995 lines
27 KiB
Python
995 lines
27 KiB
Python
#!/usr/bin/env python3
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"""
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将剧本表(Q8AyX5)中互动组件的文本配置转为结构化JSON并写回组件配置列。
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"""
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import json, subprocess, sys, re
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# --- Bot Token ---
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def get_token():
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APP_ID = "cli_a931175d41799cc7"
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import os
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with open(os.path.expanduser('/root/.openclaw/credentials/xiaoyan/config.json')) as f:
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cfg = json.load(f)
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APP_SECRET = cfg['apps'][0]['appSecret']
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r = subprocess.run([
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'curl', '-s', '-X', 'POST',
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'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal',
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'-H', 'Content-Type: application/json',
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'-d', json.dumps({"app_id": APP_ID, "app_secret": APP_SECRET})
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], capture_output=True, text=True)
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return json.loads(r.stdout)['tenant_access_token']
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TOKEN = get_token()
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SPREADSHEET_TOKEN = "VBozs8u24h4KgdtSSiFc9vHEnBd"
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SHEET_ID = "Q8AyX5"
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# ============================================================
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# Component configs (raw text from sheet column I)
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# ============================================================
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CONFIGS = {
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"1217201": {
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"type": "图片单选",
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"text": """【任务标题】
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为包裹找到正确的日期牌子
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【情境引入】
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Jay : Help me find the right place!
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【互动内容】
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Find the "Days Ago" sign.（音频）
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选项：
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00
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01
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02
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答案：
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00
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辅助信息：days ago 指"几天前"。
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【互动反馈】
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正确 Lin : Bingo!
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错误 Jay : No, look! This package is from 3 days ago!
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【后置对话】
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无""",
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},
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"1217202": {
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"type": "对话朗读",
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"text": """【任务标题】
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朗读90天前的包裹信息
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【资源配置】
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图片时机：互动内容
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【情境引入】
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无
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【互动内容】
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User: It's 90 days ago...（朗读）
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【后置对话】
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无""",
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},
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"1217203": {
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"type": "对话朗读",
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"text": """【任务标题】
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理解天数和月数的换算
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【资源配置】
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图片时机：互动内容
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【情境引入】
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User: No! 90 days! It is about...
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【互动内容】
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User: 3 months!（朗读）
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【后置对话】
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User: This is from months ago!""",
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},
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"1217204": {
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"type": "对话组句",
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"text": """【任务标题】
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用单词组句描述包裹信息
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【资源配置】
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图片时机：互动内容
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【情境引入】
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无
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【互动内容】
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要求：用所给单词或短语组句
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It says 24 months ago.（音频）
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选项1：it says
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选项2：months ago
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选项3：24
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答案：It says 24 months ago.
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【互动反馈】
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正确 无
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错误 Jay : Try again! Read what the package says.
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【后置对话】
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无""",
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},
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"1217205": {
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"type": "对话朗读",
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"text": """【任务标题】
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理解月数和年数的换算
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【资源配置】
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图片时机：互动内容
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【情境引入】
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无
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【互动内容】
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User: That's 2 years!（朗读）
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【后置对话】
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无""",
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},
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"1217206": {
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"type": "对话选读",
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"text": """【任务标题】
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选择你想表达的感受
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【资源配置】
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无
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【情境引入】
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无
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【互动内容】
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要求：选择一个你想表达的观点
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选项：（音频）
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选项1：That's a long time ago!
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- 反馈 Jay: You are right.
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选项2：That is long, long ago!
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- 反馈 Jay: You are right.
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【后置对话】
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无""",
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},
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"1217207": {
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"type": "图片多选",
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"text": """【任务标题】
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找出写有months ago的包裹
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【情境引入】
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空
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【互动内容】
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Find the "months ago" packages in the picture.（音频）
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选项：
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00
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01
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02
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答案：
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01
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02
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辅助信息：months ago 指"几个月前"。
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【互动反馈】
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正确 User : Those two are months ago!
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错误 Jay : Look again! Which ones say "months ago"?
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【后置对话】
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无""",
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},
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"1217208": {
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"type": "图片单选",
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"text": """【任务标题】
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找出写有一年前的包裹
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【情境引入】
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空
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【互动内容】
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Find the "year ago" package in the picture.（音频）
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选项：
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00
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01
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02
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答案：
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02
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辅助信息：a year ago 指"一年前"。
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【互动反馈】
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正确 User : This one is a year ago!
