fix(whoami): convert retrieval scores to float

src/rai_whoami/rai_whoami/agents/ros2/vector_store_retrieval_agent.py

@@ -71,7 +71,7 @@ def service_callback(
         response.success = True
         response.message = "Success"
         response.documents = [result[0].page_content for result in vdb_results]
-        response.scores = [result[1] for result in vdb_results]
+        response.scores = [float(result[1]) for result in vdb_results]
         self.logger.info(f"Sending response to query: {request.query}")
         return response
 

tests/rai_whoami/test_vector_store_retrieval_agent.py

@@ -0,0 +1,65 @@
+# Copyright (C) 2026 Robotec.AI
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest.mock import patch
+
+import numpy as np
+import pytest
+from langchain_core.documents import Document
+
+from rai_interfaces.srv import VectorStoreRetrieval
+from rai_whoami.agents.ros2 import vector_store_retrieval_agent
+
+
+@pytest.mark.parametrize(
+    "scores",
+    [
+        pytest.param(
+            [np.float32(0.6289791), np.float32(0.5291562)], id="numpy-float32"
+        ),
+        pytest.param([1.5, 0.25], id="python-float"),
+        pytest.param([], id="empty"),
+    ],
+)
+def test_service_callback_serializes_scores(scores, tmp_path):
+    documents = [
+        Document(page_content=f"Document {index}") for index in range(len(scores))
+    ]
+    with (
+        patch.object(vector_store_retrieval_agent, "ROS2Connector"),
+        patch.object(vector_store_retrieval_agent, "get_faiss_client") as get_client,
+    ):
+        search = get_client.return_value.similarity_search_with_score
+        search.return_value = list(zip(documents, scores))
+        agent = vector_store_retrieval_agent.ROS2VectorStoreRetrievalAgent(
+            service_name="rai_whoami_documentation_service",
+            root_dir=str(tmp_path),
+            k=2,
+        )
+        request = VectorStoreRetrieval.Request(query="maximum load")
+        # Newer ROS generators make field validation opt-in.
+        if hasattr(VectorStoreRetrieval.Response, "_check_fields"):
+            response = VectorStoreRetrieval.Response(check_fields=True)
+        else:
+            response = VectorStoreRetrieval.Response()
+
+        result = agent.service_callback(request, response)
+
+    assert result is response
+    assert response.success is True
+    assert response.message == "Success"
+    assert response.documents == [document.page_content for document in documents]
+    assert list(response.scores) == [float(score) for score in scores]
+    assert all(type(score) is float for score in response.scores)
+    search.assert_called_once_with(request.query, k=2)