Full-stack chatbot app that guides users through curated rabbit holes of information.

Pythonを使ってOpenAI APIやlangchainを用いて、RAG(Retrieval Augmented Generation)をいろいろなパターンで実装してみる.

RAG-as-a-judge augmented with human feedback

Implementation of website that allows users to easily create and interact with personalized chatbots, fostering dynamic conversations based on user-inputted data.

NLP Analysis of German election programs

This repository presents a project focused on developing a high-precision legal expert LLM application called Contract Advisor RAG. The project's goal is to create a Retrieval Augmented Generation (RAG) system for Contract Q&A, enabling users to interact with contracts by asking questions and receiving accurate, context-rich responses.

Retrieval Augmented Generation Chatbot with Langchain 🦜🔗 and HuggingFace 🤗

This repository contains code from the blog posts series on how to build RAG (Retrieval Augmented Generation) system from scratch.

Welcome to Virtuatlas 🚌, a responsive mobility app designed to make transportation in unfamiliar urban areas a breeze! With a user-friendly interface, real-time analytics, and multi-lingual support, our app ensures a comfortable journey for every traveler. Scan the surroundings, chat via text, voice, or images. Includes RAG-ML Environment.

Implementation of a Natural Disaster Chatbot Agent that utilizes tools (function calling) to invoke task specific knowledge bases and improve LLMs accuracy by proving live data.

A RAG application using local LLM to answer questions given a PDF.

Testing Different RAG Applications

A tool that allows users to engage in conversations about the contents of a website using the state-of-the-art RAG (Retrieval-Augmented Generation) technique. Simply input a website URL, and start chatting with our language model!

Chatbot powered by LLM to chat with documents

Ask any question from your virtual HR using HRBuddy . Powered by llamaindex and chatgpt3.5

LangChain framework provides chat interaction with RAG by extracting information from URL or PDF sources using OpenAI embedding and Gemini LLM

Natural Language Querying using RAG LLMs with Excel Sheets as the context

Retrieval Augmented Generation QnA application with Azure OpenAI and SpringAI

Couchbase vector RAG demo