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About graph-vl

Identity document verification using Machine Learning and GraphQL.

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Python

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More about graph-vl

graph-vl

.. image:: https://github.com/verifid/graph-vl/workflows/graph-vl%20ci/badge.svg :target: https://github.com/verifid/graph-vl/actions

.. image:: https://codecov.io/gh/verifid/graph-vl/branch/master/graph/badge.svg :target: https://codecov.io/gh/verifid/graph-vl

Self hosted identity verification layer with GraphQL.

Introduction

graph-vl is the verification layer of verifid developed with GraphQL. It's the secondary core project other than VL <https://github.com/verifid/vl/>_ that is responsible from verifying identity cards or passports. Basically it's a self hosted API which has 3 main endpoints. It runs on either Docker or Kubernetes as a container. All endpoints are documented using GraphiQL and project relies on VerifID and other Open Source Python modules.

For storage, it uses Postgres as a database and SQLAlchemy as an object relational mapper. To make it simple DB has only two tables which is enough for this project.

There is only four steps to veriy an identity of a person which you can find those steps below.

Create a user with personal details
Upload user's selfie photo
Take a photo of front page of identity card or passport, then upload
Call verify endpoint and get the result

Requirements

Python 3.6+
Postgres
Run time dependencies requirements.txt
Test dependencies requirements.testing.txt

Usage

You need a Postgres instance in your machine our a Docker container that runs database. To pull docker image and start a container

.. code::

docker pull postgres:11.5
docker run --name postgres -e POSTGRES_SERVER=localhost \
    -e POSTGRES_USER=postgres \
    -e POSTGRES_PASSWORD=postgres \
    -e POSTGRES_DB=postgres \
    -d -p 5432:5432 postgres:11.5
docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' postgres
# We will use this IP address when we build or run graph-vl

To run the graph-vl server, please execute the following commands from the root directory

.. code::

docker build --build-arg PG_SERVER=${POSTGRES_IP_ADDRESS} \
    --build-arg PG_USER=postgres \
    --build-arg PG_PASSWORD=postgres \
    --build-arg PG_DB=postgres \
    -t graphvl .
docker run --rm -it -d -p 8000:8000 --name graph-vl graphvl:latest

For running in a cluster with Kubernetes you can follow the commands below

.. code::

# Use Docker for minikube
eval $(minikube docker-env)
# Re-build the docker images

# Create developments and pods
kubectl create -f deployment-postgres.yml
kubectl create -f deployment-graphvl.yml

# Create services
kubectl create -f service-postgres.yml
kubectl create -f service-graphvl.yml

# Get url for **graphvl**
minikube service graphvl --url

Interface

+-----------------+---------------+-----------------+ ||image_expolorer|||image_queries|||image_mutations|| +-----------------+---------------+-----------------+

If you run with uvicorn graphvl.main:app after cloning the project all endpoints will be available available on http://127.0.0.1:8000

.. |image_expolorer| image:: https://raw.githubusercontent.com/verifid/graph-vl/master/resources/explorer.png .. |image_queries| image:: https://raw.githubusercontent.com/verifid/graph-vl/master/resources/queries.png .. |image_mutations| image:: https://raw.githubusercontent.com/verifid/graph-vl/master/resources/mutations.png