https://github.com/liaad/physio

A conversational AI agent to help with physical rehabilitation.
https://github.com/liaad/physio

Last synced: 10 days ago
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A conversational AI agent to help with physical rehabilitation.

• Host: GitHub
• URL: https://github.com/liaad/physio
• Owner: LIAAD
• License: other
• Created: 2023-10-12T11:18:46.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-05-18T17:22:48.000Z (6 months ago)
• Last Synced: 2024-05-18T18:29:12.706Z (6 months ago)
• Language: Python
• Size: 693 KB
• Stars: 6
• Watchers: 6
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Physio

[![https://img.shields.io/badge/website-8A2BE2](https://img.shields.io/badge/website-8A2BE2)](https://physio.inesctec.pt)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A conversational AI agent to help with physical rehabilitation.

## System Architecture

Physio is a web application developed using microservice architecture to improve scalability and enforce failure isolation. The frontend is developed in React which enables the creation of maintainable interfaces through its reusable components mechanism, effectively separating the logic from the visual interfaces. The backend makes use of Apache Airflow and consists of a data processing pipeline that effectively manages the workflow of incoming requests. Between these two services, there is a Flask server serving as a gateway for the web application. It is responsible for receiving the requests made by the client, triggering the Airflow data pipeline for execution, and storing the answers in an external database. All these services are packaged in Docker containers and aggregated on a Docker compose file for interoperability and fast deployment. For the database, we employ MongoDB to store the knowledge bases we compiled. For the generative model, Physio relies on OpenAI GPT-4 model which is the most effective LM at the time of development of this demo.

![System Architecture](imgs/system_architecture.png)

## Setup

### ML Pipeline

Check out the backend [README](backend/README.md) to set up the environment.

![Data Pipeline](imgs/data_pipeline.png)

#### Webscraping Sources

When formulating its responses, Physio relies on and references the following websites:

* [physio-pedia](www.physio-pedia.com)

* [ncbi.nlm.nih](www.ncbi.nlm.nih.gov)

* [my.clevelandclinic](www.my.clevelandclinic.org)

* [healthline](www.healthline.com)

* [webmd](www.webmd.com)

* [orthoinfo.aaos](www.orthoinfo.aaos.org)

* [mayoclinic](www.mayoclinic.org)

* [sciencedirect](www.sciencedirect.com)

* [hopkinsmedicine](www.hopkinsmedicine.org)

* [medicalnewstoday](www.medicalnewstoday.com)

* [nhs](www.nhs.uk)

* [orthobullets](www.orthobullets.com)

* [pubmed.ncbi.nlm.nih](www.pubmed.ncbi.nlm.nih.gov)

* [hss](www.hss.edu)

* [emedicine.medscape](www.emedicine.medscape.com)

* [sportdoctorlondon](www.sportdoctorlondon.com)

* [sportsinjuryclinic](www.sportsinjuryclinic.net)

* [spine-health](www.spine-health.com)

* [verywellhealth](www.verywellhealth.com)

* [bupa.co](www.bupa.co.uk)

### How to Run Locally

1. Create a `.env` file in the directories [backend/airflow](backend/airflow/), [backend/flask](backend/flask/), and [frontend](frontend/) as specified in the `.env.example` files in each directory.

2. Run `docker-compose up --build`.

## Contributing

1. Create your feature branch (`git checkout -b feature/fooBar`)

2. Commit your changes (`git commit -am 'Add some fooBar'`)

3. Push to the branch (`git push origin feature/fooBar`)

4. Create a new Pull Request