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错误 Jay : No, that's not right. Look again!
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【后置对话】
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无""",
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},
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"1217209": {
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"type": "对话挖空",
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"text": """【任务标题】
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补全对Sunny说的句子
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【资源配置】
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无
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【情境引入】
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空
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【互动内容】
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You must ___ it!（音频）
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选项1：be happy with（正确）
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选项2：happy with
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【互动反馈】
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正确 User : You must be happy with it!
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错误 Sunny : That doesn't sound quite right...
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【后置对话】
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无""",
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},
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"1217210": {
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"type": "对话选读",
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"text": """【任务标题】
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选择帮Grace拿包裹的说法
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【资源配置】
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无
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【情境引入】
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空
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【互动内容】
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要求：选择一个你想表达的观点
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选项：（音频）
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选项1：Let me get it!
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- 反馈 Grace: Thank you, kid.
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选项2：I will get it!
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- 反馈 Grace: Thank you, kid.
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【后置对话】
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无""",
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},
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"1217211": {
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"type": "对话朗读",
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"text": """【任务标题】
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对Anna的提醒
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【资源配置】
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图片时机：无
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【情境引入】
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无
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【互动内容】
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User: You will not be happy with it.（朗读）
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【后置对话】
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无""",
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},
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"1217212": {
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"type": "对话组句",
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"text": """【任务标题】
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用单词组句主动帮忙
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【资源配置】
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无
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【情境引入】
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空
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【互动内容】
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要求：用所给单词或短语组句
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Can I get it for you?（音频）
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选项1：for you
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选项2：can I
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选项3：get it
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答案：Can I get it for you?
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【互动反馈】
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正确 Jack : You are very kind. But I just want to say...
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错误 Jack: I beg your pardon?
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【后置对话】
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无""",
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},
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"1217213": {
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"type": "对话挖空",
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"text": """【任务标题】
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补全对Jack说的话
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【资源配置】
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图片时机：互动内容互动反馈
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【情境引入】
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无
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【互动内容】
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But this meat is from 2 ___ !（音频）
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选项1：years ago（正确）
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选项2：days ago
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【互动反馈】
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正确 Jack : Perfect!
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错误 Jack : No, look at the sign on it!
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【后置对话】
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无""",
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},
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"1217214": {
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"type": "听力拖拽",
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"text": """【任务标题】
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告诉 Lin 你们分发包裹的事迹
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【任务背景】
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包裹大作战！你和 Jay 热火朝天地干了半天，把很多包裹带给了他们的主人。快来回顾一下你们的战果吧！
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【通关知识】
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get v. 收到
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month n. 月
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year n. 年
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ago adv. 以前
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... month(s)/year(s) ago.
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【开场语】
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Lin: Come on, tell me what you did!
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【听力文本】
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# 文本 1
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Jay: Well, well, well! Listen up!
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Jay: Tom gets a pen!
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User: It is from 5 days ago!
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Jay: And Sunny gets a dress.
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Jay: It is from 6 months ago.
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Jay: Jack gets some meat from 2 years ago!
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【题目信息】
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#单空选择
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选项图片编号：00,01,02
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答案图片编号：
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01,00,02
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【学习过程】
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句子 1
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It is from 5 days ago!
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【ago】
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句子 2
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It is from 6 months ago. 【month】
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句子 3
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Jack gets some meat from 2 years ago! 【year】""",
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},
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"1217215": {
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"type": "对话选读",
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"text": """【任务标题】
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选择表达满意的方式
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【资源配置】
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无
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【情境引入】
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无
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【互动内容】
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要求：选择一个你想表达的观点
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选项：（音频）
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选项1：I am happy with it!
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- 反馈 Jay: That's good!
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选项2：I am happy with the result!
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- 反馈 Jay: That's good!
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【后置对话】
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无""",
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},
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"1217216": {
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"type": "对话挖空",
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"text": """【任务标题】
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补全User想要包裹的句子
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【资源配置】
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无
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【情境引入】
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空
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【互动内容】
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I want to ___ one for myself!（音频）
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选项1：get（正确）
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选项2：get up
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【互动反馈】
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正确 无
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错误 Jay : Hmm, that's not how we say it. Try again!
