init: inspiration collector v1.0

.gitignore

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+# Python
+__pycache__/
+*.pyc
+*.pyo
+.env
+venv/
+.venv/
+
+# Logs
+*.log
+
+# OS
+.DS_Store
+Thumbs.db

README.md

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+# 灵感收集器 (Inspiration Collector)
+
+手机随手记灵感 → AI 自动整理 → Obsidian 自动同步
+
+## 数据流向
+
+```
+手机 Moe Memos → 服务器 Memos 实例
+                       ↓
+              Python 脚本 + DeepSeek API
+                       ↓
+              ai-insights/daily/ 中的 .md 文件
+                       ↓
+              git push → Gitea
+                       ↓
+              Obsidian Git 插件 pull → 你看到
+```
+
+## 目录结构
+
+```
+inspiration-collector/
+├── ai-insights/       # AI 生成的报告（git 追踪）
+│   ├── daily/         # 每日灵感摘要
+│   └── weekly/        # 每周灵感趋势
+├── tools/             # 核心工具模块
+│   ├── llm.py         # DeepSeek API 客户端
+│   ├── memos_client.py # Memos 数据读取
+│   ├── config.py      # 配置加载
+│   └── formatter.py   # Markdown 输出格式化
+├── analyzers/         # 分析逻辑
+│   ├── daily_digest.py  # 每日分析
+│   └── weekly_trend.py  # 每周分析
+├── scripts/           # cron 入口脚本
+│   ├── run_daily_digest.sh
+│   └── run_weekly_trend.sh
+├── secrets/           # 密钥（不入库）
+│   ├── .gitignore
+│   └── secrets.json.template
+└── README.md
+```
+
+## 部署步骤
+
+### 1. 服务器上
+
+```bash
+# 克隆仓库
+cd ~
+git clone http://localhost:3000/你的用户名/inspiration-collector.git
+
+# 配置密钥
+cp secrets/secrets.json.template secrets/secrets.json
+# 编辑 secrets.json，填入你的 DeepSeek API Key 和 Memos Token
+chmod 600 secrets/secrets.json
+
+# 测试运行
+python3 analyzers/daily_digest.py
+
+# 设置 cron
+crontab -e
+# 添加：
+# 每日 22:00 北京时间
+0 14 * * * /home/ubuntu/inspiration-collector/scripts/run_daily_digest.sh
+# 每周日 16:00 北京时间
+0 8 * * 0 /home/ubuntu/inspiration-collector/scripts/run_weekly_trend.sh
+```
+
+### 2. 笔记本 Obsidian
+
+1. `git clone` 到本地
+2. Obsidian 中打开文件夹
+3. 安装 Obsidian Git 插件
+4. 设置自动拉取

ai-insights/daily/2026-06-12_digest.md

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+---
+date: 2026-06-12
+type: daily-digest
+tags: [灵感收集器, 每日总结]
+---
+
+# 2026-06-12 灵感摘要 · 周五
+
+## AI 分析（自动生成，请勿编辑）
+
+今日灵感围绕时间流逝与生活节奏，记录个人感受与部署服务的开始。
+
+### 分类概览
+
+- **生活感悟**：4条
+- **技术记录**：2条
+
+### 关联发现
+
+- 时间倒计时的主题贯穿生活与工作，暗示对变化的敏感
+- 部署服务与记录灵感，体现个人化数字生活的开始
+
+### 待办
+
+- [ ] 记录更多关于时间流逝的感悟
+- [ ] 完善自己部署的服务功能
+
+---
+
+## 我的批注
+
+> *在这里写下你的想法、质疑、补充*

