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embeddings-model

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This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and localizing content generation.

  • Updated May 19, 2024
  • TypeScript

A production-style RAG-based AI Knowledge Assistnt developed during the AI & Automation Internship at NEXEAGENT. The system securely uploads company documents, generates semantic embeddings, stores contextual knowledge in a vector database, and delivers accurate AI-powered responses using Google Gemini, (RAG) & intelligent vector Search pipelines.

  • Updated May 26, 2026
  • Python

ReelMind — A RAG-powered chatbot that lets you paste any YouTube URL and ask questions about the video's content. It extracts the transcript, indexes it with embeddings and FAISS, and answers your questions grounded in what was actually said.

  • Updated Sep 22, 2026
  • Python

AI-powered fashion image similarity search system. Originally built as a technical hiring assignment for LabhTeX — this project's success led directly to a full-time AI/ML Engineer offer. Uses image embeddings for visual similarity search, containerized with Docker and deployment-ready.

  • Updated Sep 29, 2026
  • Python

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