fix(vector): harden backup restore parity gates

harness/tests/l0/test_vector_adapter_parity.py

@@ -6,8 +6,9 @@ from testcontainers.postgres import PostgresContainer
 
 from tht.adapters.vector.pgvector import PgVectorStore
 from tht.adapters.vector.thoth_http import ThothHttpVectorStore
-from tht.config import DatabaseConfig
+from tht.config import DatabaseConfig, RestConfig
 from tht.ports.vector import VectorRecord, VectorStoreError, VectorWriteRecord
+from tht.vectorstore.rest_client import VectorRestClient
 
 
 def _write(record_id, kind, embedding, content_hash):
@@ -32,26 +33,46 @@ FIXTURE = [
 ]
 
 
-class FixtureHttpClient:
+class Response:
+    def __init__(self, payload=None, status=200):
+        self.status_code = status
+        self.payload = payload
+        self.text = "" if payload is None else "json"
+
+    @property
+    def ok(self):
+        return self.status_code < 400
+
+    def json(self):
+        return self.payload
+
+
+class FixtureHttpTransport:
     def __init__(self):
         self.rows = {}
+        self.calls = []
 
-    def list_tables(self):
-        return [{"table_name": "memory", "vector_dimensions": 2}]
+    def post(self, url, json, headers, **kwargs):
+        assert headers == {"X-API-Key": "parity-key"}
+        self.calls.append((url.rsplit("/", 1)[-1], json))
+        function = self.calls[-1][0]
+        if function == "list_tables":
+            return Response([{"table_name": "memory", "vector_dimensions": 2}])
+        if function == "upsert_vector_records":
+            for row in json["rows"]:
+                self.rows[(json["table_name"], row["record_key"])] = row
+            return Response({"upserted": len(json["rows"])})
+        if function == "existing_vector_hashes":
+            return Response([
+                {"record_key": row["record_key"], "content_hash": row["content_hash"]}
+                for (table, _), row in self.rows.items()
+                if table == json["table_name"] and row["kind"] in json["kinds"]
+            ])
+        assert function == "search_similar"
+        table_name = json["table_name"]
+        embedding = json["query_embedding"]
+        kinds = json.get("kinds")
 
-    def upsert_records(self, table_name, rows):
-        for row in rows:
-            self.rows[(table_name, row["record_key"])] = row
-        return len(rows)
-
-    def existing_hashes(self, table_name, kinds):
-        return {
-            row["record_key"]: row["content_hash"]
-            for (table, _), row in self.rows.items()
-            if table == table_name and row["kind"] in kinds
-        }
-
-    def search_similar(self, table_name, embedding, limit, kinds=None):
         def similarity(row):
             left, right = row["embedding"], embedding
             return sum(a * b for a, b in zip(left, right)) / (
@@ -64,10 +85,11 @@ class FixtureHttpClient:
             for (table, _), row in self.rows.items()
             if table == table_name and (not kinds or row["kind"] in kinds)
         ]
-        return sorted(
+        payload = sorted(
             rows,
             key=lambda row: (-row["similarity"], row["metadata"]["record_key"]),
-        )[:limit]
+        )[: json["limit_count"]]
+        return Response(payload)
 
 
 @pytest.fixture
@@ -100,10 +122,13 @@ def direct_store():
 
 
 @pytest.fixture
-def http_store():
-    client = FixtureHttpClient()
+def http_store(monkeypatch):
+    transport = FixtureHttpTransport()
+    monkeypatch.setattr("tht.vectorstore.rest_client.requests.post", transport.post)
+    client = VectorRestClient(RestConfig(base_url="https://vectors.test", api_key="parity-key"))
     store = ThothHttpVectorStore(client, client, expected_dimension=2)
     store.upsert("memory", FIXTURE)
+    store.transport = transport
     return store
 
 
@@ -146,3 +171,58 @@ def test_dimension_error_parity(request, store_fixture):
         store.search(["memory"], [1.0], limit=1)
     with pytest.raises(VectorStoreError, match="Embedding dimension"):
         store.upsert("memory", [_write("bad", "memory", [1.0], "bad")])
+
+
+def test_http_parity_exercises_rpc_kinds_payload(http_store):
+    http_store.search(["memory"], [1.0, 0.0], limit=2, kinds=["memory"])
+    search_calls = [payload for function, payload in http_store.transport.calls if function == "search_similar"]
+    assert search_calls[-1] == {
+        "query_embedding": [1.0, 0.0],
+        "limit_count": 2,
+        "table_name": "memory",
+        "kinds": ["memory"],
+    }
+
+
+def test_http_adapter_maps_transport_error(monkeypatch):
+    monkeypatch.setattr(
+        "tht.vectorstore.rest_client.requests.post",
+        lambda *args, **kwargs: Response({"message": "server broke"}, status=500),
+    )
+    client = VectorRestClient(RestConfig(base_url="https://vectors.test", api_key="parity-key"))
+    store = ThothHttpVectorStore(client, client, expected_dimension=2)
+    with pytest.raises(VectorStoreError, match="HTTP 500"):
+        store.search(["memory"], [1.0, 0.0], limit=1, kinds=["memory"])
+
+
+def test_http_adapter_tolerates_malformed_metadata(monkeypatch):
+    monkeypatch.setattr(
+        "tht.vectorstore.rest_client.requests.post",
+        lambda *args, **kwargs: Response([{"similarity": 0.5, "metadata": None}]),
+    )
+    client = VectorRestClient(RestConfig(base_url="https://vectors.test", api_key="parity-key"))
+    hit = ThothHttpVectorStore(client, None, expected_dimension=2).search(
+        ["memory"], [1.0, 0.0], limit=1
+    )[0]
+    assert (hit.id, hit.kind, hit.metadata) == ("", "", {})
+
+
+def test_http_adapter_legacy_fallback_preserves_kind_semantics(monkeypatch):
+    calls = []
+
+    def post(url, json, **kwargs):
+        calls.append(json)
+        if "kinds" in json:
+            return Response({"message": "function not found"}, status=404)
+        return Response([
+            {"similarity": 1.0, "metadata": {"record_key": "wrong", "kind": "solved_question"}},
+            {"similarity": 0.9, "metadata": {"record_key": "right", "kind": "memory"}},
+        ])
+
+    monkeypatch.setattr("tht.vectorstore.rest_client.requests.post", post)
+    client = VectorRestClient(RestConfig(base_url="https://vectors.test", api_key="parity-key"))
+    hits = ThothHttpVectorStore(client, None, expected_dimension=2).search(
+        ["memory"], [1.0, 0.0], limit=2, kinds=["memory"]
+    )
+    assert [hit.id for hit in hits] == ["right"]
+    assert "kinds" in calls[0] and "kinds" not in calls[1]