HealthCare Content Recommendation API

A Spring Boot application that provides RESTful APIs for healthcare content management and recommendations. It integrates with a FastAPI service to generate content recommendations.

Features

• Retrieve healthcare content by ID
• Get recommended content for a given item
• OpenAPI (Swagger) documentation
• Reactive endpoints using Spring WebFlux

Tech Stack

• Java 22
• Spring Boot 3.4.x
• Spring WebFlux
• Spring Data JPA
• PostgreSQL
• Lombok
• Reactor
• OpenAPI (springdoc)
• Maven

Getting Started

Prerequisites

• Java 22
• Maven
• PostgreSQL
• FastAPI recommendation service running at http://127.0.0.1:5000

Setup

1. Clone the repository:

   git clone https://github.com/sbm4034/HealthCareContentRecommendationService.git
   cd HealthCareContentRecommendation
   

2. Configure PostgreSQL:

   • Create a database named healthcare_content with schema org.
   • Update the application.properties file with your PostgreSQL credentials.

3. Run the FastAPI service:

   • Clone the repository for the FastAPI service: git clone https://github.com/sbm4034/AI_Projects_Experiments
   • Ensure you have setup python (3.9 or above) environment with FastAPI installed.
   • Run the FastAPI service using following command: uvicorn recommendation_api:app --reload --port 5000
   • If the fast API isn't installed, you can install it using pip: pip install uvicorn or pip install fastapi
   • Upon successful installation of fastapi, re-run the uvicorn recommendation_api:app --reload --port 5000
   • Ensure the FastAPI service is running at `http://127.0.0.1:5000'
   • Invoke the endpoint for verifying the FastAPI service works as expected by invoking the curl curl --location 'http://127.0.0.1:5000/recommend' \ --header 'Content-Type: application/json' \ --data '{ "content_id": 1, "num_recommendations": 3 }'

4. Run the following command to insert data into postgres by executing file python populate_db.py 5Build and run the Spring boot application:

mvn spotless:apply 
mvn clean install

6. Verify the recommendation API by invoking the curl curl --location 'http://localhost:8080/api/v1/content/2/recommendations'
7. You can also access the OpenAPI documentation at http://localhost:8080/swagger-ui.html.