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()