Intelligent BI Demo

中文

Deployment Guide

1. Prepare EC2 Instance

Create an EC2 with following configuration:

- Software Image (AMI): Amazon Linux 2023
- Virtual server type (instance type): t3.large or higher
- Firewall (security group): Allow 22, 80 port
- Storage (volumes): 1 volume(s) - 30 GiB

2. Config Permission

Bind an IAM Role to your EC2 instance. And attach an inline policy to this IAM Role with following permissions:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "bedrock:*",
                "secretsmanager:GetSecretValue"
            ],
            "Resource": "*"
        }
    ]
}

Make sure you have enabled model access in AWS Console in us-west-2 (美国西部 (俄勒冈州)) region for Claude 2 model and Amazon Titan embedding model.

3. Installation

Execute following commands in EC2 terminal with ec2-user as login user. If not this user, you can use following command to switch:

sudo su - ec2-user

# Install components
sudo dnf install docker python3-pip git -y && pip3 install docker-compose

#Fix docker's python wrapper 7.0 SSL version issue
pip3 install docker==6.1.3

# Config components
sudo systemctl enable docker && sudo systemctl start docker && sudo usermod -aG docker $USER

exit

# Open a new terminal session with the user ec2-user

# Config for OpenSearch
sudo sh -c "echo 'vm.max_map_count=262144' > /etc/sysctl.conf" && sudo sysctl -p

# Clone code
git clone https://github.com/fengxu1211/streamlit-data-analysis.git

# Build docker image locally
cd streamlit-data-analysis && cp .env.template .env && docker-compose build

# Start all services
docker-compose up -d

4. Initialize MySQL

Execute following commands in EC2.

cd initial_data && unzip init_mysql_db.sql.zip && cd ..
docker exec nlq-mysql sh -c "mysql -u root -ppassword -D llm  < /opt/data/init_mysql_db.sql"

5. Initialize OpenSearch

Wait for at least 3 mins after "docker-compose up" ran

5.1 Initialize index with sample data by creating a new index

docker exec nlq-webserver python opensearch_deploy.py

(Optional)

5.2 Initialize index with custom data by creating a new index

docker exec nlq-webserver python opensearch_deploy.py custom

or 5.3 Initialize index with custom data by appending an existing index

docker exec nlq-webserver python opensearch_deploy.py custom false

If the script's execution has failed with any error. Please use following command to delete index and rerun the previous command.

curl -XDELETE -k -u admin:admin "https://localhost:9200/uba"

6. Create a new data source profile （Optional)

docker exec -it nlq-webserver python deployment/generate_new_profile.py

7. Access Streamlit Web UI

Open url in the browser: http://<your-ec2-public-ip>

Note: use HTTP instead of HTTPs.