Swarmauri Vectorstore CloudWeaviate
A Weaviate-based vector store implementation for Swarmauri, providing cloud-based document storage and retrieval with vector similarity search capabilities.
Installation
pip install swarmauri_vectorstore_cloudweaviate
Usage
Here's a basic example of how to use the CloudWeaviateVectorStore:
from swarmauri.vector_stores.CloudWeaviateVectorStore import CloudWeaviateVectorStore
from swarmauri.documents.Document import Document
# Initialize the vector store
vector_store = CloudWeaviateVectorStore(
url="your-weaviate-url",
api_key="your-api-key",
collection_name="example",
vector_size=100
)
# Connect to Weaviate
vector_store.connect()
# Add documents
document = Document(
id="doc-001",
content="This is a sample document content.",
metadata={"author": "Alice", "date": "2024-01-01"}
)
vector_store.add_document(document)
# Retrieve similar documents
results = vector_store.retrieve(query="sample content", top_k=5)
# Clean up
vector_store.disconnect()
Want to help?
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1 maintainer
Metadata
1 maintainer
Release files for swarmauri_vectorstore_cloudweaviate 0.10.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| swarmauri_vectorstore_cloudweaviate-0.10.0.tar.gz | 8.3 kB | Details |
Built distribution (wheel)
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| swarmauri_vectorstore_cloudweaviate-0.10.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.6 kB
Release files / swarmauri_vectorstore_cloudweaviate-0.10.0.tar.gz
| Download URL | swarmauri_vectorstore_cloudweaviate-0.10.0.tar.gz |
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Release files / swarmauri_vectorstore_cloudweaviate-0.10.0-py3-none-any.whl
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| Tags | Python 3 |
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