SkillSphere - a holistic view of your skills and future.

Transform career uncertainty into a personalized, efficient, and cost-effective learning journey with AI-driven guidance.

Table of Contents

• Problem Statement
• Our Solution
• Features
• Architecture
• Quick Start
• Installation
• Usage
• API Documentation
• Development
• Contributing
• License

Problem Statement

Students and professionals struggle with career uncertainty and inefficient upskilling because traditional guidance is generic, stereotypical, and disconnected from the job market.

Core Issues We Solve:

• 🎯 Poor Career Fit: Individuals don't know which fields match their skills and interests
• ❓ Unclear Skill Gaps: Lack of visibility into specific knowledge needed to advance
• ⏰ Wasted Learning Time: Overwhelmed by resources without structured, personalized paths
• 💸 High Financial Risk: Spending money with no guaranteed ROI
• 🎓 Education-Employment Mismatch: Outdated curricula leaving workers underprepared

Our Solution

SkillSphere provides a data-driven AI platform that transforms career uncertainty into a personalized, efficient, and cost-effective journey. Our solution acts as a dynamic digital career advisor, aligning individual potential with real-time job market demand.

Problem	How We Solve It	Result for User
Poor Fit & Uncertainty	Personalized AI Matching using CV/Resume analysis	Clarity & Confidence in career direction
Unclear Skill Gaps	Dynamic Gap Analysis comparing current vs. required skills	Targeted Preparation with specific learning goals
Wasted Learning Time	Structured Learning Paths with personalized curricula	Efficiency & Focus with accelerated learning
High Financial Risk	Cost-Optimized Education with scholarship recommendations	Maximized ROI with smart financial planning
Education-Employment Mismatch	Real-Time Market Feedback with salary and demand data	Relevant & Employable skills for immediate value

Features

AI-Powered Intelligence

• Agentic AI: Powered by Google's Gemini 2.0 Flash for intelligent reasoning
• Context Awareness: Maintains conversation memory across sessions
• Proactive Guidance: AI takes initiative to suggest next steps

User Profiling & Analysis

• Comprehensive profile collection (skills, interests, goals)
• Resume/CV analysis with skill extraction
• Learning style and time availability assessment

Career Recommendations

• Data-driven career matching based on interests and skills
• Real salary data and job growth projections
• Market demand analysis with job posting frequency

Personalized Learning Paths

• Real Course Links: Top 3 courses with actual URLs and pricing
• Certification Guidance: Industry-recognized credentials with provider links
• Job Search Resources: Direct links to relevant job platforms
• Phase-by-phase curriculum with specific milestones

Financial Planning

• Detailed Cost Analysis: Monthly, weekly, yearly breakdowns
• ROI Calculations: Break-even time and salary increase projections
• Scholarship Finder: Targeted financial aid recommendations
• Payment Plan Options: Flexible learning investment strategies

Progress Tracking

• Skill mastery badges and achievements
• Learning milestone tracking
• Motivational progress updates

Architecture

Frontend (HTML/CSS/JS) → Backend (Flask) → Agent (ADK) → AI (Gemini 2.0 Flash)

Components:

• 🎨 Frontend: Professional web interface with real-time chat
• ⚙️ Backend: Flask server with RESTful API endpoints
• 🧠 Agent: Google ADK agent with specialized career tools
• 🔑 AI Engine: Gemini 2.0 Flash for intelligent reasoning

Quick Start

Prerequisites

• Python 3.8+
• Google API Key (for Gemini AI)
• Google ADK installed

1. Clone & Setup

git clone https://github.com/VJGit1/SkillSphere.git
cd SkillSphere
pip install -r requirements.txt

2. Configure Environment

# Create .env file in multi_tool_agent/ directory
echo "GOOGLE_GENAI_USE_VERTEXAI=FALSE" > multi_tool_agent/.env
echo "GOOGLE_API_KEY=your_api_key_here" >> multi_tool_agent/.env

3. Run Application - Three Ways to Experience SkillSphere

Option A: Complete Application (Recommended for Demos)

python server.py
# Visit: http://localhost:5000
# Professional UI with chat interface

Option B: Streamlit Interface (User-Friendly)

streamlit run streamlit_app.py
# Visit: http://localhost:8501
# Interactive web app with forms and widgets

Option C: Agent Testing (Development)

adk web
# Visit: http://localhost:8000
# Select 'multi_tool_agent' from dropdown
# Direct agent testing interface

Installation

Step 1: Install Dependencies

pip install -r requirements.txt

Step 2: Install Google ADK

pip install google-adk

Step 3: Get Google API Key

1. Visit Google AI Studio
2. Create a new API key
3. Copy the key to your .env file

Step 4: Environment Setup

Create multi_tool_agent/.env:

GOOGLE_GENAI_USE_VERTEXAI=FALSE
GOOGLE_API_KEY=your_actual_api_key_here

Usage

Three Ways to Experience SkillSphere

1. Complete Application (Best for Hackathon Demos)

python server.py
# Visit: http://localhost:5000

• Features: Professional chat interface, real-time responses
• Best For: Demonstrations, hackathon presentations
• UI: Custom HTML/CSS with agent integration

