M1+M2: RAG-Pipeline mit verbindlichem Grounding

agent/-Paket: Ingest (601 Layer-2-Eintraege -> 3005 Chunks, FTS5-BM25 +
Vektoren-Cache), Hybrid-Retrieval (RRF, Stand-Boost, cross_ref-Erweiterung),
Ollama-Client (embed/chat, think-Flag-Fallback, kurzes Connect-Budget),
Systemprompt mit Zitierpflicht, Post-Validierung (zitierte IDs gemaess
Retrieved-Set, 1x Regenerierung, dann Verweigerung), FastAPI (/ask, /health,
/reindex), CLI, Goldset (31 Fragen, IDs gegen kb.json verifiziert, inkl.
ATZ-Konfliktfall + 4 Verweigerungsfaelle), Eval-Suite, Test-Chat.

41 Offline-Tests gruen. Baseline BM25-only: Hit-Rate 0,871 / Recall@8 0,855 /
MRR 0,476. Hybrid-Messung, Antwortmodus-Eval und Modell-Bake-off (M3) auf
dem Host ausstaendig (Ollama aus der Zed-Sandbox nicht erreichbar).

MEMORY.md und planung.md Umsetzungsstand aktualisiert.

tests/test_ingest.py

@@ -0,0 +1,99 @@
+"""Tests: Index-Bau (Chunking, FTS, Metadaten, Schema-Gates)."""
+import sqlite3
+
+import pytest
+
+from agent.ingest import SCHEMA, build_index
+from agent.kb import KbValidationError
+
+
+def test_build_index_chunks_and_fts(mini_index):
+    con = sqlite3.connect(mini_index.db_path)
+    try:
+        n_chunks = con.execute("SELECT COUNT(*) FROM chunks").fetchone()[0]
+        n_fts = con.execute("SELECT COUNT(*) FROM chunks_fts").fetchone()[0]
+        n_entries = con.execute(
+            "SELECT COUNT(DISTINCT entry_id) FROM chunks"
+        ).fetchone()[0]
+        assert n_entries == 3
+        assert n_chunks == n_fts and n_chunks >= 7
+        row = con.execute(
+            "SELECT entry_id, section, norm FROM chunks WHERE entry_id='lb-min-01' "
+            "AND section LIKE 'Kernwerte%'"
+        ).fetchone()
+        assert row is not None
+        # Umlaut-Folding im FTS-Text: "Lohnausgleich" normalisiert auffindbar
+        assert "lohnausgleich" in row[2]
+        meta = dict(con.execute("SELECT key, value FROM meta").fetchall())
+        assert meta["n_entries"] == "3"
+        assert meta["embed_model"] == ""  # embed_off=True
+    finally:
+        con.close()
+
+
+def test_norm_contains_tags_and_legal_bases(mini_index):
+    con = sqlite3.connect(mini_index.db_path)
+    try:
+        norm = con.execute(
+            "SELECT norm FROM chunks WHERE entry_id='lb-min-01' "
+            "AND section='Zusammenfassung'"
+        ).fetchone()[0]
+        assert "alvg" in norm  # legal_bases im FTS-Text
+        assert "azg" in norm and "19e" in norm
+    finally:
+        con.close()
+
+
+def test_rebuild_is_idempotent(mini_index):
+    stats = build_index(mini_index)
+    assert stats.n_entries == 3
+    con = sqlite3.connect(mini_index.db_path)
+    try:
+        assert con.execute("SELECT COUNT(*) FROM chunks").fetchone()[0] == stats.n_chunks
+    finally:
+        con.close()
+
+
+def test_build_index_aborts_on_gate_error(mini_cfg):
+    """Gate-Fehler (Registry kaputt) bricht den Ingest ab — kein halber Index."""
+    from pathlib import Path
+
+    (Path(mini_cfg.kb_dir) / "kb.json").write_text(
+        '{"n_entries": 0, "entries": []}', encoding="utf-8"
+    )
+    with pytest.raises(KbValidationError):
+        build_index(mini_cfg)
+
+
+def test_vectors_table_cached_across_rebuilds(mini_index):
+    """Die Vektoren-Tabelle bleibt beim Rebuild erhalten (Cache-Garantie)."""
+    con = sqlite3.connect(mini_index.db_path)
+    try:
+        con.execute(
+            "INSERT INTO vectors(content_hash, model, dim, vec) "
+            "VALUES ('deadbeef', 'bge-m3', 2, x'000000003f800000')"
+        )  # 0.0, 1.0
+        con.commit()
+    finally:
+        con.close()
+    build_index(mini_index)
+    con = sqlite3.connect(mini_index.db_path)
+    try:
+        assert con.execute(
+            "SELECT COUNT(*) FROM vectors WHERE content_hash='deadbeef'"
+        ).fetchone()[0] == 1
+    finally:
+        con.close()
+
+
+def test_schema_creates_fts5(tmp_path):
+    con = sqlite3.connect(tmp_path / "s.db")
+    try:
+        con.executescript(SCHEMA)
+        con.execute("INSERT INTO chunks_fts(rowid, norm) VALUES (1, 'testtext')")
+        hits = con.execute(
+            "SELECT rowid FROM chunks_fts WHERE chunks_fts MATCH '\"testtext\"'"
+        ).fetchall()
+        assert hits == [(1,)]
+    finally:
+        con.close()