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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.
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.
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.
🧠 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.
AI Resume Matcher is a Spring Boot + Spring AI application that uses Retrieval-Augmented Generation (RAG) concepts to rank resumes against a job description. It parses PDF resumes, chunks content intelligently, generates embeddings, stores vectors in ChromaDB, and returns the best matching candidates with scores and reasoning.
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.