codex-lens: respect embedding config during warmup

codex-lens/src/codexlens/search/chain_search.py

@@ -3531,8 +3531,20 @@ class ChainSearchEngine:
             self.logger.debug("Using single-threaded mode for vector search (GPU safety)")
             # Pre-load embedder to avoid initialization overhead per-search
             try:
-                from codexlens.semantic.embedder import get_embedder
-                get_embedder(profile="code", use_gpu=True)
+                from codexlens.semantic.factory import get_embedder as get_embedder_factory
+
+                embedding_backend = "fastembed"
+                embedding_model = "code"
+                use_gpu = True
+                if self._config is not None:
+                    embedding_backend = getattr(self._config, "embedding_backend", embedding_backend) or embedding_backend
+                    embedding_model = getattr(self._config, "embedding_model", embedding_model) or embedding_model
+                    use_gpu = bool(getattr(self._config, "embedding_use_gpu", use_gpu))
+
+                if embedding_backend == "litellm":
+                    get_embedder_factory(backend="litellm", model=embedding_model)
+                else:
+                    get_embedder_factory(backend="fastembed", profile=embedding_model, use_gpu=use_gpu)
             except Exception:
                 pass  # Ignore pre-load failures
 

codex-lens/tests/test_chain_search.py

@@ -155,3 +155,37 @@ def test_cascade_search_invalid_strategy(temp_paths: Path) -> None:
         engine.cascade_search("query", source_path, strategy="invalid_strategy")
         mock_binary.assert_called_once()
 
+
+def test_vector_warmup_uses_embedding_config(monkeypatch: pytest.MonkeyPatch, temp_paths: Path) -> None:
+    calls: list[dict[str, object]] = []
+
+    def fake_get_embedder(**kwargs: object) -> object:
+        calls.append(dict(kwargs))
+        return object()
+
+    import codexlens.semantic.factory as factory
+
+    monkeypatch.setattr(factory, "get_embedder", fake_get_embedder)
+
+    registry = RegistryStore(db_path=temp_paths / "registry.db")
+    registry.initialize()
+    mapper = PathMapper(index_root=temp_paths / "indexes")
+    config = Config(
+        data_dir=temp_paths / "data",
+        embedding_backend="fastembed",
+        embedding_model="fast",
+        embedding_use_gpu=False,
+    )
+
+    engine = ChainSearchEngine(registry, mapper, config=config)
+    monkeypatch.setattr(engine, "_get_executor", lambda _workers: MagicMock())
+
+    engine._search_parallel([], "query", SearchOptions(enable_vector=True))
+
+    assert calls == [
+        {
+            "backend": "fastembed",
+            "profile": "fast",
+            "use_gpu": False,
+        }
+    ]