Metadata-Version: 2.3
Name: swarmauri_vectorstore_mlm
Version: 0.6.1.dev16
Summary: Swarmauri MLM Vector Store
License: Apache-2.0
Author: Jacob Stewart
Author-email: jacob@swarmauri.com
Requires-Python: >=3.10,<3.13
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: swarmauri_base (>=0.6.1.dev16,<0.7.0)
Requires-Dist: swarmauri_core (>=0.6.1.dev16,<0.7.0)
Requires-Dist: swarmauri_embedding_doc2vec (>=0.6.1.dev16,<0.7.0)
Requires-Dist: swarmauri_standard (>=0.6.1.dev3,<0.7.0)
Requires-Dist: torch (>=2.4.1,<3.0.0)
Requires-Dist: transformers (>=4.45.0)
Project-URL: Repository, http://github.com/swarmauri/swarmauri-sdk
Description-Content-Type: text/markdown

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---

# MLM Vector Store

A vector store implementation using MLM (Masked Language Model) embeddings for document storage and retrieval.

## Installation

```bash
pip install swarmauri_vectorstore_mlm
```

## Usage

Here's a basic example of how to use the MLM Vector Store:

```python
from swarmauri.documents.Document import Document
from swarmauri.vector_stores.MlmVectorStore import MlmVectorStore

# Initialize the vector store
vs = MlmVectorStore()

# Create some documents
documents = [
    Document(content="first document"),
    Document(content="second document"),
    Document(content="third document")
]

# Add documents to the store
vs.add_documents(documents)

# Retrieve similar documents
results = vs.retrieve(query="document", top_k=2)
```

## Want to help?

If you want to contribute to swarmauri-sdk, read up on our [guidelines for contributing](https://github.com/swarmauri/swarmauri-sdk/blob/master/contributing.md) that will help you get started.


