WorkWise AI

Team: The Backpropagators

Members: Harshil Patel, Tanishq Jain and Priyank Shah

Project Overview

In 2025, the world of AI agents is evolving, and we wanted to align our hackathon project with the latest trends. Inspired by ADP's requirement to build an AI-powered career guide, we present WorkWise AI—a ReACT Agent-based solution that can dynamically analyze real-time data based on the user's queries. The AI system aims to answer career-related questions, visualize compensation trends, and guide users with up-to-date, actionable insights.

What does WorkWise AI do?

WorkWise AI is an AI-powered career assistant that:

• Analyzes compensation trends – Understands salary growth, skill valuation, and career progression.
• Answers career-impacting questions – Provides strategic insights using natural language.
• Visualizes opportunities – Transforms raw data into actionable insights.
• Simulates career paths – Predicts how skill upgrades or role changes affect compensation.

How does it work?

The ReACT Agent leverages cutting-edge AI tools to perform real-time data analysis based on user queries. For example, if a user asks, "What is the average salary provided by Google for Software Engineering?", the AI performs the necessary data analysis to provide the most relevant and up-to-date information. For the scope of this hackathon, data analysis is focused on salary information and company-related queries.

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Technologies Used

• ReACT Agent Framework: Powering the dynamic, real-time query handling.
• LangChain: A framework for building applications using large language models (LLMs).
• Plotly: For generating dynamic and interactive visualizations.
• FastAPI: For building the backend API.
• Groq AI: For executing complex queries.
• Pandas: For handling and analyzing datasets.
• Tavily API: For searching and gathering general information from various sources.
• Python: Primary language used for backend development.
• .env: Environment variables to securely store API keys.

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Features

• Real-time Data Analysis: The AI can analyze and respond to queries related to salary trends, company insights, and career advice.
• Salary Analysis: Provides compensation insights and comparisons for specific roles and companies.
• Company Information: Displays employee sentiments and insights about a company's work culture, benefits, and more.
• Visualization: Dynamic, actionable visualizations (e.g., salary trends, job growth, etc.).
• Flexible Integration: Easily extensible to handle a wide variety of career-related queries beyond salaries and company data.

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How to Use

1️⃣ Clone the Repository

git clone https://github.com/your-repo/workwise-ai.git
cd workwise-ai

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Set Up Environment Variables

GROQ_API_KEY=your_groq_api_key
TAVILY_API_KEY=your_tavily_api_key

4️⃣ Run the API

uvicorn main:app --host 0.0.0.0 --port 8000 --reload

API Endpoints

API BASE: : https://3319-2601-8c-4e80-ab40-585-a716-4667-7848.ngrok-free.app

/get_response (POST)

• Description: Processes the user's query and provides career-related insights along with any relevant visualizations.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Video Link : "https://www.youtube.com/embed/VIDEO_I"