redis-movies-gen-ai

Redis Vector Similarity Search, Semantic Caching, Recommendation Systems and RAG

About this demo application

This demo showcases different GenAI use cases with redis database

• Vector Search
• Semantic Caching
• Recommendation Systems
• RAG Framework for Gen AI

Project Setup

Spin up a Redis instance enabled with RedisStack!

The easiest way to is to use a docker image using the below command

docker run -d -p 6379:6379 -p 8001:8001 redis/redis-stack:latest

If you do not want to use a docker image, you can sign up for a free Redis Cloud subscription here.

Set up the project

Download the repository

git clone https://github.com/mar1boroman/redis-movies-gen-ai.git && cd redis-movies-gen-ai

Prepare and activate the virtual environment

python3 -m venv venv && source venv/bin/activate

Install necessary libraries and dependencies

pip install -r requirements.txt

Using the project

Update Config

Make sure you update the app.config file. You need a open ai api key to update the config.

vi app.config

Load Data

Load the data into redis with embeddings and create index The data file is hosted in GCP bucket

curl -L -o utils/data_with_embeddings.csv.gz https://storage.googleapis.com/okon-datasets/data_with_embeddings.csv.gz

gunzip utils/data_with_embeddings.csv.gz

python utils/load_redis.py 

Run application

Run the UI

streamlit run app/1_🔍_Find_My_Movies.py