U25-U36（阶段5-6）：KET基础→KET强化
|
||||
> - D级 = U37-U48（阶段7-8）：KET高位→KET达标
|
||||
|
||||
> **历史 L1 规则（供参考）：**
|
||||
>
|
||||
> | 难度等级 | 对应阶段 | 剑桥对标 | 答案要求 |
|
||||
@ -372,7 +385,7 @@ description: K12英语写作看图回答题标准化设计、生产、审校工
|
||||
|
||||
## 十、能力标签
|
||||
|
||||
- **L2 Unit0-6 阶段：** `["简短作答", "一词答案"]`
|
||||
- **L2 U1-U6（阶段1，A级）：** `["简短作答", "一词答案"]`
|
||||
- 后续阶段的能力标签将在交付时逐个补充
|
||||
- 所有同阶段产出的题目，能力标签必须统一
|
||||
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语写作邮件回复题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 写作 Part1 邮件回复【阶段归属：L2专属】**，考察核心能力为**书面表达（格式规范+信息提取）**：学生阅读一封简短邮件，根据要求写20-50词的回复邮件，考察邮件格式、信息完整性、语言正确性。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 回复要求明确，只需回答2个简单问题，20-30词，格式简单 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 回复要求回答3个问题，30-40词，包含问候和结尾 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 回复要求回答3个问题+1个附加要求，40-50词，格式完整 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 回复要求回答3个问题+表达个人观点，50-60词，语言连贯 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 回复要求明确，只需回答2个简单问题，20-30词，格式简单 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 回复要求回答3个问题，30-40词，包含问候和结尾 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 回复要求回答3个问题+1个附加要求，40-50词，格式完整 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 回复要求回答3个问题+表达个人观点，50-60词，语言连贯 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：书面表达、格式规范、信息提取
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语写作邮件回复题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为生日派对邀请` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -6,12 +6,11 @@ description: K12英语写作看图写作题标准化设计、生产、审校工
|
||||
## 题型说明
|
||||
本技能对应官方题型：**L2 - Movers - 写作 Part2 看图写作【阶段归属：L2专属】**，考察核心能力为**书面表达（图片观察+逻辑组织）**：学生根据1-3张图片的提示，写3-5句话的短文，考察图片信息提取、语言组织、逻辑连贯能力。
|
||||
## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L1/L2阶段 | 对应剑桥考试等级 | 难度描述 |
|
||||
|----------|------------|------------------|----------|
|
||||
| A级 | L1 第5-6阶段 | Movers 1 | 1张简单图片，写3句话，描述图片内容即可 |
|
||||
| B级 | L2 第1-2阶段 | Movers 2 | 2张连续图片，写4句话，描述事件过程 |
|
||||
| C级 | L2 第3-4阶段 | Movers 3 | 3张连续图片，写5句话，描述完整事件 |
|
||||
| D级 | L2 第5-6阶段 | Flyers 1 | 3张连续图片，写6句话，描述事件+表达感受 |
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
| A级 | U1-U12（阶段1-2） | Flyers入门→基础 | 1张简单图片，写3句话，描述图片内容即可 |
|
||||
| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 | 2张连续图片，写4句话，描述事件过程 |
|
||||
| C级 | U25-U36（阶段5-6） | KET基础→强化 | 3张连续图片，写5句话，描述完整事件 |
|
||||
| D级 | U37-U48（阶段7-8） | KET高位→达标 | 3张连续图片，写6句话，描述事件+表达感受 |
|
||||
## 能力标签绑定规则
|
||||
1. 题型固定绑定通用能力标签：书面表达、图片观察、逻辑组织
|
||||
2. 能力标签分级规则：
|
||||
@ -31,7 +30,7 @@ description: K12英语写作看图写作题标准化设计、生产、审校工
|
||||
| 参数 | 必填 | 格式示例 | 说明 |
|
||||
|------|------|----------|------|
|
||||
| 知识点 | ✅ | `apple n.苹果;red adj.红色;eat v.吃` | 考察的核心知识点列表 |
|
||||
| 难度等级 | ✅ | `A级` / `L2第2阶段` / `Movers 2` | 难度等级或对应阶段 |
|
||||
| 难度等级 | ✅ | `A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础` | 难度等级（L2用Unit范围） |
|
||||
| 题量 | 🟢 | `5` | 生成题目数量，默认1道 |
|
||||
| 场景要求 | 🟢 | `场景为公园玩耍` | 指定题目场景，不指定则自动匹配知识点 |
|
||||
## 输出格式规范
|
||||
|
||||
@ -1,3 +1,7 @@
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-07T08:48:55.437Z","query":"王璐辰 user_id permissions","resultCount":1,"results":[{"path":"memory/2026-05-07.md","startLine":57,"endLine":74,"score":0.6621249966506227}]}
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-08T01:18:18.412Z","query":"writing_pic_qa 写作看图回答题 生产规则","resultCount":3,"results":[{"path":"memory/2026-05-07.md","startLine":215,"endLine":235,"score":1},{"path":"memory/2026-05-07.md","startLine":199,"endLine":219,"score":1},{"path":"memory/2026-05-07.md","startLine":1,"endLine":20,"score":1}]}
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-09T02:03:53.176Z","query":"reading_pic_judge bitable 多维表格 table_id 121301","resultCount":1,"results":[{"path":"memory/2026-05-07.md","startLine":1,"endLine":20,"score":1}]}
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-11T02:19:37.985Z","query":"单元挑战 unit challenge 题型 审校规范 互动组件 样题","resultCount":2,"results":[{"path":"memory/2026-04-13.md","startLine":1,"endLine":5,"score":1},{"path":"memory/2026-05-08.md","startLine":33,"endLine":55,"score":1}]}
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-11T02:37:23.203Z","query":"writing_pic_qa 看图回答题 生产流程 bitable writing","resultCount":5,"results":[{"path":"memory/2026-05-07.md","startLine":215,"endLine":235,"score":1},{"path":"memory/2026-05-08.md","startLine":33,"endLine":55,"score":1},{"path":"memory/2026-05-07.md","startLine":199,"endLine":219,"score":1},{"path":"memory/2026-05-08.md","startLine":1,"endLine":23,"score":1},{"path":"memory/2026-05-07.md","startLine":1,"endLine":20,"score":1}]}
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-11T02:37:23.204Z","query":"reading_pic_qa 看图回答题 口语看图回答题 speaking_pic_qa","resultCount":1,"results":[{"path":"memory/2026-05-07.md","startLine":1,"endLine":20,"score":1}]}
|
||||
{"type":"memory.recall.recorded","timestamp":"2026-05-11T02:51:47.112Z","query":"reading_pic_qa bitable table_id 单元挑战 阅读","resultCount":1,"results":[{"path":"memory/2026-05-07.md","startLine":1,"endLine":20,"score":1}]}
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
{
|
||||
"version": 1,
|
||||
"updatedAt": "2026-05-09T02:03:53.176Z",
|
||||
"updatedAt": "2026-05-11T02:51:47.112Z",
|
||||
"entries": {
|
||||
"memory:memory/2026-05-07.md:57:74": {
|
||||
"key": "memory:memory/2026-05-07.md:57:74",
|
||||
@ -40,18 +40,20 @@
|
||||
"endLine": 235,
|
||||
"source": "memory",
|
||||
"snippet": "3. He is (4) Japan. → from（男孩穿和服，背景富士山） 4. She is a (7). → student（女孩背书包进校门） - **JSON 结构：** questionSetID=020102, category=writing, type=writing_pic_qa - **关键教训：** - 初版设计错误：让学手写 Anna/China 等非知识点词，被用户纠正 - 初版 questionDesc \"She is a (7) girl.\" 不自然，修正为 \"She is a (7).\" - writing_pic_qa 题型核心考察点：知识点词本身（am/from），而非题干已知信息 - 挖空字母数标记（如(4)）必须与答案单词字母数一致 - **词库缺口发现：** L1和L2词库均缺失人称代词(I/you/he/she)、be动词(am/is/are)、介词(from)、国家名等基础功能词，写题时先绕过词汇校验硬性约束 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 单元挑战新增3个题型（已完结） - 详见上文 11:19-11:28 记录 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 写作看图回答题 \"I am ready / Thank you\" 样题生产 - **时间：** 15:53 ~ 15:55 - **需求：** 使用知识点 \"I am ready! / Thank you for...\" 再生产一套",
|
||||
"recallCount": 1,
|
||||
"recallCount": 2,
|
||||
"dailyCount": 0,
|
||||
"groundedCount": 0,
|
||||
"totalScore": 1,
|
||||
"totalScore": 2,
|
||||
"maxScore": 1,
|
||||
"firstRecalledAt": "2026-05-08T01:18:18.412Z",
|
||||
"lastRecalledAt": "2026-05-08T01:18:18.412Z",
|
||||
"lastRecalledAt": "2026-05-11T02:37:23.203Z",
|
||||
"queryHashes": [
|
||||
"390d35f8d143"
|
||||
"390d35f8d143",
|
||||
"be437071312f"
|
||||
],
|
||||
"recallDays": [
|
||||
"2026-05-08"
|
||||
"2026-05-08",
|
||||
"2026-05-11"
|
||||
],
|
||||
"conceptTags": [
|
||||
"writing-pic-qa",
|
||||
@ -71,18 +73,20 @@
|
||||
"endLine": 219,
|
||||
"source": "memory",
|
||||
"snippet": "### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 写作看图回答题 \"I am... / I am from...\" 样题生产 - **时间：** 15:38 ~ 15:52 - **需求：** 使用知识点 \"I am... / I am from...\" 生产一套写作看图回答题（writing_pic_qa） - **状态：** ✅ 已完成，用户确认 - **题型级别：** L2（因L1词库缺少所有代词/be动词/介词/国家名） - **难度：** A级 - **题量：** 4小题 - **核心原则（用户明确）：** 1. 挖空必须是考察知识点本身的单词（am/from/student），不是手写姓名/国名等附带信息 2. 只能为1个单词挖空，不能两个及以上 3. 正确模式示例：`I (2) Anna.` → 挖空am，数字标记字母数 4. 图片提供语境线索（名牌→am，地标→from国家，书包→student），学生填写核心知识点词 - **输出文件：** `output/writing_pic_qa_I_am_from_020102.json` - **题目清单：** 1. I (2) Anna. → am（女孩指着名牌，图片语境提示姓名已给出） 2. I am (4) China. → from（女孩站在长城前，国家名已给出） 3. He is (4) Japan. → from（男孩穿和服，背景富士山） 4. She is a (7). → student（女孩背书包进校门） - **JSON",
|
||||
"recallCount": 1,
|
||||
"recallCount": 2,
|
||||
"dailyCount": 0,
|
||||
"groundedCount": 0,
|
||||
"totalScore": 1,
|
||||
"totalScore": 2,
|
||||
"maxScore": 1,
|
||||
"firstRecalledAt": "2026-05-08T01:18:18.412Z",
|
||||
"lastRecalledAt": "2026-05-08T01:18:18.412Z",
|
||||
"lastRecalledAt": "2026-05-11T02:37:23.203Z",
|
||||
"queryHashes": [
|
||||
"390d35f8d143"
|
||||
"390d35f8d143",
|
||||
"be437071312f"
|
||||
],
|
||||
"recallDays": [
|
||||
"2026-05-08"
|
||||
"2026-05-08",
|
||||
"2026-05-11"
|
||||
],
|
||||
"conceptTags": [
|
||||
"writing-pic-qa",
|
||||
@ -102,20 +106,24 @@
|
||||
"endLine": 20,
|
||||
"source": "memory",
|
||||
"snippet": "# 2026-05-07 工作日志 ## 会话记录 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 单元挑战新增3个题型 - **时间：** 11:19 ~ 11:28 - **需求：** 单元挑战新增3个题型：阅读看图回答题（reading_pic_qa）、阅读看图判断题（reading_pic_judge）、写作看图回答题（writing_pic_qa） - **状态：** ✅ 已完成题型规范落地 - **交付内容：** 1. 创建3个题型SKILL.md： - `reading/common/reading_pic_qa/SKILL.md` — 阅读看图回答题（共享大图+多题Yes/No判断） - `reading/common/reading_pic_judge/SKILL.md` — 阅读看图判断题（每题独立配图+Yes/No判断） - `writing/common/writing_pic_qa/SKILL.md` — 写作看图回答题（看图+提示答案开头+填空） 2. 更新 `MEMORY.md` 全题型阶段归属规则 3. 明确题型JSON结构、难度等级（A/B/C/D四级）、能力标签、校验规则 - **关键决策：** 3个题型均为 L1&L2 共用，通过难度参数区分阶段；reading_pic_qa 共享大图，reading_pic_judge 每题独立配图 ### 李应瑛 (ou_1bd7317ae2ccfeb57e1132028847279e) — 单词表对比请求",
|
||||
"recallCount": 2,
|
||||
"recallCount": 5,
|
||||
"dailyCount": 0,
|
||||
"groundedCount": 0,
|
||||
"totalScore": 2,
|
||||
"totalScore": 5,
|
||||
"maxScore": 1,
|
||||
"firstRecalledAt": "2026-05-08T01:18:18.412Z",
|
||||
"lastRecalledAt": "2026-05-09T02:03:53.176Z",
|
||||
"lastRecalledAt": "2026-05-11T02:51:47.112Z",
|
||||
"queryHashes": [
|
||||
"390d35f8d143",
|
||||
"fd4c9b7de37b"
|
||||
"fd4c9b7de37b",
|
||||
"be437071312f",
|
||||
"0e27779653c1",
|
||||
"5c08c6f8788a"
|
||||
],
|
||||
"recallDays": [
|
||||
"2026-05-08",
|
||||
"2026-05-09"
|
||||
"2026-05-09",
|
||||
"2026-05-11"
|
||||
],
|
||||
"conceptTags": [
|
||||
"reading-pic-qa",
|
||||
@ -127,6 +135,100 @@
|
||||
"memory.md",
|
||||
"a/b/c/d四级"
|
||||
]
|
||||
},
|
||||
"memory:memory/2026-04-13.md:1:5": {
|
||||
"key": "memory:memory/2026-04-13.md:1:5",
|
||||
"path": "memory/2026-04-13.md",
|
||||
"startLine": 1,
|
||||
"endLine": 5,
|
||||
"source": "memory",
|
||||
"snippet": "## 2026-04-13 12:28 [童瑶需求] 读取飞书文档https://makee-interactive.feishu.cn/wiki/QkY5wkcZYindgzkv5O0cpApRnzh内L1S1_Unit 11【其他需求】中所有的图片，并根据【描述】列的ID重命名为\"ID.png\" [执行结果] 完成35张图片的提取和重命名，保存到unit11_final_images/目录下，包含L1-L5全级别教研图、选项图，全部符合命名规则。",
|
||||
"recallCount": 1,
|
||||
"dailyCount": 0,
|
||||
"groundedCount": 0,
|
||||
"totalScore": 1,
|
||||
"maxScore": 1,
|
||||
"firstRecalledAt": "2026-05-11T02:19:37.985Z",
|
||||
"lastRecalledAt": "2026-05-11T02:19:37.985Z",
|
||||
"queryHashes": [
|
||||
"6f88450e9f9b"
|
||||
],
|
||||
"recallDays": [
|
||||
"2026-05-11"
|
||||
],
|
||||
"conceptTags": [
|
||||
"id.png",
|
||||
"保存到unit11-final-images/目录下",
|
||||
"包含l1-l5全级别教研图",
|
||||
"需求",
|
||||
"https",
|
||||
"makee",
|
||||
"interactive.feishu.cn",
|
||||
"wiki"
|
||||
]
|
||||
},
|
||||
"memory:memory/2026-05-08.md:33:55": {
|
||||
"key": "memory:memory/2026-05-08.md:33:55",
|
||||
"path": "memory/2026-05-08.md",
|
||||
"startLine": 33,
|
||||
"endLine": 55,
|
||||
"source": "memory",
|
||||
"snippet": "**图片资源新规：** - 每个题组共享一张图（非每题独立配图） - 产出 JSON 同时输出图片描述 prompt（英文，卡通简线条风格） - prompt 写入 bitable `图片描述` 列，格式 `{\"first\": \"...\", \"second\": \"...\"}` **通用化写入流程：** - 单元挑战全题型适用：定位 bitable 表 → 创建/更新记录 → 写入 `题目集合 ID` + `jsonData` + `图片描述` - 各题型仅 jsonData 结构不同，写入流程统一 **重写文件：** - `business_production/单元挑战/skills/unit_challenge/questions/writing/common/writing_pic_qa/SKILL.md`（11节完整规范） - `business_production/单元挑战/skills/unit_challenge/questions/writing/writing_pic_qa/SKILL.md`（简化为快速入口） **bitable 更新：** 已将新 JSON（每题组1图2题）+ 图片描述写入 `recviZlAxxXlAb` ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 图片描述格式修正 - **时间：** 09:46 ~ 09:51 - **修正：** 用户给出中文样例格式，要求图片描述从英文 prompt 改为纯中文结构化列表 - **新格式：** 编号 `1.` / `2.` 自上而下，每段",
|
||||
"recallCount": 2,
|
||||
"dailyCount": 0,
|
||||
"groundedCount": 0,
|
||||
"totalScore": 2,
|
||||
"maxScore": 1,
|
||||
"firstRecalledAt": "2026-05-11T02:19:37.985Z",
|
||||
"lastRecalledAt": "2026-05-11T02:37:23.203Z",
|
||||
"queryHashes": [
|
||||
"6f88450e9f9b",
|
||||
"be437071312f"
|
||||
],
|
||||
"recallDays": [
|
||||
"2026-05-11"
|
||||
],
|
||||
"conceptTags": [
|
||||
"创建/更新记录",
|
||||
"图片",
|
||||
"资源",
|
||||
"共享",
|
||||
"一张",
|
||||
"每题",
|
||||
"独立",
|
||||
"同时"
|
||||
]
|
||||
},
|
||||
"memory:memory/2026-05-08.md:1:23": {
|
||||
"key": "memory:memory/2026-05-08.md:1:23",
|
||||
"path": "memory/2026-05-08.md",
|
||||
"startLine": 1,
|
||||
"endLine": 23,
|
||||
"source": "memory",
|
||||
"snippet": "### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — writing_pic_qa 样题生产 \"I am / I am going to / I am ready / Thank you for\" - **时间：** 09:26 ~ 09:34 - **需求：** 生产 writing_pic_qa A级样题，ID=000001，2题组各2小题 - **状态：** ✅ 已完成，已写入飞书多维表格 - **目标表格：** 单元挑战 → 写作-P3-看图回答题 (tblFc9TVl2PeM2tg)，record_id=recviZlAxxXlAb - **题目清单：** 题组1 (first): 1. I (2) a student. → am（女孩穿校服举手，考察be动词am） 2. I am (5) to school. → going（男孩背书包走向校门，考察going） 题组2 (second): 3. I am (5)! → ready（男孩穿泳衣戴泳镜，考察状态词ready） 4. Thank you (3) the book. → for（女孩接书微笑，考察介词for） - **核心修正（用户反馈）：** 1. 挖空必须考察知识点核心词，非附带信息（you → for） 2. 不能挖空题干已有信息（如姓名/国家名），只挖知识点词本身 3. 只能为1个单词挖空 4. question与questionDesc人称必须一致（统一改为 What does [角色] say? → 第一人称直接",
|
||||
"recallCount": 1,
|
||||
"dailyCount": 0,
|
||||
"groundedCount": 0,
|
||||
"totalScore": 1,
|
||||
"maxScore": 1,
|
||||
"firstRecalledAt": "2026-05-11T02:37:23.203Z",
|
||||
"lastRecalledAt": "2026-05-11T02:37:23.203Z",
|
||||
"queryHashes": [
|
||||
"be437071312f"
|
||||
],
|
||||
"recallDays": [
|
||||
"2026-05-11"
|
||||
],
|
||||
"conceptTags": [
|
||||
"writing-pic-qa",
|
||||
"写作-p3-看图回答题",
|
||||
"record-id",
|
||||
"如姓名/国家名",
|
||||
"彦江",
|
||||
"生产",
|
||||
"going",
|
||||
"ready"
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
109
memory/2026-05-11-0956.md
Normal file
109
memory/2026-05-11-0956.md
Normal file
@ -0,0 +1,109 @@
|
||||
# Session: 2026-05-11 09:56:30 GMT+8
|
||||
|
||||
- **Session Key**: agent:xiaoyan:feishu:direct:ou_5af74c1fb96042e33cc0f16b5ca02cf4
|
||||
- **Session ID**: 986e3170-1f81-48b5-a6b9-4154e280140d
|
||||
- **Source**: feishu
|
||||
|
||||
## Conversation Summary
|
||||
|
||||
user: 看图判断题，产出填入飞书多维表格
|
||||
|
||||
ID：121301
|
||||
L1 A级难度
|
||||
能力tag：图文判断 | 句图一致性
|
||||
题组1：
|
||||
home
|
||||
house
|
||||
sofa
|
||||
cupboard
|
||||
bedroom
|
||||
|
||||
题组2：
|
||||
zoo
|
||||
hippo
|
||||
bear
|
||||
jeans
|
||||
sock
|
||||
|
||||
ID：121401
|
||||
L1 A级难度
|
||||
能力tag：图文判断 | 句图一致性
|
||||
题组1：
|
||||
student
|
||||
school
|
||||
teacher
|
||||
crayon
|
||||
board
|
||||
|
||||
题组2：
|
||||
mat
|
||||
letter
|
||||
desk
|
||||
schoolbag
|
||||
handbag
|
||||
|
||||
ID：121501
|
||||
L1 A级难度
|
||||
能力tag：图文判断 | 句图一致性
|
||||
题组1：
|
||||
body
|
||||
head
|
||||
mouth
|
||||
ear
|
||||
friend
|
||||
|
||||
|
||||
题组2：
|
||||
camera
|
||||
boy
|
||||
girl
|
||||
skateboarding
|
||||
skateboard
|
||||
|
||||
|
||||
ID：121601
|
||||
L1 A级难度
|
||||
能力tag：图文判断 | 句图一致性
|
||||
题组1：
|
||||
summer
|
||||
autumn
|
||||
winter
|
||||
cold
|
||||
spring
|
||||
|
||||
|
||||
题组2：
|
||||
bus
|
||||
taxi
|
||||
trousers
|
||||
shorts
|
||||
snow
|
||||
assistant: 先确认身份和资源，再动手。
|
||||
assistant: 先读之前的同类任务记忆和校验词库。
|
||||
assistant: 找到了目标多维表格。现在获取表格结构和题型规范。
|
||||
assistant: 找到了！现在获取表格字段结构。
|
||||
assistant: 表格结构已确认。现在开始生产 4 套看图判断题并写入。
|
||||
assistant: 写入成功，现在回读验证。
|
||||
assistant: 问题在于 shell 脚本处理嵌套 JSON 时有转义问题。直接用 Python + curl 写入。
|
||||
assistant: 全部写入并验证通过。现在更新记忆并向用户汇报。
|
||||
assistant: 所有4套题目已完成并写入飞书多维表格。向刘彦江汇报：
|
||||
|
||||
---
|
||||
|
||||
## 📝 reading_pic_judge 看图判断题 — 4套产出完成
|
||||
|
||||
**目标表格：** 阅读-P6-看图判断题
|
||||
**难度：** L1 A级 | **能力标签：** 图文判断 + 句图一致性
|
||||
|
||||
| ID | 题组1 | 题组2 | 判断 | record_id |
|
||||
|---|---|---|---|---|
|
||||
| **121301** | home, house, sofa, cupboard, bedroom | zoo, hippo, bear, jeans, sock | **6Y/4N** | `recvj5nIAxF3XG` |
|
||||
| **121401** | student, school, teacher, crayon, board | mat, letter, desk, schoolbag, handbag | **6Y/4N** | `recvj5nJG33bBE` |
|
||||
| **121501** | body, head, mouth, ear, friend | camera, boy, girl, skateboarding, skateboard | **6Y/4N** | `recvj5nKxhm8X6` |
|
||||
| **121601** | summer, autumn, winter, cold, spring | bus, taxi, trousers, shorts, snow | **6Y/4N** | `recvj5nLUpubaU` |
|
||||
|
||||
每题配有独立图片描述（卡通简单线条，白色背景/简单场景），已全量写入+回读验证通过。
|
||||
|
||||
### ⚠️ 词汇校验提示
|
||||
|
||||
40个知识点中，仅 **8个** 在 L1 词库内（sofa / zoo / sock / student / school / teacher / mat / mouth），**32个** 不在词库。已按您直接提供的词汇产出，未禁用超纲词汇。需不需要后续调整？
|
||||
10
memory/2026-05-11-1129.md
Normal file
10
memory/2026-05-11-1129.md
Normal file
@ -0,0 +1,10 @@
|
||||
# Session: 2026-05-11 11:29:24 GMT+8
|
||||
|
||||
- **Session Key**: agent:xiaoyan:feishu:direct:ou_270924c22bf8d63cf356dbd37614055f
|
||||
- **Session ID**: e37475eb-584d-497c-bc3c-7fb5de189903
|
||||
- **Source**: feishu
|
||||
|
||||
## Conversation Summary
|
||||
|
||||
user: hi
|
||||
assistant: 你好，若松。有什么需要处理的？
|
||||
14
memory/2026-05-11-1131.md
Normal file
14
memory/2026-05-11-1131.md
Normal file
@ -0,0 +1,14 @@
|
||||
# Session: 2026-05-11 11:31:12 GMT+8
|
||||
|
||||
- **Session Key**: agent:xiaoyan:feishu:group:oc_5c9f0e631266b9ef6e05a95daa80fbda
|
||||
- **Session ID**: b1a2ee39-373d-4068-994f-57fc9205ec12
|
||||
- **Source**: feishu
|
||||
|
||||
## Conversation Summary
|
||||
|
||||
user: 你在吗
|
||||
assistant: 在的，若松。有什么需要处理的？
|
||||
user: 你在吗
|
||||
assistant: 在的，若松。有什么需要处理的？
|
||||
user: @小研 /reset
|
||||
assistant: 好的，已重置。有什么需要处理的随时说。
|
||||
88
memory/2026-05-11.md
Normal file
88
memory/2026-05-11.md
Normal file
@ -0,0 +1,88 @@
|
||||
|
||||
### 刘彦江 — reading_pic_judge 看图判断题批量生产（4套，17:28 ~ 17:35）
|
||||
- **需求：** 4套 reading_pic_judge，L1 A级，能力标签 图文匹配
|
||||
- **题型特点：** 每题独立配图（questionImage），first/second双题组包裹
|
||||
- **状态：** ✅ 已完成，4套全部入库+图片描述回填验证通过
|
||||
- **脚本：** `scripts/batch_reading_pic_judge.py`、`scripts/update_pic_judge_descriptions.py`
|
||||
|
||||
| ID | 题组1 | 题组2 | Y/N | 图片描述 |
|
||||
|----|-------|-------|-----|---------|
|
||||
| 121301 | home/house/sofa/cupboard/bedroom | zoo/hippo/bear/jeans/sock | 3Y2N | ✅ 596chars |
|
||||
| 121401 | student/school/teacher/crayon/board | mat/letter/desk/schoolbag/handbag | 3Y2N | ✅ 562chars |
|
||||
| 121501 | body/head/mouth/ear/friend | camera/boy/girl/skateboarding/skateboard | 3Y2N | ✅ 553chars |
|
||||
| 121601 | summer/autumn/winter/cold/spring | bus/taxi/trousers/shorts/snow | 3Y2N | ✅ 565chars |
|
||||
|
||||
- **L1 A级**：3-4词极简陈述句，使用单物品/场景图
|
||||
- record_ids: recvj5nIAxF3XG, recvj5nJG33bBE, recvj5nKxhm8X6, recvj5nLUpubaU
|
||||
|
||||
|
||||
### 刘彦江 — reading_pic_qa 看图回答题（2套: 010701/010801，18:00 ~ 18:10）
|
||||
- **需求：** 2套 reading_pic_qa，L2 A级，能力标签 图文判断｜句图一致性
|
||||
- 每套5+5道 Y/N 判断，3Y2N平衡，4-7词陈述句
|
||||
- **状态：** ✅ 已完成，2套全部入库 + 图片描述回填验证通过
|
||||
- **脚本：** `scripts/batch_reading_pic_qa_2.py`
|
||||
|
||||
| ID | 题组1 | 题组2 | record_id |
|
||||
|----|-------|-------|-----------|
|
||||
| 010701 | notebook/star/folder/diary/contact | friendly/crazy/brilliant/kind/afraid | recvjiQuGtsVp8 |
|
||||
| 010801 | uncle/aunt/grandma/neighbour/pet | expensive/entrance/upstairs/downstairs/toast | recvjiQvc8EsB8 |
|
||||
|
||||
- 表：阅读-P7-看图回答题（tblweY65jGBiwSdt）
|
||||
- 当前该表累计：11条记录（000001~010801，含reading_pic_judge类型 4 条及其他）
|
||||
|
||||
### 刘彦江 — 口语-P1-日常回答 ability 标签填充（18:15 ~ 18:25）
|
||||
- **需求：** 从能力标签名称图片中，选择与已生成题目契合的标签填入 jsonData
|
||||
- 表：口语-P1-日常回答（tblRGv7k4WH58Jgq），26条有效记录，185道题
|
||||
- **状态：** ✅ 全部完成
|
||||
- **脚本：** `scripts/update_speaking_qa_ability.py`
|
||||
- **标签映射（5个适用标签）：**
|
||||
- `基础信息表达｜个人信息问答` — 姓名/年龄/家庭/外貌类
|
||||
- `表达喜好与理由` — 偏好/观点/意愿类
|
||||
- `过去经历描述｜Past Activities` — 过去事件类
|
||||
- `互动应答｜问答交流` — 社交场景类
|
||||
- `信息交换｜双向问答` — 物品归属/需求类
|
||||
- 未使用标签（属看图/发音题型专用）：图片描述类(3个)、图片对比、故事讲述、发音与语调
|
||||
- **分类逻辑**：基于关键词匹配（what do you say → 互动应答; what did you/last → 过去经历; favorite/like/want → 喜好; name/age/from/family → 个人信息; whose/need → 信息交换）
|
||||
|
||||
### 刘彦江 — reading_matchInfo 阅读信息匹配题（4套: 010901/011001/011101/011201，18:55 ~ 19:15）
|
||||
- **需求：** 4套 reading_matchInfo，L2 A级，能力标签 标识与通知理解｜标识 & 通知
|
||||
- 每套 first=5q + second=5q，每题含 questionImage/question/options/answer/ability/explanation
|
||||
- **表：** 阅读-P1-信息匹配题（tblCgfYDnnqwLfgH）
|
||||
- **自动化问题：** 该表存在异步自动化，创建后会将 jsonData 改写为模板壳（减少题量+覆盖 ability）
|
||||
- **解决方案：** 两阶段延迟写入（先创建空记录→等35s让自动化完成→PUT jsonData），010901/011201 修复后验证通过
|
||||
|
||||
| ID | 题组1 | 题组2 | record_id |
|
||||
|----|-------|-------|-----------|
|
||||
| 010901 | north/east/south/west/exit（方向标识） | businessman/job/letter/call/guard（职场） | recvjiYAHtp05c |
|
||||
| 011001 | beat/dancer/drum/player/work（音乐体育） | aged/good-looking/mistake/weakness/be good at（人物描述） | recvjiXLdt5itq |
|
||||
| 011101 | dangerous/badly/worst/steal/run away（危险） | minute/close/kilometre/second/away（时间距离） | recvjiXLOOWMsq |
|
||||
| 011201 | summer/winter/Earth/holiday/term（季节） | examination/plus/minus/biology/study（学校） | recvjiYBd8Mejs |
|
||||
|
||||
- **脚本：** `scripts/batch_reading_matchInfo.py`
|
||||
- **关键教训：** reading_matchInfo 表同样需要延迟写策略，直接创建+jsonData会被自动化覆盖
|
||||
|
||||
### 刘彦江 — reading_matchInfo 图片描述+题目重写（19:20 ~ 19:30）
|
||||
- **反馈问题：**
|
||||
1. 图片应是**真实标识/通知**（非标签式），如零售楼层导览那种
|
||||
2. 图片上的文字**至少为一句话**，L2 A级难度，不能只有一个词
|
||||
- **处理：** 4 套 reading_matchInfo 全部重新设计（题目+图片描述），两阶段延迟写入
|
||||
- **新record_ids:** recvjj2Nuw9MJd / recvjj2NZz75zb / recvjj2Ov8Stks / recvjj2OX0Dmo5
|
||||
- **改进要点：**
|
||||
- 每张图改为真实通知/标识，如 "TRAINS to the NORTH. Go to Platform 3."
|
||||
- 图片文字至少 1 句完整陈述，含足够信息供阅读提取
|
||||
- 题目围绕通知/标识内容提问，考察学生从标识中抓取关键信息的能力
|
||||
|
||||
### 刘彦江 — reading_matchInfo 阅读信息匹配题（6套L2 B级: 021301-021801，19:30 ~ 19:45）
|
||||
- **需求：** 6套 reading_matchInfo，L2 B级，能力标签 标识与通知理解｜标识 & 通知
|
||||
- **B级规范：** 文本3-5词短句，图片为同类差异，简单对应；每张图是真实的标识/通知（非标签式）
|
||||
- **状态：** ✅ 全部完成（两阶段延迟写入策略，避免自动化覆盖）
|
||||
- **脚本：** `scripts/batch_reading_matchInfo.py`
|
||||
|
||||
| ID | 题组1 | 题组2 | record_id |
|
||||
|----|-------|-------|-----------|
|
||||
| 021301 | actor/beard/different/brave/neighbour（人物） | dinner/cooking/fire/album/diary（生活） | recvjjk7oAT1YN |
|
||||
| 021401 | plan/repair/newspaper/backpack/seat（日程） | garden/melon/water/plant/summer（自然） | recvjjk7TU4ZFs |
|
||||
| 021501 | visitor/welcome/invite/laugh/guest（社交） | mistake/instruction/reason/technology/brush（学习） | recvjjk8mju8ou |
|
||||
| 021601 | record/event/enter/return/sort（管理） | handbag/camera/gate/wheel/entrance（场所） | recvjjk8Q5ZMIu |
|
||||
| 021701 | driver/street/market/guidebook/shopping（出行） | machine/draw/basketball/bookcase/invention（活动） | recvjjk9m5zhMS |
|
||||
| 021801 | library/magazine/cartoon/test/carefully（学校） | battery/corner/theatre/climb/midday（场所时间） | recvjjk9OVmASC |
|
||||
889
output/单元挑战_审校规范_2026-05-11.md
Normal file
889
output/单元挑战_审校规范_2026-05-11.md
Normal file
@ -0,0 +1,889 @@
|
||||
# 单元挑战（Unit Challenge）生成规范与审校标准
|
||||
|
||||
> 最后更新：2026-05-11 | 基于 skills/unit_challenge 全部题型 SKILL.md 汇总整理
|
||||
|
||||
---
|
||||
|
||||
## 一、产品定位
|
||||
|
||||
Vala 是一款按照 KET 考试要求设计的英语学习产品。**单元挑战** 是 Unit 级别的综合评估环节，核心要求：
|
||||
|
||||
- **与考试题型一致性：** 在单元挑战上追求与 KET 考试真题样式一致
|
||||
- **以 Unit 为单位交付效果**，每个 Unit 包含 30个单词 + 20个句型 + 1个语法点 + 1个发音规则
|
||||
- **形式：** 模仿 KET 考试真题样式，时间目标 20 分钟（约 1/5 个 KET 考试）
|
||||
- **出题逻辑：** 根据回顾和总结中的错误情况，智能出题；每个题目绑定对应知识模块标签
|
||||
- **发音：** 单元挑战中不出题（发音模块在总结中完成）
|
||||
|
||||
---
|
||||
|
||||
## 二、难度等级体系
|
||||
|
||||
**L1 和 L2 使用两套不同的难度对标体系**，不可混用：
|
||||
|
||||
### L1 难度等级（对标 Starters/Movers）
|
||||
|
||||
| 难度等级 | 剑桥对标 | 通用说明 |
|
||||
|---------|---------|---------|
|
||||
| A级 | Starters 1-2 | 基础入门，简单直接，强视觉特征，低干扰 |
|
||||
| B级 | Starters 3 | 进阶入门，简单复合，细节特征，中干扰 |
|
||||
| C级 | Movers 1 | 初级提升，需要推理整合，高干扰 |
|
||||
| D级 | Movers 2-3 / Flyers 1 | 中级能力，隐含推断，极高干扰 |
|
||||
|
||||
### L2 难度等级（对标 Flyers/KET，每 2 个阶段为 1 个难度等级）
|
||||
|
||||
L2 共 48 个 Unit，分 8 个阶段，每 2 个阶段合并为 1 个难度等级（A/B/C/D）：
|
||||
|
||||
| 难度等级 | 阶段 | Unit 范围 | 对标说明 |
|
||||
|---------|------|----------|---------|
|
||||
| **A级** | 阶段1-2 | U1-U12 | Flyers 入门 → Flyers 基础 |
|
||||
| **B级** | 阶段3-4 | U13-U24 | Flyers 达标 → KET 入门 |
|
||||
| **C级** | 阶段5-6 | U25-U36 | KET 基础 → KET 强化 |
|
||||
| **D级** | 阶段7-8 | U37-U48 | KET 高位 → KET 达标 |
|
||||
|
||||
**8 个阶段明细：**
|
||||
|
||||
| 阶段 | Unit 范围 | 说明 |
|
||||
|------|----------|------|
|
||||
| 1 | U1-U6 | Flyers 入门 |
|
||||
| 2 | U7-U12 | Flyers 基础 |
|
||||
| 3 | U13-U18 | Flyers 达标 |
|
||||
| 4 | U19-U24 | KET 入门 |
|
||||
| 5 | U25-U30 | KET 基础 |
|
||||
| 6 | U31-U36 | KET 强化 |
|
||||
| 7 | U37-U42 | KET 高位 |
|
||||
| 8 | U43-U48 | KET 达标 |
|
||||
|
||||
---
|
||||
|
||||
## 三、阶段归属总表
|
||||
|
||||
### 听力类
|
||||
|
||||
| 题型 | SKILL 名称 | 剑桥对应 | 阶段归属 |
|
||||
|------|-----------|---------|---------|
|
||||
| 听力拖拽题 | listening-drag | 听力 Part1 图片连线/人物匹配 | **L1 专属** |
|
||||
| 听力选图题 | listening_picture_selection | 听力 Part6 听力选图 | **L1 专属** |
|
||||
| 听力图片选择题 | listening-choicePic | — | **L2 专属** |
|
||||
| 听力表格填空题 | listening_form_fill | 听力 Part2 表格填空 | **L2 专属** |
|
||||
| 听力长对话选择题 | listening_long_conversation | 听力 Part3 长对话选择 | **L2 专属** |
|
||||
| 听力短对话选择题 | listening_short_conversation | 听力 Part4 短对话选择 | **L2 专属** |
|
||||
| 听力信息匹配题 | listening_info_match | — | **L2 专属** |
|
||||
|
||||
### 阅读类
|
||||
|
||||
| 题型 | SKILL 名称 | 剑桥对应 | 阶段归属 |
|
||||
|------|-----------|---------|---------|
|
||||
| 阅读看图回答题 | reading_pic_qa | — | **L1&L2 共用**（通过难度参数区分） |
|
||||
| 阅读看图判断题 | reading_pic_judge | — | **L1&L2 共用**（通过难度参数区分） |
|
||||
| 阅读信息匹配题 | reading_info_match | 阅读 Part1 信息匹配 | **L2 专属** |
|
||||
| 阅读段落匹配题 | reading_paragraph_match | 阅读 Part2 段落匹配 | **L2 专属** |
|
||||
| 阅读长文选择题 | reading_long_passage | 阅读 Part3 长文选择 | **L2 专属** |
|
||||
| 阅读完形填空题 | reading_cloze | 阅读 Part4 完形填空 | **L2 专属** |
|
||||
| 阅读开放填空题 | reading_open_fill | 阅读 Part5 开放填空 | **L2 专属** |
|
||||
|
||||
### 写作类
|
||||
|
||||
| 题型 | SKILL 名称 | 剑桥对应 | 阶段归属 |
|
||||
|------|-----------|---------|---------|
|
||||
| 写作看图回答题 | writing_pic_qa | 写作 Part3 看图回答 | **L1&L2 共用**（通过难度参数区分） |
|
||||
| 写作邮件回复题 | writing_email_reply | 写作 Part1 邮件回复 | **L2 专属** |
|
||||
| 写作看图写作题 | writing_picture_writing | — | **L2 专属** |
|
||||
|
||||
### 口语类
|
||||
|
||||
| 题型 | SKILL 名称 | 剑桥对应 | 阶段归属 |
|
||||
|------|-----------|---------|---------|
|
||||
| 口语看图回答题 | speaking_pic_qa | 口语 Part2 看图问答 | **L1 专属** |
|
||||
| 口语看图识物题 | speaking_pic_recognize | — | **L1 专属** |
|
||||
| 口语日常回答题 | speaking_daily_qa / speaking_qa | 口语 Part1 日常回答 | **L1&L2 共用**（通过难度参数区分） |
|
||||
| 口语话题讨论题 | speaking_topic_discussion | 口语 Part2 话题讨论 | **L2 专属** |
|
||||
|
||||
---
|
||||
|
||||
## 四、全局通用规则
|
||||
|
||||
### 4.1 词汇管控（强制执行）
|
||||
|
||||
- **L1 级别题目：** 仅限使用 L1 词库（980词），路径：`business_knowledge/L1_word_list.json`
|
||||
- **L2 级别题目：** 可使用 L1 + L2 词库（1470词），路径：`business_knowledge/L2_word_list.json`
|
||||
- **超纲拦截：** 任何不在对应词库内的词汇禁止出现，基础功能词（代词/be动词/介词）暂豁免
|
||||
- **句型管控：** L1 题目句型必须在 L1 句型库（490个）范围内；L2 题目句型在 L2 句型库（380个）范围内
|
||||
|
||||
### 4.2 知识点去重规则
|
||||
|
||||
- 同一题包内同一知识点最多出现 2 次
|
||||
- 同一题包内不得存在语义高度重复的题目
|
||||
|
||||
### 4.3 逐题解析要求
|
||||
|
||||
所有题目必须附带标准化解析，结构固定：**能力点说明 + 做题技巧 + 正向鼓励**，80-100字，中文为主，核心关键词可标注英文。
|
||||
|
||||
### 4.4 能力标签规则
|
||||
|
||||
每道题必须绑定能力标签，格式：
|
||||
- 1级标签：题型通用大标签（如「阅读理解」「听力理解」「口语表达」「书面表达」「图文匹配」）
|
||||
- 2级标签：根据考察点动态匹配（如「细节定位」「词汇运用」「信息提取」等）
|
||||
- 口语/写作题型需绑定语言输出标签（如「简短作答」「一词答案」「信息回复」「格式应用」）
|
||||
|
||||
### 4.5 价值观导向
|
||||
|
||||
- 避免使用负面词汇评价自己或他人
|
||||
- 优先使用正向引导表述
|
||||
- 内容贴近学生生活，情节积极正向
|
||||
|
||||
---
|
||||
|
||||
## 五、各题型的生成规范与审校要点
|
||||
|
||||
---
|
||||
|
||||
### 5.1 听力拖拽题（listening-drag）★ L1 专属
|
||||
|
||||
**剑桥对应：** Starters 听力 Part1 图片连线/人物匹配
|
||||
|
||||
**核心能力：** 基础语境理解（场景/物品/动作识别）、多模态信息匹配、注意力分配
|
||||
|
||||
**题型结构：**
|
||||
- 1张场景大图（含5个角色），5段听力对话
|
||||
- 学生听对话后，将人名拖拽到对应角色
|
||||
|
||||
**题目结构（5小题）：**
|
||||
- Q1：显性事实理解（关键词识别）
|
||||
- Q2：显性事实理解（关键词识别）
|
||||
- Q3：多信息整合
|
||||
- Q4：干扰抑制 / 语用推断（否定与纠错） ← **Q4 强制要求：必须包含否定/纠错逻辑（如 No, sorry / I mean 等表述）**
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | 阶段 | 特征 |
|
||||
|------|------|------|
|
||||
| A级 | L1 1-2阶段 | 强视觉特征，听力为3-5词简单句，低干扰 |
|
||||
| B级 | L1 3-4阶段 | 细节特征，听力为5-8词复合句，中干扰 |
|
||||
| C级 | L1 5-6阶段 | 状态动作，听力为8-10词描述性语言，高干扰 |
|
||||
| D级 | L2 1-2阶段 | 情境推断，听力为10-12词隐含逻辑，极高干扰 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] Q4 是否包含「No, sorry/I mean」等否定/纠错表述
|
||||
- [ ] 听力对话是否自然日常（不用统一祈使句，用陈述句/疑问句等多种形式）
|
||||
- [ ] 图片描述中人物特征是否清晰可辨
|
||||
- [ ] 能力标签：Q1/Q2=显性事实理解（关键词识别），Q3=多信息整合，Q4=干扰抑制/语用推断
|
||||
|
||||
**输出关键字段：** 听力文本、图片描述、人物顺序、选项排序（打乱）、答案（4个索引）、能力项
|
||||
|
||||
---
|
||||
|
||||
### 5.2 听力选图题（listening_picture_selection）★ L1 专属
|
||||
|
||||
**剑桥对应：** Starters 听力 Part6 听力选图
|
||||
|
||||
**核心能力：** 图片信息识别（听力信息匹配）、快速反应
|
||||
|
||||
**题型结构：**
|
||||
- 5-6个听力单句/短对话
|
||||
- 每小题对应一组3张图片，选出与听力内容匹配的图片
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | 阶段 | 特征 |
|
||||
|------|------|------|
|
||||
| A级 | L1 1-2阶段 | 图片3张类别完全不同，听力为3-5词简单句 |
|
||||
| B级 | L1 3-4阶段 | 图片同类物品不同属性（颜色/大小），听力为5-8词 |
|
||||
| C级 | L1 5-6阶段 | 同一场景不同动作，听力为8-10词 |
|
||||
| D级 | L2 1-2阶段 | 同一场景不同逻辑，听力为10-12词 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 图片3张，差异度匹配对应难度（A级差异极大，D级需甄别细节）
|
||||
- [ ] 听力句子长度符合难度要求
|
||||
- [ ] 答案与听力内容严格匹配
|
||||
|
||||
---
|
||||
|
||||
### 5.3 听力短对话选择题（listening_short_conversation）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 听力 Part4 短对话选择
|
||||
|
||||
**核心能力：** 场景理解（快速信息抓取+反应）
|
||||
|
||||
**题型结构：**
|
||||
- 4-5段1-2轮短对话（A/B角色），每段对应1道选择题（3个选项）
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 对话轮次 | 考察特征 |
|
||||
|------|----------|---------|---------|
|
||||
| A级 | U1-U12 | 1轮 | Flyers入门~基础，直接问物品/场景，答案明确 |
|
||||
| B级 | U13-U24 | 1-2轮 | Flyers达标~KET入门，问属性/动作，同类选项差异 |
|
||||
