FIR Section Predictor

Overview

FIR Section Predictor is a web application that predicts the applicable legal sections for a given incident description. This tool is designed to assist law enforcement agencies, legal professionals, and researchers by automating the classification of FIRs based on relevant legal provisions.

Features

• Multi-label classification of FIRs using Gemini API.
• User-friendly chat interface built with Streamlit.
• Real-time prediction of applicable FIR sections.
• Supports text-based FIR inputs.

Technologies Used

• Python: Core programming language.
• Streamlit: For building the web-based user interface.
• Gemini API: For multi-label classification and FIR section prediction.
• VS Code: Development environment.

Installation

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• streamlit
• pandas
• docx
• google-generativeai
• pip (Python package manager)

Steps

1. Clone the repository:

   git clone https://github.com/your-repo/FIR-Section-Predictor.git
   cd FIR-Section-Predictor

2. Create and activate a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Run the Streamlit application:

   streamlit run app.py

Usage

1. Open the web app in your browser.
2. Enter the FIR details in the provided text box.
3. Click on Predict to get the suggested legal sections.
4. Review the predictions and use them for legal reference.

Deployment

The project is deployed on Streamlit Cloud. You can access it here: https://firfirsectionpredictor-fxu9wbfgrqufbvb8yunhkb.streamlit.app/