diff --git a/docarray/base_doc/doc.py b/docarray/base_doc/doc.py
index 9328a040957..3e8f0a09a12 100644
--- a/docarray/base_doc/doc.py
+++ b/docarray/base_doc/doc.py
@@ -72,7 +72,11 @@ class MyDoc(BaseDoc):
     https://docs.pydantic.dev/usage/models/) and can be used in a similar way.
     """
 
-    id: Optional[ID] = Field(default_factory=lambda: ID(os.urandom(16).hex()))
+    id: Optional[ID] = Field(
+        description='The ID of the BaseDoc. This is useful for indexing in vector stores. If not set by user, it will automatically be assigned a random value',
+        default_factory=lambda: ID(os.urandom(16).hex()),
+        example=os.urandom(16).hex(),
+    )
 
     class Config:
         json_loads = orjson.loads
diff --git a/docarray/index/backends/elastic.py b/docarray/index/backends/elastic.py
index b83ce826411..c008fa29de0 100644
--- a/docarray/index/backends/elastic.py
+++ b/docarray/index/backends/elastic.py
@@ -67,6 +67,9 @@
 
 
 class ElasticDocIndex(BaseDocIndex, Generic[TSchema]):
+    _index_vector_params: Optional[Tuple[str]] = ('dims', 'similarity', 'index')
+    _index_vector_options: Optional[Tuple[str]] = ('m', 'ef_construction')
+
     def __init__(self, db_config=None, **kwargs):
         """Initialize ElasticDocIndex"""
         super().__init__(db_config=db_config, **kwargs)
@@ -82,9 +85,6 @@ def __init__(self, db_config=None, **kwargs):
         self._logger.debug('ElasticSearch client has been created')
 
         # ElasticSearh index setup
-        self._index_vector_params = ('dims', 'similarity', 'index')
-        self._index_vector_options = ('m', 'ef_construction')
-
         mappings: Dict[str, Any] = {
             'dynamic': True,
             '_source': {'enabled': 'true'},
@@ -572,20 +572,23 @@ def _filter_by_parent_id(self, id: str) -> List[str]:
     # Helpers                                     #
     ###############################################
 
-    def _create_index_mapping(self, col: '_ColumnInfo') -> Dict[str, Any]:
+    @classmethod
+    def _create_index_mapping(cls, col: '_ColumnInfo') -> Dict[str, Any]:
         """Create a new HNSW index for a column, and initialize it."""
 
         index = {'type': col.config['type'] if 'type' in col.config else col.db_type}
 
         if col.db_type == 'dense_vector':
-            for k in self._index_vector_params:
-                index[k] = col.config[k]
+            if cls._index_vector_params is not None:
+                for k in cls._index_vector_params:
+                    index[k] = col.config[k]
             if col.n_dim:
                 index['dims'] = col.n_dim
-            index['index_options'] = dict(
-                (k, col.config[k]) for k in self._index_vector_options
-            )
-            index['index_options']['type'] = 'hnsw'
+            if cls._index_vector_options is not None:
+                index['index_options'] = dict(
+                    (k, col.config[k]) for k in cls._index_vector_options
+                )
+                index['index_options']['type'] = 'hnsw'
         return index
 
     def _send_requests(
diff --git a/docarray/index/backends/elasticv7.py b/docarray/index/backends/elasticv7.py
index db6e229bf25..6ff428b0436 100644
--- a/docarray/index/backends/elasticv7.py
+++ b/docarray/index/backends/elasticv7.py
@@ -1,13 +1,13 @@
 import warnings
 from dataclasses import dataclass
-from typing import Any, Dict, List, Optional, Sequence, TypeVar, Union
+from typing import Any, Dict, List, Optional, Sequence, TypeVar, Union, Tuple
 
 import numpy as np
 from pydantic import parse_obj_as
 
 from docarray import BaseDoc
 from docarray.index import ElasticDocIndex
-from docarray.index.abstract import BaseDocIndex, _ColumnInfo
+from docarray.index.abstract import BaseDocIndex
 from docarray.typing import AnyTensor
 from docarray.typing.tensor.ndarray import NdArray
 from docarray.utils.find import _FindResult
@@ -17,6 +17,9 @@
 
 
 class ElasticV7DocIndex(ElasticDocIndex):
+    _index_vector_params: Optional[Tuple[str]] = ('dims',)
+    _index_vector_options: Optional[Tuple[str]] = None
+
     def __init__(self, db_config=None, **kwargs):
         """Initialize ElasticV7DocIndex"""
         from elasticsearch import __version__ as __es__version__
@@ -130,19 +133,6 @@ def execute_query(self, query: Dict[str, Any], *args, **kwargs) -> Any:
     # Helpers                                     #
     ###############################################
 
