generative-ai

A repository of curated use cases, articles, blogs, videos on how companies are using Artificial Intelligence and Machine Learning.

Practical GenAI-Eshop application using Semantic Kernel, multi-agent orchestrations, Mcp tools, A2A Agents, Semantic Search, Aspire and more.

Text summation using python, deep learning, machine learning, transformer, huggingface, openai and langchain

Implementation of Retrieval Augmented Generation model in typescript with Gemini LLM

Finetune Web UI is a user-interface for training and deploying pre-trained models.

Comprehensive LLMs repo, where I cover both theoretical and practical aspects of LLMs.

Embark on the "Reinforcement Learning from Human Feedback" course and align Large Language Models (LLMs) with human values.

A curated full-stack LLM engineering playbook — from AI infrastructure and model lifecycle to agents, MCP, memory, and evaluation.

AI News Scraper & Semantic Search: A Python application that scrapes news articles, uses GenAI to generate summaries and identify topics, and provides semantic search capabilities through vector embeddings

FlashHead: Efficient Drop-In Replacement for the Classification Head in Language Model Inference

Fine-tune a local LLM on your own chat history to mimic how you write — an AI doppelganger / digital-twin toolkit built on LLaMA-Factory (LoRA SFT).

Learn LangChain for Genearative AI with OpenAI API using Python

A multimodal live AI assistant designed to enhance the browsing experience using Gemini.

Multi-Agent Comic Generator powered by the @google-gemini API. Turn simple prompts into comics with AI-generated stories, consistent characters, auto speech bubbles, and 7 language support. Built with FastAPI and deployed on Google Cloud Run.

[WACV 2026] The official implementation of the paper titled " End-to-End Fine-Tuning of 3D Texture Generation using Differentiable Rewards" accepted to IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026

A personal AI knowledge assistant powered by RAG, semantic search, and document understanding for context-aware answers.

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

Production-style Retrieval-Augmented Generation document Q&A: LangChain ingestion, Chroma/pgvector store, hybrid retrieval, citation-grounded answers and a streaming chat API.

A visual, web-based programming language and AI notebook: compute, compose, converse.

Companion code for the Manning book 'LLM Customization and Fine-Tuning.' Adapt open-weights LLMs end to end: prompting and RAG, LoRA/QLoRA, full SFT, distillation, and DPO/RLHF alignment.