Make test folder for src structure and refactored verify_version tests

tests/retrievers/test_base.py

@@ -0,0 +1,39 @@
+#  Copyright (c) "Neo4j"
+#  Neo4j Sweden AB [https://neo4j.com]
+#  #
+#  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
+#  #
+#      https://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.
+import pytest
+
+from neo4j_genai.retrievers.base import Retriever
+
+
+@pytest.mark.parametrize(
+    "db_version,expected_exception",
+    [
+        (["5.18-aura"], None),
+        (["5.3-aura"], ValueError),
+        (["5.19.0"], None),
+        (["4.3.5"], ValueError),
+    ],
+)
+def test_retriever_version_support(driver, db_version, expected_exception):
+    class MockRetriever(Retriever):
+        def search(self, *args, **kwargs):
+            pass
+
+    driver.execute_query.return_value = [[{"versions": db_version}], None, None]
+    if expected_exception:
+        with pytest.raises(expected_exception):
+            MockRetriever(driver=driver)
+    else:
+        MockRetriever(driver=driver)

tests/retrievers/test_hybrid.py

@@ -0,0 +1,231 @@
+#  Copyright (c) "Neo4j"
+#  Neo4j Sweden AB [https://neo4j.com]
+#  #
+#  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
+#  #
+#      https://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, MagicMock
+
+import pytest
+
+from neo4j_genai import HybridRetriever, HybridCypherRetriever
+from neo4j_genai.neo4j_queries import get_search_query
+from neo4j_genai.types import SearchType
+
+
+def test_vector_retriever_initialization(driver):
+    with patch("neo4j_genai.retrievers.base.Retriever._verify_version") as mock_verify:
+        HybridRetriever(
+            driver=driver,
+            vector_index_name="my-index",
+            fulltext_index_name="fulltext-index",
+        )
+        mock_verify.assert_called_once()
+
+
+def test_vector_cypher_retriever_initialization(driver):
+    with patch("neo4j_genai.retrievers.base.Retriever._verify_version") as mock_verify:
+        HybridCypherRetriever(
+            driver=driver,
+            vector_index_name="my-index",
+            fulltext_index_name="fulltext-index",
+            retrieval_query="",
+        )
+        mock_verify.assert_called_once()
+
+
+@patch("neo4j_genai.HybridRetriever._verify_version")
+def test_hybrid_search_text_happy_path(_verify_version_mock, driver):
+    embed_query_vector = [1.0 for _ in range(1536)]
+    custom_embeddings = MagicMock()
+    custom_embeddings.embed_query.return_value = embed_query_vector
+    vector_index_name = "my-index"
+    fulltext_index_name = "my-fulltext-index"
+    query_text = "may thy knife chip and shatter"
+    top_k = 5
+    retriever = HybridRetriever(
+        driver, vector_index_name, fulltext_index_name, custom_embeddings
+    )
+    retriever.driver.execute_query.return_value = [
+        [{"node": "dummy-node", "score": 1.0}],
+        None,
+        None,
+    ]
+    search_query = get_search_query(SearchType.HYBRID)
+
+    records = retriever.search(query_text=query_text, top_k=top_k)
+
+    retriever.driver.execute_query.assert_called_once_with(
+        search_query,
+        {
+            "vector_index_name": vector_index_name,
+            "top_k": top_k,
+            "query_text": query_text,
+            "fulltext_index_name": fulltext_index_name,
+            "query_vector": embed_query_vector,
+        },
+    )
+    custom_embeddings.embed_query.assert_called_once_with(query_text)
+    assert records == [{"node": "dummy-node", "score": 1.0}]
+
+
+@patch("neo4j_genai.HybridRetriever._verify_version")
+def test_hybrid_search_favors_query_vector_over_embedding_vector(
+    _verify_version_mock, driver
+):
+    embed_query_vector = [1.0 for _ in range(1536)]
+    query_vector = [2.0 for _ in range(1536)]
+    custom_embeddings = MagicMock()
+    custom_embeddings.embed_query.return_value = embed_query_vector
+    vector_index_name = "my-index"
+    fulltext_index_name = "my-fulltext-index"
+    query_text = "may thy knife chip and shatter"
+    top_k = 5
+    retriever = HybridRetriever(
+        driver, vector_index_name, fulltext_index_name, custom_embeddings
+    )
+    retriever.driver.execute_query.return_value = [
+        [{"node": "dummy-node", "score": 1.0}],
+        None,
+        None,
+    ]
+    search_query = get_search_query(SearchType.HYBRID)
