https://github.com/vishal150494/ai-based-web-application-develpoment-and-deployment-project2

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.
https://github.com/vishal150494/ai-based-web-application-develpoment-and-deployment-project2

error-handling flask-web ibm-watson modules nlp-library packaging pep8 python3 restful-api unit-testing

Last synced: 3 days ago
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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.

• Host: GitHub
• URL: https://github.com/vishal150494/ai-based-web-application-develpoment-and-deployment-project2
• Owner: Vishal150494
• License: apache-2.0
• Created: 2024-09-09T05:41:53.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-09-09T05:44:01.000Z (5 months ago)
• Last Synced: 2025-02-01T15:40:49.052Z (13 days ago)
• Topics: error-handling, flask-web, ibm-watson, modules, nlp-library, packaging, pep8, python3, restful-api, unit-testing
• Language: Python
• Homepage:
• Size: 8.79 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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

```python

import requests

def ():

    url = ''

    headers = {}

    myobj = {}

    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

```python 

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 

```json

{'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

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