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【后置对话】
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无""",
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},
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"1217217": {
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"type": "对话朗读",
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"text": """【任务标题】
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朗读收到帽子的喜悦
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【资源配置】
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图片时机：无
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【情境引入】
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无
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【互动内容】
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User: Now I get my own hat!（朗读）
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【后置对话】
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无""",
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},
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}
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# ============================================================
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# Parsers for each component type
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# ============================================================
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def extract_section(text, key):
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"""Extract content between 【key】and next section header 【...】."""
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# Match 【key】 then capture everything until next 【XXX】 header on its own line or end
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pattern = rf'【{re.escape(key)}】\s*\n?(.*?)(?=\n(?:【[^】]+】)\s*\n|\Z)'
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m = re.search(pattern, text, re.DOTALL)
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if m:
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return m.group(1).strip()
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return None
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def parse_context(text):
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"""Parse context intro: '角色 : 台词' or '空' or '无'"""
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if not text or text in ('无', '空', ''):
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return None
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lines = [l.strip() for l in text.strip().split('\n') if l.strip()]
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result = []
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for line in lines:
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if ':' in line:
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parts = line.split(':', 1)
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result.append({"character": parts[0].strip(), "line": parts[1].strip()})
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elif '：' in line:
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parts = line.split('：', 1)
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result.append({"character": parts[0].strip(), "line": parts[1].strip()})
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else:
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result.append(line)
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return result if result else None
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def parse_feedback(text):
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"""Parse feedback: 正确/错误 角色 : 台词"""
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if not text or text == '无':
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return {"correct": None, "incorrect": None}
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result = {"correct": None, "incorrect": None}
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lines = text.strip().split('\n')
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current_type = None
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for line in lines:
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line = line.strip()
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if not line:
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continue
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if line.startswith('正确'):
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current_type = 'correct'
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content = line[2:].strip()
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if ':' in content:
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parts = content.split(':', 1)
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char = parts[0].strip()
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msg = parts[1].strip()
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if msg == '无':
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result['correct'] = None
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else:
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result['correct'] = {"character": char, "line": msg}
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elif content == '无':
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result['correct'] = None
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elif line.startswith('错误'):
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current_type = 'incorrect'
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content = line[2:].strip()
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if ':' in content:
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parts = content.split(':', 1)
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result['incorrect'] = {"character": parts[0].strip(), "line": parts[1].strip()}
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elif '：' in content:
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parts = content.split('：', 1)
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result['incorrect'] = {"character": parts[0].strip(), "line": parts[1].strip()}
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return result
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def parse_selective_options(text):
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"""Parse 对话选读 options: 选项N：text - 反馈 X: line"""
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options = []
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lines = text.strip().split('\n')
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i = 0
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while i < len(lines):
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line = lines[i].strip()
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m = re.match(r'选项(\d+)[：:]\s*(.+)', line)
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if m:
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idx = int(m.group(1))
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opt_text = m.group(2).strip()
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feedback = None
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# Check next line for feedback
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if i + 1 < len(lines):
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next_line = lines[i + 1].strip()
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fm = re.match(r'[-–]\s*反馈\s*([^:：]+)[：:]\s*(.+)', next_line)
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if fm:
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feedback = {"character": fm.group(1).strip(), "line": fm.group(2).strip()}
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i += 1
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options.append({"index": idx, "text": opt_text, "feedback": feedback})
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i += 1
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return options
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def parse_image_options(text):
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"""Parse image choice options: 00, 01, 02 etc."""
