Finance-Complaint

Deployment Setup

# Aws Secert 
AWS_ACCESS_KEY_ID : <your AWS_ACCESS_KEY_ID >
AWS_SECRET_ACCESS_KEY: <your AWS_SECRET_ACCESS_KEY >
AWS_DEFAULT_REGION: "ap-south-1" 
MONGO_DB_URL: <your Mongo Url >

# Gcp Secert 
GCLOUD_SERVICE_KEY: <json format key>
GOOGLE_COMPUTE_ZONE: asia-south1
GOOGLE_PROJECT_ID: <project id from dashboard>

# Image Secrets
REPOSITORY: finance-complaint
GAR_IMAGE_NAME: finance-complaint
IMAGE_TAG: latest

WorkFLow setup

Step-1

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 avnish@ineuron.ai -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

3. To start your application

docker-compose up

4. To stop your application

docker-compose down