langchain-s3-cached-embeddings 0.8.3

langchain embeddings wrapper to persist embeddings for re-use later

langchain-s3-cached-embeddings

Proxies any langchain Embeddings class such as OpenAIEmbeddings, GoogleGenerativeAIEmbeddings, persisting all generated embeddings to S3. This allows subsequent calls to optionally leverage the cached embeddings, avoiding additional and unecessary cost of re-embedding.

Install

pip install langchain-s3-cached-embeddings

Usage

from langchain_s3_text_loaders import S3DirectoryLoader

   embeddings = S3EmbeddingsConduit(
        embeddings=OpenAIEmbeddings(model=model), # required
        bucket="my-embeddings-bucket", # required
        prefix="my-optional-prefix"
    )

Advanced Usage

   embeddings = S3EmbeddingsConduit(
        embeddings=OpenAIEmbeddings(model=model), # required
        bucket="my-embeddings-bucket", # required
        prefix="my-optional-prefix"
        filenaming_function: Optional[Callable[[str, int], str]] = None,
        cache_behavior = CacheBehavior.NO_CACHE):

Usage Options

• embeddings - (required) any class implementing langchain_core.embeddings.Embeddings
• bucket - (required) the s3 bucket name
• prefix - (required) the s3 key name
• filenaming_function - (optional) redeives two arguments, 1. the file contents (str), 2. the index (int) e.g. 9 for the 10the document and returns the filename ()str)
• cache_behavior - (optional)
  • CacheBehavior.NO_CACHE - do not use cached embeddings, instead embed using the embeddings class' standard embed_documents(...) method
  • CacheBehavior.ONLY_CACHE - use cached embeddings. if the embeddings are no present, it raises an exception

License

MIT