Add Maria WhatsApp+RAG bridge as a service (LXC 171)

Move the /tmp prototype (Baileys bridge + RAG consumer) into git as a
proper sibling project to discord-bridge/: own systemd --user units
(whatsapp bridge, rag consumer, dashboard, periodic Drive sync timer),
a filesystem document store with a stdlib control dashboard (start/
stop/restart, document CRUD, reindex, Google Drive sync via rclone),
and an idempotent ops/install.sh following the same conventions.

Co-Authored-By: Claude Agent <noreply@anthropic.com>

proxmox/lxc171-claude-agent/maria-whatsapp-bridge/rag/indexer.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python3
+"""(Re)construieste rag_index.json din toate documentele din depozit (store.py),
+cu embeddings Ollama. Rulat manual sau declansat din dashboard (`/api/reindex`)."""
+
+from __future__ import annotations
+
+import json
+import re
+import sys
+
+import requests
+
+import config
+import store
+
+
+def chunk_text(text: str) -> list[str]:
+    # imparte pe linii goale in paragrafe, uneste bucatile mici cu urmatoarea
+    raw_parts = re.split(r"\n\s*\n", text.strip())
+    chunks: list[str] = []
+    buffer = ""
+    for part in raw_parts:
+        part = part.strip()
+        if not part:
+            continue
+        buffer = f"{buffer}\n\n{part}" if buffer else part
+        if len(buffer) >= 200:
+            chunks.append(buffer)
+            buffer = ""
+    if buffer:
+        chunks.append(buffer)
+    return chunks
+
+
+def embed(text: str) -> list[float]:
+    resp = requests.post(
+        f"{config.get('OLLAMA_URL')}/api/embeddings",
+        json={"model": config.get("EMBED_MODEL"), "prompt": text},
+        timeout=60,
+    )
+    resp.raise_for_status()
+    return resp.json()["embedding"]
+
+
+def build() -> dict:
+    entries = []
+    docs = store.list_documents()
+    for doc in docs:
+        text = store.read_document(doc["name"])
+        for i, chunk in enumerate(chunk_text(text)):
+            vec = embed(chunk)
+            entries.append({"source": doc["name"], "chunk": i, "text": chunk, "embedding": vec})
+    config.STATE_DIR.mkdir(parents=True, exist_ok=True)
+    config.INDEX_FILE.write_text(json.dumps(entries, ensure_ascii=False), encoding="utf-8")
+    return {"documents": len(docs), "chunks": len(entries)}
+
+
+if __name__ == "__main__":
+    result = build()
+    print(
+        f"[indexer] {result['documents']} documente, {result['chunks']} chunk-uri -> {config.INDEX_FILE}",
+        file=sys.stderr,
+    )