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title: Documind
emoji: 📚
colorFrom: yellow
colorTo: gray
sdk: docker
pinned: false
license: apache-2.0
🤖 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
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
Local Setup
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