Metadata-Version: 2.4
Name: swarndb
Version: 1.0.0
Summary: Official Python SDK for SwarnDB — the vector database that thinks in graphs. Combines HNSW + IVF-PQ indexing with virtual graph traversal and 15+ vector math operations.
Project-URL: Homepage, https://github.com/SarthiAI/SwarnDB
Project-URL: Documentation, https://github.com/SarthiAI/SwarnDB#readme
Project-URL: Repository, https://github.com/SarthiAI/SwarnDB
Project-URL: Issues, https://github.com/SarthiAI/SwarnDB/issues
Author: Chirotpal Das
License: ELv2
Keywords: ai,embeddings,graph-database,grpc,hnsw,machine-learning,numpy,similarity-search,swarndb,vector-database,vector-search
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Database
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Requires-Dist: grpcio>=1.60.0
Requires-Dist: numpy>=1.24.0
Requires-Dist: protobuf>=4.25.0
Provides-Extra: async
Requires-Dist: grpcio>=1.60.0; extra == 'async'
Provides-Extra: dev
Requires-Dist: mypy>=1.0; extra == 'dev'
Requires-Dist: pytest-asyncio>=0.21.0; extra == 'dev'
Requires-Dist: pytest>=7.0; extra == 'dev'
Requires-Dist: ruff>=0.1.0; extra == 'dev'
Requires-Dist: tqdm>=4.60.0; extra == 'dev'
Description-Content-Type: text/markdown

# SwarnDB Python SDK

Official Python SDK for SwarnDB — the vector database that thinks in graphs.

Combines HNSW + IVF-PQ indexing with virtual graph traversal and 15+ vector math operations.

## Installation

```bash
pip install swarndb
```

## Quick Start

```python
from swarndb import SwarnClient

client = SwarnClient("localhost:50051")

# Create a collection
client.create_collection("my_vectors", dimension=128)

# Insert vectors
client.insert("my_vectors", vectors=[[0.1, 0.2, ...]], ids=["vec1"])

# Search
results = client.search("my_vectors", query=[0.1, 0.2, ...], top_k=10)
```

## Features

- HNSW + IVF-PQ hybrid indexing
- Virtual graph traversal
- 15+ vector math operations
- Sync and async gRPC clients
- NumPy integration

## License

ELv2
