fix: support qdrant-only vector maintenance

harness/tests/test_qdrant_cli_commands.py

@@ -0,0 +1,164 @@
+from __future__ import annotations
+
+import json
+from datetime import UTC, datetime
+from pathlib import Path
+from types import SimpleNamespace
+
+from typer.testing import CliRunner
+
+from tht.cli import app
+from tht.memory import MemoryRecord, save_registry
+
+
+class _FakeEmbedder:
+    def embed_documents(self, documents):
+        return [[0.1] * 4 for _ in documents]
+
+
+class _FakeVectorStore:
+    def __init__(self):
+        self.upserts = []
+        self.deleted = []
+
+    def existing_hashes(self, collection, kinds):
+        return {}
+
+    def upsert(self, collection, records):
+        self.upserts.append((collection, records))
+        return len(records)
+
+    def delete_kinds(self, collection, kinds):
+        self.deleted.append((collection, list(kinds)))
+        return 3
+
+
+def _qdrant_runtime_config(tmp_path: Path) -> Path:
+    cfg = tmp_path / "workspace.yaml"
+    cfg.write_text(
+        f"""
+runtime_identity:
+  workspace_id: psd-clinical
+  workspace_revision: {'a' * 40}
+dwh:
+  type: postgres_direct
+  connection: {{database: analytics, schema: mart, user: reader, password: secret}}
+vectors:
+  type: qdrant
+  base_url: http://qdrant:6333
+  collection: psd-clinical
+roots:
+  sessions: {tmp_path / 'sessions'}
+  artifacts: {tmp_path / 'artifacts'}
+  indexes: {tmp_path / 'indexes'}
+embeddings:
+  provider: ollama_internal
+  base_url: http://embedding:11434
+  model: qwen3-embedding:0.6b
+  dim: 1024
+"""
+    )
+    return cfg
+
+
+def _write_schema_artifacts(tmp_path: Path) -> None:
+    (tmp_path / "artifacts" / "mschema").mkdir(parents=True, exist_ok=True)
+    (tmp_path / "artifacts" / "mschema" / "physical.yaml").write_text(
+        """
+database: analytics
+schema: mart
+introspected_at: 2026-01-01T00:00:00+00:00
+tables:
+  fact_patient:
+    comment: Patients
+    columns:
+      id:
+        type: bigint
+"""
+    )
+    (tmp_path / "artifacts" / "mschema" / "annotations.yaml").write_text(
+        "tables: {}\n"
+    )
+
+
+def _memory_record() -> MemoryRecord:
+    return MemoryRecord(
+        id="mem-0001",
+        ts=datetime(2026, 1, 1, tzinfo=UTC),
+        session_id="s1",
+        decision_seq=7,
+        type="concept_clarified",
+        subject="paziente attivo",
+        detail="flag_attivo = TRUE",
+        rationale="r",
+        question_context="dammi i pazienti attivi",
+        tables=[],
+        concepts=["paziente attivo"],
+    )
+
+
+def test_vector_index_schema_accepts_qdrant_only_runtime_config(tmp_path, monkeypatch):
+    cfg = _qdrant_runtime_config(tmp_path)
+    _write_schema_artifacts(tmp_path)
+    store = _FakeVectorStore()
+
+    monkeypatch.setattr("tht.adapters.factory.build_vector_store", lambda cfg, require_write: store)
+    monkeypatch.setattr("tht.cli.vector_cmd.make_embedder", lambda _: _FakeEmbedder())
+
+    res = CliRunner().invoke(app, ["vector", "index-schema", "-c", str(cfg)])
+
+    assert res.exit_code == 0, res.output
+    assert store.upserts
+
+
+def test_memory_promote_accepts_qdrant_only_runtime_config(tmp_path, monkeypatch):
+    cfg = _qdrant_runtime_config(tmp_path)
+    store = _FakeVectorStore()
+    promoted = [_memory_record()]
+    snapshot = SimpleNamespace(manifest=SimpleNamespace(id="s1"))
+
+    monkeypatch.setattr("tht.cli.memory_cmd.load_snapshot_or_exit", lambda cfg, session: snapshot)
+    monkeypatch.setattr("tht.memory.promote_snapshot", lambda *args, **kwargs: promoted)
+    monkeypatch.setattr("tht.memory.load_registry", lambda path: promoted)
+    monkeypatch.setattr("tht.adapters.factory.build_vector_store", lambda cfg, require_write: store)
+    monkeypatch.setattr("tht.cli.vector_cmd.make_embedder", lambda _: _FakeEmbedder())
+
+    res = CliRunner().invoke(
+        app,
+        ["memory", "promote", "--session", "s1", "--decision", "7", "--json", "-c", str(cfg)],
+    )
+
+    assert res.exit_code == 0, res.output
+    assert json.loads(res.stdout)["indexed"] is True
+    assert store.upserts
+
+
+def test_memory_index_accepts_qdrant_only_runtime_config(tmp_path, monkeypatch):
+    cfg = _qdrant_runtime_config(tmp_path)
+    store = _FakeVectorStore()
+    records = [_memory_record()]
+
+    save_registry(records, tmp_path / "artifacts" / "memory" / "registry.jsonl")
+    monkeypatch.setattr("tht.adapters.factory.build_vector_store", lambda cfg, require_write: store)
+    monkeypatch.setattr("tht.cli.vector_cmd.make_embedder", lambda _: _FakeEmbedder())
+
+    res = CliRunner().invoke(app, ["memory", "index", "-c", str(cfg)])
+
+    assert res.exit_code == 0, res.output
+    assert "OK:" in res.output
+    assert store.upserts
+
+
+def test_memory_clear_accepts_qdrant_only_runtime_config(tmp_path, monkeypatch):
+    cfg = _qdrant_runtime_config(tmp_path)
+    store = _FakeVectorStore()
+    records = [_memory_record()]
+    registry = tmp_path / "artifacts" / "memory" / "registry.jsonl"
+    save_registry(records, registry)
+
+    monkeypatch.setattr("tht.adapters.factory.build_vector_store", lambda cfg, require_write: store)
+
+    res = CliRunner().invoke(app, ["memory", "clear", "--yes", "-c", str(cfg)])
+
+    assert res.exit_code == 0, res.output
+    assert not registry.exists()

harness/tests/test_solved_search_cli.py

@@ -7,7 +7,7 @@ puro (`[]` in modalita' --json) ed exit 0, cosi' il modello prosegue senza
 exemplar. Il finalize-hook gestisce gia' lo stesso scenario in modo analogo.
 """
 import json
-from datetime import datetime
+from datetime import UTC, datetime
 
 from typer.testing import CliRunner
 
@@ -24,7 +24,7 @@ def _cfg(tmp_path):
         "database: {database: d, schema: s, user: u, password: p, transport: direct}\n"
         f"paths: {{artifacts: {tmp_path/'a'}, indexes: {tmp_path/'i'}, sessions: {tmp_path/'se'}}}\n"
         "vector_db: {database: v, schema: vectors, user: u, password: p, transport: direct}\n"
-        "embeddings: {base_url: 'http://localhost:11434', model: nomic-embed-text, dim: 8}\n"
+        "embeddings: {base_url: 'http://localhost:11434', model: qwen3-embedding:0.6b, dim: 1024}\n"
     )
     return cfg
 
@@ -103,15 +103,15 @@ def test_solved_search_json_maps_hit_metadata(tmp_path, monkeypatch):
 
 def test_memory_search_excludes_legacy_table_records(tmp_path, monkeypatch):
     records = [
-        MemoryRecord(
-            id="mem-0001", ts=datetime(2026, 1, 1), session_id="s1",
-            decision_seq=1, type="table_promoted", subject="fact_pazienti",
-        ),
-        MemoryRecord(
-            id="mem-0002", ts=datetime(2026, 1, 1), session_id="s1",
-            decision_seq=2, type="concept_clarified", subject="paziente attivo",
-            detail="flag_attivo = TRUE",
-        ),
+            MemoryRecord(
+                id="mem-0001", ts=datetime(2026, 1, 1, tzinfo=UTC), session_id="s1",
+                decision_seq=1, type="table_promoted", subject="fact_pazienti",
+            ),
+            MemoryRecord(
+                id="mem-0002", ts=datetime(2026, 1, 1, tzinfo=UTC), session_id="s1",
+                decision_seq=2, type="concept_clarified", subject="paziente attivo",
+                detail="flag_attivo = TRUE",
+            ),
     ]
     cfg = _cfg(tmp_path)
     save_registry(records, tmp_path / "a" / "memory" / "registry.jsonl")

harness/tht/adapters/vector/pgvector.py

@@ -3,8 +3,10 @@
 import json
 import re
 
+from psycopg2 import Error as PsycopgError
 from psycopg2 import sql
 from sqlalchemy import Engine
+from sqlalchemy.exc import SQLAlchemyError
 
 from tht.config import DatabaseConfig
 from tht.db.connection import make_engine
@@ -19,7 +21,6 @@ from tht.ports.vector import (
 )
 from tht.vectorstore.store import VectorHit, hit_from_metadata
 