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options = []
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lines = text.strip().split('\n')
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in_options = False
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for line in lines:
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line = line.strip()
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if line == '选项：':
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in_options = True
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continue
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if in_options:
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if re.match(r'^\d{2}$', line):
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options.append(line)
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else:
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break
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return options
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|
||
def parse_fill_options(text):
|
||
"""Parse fill-in-blanks options: 选项N：text（正确）"""
|
||
options = []
|
||
lines = text.strip().split('\n')
|
||
for line in lines:
|
||
line = line.strip()
|
||
m = re.match(r'选项(\d+)[：:]\s*(.+)', line)
|
||
if m:
|
||
idx = int(m.group(1))
|
||
opt_text = m.group(2).strip()
|
||
correct = False
|
||
if '（正确）' in opt_text:
|
||
correct = True
|
||
opt_text = opt_text.replace('（正确）', '').strip()
|
||
options.append({"index": idx, "text": opt_text, "correct": correct})
|
||
return options
|
||
|
||
def parse_sentence_options(text):
|
||
"""Parse sentence building options: 选项N：text"""
|
||
options = []
|
||
lines = text.strip().split('\n')
|
||
for line in lines:
|
||
line = line.strip()
|
||
m = re.match(r'选项(\d+)[：:]\s*(.+)', line)
|
||
if m:
|
||
idx = int(m.group(1))
|
||
opt_text = m.group(2).strip()
|
||
options.append({"index": idx, "text": opt_text})
|
||
return options
|
||
|
||
|
||
# ============================================================
|
||
# Converters
|
||
# ============================================================
|
||
|
||
def convert_choice_image(cid, text):
|
||
"""图片单选 / 图片多选"""
|
||
is_multi = CONFIGS[cid]['type'] == '图片多选'
|
||
|
||
raw_interaction = extract_section(text, '互动内容')
|
||
context = extract_section(text, '情境引入')
|
||
feedback = extract_section(text, '互动反馈')
|
||
post = extract_section(text, '后置对话')
|
||
|
||
# Parse interaction
|
||
interaction_lines = raw_interaction.strip().split('\n')
|
||
instruction = interaction_lines[0].strip()
|
||
audio = '（音频）' in instruction
|
||
instruction = instruction.replace('（音频）', '').strip()
|
||
|
||
options = []
|
||
answers = []
|
||
hint = None
|
||
in_options = False
|
||
in_answer = False
|
||
in_hint = False
|
||
|
||
for line in interaction_lines[1:]:
|
||
line = line.strip()
|
||
if line == '选项：':
|
||
in_options = True
|
||
continue
|
||
if in_options and re.match(r'^\d{2}$', line):
|
||
options.append(line)
|
||
continue
|
||
if '答案：' in line:
|
||
in_options = False
|
||
in_answer = True
|
||
ans_text = line.replace('答案：', '').strip()
|
||
if ans_text:
|
||
answers.append(ans_text)
|
||
continue
|
||
if in_answer:
|
||
if re.match(r'^\d{2}$', line):
|
||
answers.append(line)
|
||
elif '辅助信息' in line:
|
||
in_answer = False
|
||
in_hint = True
|
||
hint = line.replace('辅助信息：', '').strip()
|
||
else:
|
||
in_answer = False
|
||
continue
|
||
if in_hint:
|
||
continue
|
||
if '辅助信息' in line:
|
||
hint = line.replace('辅助信息：', '').strip()
|
||
continue
|
||
|
||
result = {
|
||
"componentType": CONFIGS[cid]['type'],
|
||
"taskTitle": extract_section(text, '任务标题'),
|
||
"contextIntro": parse_context(context),
|
||
"interaction": {
|
||
"instruction": instruction,
|
||
"audio": audio,
|
||
"options": options,
|
||
"answers": answers,
|
||
"hint": hint
|
||
},
|
||
"feedback": parse_feedback(feedback),
|
||
"postDialogue": parse_context(post)
|
||
}
|
||
return result
|
||
|
||
def convert_reading(cid, text):
|
||
"""对话朗读"""
|
||
return {
|
||
"componentType": "对话朗读",
|
||
"taskTitle": extract_section(text, '任务标题'),
|
||
"resourceConfig": extract_section(text, '资源配置') or None,
|
||
