Add FilterQuery

redisvl/cli/index.py

@@ -1,11 +1,11 @@
 import argparse
 import sys
-from tabulate import tabulate
 from argparse import Namespace
 
+from tabulate import tabulate
 
 from redisvl.cli.log import get_logger
-from redisvl.cli.utils import create_redis_url, add_index_parsing_options
+from redisvl.cli.utils import add_index_parsing_options, create_redis_url
 from redisvl.index import SearchIndex
 from redisvl.utils.connection import get_redis_connection
 from redisvl.utils.utils import convert_bytes, make_dict
@@ -36,7 +36,7 @@ def __init__(self):
             "--format",
             help="Output format for info command",
             type=str,
-            default="rounded_outline"
+            default="rounded_outline",
         )
         parser = add_index_parsing_options(parser)
 
@@ -126,6 +126,7 @@ def _connect_to_index(self, args: Namespace) -> SearchIndex:
 
         return index
 
+
 def _display_in_table(index_info, output_format="rounded_outline"):
     print("\n")
     attributes = index_info.get("attributes", [])
@@ -183,4 +184,4 @@ def _display_in_table(index_info, output_format="rounded_outline"):
             headers=headers,
             tablefmt=output_format,
         )
-    )
+    )

redisvl/cli/main.py

@@ -3,9 +3,8 @@
 
 from redisvl.cli.index import Index
 from redisvl.cli.log import get_logger
-from redisvl.cli.version import Version
 from redisvl.cli.stats import Stats
-
+from redisvl.cli.version import Version
 
 logger = get_logger(__name__)
 
@@ -50,4 +49,3 @@ def version(self):
     def stats(self):
         Stats()
         exit(0)
-

redisvl/cli/stats.py

@@ -1,13 +1,14 @@
 import argparse
 import sys
-from tabulate import tabulate
 from argparse import Namespace
 
-from redisvl.cli.utils import create_redis_url, add_index_parsing_options
+from tabulate import tabulate
+
+from redisvl.cli.log import get_logger
+from redisvl.cli.utils import add_index_parsing_options, create_redis_url
 from redisvl.index import SearchIndex
 from redisvl.utils.connection import get_redis_connection
 
-from redisvl.cli.log import get_logger
 logger = get_logger("[RedisVL]")
 
 STATS_KEYS = [
@@ -32,6 +33,7 @@
     "vector_index_sz_mb",
 ]
 
+
 class Stats:
     usage = "\n".join(
         [
@@ -43,11 +45,7 @@ def __init__(self):
         parser = argparse.ArgumentParser(usage=self.usage)
 
         parser.add_argument(
-            "-f",
-            "--format",
-            help="Output format",
-            type=str,
-            default="rounded_outline"
+            "-f", "--format", help="Output format", type=str, default="rounded_outline"
         )
         parser = add_index_parsing_options(parser)
         args = parser.parse_args(sys.argv[2:])
@@ -57,7 +55,6 @@ def __init__(self):
             logger.error(e)
             exit(0)
 
-
     def stats(self, args: Namespace):
         """Obtain stats about an index
 

redisvl/cli/utils.py

@@ -1,5 +1,5 @@
 import os
-from argparse import Namespace, ArgumentParser
+from argparse import ArgumentParser, Namespace
 
 
 def create_redis_url(args: Namespace) -> str:
@@ -18,20 +18,15 @@ def create_redis_url(args: Namespace) -> str:
         url += args.host + ":" + str(args.port)
         return url
 
+
 def add_index_parsing_options(parser: ArgumentParser) -> ArgumentParser:
-    parser.add_argument(
-        "-i", "--index", help="Index name", type=str, required=False
-    )
+    parser.add_argument("-i", "--index", help="Index name", type=str, required=False)
     parser.add_argument(
         "-s", "--schema", help="Path to schema file", type=str, required=False
     )
     parser.add_argument("--host", help="Redis host", type=str, default="localhost")
     parser.add_argument("-p", "--port", help="Redis port", type=int, default=6379)
-    parser.add_argument(
-        "--user", help="Redis username", type=str, default="default"
-    )
+    parser.add_argument("--user", help="Redis username", type=str, default="default")
     parser.add_argument("--ssl", help="Use SSL", action="store_true")
-    parser.add_argument(
-        "-a", "--password", help="Redis password", type=str, default=""
-    )
+    parser.add_argument("-a", "--password", help="Redis password", type=str, default="")
     return parser

redisvl/query/__init__.py

@@ -1,3 +1,6 @@
-from redisvl.query.query import VectorQuery
+from redisvl.query.query import FilterQuery, VectorQuery
 
