lantern

Calculate maximal marginal relevance.

Get the embedding store class.

Base class for the Lantern embedding store.

Result from a query.

Enumerator of the Distance strategies.

Postgres with the lantern extension as a vector store.

lantern uses sequential scan by default. but you can create a HNSW index using the create_hnsw_index method.

• connection_string is a postgres connection string.
• embedding_function any embedding function implementing langchain.embeddings.base.Embeddings interface.
• collection_name is the name of the collection to use. (default: langchain)
  • NOTE: This is the name of the table in which embedding data will be stored The table will be created when initializing the store (if not exists) So, make sure the user has the right permissions to create tables.
• distance_strategy is the distance strategy to use. (default: EUCLIDEAN)
  • EUCLIDEAN is the euclidean distance.
  • COSINE is the cosine distance.
  • HAMMING is the hamming distance.
• pre_delete_collection if True, will delete the collection if it exists. (default: False)
  • Useful for testing.