README2.md

Max: AI-Powered Developer Portfolio Chatbot

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🚀 Project Overview

Max Portfolio Assistant is an advanced, production-ready AI chatbot API designed to deliver contextual, precise, and dynamic answers about Nivakaran’s professional portfolio. Leveraging the power of retrieval-augmented generation (RAG) combined with vector-based semantic search, this system intelligently interprets user queries and fetches relevant information directly from portfolio documents, including detailed PDFs.

This is not just another chatbot — it’s a smart assistant engineered to showcase developer expertise with real-world, scalable architecture.

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🔥 Why This Project Matters

• Real-world AI Integration: Implements cutting-edge LLM orchestration using LangChain with HuggingFace embeddings and Groq’s hosted large language model.
• Production-Grade API: Built on FastAPI with clear REST endpoints, session management, and CORS ready for seamless frontend integration.
• Multi-turn Dialogue: Maintains chat history context for fluid conversations — no robotic one-off answers.
• Efficient Document Retrieval: Processes and indexes large PDFs into vector embeddings enabling lightning-fast semantic search.
• Clean Code & Logging: Structured with robust error handling and logging — ready for maintenance and scaling.
• Portfolio Showcase: Serves as a unique interactive gateway into the developer’s skills, projects, and professional story.

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🛠 Technical Highlights

Feature	Details
Language Model	Groq ChatGroq (Deepseek-R1-Distill-Llama-70b)
Embeddings	HuggingFace all-MiniLM-L6-v2 for semantic vector search
Vector Store	Chroma DB for fast, persistent vector retrieval
Document Loader & Splitter	PyPDFLoader + RecursiveCharacterTextSplitter for handling large portfolio PDFs
API Framework	FastAPI with async support, CORS, and automatic Swagger docs
Session Management	Session-aware chat history using LangChain's ChatMessageHistory
Environment & Config	.env managed tokens and paths for secure, flexible deployment
Logging & Error Handling	Python logging with clear error responses for production debugging

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📦 Installation & Setup

Setup Project

git clone https://github.com/yourusername/max-portfolio-assistant.git
cd max-portfolio-assistant
python -m venv venv
source venv/bin/activate          # Windows: venv\Scripts\activate
pip install -r requirements.txt

Create .env file with the following variables:

HF_TOKEN=your_huggingface_api_token
GROQ_API_KEY=your_groq_api_key
PDF_PATH=path/to/your/portfolio.pdf
HOST=0.0.0.0
PORT=5000

Run the server:

uvicorn main:app --host $HOST --port $PORT --reload

🔍 How to Use

• Ask the assistant: Send POST requests to /ask with JSON body:

{
  "session_id": "unique-session-uuid",
  "question": "What are Nivakaran's main technical skills?"
}

• Get answers: The AI responds with precise, context-aware answers sourced directly from the portfolio.
• Maintain sessions: Use consistent session_id values to keep chat history context intact.

🧠 Architecture Overview

1. PDF Processing: Portfolio PDF is loaded and split into manageable chunks.
2. Vectorization: Text chunks converted to semantic vectors via HuggingFace embeddings.
3. Indexing: Chroma database stores vectors for similarity search.
4. Query Handling: Incoming questions are reformulated based on chat history.
5. Retrieval & Generation: System retrieves relevant document chunks and generates an answer using Groq LLM.
6. Session Management: Multi-turn dialogue history tracked to ensure coherent conversations.

🎯 Impact & Use Cases

• Personal Branding: Transform your static portfolio into an interactive, AI-powered experience.
• Recruiter Friendly: Instant access to precise answers about skills and projects—no browsing required.
• Tech Demonstration: Showcases expertise in AI integration, API design, and modern NLP pipelines.
• Scalable Architecture: Easily extend to multiple domains or add new data sources.

📚 Technologies & Tools

• Python 3.8+
• FastAPI (ASGI web framework)
• LangChain (LLM orchestration)
• Groq ChatGroq (LLM inference)
• HuggingFace Embeddings (all-MiniLM-L6-v2)
• Chroma Vector Database
• PyPDFLoader & RecursiveCharacterTextSplitter
• Pydantic for request validation
• Uvicorn ASGI server
• Python Logging

🤝 Contributing

Contributions and improvements are welcome! Feel free to open issues or submit PRs for:

• Adding new document types
• Enhancing conversation flow
• Improving deployment (Docker/K8s)
• Optimizing vector search performance

⚡ Final Notes

Max Portfolio Assistant is not just a chatbot, it’s a showcase of how to leverage modern AI, NLP, and backend engineering skills to create real, usable developer portfolio experiences that recruiters notice and remember.