Initial SQL-only 1C adapter baseline

tests/1c/test_semantic_cache_search_cli.py

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+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT / "scripts"))
+
+import search_1c_semantic_cache as semantic_search  # noqa: E402
+
+
+def test_search_semantic_cache_sends_query_embedding_and_validation(monkeypatch) -> None:
+    seen: dict = {}
+
+    def fake_adapter_call(adapter_url: str, method: str, payload: dict, *, timeout_seconds: int = 180) -> dict:
+        seen["adapter_url"] = adapter_url
+        seen["method"] = method
+        seen["payload"] = payload
+        return {
+            "status": "ok",
+            "matches": [
+                {
+                    "document_id": "doc-1",
+                    "score": 0.9,
+                    "match_by": "vector_embedding",
+                    "object": {"kind": "Template", "name": "ПФ_MXL"},
+                    "cache": {"embedding_model": "local-hashing-v1", "vector_status": "embedded"},
+                }
+            ],
+        }
+
+    monkeypatch.setattr(semantic_search, "adapter_call", fake_adapter_call)
+
+    result = semantic_search.search_semantic_cache(
+        adapter_url="http://adapter/rpc",
+        base_id="upo_test",
+        query="ОбластьШапка",
+        kind="Template",
+        limit=3,
+        dimensions=12,
+        validate_candidates=True,
+        validation_limit=2,
+    )
+
+    assert result["status"] == "ok"
+    assert result["client_embedding"]["dimensions"] == 12
+    assert seen["method"] == "semantic.cache.search"
+    assert seen["payload"]["base_id"] == "upo_test"
+    assert seen["payload"]["query"] == "ОбластьШапка"
+    assert seen["payload"]["kind"] == "Template"
+    assert seen["payload"]["limit"] == 3
+    assert seen["payload"]["validate_candidates"] is True
+    assert seen["payload"]["validation_limit"] == 2
+    assert isinstance(seen["payload"]["query_embedding"], list)
+    assert len(seen["payload"]["query_embedding"]) == 12
+
+
+def test_search_semantic_cache_can_embed_pending_before_search(monkeypatch) -> None:
+    calls: list[str] = []
+
+    def fake_embed_pending_semantic_cache(**kwargs) -> dict:
+        calls.append("embed")
+        assert kwargs["base_id"] == "upo_test"
+        assert kwargs["kind"] == "Template"
+        assert kwargs["limit"] == 7
+        assert kwargs["batch_size"] == 3
+        return {"status": "ok", "counts": {"pending": 1, "processed": 1, "stored": 1}, "embedding": {"model": "local-hashing-v1"}}
+
+    def fake_adapter_call(adapter_url: str, method: str, payload: dict, *, timeout_seconds: int = 180) -> dict:
+        calls.append(method)
+        return {"status": "ok", "matches": []}
+
+    monkeypatch.setattr(semantic_search, "embed_pending_semantic_cache", fake_embed_pending_semantic_cache)
+    monkeypatch.setattr(semantic_search, "adapter_call", fake_adapter_call)
+
+    result = semantic_search.search_semantic_cache(
+        adapter_url="http://adapter/rpc",
+        base_id="upo_test",
+        query="ОбластьШапка",
+        kind="Template",
+        dimensions=8,
+        embed_pending=True,
+        embed_limit=7,
+        embed_batch_size=3,
+    )
+
+    assert calls == ["embed", "semantic.cache.search"]
+    assert result["embedding_refresh"]["counts"]["stored"] == 1