update param name

docs/components/vectordbs/dbs/azure_ai_search.mdx

@@ -61,7 +61,7 @@ config = {
             "api_key": "*****",
             "collection_name": "mem0", 
             "embedding_model_dims": 1536,
-            "use_hybrid_search": True,
+            "hybrid_search": True,
             "vector_filter_mode": "postFilter"
         }
     }
@@ -79,7 +79,7 @@ config = {
 | `compression_type` | Type of vector compression to use | `none` | `none`, `scalar`, `binary` |
 | `use_float16` | Store vectors in half precision (Edm.Half) | `False` | `True`, `False` |
 | `vector_filter_mode` | Vector filter mode to use | `preFilter` | `postFilter`, `preFilter` |
-| `use_hybrid_search` | Use hybrid search | `False` | `True`, `False` |
+| `hybrid_search` | Use hybrid search | `False` | `True`, `False` |
 
 ## Notes on Configuration Options
 

mem0/configs/vector_stores/azure_ai_search.py

@@ -14,7 +14,7 @@ class AzureAISearchConfig(BaseModel):
         False,
         description="Whether to store vectors in half precision (Edm.Half) instead of full precision (Edm.Single)",
     )
-    use_hybrid_search: bool = Field(
+    hybrid_search: bool = Field(
         False, description="Whether to use hybrid search. If True, vector_filter_mode must be 'preFilter'"
     )
     vector_filter_mode: Optional[str] = Field(

mem0/vector_stores/azure_ai_search.py

@@ -47,7 +47,7 @@ def __init__(
         embedding_model_dims,
         compression_type: Optional[str] = None,
         use_float16: bool = False,
-        use_hybrid_search: bool = False,
+        hybrid_search: bool = False,
         vector_filter_mode: Optional[str] = None,
     ):
         """
@@ -62,7 +62,7 @@ def __init__(
                 Allowed values are None (no quantization), "scalar", or "binary".
             use_float16 (bool): Whether to store vectors in half precision (Edm.Half) or full precision (Edm.Single).
                 (Note: This flag is preserved from the initial implementation per feedback.)
-            use_hybrid_search (bool): Whether to use hybrid search. Default is False.
+            hybrid_search (bool): Whether to use hybrid search. Default is False.
             vector_filter_mode (Optional[str]): Mode for vector filtering. Default is "preFilter".
         """
         self.index_name = collection_name
@@ -210,7 +210,7 @@ def search(self, query, vectors, limit=5, filters=None):
             filter_expression = self._build_filter_expression(filters)
 
         vector_query = VectorizedQuery(vector=vectors, k_nearest_neighbors=limit, fields="vector")
-        if self.use_hybrid_search:
+        if self.hybrid_search:
             search_results = self.search_client.search(
                 search_text=query,
                 vector_queries=[vector_query],