**Description:**
This PR updates `CassandraGraphVectorStore` to be based off
`CassandraVectorStore`, instead of using a custom CQL implementation.
This allows users using a `CassandraVectorStore` to upgrade to a
`GraphVectorStore` without having to change their database schema or
re-embed documents.
This PR also updates the documentation of the `GraphVectorStore` base
class and contains native async implementations for the standard graph
methods: `traversal_search` and `mmr_traversal_search` in
`CassandraVectorStore`.
**Issue:** No issue number.
**Dependencies:** https://github.com/langchain-ai/langchain/pull/27078
(already-merged)
**Lint and test**:
- Lint and tests all pass, including existing
`CassandraGraphVectorStore` tests.
- Also added numerous additional tests based of the tests in
`langchain-astradb` which cover many more scenarios than the existing
tests for `Cassandra` and `CassandraGraphVectorStore`
** BREAKING CHANGE**
Note that this is a breaking change for existing users of
`CassandraGraphVectorStore`. They will need to wipe their database table
and restart.
However:
- The interfaces have not changed. Just the underlying storage
mechanism.
- Any one using `langchain_community.vectorstores.Cassandra` can instead
use `langchain_community.graph_vectorstores.CassandraGraphVectorStore`
and they will gain Graph capabilities without having to re-embed their
existing documents. This is the primary goal of this PR.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** this PR adds a set of methods to deal with metadata
associated to the vector store entries. These, while essential to the
Graph-related extension of the `Cassandra` vector store, are also useful
in themselves. These are (all come in their sync+async versions):
- `[a]delete_by_metadata_filter`
- `[a]replace_metadata`
- `[a]get_by_document_id`
- `[a]metadata_search`
Additionally, a `[a]similarity_search_with_embedding_id_by_vector`
method is introduced to better serve the store's internal working (esp.
related to reranking logic).
**Issue:** no issue number, but now all Document's returned bear their
`.id` consistently (as a consequence of a slight refactoring in how the
raw entries read from DB are made back into `Document` instances).
**Dependencies:** (no new deps: packaging comes through langchain-core
already; `cassio` is now required to be version 0.1.10+)
**Add tests and docs**
Added integration tests for the relevant newly-introduced methods.
(Docs will be updated in a separate PR).
**Lint and test** Lint and (updated) test all pass.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR adds a constructor `metadata_indexing` parameter to the
Cassandra vector store to allow optional fine-tuning of which fields of
the metadata are to be indexed.
This is a feature supported by the underlying CassIO library. Indexing
mode of "all", "none" or deny- and allow-list based choices are
available.
The rationale is, in some cases it's advisable to programmatically
exclude some portions of the metadata from the index if one knows in
advance they won't ever be used at search-time. this keeps the index
more lightweight and performant and avoids limitations on the length of
_indexed_ strings.
I added a integration test of the feature. I also added the possibility
of running the integration test with Cassandra on an arbitrary IP
address (e.g. Dockerized), via
`CASSANDRA_CONTACT_POINTS=10.1.1.5,10.1.1.6 poetry run pytest [...]` or
similar.
While I was at it, I added a line to the `.gitignore` since the mypy
_test_ cache was not ignored yet.
My X (Twitter) handle: @rsprrs.
The Vectorstore's API `as_retriever` doesn't expose explicitly the
parameters `search_type` and `search_kwargs` and so these are not well
documented.
This PR improves `as_retriever` for the Cassandra VectorStore by making
these parameters explicit.
NB: An alternative would have been to modify `as_retriever` in
`Vectorstore`. But there's probably a good reason these were not exposed
in the first place ? Is it because implementations may decide to not
support them and have fixed values when creating the
VectorStoreRetriever ?
If Session and/or keyspace are not provided, they are resolved from
cassio's context. So they are not required.
This change is fully backward compatible.
