AI-Powered Job Extraction and Cold Email Generator

A production-grade AI Digital Twin built from scratch. Features an evolutionary architecture: starting from raw RAG & Memory experiments, evolving into an Agentic Workflow with Tool Calling with a Streamlit UI. Powered by LangChain, OpenAI, and ChromaDB.

contextops

Sistema RAG de nueva generación powered by **Docling de IBM Research** para procesamiento inteligente de documentos complejos con análisis multimodal, extracción de tablas, descripción de imágenes y conversión a markdown estructurado.

A complete, structured, hands-on LangChain playlist covering everything from LLMs & embeddings to chains, runnables, retrievers, vector stores, tools, and RAG systems. This repository is designed to help you learn LangChain practically, step by step, with clean Python scripts and Jupyter notebooks.

Shodhak - an AI-powered research assistant that helps you analyze and ask questions about multiple online articles simultaneously.

AI-powered personalised study planner using RAG + LangChain + Groq Llama-3.1 + ChromaDB

Retail_QandA_Tool is an AI-powered Natural Language to SQL system for AtliQ Tees. It allows store managers to query inventory, sales, and discount data using simple natural language.

[MJU] 명지대학교 입학관리팀 입학처 공식 AI챗봇 서비스(RAG방식 LLM 챗봇) - 명지대학교 입학처 홈페이지 운영중

🧠 AI-powered Standard Operating Procedure (SOP) interpreter with voice-first interaction, Knowledge Graph intelligence, and RAG technology. Transform complex procedures into conversational AI assistance using React, FastAPI, Neo4j, and Groq LLM.

Reto 1 - Optimización Inteligente de Procesos de Licitación en Construcción

RAG application based on ayurvedic text Ashtang Hridayam

Building a chatbot using pre-trained LLM (Llama2) that can answer questions related to any topics it is trained on.

An AI-powered document search engine that connects to Notion and Google Drive. Uses LangChain4j, OpenAI embeddings, and ChromaDB to provide semantic search and natural language RAG answers.

Local Retrieval-Augmented Generation (RAG) pipeline using LangChain and ChromaDB to query PDF files with LLMs.