title	PeopleOps
emoji	💼
colorFrom	blue
colorTo	indigo
sdk	docker
app_port	7860
pinned	false

PeopleOps - Enterprise HRMS & AI Recruitment Management System

Project Overview

PeopleOps is a comprehensive Enterprise Human Resource Management System (HRMS) and AI-powered Recruitment Platform designed to streamline hiring, employee management, payroll operations, performance tracking, and workforce administration.

The platform combines Machine Learning-powered resume screening, intelligent candidate evaluation, automated HR workflows, payroll processing, employee analytics, and an AI assistant to help organizations manage their workforce efficiently from a single dashboard.

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Features

Recruitment & Hiring

• ✅ AI-powered resume screening and classification
• ✅ Automated PDF resume parsing and text extraction
• ✅ Resume-to-job matching and candidate scoring
• ✅ Job posting and applicant tracking
• ✅ Candidate profile management
• ✅ Interview scheduling and communication workflows

Employee Management

• ✅ Employee directory and profile management
• ✅ Dedicated dashboards for administrators, employees, and interns
• ✅ Employee onboarding workflows
• ✅ Contract tracking and management
• ✅ Leave request and approval system

Payroll & Finance

• ✅ Payroll management and processing
• ✅ Tax calculations and payroll logs
• ✅ Automated PDF payslip generation
• ✅ Employee payslip portal
• ✅ Financial reporting tools

Performance Management

• ✅ Goal setting and progress tracking
• ✅ Performance reviews and appraisals
• ✅ Employee performance analytics
• ✅ Historical performance records

Communication & Automation

• ✅ Automated email notifications
• ✅ Background task processing using Celery
• ✅ Asynchronous workflow execution
• ✅ AI-powered PeopleOps Assistant using Google Gemini

Operations & Analytics

• ✅ Employee grievance management
• ✅ Workforce analytics dashboard
• ✅ Organizational insights and reporting
• ✅ Leave tracking and monitoring

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Technology Stack

Backend

• Python
• Flask
• Celery
• Redis

Database

• MongoDB

Machine Learning & AI

• Scikit-Learn
• Joblib
• Google Gemini API

Frontend

• HTML5
• CSS3
• JavaScript
• Jinja2

Reporting & Utilities

• ReportLab
• PyMuPDF

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Project Structure

PeopleOps/
│
│── enterprise_app/
│   ├── routes/                # Flask route blueprints (Auth, Finance, Performance, etc.)
│   ├── services/              # Business logic (Appraisals, Chatbot, Email, NLP matching)
│   ├── static/                # CSS styling, brand assets, and user avatars
│   ├── templates/             # HTML templates (Layouts, Emails, Dashboards)
│   ├── tasks.py               # Background Celery task definitions
│   ├── utils.py               # Shared utility functions (PDF generation, logging, math)
│   └── __init__.py            # Flask application factory and Celery initialization
│── models/                    # Trained Machine Learning models and metrics reports
│── tools/                     # Development utilities
│── config.py                  # Global application configurations and environment maps
│── manage.py                  # Database seeders, schema alignments, and CLI utilities
│── training.py                # Pipeline script to retrain the SVM resume classifier
│── run.py                     # Entrypoint script to start the Flask application
│── requirements.txt           # Explicitly pinned application dependencies
│── start-all.bat              # Batch file to start Redis, Celery, and Flask simultaneously
│── UpdatedResumeDataSet.csv   # Dataset used to train the resume classification models
│── .gitignore                 
└── README.md

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Prerequisites

Make sure the following software is installed before running the project:

• Redis

Verify Installation

redis-server --version

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Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/Rubel286/PeopleOps.git
cd PeopleOps

2️⃣ Create & Activate Virtual Environment

Windows

python -m venv venv
venv\Scripts\activate

macOS / Linux

python3 -m venv venv
source venv/bin/activate

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Configure Environment Variables

Create a .env file in the project root:

SECRET_KEY="your-key"

MONGO_URI=mongodb://127.0.0.1:27017/recruitmentDB

MAIL_SERVER=smtp.gmail.com
MAIL_PORT=587
MAIL_USE_TLS=1
MAIL_USERNAME="your-email"
MAIL_PASSWORD="your-password"

CELERY_BROKER_URL=redis://127.0.0.1:6379/0
CELERY_RESULT_BACKEND=redis://127.0.0.1:6379/0

GEMINI_API_KEY="your-key"

5️⃣ Start Redis

redis-server

6️⃣ Database Initialization

flask --app manage.py seed-db

7️⃣ Run the Application

Quick Start (Windows)

start-all.bat

Manual Startup

Start Celery Worker:

python -m celery -A enterprise_app.celery worker -P solo --loglevel=info

Start Flask Application:

python run.py

Access the Application

Open your browser and navigate to:

http://127.0.0.1:5000

Default Login Credentials

After running flask --app manage.py seed-db, you can immediately log in to the portal using these default testing accounts.

Administrative / Recruiter Access

• Email: admin@peopleops.dev
• Password: admin

Employee Portal Access

• Email: [first_name].[last_name]@peopleops.dev
  • Example: aravind.swamy@peopleops.dev
• Password: password

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Screenshots

Admin Dashboard

Candidate Pipeline

Candidate Profile

Employee Dashboard

Grievance Management

Leave Requests

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Important

This project uses Google Gemini API.

Get your API key from:

https://aistudio.google.com/app/apikey

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License

This project is licensed under the MIT License.

See the LICENSE file for details.