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AI-Sentiment Analysis

Overview

AI-Sentiment Analysis is a Python-based application that processes customer reviews from CSV or Excel files. It performs sentiment analysis using a Groq API to classify reviews as Positive, Negative, or Neutral. The application outputs the counts and proportions of each sentiment category along with any unclassified reviews.

Tech Stack used -

  • Python
  • FastAPI
  • Groq sdk
  • pandas

Features

  • Process reviews from both CSV and Excel file formats.
  • Utilize a Groq API to analyze sentiments of reviews.
  • Return counts and proportions of Positive, Negative, and Neutral sentiments.
  • Provide a summary of unclassified reviews for further analysis.

Installation

  1. Clone the repository:

    git clone https://github.com/yashbudhia/AI-sentiment-analysis.git
cd AI-sentiment-analysis

  2. Install required packages: Make sure you have Python installed. You can create a virtual environment (recommended) and install the required packages using:

    pip install -r requirements.txt

  3. Set up environment variables:

    • Create a .env file in the root of the project and add your Groq API key as follows: 
      GROQ_API_KEY=your_api_key_here

Usage

  • To process a file of reviews, run the following command in your terminal: 
    uvicorn main:app --reload
  • Then Go to Postman or any other api tester , and send a POST request to http://127.0.0.1:8000/analyze
  • In the body go to form data , create a new field and add your csv or xlsx file there and send the post request
  • You will get the reviews counted in postive, negative and neutral based on the sentiment.
  • format of count -
{
    "positive": ,
    "negative": ,
    "neutral":
}