Skip to main content

Swarmauri MLM Vector Store

Project description

Swarmauri Logo

PyPI - Downloads PyPI - Python Version PyPI - License PyPI - Version


MLM Vector Store

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

Installation

pip install swarmauri_vectorstore_mlm

Usage

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

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 that will help you get started.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

swarmauri_vectorstore_mlm-0.6.1.dev15.tar.gz (6.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file swarmauri_vectorstore_mlm-0.6.1.dev15.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_mlm-0.6.1.dev15.tar.gz
Algorithm Hash digest
SHA256 9bea3505a9499e9094a61120eb8d20a6865821a9bb06623dd34a96bf4c645ae6
MD5 272a89dbc13eb50848bc7d90ead8d54c
BLAKE2b-256 dc3376bc3433466548b057986bce8836e9eb18953c84d4326815ab4ea3860e43

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_mlm-0.6.1.dev15-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_mlm-0.6.1.dev15-py3-none-any.whl
Algorithm Hash digest
SHA256 5d141906991acffd7d0794f0b79bf4eb0013c176e754520b0ec9d5fe7a152e76
MD5 3435a3f8d5accd993aff539c5140d0cf
BLAKE2b-256 f29120c54ea0a03a58d77ee1222c8645b29750688df3efae36d3e8cad729fb70

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page