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This project forked from machine-learning-01/finance-complaint

0.0 0.0 0.0 25.72 MB

License: Apache License 2.0

Shell 0.01% Python 25.71% HCL 1.38% Jupyter Notebook 72.73% Dockerfile 0.17%

finance-complaints's Introduction

Finance-Complaint

Architectures

WorkFLow setup

Step-1

Setup secrets

Create .env file

AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
MONGO_DB_URL=
TRAINING=1
PREDICTION=1

1- Trigger 0- Bypass

Build docker image

docker build -t tc:lts .

Lauch docker image

docker run -it -v $(pwd)/finance_artifact:/app/finance_artifact  --env-file=$(pwd)/.env fc:lts

AIRFLOW SETUP

How to setup airflow

Set airflow directory

export AIRFLOW_HOME="/home/avnish/census_consumer_project/census_consumer_complaint/airflow"

To install airflow

pip install apache-airflow

To configure databse

airflow db init

To create login user for airflow

airflow users create  -e [email protected] -f Avnish -l Yadav -p admin -r Admin  -u admin

To start scheduler

airflow scheduler

To launch airflow server

airflow webserver -p <port_number>

Update in airflow.cfg

enable_xcom_pickling = True

Steps to run project in local system

  1. Build docker image
    docker build -t fc:lts .
    
  2. Set envment variable
export AWS_ACCESS_KEY_ID=
export AWS_SECRET_ACCESS_KEY=
export MONGO_DB_URL=
export AWS_DEFAULT_REGION="ap-south-1"
export IMAGE_NAME=fc:lts
  1. To start your application
docker-compose up
  1. To stop your application
docker-compose down

finance-complaints's People

Contributors

saiineuron avatar ketangangal avatar avnyadav avatar project-neurons avatar

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