In this guide, we define a bm25 retriever that search documents using the bm25 method. BM25 (Best Matching 25) is a ranking function that extends TF-IDF by ...

BM25 is a ranking function used in information retrieval systems to estimate the relevance of documents to a given search query.

Asynchronously invoke the retriever to get relevant documents. Main entry point for asynchronous retriever invocations.

InMemoryBM25Retriever is a keyword-based Retriever that fetches Documents matching a query from a temporary in-memory database.

LlamaIndex is a data framework for your LLM applications - llama_index/llama-index-legacy/llama_index/legacy/retrievers/bm25_retriever.py at main ...

In this guide, we define a bm25 retriever that search documents using bm25 method. This notebook is very similar to the RouterQueryEngine notebook.

bm25_retriever#. BM25 retriever implementation. ... Fast Implementation of Best Matching 25 ranking function. It expects str as the final document type after ...

Retrieve the k-nearest neighbors using a lexical search based on BM25. Parameters: count_vectorizertransformer, default=None. A count vectorizer to compute the ...

An instance of the Accelerator class, used for multiprocessing. Type: Accelerator , optional.

Currently, BM25Retriever retrieves Document s without the similarity scores. It would be helpful to output the similarity scores as well by including them into ...