Use VectorStoreContent vs InterleavedContent in vector store files

This extracts the existing logic to convert chunks to
VectorStoreContent objects into a reusable method and uses that when
returning our list of Vector Store File contents.

It also adds an xfail test for deleting vector store files, as that's
not implemented yet but parking the implementation of that for now.

Signed-off-by: Ben Browning <bbrownin@redhat.com>

tests/integration/vector_io/test_openai_vector_stores.py

@@ -440,7 +440,7 @@ def test_openai_vector_store_search_with_max_num_results(
     assert len(search_response.data) == 2
 
 
-def test_openai_vector_store_attach_file_response_attributes(compat_client_with_empty_stores, client_with_models):
+def test_openai_vector_store_attach_file(compat_client_with_empty_stores, client_with_models):
     """Test OpenAI vector store attach file."""
     skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
 
@@ -453,7 +453,7 @@ def test_openai_vector_store_attach_file_response_attributes(compat_client_with_
     vector_store = compat_client.vector_stores.create(name="test_store")
 
     # Create a file
-    test_content = b"This is a test file"
+    test_content = b"The secret string is foobazbar."
     with BytesIO(test_content) as file_buffer:
         file_buffer.name = "openai_test.txt"
         file = compat_client.files.create(file=file_buffer, purpose="assistants")
@@ -480,6 +480,16 @@ def test_openai_vector_store_attach_file_response_attributes(compat_client_with_
     assert updated_vector_store.file_counts.failed == 0
     assert updated_vector_store.file_counts.in_progress == 0
 
+    # Search using OpenAI API to confirm our file attached
+    search_response = compat_client.vector_stores.search(
+        vector_store_id=vector_store.id, query="What is the secret string?", max_num_results=1
+    )
+    assert search_response is not None
+    assert len(search_response.data) > 0
+    top_result = search_response.data[0]
+    top_content = top_result.content[0].text
+    assert "foobazbar" in top_content.lower()
+
 
 def test_openai_vector_store_attach_files_on_creation(compat_client_with_empty_stores, client_with_models):
     """Test OpenAI vector store attach files on creation."""
@@ -689,6 +699,49 @@ def test_openai_vector_store_delete_file(compat_client_with_empty_stores, client
     assert updated_vector_store.file_counts.in_progress == 0
 
 
+# TODO: Remove this xfail once we have a way to remove embeddings from vector store
+@pytest.mark.xfail(reason="Vector Store Files delete doesn't remove embeddings from vecntor store", strict=True)
+def test_openai_vector_store_delete_file_removes_from_vector_store(compat_client_with_empty_stores, client_with_models):
+    """Test OpenAI vector store delete file removes from vector store."""
+    skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+    if isinstance(compat_client_with_empty_stores, LlamaStackClient):
+        pytest.skip("Vector Store Files attach is not yet supported with LlamaStackClient")
+
+    compat_client = compat_client_with_empty_stores
+
+    # Create a vector store
+    vector_store = compat_client.vector_stores.create(name="test_store")
+
+    # Create a file
+    test_content = b"The secret string is foobazbar."
+    with BytesIO(test_content) as file_buffer:
+        file_buffer.name = "openai_test.txt"
+        file = compat_client.files.create(file=file_buffer, purpose="assistants")
+
+    # Attach the file to the vector store
+    file_attach_response = compat_client.vector_stores.files.create(
+        vector_store_id=vector_store.id,
+        file_id=file.id,
+    )
+    assert file_attach_response.status == "completed"
+
+    # Search using OpenAI API to confirm our file attached
+    search_response = compat_client.vector_stores.search(
+        vector_store_id=vector_store.id, query="What is the secret string?", max_num_results=1
+    )
+    assert "foobazbar" in search_response.data[0].content[0].text.lower()
+
+    # Delete the file
+    compat_client.vector_stores.files.delete(vector_store_id=vector_store.id, file_id=file.id)
+
+    # Search using OpenAI API to confirm our file deleted
+    search_response = compat_client.vector_stores.search(
+        vector_store_id=vector_store.id, query="What is the secret string?", max_num_results=1
+    )
+    assert not search_response.data
+
+
 def test_openai_vector_store_update_file(compat_client_with_empty_stores, client_with_models):
     """Test OpenAI vector store update file."""
     skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)