https://github.com/labwhatever/surajgpt

AskSuraj is a Retrieval-Augmented Generation (RAG)-powered assistant designed to answer questions about my portfolio, skills, projects, and experiences using natural language.
https://github.com/labwhatever/surajgpt

Last synced: 9 months ago
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AskSuraj is a Retrieval-Augmented Generation (RAG)-powered assistant designed to answer questions about my portfolio, skills, projects, and experiences using natural language.

• Host: GitHub
• URL: https://github.com/labwhatever/surajgpt
• Owner: labwhatever
• Created: 2025-06-20T11:29:12.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2025-06-20T11:32:08.000Z (12 months ago)
• Last Synced: 2025-08-09T14:41:58.997Z (10 months ago)
• Language: Python
• Homepage: https://rag.surajv.me
• Size: 67.4 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# AskSuraj 🤖 — Portfolio RAG Assistant

**AskSuraj** is a Retrieval-Augmented Generation (RAG)-powered assistant designed to answer questions about my portfolio, skills, projects, and experiences using natural language.

It uses vector-based semantic search to retrieve relevant information and generates responses using an LLM. This project showcases my ability to integrate AI, NLP, and fullstack development into a smart, job-ready portfolio tool.

---

## 🚀 Features

- 🔎 Semantic Search over portfolio documents

- 🧠 LLM-powered Q&A system

- 🗂️ Supports resume, project write-ups, blogs, and more

- 🪄 Built with FastAPI, LangServe, and OpenAI embeddings

- 💡 Great for recruiters, collaborators, or curious devs!

---

## 🛠️ Tech Stack

- **FastAPI** – for serving the API

- **LangChain + LangServe** – for RAG pipeline

- **FAISS / Chroma** – for vector indexing

- **OpenAI / Local LLM** – for response generation

---

## 📚 Use Case

> Curious about my projects? Just ask:  

> _"Tell me about the tech stack used in your Tic Tac Toe game."_  

> or  

> _"What is your current DSA plan?"_  

And boom — the AI pulls the exact info from my actual docs!

---

## 📦 How to Run Locally

```bash

git clone https://github.com/smartcraze/surajGPT.git

cd asksuraj

pip install -r requirements.txt

python ingest.py   # index your portfolio docs

uvicorn app:app --reload