"""Orchestrate memory extraction from all browser sources."""

import logging
import time
from typing import Optional, Set

from ai_browser_profile.db import MemoryDB
from ai_browser_profile.embeddings import setup_embeddings_table
from ai_browser_profile.ingestors.browser_detect import detect_browsers
from ai_browser_profile.ingestors.webdata import ingest_webdata
from ai_browser_profile.ingestors.history import ingest_history
from ai_browser_profile.ingestors.logins import ingest_logins
from ai_browser_profile.ingestors.bookmarks import ingest_bookmarks

log = logging.getLogger(__name__)


def _timed(name, func, *args, **kwargs):
    """Run func with timing, log duration."""
    log.info(f"[{name}] starting...")
    t0 = time.monotonic()
    result = func(*args, **kwargs)
    elapsed = time.monotonic() - t0
    log.info(f"[{name}] done in {elapsed:.1f}s")
    return result


def extract_memories(memories_db_path: str = "memories.db",
                     browsers: Optional[Set[str]] = None,
                     skip_indexeddb: bool = False,
                     skip_localstorage: bool = False,
                     skip_notion: bool = False) -> MemoryDB:
    """Build the memories database directly from browser files.

    Args:
        memories_db_path: Output database path.
        browsers: Set of browser names to scan (None = all).
        skip_indexeddb: Skip IndexedDB extraction (requires ccl_chromium_reader).
        skip_localstorage: Skip Local Storage extraction (requires ccl_chromium_reader).
    """
    total_start = time.monotonic()
    mem = MemoryDB(memories_db_path, defer_embeddings=True)
    from ai_browser_profile.ingestors.browser_detect import permission_denied_paths
    profiles = detect_browsers(allowed=browsers)
    log.info(f"Extracting memories from {len(profiles)} profiles...")

    # 1. Autofill — saved form data, addresses, credit cards
    _timed("Autofill", ingest_webdata, mem)

    # 2. History — tools and services used
    _timed("History", ingest_history, mem, profiles)

    # 3. Bookmarks — interests and saved links
    _timed("Bookmarks", ingest_bookmarks, mem, profiles)

    # 4. Logins — saved accounts per site
    _timed("Logins", ingest_logins, mem, profiles)

    # 5. LinkedIn — connections from Local Storage
    if not skip_localstorage:
        try:
            from ai_browser_profile.ingestors.localstorage import ingest_localstorage
            _timed("LinkedIn", ingest_localstorage, mem, profiles)
        except ImportError:
            log.warning("ccl_chromium_reader not installed — skipping LinkedIn")

    # 6. Notion — workspace contacts, pages, meetings
    if not skip_notion:
        try:
            from ai_browser_profile.ingestors.notion import ingest_notion
            _timed("Notion", ingest_notion, mem)
        except Exception as e:
            log.warning(f"Notion ingestor failed: {e}")

    # -- Interim profile: core data is ready, show it before slow steps --
    mem.conn.commit()
    # Run cleanup before showing profile so noise is removed
    from clean import run_cleanup
    log.info("Running interim cleanup...")
    mem.close()
    run_cleanup(db_path=memories_db_path)
    mem = MemoryDB(memories_db_path, defer_embeddings=True)
    interim_profile = mem.profile_text()

    # Emit structured browser summary so callers can show transparency
    detected_browsers = sorted(set(p.browser for p in profiles))
    denied_browsers = sorted(set(
        p.browser for p in profiles
        if any(str(p.path) in str(denied) for denied in permission_denied_paths)
    ))
    print(f"BROWSERS_SCANNED: {','.join(detected_browsers)}", flush=True)
    if denied_browsers:
        print(f"BROWSERS_PERMISSION_DENIED: {','.join(denied_browsers)}", flush=True)

    log.info(f"Interim profile ready (WhatsApp + embeddings still running):\n{interim_profile}")

    # 7. WhatsApp — contacts from IndexedDB (slow, runs last)
    if not skip_indexeddb:
        try:
            from ai_browser_profile.ingestors.indexeddb import ingest_indexeddb
            _timed("WhatsApp", ingest_indexeddb, mem, profiles)
        except ImportError:
            log.warning("ccl_chromium_reader not installed — skipping WhatsApp")

    mem.conn.commit()

    # 8. Embeddings — backfill all at once (loads ONNX model once, batches efficiently)
    mem._vec_ready = setup_embeddings_table(mem.conn)
    mem._defer_embeddings = False
    if mem._vec_ready:
        _timed("Embeddings", mem.backfill_embeddings)

    total_elapsed = time.monotonic() - total_start
    stats = mem.stats()
    log.info(
        f"Memories: {stats['total_memories']} total, "
        f"tags: {', '.join(f'{t}={c}' for t, c in list(stats['by_tag'].items())[:10])}"
    )
    log.info(f"Total extraction time: {total_elapsed:.1f}s")
    return mem