Handle searching dataset without embedding model (#16742)

### Summary

Handle searching dataset without embedding model

In this PR, Searching datasets with different embedding models or
searching dataset with/without embedding models are not allowed. We will
improve the behavior later.

api/db/services/knowledgebase_service.py

@@ -29,6 +29,29 @@ from api.constants import DATASET_NAME_LIMIT
 from api.utils.api_utils import get_parser_config, get_data_error_result
 
 
+def _base_model_name(embd_id: str) -> str:
+    """Return the base model name by stripping provider/instance suffix from an embd_id."""
+    parts = embd_id.rsplit("@", 2)
+    return parts[0]
+
+
+def validate_dataset_embedding_models(kbs):
+    """Validate that all given datasets use the same embedding model (or all use none).
+
+    Returns an error message string on failure, or ``None`` on success.
+    """
+    # Either all datasets have an embedding model, or none do. Mixing is not allowed.
+    embd_ids = [kb.embd_id for kb in kbs if kb.embd_id]
+    has_embd = len(embd_ids) > 0
+    if has_embd and len(embd_ids) != len(kbs):
+        return "Cannot search across datasets where some have embedding models and others do not."
+    if has_embd:
+        embd_nms = list({_base_model_name(eid) for eid in embd_ids})
+        if len(embd_nms) > 1:
+            return f"Datasets use different embedding models: {[kb.embd_id for kb in kbs]}"
+    return None
+
+
 class KnowledgebaseService(CommonService):
     """Service class for managing dataset operations.