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)
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1 maintainer
Metadata
1 maintainer
Release files for swarmauri_vectorstore_redis 0.9.2
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Source distribution (sdist)
| File | Size | Uploaded | |
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| swarmauri_vectorstore_redis-0.9.2.tar.gz | 9.2 kB | Details |
Built distribution (wheel)
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| swarmauri_vectorstore_redis-0.9.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.9 kB
Release files / swarmauri_vectorstore_redis-0.9.2.tar.gz
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Release files / swarmauri_vectorstore_redis-0.9.2-py3-none-any.whl
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| Size | 10.7 kB |
| Tags | Python 3 |
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