"""
ThirdEye bot commands — voice intelligence.
Houses cmd_voicelog and any future command handlers that don't belong in the
main bot.py module.
"""
import logging
from datetime import datetime

logger = logging.getLogger("thirdeye.bot.commands")


async def cmd_voicelog(update, context):
    """
    /voicelog [filter]
    Audit trail of all voice note decisions, actions, and blockers in this group.

    Usage:
      /voicelog                — all voice-sourced signals (last 20)
      /voicelog decisions      — only decisions from voice notes
      /voicelog actions        — only action items from voice notes
      /voicelog blockers       — only blockers from voice notes
      /voicelog @Raj           — only voice notes by Raj
      /voicelog search [query] — search voice note content
    """
    from backend.db.chroma import query_signals, get_all_signals
    from backend.agents.voice_transcriber import format_duration

    chat_id = str(update.effective_chat.id)
    args = context.args or []

    filter_type = None
    filter_speaker = None
    search_query = None

    if args:
        first = args[0].lower()
        if first == "decisions":
            filter_type = "architecture_decision"
        elif first == "actions":
            filter_type = "action_item"
        elif first == "blockers":
            filter_type = "blocker"
        elif first == "search" and len(args) > 1:
            search_query = " ".join(args[1:])
        elif first.startswith("@"):
            filter_speaker = first[1:]

    await update.message.reply_text("🎤 Searching voice notes...", parse_mode="Markdown")

    if search_query:
        raw_signals = query_signals(chat_id, search_query, n_results=30)
    else:
        raw_signals = get_all_signals(chat_id)

    # Normalise: both query_signals and get_all_signals return
    # {"document": ..., "metadata": {...}, "id": ...} shaped dicts.
    # Flatten metadata to top-level for uniform field access below.
    def _flatten(s: dict) -> dict:
        meta = s.get("metadata", {})
        flat = {**meta}
        flat.setdefault("id", s.get("id", ""))
        flat.setdefault("document", s.get("document", ""))
        return flat

    all_signals = [_flatten(s) for s in raw_signals]

    # Filter to voice-sourced signals only
    voice_signals = [
        s for s in all_signals
        if s.get("source") == "voice"
        or s.get("type") == "voice_transcript"
        or "[Voice @" in s.get("summary", "")
    ]

    if filter_type:
        voice_signals = [s for s in voice_signals if s.get("type") == filter_type]
    if filter_speaker:
        voice_signals = [
            s for s in voice_signals
            if filter_speaker.lower() in s.get("speaker", "").lower()
            or filter_speaker.lower() in str(s.get("entities", [])).lower()
        ]

    # Prefer structured signals; fall back to raw transcripts if none
    structured = [s for s in voice_signals if s.get("type") != "voice_transcript"]
    display_signals = structured if structured else voice_signals

    # Sort by timestamp descending
    def _ts(s):
        try:
            return datetime.fromisoformat(s.get("timestamp", "").replace("Z", "+00:00"))
        except Exception:
            return datetime.min

    display_signals.sort(key=_ts, reverse=True)
    display_signals = display_signals[:20]

    if not display_signals:
        await update.message.reply_text(
            "📭 No voice note signals found. Voice notes are transcribed automatically when sent here.",
            parse_mode="Markdown",
        )
        return

    type_emoji = {
        "architecture_decision": "🏗️",
        "tech_debt":             "⚠️",
        "action_item":           "📌",
        "blocker":               "🚧",
        "feature_request":       "💡",
        "promise":               "🤝",
        "risk":                  "🔴",
        "recurring_bug":         "🐛",
        "voice_transcript":      "🎤",
    }

    filter_label = ""
    if filter_type:
        filter_label = f" — {filter_type.replace('_', ' ').title()}"
    elif filter_speaker:
        filter_label = f" — @{filter_speaker}"
    elif search_query:
        filter_label = f" — '{search_query}'"

    lines = [f"🎤 *Voice Note Audit Trail*{filter_label}\n_{len(display_signals)} signal(s)_\n"]

    for sig in display_signals:
        ts = sig.get("timestamp", "")
        date_str = ""
        if ts:
            try:
                dt = datetime.fromisoformat(ts.replace("Z", "+00:00"))
                date_str = dt.strftime("%b %d")
            except Exception:
                date_str = ts[:10]

        speaker = sig.get("speaker", "")
        duration = sig.get("voice_duration", 0)
        duration_str = format_duration(int(duration)) if duration else ""
        emoji = type_emoji.get(sig.get("type", ""), "🎤")

        summary = sig.get("summary", "")
        if summary.startswith("[Voice @"):
            summary = summary.split("] ", 1)[-1] if "] " in summary else summary

        meta_parts = [f"@{speaker}" if speaker else "", date_str, duration_str]
        meta = " · ".join(filter(None, meta_parts))
        lines.append(f"{emoji} *{meta}*\n   _{summary[:100]}_\n")

    await update.message.reply_text("\n".join(lines), parse_mode="Markdown")