VectorStoreMiddleware

The VectorStoreMiddleware is a powerful component designed to facilitate the connection of AI agents to various vector stores. It acts as an intermediary layer that simplifies the interaction between AI models and vector databases, enabling efficient storage and retrieval of vector data.

Usage

To use the VectorStoreMiddleware, you need to integrate it into your AI project. This middleware supports multiple vector store backends, allowing you to choose the one that best fits your needs.

Configuration and Setup

1. Install Dependencies: Ensure that you have the necessary dependencies installed. You can do this by running:

   pip install git+https://github.com/myschoolstory/VectorStoreMiddleware.git

2. Configure the Middleware: Set up the middleware by specifying the vector store backend and any required credentials in your configuration file or environment variables.

Integration Example

Here's a basic example of how to integrate the VectorStoreMiddleware into your project:

from vectorstore_middleware import VectorStoreMiddleware

# Initialize the middleware with your chosen vector store
middleware = VectorStoreMiddleware(backend='your_vector_store_backend', config={'api_key': 'your_api_key'})

# Use the middleware to store and retrieve vectors
vector_data = [0.1, 0.2, 0.3]
middleware.store_vector('vector_id', vector_data)
retrieved_vector = middleware.retrieve_vector('vector_id')

Dependencies and Prerequisites

• Python 3.6 or higher
• vectorstore-middleware package

Ensure that your environment is set up with these prerequisites before integrating the middleware into your project.