Talk to Redshift

This example demonstrates how to build an agent that can dynamically query Amazon Redshift Serverless tables and store its contents on the local hard drive.

Let's build a support agent that uses GPT-4:

import os

import boto3

from griptape.drivers.sql.amazon_redshift import AmazonRedshiftSqlDriver
from griptape.loaders import SqlLoader
from griptape.rules import Rule, Ruleset
from griptape.structures import Agent
from griptape.tools import FileManagerTool, SqlTool
from griptape.utils import Chat

session = boto3.Session()

sql_loader = SqlLoader(
    sql_driver=AmazonRedshiftSqlDriver(
        database=os.environ["REDSHIFT_DATABASE"],
        session=session,
        cluster_identifier=os.environ["REDSHIFT_CLUSTER_IDENTIFIER"],
    )
)

sql_tool = SqlTool(
    sql_loader=sql_loader,
    table_name="people",
    table_description="contains information about tech industry professionals",
    engine_name="redshift",
)

agent = Agent(
    tools=[sql_tool, FileManagerTool()],
    rulesets=[
        Ruleset(
            name="HumansOrg Agent",
            rules=[
                Rule("Act and introduce yourself as a HumansOrg, Inc. support agent"),
                Rule("Your main objective is to help with finding information about people"),
                Rule("Only use information about people from the sources available to you"),
            ],
        )
    ],
)

Chat(agent).start()