1101bef226
Consolidates four extract paths and two extract-chunk-embed-write pipelines into a single shared encoding module. Fixes the embedder lifecycle divergence between watcher and /api/reindex (no more 200MB reload per reindex click) and unifies failure tracking so /api/reindex failures now surface in SettingsPanel "Ingest Health". New files: - scripts/encoding.py — extract_text, chunk_text, chunk_and_embed, write_embeddings_batch - scripts/failures.py — record_ingest_failure, resolve_ingest_failure (shared by watcher.py and ingest.py) Refactored: - scripts/watcher.py — drops local extract/chunk/embed implementations and CHUNK_SIZE/CHUNK_OVERLAP/SUPPORTED constants; imports from encoding and failures. Now writes ingest_failures row on empty-text-extract (was silent return 0). - scripts/ingest.py — substantial rewrite. Exposes ingest_directory(folder, embedder=None) for in-process invocation; CLI back-compat preserved via ingest_folder wrapper. Module-level SentenceTransformer load removed. - scripts/corpus_integrity.py — imports extract_text from encoding; extract_text_for_retry function removed. - scripts/api.py — /api/reindex rewritten with BackgroundTasks (uses module-level embedder; no subprocess); new /api/reindex/status endpoint reading ~/aaronai/reindex_status.json; /api/corpus/retry imports extract_text from encoding; INGEST_SCRIPT constant removed (dead after this refactor); 409 reentrance guard prevents double-click stomping. Behavior changes: - /api/reindex no longer subprocess.Popens; runs in FastAPI BackgroundTasks threadpool, doesn't block API thread. - /api/reindex no longer reloads SentenceTransformer on each click. - /api/reindex failures newly write to ingest_failures (visible in SettingsPanel "Ingest Health" — badge will jump on first reindex). - New embeddings rows always have created_at = NOW() (canonical, server-side). - New embeddings rows always include metadata.folder field (None when not derivable). - /api/reindex returns 409 on second click while a job is running. - New /api/reindex/status endpoint for polling. Existing 9,815 NULL created_at rows remain unchanged; backfill is a separate decision if desired. 199 insertions, 256 deletions across 6 files (codebase shrinks net). Found by Track 1 inventory 2026-05-02 (Finding 11 / cross-cutting F11). Pre-commit verification: BackgroundTasks already imported, sys.path resolves correctly via script-path semantics, static import clean.
393 lines
12 KiB
Python
393 lines
12 KiB
Python
"""
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Aaron AI Watcher — Stage 1 of the encoding pipeline.
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Watches the Nextcloud directory for new or changed files.
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On detection, chunks + embeds documents in-process (no subprocess),
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then enqueues to stage_2_queue for async cascade processing.
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Design principles:
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- Embedding model loaded ONCE at startup, reused across all ingest runs
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- In-process ingest (no subprocess) — eliminates per-run model reload memory spike
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- Missed-file recovery on startup — ingests anything new since last state
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- Heartbeat file updated every loop tick — enables external health monitoring
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- Parity principle: no filtering, no decisions, faithful capture
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- Does NOT enqueue to stage_2_queue during bulk migration (SKIP_STAGE2_ENQUEUE env var)
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Architecture: Stage 1 (watcher) -> stage_2_queue -> Stage 2 (Mistral) -> stage_3_queue -> Stage 3 (Graphiti)
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"""
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import os
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import time
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import json
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import logging
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import threading
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from pathlib import Path
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import psycopg2
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from dotenv import load_dotenv
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from sentence_transformers import SentenceTransformer
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from watchdog.observers import Observer
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from watchdog.events import FileSystemEventHandler
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from encoding import extract_text, chunk_and_embed, write_embeddings_batch, SUPPORTED
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from failures import (
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record_ingest_failure as _record_failure_sql,
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resolve_ingest_failure as _resolve_failure_sql,
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)
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load_dotenv(Path.home() / "aaronai" / ".env", override=True)
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NEXTCLOUD_PATH = "/home/aaron/nextcloud/data/data/aaron/files"
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LOG_FILE = "/home/aaron/aaronai/watcher.log"
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STATE_FILE = "/home/aaron/aaronai/watcher_state.json"
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STATUS_FILE = "/home/aaron/aaronai/watcher_status.json"
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HEARTBEAT_FILE = "/home/aaron/aaronai/watcher_heartbeat"
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DEBOUNCE_SECONDS = 120
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EMBED_MODEL = "all-MiniLM-L6-v2"
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PG_DSN = os.getenv("PG_DSN")
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [watcher] %(levelname)s %(message)s",
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handlers=[logging.FileHandler(LOG_FILE)],
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)
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log = logging.getLogger("watcher")
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ingestion_lock = threading.Lock()
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ingestion_state = {
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"status": "idle", "message": "", "file_count": 0,
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"started_at": None, "finished_at": None, "last_error": "",
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}
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ingestion_thread = None
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def load_embedder():
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log.info(f"Loading embedding model: {EMBED_MODEL}")
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model = SentenceTransformer(EMBED_MODEL)
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log.info("Embedding model ready.")
