feat: AI-powered daily reading report\n\n- Calls DeepSeek API for deep analysis of daily highlights+thoughts\n- Detailed per-book analysis + cross-book theme connection\n- Cron: 22:00 daily (auto sync + analysis + push)\n- Sync frequency: every hour (was every 4h)\n- API key: ~/.keys/deepseek_api_key
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weread-sync/daily_report_ai.py
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291
weread-sync/daily_report_ai.py
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#!/usr/bin/env python3
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"""
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daily_report_ai.py — AI 驱动的微信读书每日阅读报告
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调用 DeepSeek API 对当日划线+批注进行深度分析，
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生成有洞察的阅读报告，推送到 Gitea。
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定时：每天 22:00（配合 sync.py 同步）
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依赖：pip install requests
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"""
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import os
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import re
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import sys
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import json
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import subprocess
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from datetime import datetime
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REPO_DIR = os.path.expanduser("~/weread-notes")
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NOTES_DIR = os.path.join(REPO_DIR, "notes")
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DAILY_DIR = os.path.join(REPO_DIR, "daily")
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SYNC_SCRIPT = os.path.expanduser("~/weread-sync/sync.py")
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API_KEY_FILE = os.path.expanduser("~/.keys/deepseek_api_key")
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DEEPSEEK_URL = "https://api.deepseek.com/chat/completions"
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DEEPSEEK_MODEL = "deepseek-chat"
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# ─── 读取今日数据 ────────────────────────────────────
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def parse_time_from_line(line):
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m = re.search(r'🕐\s*(\d{4}-\d{2}-\d{2})', line)
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return m.group(1) if m else None
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def load_today_data(date_str=None):
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"""读取当日所有划线+批注"""
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if not date_str:
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date_str = datetime.now().strftime("%Y-%m-%d")
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today_entries = []
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for fname in os.listdir(NOTES_DIR):
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if not fname.endswith(".md"):
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continue
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filepath = os.path.join(NOTES_DIR, fname)
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book_title = fname[:-3]
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with open(filepath, "r", encoding="utf-8") as f:
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lines = f.readlines()
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# 提取书籍元信息
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meta = {"author": "", "progress": "", "category": ""}
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for line in lines[:35]:
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m = re.match(r'\|\s*\*\*作者\*\*\s*\|\s*(.+?)\s*\|', line)
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if m: meta["author"] = m.group(1).strip()
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m = re.match(r'\|\s*\*\*阅读进度\*\*\s*\|\s*(\d+)%\s*\|', line)
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if m: meta["progress"] = f"{m.group(1)}%"
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m = re.match(r'\|\s*\*\*分类\*\*\s*\|\s*(.+?)\s*\|', line)
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if m: meta["category"] = m.group(1).strip()
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# 解析时间戳行
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for i, line in enumerate(lines):
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d = parse_time_from_line(line)
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if d != date_str:
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continue
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entry = {
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"book": book_title,
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"author": meta["author"],
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"progress": meta["progress"],
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"category": meta["category"],
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"time": line.strip(),
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}
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# 上一行是原文
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if i > 0:
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prev = lines[i - 1].strip()
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entry["text"] = re.sub(r'^>\s*', '', prev).strip()
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# 后续行找批注
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for j in range(i + 1, min(i + 5, len(lines))):
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t = lines[j].strip()
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if t.startswith("💬"):
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entry["thought"] = re.sub(r'^💬\s*\*{0,2}(.*?)\*{0,2}$', r'\1', t).strip()
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break
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today_entries.append(entry)
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return today_entries
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def format_entries_for_prompt(entries):
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"""将今日条目格式化为 AI 可读的文本"""
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if not entries:
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return "今日暂无阅读记录。"
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# 按书名分组
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from collections import defaultdict
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by_book = defaultdict(list)
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for e in entries:
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by_book[e["book"]].append(e)
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parts = []
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for book_name in sorted(by_book.keys()):
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items = by_book[book_name]
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info = []
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if items[0]["author"]:
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info.append(f"作者：{items[0]['author']}")
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if items[0]["category"]:
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info.append(f"分类：{items[0]['category']}")
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if items[0]["progress"]:
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info.append(f"进度：{items[0]['progress']}")
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parts.append(f"## 《{book_name}》")
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if info:
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parts.append("（" + " | ".join(info) + "）")
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parts.append("")
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for e in items:
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parts.append(f"### 划线")
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parts.append(f"{e['text']}")
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parts.append(f"时间：{e['time']}")
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if e.get("thought"):
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parts.append(f"")
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parts.append(f"我的批注：{e['thought']}")
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parts.append("")
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return "\n".join(parts)
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# ─── AI 分析 ──────────────────────────────────────────
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def call_deepseek(prompt, system_prompt):
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"""调用 DeepSeek API"""
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api_key_file = os.path.expanduser(API_KEY_FILE)
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if os.path.exists(api_key_file):
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with open(api_key_file) as f:
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api_key = f.read().strip()
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else:
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print("[ERROR] DeepSeek API Key not found")