analyzers/daily_digest.py

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+"""Daily digest analyzer - fetches today's memos and generates AI summary."""
+
+import json
+import logging
+import os
+import sys
+from datetime import datetime, timezone
+
+# Add parent dir to path for local imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from tools.config import load_secrets, get_output_dir
+from tools.llm import DeepSeekClient
+from tools.memos_client import MemosClient
+from tools.formatter import format_daily_digest
+
+logger = logging.getLogger(__name__)
+
+# System prompt for daily digest
+DAILY_SYSTEM_PROMPT = """你是一个灵感整理助手。你的任务是将用户零散的灵感记录进行智能整理。
+
+请严格按照要求整理，输出纯 JSON（不要代码块标记，不要额外说明）：
+
+{
+  "summary": "一段简短的今日灵感总结，50字以内",
+  "categories": {
+    "分类名1": ["具体灵感项1", "具体灵感项2"],
+    "分类名2": ["具体灵感项3"]
+  },
+  "connections": ["跨主题关联发现1", "2-3条"],
+  "todos": ["待办事项1", "2-3条"]
+}
+
+分类原则：根据内容自然归类，分类名不超过4个字。
+关联发现：识别不同灵感之间的关联、冲突或可串联的主题。
+待办：从灵感中提取可执行的事项。"""
+
+
+def parse_ai_response(text):
+    """Parse AI response, handling both pure JSON and code-block wrapped JSON."""
+    text = text.strip()
+    # Remove markdown code block wrappers if present
+    if text.startswith("```"):
+        lines = text.split("\n")
+        # Remove first and last ``` lines
+        if lines[0].startswith("```"):
+            lines = lines[1:]
+        if lines and lines[-1].strip() == "```":
+            lines = lines[:-1]
+        text = "\n".join(lines).strip()
+
+    return json.loads(text)
+
+
+def run(memos_client, llm_client, date=None):
+    """Run daily digest analysis."""
+    date = date or datetime.now(timezone.utc)
+
+    logger.info("Daily digest started for %s", date.strftime("%Y-%m-%d"))
+
+    # Step 1: Fetch today's memos
+    memos = memos_client.list_memos(days=1)
+
+    if not memos:
+        logger.info("No memos today, skipping")
+        # Still generate a minimal file
+        content = format_daily_digest(
+            date=date,
+            categories={},
+            summary="今天没有记录灵感。",
+            connections=[],
+            todos=[]
+        )
+        output_dir = get_output_dir("daily")
+        filename = f"{date.strftime('%Y-%m-%d')}_digest.md"
+        filepath = os.path.join(output_dir, filename)
+
+        with open(filepath, "w", encoding="utf-8") as f:
+            f.write(content)
+
+        logger.info("Empty digest written to %s", filepath)
+        return filepath, 0
+
+    # Step 2: Prepare prompt
+    memo_texts = []
+    for m in memos:
+        time_str = m["created_at"][:16].replace("T", " ")
+        memo_texts.append(f"[{time_str}] {m['content']}")
+
+    user_prompt = f"请分析以下灵感记录：\n\n" + "\n".join(memo_texts)
+
+    # Step 3: Call DeepSeek API
+    raw_response = llm_client.ask(
+        system_prompt=DAILY_SYSTEM_PROMPT,
+        user_prompt=user_prompt,
+        temperature=0.3
+    )
+
+    # Step 4: Parse and format
+    try:
+        data = parse_ai_response(raw_response)
+    except (json.JSONDecodeError, KeyError) as e:
+        logger.error("Failed to parse AI response: %s", e)
+        logger.error("Raw response: %s", raw_response[:200])
+        data = {
+            "summary": f"AI 解析失败，请查看原始 Memos。",
+            "categories": {"未分类": [m["content"] for m in memos]},
+            "connections": [],
+            "todos": []
+        }
+
+    categories = data.get("categories", {})
+    connections = data.get("connections", [])
+    todos = data.get("todos", [])
+    summary = data.get("summary", "")
+
+    # Step 5: Format and write output
+    content = format_daily_digest(
+        date=date,
+        categories=categories,
+        summary=summary,
+        connections=connections,
+        todos=todos
+    )
+
+    output_dir = get_output_dir("daily")
+    filename = f"{date.strftime('%Y-%m-%d')}_digest.md"
+    filepath = os.path.join(output_dir, filename)
+
+    with open(filepath, "w", encoding="utf-8") as f:
+        f.write(content)
+
+    logger.info(
+        "Daily digest written to %s | %d memos | %d categories",
+        filepath, len(memos), len(categories)
+    )
+    return filepath, len(memos)
+
+
+def main():
+    """CLI entry point."""
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
+    )
+
+    try:
+        secrets = load_secrets()
+    except FileNotFoundError as e:
+        print(e)
+        sys.exit(1)
+
+    memos_client = MemosClient(
+        base_url=secrets.get("memos_url", "http://localhost:5230"),
+        access_token=secrets["memos_token"]
+    )
+
+    llm_client = DeepSeekClient(
+        api_key=secrets["deepseek_api_key"],
+        model=secrets.get("deepseek_model", "deepseek-chat")
+    )
+
+    filepath, count = run(memos_client, llm_client)
+    print(f"Done: {filepath} ({count} memos)")
+
+
+if __name__ == "__main__":
+    main()

analyzers/weekly_trend.py

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+"""Weekly trend analyzer - identifies patterns across a week of memos."""
+
+import json
+import logging
+import os
+import sys
+from datetime import datetime, timezone, timedelta
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from tools.config import load_secrets, get_output_dir
+from tools.llm import DeepSeekClient
+from tools.memos_client import MemosClient
+from tools.formatter import format_weekly_trend
+
+logger = logging.getLogger(__name__)
+
+WEEKLY_SYSTEM_PROMPT = """你是一个灵感趋势分析师。你的任务是对用户一周的灵感记录进行趋势分析。
+
+请输出纯 JSON（不要代码块标记，不要额外说明）：
+
+{
+  "daily_counts": {
+    "周一": 3,
+    "周二": 1
+  },
+  "categories": {
+    "分类名1": 5,
+    "分类名2": 3
+  },
+  "highlights": ["本周最有价值的灵感1", "2-3条"],
+  "insight": "一段关于用户本周思维模式的洞察，60字以内"
+}
+
+分类原则：根据内容自然归类，分类名不超过4个字。
+亮点：选出本周最有启发性、行动性、或值得继续深挖的灵感。
+洞察：识别用户本周的关注焦点变化、思维模式、或信息缺口。"""
+
+
+def parse_ai_response(text):
+    """Parse AI JSON response, handling code block wrappers."""
+    text = text.strip()
+    if text.startswith("```"):
+        lines = text.split("\n")
+        if lines[0].startswith("```"):
+            lines = lines[1:]
+        if lines and lines[-1].strip() == "```":
+            lines = lines[:-1]
+        text = "\n".join(lines).strip()
+    return json.loads(text)
+
+
+def run(memos_client, llm_client, date=None):
+    """Run weekly trend analysis."""
+    date = date or datetime.now(timezone.utc)
+    # Calculate week start (Monday) and end (Sunday)
+    weekday = date.weekday()  # 0=Monday
+    week_start = date - timedelta(days=weekday + 7)  # Previous Monday
+    week_end = week_start + timedelta(days=6)  # Sunday
+
+    logger.info(
+        "Weekly trend started for W%s (%s - %s)",
+        week_start.isocalendar()[1],
+        week_start.strftime("%Y-%m-%d"),
+        week_end.strftime("%Y-%m-%d")
+    )
+
+    # Fetch week's memos
+    memos = memos_client.list_all_memos_from_range(week_start, week_end)
+
+    if not memos:
+        logger.info("No memos this week, skipping")
+        stats = {"total": 0, "daily_counts": {}, "categories": {}}
+        content = format_weekly_trend(week_start, week_end, stats, [], "")
+        output_dir = get_output_dir("weekly")
+        filename = f"{week_start.strftime('W%Y-%m-%d')}_trend.md"
+        filepath = os.path.join(output_dir, filename)
+        with open(filepath, "w", encoding="utf-8") as f:
+            f.write(content)
+        return filepath, 0
+
+    # Prepare prompt
+    memo_texts = []
+    for m in memos:
+        time_str = m["created_at"][:16].replace("T", " ")
+        memo_texts.append(f"[{time_str}] {m['content']}")
+
+    user_prompt = (
+        f"分析以下本周（{week_start.strftime('%m/%d')} - {week_end.strftime('%m/%d')}）"
+        f"共 {len(memos)} 条灵感记录的趋势：\n\n"
+        + "\n".join(memo_texts)
+    )
+
+    # Call API
+    raw_response = llm_client.ask(
+        system_prompt=WEEKLY_SYSTEM_PROMPT,
+        user_prompt=user_prompt,
+        temperature=0.3
+    )
+
+    # Parse
+    try:
+        data = parse_ai_response(raw_response)
+    except (json.JSONDecodeError, KeyError) as e:
+        logger.error("Failed to parse AI response: %s", e)
+        data = {"daily_counts": {}, "categories": {}, "highlights": [], "insight": ""}
+
+    stats = {
+        "total": len(memos),
+        "daily_counts": data.get("daily_counts", {}),
+        "categories": data.get("categories", {}),
+    }
+    highlights = data.get("highlights", [])
+    insight = data.get("insight", "")
+
+    # Format output
+    content = format_weekly_trend(week_start, week_end, stats, highlights, insight)
+    output_dir = get_output_dir("weekly")
+    filename = f"{week_start.strftime('W%Y-%m-%d')}_trend.md"
+    filepath = os.path.join(output_dir, filename)
+
+    with open(filepath, "w", encoding="utf-8") as f:
+        f.write(content)
+
+    logger.info(
+        "Weekly trend written to %s | %d memos | %d categories",
+        filepath, len(memos), len(stats["categories"])
+    )
+    return filepath, len(memos)
+
+
+def main():
+    """CLI entry point."""
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
+    )
+
+    try:
+        secrets = load_secrets()
+    except FileNotFoundError as e:
+        print(e)
+        sys.exit(1)
+
+    memos_client = MemosClient(
+        base_url=secrets.get("memos_url", "http://localhost:5230"),
+        access_token=secrets["memos_token"]
+    )
+    llm_client = DeepSeekClient(
+        api_key=secrets["deepseek_api_key"],
+        model=secrets.get("deepseek_model", "deepseek-chat")
+    )
+
+    filepath, count = run(memos_client, llm_client)
+    print(f"Done: {filepath} ({count} memos)")
+
+
+if __name__ == "__main__":
+    main()

