https://github.com/sirmaxx/indicator_service

Diabet Estimator Example ml-fastapi application for healthuniverse.com/ hackathon.
https://github.com/sirmaxx/indicator_service

bootstrap5 diabetes diabetes-prediction fastapi juptyernotebook-language machine-learning sklearn

Last synced: 3 months ago
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Diabet Estimator Example ml-fastapi application for healthuniverse.com/ hackathon.

• Host: GitHub
• URL: https://github.com/sirmaxx/indicator_service
• Owner: SirmaXX
• Created: 2023-08-16T23:43:17.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-08-20T19:24:34.000Z (almost 2 years ago)
• Last Synced: 2025-01-28T22:26:10.394Z (4 months ago)
• Topics: bootstrap5, diabetes, diabetes-prediction, fastapi, juptyernotebook-language, machine-learning, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 7.52 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# indicator_service

### Example ml-fastapi application  for https://www.healthuniverse.com/ hackathon.

Diabet Estimator 


source of dataset :https://www.kaggle.com/datasets/alexteboul/diabetes-health-indicators-dataset

#if you want to run only jupyter notebook you can reach from this link : https://www.kaggle.com/code/sirmax/diabet-indicator/notebook

### how to run software

type in the command line :python3 main.py

### how to run test

open the tests folder and  type in the command line :pytest

### how to use software or service

#### 1.Browser

If you run software open the browser and click this link:http://0.0.0.0:8000

![docs](/img/gui.png )

#### 2.Use with Swagger  Docs

If you run software open the browser and click this link:http://0.0.0.0:8000/docs

![docs](/img/docs.png )

#### 3.Use with Postman

![postman](/img/postman.png )

#### 4. Use with Python Script



import requests

import json

url = "http://0.0.0.0:8000/predict"

payload = json.dumps({

  "features": [

    1,

    2,

    21,

    1,

    3

  ]

})

headers = {

  'Content-Type': 'application/json'

}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)