Sentiment Analysis

USING : Python, Fastapi, Pydantic, Transformer

S/A model : https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest

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A Backend build on Python & Fastapi with a RESTful API endpoint for sentiment analysis.
The API will accept text input, validate with Pydantic and return the sentiment analysis result using a pre-trained machine learning model.

Installation

Make sure python version >=3.9.
Clone this repo, open in terminal and

Run :

python -m venv .venv 

In Terminal, Run the following commands :

In Linux: source .venv/bin/activate

In Windows: .venv\Scripts\activate

Then install the required dependencies and start app

pip install  -r requirements.txt 
uvicorn main:app

What's in it ?

• Minimal Static FrontEnd : http://127.0.0.1:8000/
  • Write an Sentence and Get Sentiment-Analyses instantly
• Request is validated
• Response is validated
• Added Extra Query Sentiment Analysis (%)Percentage Result
• Exception Handling included

API Routes

• GET REQUEST - http://127.0.0.1:8000/hello
  • Request Payload - Empty
  • Expected Response - "Hello World"
• POST REQUEST http://127.0.0.1:8000/analyze
  • Request Payload - JSON : {"text": "STRING"}
  • Expected Response - JSON : {"sentiment":"positive/negative/neutral"}
  • To get a Response with Sentence Sentiment and Score add ?withScore=True
    i.e. - POST REQUEST http://127.0.0.1:8000/analyze?withScore=True
  • With Score Expected Response - JSON : {"sentiment":"positive/negative/neutral", "score": float}