Change aggregation method names to lower case

semantic_router/hybrid_layer.py

@@ -25,7 +25,7 @@ def __init__(
         routes: List[Route] = [],
         alpha: float = 0.3,
         top_k: int = 5,
-        aggregation: str = "SUM",
+        aggregation: str = "sum",
     ):
         self.encoder = encoder
         self.score_threshold = self.encoder.score_threshold
@@ -41,7 +41,7 @@ def __init__(
         if self.top_k < 1:
             raise ValueError(f"top_k needs to be >= 1, but was: {self.top_k}.")
         self.aggregation = aggregation
-        if self.aggregation not in ["SUM", "MEAN", "MAX"]:
+        if self.aggregation not in ["sum", "mean", "max"]:
             raise ValueError(
                 f"Unsupported aggregation method chosen: {aggregation}. Choose either 'SUM', 'MEAN', or 'MAX'."
             )
@@ -172,12 +172,12 @@ def _convex_scaling(self, dense: np.ndarray, sparse: np.ndarray):
         sparse = np.array(sparse) * (1 - self.alpha)
         return dense, sparse
 
-    def _set_aggregation_method(self, aggregation: str = "SUM"):
-        if aggregation == "SUM":
+    def _set_aggregation_method(self, aggregation: str = "sum"):
+        if aggregation == "sum":
             return lambda x: sum(x)
-        elif aggregation == "MEAN":
+        elif aggregation == "mean":
             return lambda x: np.mean(x)
-        elif aggregation == "MAX":
+        elif aggregation == "max":
             return lambda x: max(x)
         else:
             raise ValueError(

semantic_router/layer.py

@@ -183,7 +183,7 @@ def __init__(
         routes: Optional[List[Route]] = None,
         index: Optional[BaseIndex] = None,  # type: ignore
         top_k: int = 5,
-        aggregation: str = "SUM",
+        aggregation: str = "sum",
     ):
         logger.info("local")
         self.index: BaseIndex = index if index is not None else LocalIndex()
@@ -202,7 +202,7 @@ def __init__(
         if self.top_k < 1:
             raise ValueError(f"top_k needs to be >= 1, but was: {self.top_k}.")
         self.aggregation = aggregation
-        if self.aggregation not in ["SUM", "MEAN", "MAX"]:
+        if self.aggregation not in ["sum", "mean", "max"]:
             raise ValueError(
                 f"Unsupported aggregation method chosen: {aggregation}. Choose either 'SUM', 'MEAN', or 'MAX'."
             )
@@ -403,12 +403,12 @@ def _retrieve(self, xq: Any, top_k: int = 5) -> List[dict]:
         scores, routes = self.index.query(vector=xq, top_k=top_k)
         return [{"route": d, "score": s.item()} for d, s in zip(routes, scores)]
 
-    def _set_aggregation_method(self, aggregation: str = "SUM"):
-        if aggregation == "SUM":
+    def _set_aggregation_method(self, aggregation: str = "sum"):
+        if aggregation == "sum":
             return lambda x: sum(x)
-        elif aggregation == "MEAN":
+        elif aggregation == "mean":
             return lambda x: np.mean(x)
-        elif aggregation == "MAX":
+        elif aggregation == "max":
             return lambda x: max(x)
         else:
             raise ValueError(

tests/unit/test_hybrid_layer.py

@@ -194,7 +194,7 @@ def test_add_route_tfidf(self, cohere_encoder, tfidf_encoder, routes):
         assert len(hybrid_route_layer.sparse_index) == len(all_utterances)
 
     def test_setting_aggregation_methods(self, openai_encoder, routes):
-        for agg in ["SUM", "MEAN", "MAX"]:
+        for agg in ["sum", "mean", "max"]:
             route_layer = HybridRouteLayer(
                 encoder=openai_encoder,
                 sparse_encoder=sparse_encoder,
@@ -217,7 +217,7 @@ def test_semantic_classify_multiple_routes_with_different_aggregation(
             {"route": "Route 3", "score": 0.1},
             {"route": "Route 3", "score": 1.0},
         ]
-        for agg in ["SUM", "MEAN", "MAX"]:
+        for agg in ["sum", "mean", "max"]:
             route_layer = HybridRouteLayer(
                 encoder=openai_encoder,
                 sparse_encoder=sparse_encoder,
@@ -226,13 +226,13 @@ def test_semantic_classify_multiple_routes_with_different_aggregation(
             )
             classification, score = route_layer._semantic_classify(route_scores)
 
-            if agg == "SUM":
+            if agg == "sum":
                 assert classification == "Route 1"
                 assert score == [0.5, 0.5, 0.5, 0.5]
-            elif agg == "MEAN":
+            elif agg == "mean":
                 assert classification == "Route 2"
                 assert score == [0.4, 0.6, 0.8]
-            elif agg == "MAX":
+            elif agg == "max":
                 assert classification == "Route 3"
                 assert score == [0.1, 1.0]
 

tests/unit/test_layer.py

@@ -525,7 +525,7 @@ def test_remove(self):
         assert layer_config.routes == []
 
     def test_setting_aggregation_methods(self, openai_encoder, routes):
-        for agg in ["SUM", "MEAN", "MAX"]:
+        for agg in ["sum", "mean", "max"]:
             route_layer = RouteLayer(
                 encoder=openai_encoder,
                 routes=routes,
@@ -547,20 +547,20 @@ def test_semantic_classify_multiple_routes_with_different_aggregation(
             {"route": "Route 3", "score": 0.1},
             {"route": "Route 3", "score": 1.0},
         ]
-        for agg in ["SUM", "MEAN", "MAX"]:
+        for agg in ["sum", "mean", "max"]:
             route_layer = RouteLayer(
                 encoder=openai_encoder,
                 routes=routes,
                 aggregation=agg,
             )
             classification, score = route_layer._semantic_classify(route_scores)
 
-            if agg == "SUM":
+            if agg == "sum":
                 assert classification == "Route 1"
                 assert score == [0.5, 0.5, 0.5, 0.5]
-            elif agg == "MEAN":
+            elif agg == "mean":
                 assert classification == "Route 2"
                 assert score == [0.4, 0.6, 0.8]
-            elif agg == "MAX":
+            elif agg == "max":
                 assert classification == "Route 3"
                 assert score == [0.1, 1.0]