Apply Q1–Q3 decisions: GraphDB/SPARQL, reuse Qdrant, self-host embeddings via TEI

- Q1 → Ontotext GraphDB (SPARQL). docs/08 fully rewritten with RDF schema,
  example SPARQL queries (transitive deps via property paths, time-windowed
  topic counts, cross-pillar joins via nexa:vectorId).
- Q2 → reuse qdrant_scientific with nexa_* collection prefix; docs/09 step 2
  now points there explicitly.
- Q3 → no OpenAI embeddings. Self-host on the docker host. Use TEI
  (HuggingFace text-embeddings-inference) — single Rust binary, ~500 MB image,
  OpenAI-compatible — instead of Ollama, since we only need embeddings.
- docs/09 Phase-3.4 add-on simplified to a single Ontotext compose snippet
  (Neo4j option dropped) plus repo creation curl.
- docs/11 Q3 marked resolved; new Q15 picks the model (bge-m3 vs nomic-embed)
  and adds the open question of whether SAIA already proxies an embedding
  model that would let us skip TEI entirely.
- docs/03 + CLAUDE.md updated with the new decisions so future runs don't
  re-litigate.

CLAUDE.md

@@ -20,6 +20,11 @@ This file tells future automated runs what they need to know about this repo.
   - VM 100 haos — Home Assistant.
 - **Already-running services on docker host** (don't redeploy):
   - Memos `:5230`, n8n `:5678`, LiteLLM `:4000` (UI LobeHub `:3210`), Qdrant (`qdrant_scientific`), ntfy `:7998`, Karakeep/Hoarder, Vaultwarden `:11001`, Pocket-ID `:1411`, Immich, Audiobookshelf, Paperless-ngx, Traccar, Prowlarr, plus MCP containers (`crawl4ai-mcp`, `markitdown-mcp`, `papersearch-mcp`).
+- **Decided for Nexa** (don't re-litigate without user input):
+  - Vector store: **reuse `qdrant_scientific`** with `nexa_*` collection prefix.
+  - Embeddings: **TEI** (HF text-embeddings-inference), self-hosted, `bge-m3` candidate (Q15 still pending the model name).
+  - Graph store: **Ontotext GraphDB** (SPARQL/RDF), Phase 3.4.
+  - Chat model: SAIA via LiteLLM virtual key.
 
 ## When working on Nexa