| C级 | U25-U36 | 2轮 | KET基础~强化，问意图/结果，需要简单推理 |
|
||||
| D级 | U37-U48 | 2轮 | KET高位~达标，问隐含观点/计划，需要推理 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 对话简短自然，符合日常交流场景
|
||||
- [ ] 干扰项为常见易混淆的场景内容（非无关内容）
|
||||
- [ ] 每段对话有明确语境和角色区分
|
||||
|
||||
---
|
||||
|
||||
### 5.4 听力长对话选择题（listening_long_conversation）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 听力 Part3 长对话选择
|
||||
|
||||
**核心能力：** 逻辑理解（信息整合+干扰抑制）
|
||||
|
||||
**题型结构：**
|
||||
- 1段3-6轮长对话（A/B角色），3-4道选择题（每道3个选项）
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 对话轮次 | 题目数 | 干扰特征 |
|
||||
|------|----------|---------|--------|---------|
|
||||
| A级 | U1-U12 | 3轮 | 3题 | Flyers入门~基础，答案直接对应，无干扰 |
|
||||
| B级 | U13-U24 | 4轮 | 3题 | Flyers达标~KET入门，需简单推理，1干扰 |
|
||||
| C级 | U25-U36 | 5轮 | 4题 | KET基础~强化，需逻辑整合，2干扰 |
|
||||
| D级 | U37-U48 | 6轮 | 4题 | KET高位~达标，隐含推断，3干扰 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 对话自然流畅，符合日常交流逻辑，角色明确
|
||||
- [ ] 干扰项设置合理（对话中出现的无关信息/部分正确信息/看似合理但错误的信息）
|
||||
- [ ] 对话长度/轮次/干扰项数量严格匹配难度等级
|
||||
|
||||
---
|
||||
|
||||
### 5.5 听力表格填空题（listening_form_fill）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 听力 Part2 表格填空
|
||||
|
||||
**核心能力：** 信息抓取（关键词识别+拼写准确性）
|
||||
|
||||
**题型结构：**
|
||||
- 1-2段短对话/独白 + 1份表格模板（含空缺位）
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 空缺数 | 答案类型 | 干扰 |
|
||||
|------|----------|--------|---------|------|
|
||||
| A级 | U1-U12 | 2-3空 | Flyers入门~基础，1-2字母/数字，直接念出 | 无 |
|
||||
| B级 | U13-U24 | 3-4空 | Flyers达标~KET入门，3-5字母单词 | 无 |
|
||||
| C级 | U25-U36 | 4-5空 | KET基础~强化，单词/短语 | 1个干扰 |
|
||||
| D级 | U37-U48 | 5-6空 | KET高位~达标，短语/短句 | 2-3个干扰 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 表格结构清晰，空缺位标注明确（用 `___`）
|
||||
- [ ] 表头信息完整
|
||||
- [ ] 答案在听力文本中有明确依据
|
||||
|
||||
---
|
||||
|
||||
### 5.6 听力图片选择题（listening-choicePic）★ L2 专属
|
||||
|
||||
**核心能力：** 图片信息提取与听力信息匹配
|
||||
|
||||
**备注：** 具体规格详见对应 SKILL.md，此处列核心框架。
|
||||
|
||||
---
|
||||
|
||||
### 5.7 听力信息匹配题（listening_info_match）★ L2 专属
|
||||
|
||||
**核心能力：** 多信息点匹配与筛选
|
||||
|
||||
**备注：** 具体规格详见对应 SKILL.md，此处列核心框架。
|
||||
|
||||
---
|
||||
|
||||
### 5.8 阅读看图回答题（reading_pic_qa）★ L1&L2 共用
|
||||
|
||||
**核心能力：** 图文匹配（阅读理解+图片信息提取）
|
||||
|
||||
**题型结构：**
|
||||
- 1张场景大图（textImage），N道 Yes/No 判断题（3-6题）
|
||||
- 所有小题共享同一张大图
|
||||
|
||||
**JSON 结构关键字段：**
|
||||
```json
|
||||
{
|
||||
"category": "reading",
|
||||
"type": "reading_pic_qa",
|
||||
"questionSetID": "阶段-U编号-自增",
|
||||
"textTitle": "Look and read. Put a tick (Yes) or a cross (No) in the box.",
|
||||
"textImage": "{ID}-00.png",
|
||||
"questionSet": [
|
||||
{
|
||||
"question": "描述性句子",
|
||||
"answerText": "Yes | No",
|
||||
"ability": ["图文匹配"],
|
||||
"explanation": "判断依据说明"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**难度细则：**
|
||||
|
||||
L1 维度（对标 Starters/Movers）：
|
||||
|
||||
| 等级 | 阶段 | 句子长度 | 图片特征 |
|
||||
|------|------|---------|---------|
|
||||
| A级 | L1 1-2阶段 | 3-5词简单陈述句 | 元素差异明显 |
|
||||
| B级 | L1 3-4阶段 | 5-8词简单陈述句 | 多人/多物但干扰少 |
|
||||
| C级 | L1 5-6阶段 | 8-12词复合陈述句 | 场景较复杂，多人物多动作 |
|
||||
| D级 | L2 1-2阶段 | 12-15词复合陈述句 | 密集场景，需仔细甄别 |
|
||||
|
||||
L2 维度（对标 Flyers/KET）：
|
||||
|
||||
| 等级 | Unit 范围 | 句子长度 | 图片特征 |
|
||||
|------|----------|---------|---------|
|
||||
| A级 | U1-U12 | 3-5词简单陈述句 | Flyers入门~基础，元素差异明显 |
|
||||
| B级 | U13-U24 | 5-8词简单陈述句 | Flyers达标~KET入门，多人/多物干扰少 |
|
||||
| C级 | U25-U36 | 8-12词复合陈述句 | KET基础~强化，场景复杂多人物动作 |
|
||||
| D级 | U37-U48 | 12-15词复合陈述句 | KET高位~达标，密集场景需甄别 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] Yes/No 题数量大致各半（偏差不超过60%）
|
||||
- [ ] No题的描述不应过于明显，需引导学生仔细甄别
|
||||
- [ ] 所有题干描述对象必须存在于图片场景中
|
||||
- [ ] textTitle 固定为 `Look and read. Put a tick (Yes) or a cross (No) in the box.`
|
||||
- [ ] A/B级单句不超过8个单词，C/D级不超过15个单词
|
||||
|
||||
---
|
||||
|
||||
### 5.9 阅读看图判断题（reading_pic_judge）★ L1&L2 共用
|
||||
|
||||
**核心能力：** 图文匹配（阅读理解+图片信息提取）
|
||||
|
||||
**题型结构：**
|
||||
- 每题独立配1张图（与 reading_pic_qa 不同，非共享大图）
|
||||
- N道 Yes/No 判断题（通常5题）
|
||||
|
||||
**JSON 结构关键字段：**
|
||||
```json
|
||||
{
|
||||
"category": "reading",
|
||||
"type": "reading_pic_judge",
|
||||
"questionSetID": "阶段-U编号-自增",
|
||||
"textTitle": "Look and read. Put a tick (Yes) or a cross (No) in the box.",
|
||||
"questionSet": [
|
||||
{
|
||||
"questionImage": "{ID}-{序号}.png",
|
||||
"question": "描述性句子",
|
||||
"answerText": "Yes | No",
|
||||
"ability": ["图文匹配"],
|
||||
"explanation": "判断依据说明"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**难度细则：**
|
||||
|
||||
L1 维度（对标 Starters/Movers）：
|
||||
|
||||
| 等级 | 阶段 | 句子长度 | 图片特征 |
|
||||
|------|------|---------|---------|
|
||||
| A级 | L1 1-2阶段 | 1-3词极简陈述句 | 单一物品，判断直接 |
|
||||
| B级 | L1 3-4阶段 | 4-6词简单陈述句 | 单一物品+简单背景，需辨识颜色/数量 |
|
||||
| C级 | L1 5-6阶段 | 6-10词复合陈述句 | 包含物品属性/动作/方位等多维信息 |
|
||||
| D级 | L2 1-2阶段 | 10-15词复合描述句 | 复杂场景缩略图，需甄别细节差异 |
|
||||
|
||||
L2 维度（对标 Flyers/KET）：
|
||||
|
||||
| 等级 | Unit 范围 | 句子长度 | 图片特征 |
|
||||
|------|----------|---------|---------|
|
||||
| A级 | U1-U12 | 1-3词极简陈述句 | Flyers入门~基础，单物品直接判断 |
|
||||
| B级 | U13-U24 | 4-6词简单陈述句 | Flyers达标~KET入门，辨识颜色/数量 |
|
||||
| C级 | U25-U36 | 6-10词复合陈述句 | KET基础~强化，属性/动作/方位多维 |
|
||||
| D级 | U37-U48 | 10-15词复合描述句 | KET高位~达标，复杂场景甄别细节 |
|
||||
|
||||
**与 reading_pic_qa 的区别：**
|
||||
|
||||
| 维度 | reading_pic_qa | reading_pic_judge |
|
||||
|------|----------------|-------------------|
|
||||
| 配图方式 | 1张大图共享 | 每题独立配图 |
|
||||
| 考察点 | 大图中定位信息并判断 | 单图直接匹配判断 |
|
||||
| 图片规模 | 复杂场景图 | 简单单物品/单场景图 |
|
||||
| L1适配 | 适合L1中期起步 | 适合L1早期入门 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 每道题独立配图，命名格式 `{ID}-{序号}.png`（序号从00开始连续递增）
|
||||
- [ ] Yes/No 题数量大致各半（偏差不超过60%）
|
||||
- [ ] No题的描述指代物品应与图片内容不同
|
||||
- [ ] 句子长度匹配难度等级
|
||||
|
||||
---
|
||||
|
||||
### 5.10 阅读信息匹配题（reading_info_match）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 阅读 Part1 信息匹配
|
||||
|
||||
**核心能力：** 信息抓取（快速阅读+图文匹配）
|
||||
|
||||
**题型结构：**
|
||||
- 5-6个简短文本（标识/告示/短句）+ 对应匹配项（图片/标题）
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 文本长度 | 匹配特征 |
|
||||
|------|----------|---------|---------|
|
||||
| A级 | U1-U12 | 1-2个单词 | Flyers入门~基础，直接对应图片内容 |
|
||||
| B级 | U13-U24 | 3-5词短句 | Flyers达标~KET入门，对应图片属性 |
|
||||
| C级 | U25-U36 | 5-8词短句 | KET基础~强化，提取关键词匹配 |
|
||||
| D级 | U37-U48 | 8-10词短句 | KET高位~达标，含干扰信息需筛选 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 干扰项为常见易混淆内容，避免过于明显的错误
|
||||
- [ ] 文本简洁清晰，符合对应难度词汇要求
|
||||
- [ ] 匹配关系有明确对应依据
|
||||
|
||||
---
|
||||
|
||||
### 5.11 阅读段落匹配题（reading_paragraph_match）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 阅读 Part2 段落匹配
|
||||
|
||||
**核心能力：** 主旨理解（信息归纳+快速阅读）
|
||||
|
||||
**题型结构：**
|
||||
- 4-5个简短段落 + 对应标题选项
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 段落长度 | 干扰项数 | 特征 |
|
||||
|------|----------|---------|---------|------|
|
||||
| A级 | U1-U12 | 3-4句话 | 无 | Flyers入门~基础，主旨直接明确 |
|
||||
| B级 | U13-U24 | 4-5句话 | 1个 | Flyers达标~KET入门，需简单归纳 |
|
||||
| C级 | U25-U36 | 5-6句话 | 2个 | KET基础~强化，需整合信息 |
|
||||
| D级 | U37-U48 | 6-7句话 | 3个 | KET高位~达标，需隐含推断 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 标题为段落主旨概括，非细节复述
|
||||
- [ ] 干扰项为段落中出现的细节信息（非完全无关内容）
|
||||
- [ ] 段落内容贴近学生生活
|
||||
|
||||
---
|
||||
|
||||
### 5.12 阅读长文选择题（reading_long_passage）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 阅读 Part3 长文选择
|
||||
|
||||
**核心能力：** 篇章理解（细节定位+推理判断）
|
||||
|
||||
**题型结构：**
|
||||
- 1篇短文 + 3-4道选择题（每道3个选项）
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 短文长度 | 题目数 | 考察特征 |
|
||||
|------|----------|---------|--------|---------|
|
||||
| A级 | U1-U12 | 100词左右 | 3题 | Flyers入门~基础，答案直接出现在原文 |
|
||||
| B级 | U13-U24 | 120-150词 | 3题 | Flyers达标~KET入门，需简单定位 |
|
||||
| C级 | U25-U36 | 150-180词 | 4题 | KET基础~强化，需简单推理 |
|
||||
| D级 | U37-U48 | 180-200词 | 4题 | KET高位~达标，需逻辑推断 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 短文内容贴近学生生活，情节积极正向
|
||||
- [ ] 干扰项为原文出现的无关信息、部分正确信息、看似合理的错误信息
|
||||
- [ ] 短文长度和问题复杂度匹配难度等级
|
||||
|
||||
---
|
||||
|
||||
### 5.13 阅读完形填空题（reading_cloze）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 阅读 Part4 完形填空
|
||||
|
||||
**核心能力：** 词汇运用（语法判断+上下文逻辑理解）
|
||||
|
||||
**题型结构：**
|
||||
- 1篇带空缺的短文 + 每个空缺3个选项
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 短文长度 | 空缺数 | 考察特征 |
|
||||
|------|----------|---------|--------|---------|
|
||||
| A级 | U1-U12 | 80词左右 | 3个空 | Flyers入门~基础，实词，上下文提示明显 |
|
||||
| B级 | U13-U24 | 100词左右 | 4个空 | Flyers达标~KET入门，实词+介词/动词 |
|
||||
| C级 | U25-U36 | 120词左右 | 5个空 | KET基础~强化，需前后句逻辑判断 |
|
||||
| D级 | U37-U48 | 150词左右 | 5个空 | KET高位~达标，需全文主旨推断 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 短文内容连贯，情节完整
|
||||
- [ ] 干扰项为常见易混淆词汇/语法形式错误的选项/不符合上下文逻辑的选项
|
||||
- [ ] 空缺单词需符合句子意思和语法
|
||||
|
||||
---
|
||||
|
||||
### 5.14 阅读开放填空题（reading_open_fill）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 阅读 Part5 开放填空
|
||||
|
||||
**核心能力：** 信息提取（词汇拼写+语法正确性）
|
||||
|
||||
**题型结构：**
|
||||
- 1篇阅读材料（短文/通知/表格）+ 3-5个填空问题，无选项提示
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 空缺数 | 答案特征 |
|
||||
|------|----------|--------|---------|
|
||||
| A级 | U1-U12 | 3个 | Flyers入门~基础，1-4字母简单名词，原文直接给出 |
|
||||
| B级 | U13-U24 | 4个 | Flyers达标~KET入门，名词/形容词，需简单变形 |
|
||||
| C级 | U25-U36 | 5个 | KET基础~强化，动词/短语，需提取多信息点后变形 |
|
||||
| D级 | U37-U48 | 5个 | KET高位~达标，需归纳总结，非原文原词 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 评分标准明确：拼写错误扣分规则、大小写/单复数处理规则
|
||||
- [ ] 答案在原文中有明确对应依据
|
||||
- [ ] 阅读材料信息点清晰
|
||||
|
||||
---
|
||||
|
||||
### 5.15 写作看图回答题（writing_pic_qa）★ L1&L2 共用
|
||||
|
||||
**这是最详细的题型规范，有完整的样板和规则沉淀。**
|
||||
|
||||
**核心能力：** 图文匹配（图片信息提取+书写表达）
|
||||
|
||||
**题型结构：**
|
||||
- 2个题组（first/second），每个题组 1张共享图 + 2-3小题（L2 U1-U6阶段1为2小题）
|
||||
- 学生看图，根据 questionDesc（含挖空标记）写出答案
|
||||
|
||||
**JSON 结构（bitable 写入格式）：**
|
||||
```json
|
||||
{
|
||||
"first": {
|
||||
"category": "writing",
|
||||
"type": "writing_pic_qa",
|
||||
"questionSetID": "000001",
|
||||
"textDesc": "Look and write.",
|
||||
"questionSet": [
|
||||
{
|
||||
"questionImage": "000001-00.png",
|
||||
"questionList": [
|
||||
{
|
||||
"question": "问题（What does the girl say about herself?）",
|
||||
"questionDesc": "完整句子骨架，含挖空标记如 I (2) a student.",
|
||||
"answerText": "答案（1个单词）",
|
||||
"ability": ["简短作答", "一词答案"],
|
||||
"explanation": "图片内容+考点+字母数说明"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
"second": { "... 同上结构 ..." }
|
||||
}
|
||||
```
|
||||
|
||||
**🔴 核心原则（强制执行，来自彦江明确反馈）：**
|
||||
|
||||
1. **挖空 = 考察知识点本身。** 挖空必须是句型结构中的核心知识词（be动词、介词、状态词等），不能是题干已给出的附带信息。
|
||||
|
||||
| ❌ 错误 | ✅ 正确 | 原因 |
|
||||
|--------|--------|------|
|
||||
| `Thank you (3) the book.` → you | `Thank you (3) the book.` → **for** | for 是介词知识点 |
|
||||
| `I (2) Anna.` → I | `I (2) Anna.` → **am** | am 是 be动词知识点 |
|
||||
| `I am from (5).` → China | `I am (4) China.` → **from** | from 是介词知识点 |
|
||||
|
||||
2. **只能为 1 个单词挖空。** 禁止多词填空。
|
||||
|
||||
3. **考察点多样化。** 同一句型结构应覆盖多种搭配用法：
|
||||
- `Thank you for...` → for + 名词 / for + 动名词
|
||||
- `I am...` → be + 状态词 / be + 身份
|
||||
- `I am going to...` → 动名词 going
|
||||
|
||||
4. **题干多样化。** question 不能全部相同，应随语境微调：
|
||||
- ❌ 全部 `What does the girl say?`
|
||||
- ✅ `What does the girl say about herself?` / `Where does the girl say she is going?` / `What does the girl say to her friend?`
|
||||
|
||||
5. **question 与 questionDesc 人称必须一致。** question 问角色说了什么 → questionDesc 用第一人称直接引语。
|
||||
|
||||
6. **问句型知识点挖空方向。** 当知识点是问句时，挖空在问句上，答句完整给出。
|
||||
- ✅ `"What (6) we do? We should go home now."` → 挖空 should
|
||||
- ❌ `"What should we do? We should (2) home."` → 挖空了答句的 go
|
||||
|
||||
**图片资源规则：**
|
||||
- 每个题组 = 1张共享图（非每题独立配图）
|
||||
- 命名：`{questionSetID}-{序号}.png`，序号跨全题组连续递增（00起始）
|
||||
- 图片描述为纯中文文本（非 JSON），格式：
|
||||
|
||||
```
|
||||
1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：{场景名称}
|
||||
{角色特征} - {动作描述} ；
|
||||
{角色特征} - {动作描述} 。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：{场景名称}
|
||||
...
|
||||
```
|
||||
|
||||
**阶段变化原则：**
|
||||
|
||||
| 维度 | L2 U1-U6（阶段1，A级） | 后续阶段 |
|
||||
|------|----------------------|---------|
|
||||
| 挖空单位 | 1 个单词 | 短语 / 完整句子 |
|
||||
| 题组小题数 | 2 小题 / 题组 | 4 小题 / 题组 |
|
||||
| 能力标签 | ["简短作答", "一词答案"] | （待补充） |
|
||||
|
||||
**历史 L1 规则（供参考）：**
|
||||
|
||||
| 等级 | 阶段 | 答案要求 |
|
||||
|------|------|---------|
|
||||
| A级 | L1 1-2阶段 | 1个核心词（功能词/名词），questionDesc提供完整句子骨架 |
|
||||
| B级 | L1 3-4阶段 | 1-2词短语 |
|
||||
| C级 | L1 5-6阶段 | 2-3词动作描述 |
|
||||
| D级 | L2 1-2阶段 | 完整简单句或3-5词短语 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 挖空词是否为知识点核心词？（不是题干已知信息）
|
||||
- [ ] 每空仅1个单词？
|
||||
- [ ] questionDesc 中数字标记 = 答案字母数？
|
||||
- [ ] question 与 questionDesc 人称是否一致？
|
||||
- [ ] 同题包内 question 是否多样化？
|
||||
- [ ] 同句型是否覆盖多种搭配？
|
||||
- [ ] 图片描述格式是否正确？（中文、编号、风格/场景/角色）
|
||||
- [ ] questionImage 序号从 00 开始连续递增？
|
||||
- [ ] L2 U1-U6（阶段1，A级）ability 固定为 `["简短作答", "一词答案"]`？
|
||||
|
||||
**完整样题（questionSetID = 000001）：**
|
||||
|
||||
题组1（first）— 校门口场景：
|
||||
1. What does the girl say about herself? → `I (2) a student.` → am（女孩穿校服举手，考察be动词am）
|
||||
2. Where does the girl say she is going? → `I am (5) to school.` → going（男孩背书包走向校门，考察going）
|
||||
|
||||
题组2（second）— 生日派对场景：
|
||||
3. What does the boy say at the party? → `I am (5)!` → ready（男孩穿泳衣戴泳镜，考察状态词ready）
|
||||
4. What does the girl say to her friend? → `Thank you (3) the book.` → for（女孩接书微笑，考察介词for）
|
||||
|
||||
---
|
||||
|
||||
### 5.16 写作邮件回复题（writing_email_reply）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 写作 Part1 邮件回复
|
||||
|
||||
**核心能力：** 书面表达（格式规范+信息提取）
|
||||
|
||||
**题型结构：**
|
||||
- 1封收到的邮件 + 回复要求 + 参考范文 + 评分标准
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 词数要求 | 考察内容 |
|
||||
|------|----------|---------|---------|
|
||||
| A级 | U1-U12 | 20-30词 | Flyers入门~基础，回答2个简单问题，格式简单 |
|
||||
| B级 | U13-U24 | 30-40词 | Flyers达标~KET入门，3个问题+问候结尾 |
|
||||
| C级 | U25-U36 | 40-50词 | KET基础~强化，3问题+1附加要求，格式完整 |
|
||||
| D级 | U37-U48 | 50-60词 | KET高位~达标，3问题+个人观点，语言连贯 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 邮件格式规范（问候、正文、结尾署名）
|
||||
- [ ] 参考范文符合字数要求，信息完整
|
||||
- [ ] 评分标准分三级（优秀/合格/不合格），判断依据明确
|
||||
|
||||
---
|
||||
|
||||
### 5.17 写作看图写作题（writing_picture_writing）★ L2 专属
|
||||
|
||||
**核心能力：** 独立书面表达
|
||||
|
||||
**备注：** 具体规格详见对应 SKILL.md。
|
||||
|
||||
---
|
||||
|
||||
### 5.18 口语看图回答题（speaking_pic_qa）★ L1 专属
|
||||
|
||||
**剑桥对应：** Starters 口语 Part2 看图问答
|
||||
|
||||
**核心能力：** 口语表达（图片信息提取+场景词汇运用）
|
||||
|
||||
**题型结构：**
|
||||
- 1张图片描述 + 1个引导问题 + 1-3个参考回答 + 三级评分标准
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | 阶段 | 图片/问题特征 | 答案要求 |
|
||||
|------|------|-------------|---------|
|
||||
| A级 | L1 1-2阶段 | 1个核心物品，无干扰，问"What's this?" | 1-2个核心名词，无语法要求 |
|
||||
| B级 | L1 3-4阶段 | 核心物品+1个属性，问属性 | 3-5词短语（名词+属性词） |
|
||||
| C级 | L1 5-6阶段 | 核心人物+1个动作，问动作 | 完整简单句（主谓宾），6-10词 |
|
||||
| D级 | L2 1-2阶段 | 完整场景（物品+人物+动作），问场景 | 2-3句连贯表达，15-20词 |
|
||||
|
||||
**题型示例（A级）：**
|
||||
```
|
||||
图片描述：白色背景下的红色苹果，无其他干扰元素
|
||||
引导问题：What's this?
|
||||
满分回答：Apple.
|
||||
合格回答：Red apple.
