Document Q&A System using LangChain, LLMs, and Python

Built semantic document QA over websites and PDFs with hybrid LLM support. This project demonstrates practical execution from architecture and implementation to measurable delivery outcomes.

Personal ProjectsYear 2025

Project Overview

Objective

Built semantic document QA over websites and PDFs with hybrid LLM support.

Stack

PythonLangChainFAISSOllama (LLaMA 3.2)GPT-4o

Delivery highlights

Developed a document questionanswering system using Python and LangChain to ingest and process content from websites and PDF files, with semantic retrieval powered by embeddings and FAISS. Integrated both local LLMs via Ollama (LLaMA 3.2) and cloud-based models (GPT-4o) to generate accurate, context-aware responses based on retrieved document content.

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