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README.md

Cortex Search SDK usage via the snowflake.core library

This directory contains example usage for the Cortex Search REST API via the snowflake.core python package. snowflake.core supports authentication and connection to a Snowflake account through several different mechanisms, a few of which are outlined in the examples.

Notably, the Cortex Search API is only available in versions of snowflake.core >= 0.8.0.

Prerequisites

Before you can run the examples, ensure you have the following prerequisites installed:

  • Python 3.11
  • pip (Python package installer)

Additionally, you must have access to a Snowflake account and the required permissions to query the Cortex Search Service at the specified database and schema.

Installation

First, clone this repository to your local machine using git and navigate to this directory:

git clone https://github.com/snowflake-labs/cortex-search.git
cd cortex-search/examples/python_sdk

Install the necessary Python dependencies by running:

pip install -r requirements.txt

Usage

1. Passing connection parameters explicitly or via environment variables

simple.py collects connection parameters from your shell environment. These can be set like so (note: we recommend setting the SNOWFLAKE_ACCOUNT using the account locator, rather than the org-account format):

export SNOWFLAKE_ACCOUNT=AID123456
export SNOWFLAKE_USER=myself
export SNOWFLAKE_PASSWORD=pass123...
export SNOWFLAKE_ROLE=my_role
export SNOWFLAKE_DATABASE=my_db
export SNOWFLAKE_SCHEMA=my_schema
export SNOWFLAKE_CORTEX_SEARCH_SERVICE=my_service

However, you may also simply replace each os.environ[".."] with hardcoded values, if you wish.

Then, after modifying the search parameters to your liking, run the example to generate results:

python simple.py

2. With a connections.toml file

To set up a connections.toml file to store aliased Snowflake connections and all the parameters needed to connect, see the snowflake connector docs

An example is found under example_connections.toml, but make sure to name yours connections.toml and ensure it is located at a valid system-dependent path as specified in the Snowflake connector docs.

Then, export your Cortex Search Service name (assuming the database and schema are already in your connection parameters):

export SNOWFLAKE_CORTEX_SEARCH_SERVICE=my_service

You can then run the using_connections_config.py file to print search results:

python using_connections_config.py

3. Executing concurrent queries with throttling

concurrent-example.py is an example for running concurrent search requests on your cortex search service along with throttling the request rate when the server is busy.

This example collects default connection parameters from a file. Add the following lines to a file named .env in the current directory:

SNOWFLAKE_ACCOUNT=AID123456
SNOWFLAKE_USER=myself
SNOWFLAKE_AUTHENTICATOR=
SNOWFLAKE_PASSWORD=
SNOWFLAKE_ROLE=my_role
SNOWFLAKE_DATABASE=my_db
SNOWFLAKE_SCHEMA=my_schema
SNOWFLAKE_CORTEX_SEARCH_SERVICE=my_service

Add the queries you want to run concurrently to a file named queries, also in the current directory, one query per line:

riding shotgun
hello
what's going on
pet sounds
blue
songs in the key of life

You can then run concurrent-example.py file to print search results:

python concurrent-example.py --columns col1 col2

You can override the connection parameters specified in .env file with command line parameters. Try:

python concurrent-example.py -h

to enumerate the list of command line options.