"""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()