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":
}