66 lines
1.7 KiB
Markdown
66 lines
1.7 KiB
Markdown
# Rendering & Guide Formatting Reference
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## `clean_guide_text(text)` function (in `blog_markdown()`)
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Strips unwanted artifacts from LLM-generated guide text:
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```python
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def clean_guide_text(text):
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# Strip all [N] reference numbers
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text = re.sub(r'\[\d+\]', '', text)
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text = re.sub(r'\[N\]', '', text).strip()
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# Strip "主线判断：" prefix
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text = re.sub(r'^主线判断[：:]\s*', '', text)
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# Clean extra whitespace
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text = re.sub(r'\s+', ' ', text).strip()
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return text
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```
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## Summary section rendering
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Type labels map: `{'strong': '强信号', 'medium': '中信号', 'risk': '待验证'}`
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Output format per type group:
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```
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## 总结
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**强信号**
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- **标题（从text第一句提取）**
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解释内容...
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- **标题**
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解释内容...
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**中信号**
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- **标题**
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解释内容...
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**待验证**
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- **标题**
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解释内容...
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```
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Title extraction logic:
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1. Try splitting on `：` or `:` — if prefix < 60 chars, use as title
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2. Otherwise, split on `。！？` and use first sentence as title
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## Title translation (Stage 2a)
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Titles are translated from English to Chinese in Stage 2a. Rules:
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- Brand names preserved: GPT-5, Codex, Gemini, OpenAI, Meta, etc.
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- Technical terms with no good Chinese equivalent: keep English
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- Everything else: translate to natural Chinese
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- LLM prompt explicitly states: "英文品牌名/模型名保留原样，其余翻译为中文"
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## LLM prompt for guide (as of 2026-05-30)
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Key instructions to LLM:
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- 不要空泛总结（如"行业焦点转向XX"），要指向具体事件
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- 不要引用编号如[1][3]，读者看不到对应关系
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- 不要建议（"开发者应该..."之类删掉）
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- 每条控制在2-3句话以内
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- 用大白话，不要学术腔
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