feat(stack): full overhaul — hardening, ops tooling, monitoring, analytics, chatbot

Security: deep /api/health (DB+MinIO probes, 503 on failure) + /api/live;
rate-limited public forms with honeypots; real client IP behind Traefik
(--proxy-headers); TipTap URL sanitization on write (nh3); non-root
containers + slim .dockerignore; prod MinIO console bound to 127.0.0.1;
HSTS/nosniff on TLS routers; JWT 8h; no default credentials in code.

Reliability: Alembic migrations (create_all baseline); graceful shutdown
(exec uvicorn); hardened backups (checksums, sanity check, freshness gauge,
optional rclone off-site) + restore.sh + hourly db-backup sidecar (ops
profile); stack.sh ops tooling (deploy/logs/health/backup/restore/monitoring);
.gitattributes LF for shell scripts.

Orchestration: json-file log rotation, pinned images, per-service memory
limits, edge/internal networks, Traefik ping/accesslog/metrics + flood
limiter, conditional minio-setup, pgvector db image, one-shot db-init
(umami + aramesh_chatbot databases).

Chatbot: unified from site-chatbot branch (RAG + pgvector, SSE, ChatWidget).

Monitoring: Prometheus/Alertmanager/Loki/Promtail/Grafana + cAdvisor,
node/postgres/blackbox exporters, provisioned dashboards and 10 alert
rules; alerts delivered to Bale (tapi.bale.ai — Telegram-compatible).

Analytics: Umami on shared Postgres, build-time tracker injection, custom
events (contact/newsletter/phone/chat/lang) via frontend/src/analytics.ts.

Hygiene: CSV export for contact messages and subscribers; upload image
optimization (Pillow); CI script + GitHub-compatible workflow; audit.sh;
gen-env.sh for strong credentials.

chatbot/indexing.py

@@ -0,0 +1,55 @@
+"""ایندکس ترکیبی روی pgvector + BM25 در حافظه.
+
+بردارها در pgvector (دیتابیس اختصاصی چت‌بات) به‌صورت افزایشی همگام می‌شوند —
+فقط سطرهای جدید یا تغییر یافته امبد می‌شوند. BM25 چون سبک است در هر شروع
+از روی همان سطرها ساخته می‌شود و نیازی به کش دیسکی ندارد.
+"""
+
+import logging
+import time
+
+from rank_bm25 import BM25Okapi
+
+from . import content as content_mod
+from .config import settings
+from .persian import tokenize
+from . import vectorstore
+
+log = logging.getLogger(__name__)
+
+
+class SiteIndex:
+    """حالت در حافظهٔ بازیابی — سندها (برای BM25) و وضعیت آماده بودن."""
+
+    def __init__(self) -> None:
+        self.docs: list[dict] = []
+        self.bm25: BM25Okapi | None = None
+
+    @property
+    def ready(self) -> bool:
+        return self.bm25 is not None and bool(self.docs)
+
+
+INDEX = SiteIndex()
+
+
+def sync_index(force_rebuild: bool = False) -> dict:
+    """همگام‌سازی کامل: محتوا → قطعه → pgvector (افزایشی) → ساخت BM25.
+
+    خروجی: آمار همگام‌سازی. خطای اتصال به دیتابیس بالا فرستاده می‌شود.
+    """
+    start = time.time()
+
+    vectorstore.ensure_schema()
+
+    docs = content_mod.fetch_site_documents(settings.database_url)
+    chunks = content_mod.chunk_documents(docs)
+    stats = vectorstore.sync_chunks(chunks, force=force_rebuild)
+
+    INDEX.docs = vectorstore.fetch_all_chunks()
+    corpus_tokens = [tokenize(d["text"]) for d in INDEX.docs]
+    INDEX.bm25 = BM25Okapi(corpus_tokens) if corpus_tokens else None
+
+    log.info("Index ready in %.1fs (%d vectors, %d docs, %s)",
+             time.time() - start, len(INDEX.docs), len(chunks), stats)
+    return stats