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5a26ae0048
- 新增小红书前端模块（启动服务、内容分析、爆款创作、发布记录、技能卡片、拟人设置、AI 助手） - 新增 xhs-agent-desktop 独立桌面 Agent，对接 OMS 任务调度 - 登录页重构，整合微信登录与 OMS JWT 认证 - 订单、渠道、用户中心等页面与 API 增强 Co-authored-by: Cursor <cursoragent@cursor.com>
95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
from __future__ import annotations
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from xhs_bridge.skill_catalog import SkillRecipe, compose_prompt_brief
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_ANALYSIS_INSTRUCTION = """
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请根据上方爆款技能配方，对下方笔记做拆解分析。输出使用 Markdown，建议包含：
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1. 爆款公式匹配（情绪/实用/视觉/社交）
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2. 标题与开头钩子
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3. 正文结构与信息密度
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4. 互动数据解读
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5. 评论区亮点（如有）
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6. 可借鉴的 3～5 条 actionable 建议
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直接输出分析正文，不要 JSON，不要重复粘贴整篇原文。
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"""
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def extract_feed_image_urls(payload: dict, *, max_images: int = 6) -> list[str]:
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"""从笔记详情中提取配图 URL（供图文模型使用）。"""
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note = payload.get("note") or {}
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images = note.get("images") or []
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urls: list[str] = []
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for img in images:
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if not isinstance(img, dict):
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continue
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url = str(img.get("url") or "").strip()
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if url.startswith("http"):
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urls.append(url)
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if len(urls) >= max_images:
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break
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return urls
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def format_feed_for_analysis(payload: dict, *, max_comments: int = 20) -> str:
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"""将详情数据整理为 AI 可读文本。"""
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note = payload.get("note") or {}
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user = note.get("user") or {}
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interact = note.get("interact") or {}
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lines = [
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"【笔记信息】",
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f"标题：{note.get('title') or '（无）'}",
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f"作者：{user.get('nickname') or '—'}",
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f"发布时间：{note.get('time') or '—'}",
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f"位置：{note.get('ip_location') or '—'}",
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f"类型：{'视频' if note.get('is_video') else '图文'}",
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"",
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"【互动数据】",
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f"点赞 {interact.get('liked_count', '0')} · "
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f"收藏 {interact.get('collected_count', '0')} · "
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f"评论 {interact.get('comment_count', '0')} · "
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f"分享 {interact.get('shared_count', '0')}",
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"",
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"【正文】",
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note.get("desc") or "（无正文）",
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]
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comments = payload.get("comments") or []
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if comments:
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lines.append("")
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lines.append(f"【评论摘录（最多 {max_comments} 条）】")
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for i, c in enumerate(comments[:max_comments]):
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cu = c.get("user") or {}
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lines.append(
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f"- {cu.get('nickname', '匿名')}：{c.get('content', '')}"
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+ (f"（赞 {c['like_count']}）" if c.get("like_count") else "")
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)
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return "\n".join(lines)
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def build_analysis_prompt(recipe: SkillRecipe, feed_payload: dict) -> str:
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return (
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compose_prompt_brief(recipe)
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+ "\n"
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+ _ANALYSIS_INSTRUCTION
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+ "\n\n"
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+ format_feed_for_analysis(feed_payload)
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)
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_COMMENT_INSTRUCTION = """
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请根据笔记内容与上方技能配方，生成 1 条适合发布在小红书评论区的中文短评。
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要求：口语自然、不超过 80 字、不要 hashtag、不要引号包裹、不要解释分析过程。
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只输出评论正文一行。
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"""
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def build_comment_prompt(recipe: SkillRecipe, feed_payload: dict) -> str:
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return (
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compose_prompt_brief(recipe)
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+ "\n"
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+ _COMMENT_INSTRUCTION
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+ "\n\n"
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+ format_feed_for_analysis(feed_payload, max_comments=8)
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)
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