# VecStore Python Bindings
High-performance vector database with RAG toolkit for Python, powered by Rust.
## Installation
```bash
pip install vecstore
```
## Quick Start
```python
from vecstore import VecStore, Query
# Create or open a vector store
store = VecStore.open("./my_db")
# Insert vectors with metadata
store.upsert(
id="doc1",
vector=[0.1, 0.2, 0.3, ...],
metadata={"text": "Hello world", "category": "greeting"}
)
# Query for similar vectors
results = store.query(
vector=[0.1, 0.2, 0.3, ...],
k=5
)
for result in results:
print(f"ID: {result.id}, Score: {result.score}")
print(f"Metadata: {result.metadata}")
```
## Features
- **Fast**: 10-100x faster than pure Python implementations
- **Complete RAG Toolkit**: Text splitting, reranking, evaluation
- **Production Ready**: Persistence, namespaces, server mode
- **Pythonic API**: Type hints, familiar patterns
- **Zero Config**: Works out of the box
## Documentation
See the main repository documentation:
- [Quick Start](../QUICKSTART.md)
- [Complete Documentation](../MASTER-DOCUMENTATION.md)
- [API Reference (Rust docs)](https://docs.rs/vecstore)
- [Examples](examples/)
## Examples
See the `examples/` directory for complete examples:
- `basic_rag.py` - Simple RAG workflow
- `fastapi_integration.py` - FastAPI REST API
- `evaluation.py` - RAG quality measurement
- `production.py` - Production deployment
## Development
Building from source:
```bash
# Install maturin
pip install maturin
# Build in development mode
maturin develop --features python
# Run tests
pytest tests/
```
## License
MIT License - see LICENSE file for details
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