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print(f" Please save your key to: {API_KEY_FILE}")
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return None
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import urllib.request
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body = json.dumps({
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"model": DEEPSEEK_MODEL,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": prompt},
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],
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"temperature": 0.7,
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"max_tokens": 4096,
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}).encode()
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req = urllib.request.Request(
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DEEPSEEK_URL,
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data=body,
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headers={
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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)
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try:
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resp = urllib.request.urlopen(req, timeout=120)
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result = json.loads(resp.read())
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return result["choices"][0]["message"]["content"]
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except Exception as e:
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print(f"[ERROR] DeepSeek API call failed: {e}")
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return None
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# ─── 报告生成 ────────────────────────────────────────
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SYSTEM_PROMPT = """你是一位深度阅读分析助手，不是摘要工具。
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你的任务是分析用户今日在微信读书上的划线和批注，生成一份高质量的阅读报告。
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## 写作要求
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- 每一条划线都要展开分析：补充背景知识、指出其深层含义、联系用户的实际场景
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- 如果有批注，要围绕批注展开讨论，追问关键问题
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- 找出当日阅读内容之间的内在联系（主题、方法、思想上的呼应）
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- 像一位私人思考伙伴一样，提供有启发的见解和追问
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- 报告要有深度、有观点，不要写成流水账或摘要
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- 使用平实、客观的语言，不要抒情、不要煽情
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- 适当引用原文，但不要大段堆砌
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## 报告结构
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1. 今日阅读概览（总览性描述当天阅读的特点）
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2. 分书深度分析（每本书独立小节，有洞察的分析）
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3. 主题串联（找出跨书的联系和启发）
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4. 明日阅读建议（基于当天阅读给出具体建议）"""
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def generate_report_md(entries, ai_analysis, date_str):
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"""组装最终报告 Markdown"""
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lines = []
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lines.append(f"# 今日阅读报告 · {date_str}")
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lines.append("")
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lines.append("---")
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lines.append("")
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lines.append(ai_analysis)
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lines.append("")
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lines.append("---")
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lines.append("")
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lines.append(f"*报告生成：{datetime.now().strftime('%Y-%m-%d %H:%M')} | AI 模型：DeepSeek*")
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return "\n".join(lines)
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# ─── Git 操作 ────────────────────────────────────────
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def save_and_push(content, date_str):
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"""保存报告并推送到 Gitea"""
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os.makedirs(DAILY_DIR, exist_ok=True)
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filename = f"每日阅读_{date_str}.md"
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filepath = os.path.join(DAILY_DIR, filename)
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with open(filepath, "w", encoding="utf-8") as f:
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f.write(content)
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print(f"[OUTPUT] {filepath}")
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try:
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subprocess.run(["git", "add", "daily/"], cwd=REPO_DIR,
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capture_output=True, timeout=30)
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result = subprocess.run(
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["git", "commit", "-m", f"report: 每日阅读报告 {date_str} (AI分析)", "--allow-empty"],
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cwd=REPO_DIR, capture_output=True, timeout=30
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)
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if result.returncode == 0:
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subprocess.run(["git", "push"], cwd=REPO_DIR,
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capture_output=True, timeout=60)
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print(f"[GIT] Pushed: 每日阅读报告 {date_str}")
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else:
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print(f"[GIT] No changes")
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except subprocess.CalledProcessError as e:
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print(f"[GIT] Error: {e.stderr.decode()[:200]}")
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# ─── 主流程 ───────────────────────────────────────────
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def main():
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date_str = datetime.now().strftime("%Y-%m-%d")
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print(f"\n{'='*50}")
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print(f"每日阅读报告 (AI) | {datetime.now().strftime('%Y-%m-%d %H:%M')}")
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print(f"{'='*50}")
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# 1. 同步
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print("\n[1/4] 同步微信读书笔记...")
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if os.path.exists(SYNC_SCRIPT):
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subprocess.run(["python3", SYNC_SCRIPT], capture_output=True, timeout=300)
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print(" 同步完成")
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else:
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print(f" [SKIP] {SYNC_SCRIPT} not found")
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# 2. 解析今日数据
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print(f"\n[2/4] 提取今日数据 ({date_str})...")
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entries = load_today_data(date_str)
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print(f" 找到 {len(entries)} 条记录")
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if not entries:
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md = f"# 今日阅读报告 · {date_str}\n\n> 暂无阅读记录\n"
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save_and_push(md, date_str)
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print("\n今日无阅读数据，已生成空报告")
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return
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# 3. AI 分析
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print(f"\n[3/4] AI 深度分析 ({len(entries)} 条)...")
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prompt = format_entries_for_prompt(entries)
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full_prompt = f"""以下是用户今日在微信读书上的划线和批注数据：
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{prompt}
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请根据这些数据生成一份高质量的今日阅读报告。"""
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ai_content = call_deepseek(full_prompt, SYSTEM_PROMPT)
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if not ai_content:
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print("[ERROR] AI 分析失败，使用备用模板")
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ai_content = "> AI 分析暂时不可用，请稍后重试。"
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# 4. 输出
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print(f"\n[4/4] 生成报告并推送...")
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md = generate_report_md(entries, ai_content, date_str)
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save_and_push(md, date_str)
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print(f"\n{'='*50}")
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print(f"每日阅读报告完成 ✅")
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print(f"{'='*50}")
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if __name__ == "__main__":
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main()
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