-
 COLLECTION_KINDS = {
     "schema_records": {"schema_table", "schema_column"},
     "evidence": {"evidence"},
@@ -243,7 +244,7 @@ class PgVectorStore:
                 return True, None, dimensions
             finally:
                 raw.close()
-        except Exception as exc:
+        except (AttributeError, TypeError, ValueError, PsycopgError, SQLAlchemyError) as exc:
             return False, f"vector database probe failed: {type(exc).__name__}", set()
 
     def health(self) -> VectorHealth:
@@ -471,6 +472,30 @@ class PgVectorStore:
             if raw is not None:
                 raw.close()
 
+    def delete_kinds(self, collection: str, kinds: list[str]) -> int:
+        _collection(self._schema, collection)
+        _validate_collection_kinds(collection, kinds)
+        raw = None
+        try:
+            raw = self._require_writer().raw_connection()
+            with raw.cursor() as cursor:
+                cursor.execute(
+                    sql.SQL("DELETE FROM {} WHERE kind = ANY(%s)").format(
+                        _collection(self._schema, collection)
+                    ),
+                    (kinds,),
+                )
+                count = cursor.rowcount
+            raw.commit()
+            return count
+        except Exception as exc:
+            if raw is not None:
+                raw.rollback()
+            raise VectorWriteUnavailable("Vector kind cleanup unavailable") from exc
+        finally:
+            if raw is not None:
+                raw.close()
+
     def list_evidence_generations(self, collection: str, workspace_id: str) -> list[str]:
         if collection != "evidence":
             raise VectorStoreError("Only exact Evidence generations may be listed")

harness/tht/adapters/vector/qdrant.py

@@ -212,6 +212,21 @@ class QdrantVectorStore:
         )
         return len(records)
 
+    def delete_kinds(self, collection: str, kinds: list[str]) -> int:
+        _collection("vectors", collection)
+        _validate_collection_kinds(collection, kinds)
+        must = [
+            *self._workspace_filter(),
+            {"key": "record_kind", "match": {"any": sorted(kinds)}},
+        ]
+        before = len(self._scroll(must))
+        self._call(
+            "POST",
+            f"/collections/{self._collection}/points/delete?wait=true",
+            {"filter": {"must": must}},
+        )
+        return before
+
     def delete_generation(self, collection: str, generation: str, workspace_id: str) -> int:
         if collection != "evidence" or _GENERATION.fullmatch(generation) is None:
             raise VectorStoreError("Only exact Evidence generations may be deleted")

harness/tht/adapters/vector/thoth_http.py

@@ -2,6 +2,11 @@
 
 import re
 
+from tht.adapters.vector.pgvector import (
+    _collection,
+    _validate_collection_kinds,
+    _validate_known_kinds,
+)
 from tht.ports.vector import (
     VectorCapabilities,
     VectorHealth,
@@ -14,11 +19,6 @@ from tht.ports.vector import (
 )
 from tht.vectorstore.rest_client import VectorRestClient, VectorRestError
 from tht.vectorstore.store import hit_from_metadata
-from tht.adapters.vector.pgvector import (
-    _collection,
-    _validate_collection_kinds,
-    _validate_known_kinds,
-)
 
 
 def _merge(hits: list[VectorHit], limit: int) -> list[VectorHit]:
@@ -85,7 +85,7 @@ class ThothHttpVectorStore:
             return None, None, []
         try:
             return True, None, client.list_tables()
-        except Exception as exc:
+        except (RuntimeError, VectorRestError) as exc:
             return False, str(exc), []
 
     def search(
@@ -155,6 +155,14 @@ class ThothHttpVectorStore:
         except VectorRestError as exc:
             raise VectorStoreError(str(exc)) from exc
 
