dim = 1536
doc1_index = faiss.IndexFlatL2(dim)
doc1_documents = []
for i, doc in enumerate(response):
    source = doc["_source"]
    doc1_index.add(np.asarray([source["content_vector"]]))
    doc1_documents.append(Document(text=source["content"]))

doc1_vector_store = FaissVectorStore(faiss_index=doc1_index)
storage_context = StorageContext.from_defaults(vector_store=doc1_vector_store)
doc1_llama_index = VectorStoreIndex.from_vector_store(doc1_documents, storage_context=storage_context)


##### Output 

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[28], line 3
      1 doc1_vector_store = FaissVectorStore(faiss_index=doc1_index)
      2 storage_context = StorageContext.from_defaults(vector_store=doc1_vector_store)
----> 3 doc1_llama_index = VectorStoreIndex.from_vector_store(doc1_documents, storage_context=storage_context)

File c:\Users\61097809\loganalytics\graph_venv\Lib\site-packages\llama_index\core\indices\vector_store\base.py:94, in VectorStoreIndex.from_vector_store(cls, vector_store, embed_model, **kwargs)
     87 @classmethod
     88 def from_vector_store(
     89     cls,
   (...)
     92     **kwargs: Any,
     93 ) -> "VectorStoreIndex":
---> 94     if not vector_store.stores_text:
     95         raise ValueError(
     96             "Cannot initialize from a vector store that does not store text."
     97         )
     99     kwargs.pop("storage_context", None)

AttributeError: 'list' object has no attribute 'stores_text'