"contextIntro": parse_context(extract_section(text, '情境引入')),
|
||
"interaction": {
|
||
"sentence": (extract_section(text, '互动内容') or '').replace('（朗读）', '').strip(),
|
||
"audio": True
|
||
},
|
||
"postDialogue": parse_context(extract_section(text, '后置对话'))
|
||
}
|
||
|
||
def convert_sentence_building(cid, text):
|
||
"""对话组句"""
|
||
raw_interaction = extract_section(text, '互动内容')
|
||
resource = extract_section(text, '资源配置') or None
|
||
context = extract_section(text, '情境引入')
|
||
feedback = extract_section(text, '互动反馈')
|
||
post = extract_section(text, '后置对话')
|
||
|
||
interaction_lines = raw_interaction.strip().split('\n')
|
||
requirement = None
|
||
sentence = None
|
||
audio = True
|
||
options = []
|
||
answer = None
|
||
hint = None
|
||
|
||
# Parse interaction
|
||
i = 0
|
||
if interaction_lines[0].startswith('要求：'):
|
||
requirement = interaction_lines[0].replace('要求：', '').strip()
|
||
i = 1
|
||
|
||
# Find sentence line (ends with （音频）)
|
||
for j in range(i, len(interaction_lines)):
|
||
line = interaction_lines[j].strip()
|
||
if '（音频）' in line:
|
||
sentence = line.replace('（音频）', '').strip()
|
||
i = j + 1
|
||
break
|
||
elif re.match(r'选项\d+', line):
|
||
# No sentence line found, use requirement as sentence
|
||
i = j
|
||
break
|
||
|
||
# Parse options
|
||
for j in range(i, len(interaction_lines)):
|
||
line = interaction_lines[j].strip()
|
||
m = re.match(r'选项(\d+)[：:]\s*(.+)', line)
|
||
if m:
|
||
options.append({"index": int(m.group(1)), "text": m.group(2).strip()})
|
||
elif '答案：' in line:
|
||
answer = line.replace('答案：', '').strip()
|
||
elif '辅助信息：' in line:
|
||
hint = line.replace('辅助信息：', '').strip()
|
||
|
||
return {
|
||
"componentType": "对话组句",
|
||
"taskTitle": extract_section(text, '任务标题'),
|
||
"resourceConfig": resource,
|
||
"contextIntro": parse_context(context),
|
||
"interaction": {
|
||
"requirement": requirement,
|
||
"sentence": sentence,
|
||
"audio": audio,
|
||
"options": options,
|
||
"answer": answer,
|
||
"hint": hint
|
||
},
|
||
"feedback": parse_feedback(feedback),
|
||
"postDialogue": parse_context(post)
|
||
}
|
||
|
||
def convert_selective_reading(cid, text):
|
||
"""对话选读"""
|
||
raw_interaction = extract_section(text, '互动内容')
|
||
resource = extract_section(text, '资源配置') or None
|
||
context = extract_section(text, '情境引入')
|
||
post = extract_section(text, '后置对话')
|
||
|
||
interaction_lines = raw_interaction.strip().split('\n')
|
||
requirement = interaction_lines[0].strip()
|
||
audio = '（音频）' in raw_interaction
|
||
if requirement.startswith('要求：'):
|
||
requirement = requirement.replace('要求：', '').strip()
|
||
|
||
options = parse_selective_options(raw_interaction)
|
||
|
||
return {
|
||
"componentType": "对话选读",
|
||
"taskTitle": extract_section(text, '任务标题'),
|
||
"resourceConfig": resource,
|
||
"contextIntro": parse_context(context),
|
||
"interaction": {
|
||
"requirement": requirement,
|
||
"audio": audio,
|
||
"options": options
|
||
},
|
||
"postDialogue": parse_context(post)
|
||
}
|
||
|
||
def convert_fill_blanks(cid, text):
|
||
"""对话挖空"""
|
||
raw_interaction = extract_section(text, '互动内容')
|
||
resource = extract_section(text, '资源配置') or None
|
||
context = extract_section(text, '情境引入')
|
||
feedback = extract_section(text, '互动反馈')
|
||
post = extract_section(text, '后置对话')
|
||
|
||
interaction_lines = raw_interaction.strip().split('\n')
|
||
sentence = None
|
||
options = []
|
||
|
||
for line in interaction_lines:
|
||
line = line.strip()
|
||
if '（音频）' in line and not line.startswith('选项'):
|
||
sentence = line.replace('（音频）', '').strip()
|
||
m = re.match(r'选项(\d+)[：:]\s*(.+)', line)
|
||
if m:
|
||
opt_text = m.group(2).strip()
|
||
correct = '（正确）' in opt_text
|
||
opt_text = opt_text.replace('（正确）', '').strip()
|
||
options.append({"index": int(m.group(1)), "text": opt_text, "correct": correct})
|
||
|
||
return {
|
||
"componentType": "对话挖空",
|
||
"taskTitle": extract_section(text, '任务标题'),
|
||
"resourceConfig": resource,
|
||
"contextIntro": parse_context(context),
|
||
"interaction": {
|
||
"sentence": sentence,
|
||
"audio": True,
|
||
"options": options
|
||
},
|
||
"feedback": parse_feedback(feedback),
|
||
"postDialogue": parse_context(post)
|
||
}
|
