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0623c74560
**Description:** Returns the document id along with the Vector Search results **Issue:** Fixes https://github.com/langchain-ai/langchain/issues/26860 for CouchbaseVectorStore - [x] **Add tests and docs**: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [x] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. Co-authored-by: Erick Friis <erick@langchain.dev>
langchain-couchbase
This package contains the LangChain integration with Couchbase
Installation
pip install -U langchain-couchbase
Usage
The CouchbaseVectorStore class exposes the connection to the Couchbase vector store.
from langchain_couchbase.vectorstores import CouchbaseVectorStore
from couchbase.cluster import Cluster
from couchbase.auth import PasswordAuthenticator
from couchbase.options import ClusterOptions
from datetime import timedelta
auth = PasswordAuthenticator(username, password)
options = ClusterOptions(auth)
connect_string = "couchbases://localhost"
cluster = Cluster(connect_string, options)
# Wait until the cluster is ready for use.
cluster.wait_until_ready(timedelta(seconds=5))
embeddings = OpenAIEmbeddings()
vectorstore = CouchbaseVectorStore(
cluster=cluster,
bucket_name="",
scope_name="",
collection_name="",
embedding=embeddings,
index_name="vector-search-index",
)