Fix: Issue with search dialect 3 and JSON (resolves #140)

redisvl/index/index.py

@@ -32,6 +32,38 @@
 logger = get_logger(__name__)
 
 
+def _handle_dialect_3(result: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Handle dialect 3 responses by converting JSON-encoded list values to strings.
+
+    Each JSON-encoded string in the result that is a list will be converted:
+    - If the list has one item, it is unpacked.
+    - If the list has multiple items, they are joined into a single comma-separated string.
+
+    Args:
+        result (Dict[str, Any]): The dictionary containing the results to process.
+
+    Returns:
+        Dict[str, Any]: The processed dictionary with updated values.
+    """
+    for field, value in result.items():
+        if isinstance(value, str):
+            try:
+                parsed_value = json.loads(value)
+            except json.JSONDecodeError:
+                continue  # Skip processing if value is not valid JSON
+
+            if isinstance(parsed_value, list):
+                # Use a single value if the list contains only one item, else join all items.
+                result[field] = (
+                    parsed_value[0]
+                    if len(parsed_value) == 1
+                    else ", ".join(map(str, parsed_value))
+                )
+
+    return result
+
+
 def process_results(
     results: "Result", query: BaseQuery, storage_type: StorageType
 ) -> List[Dict[str, Any]]:
@@ -81,7 +113,13 @@ def _process(doc: "Document") -> Dict[str, Any]:
 
         return doc_dict
 
-    return [_process(doc) for doc in results.docs]
+    processed_results = [_process(doc) for doc in results.docs]
+
+    # Handle dialect 3 responses
+    if query._dialect == 3:
+        processed_results = [_handle_dialect_3(result) for result in processed_results]
+
+    return processed_results
 
 
 def check_modules_present():

tests/integration/test_dialects.py

@@ -0,0 +1,118 @@
+import json
+
+import pytest
+from redis import Redis
+from redis.commands.search.query import Query
+
+from redisvl.index import SearchIndex
+from redisvl.query import FilterQuery, VectorQuery
+from redisvl.query.filter import Tag
+from redisvl.schema.schema import IndexSchema
+
+
+@pytest.fixture
+def sample_data():
+    return [
+        {
+            "name": "Noise-cancelling Bluetooth headphones",
+            "description": "Wireless Bluetooth headphones with noise-cancelling technology",
+            "connection": {"wireless": True, "type": "Bluetooth"},
+            "price": 99.98,
+            "stock": 25,
+            "colors": ["black", "silver"],
+            "embedding": [0.87, -0.15, 0.55, 0.03],
+            "embeddings": [[0.56, -0.34, 0.69, 0.02], [0.94, -0.23, 0.45, 0.19]],
+        },
+        {
+            "name": "Wireless earbuds",
+            "description": "Wireless Bluetooth in-ear headphones",
+            "connection": {"wireless": True, "type": "Bluetooth"},
+            "price": 64.99,
+            "stock": 17,
+            "colors": ["red", "black", "white"],
+            "embedding": [-0.7, -0.51, 0.88, 0.14],
+            "embeddings": [[0.54, -0.14, 0.79, 0.92], [0.94, -0.93, 0.45, 0.16]],
+        },
+    ]
+
+
+@pytest.fixture
+def schema_dict():
+    return {
+        "index": {"name": "products", "prefix": "product", "storage_type": "json"},
+        "fields": [
+            {"name": "name", "type": "text"},
+            {"name": "description", "type": "text"},
+            {"name": "connection_type", "path": "$.connection.type", "type": "tag"},
+            {"name": "price", "type": "numeric"},
+            {"name": "stock", "type": "numeric"},
+            {"name": "color", "path": "$.colors.*", "type": "tag"},
+            {
+                "name": "embedding",
+                "type": "vector",
+                "attrs": {"dims": 4, "algorithm": "flat", "distance_metric": "cosine"},
+            },
+            {
+                "name": "embeddings",
+                "path": "$.embeddings[*]",
+                "type": "vector",
+                "attrs": {"dims": 4, "algorithm": "hnsw", "distance_metric": "l2"},
+            },
+        ],
+    }
+
+
+@pytest.fixture
+def index(sample_data, redis_url, schema_dict):
+    index_schema = IndexSchema.from_dict(schema_dict)
+    redis_client = Redis.from_url(redis_url)
+    index = SearchIndex(index_schema, redis_client)
+    index.create(overwrite=True, drop=True)
+    index.load(sample_data)
+    yield index
+    index.delete(drop=True)
+
+
+def test_dialect_3_json(index, sample_data):
+    # Create a VectorQuery with dialect 3
+    vector_query = VectorQuery(
+        vector=[0.23, 0.12, -0.03, 0.98],
+        vector_field_name="embedding",
+        return_fields=["name", "description", "price"],
+        dialect=3,
+    )
+
+    # Execute the query
+    results = index.query(vector_query)
+
+    # Print the results
+    print("VectorQuery Results:")
+    print(results)
+
+    # Assert the expected format of the results
+    assert len(results) > 0
+    for result in results:
+        assert not isinstance(result["name"], list)
+        assert not isinstance(result["description"], list)
+        assert not isinstance(result["price"], (list, str))
+
+    # Create a FilterQuery with dialect 3
+    filter_query = FilterQuery(
+        filter_expression=Tag("color") == "black",
+        return_fields=["name", "description", "price"],
+        dialect=3,
+    )
+
+    # Execute the query
+    results = index.query(filter_query)
+
+    # Print the results
+    print("FilterQuery Results:")
+    print(results)
+
+    # Assert the expected format of the results
+    assert len(results) > 0
+    for result in results:
+        assert not isinstance(result["name"], list)
+        assert not isinstance(result["description"], list)
+        assert not isinstance(result["price"], (list, str))