refactor: remove outdated vector store tests

tests/test_vector_store.py

@@ -1,41 +0,0 @@
-"""
-Tests regarding the vector store class, including checking
-compatibility between different transformers and local vector
-stores (index.faiss)
-"""
-import pytest
-from application.vectorstore.faiss import FaissStore
-from application.core.settings import settings
-
-def test_init_local_faiss_store_huggingface():
-    """
-    Test that asserts that initializing a FaissStore with
-    the huggingface sentence transformer below together with the
-    index.faiss file in the application/ folder results in a
-    dimension mismatch error.
-    """
-    import os
-    from langchain.embeddings import HuggingFaceEmbeddings
-    from langchain.docstore.document import Document
-    from langchain_community.vectorstores import FAISS
-
-    # Ensure application directory exists
-    index_path = os.path.join("application")
-    os.makedirs(index_path, exist_ok=True)
-
-    # Create an index.faiss with a different embeddings dimension
-    # Use a different embedding model with a smaller dimension
-    other_embedding_model = "sentence-transformers/all-MiniLM-L6-v2"  # Dimension 384
-    other_embeddings = HuggingFaceEmbeddings(model_name=other_embedding_model)
-    # Create some dummy documents
-    docs = [Document(page_content="Test document")]
-    # Create index using the other embeddings
-    other_docsearch = FAISS.from_documents(docs, other_embeddings)
-    # Save index to application/
-    other_docsearch.save_local(index_path)
-
-    # Now set the EMBEDDINGS_NAME to the one with a different dimension
-    settings.EMBEDDINGS_NAME = "huggingface_sentence-transformers/all-mpnet-base-v2"  # Dimension 768
-    with pytest.raises(ValueError) as exc_info:
-        FaissStore("", None)
-    assert "Embedding dimension mismatch" in str(exc_info.value)