|
||||
```
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 引导问题复杂度匹配难度等级
|
||||
- [ ] 参考回答至少1个满分回答
|
||||
- [ ] 评分标准明确标注「优秀/合格/不合格」三个等级判断依据
|
||||
|
||||
---
|
||||
|
||||
### 5.19 口语日常回答题（speaking_daily_qa / speaking_qa）★ L1&L2 共用
|
||||
|
||||
**剑桥对应：** 口语 Part1 日常回答
|
||||
|
||||
**核心能力：** 口语表达（日常用语运用+快速反应）
|
||||
|
||||
**题型结构：**
|
||||
- 3-4个日常问题 + 每题满分/合格参考回答 + 评分标准
|
||||
|
||||
**难度细则（L1 维度，对标 Starters/Movers）：**
|
||||
|
||||
| 等级 | 阶段 | 问题类型 | 答案要求 |
|
||||
|------|------|---------|---------|
|
||||
| A级 | L1 1-2阶段 | 个人基本信息类（What's your name?） | 1-2个单词/短语 |
|
||||
| B级 | L1 3-4阶段 | 喜好/日常活动类（What color do you like?） | 1个简单句 |
|
||||
| C级 | L1 5-6阶段 | 习惯/能力类（What do you do every day?） | 2个简单句 |
|
||||
| D级 | L2 1-2阶段 | 经历/计划类（What did you do yesterday?） | 2-3个连贯句子 |
|
||||
|
||||
**难度细则（L2 维度，对标 Flyers/KET）：**
|
||||
|
||||
| 等级 | Unit 范围 | 问题类型 | 答案要求 |
|
||||
|------|----------|---------|---------|
|
||||
| A级 | U1-U12 | Flyers入门~基础，个人基本信息/喜好类 | 2个简单句 |
|
||||
| B级 | U13-U24 | Flyers达标~KET入门，喜好/日常活动类 | 2-3个连贯句 |
|
||||
| C级 | U25-U36 | KET基础~强化，习惯/能力类 | 3-4个连贯句 |
|
||||
| D级 | U37-U48 | KET高位~达标，经历/计划类 | 4-5个连贯句 |
|
||||
|
||||
**JSON 结构（speaking_qa）：**
|
||||
```json
|
||||
{
|
||||
"category": "speaking",
|
||||
"type": "speaking_qa",
|
||||
"asrPrompt": "ASR提示词列表（逗号分隔）",
|
||||
"questionSetID": "111101",
|
||||
"textDesc": "Answer these questions.",
|
||||
"questionSet": [
|
||||
{
|
||||
"content": "问题内容",
|
||||
"ability": ["能力标签数组"],
|
||||
"explanation": "回答问题时使用完整句子。"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 问题符合日常交流场景，贴近学生生活
|
||||
- [ ] 至少提供1个满分回答+1个合格回答
|
||||
- [ ] ASR 提示词覆盖问题中所有核心词汇
|
||||
- [ ] 评分标准分三级
|
||||
|
||||
---
|
||||
|
||||
### 5.20 口语话题讨论题（speaking_topic_discussion）★ L2 专属
|
||||
|
||||
**剑桥对应：** Movers 口语 Part2 话题讨论
|
||||
|
||||
**核心能力：** 口语表达（逻辑组织+观点阐述）
|
||||
|
||||
**题型结构：**
|
||||
- 1个话题 + 1-2个引导提示 + 参考回答 + 评分标准
|
||||
|
||||
**难度细则：**
|
||||
|
||||
| 等级 | Unit 范围 | 话题类型 | 要求 |
|
||||
|------|----------|---------|------|
|
||||
| A级 | U1-U12 | 具体物品/活动（Describe your favorite toy） | Flyers入门~基础，3-4句话，无复杂逻辑 |
|
||||
| B级 | U13-U24 | 喜好/习惯（Talk about your favorite food） | Flyers达标~KET入门，4-5句话，简单逻辑 |
|
||||
| C级 | U25-U36 | 观点/经历（Talk about your last birthday） | KET基础~强化，5-6句话，清晰逻辑层次 |
|
||||
| D级 | U37-U48 | 抽象感受/计划（Talk about your weekend plan） | KET高位~达标，6-8句话，逻辑连贯 |
|
||||
|
||||
**审校要点：**
|
||||
- [ ] 话题贴近学生生活，符合对应年龄段认知
|
||||
- [ ] 至少提供1个满分参考回答，结构清晰
|
||||
- [ ] 评分标准分三级
|
||||
|
||||
---
|
||||
|
||||
### 5.21 口语看图识物题（speaking_pic_recognize）★ L1 专属
|
||||
|
||||
**核心能力：** 图片辨识与口语输出
|
||||
|
||||
**备注：** 具体规格详见对应 SKILL.md。
|
||||
|
||||
---
|
||||
|
||||
## 六、飞书多维表格写入规范（通用流程）
|
||||
|
||||
### 6.1 目标表格
|
||||
|
||||
- App Token：`CMHSbUUjka3TrUsaxxEc297ongf`
|
||||
- 表格按题型分表（如 写作-P3-看图回答题、阅读-P1-看图回答题 等）
|
||||
- Bot 身份操作（App ID: `cli_a931175d41799cc7`）
|
||||
|
||||
### 6.2 通用写入字段
|
||||
|
||||
| bitable 列名 | 写入内容 | 格式 |
|
||||
|-------------|---------|------|
|
||||
| 题目集合 ID | questionSetID | 纯文本 |
|
||||
| jsonData | 完整 JSON | JSON 字符串 |
|
||||
| 图片描述 | 图片描述（如需配图） | 纯中文文本 |
|
||||
|
||||
### 6.3 写入流程图
|
||||
|
||||
```
|
||||
定位 bitable 表 → 创建/更新记录 → 写入三字段 → 回读验证
|
||||
```
|
||||
|
||||
### 6.4 注意事项
|
||||
- 嵌套 JSON 写入时避免 Shell 变量展开截断（用 Python subprocess 直接调用 curl）
|
||||
- 写入后必须回读验证 jsonData 内容完整性
|
||||
|
||||
---
|
||||
|
||||
## 七、全局审校检查清单
|
||||
|
||||
### 7.1 词汇与阶段匹配
|
||||
- [ ] 所有词汇在对应用别的词库（L1用L1词库，L2用L1+L2词库）
|
||||
- [ ] 句型在对应阶段句型库范围内
|
||||
- [ ] 题型阶段归属正确（L1专属题型不出现在L2，反之亦然）
|
||||
|
||||
### 7.2 难度匹配
|
||||
- [ ] 对话/短文长度符合等级要求
|
||||
- [ ] 选项/干扰项复杂度符合等级要求
|
||||
- [ ] 问题难度符合等级要求
|
||||
|
||||
### 7.3 格式合规
|
||||
- [ ] JSON 结构完整，必填字段齐全
|
||||
- [ ] 图片命名格式正确（`{questionSetID}-{序号}.png`）
|
||||
- [ ] 标准化解析包含（80-100字，中文为主）
|
||||
|
||||
### 7.4 逻辑合规
|
||||
- [ ] 答案有明确依据（听力文本/阅读原文/图片内容）
|
||||
- [ ] 干扰项合理，不出现明显错误选项
|
||||
- [ ] 同一题包内题目不重复（知识盲点不重复考察）
|
||||
|
||||
### 7.5 能力标签
|
||||
- [ ] 每道题绑定1级+2级能力标签
|
||||
- [ ] 能力标签与题型匹配
|
||||
- [ ] 口语/写作题型绑定语言输出标签
|
||||
|
||||
### 7.6 价值观
|
||||
- [ ] 无负面评价词汇
|
||||
- [ ] 情节积极正向
|
||||
- [ ] 内容贴近学生生活，符合年龄段认知
|
||||
|
||||
---
|
||||
|
||||
## 八、资源路径速查
|
||||
|
||||
| 资源 | 路径 |
|
||||
|------|------|
|
||||
| L1 词库（980词） | `business_knowledge/L1_word_list.json` |
|
||||
| L2 词库（1470词） | `business_knowledge/L2_word_list.json` |
|
||||
| L1 句型库（490个） | `business_knowledge/L1_pattern_list.json` |
|
||||
| L2 句型库（380个） | `business_knowledge/L2_pattern_list.json` |
|
||||
| 单元挑战 skills | `business_production/单元挑战/skills/unit_challenge/` |
|
||||
| 单元挑战记忆 | `business_production/单元挑战/memory/` |
|
||||
| 单元挑战 bitable | App Token: `CMHSbUUjka3TrUsaxxEc297ongf` |
|
||||
|
||||
---
|
||||
|
||||
*本文档依据全部题型 SKILL.md（共 18 个题型规范文件）及近期生产实践经验教训整理，可作为审校工作的一站式参照标准。*
|
||||
BIN
scripts/__pycache__/batch_reading_pic_qa.cpython-312.pyc
Normal file
BIN
scripts/__pycache__/batch_reading_pic_qa.cpython-312.pyc
Normal file
Binary file not shown.
113
scripts/batch_create_delayed.py
Normal file
113
scripts/batch_create_delayed.py
Normal file
@ -0,0 +1,113 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Create empty records, wait for automation, then update with real jsonData."""
|
||||
import json, requests, sys, time
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt"
|
||||
|
||||
sys.path.insert(0, '/root/.openclaw/workspace-xiaoyan')
|
||||
from scripts.batch_reading_pic_qa import ALL_QUESTIONS, build_json
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
def get_token():
|
||||
resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
return resp.json()["tenant_access_token"]
|
||||
|
||||
token = get_token()
|
||||
|
||||
# Step 1: Delete any existing corrupted records
|
||||
print("=== Step 1: Clean up ===")
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records?page_size=20",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
for item in resp.json()["data"]["items"]:
|
||||
fid = item["fields"].get("题目集合 ID", "")
|
||||
if fid in ALL_QUESTIONS:
|
||||
rid = item["record_id"]
|
||||
requests.delete(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
print(f" Deleted {fid}")
|
||||
|
||||
time.sleep(3)
|
||||
|
||||
# Step 2: Create ALL empty records first
|
||||
print("\n=== Step 2: Create empty records ===")
|
||||
record_ids = {}
|
||||
for qid in sorted(ALL_QUESTIONS.keys()):
|
||||
fields = {"题目集合 ID": qid, "dataStatus": "0"}
|
||||
resp = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": fields},
|
||||
)
|
||||
rid = resp.json()["data"]["record"]["record_id"]
|
||||
record_ids[qid] = rid
|
||||
print(f" {qid}: {rid}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# Step 3: Wait for automation to finish
|
||||
print("\n=== Step 3: Waiting 30s for automation... ===")
|
||||
for i in range(30, 0, -5):
|
||||
print(f" {i}s remaining...")
|
||||
time.sleep(5)
|
||||
|
||||
# Step 4: Update all with real jsonData
|
||||
print("\n=== Step 4: Update with real jsonData ===")
|
||||
token = get_token() # refresh token
|
||||
results = {}
|
||||
for qid in sorted(record_ids.keys()):
|
||||
rid = record_ids[qid]
|
||||
json_data = build_json(qid, ALL_QUESTIONS[qid])
|
||||
json_str = json.dumps(json_data, ensure_ascii=False)
|
||||
print(f" Updating {qid} ({len(json_str)} chars)...")
|
||||
|
||||
update_resp = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"jsonData": json_str}},
|
||||
)
|
||||
print(f" update code: {update_resp.json().get('code')}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# Step 5: Verify after delay
|
||||
print("\n=== Step 5: Wait 30s then verify ===")
|
||||
for i in range(30, 0, -5):
|
||||
print(f" {i}s remaining...")
|
||||
time.sleep(5)
|
||||
|
||||
token = get_token()
|
||||
print("\n=== Step 6: Final verification ===")
|
||||
all_ok = True
|
||||
for qid, rid in sorted(record_ids.items()):
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
jd = resp.json()["data"]["record"]["fields"].get("jsonData", "")
|
||||
try:
|
||||
j = json.loads(jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
if fq == 5 and sq == 5:
|
||||
q1 = j["first"]["questionSet"][0]["question"][:50]
|
||||
print(f" ✅ {qid}: {fq}q/{sq}q | Q1=\"{q1}\"")
|
||||
else:
|
||||
print(f" ❌ {qid}: {fq}q/{sq}q | jd={len(jd)}chars")
|
||||
print(f" jd preview: {jd[:200]}")
|
||||
all_ok = False
|
||||
except Exception as e:
|
||||
print(f" ❌ {qid}: {e}")
|
||||
all_ok = False
|
||||
|
||||
print(f"\n{'✅ ALL INTACT' if all_ok else '❌ SOME CORRUPTED'}")
|
||||
94
scripts/batch_create_safe.py
Normal file
94
scripts/batch_create_safe.py
Normal file
@ -0,0 +1,94 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Batch create reading_pic_qa records with delay and immediate verification."""
|
||||
import json, requests, sys, time
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt"
|
||||
|
||||
sys.path.insert(0, '/root/.openclaw/workspace-xiaoyan')
|
||||
from scripts.batch_reading_pic_qa import ALL_QUESTIONS, build_json
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
results = []
|
||||
for qid in sorted(ALL_QUESTIONS.keys()):
|
||||
print(f"\n{'='*50}")
|
||||
print(f"ID: {qid}")
|
||||
|
||||
json_data = build_json(qid, ALL_QUESTIONS[qid])
|
||||
json_str = json.dumps(json_data, ensure_ascii=False)
|
||||
print(f" jsonData: {len(json_str)} chars")
|
||||
|
||||
# Verify Y/N balance
|
||||
for grp in ('first', 'second'):
|
||||
qs = json_data[grp]['questionSet']
|
||||
yc = sum(1 for q in qs if q['answerText']=='Yes')
|
||||
nc = sum(1 for q in qs if q['answerText']=='No')
|
||||
print(f" {grp}: {yc}Y/{nc}N")
|
||||
|
||||
# Create
|
||||
fields = {
|
||||
"题目集合 ID": qid,
|
||||
"jsonData": json_str,
|
||||
"dataStatus": "0",
|
||||
}
|
||||
resp = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": fields},
|
||||
)
|
||||
result = resp.json()
|
||||
|
||||
if result.get("code") != 0:
|
||||
print(f" ❌ Create failed: {result.get('msg', result)}")
|
||||
results.append((qid, "FAIL"))
|
||||
continue
|
||||
|
||||
record_id = result["data"]["record"]["record_id"]
|
||||
print(f" record_id: {record_id}")
|
||||
|
||||
# Verify immediately
|
||||
time.sleep(0.5)
|
||||
resp2 = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
data2 = resp2.json()
|
||||
stored_jd = data2["data"]["record"]["fields"].get("jsonData", "")
|
||||
|
||||
if len(stored_jd) < 100:
|
||||
print(f" ❌ TRUNCATED ({len(stored_jd)} chars)! Deleting...")
|
||||
requests.delete(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
results.append((qid, "TRUNCATED"))
|
||||
continue
|
||||
|
||||
try:
|
||||
j = json.loads(stored_jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
print(f" ✅ Verified: first={fq}q, second={sq}q")
|
||||
results.append((qid, "OK", record_id))
|
||||
except Exception as e:
|
||||
print(f" ❌ Parse error: {e}")
|
||||
results.append((qid, "PARSE_ERROR"))
|
||||
|
||||
time.sleep(1.0)
|
||||
|
||||
print(f"\n{'='*50}")
|
||||
print("SUMMARY")
|
||||
print(f"{'='*50}")
|
||||
for r in results:
|
||||
print(f" {r}")
|
||||
115
scripts/batch_create_two_step.py
Normal file
115
scripts/batch_create_two_step.py
Normal file
@ -0,0 +1,115 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Create records first, then update jsonData separately."""
|
||||
import json, requests, sys, time
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt"
|
||||
|
||||
sys.path.insert(0, '/root/.openclaw/workspace-xiaoyan')
|
||||
from scripts.batch_reading_pic_qa import ALL_QUESTIONS, build_json
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
# First delete all corrupted records
|
||||
print("=== Cleaning corrupted records ===")
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records?page_size=20",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
for item in resp.json()["data"]["items"]:
|
||||
fid = item["fields"].get("题目集合 ID", "")
|
||||
if fid in ("000001", "010101", "010201", "010301", "010401", "010501", "010601"):
|
||||
rid = item["record_id"]
|
||||
del_resp = requests.delete(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
print(f" Deleted {fid} ({rid}): {del_resp.json().get('code')}")
|
||||
|
||||
time.sleep(2)
|
||||
|
||||
results = {}
|
||||
for qid in sorted(ALL_QUESTIONS.keys()):
|
||||
print(f"\n{'='*50}")
|
||||
print(f"ID: {qid}")
|
||||
|
||||
# Step 1: Create with minimal fields (no jsonData)
|
||||
fields = {
|
||||
"题目集合 ID": qid,
|
||||
"dataStatus": "0",
|
||||
}
|
||||
resp = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": fields},
|
||||
)
|
||||
result = resp.json()
|
||||
if result.get("code") != 0:
|
||||
print(f" ❌ Create failed: {result.get('msg')}")
|
||||
results[qid] = "FAIL_CREATE"
|
||||
continue
|
||||
|
||||
record_id = result["data"]["record"]["record_id"]
|
||||
print(f" Created: {record_id}")
|
||||
|
||||
# Step 2: Update with jsonData
|
||||
json_data = build_json(qid, ALL_QUESTIONS[qid])
|
||||
json_str = json.dumps(json_data, ensure_ascii=False)
|
||||
print(f" Updating jsonData ({len(json_str)} chars)...")
|
||||
|
||||
update_resp = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"jsonData": json_str}},
|
||||
)
|
||||
up_result = update_resp.json()
|
||||
print(f" Update: code={up_result.get('code')}")
|
||||
|
||||
if up_result.get("code") != 0:
|
||||
print(f" ❌ Update failed: {up_result.get('msg')}")
|
||||
results[qid] = "FAIL_UPDATE"
|
||||
continue
|
||||
|
||||
# Wait for any automation to process
|
||||
time.sleep(1.0)
|
||||
|
||||
# Step 3: Read back and verify
|
||||
resp3 = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
data3 = resp3.json()
|
||||
stored_jd = data3["data"]["record"]["fields"].get("jsonData", "")
|
||||
|
||||
try:
|
||||
j = json.loads(stored_jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
if fq == 5 and sq == 5:
|
||||
first_q = j["first"]["questionSet"][0]["question"][:50]
|
||||
print(f" ✅ VERIFIED: first={fq}q, second={sq}q, Q1='{first_q}'")
|
||||
results[qid] = ("OK", record_id)
|
||||
else:
|
||||
print(f" ⚠️ PARTIAL: first={fq}q, second={sq}q")
|
||||
results[qid] = ("PARTIAL", record_id)
|
||||
except Exception as e:
|
||||
print(f" ❌ CORRUPTED: {e} | jd_len={len(stored_jd)}")
|
||||
results[qid] = ("CORRUPTED", record_id)
|
||||
|
||||
time.sleep(1.0)
|
||||
|
||||
print(f"\n{'='*50}")
|
||||
print("FINAL SUMMARY")
|
||||
print(f"{'='*50}")
|
||||
for qid, val in sorted(results.items()):
|
||||
print(f" {qid}: {val}")
|
||||
509
scripts/batch_reading_matchInfo.py
Normal file
509
scripts/batch_reading_matchInfo.py
Normal file
@ -0,0 +1,509 @@
|
||||
#!/usr/bin/env python3
|
||||
"""reading_matchInfo 021301-021801 (6套), L2 B级 3-5词短句通知"""
|
||||
import json, requests, time
|
||||
|
||||
CRED = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
TOKEN_APP = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TBL = "tblCgfYDnnqwLfgH"
|
||||
AB = ["标识与通知理解｜标识 & 通知"]
|
||||
|
||||
with open(CRED) as f:
|
||||
cred = json.load(f)
|
||||
aid = cred["apps"][0]["appId"]
|
||||
asecret = cred["apps"][0]["appSecret"]
|
||||
|
||||
def get_token():
|
||||
r = requests.post("https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": aid, "app_secret": asecret})
|
||||
return r.json()["tenant_access_token"]
|
||||
|
||||
# ==================== QUESTION DATA ====================
|
||||
# Each entry: (questionImage, question, [options], [answer_index], explanation)
|
||||
# Format: image text is 3-5 word real notice/sign
|
||||
|
||||
I = lambda img, q, opts, ans, exp: {
|
||||
"questionImage": img, "question": q, "options": opts,
|
||||
"answer": ans, "explanation": exp
|
||||
}
|
||||
|
||||
DATA = {
|
||||
"021301": {
|
||||
"first": [
|
||||
I("021301-00.png","What does this poster say?",
|
||||
["The singer is here","The actor is on stage","The dancer is late"],[1],
|
||||
"海报上写着 The ACTOR is on stage，演员在舞台上。"),
|
||||
I("021301-01.png","What does the man have?",
|
||||
["White hair","Black beard","Red hat"],[1],
|
||||
"通缉令上写着 Man with black BEARD，男子有黑胡子。"),
|
||||
I("021301-02.png","What does the label say?",
|
||||
["The pictures are the same","The pictures are different","The pictures are old"],[1],
|
||||
"标签上写着 These pictures are DIFFERENT，两幅画不一样。"),
|
||||
I("021301-03.png","What was Lily today?",
|
||||
["Brave","Sad","Tired"],[0],
|
||||
"奖状上写着 Lily was very BRAVE today，Lily 今天很勇敢。"),
|
||||
I("021301-04.png","Who just moved in?",
|
||||
["A new teacher","A new neighbour","A new student"],[1],
|
||||
"卡片上写着 A new NEIGHBOUR moved in，新邻居搬来了。"),
|
||||
],
|
||||
"second": [
|
||||
I("021301-05.png","What time is dinner?",
|
||||
["At five","At six","At seven"],[1],
|
||||
"便条上写着 DINNER at six tonight，晚饭六点吃。"),
|
||||
I("021301-06.png","What is Mum doing?",
|
||||
["Sleeping","Cooking","Reading"],[1],
|
||||
"门牌上写着 Mum is COOKING right now，妈妈在做饭。"),
|
||||
I("021301-07.png","What kind of exit is this?",
|
||||
["Fire exit","Park exit","Shop exit"],[0],
|
||||
"标志上写着 FIRE exit this way，这是消防出口。"),
|
||||
I("021301-08.png","What is on show Friday?",
|
||||
["A family album","A film","A play"],[0],
|
||||
"海报上写着 Family ALBUM on show Friday，周五展示家庭相册。"),
|
||||
I("021301-09.png","What does this note ask?",
|
||||
["Read my diary","Do not read my diary","Buy a new diary"],[1],
|
||||
"便条上写着 Do not read my DIARY，不要看我的日记。"),
|
||||
],
|
||||
"desc": """1.
|
||||
图片材料文本：
|
||||
The ACTOR is on stage.
|
||||
|
||||
图片材料文本：
|
||||
Man with black BEARD wanted.
|
||||
|
||||
图片材料文本：
|
||||
These pictures are DIFFERENT.
|
||||
|
||||
图片材料文本：
|
||||
Lily was very BRAVE today.
|
||||
|
||||
图片材料文本：
|
||||
A new NEIGHBOUR moved in.
|
||||
|
||||
2.
|
||||
图片材料文本：
|
||||
DINNER at six tonight.
|
||||
|
||||
图片材料文本：
|
||||
Mum is COOKING right now.
|
||||
|
||||
图片材料文本：
|
||||
FIRE exit this way →
|
||||
|
||||
图片材料文本：
|
||||
Family ALBUM on show Friday.
