README.md

metadata

license: apache-2.0
title: Chatbotv2
sdk: gradio
colorTo: blue

HRMS Email Automation & Legal Assistant Chatbot

Overview

This repository contains three separate applications:

1. HRMS Email Automation - A Streamlit-based application for automating HR interview invitation emails.
2. Legal Assistant Chatbot - A Streamlit-based chatbot leveraging Retrieval-Augmented Generation (RAG) for legal assistance.
3. Employee Performance & Retention Analytics Dashboard - A Streamlit-based analytics dashboard providing insights into employee attrition, performance, and retention risk.

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1️⃣ HRMS Email Automation

Description

The HRMS Email Automation tool simplifies the process of sending interview invitations via email. It provides a user-friendly form to collect candidate details and automatically sends emails for both Online and Face-to-Face interviews.

Features

• Select interview type: Online or Face-to-Face.
• Input relevant details like candidate name, interview time, PIC (Person in Charge), and contact details.
• Validate form fields to ensure required details are entered.
• Send email automatically using the EmailAuto class.
• User-friendly interface built with Streamlit.

Installation & Usage

# Clone the repository
git clone https://github.com/your-repo.git
cd your-repo

# Install dependencies
pip install -r requirements.txt

# Run the Streamlit app
streamlit run email_ui.py

File Structure

├── automation/
│   ├── emailAuto.py  # Handles email automation
├── email_ui.py  # Streamlit UI for HRMS Email Automation

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2️⃣ Legal Assistant Chatbot

Description

The Legal Assistant Chatbot is a chatbot designed to provide legal assistance by retrieving relevant legal context from Pinecone and responding based on a fine-tuned TinyLlama model.

Features

• Uses Retrieval-Augmented Generation (RAG) for context-aware legal responses.
• Retrieves legal documents from Pinecone to enhance responses.
• Fine-tuned TinyLlama-1.1B-Chat model for legal domain understanding.
• Interactive chat interface built with Gradio.
• Supports file uploads (optional).

Installation & Usage

# Install dependencies
pip install -r requirements.txt

# Run the chatbot
python app.py

File Structure

├── backend/
│   ├── train.py  # Handles model training
│   ├── rag.py  # Handles Pinecone-based retrieval
├── app.py  # Gradio UI for the Legal Assistant Chatbot

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3️⃣ Employee Performance & Retention Analytics Dashboard

Description

The Employee Performance & Retention Analytics Dashboard provides insights into employee attrition, performance, and retention risk. It includes interactive visualizations, ML-based attrition predictions, and employee-specific evaluations.

Features

• Attrition Prediction: Uses a RandomForest model to predict employee attrition likelihood.
• Performance Analysis: Visualizations of performance rating, salary, and tenure.
• Retention Analysis: Highlights risks based on job satisfaction, work-life balance, and promotion history.
• Employee Evaluation: Individual employee performance and retention insights.
• AI-Powered Insights: Generates department-specific insights based on filtered employee data.

Installation & Usage

# Install dependencies
pip install -r requirements.txt

# Run the Streamlit dashboard
streamlit run dashboard.py

File Structure

├── dashboard.py  # Streamlit UI for HR analytics
├── HR-Employee-Attrition.csv  # Employee dataset

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Environment Variables

Both applications require environment variables to function correctly. Create a .env file and add the following:

PINECONE_API_KEY=your_pinecone_api_key
PINECONE_INDEX=your_pinecone_index
PINECONE_NAMESPACE=your_pinecone_namespace

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Contribution

Feel free to contribute to this project by submitting issues, pull requests, or feature suggestions!

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License

This project is licensed under the MIT License.