+    def delete_kinds(self, collection: str, kinds: list[str]) -> int:
+        _collection("vectors", collection)
+        _validate_collection_kinds(collection, kinds)
+        try:
+            return self._require_writer().delete_kinds(collection, kinds)
+        except VectorRestError as exc:
+            raise VectorStoreError(str(exc)) from exc
+
     def delete_generation(self, collection: str, generation: str, workspace_id: str) -> int:
         if collection != "evidence" or re.fullmatch(r"gen:[0-9a-f]{32}", generation) is None:
             raise VectorStoreError("Only exact Evidence generations may be deleted")

harness/tht/cli/memory_cmd.py

@@ -43,6 +43,12 @@ def _resync_memory(cfg):
     )
 
 
+def clear_memory_index(cfg):
+    from tht.adapters.factory import build_vector_store
+
+    return build_vector_store(cfg, require_write=True).delete_kinds("memory", ["memory"])
+
+
 @memory_app.command("promote")
 def promote_cmd(
     session: str = typer.Option(..., "--session"),
@@ -192,7 +198,6 @@ def clear_cmd(
     config: Path = CONFIG_OPT,
 ) -> None:
     """Cancella TUTTA la review memory: registro canonico + indice pgvector (kind=memory)."""
-    from tht.cli.vector_cmd import make_embedder, open_store, require_direct_vector_cfg
     from tht.memory import load_registry
 
     cfg = _load_config_or_exit(config)
@@ -209,10 +214,7 @@ def clear_cmd(
         typer.secho("Annullato.", fg=typer.colors.YELLOW)
         raise typer.Exit(code=1)
 
-    # Indice pgvector: rimuove i record kind=memory (sync con insieme vuoto).
-    require_direct_vector_cfg(cfg)
-    store = open_store(cfg, "memory")
-    store.sync([], make_embedder(cfg.embeddings), kinds={"memory"})
+    clear_memory_index(cfg)
 
     # Registro canonico.
     registry.unlink()

harness/tht/cli/vector_cmd.py

@@ -26,8 +26,8 @@ def require_vector_cfg(cfg):
     missing = []
     if cfg.embeddings is None:
         missing.append("embeddings")
-    if cfg.vector_db is None and not has_vector_write_rest(cfg):
-        missing.append("vector_db o vector_write_rest")
+    if cfg.vectors is None and cfg.vector_db is None and not has_vector_write_rest(cfg):
+        missing.append("vectors o vector_db o vector_write_rest")
     if missing:
         typer.secho(
             f"ERRORE: sezioni mancanti nel workspace yaml: {', '.join(missing)}.",

harness/tht/ports/vector.py

@@ -80,6 +80,8 @@ class VectorStore(Protocol):
 
     def upsert(self, collection: str, records: list[VectorWriteRecord]) -> int: ...
 
+    def delete_kinds(self, collection: str, kinds: list[str]) -> int: ...
+
     def delete_generation(self, collection: str, generation: str, workspace_id: str) -> int: ...
 
     def list_evidence_generations(self, collection: str, workspace_id: str) -> list[str]: ...

harness/tht/vectorstore/rest_client.py

@@ -5,9 +5,10 @@ Endpoint dedicato (es. https://host/vector/v1/), distinto dal DWH. La lettura us
 Errori in italiano e azionabili, stile `rest/client.py`.
 """
 
-import requests
 import re
 
+import requests
+
 from tht.config import RestConfig
 
 
@@ -46,7 +47,7 @@ class VectorRestClient:
         try:
             body = resp.json()
             detail = body.get("message") or body.get("details") or resp.text
-        except Exception:
+        except ValueError:
             detail = resp.text
         return f"Vector REST rpc {fn} → HTTP {resp.status_code}: {detail}"
 
@@ -149,6 +150,22 @@ class VectorRestClient:
             return int(payload.get("deleted", 0))
         return 0
 
+    def delete_kinds(self, table_name: str, kinds: list[str]) -> int:
+        try:
+            payload = self._call(
+                "delete_vector_kinds",
+                {"table_name": table_name, "kinds": kinds},
+            )
+        except VectorRestError as error:
+            if "HTTP 404" in str(error):
+                raise VectorRestError(
+                    "delete_vector_kinds RPC is unavailable; deploy the cleanup migration"
+                ) from None
+            raise
+        if isinstance(payload, dict):
+            return int(payload.get("deleted", 0))
+        return 0
+
     def list_evidence_generations(self, table_name: str, workspace_id: str) -> list[str]:
         if re.fullmatch(r"[a-z][a-z0-9_-]{0,63}", workspace_id) is None:
             raise ValueError("workspace namespace must be canonical")