From eb2b24059433a52d339769be96992154573e72b6 Mon Sep 17 00:00:00 2001
From: slekkala1 <swapna942@meta.com>
Date: Tue, 21 Oct 2025 14:40:14 -0700
Subject: [PATCH] fix: remove consistency checks (#3881)

# What does this PR do?
metadata is conflicting with the default embedding model set on server
side via extra body, removing the check and just letting metadata take
precedence over extra body

`ValueError: Embedding model inconsistent between metadata
('text-embedding-3-small') and extra_body
     ('sentence-transformers/nomic-ai/nomic-embed-text-v1.5')`
## Test Plan
CI
---
 .../utils/memory/openai_vector_store_mixin.py | 10 -----
 .../test_vector_io_openai_vector_stores.py    | 44 -------------------
 2 files changed, 54 deletions(-)

diff --git a/llama_stack/providers/utils/memory/openai_vector_store_mixin.py b/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
index 6629fb965..8f9fb9fb4 100644
--- a/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
+++ b/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
@@ -370,16 +370,6 @@ class OpenAIVectorStoreMixin(ABC):
             logger.debug(
                 f"Using embedding config from metadata (takes precedence over extra_body): model='{embedding_model}', dimension={embedding_dimension}"
             )
-
-            # Check for conflicts with extra_body
-            if extra_body.get("embedding_model") and extra_body["embedding_model"] != embedding_model:
-                raise ValueError(
-                    f"Embedding model inconsistent between metadata ('{embedding_model}') and extra_body ('{extra_body['embedding_model']}')"
-                )
-            if extra_body.get("embedding_dimension") and extra_body["embedding_dimension"] != embedding_dimension:
-                raise ValueError(
-                    f"Embedding dimension inconsistent between metadata ({embedding_dimension}) and extra_body ({extra_body['embedding_dimension']})"
-                )
         else:
             embedding_model = extra_body.get("embedding_model")
             embedding_dimension = extra_body.get("embedding_dimension", EMBEDDING_DIMENSION)
diff --git a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py
index 65d7b7602..9d9c767f6 100644
--- a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py
+++ b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py
@@ -1079,50 +1079,6 @@ async def test_embedding_config_consistency_check_passes(vector_io_adapter):
     assert call_args.embedding_dimension == 768
 
 
-async def test_embedding_config_inconsistency_errors(vector_io_adapter):
-    """Test that inconsistent embedding config between metadata and extra_body raises errors."""
-
-    # Mock register_vector_store to avoid actual registration
-    vector_io_adapter.register_vector_store = AsyncMock()
-    # Set provider_id attribute for the adapter
-    vector_io_adapter.__provider_id__ = "test_provider"
-
-    # Test with inconsistent embedding model
-    params = OpenAICreateVectorStoreRequestWithExtraBody(
-        name="test_store",
-        metadata={
-            "embedding_model": "metadata-model",
-            "embedding_dimension": "768",
-        },
-        **{
-            "embedding_model": "extra-body-model",
-            "embedding_dimension": 768,
-        },
-    )
-
-    with pytest.raises(ValueError, match="Embedding model inconsistent between metadata"):
-        await vector_io_adapter.openai_create_vector_store(params)
-
-    # Reset mock for second test
-    vector_io_adapter.register_vector_store.reset_mock()
-
-    # Test with inconsistent embedding dimension
-    params = OpenAICreateVectorStoreRequestWithExtraBody(
-        name="test_store",
-        metadata={
-            "embedding_model": "same-model",
-            "embedding_dimension": "512",
-        },
-        **{
-            "embedding_model": "same-model",
-            "embedding_dimension": 1024,
-        },
-    )
-
-    with pytest.raises(ValueError, match="Embedding dimension inconsistent between metadata"):
-        await vector_io_adapter.openai_create_vector_store(params)
-
-
 async def test_embedding_config_defaults_when_missing(vector_io_adapter):
     """Test that embedding dimension defaults to 768 when not provided."""