similarity_threshold -> score_threshold

semantic_router/splitters/base.py

@@ -7,7 +7,7 @@ from semantic_router.encoders import BaseEncoder
 class BaseSplitter(BaseModel):
     name: str
     encoder: BaseEncoder
-    similarity_threshold: float
+    score_threshold: float
 
     def __call__(self, docs: List[str]) -> List[List[float]]:
         raise NotImplementedError("Subclasses must implement this method")

semantic_router/splitters/consecutive_sim.py

@@ -15,10 +15,10 @@ class ConsecutiveSimSplitter(BaseSplitter):
         self,
         encoder: BaseEncoder,
         name: str = "consecutive_similarity_splitter",
-        similarity_threshold: float = 0.45,
+        score_threshold: float = 0.45,
     ):
         super().__init__(
-            name=name, similarity_threshold=similarity_threshold, encoder=encoder
+            name=name, score_threshold=score_threshold, encoder=encoder
         )
 
     def __call__(self, docs: List[str]):
@@ -38,7 +38,7 @@ class ConsecutiveSimSplitter(BaseSplitter):
 
         for idx in range(1, total_docs):
             curr_sim_score = sim_matrix[idx - 1][idx]
-            if idx < len(sim_matrix) and curr_sim_score < self.similarity_threshold:
+            if idx < len(sim_matrix) and curr_sim_score < self.score_threshold:
                 splits.append(
                     DocumentSplit(
                         docs=list(docs[curr_split_start_idx:idx]),

semantic_router/splitters/cumulative_sim.py

@@ -15,10 +15,10 @@ class CumulativeSimSplitter(BaseSplitter):
         self,
         encoder: BaseEncoder,
         name: str = "cumulative_similarity_splitter",
-        similarity_threshold: float = 0.45,
+        score_threshold: float = 0.45,
     ):
         super().__init__(
-            name=name, similarity_threshold=similarity_threshold, encoder=encoder
+            name=name, score_threshold=score_threshold, encoder=encoder
         )
 
     def __call__(self, docs: List[str]):
@@ -49,7 +49,7 @@ class CumulativeSimSplitter(BaseSplitter):
                     * np.linalg.norm(next_doc_embed)
                 )
                 # Decision to split based on similarity score.
-                if curr_sim_score < self.similarity_threshold:
+                if curr_sim_score < self.score_threshold:
                     splits.append(
                         DocumentSplit(
                             docs=list(docs[curr_split_start_idx : idx + 1]),

semantic_router/text.py

@@ -61,11 +61,11 @@ class Conversation(BaseModel):
 
         if split_method == "consecutive_similarity":
             self.splitter = ConsecutiveSimSplitter(
-                encoder=encoder, similarity_threshold=threshold
+                encoder=encoder, score_threshold=threshold
             )
         elif split_method == "cumulative_similarity":
             self.splitter = CumulativeSimSplitter(
-                encoder=encoder, similarity_threshold=threshold
+                encoder=encoder, score_threshold=threshold
             )
         else:
             raise ValueError(f"Invalid split method: {split_method}")

tests/unit/test_splitters.py

@@ -22,7 +22,7 @@ def test_consecutive_sim_splitter():
         input_type="",
     )
     # Instantiate the ConsecutiveSimSplitter with the mock encoder
-    splitter = ConsecutiveSimSplitter(encoder=cohere_encoder, similarity_threshold=0.9)
+    splitter = ConsecutiveSimSplitter(encoder=cohere_encoder, score_threshold=0.9)
     splitter.encoder = mock_encoder
 
     # Define some documents
@@ -58,7 +58,7 @@ def test_cumulative_sim_splitter():
         cohere_api_key="",
         input_type="",
     )
-    splitter = CumulativeSimSplitter(encoder=cohere_encoder, similarity_threshold=0.9)
+    splitter = CumulativeSimSplitter(encoder=cohere_encoder, score_threshold=0.9)
     splitter.encoder = mock_encoder
 
     # Define some documents
@@ -163,7 +163,7 @@ def test_consecutive_similarity_splitter_single_doc():
     # Assuming any return value since it should not reach the point of using the encoder
     mock_encoder.return_value = np.array([[0.5, 0]])
 
-    splitter = ConsecutiveSimSplitter(encoder=mock_encoder, similarity_threshold=0.5)
+    splitter = ConsecutiveSimSplitter(encoder=mock_encoder, score_threshold=0.5)
 
     docs = ["doc1"]
     with pytest.raises(ValueError) as excinfo:
@@ -176,7 +176,7 @@ def test_cumulative_similarity_splitter_single_doc():
     # Assuming any return value since it should not reach the point of using the encoder
     mock_encoder.return_value = np.array([[0.5, 0]])
 
-    splitter = CumulativeSimSplitter(encoder=mock_encoder, similarity_threshold=0.5)
+    splitter = CumulativeSimSplitter(encoder=mock_encoder, score_threshold=0.5)
 
     docs = ["doc1"]
     with pytest.raises(ValueError) as excinfo: