Skip to main content

Swarmauri Redis Vector Store

Project description

Swamauri Logo

PyPI - Downloads Hits PyPI - Python Version PyPI - License PyPI - swarmauri_vectorstore_redis


Swarmauri Vectorstore Redis

A Redis-based vector store implementation for the Swarmauri SDK that enables efficient storage and retrieval of document embeddings.

Installation

pip install swarmauri_vectorstore_redis

Usage

Basic example of using RedisVectorStore:

from swarmauri.vector_stores.RedisVectorStore import RedisVectorStore
from swarmauri.documents.Document import Document

# Initialize the vector store
vector_store = RedisVectorStore(
    redis_host="localhost",
    redis_port=6379,
    redis_password="your_password",
    embedding_dimension=8000
)

# Add documents
document = Document(
    id="doc1",
    content="Sample document content",
    metadata={"category": "sample"}
)
vector_store.add_document(document)

# Retrieve similar documents
similar_docs = vector_store.retrieve("sample content", top_k=5)

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_redis-0.9.0.dev4.tar.gz (9.0 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_redis-0.9.0.dev4.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_redis-0.9.0.dev4.tar.gz
Algorithm Hash digest
SHA256 94dac2ebfc39014b163343752b58e0c3dd236aac9a62690d96a143782171a0f3
MD5 8f9e2badc067339bd6d15b322538e3de
BLAKE2b-256 1ce20203161a27d4d09aa07765eb4a2d560fa8f638560cb79a53e60bf828b025

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_redis-0.9.0.dev4-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_redis-0.9.0.dev4-py3-none-any.whl
Algorithm Hash digest
SHA256 a77f05250cce6a7895b0792dbc49268eafb410aba44c72bc3f6f8a158933732f
MD5 8e085da3e336dbd62810687de4c48041
BLAKE2b-256 4aebad52f9d1f25d936cb3c1e8b5d978ecb243d77ef5a2e17b9d658b3d91b408

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