Metadata-Version: 2.4
Name: llama-index-retrievers-mongodb-atlas-bm25-retriever
Version: 0.5.0
Summary: llama-index retrievers mongodb-atlas-bm25-retriever integration
Author-email: Your Name <you@example.com>
License-Expression: MIT
License-File: LICENSE
Requires-Python: <4.0,>=3.10
Requires-Dist: llama-index-core<0.15,>=0.13.0
Requires-Dist: pymongo<5,>=4.6.1
Description-Content-Type: text/markdown

# LlamaIndex Retrievers Integration: MongoDBAtlasBM25Retriever

## What is this?

This is a BM25 Retriever for MongoDB Atlas that can be used with LlamaIndex.

## How to use

This was created with reference to [MongoDBAtlasVectorSearch](https://docs.llamaindex.ai/en/stable/examples/vector_stores/MongoDBAtlasVectorSearch.html), so it's mostly the same.

Please refer to that.

However, while `MongoDBAtlasVectorSearch` is an VectorStore, `MongoDBAtlasBM25Retriever` is a Retriever.

MongoDBAtlasBM25Retriever Example:

```python
mongodb_client = pymongo.MongoClient(mongo_uri)

retriever = MongoDBAtlasBM25Retriever(
    mongodb_client=mongodb_client,
    db_name="vectorstore",
    collection_name="vector_collection",
    index_name="index_vector_collection",
)
nodes = retriever.retrieve("retrieve_query")
```
