address comments

Author: Daria

docs/index.rst

@@ -428,7 +428,7 @@ A `sample benchmark <https://github.com/zilliztech/gpt-cache/blob/main/examples/
   * [x] Support `Chroma <https://github.com/chroma-core/chroma>`_\ , the AI-native open-source embedding database.
   * [x] Support `DocArray <https://github.com/docarray/docarray>`_\ , DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
   * [x] Support `Redis <https://redis.io/>`_.
-  * [x] Support `ValkeySearch <https://github.com/valkey-io/valkey-search/>`_\ , provided as a Valkey module, is a high-performance Vector Similarity Search engine optimized for AI-driven workloads.
+  * [x] Support `Valkey with valkey-search <https://github.com/valkey-io/valkey-search/>`_\ , is a high-performance Vector Similarity Search engine optimized for AI-driven workloads.
   * [ ] Support qdrant
   * [ ] Support weaviate
   * [ ] Support other vector databases.

gptcache/manager/vector_data/redis_vectorstore.py

@@ -41,6 +41,7 @@ class RedisVectorStore(VectorBase):
 
             vector_base = VectorBase("redis", dimension=10)
     """
+
     def __init__(
         self,
         host: str = "localhost",
@@ -72,6 +73,9 @@ def _check_sortby_support(self, index_name: str, sort_field: str) -> bool:
         - If the server *parses* SORTBY but complains about the field or schema (e.g., 'Property is not sortable'
         or 'No such field'), we treat that as SORTBY being *supported* and bubble up the original error when the real
         query runs.
+        NOTE: Valkey KNN results are ALWAYS sorted by distance.
+        'The first name/value pair is for the distance computed' -
+        Ref: https://github.com/valkey-io/valkey-search/blob/main/COMMANDS.md
         """
 
         if self._sortby_supported is not None:
@@ -83,7 +87,12 @@ def _check_sortby_support(self, index_name: str, sort_field: str) -> bool:
 
         except ResponseError as e:
             if "SORTBY" in str(e):
-                self._sortby_supported = False
+                try:
+                    info = self._client.info("server")
+                    is_valkey = info.get("server_name") == "valkey" or "valkey_version" in info
+                    self._sortby_supported = not is_valkey
+                except Exception:
+                    self._sortby_supported = False
             else:
                 self._sortby_supported = True
             return self._sortby_supported

tests/unit_tests/manager/test_redis.py

@@ -78,7 +78,7 @@ def test_redis_vector_store_sortby_supported(monkeypatch, ascending):
 
     from gptcache.manager.vector_data.redis_vectorstore import RedisVectorStore
 
-    def _always_supports_sortby() -> bool:  # noqa: ARG002
+    def _always_supports_sortby(self, index_name, field) -> bool:  # noqa: ARG002
         return not _is_valkey()
 
     monkeypatch.setattr(
@@ -101,7 +101,7 @@ def _always_supports_sortby() -> bool:  # noqa: ARG002
 def test_redis_vector_store_sortby_unsupported(monkeypatch):
     """
     Force the probe to say SORTBY is NOT supported (e.g., Valkey without SORTBY).
-    The search should still succeed and return k results; we don't assert ordering here.
+    The search should still succeed and return k results;
     """
     encoder = Onnx()
     dim = encoder.dimension
@@ -125,3 +125,9 @@ def _never_supports_sortby(self, index_name, field):  # noqa: ARG002
     res = vector_base.search(query_vec, top_k=k)
     assert isinstance(res, (list, tuple))
     assert len(res) == k
+
+    scores = [extract_score(item) for item in res]
+    if _is_valkey():
+        assert is_nondecreasing(scores), f"Scores not sorted ASC: {scores}"
+    else:
+        assert not is_nondecreasing(scores) and not _is_nonincreasing(scores), f"Scores sorted: {scores}"