|
||||
|
||||
图片材料文本：
|
||||
Do not read my DIARY.""",
|
||||
},
|
||||
"021401": {
|
||||
"first": [
|
||||
I("021401-00.png","What should you plan?",
|
||||
["Your weekend","Your lesson","Your dinner"],[0],
|
||||
"便签上写着 PLAN your weekend now，现在就计划周末吧。"),
|
||||
I("021401-01.png","How fast is the bike repair?",
|
||||
["In one day","In one hour","In one week"],[1],
|
||||
"店招牌上写着 Bike REPAIR in one hour，一小时修好自行车。"),
|
||||
I("021401-02.png","Where is today's newspaper?",
|
||||
["On the shelf","On the desk","In the bag"],[1],
|
||||
"图书馆标牌上写着 Today's NEWSPAPER on the desk，报纸在桌上。"),
|
||||
I("021401-03.png","What is lost?",
|
||||
["A blue backpack","A red pen","A white book"],[0],
|
||||
"失物招领上写着 Lost: Blue BACKPACK in Room 3，蓝色背包丢了。"),
|
||||
I("021401-04.png","What should you do on the bus?",
|
||||
["Stand up","Give your seat to old people","Sing songs"],[1],
|
||||
"公交标牌上写着 Give your SEAT to old people，给老人让座。"),
|
||||
],
|
||||
"second": [
|
||||
I("021401-05.png","When is the garden open?",
|
||||
["In the morning","After class","At lunch"],[1],
|
||||
"公告上写着 School GARDEN open after class，花园放学后开放。"),
|
||||
I("021401-06.png","What fruit is on sale?",
|
||||
["Apple","Banana","Melon"],[2],
|
||||
"市场标牌上写着 Sweet MELON for sale today，今天甜瓜热卖。"),
|
||||
I("021401-07.png","What does this lake sign say?",
|
||||
["Drink lake water","Do not drink lake water","Swim in the lake"],[1],
|
||||
"警示牌上写着 Do not drink lake WATER，不要喝湖水。"),
|
||||
I("021401-08.png","When should you plant a tree?",
|
||||
["On Monday","On Friday","On Sunday"],[1],
|
||||
"公告上写着 PLANT a tree on Friday，周五植树。"),
|
||||
I("021401-09.png","What starts next week?",
|
||||
["Summer camp","Winter camp","Spring class"],[0],
|
||||
"校园通知上写着 SUMMER camp starts next week，夏令营下周开始。"),
|
||||
],
|
||||
"desc": """1.
|
||||
图片材料文本：
|
||||
PLAN your weekend now.
|
||||
|
||||
图片材料文本：
|
||||
Bike REPAIR in one hour.
|
||||
|
||||
图片材料文本：
|
||||
Today's NEWSPAPER on the desk.
|
||||
|
||||
图片材料文本：
|
||||
Lost: Blue BACKPACK in Room 3.
|
||||
|
||||
图片材料文本：
|
||||
Give your SEAT to old people.
|
||||
|
||||
2.
|
||||
图片材料文本：
|
||||
School GARDEN open after class.
|
||||
|
||||
图片材料文本：
|
||||
Sweet MELON for sale today.
|
||||
|
||||
图片材料文本：
|
||||
Do not drink lake WATER.
|
||||
|
||||
图片材料文本：
|
||||
PLANT a tree on Friday.
|
||||
|
||||
图片材料文本：
|
||||
SUMMER camp starts next week.""",
|
||||
},
|
||||
"021501": {
|
||||
"first": [
|
||||
I("021501-00.png","Where should visitors sign in?",
|
||||
["At the gate","At the office","At the shop"],[1],
|
||||
"校门标识上写着 VISITORs sign in at the office，访客去办公室签到。"),
|
||||
I("021501-01.png","What kind of party is it?",
|
||||
["Birthday party","School party","Garden party"],[0],
|
||||
"横幅上写着 WELCOME to the birthday party，生日派对欢迎你。"),
|
||||
I("021501-02.png","Whose party are you invited to?",
|
||||
["Lily's","Tom's","Mum's"],[1],
|
||||
"邀请函上写着 You are INVITEd to Tom's party，你被邀请参加Tom的派对。"),
|
||||
I("021501-03.png","What can you do here?",
|
||||
["Sleep","Laugh","Cry"],[1],
|
||||
"海报上写着 Come and LAUGH with us，来和我们一起大笑。"),
|
||||
I("021501-04.png","What time does breakfast end?",
|
||||
["At 7 a.m.","At 8 a.m.","At 9 a.m."],[2],
|
||||
"酒店通知上写着 GUESTs: breakfast 7 to 9 a.m.，早餐9点结束。"),
|
||||
],
|
||||
"second": [
|
||||
I("021501-05.png","What should you check for?",
|
||||
["Mistakes","Stars","Pictures"],[0],
|
||||
"作业提醒上写着 Check for MISTAKEs first，先检查有没有错误。"),
|
||||
I("021501-06.png","What should you read carefully?",
|
||||
["The story","The instruction","The picture"],[1],
|
||||
"考试通知上写着 Read the INSTRUCTION carefully，仔细读说明。"),
|
||||
I("021501-07.png","What must you give if late?",
|
||||
["A reason","A gift","A book"],[0],
|
||||
"办公室告知上写着 Give a REASON if late，迟到要说明原因。"),
|
||||
I("021501-08.png","Where must you not bring drinks?",
|
||||
["Near the library","Near technology room","Near the garden"],[1],
|
||||
"电脑室标识上写着 No drinks near TECHNOLOGY room，科技室附近不准带饮料。"),
|
||||
I("021501-09.png","Where should you wash your brush?",
|
||||
["At home","Here","Outside"],[1],
|
||||
"美术室标识上写着 Wash your paint BRUSH here，在这里洗画笔。"),
|
||||
],
|
||||
"desc": """1.
|
||||
图片材料文本：
|
||||
VISITORs sign in at the office.
|
||||
|
||||
图片材料文本：
|
||||
WELCOME to the birthday party!
|
||||
|
||||
图片材料文本：
|
||||
You are INVITEd to Tom's party.
|
||||
|
||||
图片材料文本：
|
||||
Come and LAUGH with us!
|
||||
|
||||
图片材料文本：
|
||||
GUESTs: breakfast 7 to 9 a.m.
|
||||
|
||||
2.
|
||||
图片材料文本：
|
||||
Check for MISTAKEs first.
|
||||
|
||||
图片材料文本：
|
||||
Read the INSTRUCTION carefully.
|
||||
|
||||
图片材料文本：
|
||||
Give a REASON if late.
|
||||
|
||||
图片材料文本：
|
||||
No drinks near TECHNOLOGY room.
|
||||
|
||||
图片材料文本：
|
||||
Wash your paint BRUSH here.""",
|
||||
},
|
||||
"021601": {
|
||||
"first": [
|
||||
I("021601-00.png","What is the new record in?",
|
||||
["Run","Jump","Swim"],[1],
|
||||
"体育公告上写着 New school RECORD in jump，跳高破了新纪录。"),
|
||||
I("021601-01.png","What is the big event?",
|
||||
["Sports day","Exam day","Book day"],[0],
|
||||
"公告上写着 Sports day — a big EVENT，运动会是件大事。"),
|
||||
I("021601-02.png","Who must you have to enter?",
|
||||
["A friend","A teacher","A parent"],[1],
|
||||
"门上写着 Do not ENTER without teacher，没有老师不能进。"),
|
||||
I("021601-03.png","When should you return books?",
|
||||
["By Monday","By Friday","By Sunday"],[1],
|
||||
"图书馆通知上写着 RETURN books by this Friday，周五前还书。"),
|
||||
I("021601-04.png","What should you sort?",
|
||||
["Paper and food","Paper and glass","Glass and water"],[1],
|
||||
"回收标识上写着 Please SORT paper and glass，请把纸和玻璃分开。"),
|
||||
],
|
||||
"second": [
|
||||
I("021601-05.png","What colour is the handbag?",
|
||||
["Blue","Red","Green"],[1],
|
||||
"失物招领上写着 Lost: red HANDBAG near playground，丢了红色手提包。"),
|
||||
I("021601-06.png","What is not allowed here?",
|
||||
["Camera","Books","Shoes"],[0],
|
||||
"展馆标识上写着 No CAMERA in this room，此房间不许拍照。"),
|
||||
I("021601-07.png","When does the park gate close?",
|
||||
["At seven","At eight","At nine"],[1],
|
||||
"公园标牌上写着 Park GATE closes at eight，大门8点关闭。"),
|
||||
I("021601-08.png","How long to fix a wheel?",
|
||||
["10 minutes","30 minutes","60 minutes"],[1],
|
||||
"车店标牌上写着 Fix your WHEEL in 30 minutes，30分钟修好轮子。"),
|
||||
I("021601-09.png","Where is the main entrance?",
|
||||
["South side","East side","North side"],[2],
|
||||
"大楼标识上写着 Main ENTRANCE on north side，主入口在北边。"),
|
||||
],
|
||||
"desc": """1.
|
||||
图片材料文本：
|
||||
New school RECORD in jump!
|
||||
|
||||
图片材料文本：
|
||||
Sports day — a big EVENT.
|
||||
|
||||
图片材料文本：
|
||||
Do not ENTER without teacher.
|
||||
|
||||
图片材料文本：
|
||||
RETURN books by this Friday.
|
||||
|
||||
图片材料文本：
|
||||
Please SORT paper and glass.
|
||||
|
||||
2.
|
||||
图片材料文本：
|
||||
Lost: red HANDBAG near playground.
|
||||
|
||||
图片材料文本：
|
||||
No CAMERA in this room.
|
||||
|
||||
图片材料文本：
|
||||
Park GATE closes at eight.
|
||||
|
||||
图片材料文本：
|
||||
Fix your WHEEL in 30 minutes.
|
||||
|
||||
图片材料文本：
|
||||
Main ENTRANCE on north side.""",
|
||||
},
|
||||
"021701": {
|
||||
"first": [
|
||||
I("021701-00.png","Who should you not talk to?",
|
||||
["The driver","The guard","The teacher"],[0],
|
||||
"公交标牌上写着 Do not talk to the DRIVER，不要和司机说话。"),
|
||||
I("021701-01.png","Where should you look both ways?",
|
||||
["At school","On the street","At home"],[1],
|
||||
"安全海报上写着 Look both ways on the STREET，过街道要左右看。"),
|
||||
I("021701-02.png","When is the farmers' market?",
|
||||
["Every Monday","Every Saturday","Every Sunday"],[1],
|
||||
"市场标牌上写着 Farmers' MARKET every Saturday，每周六有农夫市集。"),
|
||||
I("021701-03.png","Where can you get a guidebook?",
|
||||
["At this desk","At the gate","In the shop"],[0],
|
||||
"咨询台标牌上写着 Free GUIDEBOOK at this desk，此处免费领指南。"),
|
||||
I("021701-04.png","What time does shopping start?",
|
||||
["At 10 a.m.","At 11 a.m.","At 12 p.m."],[0],
|
||||
"商场标牌上写着 SHOPPING hours: 10 a.m. to 8 p.m.，购物10点开始。"),
|
||||
],
|
||||
"second": [
|
||||
I("021701-05.png","Where is the washing machine?",
|
||||
["On first floor","On second floor","Outside"],[0],
|
||||
"洗衣房标识上写着 Washing MACHINE on first floor，洗衣机在一楼。"),
|
||||
I("021701-06.png","What should you draw?",
|
||||
["Your school","Your family","Your pet"],[1],
|
||||
"美术社通知上写着 DRAW your family for the show，画你的家人参展。"),
|
||||
I("021701-07.png","When is basketball practice?",
|
||||
["At three","At four","At five"],[1],
|
||||
"体育通知上写着 BASKETBALL practice at four today，今天四点篮球训练。"),
|
||||
I("021701-08.png","Where should you put the books?",
|
||||
["On the desk","On the bookcase","On the floor"],[1],
|
||||
"图书馆标识上写着 Put books on the BOOKCASE，把书放回书柜。"),
|
||||
I("021701-09.png","When is the science fair?",
|
||||
["On Friday","On Monday","On Wednesday"],[1],
|
||||
"科学展标识上写着 Show your INVENTION on Monday，周一展示你的发明。"),
|
||||
],
|
||||
"desc": """1.
|
||||
图片材料文本：
|
||||
Do not talk to the DRIVER.
|
||||
|
||||
图片材料文本：
|
||||
Look both ways on the STREET.
|
||||
|
||||
图片材料文本：
|
||||
Farmers' MARKET every Saturday.
|
||||
|
||||
图片材料文本：
|
||||
Free GUIDEBOOK at this desk.
|
||||
|
||||
图片材料文本：
|
||||
SHOPPING hours: 10 a.m. to 8 p.m.
|
||||
|
||||
2.
|
||||
图片材料文本：
|
||||
Washing MACHINE on first floor.
|
||||
|
||||
图片材料文本：
|
||||
DRAW your family for the show.
|
||||
|
||||
图片材料文本：
|
||||
BASKETBALL practice at four today.
|
||||
|
||||
图片材料文本：
|
||||
Put books on the BOOKCASE.
|
||||
|
||||
图片材料文本：
|
||||
Show your INVENTION on Monday.""",
|
||||
},
|
||||
"021801": {
|
||||
"first": [
|
||||
I("021801-00.png","What time does the library close?",
|
||||
["At 2 p.m.","At 4 p.m.","At 6 p.m."],[1],
|
||||
"图书馆通知上写着 LIBRARY open 8 a.m. to 4 p.m.，下午4点闭馆。"),
|
||||
I("021801-01.png","Where can you read the magazines?",
|
||||
["At home","Here only","In the park"],[1],
|
||||
"阅览室标牌上写着 New MAGAZINEs — read here only，杂志仅供此处阅读。"),
|
||||
I("021801-02.png","What is on at three?",
|
||||
["A film","A cartoon","A play"],[1],
|
||||
"TV室标牌上写着 CARTOON at three this afternoon，下午三点播动画片。"),
|
||||
I("021801-03.png","When is the English test?",
|
||||
["Friday morning","Monday afternoon","Wednesday evening"],[0],
|
||||
"考试通知上写着 English TEST on Friday morning，周五上午英语考试。"),
|
||||
I("021801-04.png","How should you read the instructions?",
|
||||
["Quickly","Carefully","Slowly"],[1],
|
||||
"实验室标牌上写着 Read CAREFULLY before you start，开始前仔细阅读。"),
|
||||
],
|
||||
"second": [
|
||||
I("021801-05.png","What does the toy need?",
|
||||
["A new book","A new battery","A new bag"],[1],
|
||||
"玩具上贴着 This toy needs a new BATTERY，玩具需要新电池。"),
|
||||
I("021801-06.png","Where is the reading corner?",
|
||||
["On the right","On the left","In the middle"],[1],
|
||||
"图书馆标牌上写着 Reading CORNER on the left side，阅读角在左边。"),
|
||||
I("021801-07.png","When is the school play?",
|
||||
["On Friday","On Saturday","On Sunday"],[1],
|
||||
"校公告上写着 Play at the THEATRE this Saturday，周六剧院有演出。"),
|
||||
I("021801-08.png","What should you not climb?",
|
||||
["The wall","The stairs","The park trees"],[2],
|
||||
"公园警示牌上写着 Do not CLIMB the park trees，不要爬公园的树。"),
|
||||
I("021801-09.png","When is lunch today?",
|
||||
["At midday","At one","At two"],[0],
|
||||
"食堂通知上写着 Lunch is at MIDDAY today，今天中午十二点午饭。"),
|
||||
],
|
||||
"desc": """1.
|
||||
图片材料文本：
|
||||
LIBRARY open 8 a.m. to 4 p.m.
|
||||
|
||||
图片材料文本：
|
||||
New MAGAZINEs — read here only.
|
||||
|
||||
图片材料文本：
|
||||
CARTOON at three this afternoon.
|
||||
|
||||
图片材料文本：
|
||||
English TEST on Friday morning.
|
||||
|
||||
图片材料文本：
|
||||
Read CAREFULLY before you start.
|
||||
|
||||
2.
|
||||
图片材料文本：
|
||||
This toy needs a new BATTERY.
|
||||
|
||||
图片材料文本：
|
||||
Reading CORNER on the left side.
|
||||
|
||||
图片材料文本：
|
||||
Play at the THEATRE this Saturday.
|
||||
|
||||
图片材料文本：
|
||||
Do not CLIMB the park trees.
|
||||
|
||||
图片材料文本：
|
||||
Lunch is at MIDDAY today.""",
|
||||
},
|
||||
}
|
||||
|
||||
# ==================== BUILD & WRITE ====================
|
||||
def build(qid):
|
||||
def qset(qs):
|
||||
return [{
|
||||
"questionImage": q["questionImage"], "question": q["question"],
|
||||
"options": q["options"], "answer": q["answer"],
|
||||
"ability": AB, "explanation": q["explanation"],
|
||||
} for q in qs]
|
||||
return {
|
||||
"first": {"category": "reading", "type": "reading_matchInfo", "questionSetID": qid, "questionSet": qset(DATA[qid]["first"])},
|
||||
"second": {"category": "reading", "type": "reading_matchInfo", "questionSetID": qid, "questionSet": qset(DATA[qid]["second"])},
|
||||
}
|
||||
|
||||
# === STEP 1: Create empty records ===
|
||||
token = get_token()
|
||||
print("=== Step 1: Create empty records ===")
|
||||
new_rids = {}
|
||||
for qid in sorted(DATA):
|
||||
r = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"题目集合 ID": qid, "dataStatus": "0"}})
|
||||
new_rids[qid] = r.json()["data"]["record"]["record_id"]
|
||||
print(f" {qid}: {new_rids[qid]}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# === STEP 2: Wait for automation ===
|
||||
print("\n=== Step 2: Wait 35s ===")
|
||||
time.sleep(35)
|
||||
|
||||
# === STEP 3: PUT jsonData ===
|
||||
print("\n=== Step 3: PUT jsonData ===")
|
||||
token = get_token()
|
||||
for qid in sorted(new_rids):
|
||||
j = build(qid)
|
||||
js = json.dumps(j, ensure_ascii=False)
|
||||
r = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records/{new_rids[qid]}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"jsonData": js}})
|
||||
print(f" {qid}: json={len(js)}chars code={r.json().get('code')}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# === STEP 4: Wait then PUT 图片描述 ===
|
||||
print("\n=== Step 4: Wait 15s + PUT 图片描述 ===")
|
||||
time.sleep(15)
|
||||
token = get_token()
|
||||
for qid in sorted(new_rids):
|
||||
r = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records/{new_rids[qid]}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"图片描述": DATA[qid]["desc"]}})
|
||||
print(f" {qid}: desc code={r.json().get('code')} len={len(DATA[qid]['desc'])}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# === STEP 5: Final verify ===
|
||||
print("\n=== Step 5: Wait 20s + Verify ===")
|
||||
time.sleep(20)
|
||||
token = get_token()
|
||||
for qid in sorted(new_rids):
|
||||
r = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records/{new_rids[qid]}",
|
||||
headers={"Authorization": f"Bearer {token}"})
|
||||
fields = r.json()["data"]["record"]["fields"]
|
||||
jd = fields.get("jsonData", "")
|
||||
desc = fields.get("图片描述", "") or ""
|
||||
try:
|
||||
j = json.loads(jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
ok = (fq == 5 and sq == 5 and len(desc) > 100)
|
||||
print(f" {'✅' if ok else '❌'} {qid} ({new_rids[qid]}): {fq}/{sq}q desc={len(desc)}chars")
|
||||
except Exception as e:
|
||||
print(f" ❌ {qid}: {e}")
|
||||
|
||||
print("\nDone.")
|
||||
265
scripts/batch_reading_pic_judge.py
Normal file
265
scripts/batch_reading_pic_judge.py
Normal file
@ -0,0 +1,265 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Produce reading_pic_judge for 4 IDs (121301-121601), L1 A级."""
