faiss-api

Simple faiss API for index search with flask and docker

About Faiss

Faiss is a tool created by the Facebook Research team to efficiently get vector similarities, more info on https://github.com/facebookresearch/faiss/

How to use

• Export your faiss index to .index file like:

import faiss
index = ... #your index logic
index.train(data)
index.add(data)
faiss.write_index(index, "latest.index")
#optional - save the sequencial list of keys
import numpy as np
np.save('keys.npy', np.array(keys_list)) 

• clone this repository
• add the latest.index in the app root path
• add the keys.npy in the app root path (optional)

Run local with Docker

• Build docker image (in the app root path)

docker build -t samuelhei/faiss-api:latest .

• Run Image

docker run -e LD_LIBRARY_PATH='/usr/local/lib' -p 5000:5000 samuelhei/faiss-api:latest

• Open a new terminal and get the docker IP

$ docker ps $ docker inspect | grep "IPAddress"

Change the <container id> part with the id returned on the docker ps command, the returned IP address will be your host, using the port 5000 like http://127.0.0.2:5000

Deploy on AWS beanstalk

• Install the AWS client (if not installed)

$ pip install awscli $ pip install awsebcli

• Set your preferences of the region and set Docker as Environment

$ eb init

• Create and Deploy application (This will use t2.micro as default)

$ eb create -d --envvars LD_LIBRARY_PATH=/usr/local/lib

• When you update your application then you can redeploy

$ eb deploy

Test the endpoint

• Open in your browser <host>/ping, if everything is ok it will be returned the following result: {"ping":"pong"}

Getting search results from the index

• Send a POST method to <host>/get_similarities with the following parms:
  • vector as text like 0.10359007865190506,0.25027135014533997,0.6511507034301758,0.501607358455658,0.39755818247795105,0.007388297468423843,0.33636972308158875,0.1718718260526657,0.1494559347629547,0.23654937744140625,0.39706116914749146
  • n as the number of itens to return (default value 5)