2. Streamlit Interface (User-Friendly)

streamlit run streamlit_app.py
# Visit: http://localhost:8501

• Features: Interactive forms, widgets, step-by-step guidance
• Best For: User testing, interactive exploration
• UI: Streamlit's native components with sidebar navigation

3. ADK Agent Testing (Development)

adk web
# Visit: http://localhost:8000
# Select 'multi_tool_agent' from the dropdown

• Features: Direct agent tool testing, function debugging
• Best For: Development, tool validation
• UI: ADK's default agent testing interface

All Three Provide Same Core Intelligence

• ✅ Same Gemini 2.0 Flash AI model
• ✅ Same 9 career guidance tools
• ✅ Same real course links and cost calculations
• ✅ Same personalized recommendations

Choose based on your audience:

• Judges/Demos: Flask app (localhost:5000)
• End Users: Streamlit app (localhost:8501)
• Developers: ADK web (localhost:8000)

Example Prompts to Try

• Career Exploration: "I'm a marketing graduate interested in technology. Help me find a career path."
• Learning Resources: "Show me the top 3 courses for software development with real links."
• Cost Analysis: "Calculate monthly costs for becoming a data scientist."
• Job Search: "Where can I find UX design jobs?"

ADK Agent Testing (Development)

adk web
# Visit: http://localhost:8000
# Select 'multi_tool_agent' from dropdown (as shown in screenshot)
# Test individual agent functions directly

What you'll see:

1. ADK web interface opens
2. Dropdown shows "multi_tool_agent" and "templates"
3. Select "multi_tool_agent" to test your SkillSphere agent
4. Direct access to all 9 career guidance tools

API Documentation

Base URL: http://localhost:5000/api

Endpoints

POST /api/chat

Main chat endpoint for conversation with AI agent.

{
  "message": "I want to become a software developer",
  "user_id": "unique_user_identifier"
}

Response:

{
  "status": "success",
  "response": {
    "message": "Formatted response with course links",
    "suggestions": ["Calculate costs", "Find scholarships"],
    "type": "curriculum"
  }
}

POST /api/start-journey

Initialize a career guidance session.

{
  "name": "Sarah",
  "user_id": "user_123"
}

GET /health

Health check endpoint.

Response:

{
  "status": "healthy",
  "agent_loaded": true,
  "message": "SkillSphere backend is running"
}

Development

Project Structure

SkillSphere/
├── multi_tool_agent/
│   ├── agent.py          # Main ADK agent with career tools
│   ├── .env              # Google API key configuration
│   └── __init__.py       # Module initialization
├── templates/
│   └── index.html        # Frontend UI
├── server.py             # Flask backend server
├── streamlit_app.py      # Alternative Streamlit interface
├── requirements.txt      # Python dependencies
├── .gitignore           # Git ignore rules
└── README.md            # This file

Agent Tools

• start_career_journey() - Welcome and initial guidance
• collect_user_profile() - Comprehensive profile collection
• analyze_resume_skills() - Resume/CV skill extraction
• recommend_career_paths() - AI-powered career matching
• generate_learning_curriculum() - Personalized learning paths
• track_learning_progress() - Progress monitoring with badges
• calculate_learning_costs() - Detailed financial analysis
• find_scholarships() - Targeted scholarship recommendations
• manage_conversation_state() - Session memory management

Testing the Agent

1. Individual Tool Testing

   adk web
   # Test: "Start my career journey"
   # Test: "Analyze my resume: [paste resume text]"
   # Test: "Recommend careers for technology interests"

2. Complete Flow Testing

   python server.py
   # Test full user journey from profile to job placement

Adding New Features

1. New Agent Tool

   def new_career_tool(parameter: str) -> Dict[str, Any]:
       """New tool description"""
       return {"status": "success", "data": "result"}

2. Add to Agent

   tools=[..., new_career_tool]

3. Update Server Route

   # Add keyword detection in call_agent_sync()
   elif 'new_feature' in message_lower:
       result = new_career_tool(parameter)

Deployment Options

Local Development

python server.py  # Development server

Production Deployment

# Using Gunicorn
pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 server:app

# Using Docker
docker build -t skillsphere .
docker run -p 5000:5000 skillsphere

Cloud Deployment

• Google Cloud Run: Deploy with ADK integration
• Heroku: Easy deployment with Procfile
• AWS EC2: Full control deployment
• Streamlit Cloud: For Streamlit version

Contributing

We welcome contributions! Please see our Contributing Guidelines.

Development Setup

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit changes: git commit -m 'Add amazing feature'
4. Push to branch: git push origin feature/amazing-feature
5. Open a Pull Request

License

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

Hackathon Information

Project: SkillSphere - AI Career Advisor
Team: VB
Technology Stack: Google ADK, Gemini AI, Flask, HTML/CSS/JS
Demo URL: http://localhost:5000

Key Innovation Points

• ✅ Real-time AI agent powered by Google's latest Gemini model
• ✅ Actual course links and certification URLs (not mock data)
• ✅ Detailed financial analysis with ROI calculations
• ✅ Agentic AI that takes initiative and maintains context
• ✅ Professional UI with seamless agent integration

Acknowledgments

• Google ADK Team for the powerful agent development framework
• Google AI for Gemini 2.0 Flash model access
• Course Providers (Coursera, Udemy, edX) for educational resources
• Open Source Community for inspiration and tools

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Made with ❤️ for career transformation through AI