|
||||
import json, requests, time
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblJc60aO0T163MJ"
|
||||
|
||||
# ============================================================
|
||||
# ALL QUESTIONS — L1 A级, 3-4词极简句, L1词汇
|
||||
# ============================================================
|
||||
ALL_DATA = {}
|
||||
|
||||
# ---- 121301 ----
|
||||
ALL_DATA["121301"] = {
|
||||
"first": [
|
||||
{"qi": "121301-00.png", "q": "These are houses.", "a": "Yes",
|
||||
"x": "图上有三栋房子，句子说「这些是房子」，匹配。"},
|
||||
{"qi": "121301-01.png", "q": "This is a home.", "a": "No",
|
||||
"x": "图上是一个橱柜，不是家(home)，句子与图片不匹配。"},
|
||||
{"qi": "121301-02.png", "q": "This is a sofa.", "a": "Yes",
|
||||
"x": "图上是一张沙发，句子说「这是一张沙发」，匹配。"},
|
||||
{"qi": "121301-03.png", "q": "These are cupboards.", "a": "No",
|
||||
"x": "图上是一间卧室放着一张床，句子说「这些是橱柜」，与图片不匹配。"},
|
||||
{"qi": "121301-04.png", "q": "This is a bedroom.", "a": "Yes",
|
||||
"x": "图上是一间有床的卧室，句子说「这是一间卧室」，匹配。"},
|
||||
],
|
||||
"second": [
|
||||
{"qi": "121301-05.png", "q": "This is a zoo.", "a": "Yes",
|
||||
"x": "图上是动物园入口，能看到动物，句子说「这是一个动物园」，匹配。"},
|
||||
{"qi": "121301-06.png", "q": "This is a hippo.", "a": "Yes",
|
||||
"x": "图上是一只河马在水里，句子说「这是一只河马」，匹配。"},
|
||||
{"qi": "121301-07.png", "q": "This is a bear.", "a": "No",
|
||||
"x": "图上是一条牛仔裤，不是熊(bear)，句子与图片不匹配。"},
|
||||
{"qi": "121301-08.png", "q": "These are jeans.", "a": "Yes",
|
||||
"x": "图上是一条牛仔裤，句子说「这些是牛仔裤」，匹配。"},
|
||||
{"qi": "121301-09.png", "q": "This is a sock.", "a": "No",
|
||||
"x": "图上是一只大棕熊在森林里，不是袜子(sock)，句子与图片不匹配。"},
|
||||
],
|
||||
}
|
||||
|
||||
# ---- 121401 ----
|
||||
ALL_DATA["121401"] = {
|
||||
"first": [
|
||||
{"qi": "121401-00.png", "q": "These are students.", "a": "Yes",
|
||||
"x": "图上是几个学生坐在教室里，句子说「这些是学生」，匹配。"},
|
||||
{"qi": "121401-01.png", "q": "This is a school.", "a": "Yes",
|
||||
"x": "图上是一所学校建筑，句子说「这是一所学校」，匹配。"},
|
||||
{"qi": "121401-02.png", "q": "This is a teacher.", "a": "No",
|
||||
"x": "图上是几支蜡笔，不是老师(teacher)，句子与图片不匹配。"},
|
||||
{"qi": "121401-03.png", "q": "These are crayons.", "a": "Yes",
|
||||
"x": "图上是几支彩色蜡笔放在桌上，句子说「这些是蜡笔」，匹配。"},
|
||||
{"qi": "121401-04.png", "q": "These are boards.", "a": "No",
|
||||
"x": "图上是一位老师在讲桌前，不是黑板(board)，句子与图片不匹配。"},
|
||||
],
|
||||
"second": [
|
||||
{"qi": "121401-05.png", "q": "This is a mat.", "a": "Yes",
|
||||
"x": "图上是一张地板上的垫子，句子说「这是一张垫子」，匹配。"},
|
||||
{"qi": "121401-06.png", "q": "This is a letter.", "a": "No",
|
||||
"x": "图上是一张课桌上面有台灯，不是信(letter)，句子与图片不匹配。"},
|
||||
{"qi": "121401-07.png", "q": "This is a desk.", "a": "Yes",
|
||||
"x": "图上是一张课桌，句子说「这是一张课桌」，匹配。"},
|
||||
{"qi": "121401-08.png", "q": "This is a schoolbag.", "a": "No",
|
||||
"x": "图上是一个女士手提包，不是书包(schoolbag)，句子与图片不匹配。"},
|
||||
{"qi": "121401-09.png", "q": "This is a handbag.", "a": "Yes",
|
||||
"x": "图上是一个手提包，句子说「这是一个手提包」，匹配。"},
|
||||
],
|
||||
}
|
||||
|
||||
# ---- 121501 ----
|
||||
ALL_DATA["121501"] = {
|
||||
"first": [
|
||||
{"qi": "121501-00.png", "q": "This is a body.", "a": "Yes",
|
||||
"x": "图上是一个孩子的全身，句子说「这是一个身体」，匹配。"},
|
||||
{"qi": "121501-01.png", "q": "This is a head.", "a": "No",
|
||||
"x": "图上是一张嘴的特写，不是头(head)，句子与图片不匹配。"},
|
||||
{"qi": "121501-02.png", "q": "These are mouths.", "a": "No",
|
||||
"x": "图上是两个孩子在玩耍（朋友），不是嘴(mouth)，句子与图片不匹配。"},
|
||||
{"qi": "121501-03.png", "q": "This is an ear.", "a": "Yes",
|
||||
"x": "图上是一只耳朵的特写，句子说「这是一只耳朵」，匹配。"},
|
||||
{"qi": "121501-04.png", "q": "These are friends.", "a": "Yes",
|
||||
"x": "图上是两个小朋友在一起玩，句子说「这些是朋友」，匹配。"},
|
||||
],
|
||||
"second": [
|
||||
{"qi": "121501-05.png", "q": "This is a camera.", "a": "Yes",
|
||||
"x": "图上是一台相机，句子说「这是一台相机」，匹配。"},
|
||||
{"qi": "121501-06.png", "q": "This is a boy.", "a": "Yes",
|
||||
"x": "图上是一个小男孩，句子说「这是一个男孩」，匹配。"},
|
||||
{"qi": "121501-07.png", "q": "This is a girl.", "a": "No",
|
||||
"x": "图上是一个滑板，不是女孩(girl)，句子与图片不匹配。"},
|
||||
{"qi": "121501-08.png", "q": "These are skateboards.", "a": "No",
|
||||
"x": "图上是一个女孩在滑滑板，句子说「这些是滑板」但图中只有一个，且重点是人在滑板动作，与句子描述不符。"},
|
||||
{"qi": "121501-09.png", "q": "This is a skateboard.", "a": "Yes",
|
||||
"x": "图上是一个滑板，句子说「这是一个滑板」，匹配。"},
|
||||
],
|
||||
}
|
||||
|
||||
# ---- 121601 ----
|
||||
ALL_DATA["121601"] = {
|
||||
"first": [
|
||||
{"qi": "121601-00.png", "q": "It is summer.", "a": "Yes",
|
||||
"x": "图上是阳光海滩夏天场景，句子说「现在是夏天」，匹配。"},
|
||||
{"qi": "121601-01.png", "q": "It is autumn.", "a": "No",
|
||||
"x": "图上是冬天白雪覆盖的场景，不是秋天(autumn)，句子与图片不匹配。"},
|
||||
{"qi": "121601-02.png", "q": "It is winter.", "a": "Yes",
|
||||
"x": "图上是一片雪景，句子说「现在是冬天」，匹配。"},
|
||||
{"qi": "121601-03.png", "q": "It is cold.", "a": "Yes",
|
||||
"x": "图上是一个孩子穿着厚棉衣冬天场景，句子说「天气冷」，匹配。"},
|
||||
{"qi": "121601-04.png", "q": "It is spring.", "a": "No",
|
||||
"x": "图上是秋天落叶满地，不是春天(spring)，句子与图片不匹配。"},
|
||||
],
|
||||
"second": [
|
||||
{"qi": "121601-05.png", "q": "This is a bus.", "a": "Yes",
|
||||
"x": "图上是一辆公交车，句子说「这是一辆公交车」，匹配。"},
|
||||
{"qi": "121601-06.png", "q": "This is a taxi.", "a": "No",
|
||||
"x": "图上是一条长裤，不是出租车(taxi)，句子与图片不匹配。"},
|
||||
{"qi": "121601-07.png", "q": "These are trousers.", "a": "Yes",
|
||||
"x": "图上是一条长裤，句子说「这些是长裤」，匹配。"},
|
||||
{"qi": "121601-08.png", "q": "These are shorts.", "a": "No",
|
||||
"x": "图上是白雪皑皑的下雪场景，不是短裤(shorts)，句子与图片不匹配。"},
|
||||
{"qi": "121601-09.png", "q": "This is snow.", "a": "Yes",
|
||||
"x": "图上是一片雪景，句子说「这是雪」，匹配。"},
|
||||
],
|
||||
}
|
||||
|
||||
# ============================================================
|
||||
# Build JSON
|
||||
# ============================================================
|
||||
def build_json(qid, groups):
|
||||
return {
|
||||
"first": {
|
||||
"category": "reading",
|
||||
"type": "reading_pic_judge",
|
||||
"questionSetID": qid,
|
||||
"textTitle": "Look and read. Put a tick (Yes) or a cross (No) in the box.",
|
||||
"questionSet": [
|
||||
{
|
||||
"questionImage": item["qi"],
|
||||
"question": item["q"],
|
||||
"answerText": item["a"],
|
||||
"ability": ["图文匹配"],
|
||||
"explanation": item["x"],
|
||||
}
|
||||
for item in groups["first"]
|
||||
],
|
||||
},
|
||||
"second": {
|
||||
"category": "reading",
|
||||
"type": "reading_pic_judge",
|
||||
"questionSetID": qid,
|
||||
"textTitle": "Look and read. Put a tick (Yes) or a cross (No) in the box.",
|
||||
"questionSet": [
|
||||
{
|
||||
"questionImage": item["qi"],
|
||||
"question": item["q"],
|
||||
"answerText": item["a"],
|
||||
"ability": ["图文匹配"],
|
||||
"explanation": item["x"],
|
||||
}
|
||||
for item in groups["second"]
|
||||
],
|
||||
},
|
||||
}
|
||||
|
||||
# ============================================================
|
||||
# Get token & find existing records
|
||||
# ============================================================
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
# Find existing records
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records?page_size=20",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
record_map = {}
|
||||
for item in resp.json()["data"]["items"]:
|
||||
fid = item["fields"].get("题目集合 ID", "")
|
||||
if fid in ALL_DATA:
|
||||
record_map[fid] = item["record_id"]
|
||||
print(f"Found: {fid} → {item['record_id']}")
|
||||
|
||||
# ============================================================
|
||||
# Update each record with real jsonData
|
||||
# ============================================================
|
||||
for qid in sorted(ALL_DATA.keys()):
|
||||
rid = record_map.get(qid)
|
||||
if not rid:
|
||||
print(f"❌ {qid}: no existing record, creating new...")
|
||||
resp = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"题目集合 ID": qid, "dataStatus": "0"}},
|
||||
)
|
||||
rid = resp.json()["data"]["record"]["record_id"]
|
||||
print(f" Created: {rid}")
|
||||
time.sleep(1.0)
|
||||
|
||||
json_data = build_json(qid, ALL_DATA[qid])
|
||||
json_str = json.dumps(json_data, ensure_ascii=False)
|
||||
|
||||
# Verify balance
|
||||
for grp in ("first", "second"):
|
||||
qs = json_data[grp]["questionSet"]
|
||||
yc = sum(1 for q in qs if q["answerText"] == "Yes")
|
||||
nc = sum(1 for q in qs if q["answerText"] == "No")
|
||||
print(f" {qid} {grp}: {yc}Y/{nc}N, json={len(json_str)}chars")
|
||||
|
||||
# Update
|
||||
resp = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"jsonData": json_str}},
|
||||
)
|
||||
code = resp.json().get("code")
|
||||
print(f" Update: code={code}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# ============================================================
|
||||
# Wait & Verify
|
||||
# ============================================================
|
||||
print("\nWaiting 15s for verification...")
|
||||
time.sleep(15)
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
print("\n=== Final Verification ===")
|
||||
all_ok = True
|
||||
for qid in sorted(ALL_DATA.keys()):
|
||||
rid = record_map.get(qid)
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
jd = resp.json()["data"]["record"]["fields"].get("jsonData", "")
|
||||
try:
|
||||
j = json.loads(jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
if fq == 5 and sq == 5:
|
||||
fq1 = j["first"]["questionSet"][0]["question"]
|
||||
sq1 = j["second"]["questionSet"][0]["question"]
|
||||
fy = sum(1 for q in j["first"]["questionSet"] if q["answerText"] == "Yes")
|
||||
fn = sum(1 for q in j["first"]["questionSet"] if q["answerText"] == "No")
|
||||
print(f"✅ {qid}: first={fq}q({fy}Y{fn}N) second={sq}q | Q1='{fq1}' | SQ1='{sq1}'")
|
||||
else:
|
||||
print(f"❌ {qid}: first={fq}q second={sq}q | jd={len(jd)}chars")
|
||||
all_ok = False
|
||||
except Exception as e:
|
||||
print(f"❌ {qid}: PARSE_ERROR {e} | jd={len(jd)}chars")
|
||||
all_ok = False
|
||||
|
||||
print(f"\n{'✅ ALL VERIFIED' if all_ok else '❌ SOME CORRUPTED'}")
|
||||
600
scripts/batch_reading_pic_qa.py
Normal file
600
scripts/batch_reading_pic_qa.py
Normal file
@ -0,0 +1,600 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Batch produce reading_pic_qa questions and write to bitable."""
|
||||
|
||||
import json
|
||||
import subprocess
|
||||
import sys
|
||||
import os
|
||||
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt" # 阅读-P7-看图回答题
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
|
||||
TEXT_TITLE = "Look and read. Put a tick (Yes) or a cross (No) in the box."
|
||||
|
||||
# ============================================================
|
||||
# All question data
|
||||
# ============================================================
|
||||
|
||||
ALL_QUESTIONS = {
|
||||
"000001": {
|
||||
"first": {
|
||||
"textImage": "000001-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A boy looks out of the window.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中男孩正站在窗前往外看，与句子描述一致。考察知识点：look out of（向外看）。"
|
||||
},
|
||||
{
|
||||
"question": "The boy finds a red ball.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中男孩从床底下找到一只红色的皮球，与句子描述一致。考察知识点：find（找到）。"
|
||||
},
|
||||
{
|
||||
"question": "A girl picks up a sock.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中是男孩捡起一只袜子，并非女孩，与句子描述不符「女孩捡起袜子」。考察知识点：pick up（捡起）。"
|
||||
},
|
||||
{
|
||||
"question": "The boy puts on a hat.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中男孩正在穿鞋，并非戴帽子。put on 的对象是 shoe 而非 hat，与句子描述不符。考察知识点：put on（穿上/戴上）。"
|
||||
},
|
||||
{
|
||||
"question": "The boy stops at the door.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中男孩在门口停下脚步回头看，与句子描述一致。考察知识点：stop（停下）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "000001-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A boy fastens his helmet.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中男孩正在系紧头盔的带子，与句子描述一致。考察知识点：fasten（系紧/扣紧）。"
|
||||
},
|
||||
{
|
||||
"question": "A girl unfastens the rope.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中女孩在攀爬架上正在解开安全绳，与句子描述一致。考察知识点：unfasten（解开）。"
|
||||
},
|
||||
{
|
||||
"question": "The playground is dangerous.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中游乐场有安全绳、防护垫等安全设施，是安全的游戏区域，并非危险。考察知识点：dangerous（危险的）。"
|
||||
},
|
||||
{
|
||||
"question": "A woman guides the boy.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中一位女士正在指导男孩如何攀爬，与句子描述一致。考察知识点：guide（指导/引导）。"
|
||||
},
|
||||
{
|
||||
"question": "The pirate is on a ship.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中穿海盗服装的男孩在游乐场攀爬架上玩耍，并不在船上。考察知识点：pirate（海盗）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
"010101": {
|
||||
"first": {
|
||||
"textImage": "010101-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "The chicken is on the plate.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中盘子里放着鸡肉，与句子描述一致。考察知识点：chicken（鸡；鸡肉）。"
|
||||
},
|
||||
{
|
||||
"question": "The girl reads a menu.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中女孩正在看菜单，与句子描述一致。考察知识点：menu（菜单）。"
|
||||
},
|
||||
{
|
||||
"question": "The boy cooks the steak.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中是厨师在烹饪牛排，并非男孩在烹饪，与句子描述不符。考察知识点：cook（烹饪）。"
|
||||
},
|
||||
{
|
||||
"question": "The steak is on the table.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中桌上放着一块牛排，与句子描述一致。考察知识点：steak（牛排）。"
|
||||
},
|
||||
{
|
||||
"question": "A chef has a red hat.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中厨师帽是白色的，并非红色，与句子描述不符。考察知识点：chef（厨师）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "010101-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "The onion is white.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中摊位上放着白色的洋葱，与句子描述一致。考察知识点：onion（洋葱）。"
|
||||
},
|
||||
{
|
||||
"question": "The curry is yellow.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中碗里的咖喱是黄色的，与句子描述一致。考察知识点：curry（咖喱）。"
|
||||
},
|
||||
{
|
||||
"question": "The mushroom is blue.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中蘑菇是棕色/白色的，并非蓝色。自然界没有蓝色的蘑菇，与句子描述不符。考察知识点：mushroom（蘑菇）。"
|
||||
},
|
||||
{
|
||||
"question": "The garlic is green.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中大蒜是白色的，并非绿色，与句子描述不符。考察知识点：garlic（大蒜）。"
|
||||
},
|
||||
{
|
||||
"question": "The chilli is red.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中摊位上放着红色的辣椒，与句子描述一致。考察知识点：chilli（辣椒）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
"010201": {
|
||||
"first": {
|
||||
"textImage": "010201-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A robot is in the room.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中房间中央站着一个机器人，与句子描述一致。考察知识点：robot（机器人）。"
|
||||
},
|
||||
{
|
||||
"question": "The robot has a big head.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中机器人的头部很大，与句子描述一致。考察知识点：head（头）。"
|
||||
},
|
||||
{
|
||||
"question": "The robot has four legs.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中机器人只有两条腿，并非四条，与句子描述不符。考察知识点：leg（腿）。"
|
||||
},
|
||||
{
|
||||
"question": "The robot has two arms.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中机器人有两条手臂，与句子描述一致。考察知识点：arm（手臂）。"
|
||||
},
|
||||
{
|
||||
"question": "The robot's body is green.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中机器人身体是银灰色的，并非绿色，与句子描述不符。考察知识点：body（身体）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "010201-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A story is on the wall.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中布告栏上贴着一篇故事，与句子描述一致。考察知识点：story（故事）。"
|
||||
},
|
||||
{
|
||||
"question": "A poster is on the door.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中海报贴在布告栏上，并非贴在门上，与句子描述不符。考察知识点：poster（海报）。"
|
||||
},
|
||||
{
|
||||
"question": "A report is on the desk.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中桌上放着一份报告，与句子描述一致。考察知识点：report（报告）。"
|
||||
},
|
||||
{
|
||||
"question": "The news is on TV.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中场景是教室布告栏，没有电视。新闻印在纸上贴在布告栏上，并非在电视上播放。考察知识点：news（新闻）。"
|
||||
},
|
||||
{
|
||||
"question": "A picture is on the board.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中布告板上贴着一张图片，与句子描述一致。考察知识点：picture（图片）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
"010301": {
|
||||
"first": {
|
||||
"textImage": "010301-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "The lion has a mane.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中狮子有一圈鬃毛，与句子描述一致。考察知识点：lion（狮子）。"
|
||||
},
|
||||
{
|
||||
"question": "The animal is a dog.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中动物是狮子，并非狗，与句子描述不符。考察知识点：animal（动物）。"
|
||||
},
|
||||
{
|
||||
"question": "A bear is in the tree.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中树洞里有一只熊，与句子描述一致。考察知识点：bear（熊）。"
|
||||
},
|
||||
{
|
||||
"question": "The butterfly is pink.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中蝴蝶是黄色和黑色的，并非粉色，与句子描述不符。考察知识点：butterfly（蝴蝶）。"
|
||||
},
|
||||
{
|
||||
"question": "The fish is in water.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中鱼在水中游动，与句子描述一致。考察知识点：fish（鱼）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "010301-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "The pool is blue.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中游泳池的水是蓝色的，与句子描述一致。考察知识点：pool（水池/游泳池）。"
|
||||
},
|
||||
{
|
||||
"question": "A storm is in the sky.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中天空晴朗有太阳，并没有暴风雨，与句子描述不符。考察知识点：storm（暴风雨）。"
|
||||
},
|
||||
{
|
||||
"question": "The lake is big.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中的湖泊很大，与句子描述一致。考察知识点：lake（湖泊）。"
|
||||
},
|
||||
{
|
||||
"question": "The grass is brown.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中草地是绿色的，并非棕色，与句子描述不符。考察知识点：grass（草地）。"
|
||||
},
|
||||
{
|
||||
"question": "A forest has many trees.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中森林里有很多树，与句子描述一致。考察知识点：forest（森林）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
"010401": {
|
||||
"first": {
|
||||
"textImage": "010401-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A purple hat is on the chair.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中紫色帽子在桌上，并不在椅子上，与句子描述不符。考察知识点：purple（紫色的）。"
|
||||
},
|
||||
{
|
||||
"question": "The pink flower is big.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中有朵粉色的花很大，与句子描述一致。考察知识点：pink（粉色的）。"
|
||||
},
|
||||
{
|
||||
"question": "The picture is colourful.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中的画色彩丰富，与句子描述一致。考察知识点：colourful（色彩丰富的）。"
|
||||
},
|
||||
{
|
||||
"question": "The spoon is silver.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中勺子为木色的，并非银色，与句子描述不符。考察知识点：silver（银色的）。"
|
||||
},
|
||||
{
|
||||
"question": "A special cake is on the desk.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中桌中央有一个装饰特别的生日蛋糕，与其他物品不同。考察知识点：special（特别的）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "010401-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A sour lemon is on the table.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中桌上放着一个柠檬（柠檬是酸的），与句子描述一致。考察知识点：sour（酸的）。"
|
||||
},
|
||||
{
|
||||
"question": "The mango is yellow.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中芒果是黄色的，与句子描述一致。考察知识点：mango（芒果）。"
|
||||
},
|
||||
{
|
||||
"question": "The grape is purple.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中葡萄是紫色的，与句子描述一致。考察知识点：grape（葡萄）。"
|
||||
},
|
||||
{
|
||||
"question": "The lemon is sweet.",
|
||||
"answerText": "No",
|
||||
"explanation": "柠檬是酸的，并非甜的，与句子描述不符。考察知识点：lemon（柠檬）。"
|
||||
},
|
||||
{
|
||||
"question": "The juice is orange.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中果汁是紫色的葡萄汁，并非橙色的橙汁，与句子描述不符。考察知识点：juice（果汁）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
"010501": {
|
||||
"first": {
|
||||
"textImage": "010501-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "The company has an office.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中公司设有办公室，与句子描述一致。考察知识点：company（公司）。"
|
||||
},
|
||||
{
|
||||
"question": "A card is on the desk.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中桌面上放着一张卡片，与句子描述一致。考察知识点：card（卡片）。"
|
||||
},
|
||||
{
|
||||
"question": "The receptionist is a man.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中前台接待员是女性，并非男性，与句子描述不符。考察知识点：receptionist（接待员）。"
|
||||
},
|
||||
{
|
||||
"question": "The office is small.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中的办公室不大/是小的，与句子描述一致。考察知识点：office（办公室）。"
|
||||
},
|
||||
{
|
||||
"question": "A meeting is in the park.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中会议在办公室会议室举行，不在公园里，与句子描述不符。考察知识点：meeting（会议）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "010501-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "The bathroom is clean.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中卫生间干净整洁，与句子描述一致。考察知识点：bathroom（卫生间）。"
|
||||
},
|
||||
{
|
||||
"question": "A bookshelf is on the wall.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中书柜靠墙摆放，与句子描述一致。考察知识点：bookshelf（书架）。"
|
||||
},
|
||||
{
|
||||
"question": "The toilet is in the kitchen.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中马桶在卫生间里，不在厨房里，与句子描述不符。考察知识点：toilet（马桶）。"
|
||||
},
|
||||
{
|
||||
"question": "The lamp is on the table.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中台灯放在桌上，与句子描述一致。考察知识点：lamp（台灯）。"
|
||||
},
|
||||
{
|
||||
"question": "A laptop is on the bed.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中笔记本电脑在书桌上，不在床上，与句子描述不符。考察知识点：laptop（笔记本电脑）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
"010601": {
|
||||
"first": {
|
||||
"textImage": "010601-00.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A big stone is on the ground.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中地上一块大石头，与句子描述一致。考察知识点：stone（石头）。"
|
||||
},
|
||||
{
|
||||
"question": "A dinosaur has big bones.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中恐龙骨架有巨大的骨头，与句子描述一致。考察知识点：dinosaur（恐龙）。"
|
||||
},
|
||||
{
|
||||
"question": "The sky is gray.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中天空是蓝色的，并非灰色，与句子描述不符。考察知识点：gray（灰色的）。"
|
||||
},
|
||||
{
|
||||
"question": "The rock is very big.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中的岩石非常大，与句子描述一致。考察知识点：rock（岩石）。"
|
||||
},
|
||||
{
|
||||
"question": "The flower is fresh.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中场景是岩石挖掘区，没有鲜花。花朵不存在于场景中，与句子描述不符。考察知识点：fresh（新鲜的）。"
|
||||
},
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"textImage": "010601-01.png",
|
||||
"questions": [
|
||||
{
|
||||
"question": "A tool is on the desk.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中桌上放着一件工具，与句子描述一致。考察知识点：tool（工具）。"
|
||||
},
|
||||
{
|
||||
"question": "A scientist has a white coat.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中科学家穿着白色实验服，与句子描述一致。考察知识点：scientist（科学家）。"
|
||||
},
|
||||
{
|
||||
"question": "A brain is in the jar.",
|
||||
"answerText": "Yes",
|
||||
"explanation": "图中罐子里放着一个大脑模型，与句子描述一致。考察知识点：brain（大脑）。"
|
||||
},
|
||||
{
|
||||
"question": "The boy dives in the sea.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中男孩在实验室里看潜水设备，并没有在海里潜水，与句子描述不符。考察知识点：dive（潜水）。"
|
||||
},
|
||||
{
|
||||
"question": "The adventure is on TV.",
|
||||
"answerText": "No",
|
||||
"explanation": "图中实验室里没有电视，探险装备是实物放在桌上，不在电视上。考察知识点：adventure（探险/冒险）。"
|
||||
},
|
||||
]
|
||||
}
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def build_json(question_set_id, data):
|
||||
"""Build the full JSON structure for one questionSetID."""
|
||||
result = {
|
||||
"first": {
|
||||
"category": "reading",
|
||||
"type": "reading_pic_qa",
|
||||
"questionSetID": question_set_id,
|
||||
"textTitle": TEXT_TITLE,
|
||||
"textImage": data["first"]["textImage"],
|
||||
"questionSet": [
|
||||
{
|
||||
"question": q["question"],
|
||||
"answerText": q["answerText"],
|
||||
"ability": ["图文判断", "句图一致性"],
|
||||
"explanation": q["explanation"],
|
||||
}
|
||||
for q in data["first"]["questions"]
|
||||
]
|
||||
},
|
||||
"second": {
|
||||
"category": "reading",
|
||||
"type": "reading_pic_qa",
|
||||
"questionSetID": question_set_id,
|
||||
"textTitle": TEXT_TITLE,
|
||||
"textImage": data["second"]["textImage"],
|
||||
"questionSet": [
|
||||
{
|
||||
"question": q["question"],
|
||||
"answerText": q["answerText"],
|
||||
"ability": ["图文判断", "句图一致性"],
|
||||
"explanation": q["explanation"],
|
||||
}
|
||||
for q in data["second"]["questions"]
|
||||
]
|
||||
}
|
||||
}
|
||||
return result
|
||||
|
||||
|
||||
def get_token():
|
||||
"""Get tenant_access_token from credentials."""
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
import requests
|
||||
resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
return resp.json()["tenant_access_token"]
|
||||
|
||||
|
||||
def create_record(token, question_set_id, json_data):
|
||||
"""Create a record in the bitable."""
|
||||
import requests
|
||||
|
||||
fields = {
|
||||
"题目集合 ID": question_set_id,
|
||||
"jsonData": json.dumps(json_data, ensure_ascii=False),
|
||||
"dataStatus": "0",
|
||||
}
|
||||
|
||||
resp = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
|
||||
headers={
|
||||
"Authorization": f"Bearer {token}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
json={"fields": fields},
|
||||
)
|
||||
return resp.json()
|
||||
|
||||
|
||||
def verify_record(token, record_id):
|
||||
"""Verify a record by reading it back."""
|
||||
import requests
|
||||
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
return resp.json()
|
||||
|
||||
|
||||
def main():
|
||||
token = get_token()
|
||||
|
||||
results = []
|
||||
for qid in sorted(ALL_QUESTIONS.keys()):
|
||||
print(f"\n{'='*60}")
|
||||
print(f"Processing ID: {qid}")
|
||||
print(f"{'='*60}")
|
||||
|
||||
data = ALL_QUESTIONS[qid]
|
||||
json_data = build_json(qid, data)
|
||||
|
||||
# Count Yes/No per 题组
|
||||
for grp_name in ("first", "second"):
|
||||
qs = json_data[grp_name]["questionSet"]
|
||||
yes_count = sum(1 for q in qs if q["answerText"] == "Yes")
|
||||
no_count = sum(1 for q in qs if q["answerText"] == "No")
|
||||
print(f" {grp_name}: {yes_count}Y / {no_count}N")
|
||||
|
||||
# Create record
|
||||
resp = create_record(token, qid, json_data)
|
||||
if resp.get("code") != 0:
|
||||
print(f" ❌ 创建失败: {resp.get('msg', resp)}")
|
||||
results.append((qid, "FAIL", resp.get("msg", "")))
|
||||
continue
|
||||
|
||||
record_id = resp["data"]["record"]["record_id"]
|
||||
print(f" ✅ 创建成功, record_id: {record_id}")
|
||||
|
||||
# Verify
|
||||
verify_resp = verify_record(token, record_id)
|
||||
if verify_resp.get("code") != 0:
|
||||
print(f" ⚠️ 回读失败: {verify_resp.get('msg', verify_resp)}")
|
||||
results.append((qid, "CREATED_NO_VERIFY", record_id))
|
||||
continue
|
||||
|
||||
# Check jsonData完整性
|
||||
stored_fields = verify_resp["data"]["record"]["fields"]
|
||||
stored_json = stored_fields.get("jsonData", "")
|
||||
try:
|
||||
parsed = json.loads(stored_json)
|
||||
f_count = len(parsed.get("first", {}).get("questionSet", []))
|
||||
s_count = len(parsed.get("second", {}).get("questionSet", []))
|
||||
print(f" ✅ 回读验证: first={f_count}题, second={s_count}题, jsonData完整")
|
||||
except Exception as e:
|
||||
print(f" ⚠️ 回读JSON解析失败: {e}")
|
||||
|
||||
results.append((qid, "OK", record_id))
|
||||
|
||||
print(f"\n{'='*60}")
|
||||
print(f"汇总")
|
||||
print(f"{'='*60}")
|
||||
for qid, status, detail in results:
|
||||
print(f" {qid}: {status} ({detail})")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
141
scripts/batch_reading_pic_qa_2.py
Normal file
141
scripts/batch_reading_pic_qa_2.py
Normal file
@ -0,0 +1,141 @@
|
||||
#!/usr/bin/env python3
|
||||
"""reading_pic_qa 010701 + 010801, L2 A级"""
|
||||
import json, requests, time
|
||||
|
||||
CRED = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TBL = "tblweY65jGBiwSdt"
|
||||
|
||||
with open(CRED) as f:
|
||||
cred = json.load(f)
|
||||
aid = cred["apps"][0]["appId"]
|
||||
asecret = cred["apps"][0]["appSecret"]
|
||||
|
||||
def get_token():
|
||||
r = requests.post("https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": aid, "app_secret": asecret})
|
||||
return r.json()["tenant_access_token"]
|
||||
|
||||
token = get_token()
|
||||
|
||||
DATA = {
|
||||
"010701": {
|
||||
"first": [
|
||||
("A notebook is on the desk.", "Yes", "桌子上放着一本打开的笔记本，句子描述正确。"),
|
||||
("A star is on the wall.", "Yes", "墙上贴着一颗黄色的星星贴纸，句子描述正确。"),
|
||||
("A folder is under the chair.", "No", "文件夹在桌上，不在椅子下面，句子与图片不匹配。"),
|
||||
("The girl reads a diary.", "Yes", "女孩坐在桌前翻开一本日记在阅读，句子描述正确。"),
|
||||
("The contact list is on the wall.", "No", "联系人列表在电脑屏幕上，不在墙上贴着，句子与图片不匹配。"),
|
||||
],
|
||||
"second": [
|
||||
("A friendly girl gives you a flower.", "Yes", "一个面带微笑的女孩伸手递出一朵花，她很友好，句子描述正确。"),
|
||||
("A crazy boy is jumping on the desk.", "No", "男孩安静地坐在桌前看书，没有在桌上跳，他不疯狂，句子与图片不匹配。"),
|
||||
("A brilliant student has a gold star.", "Yes", "一个学生拿着A+试卷，上面贴着金色星星，她非常优秀，句子描述正确。"),
|
||||
("A kind boy helps his friend.", "Yes", "一个男孩蹲下帮另一个孩子捡起掉在地上的书，他很善良，句子描述正确。"),
|
||||
("The little girl is afraid of the dog.", "No", "小女孩开心地摸着小狗的头，她并不害怕，句子与图片不匹配。"),
|
||||
],
|
||||
},
|
||||
"010801": {
|
||||
"first": [
|
||||
("Uncle is reading a newspaper.", "Yes", "叔叔坐在沙发上展开一份报纸在读，句子描述正确。"),
|
||||
("Aunt is cooking in the kitchen.", "No", "阿姨坐在沙发上织毛衣，不在厨房做饭，句子与图片不匹配。"),
|
||||
("Grandma is sitting in an armchair.", "Yes", "奶奶坐在一张扶手椅上，腿上盖着毯子，句子描述正确。"),
|
||||
("The neighbour is at the door.", "No", "门口没有邻居，只有一只宠物狗趴在地板上，句子与图片不匹配。"),
|
||||
("A pet dog is sleeping on the floor.", "Yes", "一只宠物狗趴在客厅地板上闭着眼睛睡觉，句子描述正确。"),
|
||||
],
|
||||
"second": [
|
||||
("The house looks expensive.", "Yes", "房子外观很大气，花园整洁，有雕花栏杆，看起来很贵，句子描述正确。"),
|
||||
("A boy is at the entrance.", "Yes", "男孩站在房子大门口（入口处），正按门铃，句子描述正确。"),
|
||||
("A cat is walking upstairs.", "No", "小猫正在沿着楼梯往下走（downstairs），不是往上走（upstairs），句子与图片不匹配。"),
|
||||
("A girl is running downstairs.", "Yes", "一个女孩正从楼梯上跑下来，头发飘起，句子描述正确。"),
|
||||
("Mum is making toast in the kitchen.", "No", "妈妈在客厅窗边看书，不在厨房做吐司，句子与图片不匹配。"),
|
||||
],
|
||||
},
|
||||
}
|
||||
|
||||
TT = "Look and read. Put a tick (Yes) or a cross (No) in the box."
|
||||
AB = ["图文判断", "句图一致性"]
|
||||
|
||||
def build(qid, grp_name, questions):
|
||||
return {
|
||||
"category": "reading",
|
||||
"type": "reading_pic_qa",
|
||||
"questionSetID": qid,
|
||||
"textTitle": TT,
|
||||
"textImage": f"{qid}-{'00' if grp_name=='first' else '01'}.png",
|
||||
"questionSet": [
|
||||
{"question": q, "answerText": a, "ability": AB, "explanation": x}
|
||||
for q, a, x in questions
|
||||
],
|
||||
}
|
||||
|
||||
def build_full(qid):
|
||||
return {
|
||||
"first": build(qid, "first", DATA[qid]["first"]),
|
||||
"second": build(qid, "second", DATA[qid]["second"]),
|
||||
}
|
||||
|
||||
# Delete existing
|
||||
print("=== Clean ===")
|
||||
resp = requests.get(f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN}/tables/{TBL}/records?page_size=20",
|
||||
headers={"Authorization": f"Bearer {token}"})
|
||||
for item in resp.json()["data"]["items"]:
|
||||
fid = item["fields"].get("题目集合 ID", "")
|
||||
if fid in DATA:
|
||||
requests.delete(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN}/tables/{TBL}/records/{item['record_id']}",
|
||||
headers={"Authorization": f"Bearer {token}"})
|
||||
print(f" Deleted {fid}")
|
||||
|
||||
time.sleep(2)
|
||||
|
||||
# Create empty
|
||||
print("\n=== Create ===")
|
||||
rids = {}
|
||||
for qid in sorted(DATA):
|
||||
r = requests.post(f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN}/tables/{TBL}/records",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"题目集合 ID": qid, "dataStatus": "0"}})
|
||||
rid = r.json()["data"]["record"]["record_id"]
|
||||
rids[qid] = rid
|
||||
print(f" {qid}: {rid}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# Wait for automation
|
||||
print("\n=== Wait 30s ===")
|
||||
time.sleep(30)
|
||||
|
||||
# Update with jsonData
|
||||
print("\n=== Update ===")
|
||||
token = get_token()
|
||||
for qid in sorted(rids):
|
||||
j = build_full(qid)
|
||||
js = json.dumps(j, ensure_ascii=False)
|
||||
fy = sum(1 for q in j["first"]["questionSet"] if q["answerText"] == "Yes")
|
||||
fn = 5 - fy
|
||||
print(f" {qid}: first={fy}Y/{fn}N, json={len(js)}chars")
|
||||
r = requests.put(f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN}/tables/{TBL}/records/{rids[qid]}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"jsonData": js}})
|
||||
print(f" update code={r.json().get('code')}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# Wait & verify
|
||||
print("\n=== Wait 30s ===")
|
||||
time.sleep(30)
|
||||
|
||||
token = get_token()
|
||||
print("\n=== Verify ===")
|
||||
for qid in sorted(rids):
|
||||
r = requests.get(f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN}/tables/{TBL}/records/{rids[qid]}",
|
||||
headers={"Authorization": f"Bearer {token}"})
|
||||
jd = r.json()["data"]["record"]["fields"].get("jsonData", "")
|
||||
try:
|
||||
j = json.loads(jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
q1 = j["first"]["questionSet"][0]["question"][:50]
|
||||
print(f" {'✅' if fq==5 and sq==5 else '❌'} {qid}: {fq}/{sq}q Q1='{q1}'")
|
||||
except Exception as e:
|
||||
print(f" ❌ {qid}: {e}")
|
||||
print("Done.")
|
||||
80
scripts/test_one_record.py
Normal file
80
scripts/test_one_record.py
Normal file
@ -0,0 +1,80 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Create ONE reading_pic_qa record with immediate verification."""
|
||||
import json, requests, sys
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt"
|
||||
|
||||
sys.path.insert(0, '/root/.openclaw/workspace-xiaoyan')
|
||||
from scripts.batch_reading_pic_qa import ALL_QUESTIONS, build_json
|
||||
|
||||
qid = "000001"
|
||||
json_data = build_json(qid, ALL_QUESTIONS[qid])
|
||||
json_str = json.dumps(json_data, ensure_ascii=False)
|
||||
print(f"jsonData size: {len(json_str)} chars")
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
# Create record
|
||||
fields = {
|
||||
"题目集合 ID": qid,
|
||||
"jsonData": json_str,
|
||||
"dataStatus": "0",
|
||||
}
|
||||
|
||||
print(f"\n=== Creating record ===")
|
||||
resp = requests.post(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
|
||||
headers={
|
||||
"Authorization": f"Bearer {token}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
json={"fields": fields},
|
||||
)
|
||||
result = resp.json()
|
||||
print(f"Create response code: {result.get('code')}")
|
||||
|
||||
if result.get("code") != 0:
|
||||
print(f"ERROR: {result}")
|
||||
sys.exit(1)
|
||||
|
||||
record_id = result["data"]["record"]["record_id"]
|
||||
print(f"record_id: {record_id}")
|
||||
|
||||
# Read back immediately
|
||||
print(f"\n=== Reading back ===")
|
||||
resp2 = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
data2 = resp2.json()
|
||||
stored_jd = data2["data"]["record"]["fields"].get("jsonData", "")
|
||||
print(f"Stored jsonData size: {len(stored_jd)} chars")
|
||||
|
||||
if len(stored_jd) < 100:
|
||||
print(f"TRUNCATED! Content: {repr(stored_jd)}")
|
||||
# Delete it
|
||||
requests.delete(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
else:
|
||||
# Verify content
|
||||
try:
|
||||
j = json.loads(stored_jd)
|
||||
fq = len(j["first"]["questionSet"])
|
||||
sq = len(j["second"]["questionSet"])
|
||||
print(f"✅ OK: first={fq} questions, second={sq} questions")
|
||||
except Exception as e:
|
||||
print(f"Parse error: {e}")
|
||||
print(f"First 200 chars: {stored_jd[:200]}")
|
||||
185
scripts/update_image_descriptions.py
Normal file
185
scripts/update_image_descriptions.py
Normal file
@ -0,0 +1,185 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Update 图片描述 field for reading_pic_qa records."""
|
||||
import json, requests, time
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt"
|
||||
|
||||
IMAGE_DESCRIPTIONS = {
|
||||
"recvjhhtWLApoW": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：儿童卧室早晨，阳光从窗户照进来
|
||||
穿睡衣的小男孩 - 站在窗前往外看，窗外有树和小鸟 ；
|
||||
同一个穿睡衣的小男孩 - 跪在床前地板上，从床底下伸手找到一只红色皮球，脸上表情惊喜 ；
|
||||
同一个男孩 - 从地板上弯腰捡起一只蓝白条纹袜子 ；
|
||||
穿好外出衣服的小男孩 - 坐在床边正穿一只蓝色运动鞋，另一只已穿好 ；
|
||||
背书包的小男孩 - 在房间门口停下脚步回头看向房间，面带微笑。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外游乐场攀爬区，有彩色攀爬架、滑梯、秋千
|
||||
戴蓝色头盔的小男孩 - 双手系紧头盔下巴带子，站在攀爬架旁 ；
|
||||
扎马尾穿粉色运动服的女孩 - 在攀爬架高处双手解开安全绳 ；
|
||||
攀爬架旁立着黄色安全警示牌（感叹号标志），地面铺彩色防护软垫 ；
|
||||
穿红色外套的女教练 - 蹲在攀爬架旁指导男孩攀爬 ；
|
||||
戴海盗帽和黑色眼罩的男孩 - 举着玩具剑站在攀爬架平台，做夸张海盗表情。""",
|
||||
|
||||
"recvjhhurtvJRc": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：温馨餐厅内，靠窗的餐桌，阳光明媚
|
||||
桌上白色盘子里 - 放着一块金黄烤鸡肉 ；
|
||||
扎双马尾的小女孩 - 坐在餐桌旁，双手捧着一本打开的菜单在看 ；
|
||||
戴白色高厨师帽的厨师 - 在开放式厨房灶台前翻动平底锅里的牛排，穿着白色围裙 ；
|
||||
同一张餐桌上 - 另一个盘子里放着一块煎好的牛排，旁边配蔬菜 ；
|
||||
戴白色高厨师帽的厨师 - 头戴白色厨师帽，面带微笑。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：菜市场蔬菜摊位，木制摊位上摆满各种蔬菜
|
||||
白色洋葱 - 放在摊位左侧的木篮里 ；
|
||||
黄色咖喱 - 盛在摊位前的小碗里，旁边有标签 ；
|
||||
棕白色蘑菇 - 整齐摆放在摊位的竹篮中 ；
|
||||
白色大蒜 - 串成一串挂在摊位上方 ；
|
||||
红色辣椒 - 堆放在摊位右侧的红色小筐里。""",
|
||||
|
||||
"recvjhhv24p2Pu": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：儿童游戏室，地板上铺着彩色地毯，墙上有时钟和画
|
||||
银灰色卡通机器人 - 站在房间中央，有大大的方脑袋，两只圆圆的眼睛，两条手臂，两条腿 ；
|
||||
同一机器人 - 脑袋特别大，占据了身体三分之一的高度 ；
|
||||
同一机器人 - 两条银色金属腿，每条腿有三个关节 ；
|
||||
同一机器人 - 两条手臂可以弯曲，末端是钳子状抓手 ；
|
||||
同一机器人 - 身体是银灰色的长方体，胸前有闪烁的小灯。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：教室布告栏，绿色布告板挂在墙上，旁边有老师的讲台和学生的课桌
|
||||
墙上布告栏 - 贴着一篇手写的故事，标题彩色大字 ；
|
||||
布告栏上 - 贴着一张彩色大海报，上面画着动物图案 ；
|
||||
教师讲台上 - 放着一份装订好的报告，封面写着"Report" ；
|
||||
墙上布告栏下方 - 贴着一张打印的校园新闻，标题可见"School News" ；
|
||||
布告栏中央 - 贴着一张彩色图画，画的是太阳花。""",
|
||||
|
||||
"recvjhhvB36ro1": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：动物园/野生动物园，有草地、树木、水池
|
||||
一头雄狮 - 金色鬃毛浓密蓬松，站在草地上 ；
|
||||
同一头狮子 - 站在草地中央，周围有其他小动物 ；
|
||||
一棵大树 - 树洞里探出一只棕熊的头和爪子 ；
|
||||
黄色和黑色的蝴蝶 - 停在花丛中的一朵红花上 ；
|
||||
蓝色水池里 - 一条橙色金鱼在游动，水面有波纹。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：自然风景区，有游泳池、湖泊、草地、远处森林
|
||||
蓝色游泳池 - 池水清澈蔚蓝，池边有躺椅和遮阳伞 ；
|
||||
天空晴朗 - 几朵白云，大太阳，空中没有乌云和闪电 ；
|
||||
湖泊 - 在游泳池后方，湖面宽阔，远处有小船 ；
|
||||
大片绿色草地 - 从游泳池边延伸到湖边，草地上有几朵小野花 ；
|
||||
远景 - 大片深绿色森林，树木茂密成片。""",
|
||||
|
||||
"recvjhhwbepReL": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：美术教室，桌上和墙上展示着各种色彩鲜艳的物品
|
||||
桌上放着一顶紫色帽子 - 帽子上有彩色波点装饰 ；
|
||||
桌上花瓶里 - 插着一朵粉色大花，花瓣层层叠叠 ；
|
||||
墙上贴着一幅画 - 画面色彩非常丰富，有红黄蓝绿紫多种颜色 ；
|
||||
桌边放着几把勺子 - 其中一把是木色/米色的，旁边是彩色笔筒 ；
|
||||
桌子中央 - 放着一个装饰特别的生日蛋糕，插着蜡烛，蛋糕上有彩色糖粒。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：果汁店/厨房操作台，桌上摆满各种水果
|
||||
桌上 - 放着一个黄色柠檬，旁边有切开的半个柠檬 ；
|
||||
黄色芒果 - 放在水果篮里，表皮光滑 ；
|
||||
紫色葡萄 - 一串放在白色盘子里 ；
|
||||
同一个柠檬 - 旁边贴着"酸"的标签/符号 ；
|
||||
玻璃杯里 - 装着紫色葡萄汁，不是橙色橙汁，旁边有榨汁机。""",
|
||||
|
||||
"recvjhhwIKni7F": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：公司办公室前台区域，玻璃大门，接待台
|
||||
墙上挂着公司名称牌 - 上面印着公司logo和名称 ；
|
||||
办公桌上 - 放着一张访客登记卡片 ；
|
||||
女性前台接待员 - 坐在接待台后，穿着职业装，戴着耳麦，微笑面对访客 ；
|
||||
小小的单间办公室 - 里面有一张办公桌和电脑，门半开 ；
|
||||
办公室里的会议室 - 椭圆长桌周围坐满了人，有人在白板前讲解。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：现代家庭/公寓内部，多个房间
|
||||
干净整洁的卫生间 - 白色瓷砖墙面，洗手台和镜子 ；
|
||||
墙上 - 靠着一个大书柜，上面整齐排列着各种颜色的书 ；
|
||||
白色马桶 - 在卫生间角落里，旁边有卫生纸架 ；
|
||||
书桌上 - 放着一盏亮着的台灯，灯光照在桌面上 ；
|
||||
书桌上 - 放着一台打开的笔记本电脑，屏幕亮着，鼠标在旁，不是在床上。""",
|
||||
|
||||
"recvjhhxe6QPYd": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：考古挖掘现场/自然博物馆，沙土地面，有围栏
|
||||
一块大石头 - 埋在沙土里半露在外面，上面有纹理 ；
|
||||
巨大的恐龙骨架化石 - 立在场地中央，骨骼巨大清晰可见 ；
|
||||
蔚蓝的天空 - 有几朵白云，阳光明媚，不是阴天灰色 ；
|
||||
一块巨大的岩石 - 竖立在挖掘坑旁边，比人还高 ；
|
||||
沙土地面 - 到处是石头和化石碎片，没有鲜花和绿色植物。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：科学实验室/探险研究基地，墙上贴满图表
|
||||
实验桌上 - 放着扳手、螺丝刀等工具 ；
|
||||
穿白色实验服的科学家 - 戴着护目镜，站在实验台前做实验 ；
|
||||
透明玻璃罐里 - 浸泡着一个大脑模型，放在架子上 ；
|
||||
墙上贴着潜水海报 - 海报里有人在海里潜水，实验室里的男孩指着海报看，男孩本人不在海里 ；
|
||||
实验室内 - 地上放着探险设备（背包、绳索、指南针等），没有电视，实验室门上有"Adventure Lab"标志。""",
|
||||
}
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
results = {}
|
||||
for record_id, desc in IMAGE_DESCRIPTIONS.items():
|
||||
print(f"Updating {record_id}...")
|
||||
resp = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"图片描述": desc}},
|
||||
)
|
||||
code = resp.json().get("code")
|
||||
print(f" code={code}")
|
||||
results[record_id] = code
|
||||
time.sleep(0.5)
|
||||
|
||||
# Verify
|
||||
print("\n=== Verification ===")
|
||||
for record_id in IMAGE_DESCRIPTIONS:
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{record_id}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
img_desc = resp.json()["data"]["record"]["fields"].get("图片描述", "")
|
||||
print(f" {record_id}: 图片描述={len(img_desc)} chars {'✅' if len(img_desc) > 100 else '❌ EMPTY'}")
|
||||
|
||||
print("\nDone.")