||
|
||
def convert_listening_drag(cid, text):
|
||
"""听力拖拽 → core_listening_drag JSON"""
|
||
task_title = extract_section(text, '任务标题')
|
||
task_bg = extract_section(text, '任务背景') or ''
|
||
knowledge = extract_section(text, '通关知识') or ''
|
||
opening = extract_section(text, '开场语') or ''
|
||
audio_text = extract_section(text, '听力文本') or ''
|
||
question_info = extract_section(text, '题目信息') or ''
|
||
learning = extract_section(text, '学习过程') or ''
|
||
|
||
# Parse audio text into dialogs
|
||
dialog_list = []
|
||
for line in audio_text.strip().split('\n'):
|
||
line = line.strip()
|
||
if not line or line.startswith('#'):
|
||
continue
|
||
if ':' in line or '：' in line:
|
||
sep = ':' if ':' in line else '：'
|
||
parts = line.split(sep, 1)
|
||
dialog_list.append({"character": parts[0].strip(), "line": parts[1].strip()})
|
||
|
||
# Parse question info
|
||
option_images = []
|
||
answer_images = []
|
||
for line in question_info.strip().split('\n'):
|
||
line = line.strip()
|
||
if '选项图片编号' in line:
|
||
option_images = [x.strip() for x in line.split('：', 1)[1].split(',') if x.strip()]
|
||
if '答案图片编号' in line:
|
||
# Answer on next line
|
||
pass
|
||
|
||
# Get answer from question info - look for answer after 答案图片编号
|
||
q_lines = question_info.strip().split('\n')
|
||
for i, line in enumerate(q_lines):
|
||
if '答案图片编号' in line and i + 1 < len(q_lines):
|
||
answer_images = [x.strip() for x in q_lines[i+1].split(',') if x.strip() and x.strip() != '答案图片编号']
|
||
|
||
# For 听力拖拽, 【学习过程】 is the LAST section and contains inline 【kp】.
|
||
# Extract it manually: everything after 【学习过程】
|
||
lp_match = re.search(r'【学习过程】\s*\n(.*)', text, re.DOTALL)
|
||
learning = lp_match.group(1).strip() if lp_match else ''
|
||
|
||
learning_steps = []
|
||
# Split by sentence markers
|
||
blocks = re.split(r'\n(?=句子\s*\d*)', learning)
|
||
for block in blocks:
|
||
block = block.strip()
|
||
if not block:
|
||
continue
|
||
# Remove the 句子 N header
|
||
block = re.sub(r'^句子\s*\d*\s*\n?', '', block).strip()
|
||
if not block:
|
||
continue
|
||
# Extract kp from 【...】
|
||
kp_match = re.search(r'【(.+?)】', block)
|
||
kp = kp_match.group(1).strip() if kp_match else ""
|
||
# Extract sentence (text before 【 or whole block if no 【)
|
||
if kp_match:
|
||
sentence = block[:kp_match.start()].strip()
|
||
else:
|
||
sentence = block.strip()
|
||
if sentence or kp:
|
||
learning_steps.append({"sentence": sentence, "knowledgePoint": kp})
|
||
|
||
# Scene description
|
||
scene_desc = f"{task_bg}\n\n{opening}"
|
||
|
||
return {
|
||
"componentType": "听力拖拽",
|
||
"cType": "core_listening_drag",
|
||
"taskData": {
|
||
"cType": "core_listening_drag",
|
||
"cId": cid,
|
||
"title": task_title,
|
||
"sceneDesc": scene_desc,
|
||
"key": "ago, month, year, get"
|
||
},
|
||
"dialogList": dialog_list,
|
||
"preDialog": [],
|
||
"questionList": [
|
||
{
|
||
"type": "drag_match",
|
||
"optionImages": option_images,
|
||
"answerImages": answer_images,
|
||
"itemCount": len(option_images)
|
||
}
|
||
],
|
||
"learningData": {
|
||
"learningPart": learning_steps,
|
||
"closing": ""
|
||
},
|
||
"audioText": audio_text,
|
||
"knowledgeSummary": knowledge
|
||
}
|
||
|
||
|
||
# ============================================================
|
||
# Main conversion
|
||
# ============================================================
|
||
|
||
CONVERTERS = {
|
||
"图片单选": convert_choice_image,
|
||
"图片多选": convert_choice_image,
|
||
"对话朗读": convert_reading,
|
||
"对话组句": convert_sentence_building,
|
||
"对话选读": convert_selective_reading,
|
||
"对话挖空": convert_fill_blanks,
|
||
"听力拖拽": convert_listening_drag,
|
||
}
|
||
|
||
# Component row mapping (from sheet data: which row has which component ID)
|
||
COMPONENT_ROWS = {
|
||
"1217201": 33,
|
||
"1217202": 40,
|
||
"1217203": 43,
|
||
"1217204": 50,
|
||
"1217205": 51,
|
||
"1217206": 53,
|
||
"1217207": 68,
|
||
"1217208": 70,
|
||
"1217209": 89,
|
||
"1217210": 95,
|
||
"1217211": 107,
|
||
"1217212": 120,
|
||
"1217213": 123,
|
||
"1217214": 157,
|
||
"1217215": 164,
|
||
"1217216": 168,
|
||
"1217217": 173,
|
||
}
|
||
|
||
|
||
def write_cell(row, col_letter, value, token):
|
||
"""Write a single cell to the sheet."""