-__all__ = ["VectorQuery"]
+__all__ = [
+    "VectorQuery",
+    "FilterQuery",
+]

redisvl/query/filter.py

@@ -117,6 +117,7 @@ class Geo(FilterField):
     field in a Redis index.
 
     """
+
     OPERATORS = {
         FilterOperator.EQ: "==",
         FilterOperator.NE: "!=",
@@ -174,12 +175,13 @@ def __init__(self, longitude: float, latitude: float, unit: str = "km"):
 
 class GeoRadius(GeoSpec):
     """A GeoRadius is a GeoSpec representing a geographic radius"""
+
     def __init__(
         self,
         longitude: float,
         latitude: float,
         radius: Optional[int] = 1,
-        unit: Optional[str] = "km"
+        unit: Optional[str] = "km",
     ):
         """Create a GeoRadius specification (GeoSpec)
 
@@ -202,6 +204,7 @@ def get_args(self) -> List[Union[float, int, str]]:
 
 class Num(FilterField):
     """A Num is a FilterField representing a numeric field in a Redis index."""
+
     OPERATORS = {
         FilterOperator.EQ: "==",
         FilterOperator.NE: "!=",
@@ -311,6 +314,7 @@ def __le__(self, other: str) -> "FilterExpression":
 
 class Text(FilterField):
     """A Text is a FilterField representing a text field in a Redis index."""
+
     OPERATORS = {
         FilterOperator.EQ: "==",
         FilterOperator.NE: "!=",
@@ -399,6 +403,7 @@ class FilterExpression:
         ...     filter_expression=filter,
         ... )
     """
+
     def __init__(
         self,
         _filter: str = None,

redisvl/query/query.py

@@ -23,6 +23,88 @@ def params(self) -> Dict[str, Any]:
         pass
 
 
+class FilterQuery(BaseQuery):
+    def __init__(
+        self,
+        return_fields: List[str],
+        filter_expression: FilterExpression,
+        num_results: Optional[int] = 10,
+        params: Optional[Dict[str, Any]] = None,
+    ):
+        """Query for a filter expression.
+
+        Args:
+            return_fields (List[str]): The fields to return.
+            filter_expression (FilterExpression): The filter expression to query for.
+            num_results (Optional[int], optional): The number of results to return. Defaults to 10.
+            params (Optional[Dict[str, Any]], optional): The parameters for the query. Defaults to None.
+
+        Raises:
+            TypeError: If filter_expression is not of type redisvl.query.FilterExpression
+
+        Examples:
+            >>> from redisvl.query import FilterQuery
+            >>> from redisvl.query.filter import Tag
+            >>> t = Tag("brand") == "Nike"
+            >>> q = FilterQuery(return_fields=["brand", "price"], filter_expression=t)
+        """
+
+        super().__init__(return_fields, num_results)
+        self.set_filter(filter_expression)
+        self._params = params
+
+    def __str__(self) -> str:
+        return " ".join([str(x) for x in self.query.get_args()])
+
+    def set_filter(self, filter_expression: FilterExpression):
+        """Set the filter for the query.
+
+        Args:
+            filter_expression (FilterExpression): The filter to apply to the query.
+
+        Raises:
+            TypeError: If filter_expression is not of type redisvl.query.FilterExpression
+        """
+        if not isinstance(filter_expression, FilterExpression):
+            raise TypeError(
+                "filter_expression must be of type redisvl.query.FilterExpression"
+            )
+        self._filter = str(filter_expression)
+
+    def get_filter(self) -> FilterExpression:
+        """Get the filter for the query.
+
+        Returns:
+            FilterExpression: The filter for the query.
+        """
+        return self._filter
+
+    @property
+    def query(self) -> Query:
+        """Return a Redis-Py Query object representing the query.
+
+        Returns:
+            redis.commands.search.query.Query: The query object.
+        """
+        base_query = str(self._filter)
+        query = (
+            Query(base_query)
+            .return_fields(*self._return_fields)
+            .paging(0, self._num_results)
+            .dialect(2)
+        )
+        return query
+
+    @property
+    def params(self) -> Dict[str, Any]:
+        """Return the parameters for the query.
+
+        Returns:
+            Dict[str, Any]: The parameters for the query.
+        """
+        return self._params
+
+
 class VectorQuery(BaseQuery):
     dtypes = {
         "float32": np.float32,

