1. Setup the Postgres loader by configuring the postgres db.
from embedchain.loaders.postgres import PostgresLoader

config = {
    "host": "host_address",
    "port": "port_number",
    "dbname": "database_name",
    "user": "username",
    "password": "password",

config = {
    "url": "your_postgres_url"

postgres_loader = PostgresLoader(config=config)

You can either setup the loader by passing the postgresql url or by providing the config data. For more details on how to setup with valid url and config, check postgres documentation.

NOTE: if you provide the url field in config, all other fields will be ignored.

  1. Once you setup the loader, you can create an app and load data using the above postgres loader
import os
from embedchain.pipeline import Pipeline as App

os.environ["OPENAI_API_KEY"] = "sk-xxx"

app = App()

question = "What is Elon Musk's networth?"
response = app.query(question)
# Answer: As of September 2021, Elon Musk's net worth is estimated to be around $250 billion, making him one of the wealthiest individuals in the world. However, please note that net worth can fluctuate over time due to various factors such as stock market changes and business ventures.

app.add("SELECT * FROM table_name;", data_type='postgres', loader=postgres_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 as they will result in not adding any data, so it is pointless.

  1. We automatically create a chunker to chunk your postgres data, however if you wish to provide your own chunker class. Here is how you can do that:

from embedchain.chunkers.postgres import PostgresChunker
from embedchain.config.add_config import ChunkerConfig

postgres_chunker_config = ChunkerConfig(chunk_size=1000, chunk_overlap=0, length_function=len)
postgres_chunker = PostgresChunker(config=postgres_chunker_config)

app.add("SELECT * FROM table_name;", data_type='postgres', loader=postgres_loader, chunker=postgres_chunker)