+
+    retriever.search(query_text=query_text, query_vector=query_vector, top_k=top_k)
+
+    retriever.driver.execute_query.assert_called_once_with(
+        search_query,
+        {
+            "vector_index_name": vector_index_name,
+            "top_k": top_k,
+            "query_text": query_text,
+            "fulltext_index_name": fulltext_index_name,
+            "query_vector": query_vector,
+        },
+    )
+    custom_embeddings.embed_query.assert_not_called()
+
+
+def test_error_when_hybrid_search_only_text_no_embedder(hybrid_retriever):
+    query_text = "may thy knife chip and shatter"
+    top_k = 5
+
+    with pytest.raises(ValueError, match="Embedding method required for text query."):
+        hybrid_retriever.search(
+            query_text=query_text,
+            top_k=top_k,
+        )
+
+
+def test_hybrid_search_retriever_search_missing_embedder_for_text(
+    hybrid_retriever,
+):
+    query_text = "may thy knife chip and shatter"
+    top_k = 5
+
+    with pytest.raises(ValueError, match="Embedding method required for text query"):
+        hybrid_retriever.search(
+            query_text=query_text,
+            top_k=top_k,
+        )
+
+
+@patch("neo4j_genai.HybridRetriever._verify_version")
+def test_hybrid_retriever_return_properties(_verify_version_mock, driver):
+    embed_query_vector = [1.0 for _ in range(1536)]
+    custom_embeddings = MagicMock()
+    custom_embeddings.embed_query.return_value = embed_query_vector
+    vector_index_name = "my-index"
+    fulltext_index_name = "my-fulltext-index"
+    query_text = "may thy knife chip and shatter"
+    top_k = 5
+    return_properties = ["node-property-1", "node-property-2"]
+    retriever = HybridRetriever(
+        driver,
+        vector_index_name,
+        fulltext_index_name,
+        custom_embeddings,
+        return_properties,
+    )
+    driver.execute_query.return_value = [
+        [{"node": "dummy-node", "score": 1.0}],
+        None,
+        None,
+    ]
+    search_query = get_search_query(SearchType.HYBRID, return_properties)
+
+    records = retriever.search(query_text=query_text, top_k=top_k)
+
+    custom_embeddings.embed_query.assert_called_once_with(query_text)
+    driver.execute_query.assert_called_once_with(
+        search_query,
+        {
+            "vector_index_name": vector_index_name,
+            "top_k": top_k,
+            "query_text": query_text,
+            "fulltext_index_name": fulltext_index_name,
+            "query_vector": embed_query_vector,
+        },
+    )
+    assert records == [{"node": "dummy-node", "score": 1.0}]
+
+
+@patch("neo4j_genai.HybridCypherRetriever._verify_version")
+def test_hybrid_cypher_retrieval_query_with_params(_verify_version_mock, driver):
+    embed_query_vector = [1.0 for _ in range(1536)]
+    custom_embeddings = MagicMock()
+    custom_embeddings.embed_query.return_value = embed_query_vector
+    vector_index_name = "my-index"
+    fulltext_index_name = "my-fulltext-index"
+    query_text = "may thy knife chip and shatter"
+    top_k = 5
+    retrieval_query = """
+        RETURN node.id AS node_id, node.text AS text, score, {test: $param} AS metadata
+        """
+    query_params = {
+        "param": "dummy-param",
+    }
+    retriever = HybridCypherRetriever(
+        driver,
+        vector_index_name,
+        fulltext_index_name,
+        retrieval_query,
+        custom_embeddings,
+    )
+    driver.execute_query.return_value = [
+        [{"node_id": 123, "text": "dummy-text", "score": 1.0}],
+        None,
+        None,
+    ]
+    search_query = get_search_query(SearchType.HYBRID, retrieval_query=retrieval_query)
+
+    records = retriever.search(
+        query_text=query_text,
+        top_k=top_k,
+        query_params=query_params,
+    )
+
+    custom_embeddings.embed_query.assert_called_once_with(query_text)
+
+    driver.execute_query.assert_called_once_with(
+        search_query,
+        {
+            "vector_index_name": vector_index_name,
+            "top_k": top_k,
+            "query_text": query_text,
+            "fulltext_index_name": fulltext_index_name,
+            "query_vector": embed_query_vector,
+            "param": "dummy-param",
+        },
+    )
+
+    assert records == [{"node_id": 123, "text": "dummy-text", "score": 1.0}]