# Import required libraries for portfolio
from portfolio import Engineer
from skills import AI, MachineLearning, DataScience
from tools import Python, PyTorch, TensorFlow, React
import passion

# Initialize Kavya's Profile
kavya = Engineer(
    name="Kavya Chouhan",
    role="AI/ML Engineer & Data Scientist",
    location="India",
    status="Open to opportunities"
)

# Display profile
kavya.introduce()

# Technical Skills
skills = {
    "ML & AI": ["TensorFlow", "PyTorch", "Scikit-Learn", "LangChain", "OpenCV"],
    "Data & Analytics": ["Power BI", "Tableau", "Pandas", "NumPy", "MongoDB", "Pinecone"],
    "Programming": ["Python", "JavaScript", "SQL"],
    "Frameworks": ["FastAPI", "Django", "Flask", "React.js", "Next.js", "Bootstrap", "TailwindCSS"],
    "Deployment": ["Git/GitHub", "CI/CD", "Docker", "AWS", "Azure"]
}

# Display skills
print("Technical Skills:")
for category, techs in skills.items():
    print(f"{category}: {', '.join(techs)}")

# About Kavya Chouhan
intro = """
Hey there! I’m Kavya. I love puzzles, whether it’s solving a tough coding problem, 
solving a Rubik’s cube in record time, or brainstorming the next fun idea for my 
tech club. My approach to life is simple: stay curious, keep experimenting, 
and enjoy the journey.
"""

print(intro)

# Academic Background
education = [
    {
        "degree": "BS in Data Science",
        "institution": "Indian Institute of Technology Madras (IITM)",
        "status": "Pursuing"
    },
    {
        "degree": "BSc in Information Technology",
        "institution": "Jai Hind College",
        "status": "Pursuing"
    }
]

print("EDUCATION")
for edu in education:
    print(f"  {edu['degree']}")
    print(f"  {edu['institution']} ({edu['status']})")
    print()

# Work Experience
experience = [
    {
        "role": "Data Analyst Intern",
        "company": "GAC Shipping",
        "period": "Jan 2025 - May 2025",
        "description": "Built Power BI dashboards for data visualization"
    },
    {
        "role": "AI Intern",
        "company": "AITS Software Pvt. Ltd.",
        "period": "Sept 2025 - Dec 2025",
        "description": "Tested and deployed AI Agents for MSMEs"
    }
]

print("WORK EXPERIENCE")
for exp in experience:
    print(f"  {exp['role']}")
    print(f"  {exp['company']} | {exp['period']}")
    print(f"  {exp['description']}")
    print()

# Load and display projects
projects = [
    {
        "name": "Saarthi - AI Academic Assistant",
        "description": "RAG-powered chatbot for IITM BS students",
        "type": "Personal Project",
        "tags": ["RAG", "LangChain", "React.js", "FastAPI"],
        "timeline": "March 2025 - Present"
    },
    
    {
        "name": "CubeDev",
        "description": "A comprehensive speedcubing platform",
        "type": "Personal Project",
        "tags": ["Next.js", "TypeScript", "Finetuned Llama3", "Tailwind CSS"],
        "timeline": "Sept 2025 - Present"
    },
    {
        "name": "Hand Gesture System Control",
        "description": "CV system for hands-free device control",
        "type": "College Project",
        "tags": ["Computer Vision", "OpenCV", "MediaPipe"],
        "timeline": "Feb 2024 - March 2024"
    },
    {
        "name": "ExploreMyData",
        "description": "Automated EDA platform for data scientists and ML engineers",
        "type": "Personal Project",
        "tags": ["Next.js", "TypeScript", "Tailwind CSS", "Python", "Pandas", "Matplotlib", "Seaborn"],
        "timeline": "Jan 2026"
    },
    {
        "name": "FillMyForm",
        "description": "Synthetic response generator for Google Forms",
        "type": "Personal Project",
        "tags": ["Next.js", "TypeScript", "Tailwind CSS", "Google Forms API"],
        "timeline": "Jan 2026"
    }
]

# Display projects
for i, proj in enumerate(projects, 1):
    print(f"{i}. {proj['name']}")

# Load research publications
publications = [
    {
        "title": "Phishing Detection and Prevention Using ML Algorithms",
        "authors": ["Kavya Chouhan", "Rohana Deshpande", "Fatima Shaikh"],
        "venue": "Zenodo",
        "year": 2025,
        "type": "Research Paper",
        "doi": "10.5281/zenodo.15681835",
        "status": "Published"
    }
]

# Display publications
for i, pub in enumerate(publications, 1):
    print(f"{i}. {pub['title']}")
    print(f"   Authors: {', '.join(pub['authors'])}")
    print(f"   {pub['venue']}, {pub['year']}")
    print(f"   DOI: {pub['doi']}")
    print(f"   Status: {pub['status']}")
    print()

# Contact information
contact = {
    "email": "kavyachouhan2005@gmail.com",
    "linkedin": "linkedin.com/in/kavya-chouhan",
    "github": "github.com/kavyachouhan",
    "location": "India",
    "availability": "Open to opportunities"
}

# Display contact methods
for platform, info in contact.items():
    print(f"{platform.title()}: {info}")

# Send a message
def send_message(name, email, subject, message):
    """
    Submit a contact form message
    """
    return {
        "status": "pending",
        "name": name,
        "email": email,
        "subject": subject,
        "message": message
    }

# Example usage
# result = send_message("Your Name", "email@example.com", "Subject", "Hello!")