refactor(search): remove NLP/smart-search feature entirely (#772)

## Summary

- Removes the NLP/smart-search feature completely — the feature was too unreliable and slow; users get better results with the regular search filters
- Deletes the entire backend `search/` package (NlSearchController, NlQueryParserService, NlpClient, NlSearchRateLimiter — 14 classes + 6 test classes)
- Deletes the `nlp-service/` Python microservice (FastAPI, rapidfuzz, DB-backed person matching)
- Removes all frontend NL search components: SmartModeToggle, SmartSearchStatus, InterpretationChipRow, DisambiguationPicker, chip-types, theme-chip-removal
- Strips smart-mode logic from SearchFilterBar and documents/+page.svelte
- Removes `SMART_SEARCH_UNAVAILABLE` / `SMART_SEARCH_RATE_LIMITED` error codes from backend, frontend types, and all three i18n files (de/en/es)
- Removes `nlp-service` container and `APP_NLP_BASE_URL` from both docker-compose files
- Removes Ollama/NLP Prometheus scrape job and Grafana dashboard
- Deletes ADRs 028 (×2), 034, 035

## Test plan

- [ ] Backend compiles: `cd backend && ./mvnw compile -q` → BUILD SUCCESS
- [ ] Frontend server tests pass: `cd frontend && npm run test -- --project=server`
- [ ] No NLP/smart-search references remain in source: `grep -r "SmartSearch\|NlSearch\|nlp-service\|SMART_SEARCH" backend/src frontend/src`
- [ ] `docker compose config` validates both compose files
- [ ] Search page loads, filter bar works, no smart-mode toggle visible

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-authored-by: Marcel <marcel@familienarchiv>
Reviewed-on: #772

docs/adr/034-remove-nl-search.md

@@ -0,0 +1,53 @@
+# ADR-034 — Remove NL/smart-search (supersedes ADR-028 ×2, ADR-034-ollama, ADR-035)
+
+**Date:** 2026-06-07
+**Status:** Accepted
+**Issue:** #772
+**Supersedes:** ADR-028 (nl-search-ollama), ADR-028 (ollama-docker-compose-service), ADR-034 (ollama-production-deployment-and-keep-alive), ADR-035 (rule-based-nlp-service)
+
+---
+
+## Context
+
+The natural-language search feature ("KI-Suche" / smart search) allowed users to enter
+free-form queries like *"Was hat Walter an Emma im Krieg geschrieben?"* and have them
+interpreted by an LLM into structured filters (persons, tags, date range, keywords).
+
+The feature went through two major iterations:
+1. **Ollama integration** (ADR-028): an `ollama` Docker service running a local LLM
+   (llama3.2/gemma3) parsed queries via a JSON-mode prompt.
+2. **Rule-based NLP service** (ADR-035): after Ollama proved too slow and unreliable on
+   CPU-only hardware, a Python FastAPI microservice (`nlp-service`, port 8001) replaced
+   it with deterministic regex + spaCy parsing plus a lightweight LLM call.
+
+Both approaches shared the same fundamental problem: inference on the production server
+(Hetzner Serverbörse, no GPU, 64 GB RAM, i7-6700) was too slow to be useful, with
+typical query latencies of 10–30 seconds. Users got better and faster results from
+the existing keyword search with date/person/tag filters.
+
+## Decision
+
+**Remove the NL search feature entirely.** The Python `nlp-service` microservice, the
+Spring Boot `search/` package (`NlSearchController`, `NlQueryParserService`,
+`RestClientNlpClient`, `NlSearchRateLimiter`, and all supporting classes), the frontend
+NL search components (`SmartModeToggle`, `SmartSearchStatus`, `InterpretationChipRow`,
+`DisambiguationPicker`), the related Docker Compose services, Prometheus scrape job,
+Grafana dashboard, and all i18n keys are removed.
+
+The existing structured search (FTS keyword + person/tag/date/directional filters) is
+sufficient for the archive's current audience and search workload.
+
+## Consequences
+
+- **Capability removed:** users can no longer enter free-form natural-language queries.
+  They must use the structured filter bar (keyword text box + person/tag/date/directional
+  dropdowns). For documents where these filters are sufficient, there is no regression.
+- **Operational simplification:** the Docker Compose stack loses two services
+  (`nlp-service` and previously `ollama`/`ollama-model-init`). Memory budget on the
+  production host is freed. No external model weights need to be kept warm.
+- **Future reinstatement:** if a GPU-capable host becomes available, re-implementing
+  server-side LLM inference would be straightforward given the clean separation of the
+  `NlSearchController` entry point. However, this ADR deliberately avoids leaving dead
+  infrastructure or stub code in place — start clean if and when that becomes viable.
+- **No data or schema change:** only query/endpoint code and Docker services are removed.
+  The `documents`, `persons`, and `tags` tables and their FTS indexes are untouched.