Multi AI agents for customer support email automation built with Langchain & Langgraph
Local RAG researcher agent built using Langgraph, DeepSeek R1 and Ollama
Educational toolkit for all things RAG (Retrieval Augmented Generation)
A full-stack, microservices-based application for secure document management, enabling users to upload, parse, index, and query various file types through advanced NLP and RAG agents. Built with Docker and Kubernetes for scalability, and integrates Elasticsearch, Redis, and AWS S3 for efficient storage and search capabilities.
QueryPilot is an advanced document intelligence platform that combines Large Language Models (LLMs) with vector embeddings to enable natural language querying of your documents. The application processes various file formats (PDFs, DOCXs, TXT files, and images), extracting and embedding content for semantic search and AI-powered analysis.
This repository contains the implementation of a Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs). RAG agents combine the power of information retrieval with text generation, enabling applications such as intelligent question-answering systems, and more.
This python powered AI based RAG Scraper allows you to ask question based on PDF/URL provided to the software using local Ollama powered LLMs
AI driven Content Creation Automation.
Agentic RAG for journalling
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