HRPro

AI-Driven Talent Acquisition and Onboarding Assistant

HRPro is an innovative AI-powered assistant designed to revolutionize talent acquisition and employee onboarding. By integrating web scraping, Retrieval-Augmented Generation (RAG), and dynamic prompts, HRPro streamlines the recruitment process, enhances candidate evaluation, and ensures a smooth, personalized onboarding experience for new hires.

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Table of Contents

• HRPro
  • Table of Contents
  • Overview
  • Features
    • Talent Acquisition Support
    • Employee Training and Onboarding
  • Project Structure
  • Installation
  • Usage
    • Running the Applications
    • Building for Production
  • Contributing
  • License

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Overview

In today’s competitive job market, efficient talent acquisition and onboarding are crucial for any organization. HRPro leverages advanced AI techniques to:

• Automate the creation and validation of job descriptions.
• Evaluate candidates by scoring their resumes against job requirements.
• Manage candidate communication, from scheduling interviews to sending rejection notifications.
• Provide new hires with personalized onboarding materials and real-time support through dynamic prompts and follow-up questions.

By integrating these capabilities, HRPro not only enhances recruitment efficiency but also accelerates the onboarding process, ensuring that both recruiters and new employees have immediate access to context-aware guidance and internal resources.

For more details about the architecture and features of HRPro, please refer to the API README.

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Features

Talent Acquisition Support

• Automated Job Posting: Generate job descriptions and post listings across multiple platforms based on initial requirements.
• Job Description Validation: Ensure job descriptions align with the necessary technologies and skills.
• Candidate Scoring: Evaluate candidates by comparing their resumes with job requirements.
• Communication Automation: Automate email notifications for rejected candidates and schedule interviews with selected candidates.

Employee Training and Onboarding

• Personalized Onboarding: Utilize RAG-powered retrieval to provide personalized onboarding materials, FAQs, and internal resources.
• Dynamic Prompts: Deliver role-specific, team-tailored prompts that guide new hires through their onboarding journey.
• AI-Generated Follow-Up: Generate follow-up questions to ensure thorough understanding and assist employees throughout their training modules.

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Project Structure

HRPro is organized as a Turborepo monorepo, leveraging TypeScript across its services. The main directories are:

• Frontend: Located at ./apps/web Contains the web application interface where users can interact with the HRPro assistant.

• API: Located at ./apps/api Houses the backend services that power the AI functionalities, data processing, and integrations.

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Installation

1. Clone the Repository:

   git clone https://github.com/your-username/HRPro.git
   cd HRPro

2. Install Dependencies:

   HRPro uses a monorepo structure, so you might need to install dependencies at the root level as well as in each app.

   # Install root-level dependencies
   npm install
   
   # Install dependencies for the web app
   cd apps/web
   npm install
   
   # Install dependencies for the API
   cd ../api
   npm install

3. Configure Environment Variables:

   Create a .env file in both the ./apps/web and ./apps/api directories if required. Refer to the provided .env.example files for guidance.

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Usage

Running the Applications

• Frontend (Web):

  Navigate to the apps/web directory and start the development server:

  cd apps/web
  npm run dev

• Backend (API):

  Navigate to the apps/api directory and start the API server:

  cd apps/api
  npm run dev

Building for Production

Ensure that all configurations are set for a production environment. Then, build the projects accordingly:

# Build the API
cd apps/api
npm run build

# Build the Web app
cd ../web
npm run build

Deploy your applications using your preferred hosting provider.

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Contributing

Contributions to HRPro are welcome! To contribute:

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Commit your changes with clear, descriptive commit messages.
4. Open a pull request detailing your changes.

For major changes, please open an issue first to discuss what you would like to change.

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License

This project is licensed under the MIT License.