Reset function for VectorDBs (#2584)

mem0/vector_stores/redis.py

@@ -75,9 +75,48 @@ class RedisDB(VectorStoreBase):
         self.index.set_client(self.client)
         self.index.create(overwrite=True)
 
-    # TODO: Implement multiindex support.
-    def create_col(self, name, vector_size, distance):
-        raise NotImplementedError("Collection/Index creation not supported yet.")
+    def create_col(self, name=None, vector_size=None, distance=None):
+        """
+        Create a new collection (index) in Redis.
+
+        Args:
+            name (str, optional): Name for the collection. Defaults to None, which uses the current collection_name.
+            vector_size (int, optional): Size of the vector embeddings. Defaults to None, which uses the current embedding_model_dims.
+            distance (str, optional): Distance metric to use. Defaults to None, which uses 'cosine'.
+
+        Returns:
+            The created index object.
+        """
+        # Use provided parameters or fall back to instance attributes
+        collection_name = name or self.schema['index']['name']
+        embedding_dims = vector_size or self.embedding_model_dims
+        distance_metric = distance or "cosine"
+
+        # Create a new schema with the specified parameters
+        index_schema = {
+            "name": collection_name,
+            "prefix": f"mem0:{collection_name}",
+        }
+
+        # Copy the default fields and update the vector field with the specified dimensions
+        fields = DEFAULT_FIELDS.copy()
+        fields[-1]["attrs"]["dims"] = embedding_dims
+        fields[-1]["attrs"]["distance_metric"] = distance_metric
+
+        # Create the schema
+        schema = {"index": index_schema, "fields": fields}
+
+        # Create the index
+        index = SearchIndex.from_dict(schema)
+        index.set_client(self.client)
+        index.create(overwrite=True)
+
+        # Update instance attributes if creating a new collection
+        if name:
+            self.schema = schema
+            self.index = index
+
+        return index
 
     def insert(self, vectors: list, payloads: list = None, ids: list = None):
         data = []
@@ -194,6 +233,25 @@ class RedisDB(VectorStoreBase):
     def col_info(self, name):
         return self.index.info()
 
+    def reset(self):
+        """
+        Reset the index by deleting and recreating it.
+        """
+        collection_name = self.schema['index']['name']
+        logger.warning(f"Resetting index {collection_name}...")
+        self.delete_col()
+        
+        self.index = SearchIndex.from_dict(self.schema)
+        self.index.set_client(self.client)
+        self.index.create(overwrite=True)
+        
+        #or use 
+        #self.create_col(collection_name, self.embedding_model_dims)
+
+
+        # Recreate the index with the same parameters
+        self.create_col(collection_name, self.embedding_model_dims)
+
     def list(self, filters: dict = None, limit: int = None) -> list:
         """
         List all recent created memories from the vector store.