-    # ElasticSearch helpers
-    def _create_index_mapping(self, col: '_ColumnInfo') -> Dict[str, Any]:
-        """Create a new HNSW index for a column, and initialize it."""
-
-        index = col.config.copy()
-        if 'type' not in index:
-            index['type'] = col.db_type
-
-        if col.db_type == 'dense_vector' and col.n_dim:
-            index['dims'] = col.n_dim
-
-        return index
-
     def _form_search_body(self, query: np.ndarray, limit: int, search_field: str = '') -> Dict[str, Any]:  # type: ignore
         body = {
             'size': limit,
diff --git a/docarray/index/backends/hnswlib.py b/docarray/index/backends/hnswlib.py
index 8f08ae5c39d..c0ee904fb48 100644
--- a/docarray/index/backends/hnswlib.py
+++ b/docarray/index/backends/hnswlib.py
@@ -115,7 +115,7 @@ def __init__(self, db_config=None, **kwargs):
                 sub_docs_exist = True
             if safe_issubclass(col.docarray_type, AnyDocArray):
                 continue
-            if not col.config:
+            if not col.config or 'dim' not in col.config:
                 # non-tensor type; don't create an index
                 continue
             if not load_existing and (
diff --git a/tests/index/base_classes/test_base_doc_store.py b/tests/index/base_classes/test_base_doc_store.py
index 09f46ee4535..fa9444dcf5e 100644
--- a/tests/index/base_classes/test_base_doc_store.py
+++ b/tests/index/base_classes/test_base_doc_store.py
@@ -157,7 +157,7 @@ def test_create_columns():
     assert index._column_infos['id'].docarray_type == ID
     assert index._column_infos['id'].db_type == str
     assert index._column_infos['id'].n_dim is None
-    assert index._column_infos['id'].config == {'hi': 'there'}
+    assert index._column_infos['id'].config['hi'] == 'there'
 
     assert issubclass(index._column_infos['tens'].docarray_type, AbstractTensor)
     assert index._column_infos['tens'].db_type == str
@@ -171,7 +171,7 @@ def test_create_columns():
     assert index._column_infos['id'].docarray_type == ID
     assert index._column_infos['id'].db_type == str
     assert index._column_infos['id'].n_dim is None
-    assert index._column_infos['id'].config == {'hi': 'there'}
+    assert index._column_infos['id'].config['hi'] == 'there'
 
     assert issubclass(index._column_infos['tens_one'].docarray_type, AbstractTensor)
     assert index._column_infos['tens_one'].db_type == str
@@ -190,7 +190,7 @@ def test_create_columns():
     assert index._column_infos['id'].docarray_type == ID
     assert index._column_infos['id'].db_type == str
     assert index._column_infos['id'].n_dim is None
-    assert index._column_infos['id'].config == {'hi': 'there'}
+    assert index._column_infos['id'].config['hi'] == 'there'
 
     assert issubclass(index._column_infos['d__tens'].docarray_type, AbstractTensor)
     assert index._column_infos['d__tens'].db_type == str
@@ -214,7 +214,7 @@ def test_create_columns():
     assert index._subindices['d']._column_infos['id'].docarray_type == ID
     assert index._subindices['d']._column_infos['id'].db_type == str
     assert index._subindices['d']._column_infos['id'].n_dim is None
-    assert index._subindices['d']._column_infos['id'].config == {'hi': 'there'}
+    assert index._subindices['d']._column_infos['id'].config['hi'] == 'there'
 
     assert issubclass(
         index._subindices['d']._column_infos['tens'].docarray_type, AbstractTensor
@@ -262,10 +262,10 @@ def test_create_columns():
     assert (
         index._subindices['d_root']._subindices['d']._column_infos['id'].n_dim is None
     )
-    assert index._subindices['d_root']._subindices['d']._column_infos['id'].config == {
-        'hi': 'there'
-    }
-
+    assert (
+        index._subindices['d_root']._subindices['d']._column_infos['id'].config['hi']
+        == 'there'
+    )
     assert issubclass(
         index._subindices['d_root']
         ._subindices['d']