FAISS

!!!!!!!!!DEPRECATED-Not in use!!!!!!!!!

Facebook AI Similarity Search

FAISS (Facebook AI Similarity Search) is a powerful library for performing efficient similarity searches and clustering on dense vectors. It provides various indexing options and algorithms that enhance search speed and reduce memory consumption, making it ideal for high-dimensional data. We used this FAISS to maintain our vector data efficiently.

Contents

1. Installation
2. Configuration
3. Implementation
4. Usage
5. Troubleshooting

Installation

FAISS is a python library so for installation, first your system should have python installed already and then you need to go to command prompt then use this command "pip install faiss-cpu" this command is for CPU version for GPU version you can use "pip install faiss-gpu" after these commands the library is ready to be used

FAISS can be installed using several methods depending on your environment:

• Via Pip (Python):

       pip install faiss-cpu
  

• For GPU support:

       pip install faiss-gpu
  

• Installing FAISS via Docker

• From Source:

• Clone the repository:

          git clone https://github.com/facebookresearch/faiss.git
  

• Install dependencies and build:

          cd faiss
          ./configure
          make
          sudo make instal
  

For more detailed installation instructions for different platforms, refer to the FAISS GitHub repository

Configuration

Implementation

Usage

Troubleshooting