Skip to content

Created an AI-based web app that performs analytics on customer feedback for their signature products. To accomplish this requirement, I created an Emotion Detection system that processes feedback provided by the customer in text format and deciphers the associated emotion expressed.

License

Notifications You must be signed in to change notification settings

VishalAshok1504/AI-based-Web-Application-develpoment-and-deployment-Project2

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Detect Emotion from a Given Text

This repo is for a reflection on my attempt to learn and implement my gained knowledge in the area of Flask Web Application framework, Python programming (Unit Testing, Packaging Modules, Error handling & PEP8 guidelines) and RESTful Api.

This is a practice project where in I have demonstrated my programming skills in developing an AI based Application using Python and Flask. I have integrated the Web app with Watson-NLP AI library (based on Emotion Detection Function of the Watson NLP Library) which is used to perfome "Emotion Detection" for a given text. In other words, this AI application will detect the emotion with which a given text was written.

A sample code for such an application could be

import requests
def <function_name>(<input_args>):
    url = '<relevant_url>'
    headers = {<header_dictionary>}
    myobj = {<input_dictionary_to_the_function>}
    response = requests.post(url, json = myobj, headers=header)
    return response.text

Since I made use of the IBM Watson AI Library services, to access this function, the UTL, headers and input json format is as follows

URL: 'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'
Headers: {"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock"}
Input json: { "raw_document": { "text": text_to_analyse } }

A sample application response for a given etxt input "I love this new technology" is something like this

{'anger': 0.025952177, 'disgust': 0.022372011, 'fear': 0.17840633, 'joy': 0.61990315, 'sadness': 0.20243862, 'dominant_emotion': 'joy'}

Summary

With this project, I have successfully

  • Created an Emotion Detection application using the functions from embeddable AI libraries

  • Extracted relevant information from the output received from the function

  • Tested and packaged the application created using the Emotion Detection function

  • Completed web deployment of my application using Flask

  • Incorporated error handling in my application to account for invalid input to your application

  • Written codes that are in perfect compliance with PEP8 guidelines, getting 10/10 score in static code analysis

© IBM Corporation 2023. All rights reserved.

About

Created an AI-based web app that performs analytics on customer feedback for their signature products. To accomplish this requirement, I created an Emotion Detection system that processes feedback provided by the customer in text format and deciphers the associated emotion expressed.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published