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  1. Setup the MySQL loader by configuring the SQL db.
from embedchain.loaders.mysql import MySQLLoader

config = {
    "host": "host",
    "port": "port",
    "database": "database",
    "user": "username",
    "password": "password",
}

mysql_loader = MySQLLoader(config=config)
For more details on how to setup with valid config, check MySQL documentation.
  1. Once you setup the loader, you can create an app and load data using the above MySQL loader
from embedchain.pipeline import Pipeline as App

app = App()

app.add("SELECT * FROM table_name;", data_type='mysql', loader=mysql_loader)
# Adds `(1, 'What is your net worth, Elon Musk?', "As of October 2023, Elon Musk's net worth is $255.2 billion.")`

response = app.query(question)
# Answer: As of October 2023, Elon Musk's net worth is $255.2 billion.
NOTE: The add function of the app will accept any executable query to load data. DO NOT pass the CREATE, INSERT queries in add function.
  1. We automatically create a chunker to chunk your SQL data, however if you wish to provide your own chunker class. Here is how you can do that: “Python
from embedchain.chunkers.mysql import MySQLChunker from embedchain.config.add_config import ChunkerConfig mysql_chunker_config = ChunkerConfig(chunk_size=1000, chunk_overlap=0, length_function=len) mysql_chunker = MySQLChunker(config=mysql_chunker_config) app.add(“SELECT * FROM table_name;”, data_type=‘mysql’, loader=mysql_loader, chunker=mysql_chunker)