bed-occupancy

An app that optimizes hospital resource management by simulating patient admissions, bed allocations, and managing no-shows effectively. Ideal for predictive occupancy planning and streamlined departmental coordination

Table of contents

• bed-occupancy
  • Table of contents
  • Technologies
  • Setup
    • Prerequisites
      • Docker
      • Twilio
      • Elevenlabs
    • How to run?
  • Screenshots
  • Status
  • Our team

Technologies

• Python version: 3.13, and its libraries:
  • streamlit version: 1.41.1
  • pydantic version: 2.11.4
  • pandas version: 2.2.3
  • fastapi version: 0.115.12
  • and many other less important modules listed here
• Docker version: 27.4
• PostgreSQL
• Twilio for phone calls
• ElevenLabs for voice agents

Setup

Prerequisites

• Docker
• Twilio account
  • phone number for outbound calls
• Elevenlabs account
  • at least one voice agent (conversational_ai)
  • phone number connected to twilio

Docker

In order to run this app, docker is required.

If you don't have docker installed on your computer yet, you can install it here

Twilio

You can find out how to do that here

Elevenlabs

You can find out how to do that here

How to run?

Once you have docker installed, follow these guidelines:

1. Clone the repo on your local machine

   1. You can do it by running this command in terminal:

      git clone https://github.com/datarabbit-ai/bed-occupancy
      cd bed-occupancy
      

2. Prepare the .env file, it should be placed in the project's root folder

   It should contain variables like this:

   POSTGRES_NAME=postgres
   POSTGRES_USERNAME=postgres
   POSTGRES_PASSWORD=postgres
   POSTGRES_HOST=db
   POSTGRES_PORT=5432
   ELEVENLABS_API_KEY=your_api_key_to_elevenlabs
   AGENT_ID=polish_voice_agent_id
   AGENT_UA_ID=ukrainian_voice_agent_id
   AGENT_PHONE_NUMBER_ID=phone_number_id_from_elevenlabs
   TWILIO_SID=your_twilio_sid
   TWILIO_AUTH_TOKEN=your_twilio_auth_token
   OPENAI_API_KEY=your_openai_api_key
   

3. Make sure you are in the project's root folder and run the command: 1.

   docker compose up
   

   There are two versions of this command: docker-compose up and docker compose up. The command docker compose up forces docker to use docker_compose_v2 which is just better, more stable and more reliable.

   1. By running the above command, docker should:
   • launch faker, which will allow you to create a database and/or fill it with data
   • launch the backend and frontend of the application, allowing the browser to open the application, view data from the database and simulate the other day's hospital occupancy rates
   2. The whole process could take even a few minutes, especially when running for the first time

4. If you see in docker logs that frontend container is starting to run, you can visit the webapp in browser

Screenshots

Correctly set up and working app looks like this:

Status

The project is: in development

Our team

Rumeleq

wiktorKycia

JanTopolewski