community[patch]: Add the ability to pass maps to neo4j retrieval query (#19758)

Makes it easier to flatten complex values to text, so you don't have to
use a lot of Cypher to do it.

libs/community/langchain_community/vectorstores/neo4j_vector.py

@@ -108,6 +108,31 @@ def remove_lucene_chars(text: str) -> str:
     return text.strip()
 
 
+def dict_to_yaml_str(input_dict: Dict, indent: int = 0) -> str:
+    """
+    Converts a dictionary to a YAML-like string without using external libraries.
+
+    Parameters:
+    - input_dict (dict): The dictionary to convert.
+    - indent (int): The current indentation level.
+
+    Returns:
+    - str: The YAML-like string representation of the input dictionary.
+    """
+    yaml_str = ""
+    for key, value in input_dict.items():
+        padding = "  " * indent
+        if isinstance(value, dict):
+            yaml_str += f"{padding}{key}:\n{dict_to_yaml_str(value, indent + 1)}"
+        elif isinstance(value, list):
+            yaml_str += f"{padding}{key}:\n"
+            for item in value:
+                yaml_str += f"{padding}- {item}\n"
+        else:
+            yaml_str += f"{padding}{key}: {value}\n"
+    return yaml_str
+
+
 class Neo4jVector(VectorStore):
     """`Neo4j` vector index.
 
@@ -646,7 +671,9 @@ class Neo4jVector(VectorStore):
         docs = [
             (
                 Document(
-                    page_content=result["text"],
+                    page_content=dict_to_yaml_str(result["text"])
+                    if isinstance(result["text"], dict)
+                    else result["text"],
                     metadata={
                         k: v for k, v in result["metadata"].items() if v is not None
                     },

libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py

@@ -741,3 +741,29 @@ def test_retrieval_params() -> None:
         Document(page_content="test", metadata={"test": "test1"}),
         Document(page_content="test", metadata={"test": "test1"}),
     ]
+
+
+def test_retrieval_dictionary() -> None:
+    """Test if we use parameters in retrieval query"""
+    docsearch = Neo4jVector.from_texts(
+        texts=texts,
+        embedding=FakeEmbeddings(),
+        pre_delete_collection=True,
+        retrieval_query="""
+        RETURN {
+            name:'John', 
+            age: 30,
+            skills: ["Python", "Data Analysis", "Machine Learning"]} as text, 
+            score, {} AS metadata
+        """,
+    )
+    expected_output = [
+        Document(
+            page_content=(
+                "skills:\n- Python\n- Data Analysis\n- "
+                "Machine Learning\nage: 30\nname: John\n"
+            )
+        )
+    ]
+    output = docsearch.similarity_search("Foo", k=1)
+    assert output == expected_output

libs/community/tests/unit_tests/vectorstores/test_neo4j.py

@@ -1,6 +1,9 @@
 """Test Neo4j functionality."""
 
-from langchain_community.vectorstores.neo4j_vector import remove_lucene_chars
+from langchain_community.vectorstores.neo4j_vector import (
+    dict_to_yaml_str,
+    remove_lucene_chars,
+)
 
 
 def test_escaping_lucene() -> None:
@@ -43,3 +46,22 @@ def test_escaping_lucene() -> None:
         remove_lucene_chars("It is the end of the world. Take shelter~")
         == "It is the end of the world. Take shelter"
     )
+
+
+def test_converting_to_yaml() -> None:
+    example_dict = {
+        "name": "John Doe",
+        "age": 30,
+        "skills": ["Python", "Data Analysis", "Machine Learning"],
+        "location": {"city": "Ljubljana", "country": "Slovenia"},
+    }
+
+    yaml_str = dict_to_yaml_str(example_dict)
+
+    expected_output = (
+        "name: John Doe\nage: 30\nskills:\n- Python\n- "
+        "Data Analysis\n- Machine Learning\nlocation:\n  city: Ljubljana\n"
+        "  country: Slovenia\n"
+    )
+
+    assert yaml_str == expected_output