|
||||
193
scripts/update_l2_difficulty_skills.py
Normal file
193
scripts/update_l2_difficulty_skills.py
Normal file
@ -0,0 +1,193 @@
|
||||
#!/usr/bin/env python3
|
||||
"""批量更新 L2 和共用题型 SKILL.md 中的难度对应关系表"""
|
||||
|
||||
import os
|
||||
import re
|
||||
|
||||
BASE = "/root/.openclaw/workspace-xiaoyan/business_production/单元挑战/skills/unit_challenge/questions"
|
||||
|
||||
# New L2 8-stage difficulty table
|
||||
L2_NEW_TABLE = """## 难度对应关系（与教研标准对齐）
|
||||
| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |
|
||||
|------|---------|---------|------|
|
||||
"""
|
||||
|
||||
# Store the A/B/C/D rows with the new mapping - 通用声明式,实际难度描述(最后一列)保留原样
|
||||
L2_NEW_HEADER = "| 难度等级 | 对应L2阶段（Unit范围） | 对标说明 | 难度描述 |"
|
||||
|
||||
# Maps for old->new grade columns
|
||||
L2_GRADE_MAP = {
|
||||
"A级": "| A级 | U1-U12（阶段1-2） | Flyers入门→基础 |",
|
||||
"B级": "| B级 | U13-U24（阶段3-4） | Flyers达标→KET入门 |",
|
||||
"C级": "| C级 | U25-U36（阶段5-6） | KET基础→强化 |",
|
||||
"D级": "| D级 | U37-U48（阶段7-8） | KET高位→达标 |",
|
||||
}
|
||||
|
||||
def update_l2_exclusive(filepath):
|
||||
"""Update L2专属题型: replace entire difficulty table with 8-stage version"""
|
||||
with open(filepath, 'r', encoding='utf-8') as f:
|
||||
content = f.read()
|
||||
|
||||
original = content
|
||||
|
||||
# ---- Part 1: Replace the difficulty table ----
|
||||
# Find the section from "## 难度对应关系" to next heading/separator
|
||||
pattern = r'(## 难度对应关系.*?\n)\| 难度等级 \|.*?\n\|[-|\s]*\n((?:\| [ABCD]级 \|.*?\n)+)'
|
||||
|
||||
def replace_table(match):
|
||||
section_title = match.group(1)
|
||||
old_rows = match.group(2)
|
||||
|
||||
new_rows = []
|
||||
for old_row in old_rows.strip().split('\n'):
|
||||
# Extract the last column (难度描述) from old row
|
||||
parts = old_row.split('|')
|
||||
if len(parts) >= 4:
|
||||
desc = parts[-2].strip() if len(parts) > 4 else parts[-1].strip()
|
||||
# Determine which grade
|
||||
for grade, new_prefix in L2_GRADE_MAP.items():
|
||||
if grade in old_row:
|
||||
new_rows.append(f"{new_prefix} {desc} |")
|
||||
break
|
||||
else:
|
||||
new_rows.append(old_row)
|
||||
|
||||
return section_title + L2_NEW_HEADER + '\n' + '\n'.join(new_rows) + '\n'
|
||||
|
||||
content = re.sub(pattern, replace_table, content, flags=re.DOTALL)
|
||||
|
||||
# ---- Part 2: Update config field description for 难度等级 ----
|
||||
# Pattern: | 难度等级 | ✅ | `A级` / `...` / `...` | ... |
|
||||
# Replace with new references
|
||||
def replace_config(match):
|
||||
full_line = match.group(0)
|
||||
# Replace old stage/cambridge refs with new ones
|
||||
new_line = re.sub(
|
||||
r'`[ABCD]级` / `(?:L[12])(?:第)?[\d-]+阶段` / `(?:Starters|Movers|Flyers)[\s\d-]*`',
|
||||
lambda m: m.group(0).replace(
|
||||
m.group(0),
|
||||
re.sub(
|
||||
r'`([ABCD]级)` / `.*?` / `.*?`',
|
||||
lambda g: {
|
||||
'A级': '`A级` / `U1-U12（阶段1-2）` / `Flyers入门→基础`',
|
||||
'B级': '`B级` / `U13-U24（阶段3-4）` / `Flyers达标→KET入门`',
|
||||
'C级': '`C级` / `U25-U36（阶段5-6）` / `KET基础→强化`',
|
||||
'D级': '`D级` / `U37-U48（阶段7-8）` / `KET高位→达标`',
|
||||
}[g.group(1)],
|
||||
m.group(0)
|
||||
)
|
||||
),
|
||||
full_line
|
||||
)
|
||||
# Also update the note column
|
||||
new_line = new_line.replace('难度等级或对应阶段', '难度等级（L2用Unit范围）')
|
||||
return new_line
|
||||
|
||||
content = re.sub(
|
||||
r'\| 难度等级 \| ✅ \|.*?\|.*?\|',
|
||||
replace_config,
|
||||
content
|
||||
)
|
||||
|
||||
if content != original:
|
||||
with open(filepath, 'w', encoding='utf-8') as f:
|
||||
f.write(content)
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def update_common(filepath):
|
||||
"""Update L1&L2共用题型: add L2 dimension after L1 table"""
|
||||
with open(filepath, 'r', encoding='utf-8') as f:
|
||||
content = f.read()
|
||||
|
||||
original = content
|
||||
|
||||
# Check if already has L2 dimension
|
||||
if 'L2 维度' in content or 'L2阶段（Unit范围）' in content:
|
||||
return False
|
||||
|
||||
# Find end of L1 difficulty table (## 难度对应关系 ... through last D级 row)
|
||||
pattern = r'(## 难度对应关系.*?\n(?:\| .*?\n)*)'
|
||||
|
||||
def add_l2_dimension(match):
|
||||
table_block = match.group(1)
|
||||
l2_note = (
|
||||
"\n> **L2 难度维度（对标 Flyers/KET，每2阶段为1个难度等级）：**\n"
|
||||
"> - A级 = U1-U12（阶段1-2）：Flyers入门→Flyers基础\n"
|
||||
"> - B级 = U13-U24（阶段3-4）：Flyers达标→KET入门\n"
|
||||
"> - C级 = U25-U36（阶段5-6）：KET基础→KET强化\n"
|
||||
"> - D级 = U37-U48（阶段7-8）：KET高位→KET达标\n"
|
||||
)
|
||||
return table_block + l2_note
|
||||
|
||||
content = re.sub(pattern, add_l2_dimension, content, flags=re.DOTALL)
|
||||
|
||||
# Also update config row if it references Starters/Movers
|
||||
content = re.sub(
|
||||
r'\| 难度等级 \| ✅ \|.*?\| 难度等级或对应阶段 \|',
|
||||
lambda m: m.group(0).replace('难度等级或对应阶段', '难度等级（L1用Starters/Movers，L2用Unit范围）'),
|
||||
content
|
||||
)
|
||||
|
||||
if content != original:
|
||||
with open(filepath, 'w', encoding='utf-8') as f:
|
||||
f.write(content)
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def main():
|
||||
L2_FILES = [
|
||||
"listening/L2/listening_short_conversation/SKILL.md",
|
||||
"listening/L2/listening_long_conversation/SKILL.md",
|
||||
"listening/L2/listening_form_fill/SKILL.md",
|
||||
"listening/L2/listening-choicePic/SKILL.md",
|
||||
"listening/L2/listening_info_match/SKILL.md",
|
||||
"reading/reading_info_match/SKILL.md",
|
||||
"reading/reading_paragraph_match/SKILL.md",
|
||||
"reading/reading_long_passage/SKILL.md",
|
||||
"reading/reading_cloze/SKILL.md",
|
||||
"reading/reading_open_fill/SKILL.md",
|
||||
"writing/writing_email_reply/SKILL.md",
|
||||
"writing/writing_picture_writing/SKILL.md",
|
||||
"speaking/L2/speaking_topic_discussion/SKILL.md",
|
||||
]
|
||||
|
||||
COMMON_FILES = [
|
||||
"reading/common/reading_pic_qa/SKILL.md",
|
||||
"reading/common/reading_pic_judge/SKILL.md",
|
||||
"speaking/common/speaking_daily_qa/SKILL.md",
|
||||
"writing/common/writing_pic_qa/SKILL.md",
|
||||
]
|
||||
|
||||
updated = 0
|
||||
|
||||
print("=== L2 专属题型 ===")
|
||||
for rel_path in L2_FILES:
|
||||
full = os.path.join(BASE, rel_path)
|
||||
if not os.path.exists(full):
|
||||
print(f" [MISS] {rel_path}")
|
||||
continue
|
||||
if update_l2_exclusive(full):
|
||||
print(f" [OK] {rel_path}")
|
||||
updated += 1
|
||||
else:
|
||||
print(f" [NO CHANGE] {rel_path}")
|
||||
|
||||
print("\n=== L1&L2 共用题型 ===")
|
||||
for rel_path in COMMON_FILES:
|
||||
full = os.path.join(BASE, rel_path)
|
||||
if not os.path.exists(full):
|
||||
print(f" [MISS] {rel_path}")
|
||||
continue
|
||||
if update_common(full):
|
||||
print(f" [OK] {rel_path}")
|
||||
updated += 1
|
||||
else:
|
||||
print(f" [NO CHANGE] {rel_path}")
|
||||
|
||||
print(f"\n=== Done: {updated} files updated ===")
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
285
scripts/update_pic_judge_descriptions.py
Normal file
285
scripts/update_pic_judge_descriptions.py
Normal file
@ -0,0 +1,285 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Update 图片描述 for reading_pic_judge records."""
|
||||
import json, requests, time
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblJc60aO0T163MJ"
|
||||
|
||||
IMAGE_DESC = {
|
||||
# ---- 121301 ----
|
||||
"recvj5nIAxF3XG": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：住宅街道，阳光下三栋彩色小房子并排而立
|
||||
三栋卡通房子 - 黄色屋顶、红色屋顶、蓝色屋顶，并排站着，前面有小路和花草。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：厨房一角
|
||||
棕色木质橱柜 - 靠着墙，柜子上放着几个盘子，柜门半开能看到里面的杯子。
|
||||
|
||||
3.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：客厅一角
|
||||
一张大沙发 - 蓝色软沙发，沙发上有两个彩色靠垫，沙发前有小茶几。
|
||||
|
||||
4.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室
|
||||
一间卧室 - 里面有粉色小床、床头柜，墙上有时钟和画，地板上铺着地毯。
|
||||
|
||||
5.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室
|
||||
一张小床 - 粉色小床上有枕头和被子，床头柜上放着一盏台灯，房间墙上贴着星星贴纸。
|
||||
|
||||
6.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：动物园门口
|
||||
动物园入口 - 大拱门上写着"ZOO"，门外能看到长颈鹿和狮子在围栏里。
|
||||
|
||||
7.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：动物园水池
|
||||
河马 - 一只胖胖的河马泡在浅蓝色的水池里，只露出头和两只小耳朵，旁边有水草。
|
||||
|
||||
8.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室衣柜前
|
||||
牛仔裤 - 一条蓝色牛仔裤叠放在椅子上。
|
||||
|
||||
9.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室衣柜前
|
||||
牛仔裤 - 一条蓝色牛仔裤挂在衣架上。
|
||||
|
||||
10.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：森林里
|
||||
大棕熊 - 一只棕色大熊站在绿色森林中，旁边有大树。""",
|
||||
|
||||
# ---- 121401 ----
|
||||
"recvj5nJG33bBE": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：小学教室
|
||||
学生们 - 三个穿校服的小学生坐在课桌前，女孩扎着马尾，男孩短发，每人桌上放着课本。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：学校外观
|
||||
学校建筑 - 一栋红色砖墙的学校大楼，楼顶有国旗飘动，大门敞开，门口有"School"标牌。
|
||||
|
||||
3.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：美术课桌面
|
||||
蜡笔 - 桌上散落着红黄蓝绿紫五支彩色蜡笔。
|
||||
|
||||
4.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：美术课桌面
|
||||
蜡笔 - 红黄蓝绿四支蜡笔整齐排放在白纸上。
|
||||
|
||||
5.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：教室
|
||||
女老师 - 穿着裙子的女老师站在讲台前，手里拿着粉笔，身后的黑板上写着字母。
|
||||
|
||||
6.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：儿童卧室地面
|
||||
垫子 - 一张彩色图案的方形游戏垫铺在地板上，垫子旁边散放着积木玩具。
|
||||
|
||||
7.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：儿童卧室
|
||||
课桌 - 一张木色小课桌，桌上有台灯、铅笔筒和一本打开的书。
|
||||
|
||||
8.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：衣帽间
|
||||
手提包 - 一个红色女士手提包挂在挂钩上，包上有金色扣子。
|
||||
|
||||
9.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室门口
|
||||
书包 - 一个蓝色卡通书包靠在门边。
|
||||
|
||||
10.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：衣帽间
|
||||
手提包 - 一个红色手提包放在白色架子上。""",
|
||||
|
||||
# ---- 121501 ----
|
||||
"recvj5nKxhm8X6": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：白色背景前
|
||||
小男孩全身 - 一个穿红色T恤和蓝色短裤的男孩，从头到脚完整站立，双臂自然下垂。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：白色背景前
|
||||
嘴的特写 - 一张微笑的嘴，上下两排白色牙齿，嘴唇粉色。
|
||||
|
||||
3.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：公园草地上
|
||||
两个小朋友 - 男孩和女孩在草地上一起玩球，两人都笑得很开心。
|
||||
|
||||
4.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：白色背景前
|
||||
耳朵的特写 - 一只人的耳朵，耳廓清晰可见。
|
||||
|
||||
5.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：公园
|
||||
两个小朋友 - 一个男孩和一个女孩手牵手站在树下，两人微笑着看向前方。
|
||||
|
||||
6.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：白色背景前
|
||||
相机 - 一台黑色单反相机，镜头朝前，闪光灯在顶部。
|
||||
|
||||
7.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：公园
|
||||
小男孩 - 一个戴棒球帽的男孩，穿着条纹T恤和短裤，站在草地上微笑。
|
||||
|
||||
8.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：背景前
|
||||
滑板 - 一个蓝色滑板平放在地上，侧面有火焰图案。
|
||||
|
||||
9.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外滑板场
|
||||
女孩滑滑板 - 一个扎马尾的女孩踩在滑板上滑行，滑板在脚下。
|
||||
|
||||
10.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：背景前
|
||||
滑板 - 一个蓝色带火焰图案的滑板平放在地面。""",
|
||||
|
||||
# ---- 121601 ----
|
||||
"recvj5nLUpubaU": """1.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：海滩
|
||||
夏天 - 金色沙滩上有一把遮阳伞，蓝色大海远处有小帆船，天空挂着大太阳。
|
||||
|
||||
2.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外
|
||||
冬天雪景 - 白色雪覆盖地面和房屋屋顶，树木光秃秃的没有树叶，空中飘着雪花。
|
||||
|
||||
3.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外
|
||||
冬天雪景 - 一个雪人戴着帽子和围巾站在雪地里，房屋和树上都覆盖着白雪。
|
||||
|
||||
4.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：冬天户外
|
||||
穿厚棉衣的男孩 - 一个男孩穿着厚厚的外套，戴着围巾和手套，嘴里呼出白气，背景是雪地。
|
||||
|
||||
5.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外
|
||||
秋天 - 橙色和黄色的落叶铺满地面，树木只剩下稀疏的叶子，天空有一群飞鸟。
|
||||
|
||||
6.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：马路上
|
||||
公交车 - 一辆红色双层公交车停在路边，有窗户和车门。
|
||||
|
||||
7.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室
|
||||
长裤 - 一条蓝色长裤叠放在床边的凳子上。
|
||||
|
||||
8.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：卧室
|
||||
长裤 - 一条深蓝色长裤挂在衣架上。
|
||||
|
||||
9.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外
|
||||
下雪 - 白色雪花从天空中纷纷落下，地面和房屋屋顶积了厚厚一层雪。
|
||||
|
||||
10.
|
||||
|
||||
风格: 卡通，简单线条
|
||||
场景：户外
|
||||
雪地 - 白色雪覆盖了整个地面，空中飘着雪花，远处有积雪覆盖的屋顶。""",
|
||||
}
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
for rid, desc in IMAGE_DESC.items():
|
||||
resp = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"图片描述": desc}},
|
||||
)
|
||||
code = resp.json().get("code")
|
||||
print(f" {rid}: code={code}, desc_len={len(desc)}")
|
||||
time.sleep(0.5)
|
||||
|
||||
# Verify
|
||||
print("\nVerification:")
|
||||
for rid in IMAGE_DESC:
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
desc_len = len(resp.json()["data"]["record"]["fields"].get("图片描述", ""))
|
||||
print(f" {rid}: 图片描述={desc_len}chars {'✅' if desc_len > 100 else '❌'}")
|
||||
print("\nDone.")
|
||||
173
scripts/update_speaking_qa_ability.py
Normal file
173
scripts/update_speaking_qa_ability.py
Normal file
@ -0,0 +1,173 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Update ability labels for speaking_qa records based on question content."""
|
||||
import json, requests, time
|
||||
|
||||
CRED = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
TOKEN_APP = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TBL = "tblRGv7k4WH58Jgq"
|
||||
|
||||
L_INFO = "基础信息表达｜个人信息问答"
|
||||
L_PREF = "表达喜好与理由"
|
||||
L_PAST = "过去经历描述｜Past Activities"
|
||||
L_INTR = "互动应答｜问答交流"
|
||||
L_EXCH = "信息交换｜双向问答"
|
||||
|
||||
def classify(question):
|
||||
q = question.lower()
|
||||
|
||||
# 互动应答
|
||||
if any(kw in q for kw in ["what do you say", "what will you say", "what would you say",
|
||||
"what shouldn't we do", "what must we not do", "what should we do",
|
||||
"what do we do next", "what do the shop workers say"]):
|
||||
return L_INTR
|
||||
|
||||
# 过去经历描述
|
||||
if any(kw in q for kw in ["what did you", "when did you last", "who did you help",
|
||||
"last weekend", "what have you learned", "what have you decided",
|
||||
"what toy did you buy", "where did you meet",
|
||||
"what did your father say", "what did you first find",
|
||||
"what gift have you got", "what did you see",
|
||||
"what you're glad you could do"]):
|
||||
return L_PAST
|
||||
|
||||
# 信息交换
|
||||
if any(kw in q for kw in ["what do we need", "what things are there",
|
||||
"what will your friends bring", "what do people use",
|
||||
"what do we use", "what shall we", "whose bag",
|
||||
"whose schoolbag", "whose pen is this", "who is this gift for"]):
|
||||
return L_EXCH
|
||||
|
||||
# 个人信息: name, age, from, family, appearance
|
||||
if any(kw in q for kw in ["what's your name", "how old", "where are you from",
|
||||
"who do you live", "is your home in", "what rooms",
|
||||
"what does your dad look like", "what does your mother look like",
|
||||
"what is your mom's hair", "what are your mom's",
|
||||
"what does your sister wear", "what does a dinosaur look like",
|
||||
"what do the clouds look like", "what is the moon like",
|
||||
"what's your best friend like", "what does your cat look like",
|
||||
"how is the bear", "who is your best", "who is taller",
|
||||
"what are you good at", "what is your best friend good at",
|
||||
"what is your main study goal", "what is your goal",
|
||||
"what habit is very important", "what information",
|
||||
"what do you have to do every day",
|
||||
"tell me what you're glad", "please introduce your pet",
|
||||
"what pet do you love", "any animals. which one",
|
||||
"what toys do you have", "how many books does your dad have",
|
||||
"what is in your schoolbag", "what's in your schoolbag",
|
||||
"what can you find", "what is there in your schoolbag",
|
||||
"what is in your classroom", "what are in the classroom"]):
|
||||
return L_INFO
|
||||
|
||||
# 信息交换 fallback
|
||||
if any(kw in q for kw in ["where is your book", "is this pen yours", "where are your books",
|
||||
"which page", "where should you put", "can you swim",
|
||||
"is there a book", "can you help me", "what do you say to make",
|
||||
"what do you say when others", "what do you say when your friend",
|
||||
"what do you say when you want", "what do you say to draw",
|
||||
"what do you say to introduce"]):
|
||||
return L_INTR
|
||||
|
||||
# 表达喜好
|
||||
if any(kw in q for kw in ["favorite", "favourite", "what do you like", "what kind of",
|
||||
"what do you think", "what do you want", "do you like",
|
||||
"what do you enjoy", "what books do you", "do you keep",
|
||||
"are your classmates", "are you afraid",
|
||||
"what do your family plan", "what do your parents plan",
|
||||
"what do you plan", "what are you going to",
|
||||
"what will you", "what would you", "what can you do",
|
||||
"how do you like", "what colour do you like", "what colour do you want",
|
||||
"what gift do you want", "what do you want to eat", "why do you like",
|
||||
"which car is faster", "what sport can't you do",
|
||||
"what can you see", "who will you sit with",
|
||||
"how is the ice cream", "what animal might it be",
|
||||
"what is the rabbit eating", "what is the bird",
|
||||
"what do you need", "what will we have at the party",
|
||||
"what must we protect", "what do you believe",
|
||||
"what makes your dad unhappy", "what do your friends",
|
||||
"whose pen do you think", "what hair has your dad",
|
||||
"what sports can you do", "what do you need for",
|
||||
"if you can't find", "where will we go", "what do people use",
|
||||
"the radio has no sound", "what do you need to do"]):
|
||||
return L_PREF
|
||||
|
||||
return L_INFO
|
||||
|
||||
# Main
|
||||
with open(CRED) as f:
|
||||
cred = json.load(f)
|
||||
aid = cred["apps"][0]["appId"]
|
||||
asecret = cred["apps"][0]["appSecret"]
|
||||
|
||||
def get_token():
|
||||
r = requests.post("https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": aid, "app_secret": asecret})
|
||||
return r.json()["tenant_access_token"]
|
||||
|
||||
token = get_token()
|
||||
|
||||
all_items = []
|
||||
page_token = None
|
||||
while True:
|
||||
url = f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records?page_size=50"
|
||||
if page_token:
|
||||
url += f"&page_token={page_token}"
|
||||
resp = requests.get(url, headers={"Authorization": f"Bearer {token}"})
|
||||
data = resp.json()
|
||||
all_items.extend(data["data"].get("items", []))
|
||||
if not data["data"].get("has_more"):
|
||||
break
|
||||
page_token = data["data"].get("page_token")
|
||||
|
||||
updates = 0
|
||||
stats = {}
|
||||
for item in all_items:
|
||||
rid = item["record_id"]
|
||||
r = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}"})
|
||||
fields = r.json()["data"]["record"]["fields"]
|
||||
fid = fields.get("题目集合 ID", "")
|
||||
jd = fields.get("jsonData", "")
|
||||
|
||||
if not jd or fid in ("L1", "L2", None):
|
||||
continue
|
||||
|
||||
try:
|
||||
j = json.loads(jd)
|
||||
except:
|
||||
continue
|
||||
|
||||
changed = False
|
||||
for grp_name in ["first", "second"]:
|
||||
if grp_name not in j:
|
||||
continue
|
||||
for q in j[grp_name].get("questionSet", []):
|
||||
existing = q.get("ability", [])
|
||||
valid_labels = {L_INFO, L_PREF, L_PAST, L_INTR, L_EXCH}
|
||||
if existing and all(a in valid_labels for a in existing):
|
||||
continue
|
||||
|
||||
content = q.get("content", q.get("question", ""))
|
||||
label = classify(content)
|
||||
q["ability"] = [label]
|
||||
changed = True
|
||||
stats[label] = stats.get(label, 0) + 1
|
||||
|
||||
if changed:
|
||||
new_jd = json.dumps(j, ensure_ascii=False)
|
||||
r = requests.put(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{TOKEN_APP}/tables/{TBL}/records/{rid}",
|
||||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||||
json={"fields": {"jsonData": new_jd}})
|
||||
code = r.json().get("code")
|
||||
if code == 0:
|
||||
updates += 1
|
||||
print(f"✅ {fid}: updated")
|
||||
else:
|
||||
print(f"❌ {fid}: code={code}")
|
||||
time.sleep(0.3)
|
||||
|
||||
print(f"\nUpdated {updates} records")
|
||||
print("\nLabel distribution:")
|
||||
for label, count in sorted(stats.items(), key=lambda x: -x[1]):
|
||||
print(f" {label}: {count}")
|
||||
38
scripts/verify_record.py
Normal file
38
scripts/verify_record.py
Normal file
@ -0,0 +1,38 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Verify a single bitable record."""
|
||||
import json, requests, sys
|
||||
|
||||
CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
|
||||
APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
|
||||
TABLE_ID = "tblweY65jGBiwSdt"
|
||||
RECORD_ID = sys.argv[1] if len(sys.argv) > 1 else "recvjhdXiBCoE4"
|
||||
|
||||
with open(CRED_FILE) as f:
|
||||
cred = json.load(f)
|
||||
app_id = cred["apps"][0]["appId"]
|
||||
app_secret = cred["apps"][0]["appSecret"]
|
||||
|
||||
token_resp = requests.post(
|
||||
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
|
||||
json={"app_id": app_id, "app_secret": app_secret},
|
||||
)
|
||||
token = token_resp.json()["tenant_access_token"]
|
||||
|
||||
resp = requests.get(
|
||||
f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{RECORD_ID}",
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
data = resp.json()
|
||||
jd = data["data"]["record"]["fields"]["jsonData"]
|
||||
print(f"jsonData length: {len(jd)} chars")
|
||||
j = json.loads(jd)
|
||||
fqs = j["first"]["questionSet"]
|
||||
sqs = j["second"]["questionSet"]
|
||||
print(f"first questionSet: {len(fqs)} items")
|
||||
print(f"second questionSet: {len(sqs)} items")
|
||||
if fqs:
|
||||
for i, q in enumerate(fqs):
|
||||
print(f" first[{i}]: {q['answerText']} | {q['question'][:60]}")
|
||||
if sqs:
|
||||
for i, q in enumerate(sqs):
|
||||
print(f" second[{i}]: {q['answerText']} | {q['question'][:60]}")
|
||||
Loading…
Reference in New Issue
Block a user