scripts/run_daily_digest.sh

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+#!/bin/bash
+# Daily digest cron wrapper
+# Run daily at 14:00 UTC (22:00 Beijing)
+
+set -e
+
+PROJECT_DIR="$HOME/inspiration-collector"
+LOG_FILE="$PROJECT_DIR/ai-insights/logs/daily_digest.log"
+
+mkdir -p "$(dirname "$LOG_FILE")"
+
+echo "[$(date '+%Y-%m-%d %H:%M:%S')] Starting daily digest..." >> "$LOG_FILE"
+
+cd "$PROJECT_DIR"
+python3 analyzers/daily_digest.py >> "$LOG_FILE" 2>&1
+
+# Git push to Gitea
+cd "$PROJECT_DIR"
+
+# Check if there are changes
+if [[ -n $(git status --porcelain ai-insights/) ]]; then
+    git add ai-insights/
+    git commit -m "daily digest $(date '+%Y-%m-%d')"
+    git push origin main 2>&1 | tail -3 >> "$LOG_FILE"
+    echo "Pushed to Gitea" >> "$LOG_FILE"
+else
+    echo "No changes to push" >> "$LOG_FILE"
+fi
+
+echo "[$(date '+%Y-%m-%d %H:%M:%S')] Daily digest done." >> "$LOG_FILE"

scripts/run_weekly_trend.sh

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+#!/bin/bash
+# Weekly trend cron wrapper
+# Run every Sunday at 08:00 UTC (16:00 Beijing)
+
+set -e
+
+PROJECT_DIR="$HOME/inspiration-collector"
+LOG_FILE="$PROJECT_DIR/ai-insights/logs/weekly_trend.log"
+
+mkdir -p "$(dirname "$LOG_FILE")"
+
+echo "[$(date '+%Y-%m-%d %H:%M:%S')] Starting weekly trend..." >> "$LOG_FILE"
+
+cd "$PROJECT_DIR"
+python3 analyzers/weekly_trend.py >> "$LOG_FILE" 2>&1
+
+# Git push to Gitea
+cd "$PROJECT_DIR"
+if [[ -n $(git status --porcelain ai-insights/) ]]; then
+    git add ai-insights/
+    git commit -m "weekly trend W$(date '+%V')"
+    git push origin main 2>&1 | tail -3 >> "$LOG_FILE"
+    echo "Pushed to Gitea" >> "$LOG_FILE"
+else
+    echo "No changes to push" >> "$LOG_FILE"
+fi
+
+echo "[$(date '+%Y-%m-%d %H:%M:%S')] Weekly trend done." >> "$LOG_FILE"

