semantic-store 0.0.7

An in-memory vector store for semantic data storage and retrieval

SemanticStore

A simple easy to use vector store for small hobby projects.

A versatile vector store designed for multimodal search. This store seamlessly integrates with Faiss to provide efficient similarity search capabilities. Whether you're working with image, text, or audio data, SemanticStore has you covered.

Features

• Multimodal Support: Handle a wide range of data types, including image, text, and audio vectors.
• Faiss Integration: Utilize the speed and efficiency of Faiss for similarity search.
• Custom Pipelines: Create customizable pipelines for processing and indexing your data.
• Ease of Use: Designed for simplicity, making it accessible to developers of all levels.

Getting Started

Follow these steps to get started with the SemanticStore:

1. Install into environment

   pip install semantic-store
   

2. Install requirements

   Will try to package CLIP in next release version

   pip install git+https://github.com/openai/CLIP.git
   

3. Get started in python

     from SemanticStore import Store
   
     store = Store()
     store.connect('semantic.db')
     store.insert('gita.txt')
     store.commit()
     res = store.search("what is meaning of life according to gita ?", 5, modals=['text', 'image'])
     print(res)
   

Models

SemanticStore uses various state-of-the-art models to process text, images and audio.

Pipelines	Model 1	Model 2	Model 3	Model 4
Text	multi-qa-MiniLM-L6-cos-v1	CLIP	-	-
Audio	Whisper	multi-qa-MiniLM-L6-cos-v1	CLIP	-
Image	CLIP	BLIP	multi-qa-MiniLM-L6-cos-v1	-
Video	Whisper	CLIP	BLIP	multi-qa-MiniLM-L6-cos-v1

Note : Models and pipeines in Italics are still to be implemented.

Contributing

Contributions are welcome! If you'd like to enhance the SemanticStore or fix issues, please follow these steps:

1. Fork the repository.
2. Create a branch: git checkout -b feature/your-feature or fix/your-fix.
3. Commit your changes: git commit -m 'Add some feature' or git commit -m 'Fix some issue'.
4. Push to the branch: git push origin feature/your-feature or git push origin fix/your-fix.
5. Open a pull request

Note: This vector store is intended for small hobby projects and personal use. It may not be suitable for large-scale or production environments.