TypeError                                 Traceback (most recent call last)
Cell In[23], line 15
     12 embed_model = "local:BAAI/bge-small-en-v1.5"
     13 service_context = ServiceContext.from_defaults(embed_model=embed_model, text_splitter=splitter)
---> 15 index = VectorStoreIndex.from_documents(docs, storage_context=storage_context, service_context=service_context, show_progress=True)

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/indices/base.py:107, in BaseIndex.from_documents(cls, documents, storage_context, service_context, show_progress, **kwargs)
     98     docstore.set_document_hash(doc.get_doc_id(), doc.hash)
    100 nodes = run_transformations(
    101     documents,  # type: ignore
    102     service_context.transformations,
    103     show_progress=show_progress,
    104     **kwargs,
    105 )
--> 107 return cls(
    108     nodes=nodes,
    109     storage_context=storage_context,
    110     service_context=service_context,
    111     show_progress=show_progress,
    112     **kwargs,
    113 )

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/indices/vector_store/base.py:52, in VectorStoreIndex.__init__(self, nodes, index_struct, service_context, storage_context, use_async, store_nodes_override, insert_batch_size, show_progress, **kwargs)
     50 self._store_nodes_override = store_nodes_override
     51 self._insert_batch_size = insert_batch_size
---> 52 super().__init__(
     53     nodes=nodes,
     54     index_struct=index_struct,
     55     service_context=service_context,
     56     storage_context=storage_context,
     57     show_progress=show_progress,
     58     **kwargs,
     59 )

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/indices/base.py:72, in BaseIndex.__init__(self, nodes, index_struct, storage_context, service_context, show_progress, **kwargs)
     70 if index_struct is None:
     71     assert nodes is not None
---> 72     index_struct = self.build_index_from_nodes(nodes)
     73 self._index_struct = index_struct
     74 self._storage_context.index_store.add_index_struct(self._index_struct)

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/indices/vector_store/base.py:271, in VectorStoreIndex.build_index_from_nodes(self, nodes, **insert_kwargs)
    263 if any(
    264     node.get_content(metadata_mode=MetadataMode.EMBED) == "" for node in nodes
    265 ):
    266     raise ValueError(
    267         "Cannot build index from nodes with no content. "
    268         "Please ensure all nodes have content."
    269     )
--> 271 return self._build_index_from_nodes(nodes, **insert_kwargs)

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/indices/vector_store/base.py:243, in VectorStoreIndex._build_index_from_nodes(self, nodes, **insert_kwargs)
    241     run_async_tasks(tasks)
    242 else:
--> 243     self._add_nodes_to_index(
    244         index_struct,
    245         nodes,
    246         show_progress=self._show_progress,
    247         **insert_kwargs,
    248     )
    249 return index_struct

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/indices/vector_store/base.py:197, in VectorStoreIndex._add_nodes_to_index(self, index_struct, nodes, show_progress, **insert_kwargs)
    195 for nodes_batch in iter_batch(nodes, self._insert_batch_size):
    196     nodes_batch = self._get_node_with_embedding(nodes_batch, show_progress)
--> 197     new_ids = self._vector_store.add(nodes_batch, **insert_kwargs)
    199     if not self._vector_store.stores_text or self._store_nodes_override:
    200         # NOTE: if the vector store doesn't store text,
    201         # we need to add the nodes to the index struct and document store
    202         for node, new_id in zip(nodes_batch, new_ids):
    203             # NOTE: remove embedding from node to avoid duplication

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/vector_stores/elasticsearch.py:316, in ElasticsearchStore.add(self, nodes, create_index_if_not_exists, **add_kwargs)
    293 def add(
    294     self,
    295     nodes: List[BaseNode],
   (...)
    298     **add_kwargs: Any,
    299 ) -> List[str]:
    300     """Add nodes to Elasticsearch index.
    301 
    302     Args:
   (...)
    314         BulkIndexError: If AsyncElasticsearch async_bulk indexing fails.
    315     """
--> 316     return asyncio.get_event_loop().run_until_complete(
    317         self.async_add(nodes, create_index_if_not_exists=create_index_if_not_exists)
    318     )

File /anaconda/envs/openai/lib/python3.10/site-packages/nest_asyncio.py:99, in _patch_loop.<locals>.run_until_complete(self, future)
     96 if not f.done():
     97     raise RuntimeError(
     98         'Event loop stopped before Future completed.')
---> 99 return f.result()

File /anaconda/envs/openai/lib/python3.10/asyncio/futures.py:201, in Future.result(self)
    199 self.__log_traceback = False
    200 if self._exception is not None:
--> 201     raise self._exception.with_traceback(self._exception_tb)
    202 return self._result

File /anaconda/envs/openai/lib/python3.10/asyncio/tasks.py:232, in Task.__step(***failed resolving arguments***)
    228 try:
    229     if exc is None:
    230         # We use the `send` method directly, because coroutines
    231         # don't have `__iter__` and `__next__` methods.
--> 232         result = coro.send(None)
    233     else:
    234         result = coro.throw(exc)

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/vector_stores/elasticsearch.py:356, in ElasticsearchStore.async_add(self, nodes, create_index_if_not_exists, **add_kwargs)
    354 if create_index_if_not_exists:
    355     dims_length = len(nodes[0].get_embedding())
--> 356     await self._create_index_if_not_exists(
    357         index_name=self.index_name, dims_length=dims_length
    358     )
    360 embeddings: List[List[float]] = []
    361 texts: List[str] = []

File /anaconda/envs/openai/lib/python3.10/site-packages/llama_index/vector_stores/elasticsearch.py:246, in ElasticsearchStore._create_index_if_not_exists(self, index_name, dims_length)
    237 async def _create_index_if_not_exists(
    238     self, index_name: str, dims_length: Optional[int] = None
    239 ) -> None:
    240     """Create the AsyncElasticsearch index if it doesn't already exist.
    241 
    242     Args:
    243         index_name: Name of the AsyncElasticsearch index to create.
    244         dims_length: Length of the embedding vectors.
    245     """
--> 246     if await self.client.indices.exists(index=index_name):
    247         logger.debug(f"Index {index_name} already exists. Skipping creation.")
    249     else:

TypeError: object HeadApiResponse can't be used in 'await' expression