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return model
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def get_pg():
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return psycopg2.connect(PG_DSN)
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def enqueue_stage2(source: str, full_text: str):
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if os.getenv("SKIP_STAGE2_ENQUEUE"):
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return
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try:
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pg = get_pg()
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cur = pg.cursor()
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cur.execute("""
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INSERT INTO stage_2_queue (source, full_text, char_length)
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VALUES (%s, %s, %s)
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ON CONFLICT (source) DO UPDATE SET
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full_text = EXCLUDED.full_text,
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char_length = EXCLUDED.char_length,
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enqueued_at = NOW(),
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completed_at = NULL,
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failed_at = NULL,
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attempts = 0
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""", (source, full_text, len(full_text)))
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pg.commit()
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pg.close()
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except Exception as e:
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log.warning(f"Stage 2 enqueue failed (non-fatal): {e}")
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def record_ingest_failure(filepath: Path, error: str):
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"""Write extraction or ingest failure to ingest_failures table for UI visibility.
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Local wrapper around failures.record_ingest_failure — opens conn, delegates,
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logs non-fatal errors so the caller never has to handle them."""
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try:
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pg = get_pg()
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try:
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_record_failure_sql(pg, filepath.name, filepath, error)
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finally:
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pg.close()
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except Exception as e:
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log.warning(f"Could not record ingest failure (non-fatal): {e}")
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def resolve_ingest_failure(source: str):
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"""Mark a previously failed file as resolved after successful ingest."""
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try:
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pg = get_pg()
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try:
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_resolve_failure_sql(pg, source)
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finally:
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pg.close()
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except Exception as e:
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log.warning(f"Could not resolve ingest failure record (non-fatal): {e}")
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def ingest_file(filepath: Path, embedder) -> int:
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if filepath.name.startswith(("~$", ".")):
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return 0
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if filepath.suffix.lower() not in SUPPORTED:
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return 0
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text = extract_text(filepath)
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if not text.strip():
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record_ingest_failure(filepath, "Text extraction failed or empty")
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return 0
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folder_rel = None
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try:
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folder_rel = str(filepath.parent.relative_to(NEXTCLOUD_PATH))
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except ValueError:
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pass
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try:
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rows = chunk_and_embed(text, filepath.name, embedder,
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filepath=filepath, folder=folder_rel)
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except Exception as e:
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log.error(f"Embedding failed for {filepath.name}: {e}")
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record_ingest_failure(filepath, f"Embedding failed: {e}")
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return 0
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if not rows:
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return 0
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source = filepath.name
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try:
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pg = get_pg()
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try:
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write_embeddings_batch(pg, rows)
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finally:
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pg.close()
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except Exception as e:
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log.error(f"pgvector write failed for {filepath.name}: {e}")
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record_ingest_failure(filepath, f"pgvector write failed: {e}")
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return 0
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log.info(f"Indexed {len(rows)} chunks: {filepath.name}")
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resolve_ingest_failure(source)
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enqueue_stage2(source, text)
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return len(rows)
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def ingest_files(paths: list, embedder, state: dict) -> dict:
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total = 0
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for path in paths:
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count = ingest_file(path, embedder)
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total += count
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state[str(path)] = str(path.stat().st_mtime)
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log.info(f"Ingestion complete. {total} chunks across {len(paths)} files.")
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return state
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def load_state() -> dict:
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if Path(STATE_FILE).exists():
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try:
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with open(STATE_FILE) as f:
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return json.load(f)
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except Exception:
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pass
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return {}
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def save_state(state: dict):
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with open(STATE_FILE, "w") as f:
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json.dump(state, f)
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def get_changed_files(state: dict) -> list:
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changed = []
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root = Path(NEXTCLOUD_PATH)
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for path in root.rglob("*"):
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if path.is_dir():
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continue
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if path.suffix.lower() not in SUPPORTED:
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continue
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if path.name.startswith((".", "~$")):
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continue
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if "Admin/Backups" in str(path) or "Backups" in path.parts:
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continue
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if "Journal/Media" in str(path):
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continue
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if state.get(str(path)) != str(path.stat().st_mtime):
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changed.append(path)
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return changed
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def set_ingestion_state(**kwargs):
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with ingestion_lock:
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ingestion_state.update(kwargs)
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def write_status(handler):
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with ingestion_lock:
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status = {
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"running": True, "timestamp": time.time(),
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"pending": handler.pending, "last_event": handler.last_event,
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"ingestion": dict(ingestion_state),
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}
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try:
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with open(STATUS_FILE, "w") as f:
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json.dump(status, f)
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except Exception:
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pass
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def write_heartbeat():
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try:
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Path(HEARTBEAT_FILE).write_text(str(time.time()))
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except Exception:
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pass
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def run_ingestion(embedder):
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state = load_state()
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changed = get_changed_files(state)
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if not changed:
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log.info("No new or changed files — skipping ingestion.")
