Since you already have Docker and docker-compose installed, there's just one step:

docker-compose up -d

Activate python virtual envirnonment and install the requirements

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Preprocess the data set, actually we just clean the missing values data and create a column with the features we will use

(venv) python preprocess.py

Create the model

(venv) python recommendation.py

The two previous steps we run once. The results are the data set preprocessed movies_pos.csv and the pickle binary cosine.pkl with the cosine simirality array already trained on the dataset, we will use both in the api.py. We only will need to run these two steps again if we change the data set, or change the preprocess steps, or the model parameters.

Run the fastapi server

uvicorn api:app --reload

Access the application on: http://127.0.0.1:8000

Access the API documentation on : http://127.0.0.1:8000/docs or http://127.0.0.1:8000/redoc

Make request using a browser, the docs pages or any other API request application

Examples using curl:

curl -X GET "http://127.0.0.1:8000/movies/?q=Interstellar" -H  "accept: application/json"

curl -X GET "http://127.0.0.1:8000/movies/93" -H  "accept: application/json"

curl -X GET "http://127.0.0.1:8000/movies/93/recommendation" -H  "accept: application/json"