Linted code

semantic_router/encoders/mistral.py

 """This file contains the MistralEncoder class which is used to encode text using MistralAI"""
+
 import os
 from time import sleep
 from typing import List, Optional

semantic_router/encoders/zure.py

@@ -66,9 +66,9 @@ class AzureOpenAIEncoder(BaseEncoder):
 
         try:
             self.client = openai.AzureOpenAI(
-                azure_deployment=str(self.deployment_name)
-                if self.deployment_name
-                else None,
+                azure_deployment=(
+                    str(self.deployment_name) if self.deployment_name else None
+                ),
                 api_key=str(self.api_key),
                 azure_endpoint=str(self.azure_endpoint),
                 api_version=str(self.api_version),

semantic_router/layer.py

@@ -111,9 +111,9 @@ class LayerConfig:
                     llm_class = getattr(llm_module, llm_data["class"])
                     # Instantiate the LLM class with the provided model name
                     llm = llm_class(name=llm_data["model"])
-                    route_data[
-                        "llm"
-                    ] = llm  # Reassign the instantiated llm object back to route_data
+                    route_data["llm"] = (
+                        llm  # Reassign the instantiated llm object back to route_data
+                    )
 
                 # Dynamically create the Route object using the remaining route_data
                 route = Route(**route_data)

semantic_router/splitters/consecutive_sim.py

@@ -8,7 +8,6 @@ from semantic_router.splitters.base import BaseSplitter
 
 
 class ConsecutiveSimSplitter(BaseSplitter):
-
     """
     Called "consecutive sim splitter" because we check the similarities of consecutive document embeddings (compare ith to i+1th document embedding).
     """

tests/unit/test_hybrid_layer.py

@@ -81,7 +81,11 @@ sparse_encoder.fit(["The quick brown fox", "jumps over the lazy dog", "Hello, wo
 class TestHybridRouteLayer:
     def test_initialization(self, openai_encoder, routes):
         route_layer = HybridRouteLayer(
-            encoder=openai_encoder, sparse_encoder=sparse_encoder, routes=routes, top_k=10, alpha=0.8,
+            encoder=openai_encoder,
+            sparse_encoder=sparse_encoder,
+            routes=routes,
+            top_k=10,
+            alpha=0.8,
         )
         assert route_layer.index is not None and route_layer.categories is not None
         assert openai_encoder.score_threshold == 0.82

tests/unit/test_splitters.py

@@ -47,10 +47,8 @@ def test_cumulative_sim_splitter():
     # Adjust the side_effect to simulate the encoder's behavior for cumulative document comparisons
     # This simplistic simulation assumes binary embeddings for demonstration purposes
     # Define a side_effect function for the mock encoder
-    mock_encoder.side_effect = (
-        lambda x: [[0.5, 0]]
-        if "doc1" in x or "doc1\ndoc2" in x or "doc2" in x
-        else [[0, 0.5]]
+    mock_encoder.side_effect = lambda x: (
+        [[0.5, 0]] if "doc1" in x or "doc1\ndoc2" in x or "doc2" in x else [[0, 0.5]]
     )
 
     # Instantiate the CumulativeSimSplitter with the mock encoder
@@ -112,8 +110,8 @@ def test_split_by_topic_consecutive_similarity():
 
 def test_split_by_topic_cumulative_similarity():
     mock_encoder = Mock()
-    mock_encoder.side_effect = (
-        lambda x: [[0.5, 0]] if "User: What is the latest news?" in x else [[0, 0.5]]
+    mock_encoder.side_effect = lambda x: (
+        [[0.5, 0]] if "User: What is the latest news?" in x else [[0, 0.5]]
     )
 
     messages = [