import gradio as gr
from datetime import datetime

SUMMARY = """
Data Scientist with deep expertise in credit risk modeling, statistical analysis, and advanced AI—including agentic systems and Retrieval-Augmented Generation (RAG) architectures.
I build scalable, interpretable models for multi-billion-dollar portfolios and design advanced analytics pipelines that support high-stakes financial decision-making.
"""

EDUCATION = """
**Rutgers Business School – Master of Quantitative Finance (2019–2021)**  
Relevant Coursework: Fixed Income, Derivatives, Econometrics, Financial Time Series, Stochastic Calculus,
Optimization Models, OOP (C++/Python), Risk Management, Equity Trading

**BITS Pilani – B.Tech in Electrical & Electronics Engineering, Minor in Finance (2013–2017)**
"""

EXPERIENCE = """
### Global Monitor – Data Scientist (Oct 2024 – Present, Hyderabad, India)
- Built conversational AI and RAG-based systems over 10M+ market research records, improving actionable insight extraction by ~30%.
- Designed NLP pipelines and QA systems that reduced data exploration and analysis turnaround by ~40%.
- Applied agentic AI and RAG techniques to autonomously enhance retrieval, reasoning, and precision of responses.

### CRISIL (an S&P Global Company) – Data Scientist (Mar 2021 – Jul 2024, New York, USA)
- Built credit risk models for a $5Bn cryptocurrency loan portfolio (PD, LGD, EAD, EEPE, Pluto–Tasche methodology, credit VaR).
- Designed scenario-driven loss forecasting models that improved transparency and contributed to a six‑month delay in client bankruptcy.
- Developed dual Monte Carlo simulation frameworks for 365‑day price paths with stress‑testing variants (1.5x negative return weighting).
- Migrated financial models from R/MATLAB/SQL to Python, improving accuracy, speed, and maintainability.
- Automated analytics pipelines and reporting for 25+ Tier‑1 banks.

### Deutsche Bank – Credit Risk Analyst (Feb 2017 – Jun 2019, Mumbai, India)
- Performed in-depth credit analysis for 40+ counterparties using financial statements, liquidity profiling, and peer benchmarking.
- Built scorecard models for corporates, banks, insurers, and brokerages in Southeast Asia.
- Produced forward-looking projections combining KPIs, macro trends, and DCF inputs; supported rating decisions with Bloomberg and research data.
"""

PROJECTS = """
### NyayaSpashti – AI-Powered Legal Research Assistant
- Hybrid RAG (Chroma + BM25 + cross-encoder reranking) over 12 core Indian Acts.
- Self-verifying RAG workflow with section-level citations and PDF-to-citation mapping.
- Production deployment on Hugging Face Spaces with secure Gemini integration.  
[Open Space](https://huggingface.co/spaces/the-dreimar/NyayaSpashti)

### Credit Default Prediction (American Express)
- LightGBM on 11M+ records with extensive EDA, feature engineering, and validation (TimeSeriesSplit, StratifiedKFold).
- Model evaluation using AUC, Gini; explainability with SHAP and LIME.  
[View Kaggle Notebook](https://www.kaggle.com/code/thuggilisaireddy/credit-default-prediction)

### MarketLens – Multi-Agent Financial Analysis
- CrewAI-based multi-agent system (Fundamental, Technical, News, Bull/Bear, Trader agents).
- Iterative debate workflows, SEC EDGAR + XBRL pipeline, 15+ ratios for S&P 500 fundamentals.
- Gemini-based map–reduce summarization of 10‑K/10‑Q; caching-based API optimization.  
[Open Space](https://huggingface.co/spaces/the-dreimar/MarketLens)
"""

SKILLS = """
**Programming & Databases**: Python, SQL (PostgreSQL, MySQL), R, MATLAB  
**AI/ML**: LangChain, CrewAI, Hugging Face, Google Gemini, OpenAI, RAG Architectures, Multi-Agent Systems  
**Modeling**: Classification, Regression, Clustering, PCA, Ensemble Methods, Deep Learning, Time Series,
Cross-Validation, Hyperparameter Tuning, SHAP, LIME, Feature Engineering  
**Financial Modeling**: Credit Risk (PD, LGD, EAD, VaR), Monte Carlo, Stress Testing, Scenario Analysis  
**Cloud & MLOps**: AWS (AI Practitioner), MLflow, GitHub Actions, CI/CD, Docker  
**Visualization & Apps**: Streamlit, Plotly, Matplotlib, Seaborn, Hugging Face Spaces
"""

CERTIFICATIONS = """
- AWS Certified AI Practitioner (AIF‑C01), 2025  
- IBM Certificate in Retrieval-Augmented Generation (RAG) and Agentic AI, 2025  
- Applied Data Science Lab – WorldQuant University, 2024
"""

CONTACT = f"""
**Hugging Face**: https://huggingface.co/the-dreimar  
**Email**: thuggilisaireddy@gmail.com  
**Phone**: +91 9948343852  
**LinkedIn**: https://www.linkedin.com/in/sai-reddy-thuggili/

**Spaces**:
- NyayaSpashti: https://huggingface.co/spaces/the-dreimar/NyayaSpashti  
- MarketLens: https://huggingface.co/spaces/the-dreimar/MarketLens

_Last updated: {datetime.now().strftime("%B %Y")}_
"""


with gr.Blocks(title="Data Science & AI Portfolio – the-dreimar", theme=gr.themes.Soft()) as demo:
    gr.Markdown("## Data Science & AI Portfolio – Credit Risk, RAG & Multi-Agent Systems")
    gr.Markdown(SUMMARY)

    with gr.Tabs():
        with gr.Tab("👨‍💻 Experience"):
            gr.Markdown(EXPERIENCE)

        with gr.Tab("📁 Projects"):
            gr.Markdown(PROJECTS)

        with gr.Tab("🛠️ Skills & Certifications"):
            gr.Markdown(SKILLS)
            gr.Markdown("### Certifications")
            gr.Markdown(CERTIFICATIONS)

        with gr.Tab("🎓 Education"):
            gr.Markdown(EDUCATION)

        with gr.Tab("📧 Contact"):
            gr.Markdown(CONTACT)

if __name__ == "__main__":
    demo.launch()