secrets/.gitignore

@@ -0,0 +1,4 @@
+# Secrets directory - never checked into git
+# Copy secrets.json.template to secrets.json and fill in your keys
+secrets.json
+*.json

secrets/secrets.json.template

@@ -0,0 +1,6 @@
+{
+    "memos_url": "http://localhost:5230",
+    "memos_token": "YOUR_MEMOS_TOKEN_HERE",
+    "deepseek_api_key": "YOUR_DEEPSEEK_API_KEY_HERE",
+    "deepseek_model": "deepseek-chat"
+}

tools/config.py

@@ -0,0 +1,35 @@
+"""Configuration loader - loads secrets from secrets.json"""
+
+import json
+import os
+from pathlib import Path
+
+# Default location: ~/inspiration-collector/secrets/secrets.json on server
+SECRETS_PATH = os.environ.get(
+    "IC_SECRETS_PATH",
+    str(Path.home() / "inspiration-collector" / "secrets" / "secrets.json")
+)
+
+DEFAULT_OUTPUT_DIR = os.environ.get(
+    "IC_OUTPUT_DIR",
+    str(Path.home() / "inspiration-collector" / "ai-insights")
+)
+
+
+def load_secrets(path=None):
+    """Load secrets from JSON file. Returns dict with api_key, memos_token, memos_url."""
+    path = path or SECRETS_PATH
+    if not os.path.exists(path):
+        raise FileNotFoundError(
+            f"Secrets file not found: {path}\n"
+            f"Copy secrets/secrets.json.template to {path} and fill in your keys."
+        )
+    with open(path) as f:
+        return json.load(f)
+
+
+def get_output_dir(subdir="daily"):
+    """Get output directory for AI-generated insights."""
+    base = DEFAULT_OUTPUT_DIR
+    os.makedirs(os.path.join(base, subdir), exist_ok=True)
+    return os.path.join(base, subdir)

tools/formatter.py

@@ -0,0 +1,122 @@
+"""Markdown formatter - converts AI analysis results to beautiful .md files."""
+
+from datetime import datetime
+
+
+def format_daily_digest(date, categories, summary, connections, todos):
+    """Format daily digest markdown file."""
+    date_str = date.strftime("%Y-%m-%d")
+    weekday = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"][date.weekday()]
+
+    lines = []
+    lines.append("---")
+    lines.append(f"date: {date_str}")
+    lines.append("type: daily-digest")
+    lines.append("tags: [灵感收集器, 每日总结]")
+    lines.append("---")
+    lines.append("")
+    lines.append(f"# {date_str} 灵感摘要 · {weekday}")
+    lines.append("")
+
+    # Summary
+    lines.append("## AI 分析（自动生成，请勿编辑）")
+    lines.append("")
+    lines.append(summary)
+    lines.append("")
+
+    # Categories
+    if categories:
+        lines.append("### 分类概览")
+        lines.append("")
+        for cat, items in categories.items():
+            count = len(items) if isinstance(items, list) else items
+            lines.append(f"- **{cat}**：{count}条")
+        lines.append("")
+
+    # Connections
+    if connections:
+        lines.append("### 关联发现")
+        lines.append("")
+        for conn in connections:
+            lines.append(f"- {conn}")
+        lines.append("")
+
+    # Todos
+    if todos:
+        lines.append("### 待办")
+        lines.append("")
+        for todo in todos:
+            lines.append(f"- [ ] {todo}")
+        lines.append("")
+
+    # User annotation area
+    lines.append("---")
+    lines.append("")
+    lines.append("## 我的批注")
+    lines.append("")
+    lines.append("> *在这里写下你的想法、质疑、补充*")
+    lines.append("")
+
+    return "\n".join(lines)
+
+
+def format_weekly_trend(start_date, end_date, stats, highlights, insight):
+    """Format weekly trend markdown file."""
+    week_start = start_date.strftime("%m/%d")
+    week_end = end_date.strftime("%m/%d")
+    week_number = start_date.isocalendar()[1]
+
+    lines = []
+    lines.append("---")
+    lines.append(f"date: {start_date.year}-W{week_number}")
+    lines.append("type: weekly-trend")
+    lines.append("tags: [灵感收集器, 每周趋势]")
+    lines.append("---")
+    lines.append("")
+    lines.append(f"# 第 {week_number} 周灵感趋势（{week_start} - {week_end}）")
+    lines.append("")
+
+    # Stats
+    lines.append("## AI 分析（自动生成，请勿编辑）")
+    lines.append("")
+    lines.append(f"本周共记录 **{stats.get('total', 0)}** 条灵感。")
+    lines.append("")
+
+    if stats.get("daily_counts"):
+        lines.append("### 每日活跃度")
+        lines.append("")
+        for day, count in stats["daily_counts"].items():
+            bar = "█" * count if count > 0 else "▏"
+            lines.append(f"- {day}：{bar} {count}条")
+        lines.append("")
+
+    if stats.get("categories"):
+        lines.append("### 主题分布")
+        lines.append("")
+        for cat, count in stats["categories"].items():
+            pct = count / stats["total"] * 100 if stats["total"] else 0
+            lines.append(f"- **{cat}**：{count}条（{pct:.0f}%）")
+        lines.append("")
+
+    if highlights:
+        lines.append("### 本周亮点")
+        lines.append("")
+        for h in highlights:
+            lines.append(f"- {h}")
+        lines.append("")
+
+    if insight:
+        lines.append("### 值得关注的模式")
+        lines.append("")
+        lines.append(insight)
+        lines.append("")
+
+    # User annotation
+    lines.append("---")
+    lines.append("")
+    lines.append("## 我的批注")
+    lines.append("")
+    lines.append("> *有什么想补充的写在下面*")
+    lines.append("")
+
+    return "\n".join(lines)

tools/llm.py

@@ -0,0 +1,71 @@
+"""DeepSeek API client - OpenAI-compatible, zero extra dependencies."""
+
+import json
+import logging
+import time
+import requests
+
+logger = logging.getLogger(__name__)
+
+
+class DeepSeekClient:
+    """Client for DeepSeek API (OpenAI-compatible format)."""
+
+    BASE_URL = "https://api.deepseek.com/v1/chat/completions"
+
+    def __init__(self, api_key, model="deepseek-chat", temperature=0.7, max_retries=3):
+        self.api_key = api_key
+        self.model = model
+        self.temperature = temperature
+        self.max_retries = max_retries
+        self.session = requests.Session()
+        self.session.headers.update({
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json"
+        })
+
+    def ask(self, system_prompt, user_prompt, temperature=None):
+        """Send a chat completion request. Returns response text."""
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_prompt}
+        ]
+        payload = {
+            "model": self.model,
+            "messages": messages,
+            "temperature": temperature or self.temperature
+        }
+
+        last_error = None
+        for attempt in range(self.max_retries):
+            try:
+                resp = self.session.post(self.BASE_URL, json=payload, timeout=60)
+                resp.raise_for_status()
+                data = resp.json()
+                result = data["choices"][0]["message"]["content"]
+                logger.info(
+                    "DeepSeek API OK | model=%s | input=%d chars | output=%d chars",
+                    self.model, len(user_prompt), len(result)
+                )
+                return result
+
+            except requests.exceptions.Timeout:
+                last_error = "Timeout"
+                logger.warning("Attempt %d/%d timed out", attempt + 1, self.max_retries)
+            except requests.exceptions.HTTPError as e:
+                last_error = str(e)
+                logger.warning("Attempt %d/%d HTTP error: %s", attempt + 1, self.max_retries, e)
+                if "insufficient_quota" in str(e).lower() or "invalid_api_key" in str(e).lower():
+                    raise  # don't retry these
+            except (json.JSONDecodeError, KeyError) as e:
+                last_error = f"Parse error: {e}"
+                logger.warning("Attempt %d/%d parse error: %s", attempt + 1, self.max_retries, e)
+
+            if attempt < self.max_retries - 1:
+                sleep_time = 2 ** attempt
+                logger.info("Retrying in %ds...", sleep_time)
+                time.sleep(sleep_time)
+
+        raise RuntimeError(
+            f"DeepSeek API failed after {self.max_retries} retries. Last error: {last_error}"
+        )

