Adding latest 8.4 image to test matrix. Updating the Hybrid VSIM query format to be in sync with spec after srv issue was fixed. (#3843)

Author: petyaslavova

.github/workflows/integration.yaml

@@ -76,7 +76,7 @@ jobs:
       max-parallel: 15
       fail-fast: false
       matrix:
-        redis-version: ['8.4-RC1-pre.2', '${{ needs.redis_version.outputs.CURRENT }}', '8.0.2' ,'7.4.4', '7.2.9']
+        redis-version: ['8.4-GA-pre.2', '${{ needs.redis_version.outputs.CURRENT }}', '8.0.2' ,'7.4.4', '7.2.9']
         python-version: ['3.10', '3.14']
         parser-backend: ['plain']
         event-loop: ['asyncio']

redis/commands/search/hybrid_query.py

@@ -77,6 +77,7 @@ def __init__(
         vsim_search_method: Optional[VectorSearchMethods] = None,
         vsim_search_method_params: Optional[Dict[str, Any]] = None,
         filter: Optional["Filter"] = None,
+        yield_score_as: Optional[str] = None,
     ) -> None:
         """
         Create a new hybrid vsim query object.
@@ -96,8 +97,7 @@ def __init__(
                 Example for RANGE: {"RADIUS": 10, "EPSILON": 0.1}
                                     where RADIUS is mandatory and defines the radius of the search
                                     and EPSILON is optional and defines the accuracy of the search.
-                For both KNN and RANGE, the following parameter is optional:
-                    YIELD_SCORE_AS: The name of the field to yield the calculated score as.
+            yield_score_as: The name of the field to yield the score as.
 
             filter: If defined, a filter will be applied on the vsim query results.
         """
@@ -108,6 +108,7 @@ def __init__(
         else:
             self._vsim_method_params = None
         self._filter = filter
+        self._yield_score_as = yield_score_as
 
     def vector_field(self) -> str:
         """Return the vector field name of this query object."""
@@ -149,12 +150,21 @@ def filter(self, flt: "HybridFilter") -> "HybridVsimQuery":
         self._filter = flt
         return self
 
+    def yield_score_as(self, alias: str) -> "HybridVsimQuery":
+        """
+        Return the score as a field with name `alias`.
+        """
+        self._yield_score_as = alias
+        return self
+
     def get_args(self) -> List[str]:
         args = ["VSIM", self._vector_field, self._vector_data]
         if self._vsim_method_params:
             args.extend(self._vsim_method_params)
         if self._filter:
             args.extend(self._filter.args)
+        if self._yield_score_as:
+            args.extend(("YIELD_SCORE_AS", self._yield_score_as))
 
         return args
 

tests/test_asyncio/test_search.py

@@ -2636,11 +2636,8 @@ async def test_hybrid_search_query_with_combine_all_score_aliases(self, decoded_
             vector_field_name="@embedding-hnsw",
             vector_data="abcd1234efgh5678",
             vsim_search_method=VectorSearchMethods.KNN,
-            vsim_search_method_params={
-                "K": 3,
-                "EF_RUNTIME": 1,
-                "YIELD_SCORE_AS": "vsim_score",
-            },
+            vsim_search_method_params={"K": 3, "EF_RUNTIME": 1},
+            yield_score_as="vsim_score",
         )
 
         hybrid_query = HybridQuery(search_query, vsim_query)

tests/test_search.py

@@ -4347,11 +4347,8 @@ def test_hybrid_search_query_with_vsim_score_aliases(self, client):
             vector_field_name="@embedding-hnsw",
             vector_data="abcd1234efgh5678",
             vsim_search_method=VectorSearchMethods.KNN,
-            vsim_search_method_params={
-                "K": 3,
-                "EF_RUNTIME": 1,
-                "YIELD_SCORE_AS": "vsim_score",
-            },
+            vsim_search_method_params={"K": 3, "EF_RUNTIME": 1},
+            yield_score_as="vsim_score",
         )
 
         hybrid_query = HybridQuery(search_query, vsim_query)
@@ -4433,11 +4430,8 @@ def test_hybrid_search_query_with_combine_all_score_aliases(self, client):
             vector_field_name="@embedding-hnsw",
             vector_data="abcd1234efgh5678",
             vsim_search_method=VectorSearchMethods.KNN,
-            vsim_search_method_params={
-                "K": 3,
-                "EF_RUNTIME": 1,
-                "YIELD_SCORE_AS": "vsim_score",
-            },
+            vsim_search_method_params={"K": 3, "EF_RUNTIME": 1},
+            yield_score_as="vsim_score",
         )
 
         hybrid_query = HybridQuery(search_query, vsim_query)