Support for context documents in search (Personalization) - Revised

src/marqo/index.py

@@ -227,7 +227,8 @@ def search(self, q: Optional[Union[str, dict]] = None, searchable_attributes: Op
                approximate_threshold: Optional[float] = None,
                language: Optional[str] = None,
                sort_by: Optional[dict] = None,
-               relevance_cutoff: Optional[dict] = None
+               relevance_cutoff: Optional[dict] = None,
+               interpolation_method: Optional[str] = None
                ) -> Dict[str, Any]:
         """Search the index.
 
@@ -268,11 +269,12 @@ def search(self, q: Optional[Union[str, dict]] = None, searchable_attributes: Op
             rerank_depth: The number of documents to rerank with score modifiers if used with hybrid search.
                 Number of hits to get from each shard if used with tensor search.
             facets: a dictionary of facets to be used for facet search.
-            track_total_hits: return total number of lexical matches
+            track_total_hits: Set to True to return total number of lexical or tensor matches
             approximate_threshold: hit ratio threshold for deciding if a nearest neighbor search should be performed as
                 an exact search, rather than an approximate search
             sort_by: a dictionary of the sort_by parameters to be used for sorting the results
             relevance_cutoff: a dictionary of the relevance cutoff parameters
+            interpolation_method: the interpolation method to use for combining query & context embeddings.
 
         Returns:
             Dictionary with hits and other metadata
@@ -314,7 +316,8 @@ def search(self, q: Optional[Union[str, dict]] = None, searchable_attributes: Op
             "trackTotalHits": track_total_hits,
             "language": language,
             "sortBy": sort_by,
-            "relevanceCutoff": relevance_cutoff
+            "relevanceCutoff": relevance_cutoff,
+            "interpolationMethod": interpolation_method
         }
 
         body = {k: v for k, v in body.items() if v is not None}