tools/memos_client.py

@@ -0,0 +1,138 @@
+"""Memos API client - fetch memos using Connect RPC protocol."""
+
+import logging
+from datetime import datetime, timezone, timedelta
+
+import requests
+
+logger = logging.getLogger(__name__)
+
+
+class MemosClient:
+    """Client for self-hosted Memos API (Connect RPC protocol)."""
+
+    def __init__(self, base_url, access_token):
+        self.base_url = base_url.rstrip("/")
+        self.session = requests.Session()
+        self.session.headers.update({
+            "Authorization": f"Bearer {access_token}",
+            "Content-Type": "application/json",
+        })
+        self._user_id = None
+
+    def get_user(self):
+        """Get current user info via Connect RPC."""
+        resp = self.session.post(
+            f"{self.base_url}/memos.api.v1.AuthService/GetCurrentUser",
+            json={},
+            timeout=10
+        )
+        resp.raise_for_status()
+        data = resp.json()
+        user = data.get("user", data)
+        self._user_id = user.get("name", "")
+        logger.info("Memos user: %s (%s)", user.get("username"), self._user_id)
+        return user
+
+    def get_user_id(self):
+        """Get current user's resource name (e.g. 'users/FXY')."""
+        if not self._user_id:
+            self.get_user()
+        return self._user_id
+
+    def list_memos(self, days=1, page_size=100):
+        """Fetch memos from the last N days via Connect RPC."""
+        user = self.get_user_id()
+        since = (datetime.now(timezone.utc) - timedelta(days=days)).isoformat()
+
+        # Connect RPC uses POST with JSON body
+        payload = {
+            "pageSize": page_size,
+            "filter": f"creator == '{user}'",
+        }
+
+        resp = self.session.post(
+            f"{self.base_url}/memos.api.v1.MemoService/ListMemos",
+            json=payload,
+            timeout=15
+        )
+        resp.raise_for_status()
+        data = resp.json()
+
+        memos = data.get("memos", [])
+        logger.info("Memos API OK | fetched %d memos", len(memos))
+
+        # Filter by time client-side (Connect RPC filter might not work as expected)
+        results = []
+        since_dt = datetime.now(timezone.utc) - timedelta(days=days)
+        for m in memos:
+            created = m.get("createTime", "")
+            try:
+                created_dt = datetime.fromisoformat(created.replace("Z", "+00:00"))
+            except (ValueError, AttributeError):
+                created_dt = datetime.now(timezone.utc)
+
+            if created_dt < since_dt:
+                continue
+
+            results.append({
+                "id": m.get("name", "").split("/")[-1],
+                "content": m.get("content", ""),
+                "created_at": created,
+                "tags": self._extract_tags(m.get("content", "")),
+                "visibility": m.get("visibility", ""),
+            })
+
+        logger.info(
+            "Filtered to %d memos since %s", len(results), since[:10]
+        )
+        return results
+
+    def list_all_memos_from_range(self, start_date, end_date, page_size=200):
+        """Fetch memos within a date range via Connect RPC."""
+        user = self.get_user_id()
+
+        payload = {"pageSize": page_size}
+
+        resp = self.session.post(
+            f"{self.base_url}/memos.api.v1.MemoService/ListMemos",
+            json=payload,
+            timeout=15
+        )
+        resp.raise_for_status()
+        data = resp.json()
+
+        memos = data.get("memos", [])
+        logger.info("Memos API OK | fetched %d memos total", len(memos))
+
+        # Client-side date range filtering
+        results = []
+        for m in memos:
+            created = m.get("createTime", "")
+            try:
+                created_dt = datetime.fromisoformat(created.replace("Z", "+00:00"))
+            except (ValueError, AttributeError):
+                continue
+
+            if created_dt < start_date or created_dt > end_date:
+                continue
+
+            results.append({
+                "id": m.get("name", "").split("/")[-1],
+                "content": m.get("content", ""),
+                "created_at": created,
+                "tags": self._extract_tags(m.get("content", "")),
+                "visibility": m.get("visibility", ""),
+            })
+
+        logger.info(
+            "Filtered to %d memos in range %s - %s",
+            len(results), start_date.strftime("%m/%d"), end_date.strftime("%m/%d")
+        )
+        return results
+
+    @staticmethod
+    def _extract_tags(content):
+        """Extract #tags from memo content."""
+        import re
+        return re.findall(r"#(\w[\w\-]*)", content)