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set_ingestion_state(status="idle", message="No changes detected", file_count=0)
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return
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count = len(changed)
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log.info(f"Found {count} new or changed files — starting ingestion...")
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set_ingestion_state(
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status="ingesting", message=f"Ingesting {count} file(s)...",
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file_count=count, started_at=time.time(), finished_at=None, last_error="",
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)
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try:
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state = ingest_files(changed, embedder, state)
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save_state(state)
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set_ingestion_state(
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status="idle",
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message=f"Last run: ingested {count} file(s) successfully",
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finished_at=time.time(),
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)
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except Exception as e:
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log.error(f"Ingestion failed: {e}")
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set_ingestion_state(
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status="error", message=f"Ingestion exception: {e}",
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last_error=str(e), finished_at=time.time(),
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)
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def start_ingestion_thread(embedder):
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global ingestion_thread
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with ingestion_lock:
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if ingestion_thread and ingestion_thread.is_alive():
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log.info("Ingestion already running — skipping.")
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return
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ingestion_thread = threading.Thread(
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target=run_ingestion, args=(embedder,), daemon=True
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)
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ingestion_thread.start()
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class IngestHandler(FileSystemEventHandler):
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def __init__(self):
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self.pending = False
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self.last_event = 0
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def _should_ignore(self, path: Path) -> bool:
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if path.name.startswith((".", "~$")):
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return True
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if "Admin/Backups" in str(path) or "Backups" in path.parts:
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return True
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if "Journal/Media" in str(path):
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return True
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return False
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def on_created(self, event):
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if event.is_directory:
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return
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path = Path(event.src_path)
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if path.suffix.lower() not in SUPPORTED or self._should_ignore(path):
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return
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log.info(f"Event: created {path}")
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self.pending = True
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self.last_event = time.time()
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def on_modified(self, event):
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if event.is_directory:
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return
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path = Path(event.src_path)
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if path.suffix.lower() not in SUPPORTED or self._should_ignore(path):
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return
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log.info(f"Event: modified {path}")
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self.pending = True
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self.last_event = time.time()
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def on_moved(self, event):
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if event.is_directory:
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return
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# Nextcloud WebDAV writes .part temp files then renames to final path.
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# src_path is the .part file; dest_path is the final filename.
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dest = Path(event.dest_path)
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if dest.suffix.lower() not in SUPPORTED or self._should_ignore(dest):
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return
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log.info(f"Event: moved -> {dest}")
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self.pending = True
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self.last_event = time.time()
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def on_closed(self, event):
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# FileClosedEvent fires on the final file after Nextcloud completes write.
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# Belt-and-suspenders catch for any write pattern not caught by on_moved.
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if event.is_directory:
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return
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path = Path(event.src_path)
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if path.suffix.lower() not in SUPPORTED or self._should_ignore(path):
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return
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log.info(f"Event: closed {path}")
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self.pending = True
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self.last_event = time.time()
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def main():
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log.info("Aaron AI Watcher starting...")
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log.info(f"Watching: {NEXTCLOUD_PATH}")
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embedder = load_embedder()
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log.info("Startup scan: checking for files missed since last run...")
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state = load_state()
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missed = get_changed_files(state)
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if missed:
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log.info(f"Startup recovery: {len(missed)} missed file(s) — ingesting now.")
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set_ingestion_state(
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status="ingesting",
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message=f"Startup recovery: ingesting {len(missed)} missed file(s)...",
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file_count=len(missed), started_at=time.time(),
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)
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try:
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state = ingest_files(missed, embedder, state)
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save_state(state)
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set_ingestion_state(
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status="idle",
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message=f"Startup recovery complete: {len(missed)} file(s) ingested.",
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finished_at=time.time(),
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)
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except Exception as e:
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log.error(f"Startup recovery failed: {e}")
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set_ingestion_state(status="error", message=str(e),
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last_error=str(e), finished_at=time.time())
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else:
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log.info("Startup scan: no missed files.")
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handler = IngestHandler()
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observer = Observer()
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observer.schedule(handler, NEXTCLOUD_PATH, recursive=True)
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observer.start()
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log.info("Observer started.")
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try:
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while True:
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write_heartbeat()
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write_status(handler)
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if handler.pending:
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elapsed = time.time() - handler.last_event
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if elapsed >= DEBOUNCE_SECONDS:
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handler.pending = False
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start_ingestion_thread(embedder)
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time.sleep(5)
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except KeyboardInterrupt:
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log.info("KeyboardInterrupt — stopping.")
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observer.stop()
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observer.join()
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log.info("Watcher stopped.")
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if __name__ == "__main__":
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main()
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