redisvl/schema.py

@@ -156,4 +156,4 @@ def read_schema(file_path: str):
     with open(fp, "r") as f:
         schema = yaml.safe_load(f)
 
-    return SchemaModel(**schema)
+    return SchemaModel(**schema)

redisvl/vectorize/text/huggingface.py

@@ -80,9 +80,9 @@ def embed_many(
             TypeError: If the wrong input type is passed in for the test.
         """
         if not isinstance(texts, list):
-                raise TypeError("Must pass in a list of str values to embed.")
-        if  len(texts) > 0 and not isinstance(texts[0], str):
-                raise TypeError("Must pass in a list of str values to embed.")
+            raise TypeError("Must pass in a list of str values to embed.")
+        if len(texts) > 0 and not isinstance(texts[0], str):
+            raise TypeError("Must pass in a list of str values to embed.")
 
         embeddings: List = []
         for batch in self.batchify(texts, batch_size, preprocess):

redisvl/vectorize/text/openai.py

@@ -13,6 +13,7 @@ class OpenAITextVectorizer(BaseVectorizer):
     API key to be passed in the api_config dictionary. The API key can be obtained from
     https://api.openai.com/.
     """
+
     def __init__(self, model: str, api_config: Optional[Dict] = None):
         """Initialize the OpenAI vectorizer.
 
@@ -45,14 +46,13 @@ def __init__(self, model: str, api_config: Optional[Dict] = None):
     def _set_model_dims(self) -> int:
         try:
             embedding = self._model_client.create(
-                input=["dimension test"],
-                engine=self._model
+                input=["dimension test"], engine=self._model
             )["data"][0]["embedding"]
         except (KeyError, IndexError) as ke:
             raise ValueError(f"Unexpected response from the OpenAI API: {str(ke)}")
         except openai.error.AuthenticationError as ae:
             raise ValueError(f"Error authenticating with the OpenAI API: {str(ae)}")
-        except Exception as e: # pylint: disable=broad-except
+        except Exception as e:  # pylint: disable=broad-except
             # fall back (TODO get more specific)
             raise ValueError(f"Error setting embedding model dimensions: {str(e)}")
         return len(embedding)
@@ -87,9 +87,9 @@ def embed_many(
             TypeError: If the wrong input type is passed in for the test.
         """
         if not isinstance(texts, list):
-                raise TypeError("Must pass in a list of str values to embed.")
-        if  len(texts) > 0 and not isinstance(texts[0], str):
-                raise TypeError("Must pass in a list of str values to embed.")
+            raise TypeError("Must pass in a list of str values to embed.")
+        if len(texts) > 0 and not isinstance(texts[0], str):
+            raise TypeError("Must pass in a list of str values to embed.")
 
         embeddings: List = []
         for batch in self.batchify(texts, batch_size, preprocess):
@@ -164,9 +164,9 @@ async def aembed_many(
             TypeError: If the wrong input type is passed in for the test.
         """
         if not isinstance(texts, list):
-                raise TypeError("Must pass in a list of str values to embed.")
-        if  len(texts) > 0 and not isinstance(texts[0], str):
-                raise TypeError("Must pass in a list of str values to embed.")
+            raise TypeError("Must pass in a list of str values to embed.")
+        if len(texts) > 0 and not isinstance(texts[0], str):
+            raise TypeError("Must pass in a list of str values to embed.")
 
         embeddings: List = []
         for batch in self.batchify(texts, batch_size, preprocess):