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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oliver 2026-05-10 04:41:42 +08:00
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# 电影周度票房
**文档ID**: 114
**原始链接**: https://tushare.pro/document/2?doc_id=114
---
## 电影周度票房
接口:bo_weekly描述:获取周度票房数据数据更新:本周更新上一周数据数据历史: 数据从2008年第一周开始,超过10年历史数据。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
输入参数
<table>
<thead>
<tr>
<th>名称</th>
<th>类型</th>
<th>必选</th>
<th>描述</th>
</tr>
</thead>
<tbody><tr>
<td>date</td>
<td>str</td>
<td>Y</td>
<td>日期(每周一日期,格式YYYYMMDD)</td>
</tr>
</tbody></table>
输出参数
<table>
<thead>
<tr>
<th>名称</th>
<th>类型</th>
<th>默认显示</th>
<th>描述</th>
</tr>
</thead>
<tbody><tr>
<td>date</td>
<td>str</td>
<td>Y</td>
<td>日期</td>
</tr>
<tr>
<td>name</td>
<td>str</td>
<td>Y</td>
<td>影片名称</td>
</tr>
<tr>
<td>avg_price</td>
<td>float</td>
<td>Y</td>
<td>平均票价</td>
</tr>
<tr>
<td>week_amount</td>
<td>float</td>
<td>Y</td>
<td>当周票房(万)</td>
</tr>
<tr>
<td>total</td>
<td>float</td>
<td>Y</td>
<td>累计票房(万)</td>
</tr>
<tr>
<td>list_day</td>
<td>int</td>
<td>Y</td>
<td>上映天数</td>
</tr>
<tr>
<td>p_pc</td>
<td>int</td>
<td>Y</td>
<td>场均人次</td>
</tr>
<tr>
<td>wom_index</td>
<td>float</td>
<td>Y</td>
<td>口碑指数</td>
</tr>
<tr>
<td>up_ratio</td>
<td>float</td>
<td>Y</td>
<td>环比变化 (%)</td>
</tr>
<tr>
<td>rank</td>
<td>int</td>
<td>Y</td>
<td>排名</td>
</tr>
</tbody></table>
接口使用
```
pro = ts.pro_api()
#或者
#pro = ts.pro_api('your token')
df = pro.bo_weekly(date='20181008')
```
数据示例
```
date name avg_price week_amount total list_day p_pc \
0 20181008 无双 36.0 25640.0 93705.0 15 12
1 20181008 影 36.0 10277.0 55406.0 15 8
2 20181008 找到你 32.0 9318.0 15234.0 10 11
3 20181008 李茶的姑妈 35.0 5823.0 57263.0 15 6
4 20181008 胖子行动队 34.0 3875.0 23683.0 15 7
5 20181008 嗝嗝老师 30.0 2917.0 2941.0 3 10
6 20181008 悲伤逆流成河 34.0 2475.0 33532.0 24 7
7 20181008 超能泰坦 30.0 1202.0 1202.0 3 4
8 20181008 阿凡提之奇缘历险 34.0 675.0 7251.0 14 5
```