LangChain retriever for traversing document graphs on top of vector-based similarity search.

LangChain Graph Retriever LangChain Graph Retriever is a Python library that supports traversing a document graph on top of vector-based similarity search. It works seamlessly with LangChain's retriever framework and supports various graph traversal strategies for efficient document discovery. Features Vector Search: Perform similarity searches using vector embeddings. Graph Traversal: Apply traversal strategies such as breadth-first (Eager) or Maximal Marginal Relevance (MMR) to explore document relationships. Customizable Strategies: Easily extend and configure traversal strategies to meet your specific use case. Multiple Adapters: Support for various vector stores, including AstraDB, Cassandra, Chroma, OpenSearch, and in-memory storage. Synchronous and Asynchronous Retrieval: Supports both sync and async workflows for flexibility in different applications. Installation Install the library via pip: pip install langchain-graph-retriever Getting Started Here is an example of how to