|
||
cell_range = f"{SHEET_ID}!{col_letter}{row}:{col_letter}{row}"
|
||
payload = {
|
||
"valueRange": {
|
||
"range": cell_range,
|
||
"values": [[value]]
|
||
}
|
||
}
|
||
r = subprocess.run([
|
||
'curl', '-s', '-X', 'PUT',
|
||
f'https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/values',
|
||
'-H', f'Authorization: Bearer {token}',
|
||
'-H', 'Content-Type: application/json',
|
||
'-d', json.dumps(payload, ensure_ascii=False)
|
||
], capture_output=True, text=True)
|
||
result = json.loads(r.stdout)
|
||
if result.get('code') != 0:
|
||
print(f" ❌ Write failed: {result}", file=sys.stderr)
|
||
return False
|
||
return True
|
||
|
||
|
||
def main():
|
||
results = {}
|
||
for cid, cfg in CONFIGS.items():
|
||
ctype = cfg['type']
|
||
converter = CONVERTERS.get(ctype)
|
||
if not converter:
|
||
print(f"⚠️ Unknown type {ctype} for {cid}", file=sys.stderr)
|
||
continue
|
||
try:
|
||
json_data = converter(cid, cfg['text'])
|
||
results[cid] = json_data
|
||
print(f"✅ {cid} ({ctype}) → JSON OK")
|
||
except Exception as e:
|
||
print(f"❌ {cid} ({ctype}) → ERROR: {e}", file=sys.stderr)
|
||
import traceback
|
||
traceback.print_exc()
|
||
|
||
# Print all JSONs for review
|
||
print("\n" + "=" * 60)
|
||
print("GENERATED JSONS")
|
||
print("=" * 60)
|
||
for cid, data in results.items():
|
||
print(f"\n--- {cid} ({data['componentType']}) ---")
|
||
print(json.dumps(data, ensure_ascii=False, indent=2))
|
||
|
||
# Save to file for inspection
|
||
with open('/root/.openclaw/workspace-xiaoyan/output/component_jsons.json', 'w', encoding='utf-8') as f:
|
||
json.dump(results, f, ensure_ascii=False, indent=2)
|
||
print(f"\n📁 Saved to output/component_jsons.json")
|
||
|
||
# Write back to sheet
|
||
print("\n" + "=" * 60)
|
||
print("WRITING BACK TO SHEET")
|
||
print("=" * 60)
|
||
|
||
# Re-fetch token (may have expired)
|
||
token = get_token()
|
||
|
||
success = 0
|
||
fail = 0
|
||
for cid, data in results.items():
|
||
row = COMPONENT_ROWS.get(cid)
|
||
if not row:
|
||
print(f"⚠️ {cid}: no row mapping, skipped")
|
||
continue
|
||
json_str = json.dumps(data, ensure_ascii=False)
|
||
if write_cell(row, 'I', json_str, token):
|
||
print(f"✅ {cid} → row {row} written")
|
||
success += 1
|
||
else:
|
||
fail += 1
|
||
|
||
print(f"\nDone: {success} written, {fail} failed")
|
||
|
||
|
||
if __name__ == '__main__':
|
||
main()
|