Multi AI agents for customer support email automation built with Langchain & Langgraph
Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python
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
pdfKotha.AI - Interact with PDFs using AI! Upload, ask questions, and get instant answers from Google's Gemini model. Streamline your research and information retrieval tasks effortlessly
RAG-API: A production-ready Retrieval Augmented Generation API leveraging LLMs, vector databases, and hybrid search for accurate, context-aware responses with citation support.
ML Bot is a RAG Application built using google/gemma-2b-it local LLM
BetterRAG: Powerful RAG evaluation toolkit for LLMs. Measure, analyze, and optimize how your AI processes text chunks with precision metrics. Perfect for RAG systems, document processing, and embedding quality assessment.
A supportive server to handle telegram messages using telegram bot API, return back the response to the user with RAG application techniques
AI-powered platform that turns study notes into podcast episodes with two hosts and lets you chat with documents.
This project processes and retrieves information from PDF file or PDF collection. It leverages Qdrant as a vector database for similarity searches and employs a Retrieval-Augmented Generation (RAG).
A basic RAG application for inventory management. Provides real-time stock updates, checks availability, suggests similar products, and generates responses to both customer and manager queries .
A simple Retrieval-Augmented Generation (RAG) web application chatbot called Raggy 🤖
A command-line RAG Chatbot application built from scratch
LLM based rag application that embed given web page to vector db and answer given query using vector similarity cosine.
A Customizable RAG (Retrieval Augmented Generation) App
This project utilizes advanced Large Language Models (LLMs) and vector database technologies to extract structured information about characters from literary texts. It is designed to analyze a given text, identify key characters, and determine their summaries, relationships, and roles (e.g., Protagonist, Antagonist, or Side character)
A dynamic web application made using MERN stack
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