{"book": <str>, "page": <int>}
Please answer only with the information given in context: """ Metadata: { "book": "xyz", "page": "3" } This is a chapter on the history of Rome etc { "book": "gef", "page": "374" } This is a chapter on Athens etc ... """ Question: {}
def get_pg_storage_context(): from llama_index.storage.docstore.postgres import PostgresDocumentStore from llama_index.storage.index_store.postgres import PostgresIndexStore from llama_index.vector_stores.postgres import PGVectorStore storage_context = StorageContext.from_defaults( docstore=PostgresDocumentStore.from_uri(uri="postgres://....."), index_store=PostgresIndexStore.from_uri="postgres://..."), vector_store=PGVectorStore.from_uri="postgres://...", ) return storage_context
File ~/.virtualenvs/grizzly_3.10/lib/python3.10/site-packages/llama_index/storage/docstore/postgres/base.py:5 3 from llama_index.core.storage.docstore.keyval_docstore import KVDocumentStore 4 from llama_index.core.storage.docstore.types import DEFAULT_BATCH_SIZE ----> 5 from llama_index.storage.kvstore.postgres import PostgresKVStore ModuleNotFoundError: No module named 'llama_index.storage.kvstore'
llama_index/storage/index_store/postgres/base.py:4
PostgresKVStore
is at from llama_index.core.storage.kvstore.postgres_kvstore import PostgresKVStore
PostgresDocumentStore
and PostgresIndexStore
. Should I submit a PR for this?doc_id
for each documentPGVectorStore
support FilterCondition.OR
?!SimpleDataStore
as storage context.FilterCondition.OR
?!MetadataFilters
MetadataFilters
were introduced in version 0.10.19llama_index.core.vector_stores.types.py::MetadataFilters
:class MetadataFilters(BaseModel): """Metadata filters for vector stores.""" # Exact match filters and Advanced filters with operators like >, <, >=, <=, !=, etc. filters: List[Union[MetadataFilter, ExactMatchFilter, "MetadataFilters"]]