The name of the Infinispan client to use. These clients are configured by means of the infinispan-client extension. If unspecified, it will use the default Infinispan client.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_CLIENT_NAME

The dimension of the embedding vectors. This has to be the same as the dimension of vectors produced by the embedding model that you use. For example, AllMiniLmL6V2QuantizedEmbeddingModel produces vectors of dimension 384. OpenAI’s text-embedding-ada-002 produces vectors of dimension 1536.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_DIMENSION

Name of the cache that will be used in Infinispan when searching for related embeddings. If this cache doesn’t exist, it will be created.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_CACHE_NAME

The maximum distance. The most distance between vectors is how close or far apart two embeddings are.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_DISTANCE

The similarity metric to use for vector search. Supported values: COSINE, L2, INNER_PRODUCT, MAX_INNER_PRODUCT.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_SIMILARITY

Whether to create the cache on startup if it does not exist. Set to false if the cache is pre-configured on the Infinispan server.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_CREATE_CACHE

Optional full XML or JSON cache configuration. When provided, this overrides the default cache configuration generated by the extension.

Environment variable: QUARKUS_LANGCHAIN4J_INFINISPAN_CACHE_CONFIG