dosubot[bot]
commented
4 months ago Hey @stamak! I'm here to help you with any bugs, questions, or contributions. Let's tackle this together while we wait for a human maintainer.
To resolve the IndexError: list index out of range when initializing a VertexAIVectorStore, ensure that all required parameters are correctly provided and initialized. The error might be due to missing or incorrectly specified parameters.
Here is the corrected initialization code for VertexAIVectorStore:
from llama_index.vector_stores.vertexaivectorsearch import VertexAIVectorStore
vector_store = VertexAIVectorStore(
project_id=PROJECT_ID,
region=REGION,
index_id=vs_index.resource_name,
endpoint_id=vs_endpoint.resource_name,
gcs_bucket_name=GCS_BUCKET_NAME, # Optional
credentials_path="<path_to_credentials>" # Optional
)Ensure that PROJECT_ID, REGION, vs_index.resource_name, and vs_endpoint.resource_name are correctly specified. If using optional parameters like gcs_bucket_name and credentials_path, make sure they are also correctly provided.
Additionally, verify that the VertexAIVectorStore class is correctly implemented and all required attributes are initialized properly. Here is a snippet of the class definition for reference:
class VertexAIVectorStore(BasePydanticVectorStore):
def __init__(
self,
project_id: Optional[str] = None,
region: Optional[str] = None,
index_id: Optional[str] = None,
endpoint_id: Optional[str] = None,
gcs_bucket_name: Optional[str] = None,
credentials_path: Optional[str] = None,
text_key: str = DEFAULT_TEXT_KEY,
remove_text_from_metadata: bool = True,
**kwargs: Any,
) -> None:
super().__init__(
project_id=project_id,
region=region,
index_id=index_id,
endpoint_id=endpoint_id,
gcs_bucket_name=gcs_bucket_name,
credentials_path=credentials_path,
text_key=text_key,
remove_text_from_metadata=remove_text_from_metadata,
)
_sdk_manager = VectorSearchSDKManager(
project_id=project_id, region=region, credentials_path=credentials_path
)
self._index = _sdk_manager.get_index(index_id=index_id)
self._endpoint = _sdk_manager.get_endpoint(endpoint_id=endpoint_id)
self._index_metadata = self._index.to_dict()
self._stream_update = False
if self._index_metadata["indexUpdateMethod"] == "STREAM_UPDATE":
self._stream_update = True
if self.gcs_bucket_name:
self._staging_bucket = _sdk_manager.get_gcs_bucket(
bucket_name=gcs_bucket_name
)
else:
self._staging_bucket = NoneBy ensuring all required parameters are correctly provided and initialized, you can avoid the IndexError: list index out of range. Additionally, you can refer to the test cases provided in the test_vector_stores_vertexaivectorsearch.py file to ensure your setup is correct and to see examples of how to use the VertexAIVectorStore class [1][2][3].
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Bug Description
Following this https://docs.llamaindex.ai/en/stable/examples/vector_stores/VertexAIVectorSearchDemo/#create-a-simple-vector-store-from-plain-text-without-metadata-filters
When executing
It fails w/ an error
IndexError: list index out of rangeVersion
0.10.43
Steps to Reproduce
Follow https://docs.llamaindex.ai/en/stable/examples/vector_stores/VertexAIVectorSearchDemo/#create-a-simple-vector-store-from-plain-text-without-metadata-filters
Relevant Logs/Tracbacks