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Client library for Vector Store service

Project description

Vector Store Client

A Python client for interacting with Vector Store API services. This client provides a convenient interface for working with vector embeddings, semantic search, and metadata filtering.

PyPI Version Python Versions License

Features

  • Full-featured API for Vector Store operations
  • Asynchronous interface based on httpx
  • Automatic parameter handling and validation
  • Comprehensive error management
  • Support for all vector store operations:
    • Creating records from text or vectors
    • Vector similarity search
    • Metadata filtering
    • Record management

Installation

pip install vector-store-client

Or install from source:

git clone https://github.com/yourusername/vector-store-client.git
cd vector-store-client
pip install -e .

Quick Start

import asyncio
from vector_store_client import create_client

async def main():
    # Create client with connection to the service
    client = await create_client(base_url="http://localhost:8007")
    
    # Create a record from text
    record_id = await client.create_text_record(
        text="Example text for vectorization",
        metadata={"type": "example", "tags": ["test", "vector"]}
    )
    
    # Search for similar records
    results = await client.search_text_records(
        text="vectorization example",
        limit=5
    )
    
    for result in results:
        print(f"ID: {result.id}, Similarity: {result.score:.4f}")
    
    # Close the client session
    await client._client.aclose()

if __name__ == "__main__":
    asyncio.run(main())

Documentation

Detailed documentation is available in both English and Russian:

Examples

Check out the example scripts to get started:

Development

Requirements

  • Python 3.7+
  • httpx
  • pydantic

Running Tests

# Install test dependencies
pip install pytest pytest-asyncio pytest-cov

# Run tests
python run_tests.py

License

MIT

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