ray-vector-embedding

This is a quick demo for how you can use Ray to ingest text into Astra for Vector Search

Setup

Clone the Repo

To get started, you need to get the code onto your machine. So Start by cloning this GitHub repository. If you have git installed, you can do this by running the following command in your terminal:

git clone [email protected]:Anant/ray-vector-embedding.git

This will create a copy of the repository on your local machine. Once you have cloned the repository, navigate into the directory:

cd ray-vector-embedding

Install Prerequisites

To install the required packages for this plugin, run the following command:

pip install -r requirements.txt

Setup A DataBase

In order to run the examples from this repo, you will need to set up a database and create a keyspace. The details of how to do this should be found under the following link

Setup the DataBase Details

Once you've got the database up and running and the keyspace created, make sure you download the bundle as described in the link above and get the keys needed to access your database. Now open the local_creds_secrets.py file and make sure you fill in the details

client_id="<your-client_id>"
client_secret="<your-client_secret>"
db_keyspace="<your-keyspace>"
secure_bundle_path="<path-to-bundle>/secure-connect-<YOUR_DB_NAME>.zip"

Launch a Google Colab

Upload this notebook, the local_creds_secrets, requirements.txt and your secure bundle, and start running the cells one by one.

To be fixed