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feat: multimodal image clients, workspaces, Tushare skill, test fixes
- Replace monolithic image_message_client with HTTP/OCR/legacy modules; tighten OpenAI transport + tool schemas for multimodal downgrade to OCR specialist path. - Add image/stock workspace prompts (META/SOUL/ROLE_SYSTEM); register experts; tweak specialist agent/direct loop/query_image_attachment. - Add bundled runtime/skills/tushare-finance (references, api_client, SKILL metadata). - Document OCR-related env vars; admin chat tweaks; README; weixin_install Ensure-OfficialPluginRuntimeDeps helper. - Tests: multimodal downgrade + OCR coverage, strict tool pairing in attachment replay guard, workspace contract skips _internal/_system dirs, router/trace/prompt guards. Co-authored-by: Cursor <cursoragent@cursor.com>
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runtime/skills/tushare-finance/reference/接口文档/影院日度票房.md
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runtime/skills/tushare-finance/reference/接口文档/影院日度票房.md
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# 影院日度票房
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**文档ID**: 116
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**原始链接**: https://tushare.pro/document/2?doc_id=116
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---
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## 影院每日票房
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接口:bo_cinema描述:获取每日各影院的票房数据数据历史: 数据从2018年9月开始,更多历史数据正在补充数据权限:用户需要至少500积分才可以调取,具体请参阅积分获取办法
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输入参数
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<table>
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<thead>
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<tr>
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<th>名称</th>
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<th>类型</th>
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<th>必选</th>
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<th>描述</th>
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</tr>
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</thead>
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<tbody><tr>
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<td>date</td>
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<td>str</td>
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<td>Y</td>
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<td>日期(格式:YYYYMMDD)</td>
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</tr>
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</tbody></table>
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输出参数
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<table>
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<thead>
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<tr>
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<th>名称</th>
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<th>类型</th>
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<th>默认显示</th>
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<th>描述</th>
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</tr>
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</thead>
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<tbody><tr>
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<td>date</td>
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<td>str</td>
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<td>Y</td>
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<td>日期</td>
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</tr>
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<tr>
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<td>c_name</td>
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<td>str</td>
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<td>Y</td>
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<td>影院名称</td>
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</tr>
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<tr>
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<td>aud_count</td>
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<td>int</td>
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<td>Y</td>
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<td>观众人数</td>
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</tr>
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<tr>
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<td>att_ratio</td>
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<td>float</td>
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<td>Y</td>
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<td>上座率</td>
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</tr>
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<tr>
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<td>day_amount</td>
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<td>float</td>
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<td>Y</td>
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<td>当日票房</td>
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</tr>
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<tr>
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<td>day_showcount</td>
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<td>float</td>
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<td>Y</td>
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<td>当日场次</td>
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</tr>
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<tr>
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<td>avg_price</td>
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<td>float</td>
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<td>Y</td>
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<td>场均票价(元)</td>
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</tr>
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<tr>
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<td>p_pc</td>
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<td>float</td>
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<td>Y</td>
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<td>场均人次</td>
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</tr>
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<tr>
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<td>rank</td>
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<td>int</td>
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<td>Y</td>
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<td>排名</td>
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</tr>
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</tbody></table>
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接口使用
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```
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pro = ts.pro_api()
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#或者
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#pro = ts.pro_api('your token')
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df = pro.bo_cinema(date='20181014')
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```
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数据示例
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```
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date c_name aud_count att_ratio day_amount \
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0 20181014 Jackie Chan北京耀莱 4973 20.70 215721.00
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1 20181014 金逸北京大悦城IMAX店 3160 29.65 197890.50
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2 20181014 广州飞扬影城(正佳分店) 3279 23.30 173564.30
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3 20181014 首都电影院西单店 3412 30.01 167779.68
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4 20181014 北京寰映合生汇店 2554 30.69 161035.50
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5 20181014 金逸北京荟聚IMAX店 2710 18.34 150530.10
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6 20181014 南京新街口国际影城 3685 23.58 144884.50
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7 20181014 武商摩尔国际电影城 4232 23.22 144577.00
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8 20181014 广州飞扬影城 2775 22.38 144180.00
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9 20181014 中影国际影城武汉光谷天河店 4078 37.00 137562.00
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10 20181014 中影国际影城珠海华发2店 3228 34.78 136909.00
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11 20181014 卢米埃北京长楹天街IMAX影城 2197 18.04 132217.00
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12 20181014 中影国际影城北京昌平永旺店 3002 35.76 130213.40
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13 20181014 CGV影城 深圳壹方城店 2423 19.03 130132.00
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14 20181014 北京市金泉港国际影城 2538 16.75 129530.00
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15 20181014 北京UME国际影城双井店 2052 17.98 129479.59
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16 20181014 深圳市百老汇电影中心影城 2515 19.71 128600.00
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17 20181014 广州市百丽宫猎德影院 2007 24.84 125094.00
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18 20181014 郑州奥斯卡熙地港国际影城 3286 27.60 124663.00
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```
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