A project for summarization in tf2 and pytorch

SummarAIze is a smart research assistant that reads your uploaded PDFs, generates contextual summaries, answers deep questions, and evaluates your logical reasoning — powered by RAG, LangChain, and Groq API.

Hybrid Movie Intelligence Agent combining analytics, retrieval-augmented generation (RAG), and local LLM reasoning over IMDB Top 1000 movies. Ask free-form movie questions, get precise answers, and explore top movies, directors, and summaries.

An Investment Due Diligence RAG assistant that uses an LLM-based routing agent for multi-source reasoning across public docs, internal notes, and models/tables. It routes each question to the right sources, retrieves with FAISS, and returns a grounded answer, highlights conflicts and delivers a summary of risks and follow‑ups for stakeholders.