A DuckDB based Vector Store
Project description
Swarmauri Vectorstore Duckdb
A vector store implementation using DuckDB as the backend for efficient document storage and similarity search.
Installation
pip install swarmauri_vectorstore_duckdb
Usage
from swarmauri.vector_stores.DuckDBVectorStore import DuckDBVectorStore
from swarmauri.documents.Document import Document
# Initialize vector store
vector_store = DuckDBVectorStore(database_name="my_vectors.db")
vector_store.connect()
# Add documents
doc = Document(
id="doc1",
content="The quick brown fox jumps over the lazy dog",
metadata={"type": "example"}
)
vector_store.add_document(doc)
# Retrieve similar documents
results = vector_store.retrieve("fox jumping", top_k=2)
# Clean up
vector_store.disconnect()
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