support dynamic distance threshold

redisvl/extensions/llmcache/semantic.py

@@ -233,6 +233,7 @@ def check(
         num_results: int = 1,
         return_fields: Optional[List[str]] = None,
         filter_expression: Optional[FilterExpression] = None,
+        distance_threshold: Optional[float] = None,
     ) -> List[Dict[str, Any]]:
         """Checks the semantic cache for results similar to the specified prompt
         or vector.
@@ -255,6 +256,8 @@ def check(
             filter_expression (Optional[FilterExpression]) : Optional filter expression
                 that can be used to filter cache results. Defaults to None and
                 the full cache will be searched.
+            distance_threshold (Optional[float]): The threshold for semantic
+                vector distance.
 
         Returns:
             List[Dict[str, Any]]: A list of dicts containing the requested
@@ -274,9 +277,12 @@ def check(
         if not (prompt or vector):
             raise ValueError("Either prompt or vector must be specified.")
 
+        # overrides
+        distance_threshold = distance_threshold or self._distance_threshold
+        return_fields = return_fields or self.return_fields
         vector = vector or self._vectorize_prompt(prompt)
+
         self._check_vector_dims(vector)
-        return_fields = return_fields or self.return_fields
 
         if not isinstance(return_fields, list):
             raise TypeError("return_fields must be a list of field names")
@@ -285,7 +291,7 @@ def check(
             vector=vector,
             vector_field_name=self.vector_field_name,
             return_fields=self.return_fields,
-            distance_threshold=self._distance_threshold,
+            distance_threshold=distance_threshold,
             num_results=num_results,
             return_score=True,
             filter_expression=filter_expression,

redisvl/extensions/session_manager/semantic_session.py

@@ -137,6 +137,7 @@ def get_relevant(
         fall_back: bool = False,
         session_tag: Optional[str] = None,
         raw: bool = False,
+        distance_threshold: Optional[float] = None,
     ) -> Union[List[str], List[Dict[str, str]]]:
         """Searches the chat history for information semantically related to
         the specified prompt.
@@ -151,10 +152,12 @@ def get_relevant(
             as_text (bool): Whether to return the prompts and responses as text
             or as JSON
             top_k (int): The number of previous messages to return. Default is 5.
-            fall_back (bool): Whether to drop back to recent conversation history
-                if no relevant context is found.
             session_tag (Optional[str]): Tag to be added to entries to link to a specific
                 session. Defaults to instance uuid.
+            distance_threshold (Optional[float]): The threshold for semantic
+                vector distance.
+            fall_back (bool): Whether to drop back to recent conversation history
+                if no relevant context is found.
             raw (bool): Whether to return the full Redis hash entry or just the
                 message.
 
@@ -169,6 +172,9 @@ def get_relevant(
         if top_k == 0:
             return []
 
+        # override distance threshold
+        distance_threshold = distance_threshold or self._distance_threshold
+
         return_fields = [
             self.session_field_name,
             self.role_field_name,
@@ -187,7 +193,7 @@ def get_relevant(
             vector=self._vectorizer.embed(prompt),
             vector_field_name=self.vector_field_name,
             return_fields=return_fields,
-            distance_threshold=self._distance_threshold,
+            distance_threshold=distance_threshold,
             num_results=top_k,
             return_score=True,
             filter_expression=session_filter,

tests/integration/test_llmcache.py

@@ -95,7 +95,7 @@ def test_store_and_check(cache, vectorizer):
     vector = vectorizer.embed(prompt)
 
     cache.store(prompt, response, vector=vector)
-    check_result = cache.check(vector=vector)
+    check_result = cache.check(vector=vector, distance_threshold=0.4)
 
     assert len(check_result) == 1
     print(check_result, flush=True)

tests/integration/test_session_manager.py

@@ -463,6 +463,10 @@ def test_semantic_add_and_get_relevant(semantic_session):
     semantic_session.set_distance_threshold(0.5)
     default_context = semantic_session.get_relevant("list of fruits and vegetables")
     assert len(default_context) == 5  # 2 pairs of prompt:response, and system
+    assert default_context == semantic_session.get_relevant(
+        "list of fruits and vegetables",
+        distance_threshold=0.5
+    )
 
     # test tool calls can also be returned
     context = semantic_session.get_relevant("winter sports like skiing")