langchain-cairn

LangChain vector store for Cairn, the hybrid search database where a deletion is final.

pip install langchain-cairn

from cairn_db import Client
from langchain_cairn import CairnVectorStore, collection_schema

admin = Client("http://localhost:7200", api_key=ADMIN_KEY)
admin.create_collection("docs", collection_schema(1536, filterable={"source": "Enum"}))

store = CairnVectorStore(Client("http://localhost:7200", api_key=KEY).collection("docs"), embeddings)
store.add_documents(chunks)                      # chunk.metadata["parent"] = the source document
store.similarity_search("what changed in 2024?", k=4, filter={"source": "handbook"})
store.similarity_search("...", k=4, group_by="parent")   # each document once
store.hybrid_search("error E1234", k=4)          # vector + BM25, fused
store.as_retriever()
store.delete(parent="handbook.pdf")              # the document and all its chunks, everywhere

• Schema. collection_schema creates the fields the store needs:
  • the text and the embedding;
  • parent;
  • metadata, which holds each document's whole metadata as JSON, so any metadata round-trips;
  • the filterable fields, which store the same metadata keys so they can be filtered.
• Filters. Either a plain dict ({"source": "a"}: every key equals its value), or a Cairn filter ({"field": "page", "gte": 2}, and/or/not).
• Scores. similarity_search_with_score returns the similarity for Cosine and Dot, and the squared distance for L2. similarity_search_with_relevance_scores maps them to [0, 1].
• Deletions. A deletion by ids, by parent or by filter is final. The client carries its consistency token, so later searches never return the deleted documents, on any node.