Metadata-Version: 2.3
Name: swarmauri_vectorstore_duckdb
Version: 0.7.2.dev3
Summary: A DuckDB based Vector Store
License: Apache-2.0
Author: Jacob Stewart
Author-email: jacob@swarmauri.com
Requires-Python: >=3.10,<3.13
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: duckdb (>=1.1.1)
Requires-Dist: swarmauri_base
Requires-Dist: swarmauri_core
Requires-Dist: swarmauri_embedding_doc2vec
Requires-Dist: swarmauri_standard
Description-Content-Type: text/markdown


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---

# Swarmauri Vectorstore Duckdb

A vector store implementation using DuckDB as the backend for efficient document storage and similarity search.

## Installation

```bash
pip install swarmauri_vectorstore_duckdb
```

## Usage

```python
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()
```

## Want to help?

If you want to contribute to swarmauri-sdk, read up on our [guidelines for contributing](https://github.com/swarmauri/swarmauri-sdk/blob/master/contributing.md) that will help you get started.


