Update README.md

README.md

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 license: apache-2.0
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+# 🤖 Portfolio-AI — The Backend Brain of My Portfolio
+
+> A RAG-powered AI that knows everything I've built — and can talk about it.
+
+**Live Site → [aaravkumarranjan.netlify.app](https://aaravkumarranjan.netlify.app)**
+
+---
+
+## What Is This?
+
+This is the backend powering the AI chat feature on my personal portfolio. Instead of a static "About Me" page, visitors can actually *talk* to my portfolio — asking about my projects, my stack, how I learn, or anything else.
+
+Under the hood, it's a **Retrieval-Augmented Generation (RAG)** system built from scratch. The knowledge base is a PDF of my portfolio content. When someone asks a question, the system retrieves the most relevant chunks from that PDF and passes them to an LLM to generate a grounded, accurate answer.
+
+This backend is built on the same architecture as Documind, adapted specifically to power the AI chat feature on my personal portfolio.
+
+
+
+---
+
+## Architecture
+
+```
+portfolio.pdf  →  loader  →  chunker  →  embedder  →  vector store
+                                                            ↓
+User Question  →  embed query  →  cosine similarity  →  top chunks
+                                                            ↓
+                                                    LLM → Answer
+```
+
+| Module | Role |
+|---|---|
+| `loader.py` | Extracts text from `portfolio.pdf` |
+| `chunker.py` | Splits text into overlapping chunks |
+| `embedder.py` | Generates semantic embeddings via `sentence-transformers` |
+| `vector.py` | In-memory vector store for chunk embeddings |
+| `retriever.py` | Cosine similarity search — returns top-k relevant chunks |
+| `app.py` | FastAPI server that ties everything together |
+
+---
+
+## Why Build This Instead of Using a Library?
+
+Because I wanted to understand what's actually happening. LangChain and LlamaIndex are great tools, but they abstract away the parts I care most about — how chunking affects retrieval quality, how similarity thresholds prevent hallucination, how the pipeline actually flows end to end.
+
+This project is both a portfolio feature and a learning exercise.
+
+---
+
+## Tech Stack
+
+**Backend:** Python, FastAPI, Sentence Transformers, scikit-learn, NumPy, PyPDF2  
+**Deployment:** Render  
+**Connected Frontend:** [aaravkumarranjan.netlify.app](https://aaravkumarranjan.netlify.app)
+
+---
+
+## Local Setup
+
+```bash
+git clone https://huggingface.co/spaces/Aaravkumar/documind
+cd Portfolio-ai
+pip install -r requirements.txt
+uvicorn app:app --reload
+```
+
+Replace `portfolio.pdf` with your own PDF knowledge base to adapt this for your own portfolio.
+
+---
+
+## Author
+
+**Aarav Kumar Ranjan** 
+
+[Portfolio](https://aaravkumarranjan.netlify.app) · [GitHub](https://github.com/akop-cyber) · [Kaggle](https://kaggle.com/aaravkumarranjan)
+
+
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference