diff --git a/meilisearch/models/index.py b/meilisearch/models/index.py
index ada1782b..e1e286f9 100644
--- a/meilisearch/models/index.py
+++ b/meilisearch/models/index.py
@@ -56,10 +56,11 @@ class ProximityPrecision(str, Enum):
 
 class OpenAiEmbedder(CamelBase):
     source: str = "openAi"
-    model: Optional[str] = None  # Defaults to text-embedding-ada-002
+    model: Optional[str] = None  # Defaults to text-embedding-3-small
     dimensions: Optional[int] = None  # Uses the model default
     api_key: Optional[str] = None  # Can be provided through a CLI option or environment variable
     document_template: Optional[str] = None
+    document_template_max_bytes: Optional[int] = None  # Default to 400
 
 
 class HuggingFaceEmbedder(CamelBase):
@@ -67,6 +68,7 @@ class HuggingFaceEmbedder(CamelBase):
     model: Optional[str] = None  # Defaults to BAAI/bge-base-en-v1.5
     revision: Optional[str] = None
     document_template: Optional[str] = None
+    document_template_max_bytes: Optional[int] = None  # Default to 400
 
 
 class UserProvidedEmbedder(CamelBase):
diff --git a/tests/index/test_index_search_meilisearch.py b/tests/index/test_index_search_meilisearch.py
index ddf56e60..64840687 100644
--- a/tests/index/test_index_search_meilisearch.py
+++ b/tests/index/test_index_search_meilisearch.py
@@ -505,7 +505,8 @@ def test_show_ranking_score(index_with_documents):
 @pytest.mark.usefixtures("enable_vector_search")
 def test_vector_search(index_with_documents_and_vectors):
     response = index_with_documents_and_vectors().search(
-        "", opt_params={"vector": [0.1, 0.2], "hybrid": {"semanticRatio": 1.0}}
+        "",
+        opt_params={"vector": [0.1, 0.2], "hybrid": {"semanticRatio": 1.0, "embedder": "default"}},
     )
     assert len(response["hits"]) > 0