Merge 0fb6fecedb into sapling-pr-archive-ehhuang

src/llama_stack/apis/vector_io/vector_io.py

@@ -260,7 +260,7 @@ class VectorStoreSearchResponsePage(BaseModel):
     """
 
     object: str = "vector_store.search_results.page"
-    search_query: str
+    search_query: list[str]
     data: list[VectorStoreSearchResponse]
     has_more: bool = False
     next_page: str | None = None
@@ -478,7 +478,7 @@ class OpenAICreateVectorStoreRequestWithExtraBody(BaseModel, extra="allow"):
     name: str | None = None
     file_ids: list[str] | None = None
     expires_after: dict[str, Any] | None = None
-    chunking_strategy: dict[str, Any] | None = None
+    chunking_strategy: VectorStoreChunkingStrategy | None = None
     metadata: dict[str, Any] | None = None
 
 

src/llama_stack/core/routers/vector_io.py

@@ -20,6 +20,8 @@ from llama_stack.apis.vector_io import (
     SearchRankingOptions,
     VectorIO,
     VectorStoreChunkingStrategy,
+    VectorStoreChunkingStrategyStatic,
+    VectorStoreChunkingStrategyStaticConfig,
     VectorStoreDeleteResponse,
     VectorStoreFileBatchObject,
     VectorStoreFileContentsResponse,
@@ -167,6 +169,13 @@ class VectorIORouter(VectorIO):
         if embedding_dimension is not None:
             params.model_extra["embedding_dimension"] = embedding_dimension
 
+        # Set chunking strategy explicitly if not provided
+        if params.chunking_strategy is None or params.chunking_strategy.type == "auto":
+            # actualize the chunking strategy to static
+            params.chunking_strategy = VectorStoreChunkingStrategyStatic(
+                static=VectorStoreChunkingStrategyStaticConfig()
+            )
+
         return await provider.openai_create_vector_store(params)
 
     async def openai_list_vector_stores(

tests/integration/vector_io/test_openai_vector_stores.py

@@ -350,7 +350,7 @@ def test_openai_vector_store_search_empty(
     assert search_response is not None
     assert hasattr(search_response, "data")
     assert len(search_response.data) == 0  # Empty store should return no results
-    assert search_response.search_query == "test query"
+    assert search_response.search_query == ["test query"]
     assert search_response.has_more is False
 
 
@@ -679,7 +679,7 @@ def test_openai_vector_store_attach_file(
     assert file_attach_response.id == file.id
     assert file_attach_response.vector_store_id == vector_store.id
     assert file_attach_response.status == "completed"
-    assert file_attach_response.chunking_strategy.type == "auto"
+    assert file_attach_response.chunking_strategy.type == "static"
     assert file_attach_response.created_at > 0
     assert not file_attach_response.last_error
 
@@ -815,8 +815,8 @@ def test_openai_vector_store_list_files(
     assert set(file_ids) == {file.id for file in files_list.data}
     assert files_list.data[0].object == "vector_store.file"
     assert files_list.data[0].vector_store_id == vector_store.id
-    assert files_list.data[0].status == "completed"
+    assert files_list.data[0].status in ["completed", "in_progress"]
-    assert files_list.data[0].chunking_strategy.type == "auto"
+    assert files_list.data[0].chunking_strategy.type == "static"
     assert files_list.data[0].created_at > 0
     assert files_list.first_id == files_list.data[0].id
     assert not files_list.data[0].last_error