A developer reference project for creating Retrieval Augmented Generation (RAG) chatbots on Windows using TensorRT-LLM

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS

This repository contains different LLM chatbot projects (RAG, LLM agents, etc.) and well-known techniques for training and fine tuning LLMs.

This repository contains advanced LLM-based chatbots for Q&A using LLM agents, and Retrieval Augmented Generation (RAG) and with different databases. (VectorDB, GraphDB, SQLite, CSV, XLSX, etc.)

Your Trusty Memory-enabled AI Companion - Simple RAG chatbot optimized for local LLMs | 12 Languages Supported | OpenAI API Compatible

Llama-github is an open-source Python library that empowers LLM Chatbots, AI Agents, and Auto-dev Solutions to conduct Agentic RAG from actively selected GitHub public projects. It Augments through LLMs and Generates context for any coding question, in order to streamline the development of sophisticated AI-driven applications.

An LLM Chatbot that dynamically retrieves and processes resumes using RAG to perform resume screening.

NTTU Chatbot - A student support chatbot using LLM + Document Retriever (RAG) in Vietnamese

MIT-licensed Framework for LLMs, RAGs, Chatbots testing. Configurable via YAML and integrable into CI pipelines for automated testing.

A local LLM chatbot with RAG for PDF input files

smart-llm-loader is a lightweight yet powerful Python package that transforms any document into LLM-ready chunks. Spend less time on preprocessing headaches and more time building what matters. From RAG systems to chatbots to document Q&A, SmartLLMLoader handles the heavy lifting so you can focus on creating exceptional AI applications.

Empire Chain is a Python framework that orchestrates all your AI needs by seamlessly integrating LLMs (OpenAI, Anthropic, Groq), vector stores (Qdrant, ChromaDB), document processing, speech-to-text, web crawling, data visualization, and interactive chatbots into a unified interface, making it easy to build powerful AI applications like RAG systems

RAG/LLM Security Scanner identifies critical vulnerabilities in AI-powered applications, including chatbots, virtual assistants, and knowledge retrieval systems.

Build-An-LLM-RAG-Chatbot-With-LangChain-Python

LLM evaluation framework for Ruby, powered by RubyLLM. Tribunal provides tools for evaluating and testing LLM outputs, detecting hallucinations, measuring response quality, and ensuring safety. Perfect for RAG systems, chatbots, and any LLM-powered application.

Java 23, SpringBoot 3.4.1 Examples using Deep Learning 4 Java & LangChain4J for Generative AI using ChatGPT LLM, RAG and other open source LLMs. Sentiment Analysis, Application Context based ChatBots. Custom Data Handling. LLMs - GPT 3.5 / 4o, Gemini Pro 1.5, Claude 3, Llama 3.1, Phi-3, Gemma 2, Falcon 3, Qwen 2.5, Mistral Nemo, Wizard Math

Interactive LLM Chatbot that constructs direct and transitive software dependencies as a knowledge graph and answers user's questions leveraging RAG and critic-agent approach

This is the final year project of university, in which my group is developing a chatbot for university admissions using LLMS and RAG. The bot is powered by Langchain and FastAPI. The UI and frontend is developed in Next.js.

An LLM Chatbot based on LangGraph and LangChain that dynamically retrieves and processes resumes using RAG to perform resume screening.

A Retrieval-Augmented Generation (RAG) chatbot that answers questions from your own documents using local or cloud-based LLMs.

Campus Docs Assistant – Built to solve a common challenge in universities, this AI-powered chatbot uses LLMs, intelligent agents and RAG to make academic documents and institutional information easier to access and understand.

A developer reference project for creating Retrieval Augmented Generation (RAG) chatbots on Linux using TensorRT-LLM

Insurance-RAG-Chatbot(IVA): An open-source project featuring a retrieval-augmented chatbot developed using Bedrock, LLM, LangChain, Docker, and more. Contribute to advancing insurance interaction with the power of open collaboration

RAG Based LLM Chatbot Built using Open Source Stack (Llama 3.2 Model, BGE Embeddings, and Qdrant running locally within a Docker Container)

🧬 Build your own conversational AI in minutes (or seconds) with this customizable chatbot template, utilizing modern technologies like Next.js, Tailwind CSS, RAG, Pinecone, and powerful LLM/GenAI APIs (with chunk streaming!) including OpenAI, Fireworks AI, and Anthropic AI. Time to unleash your creativity and transform ideas into reality! 🚀

Retrieval-Augmented Generation on PDF for Free, Integrated with Memory to recall previous interactions, it operates as a sophisticated lang-chain application.

Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.

This project leverages Language Model (LLM) finetuning, Semantic Chunking, and a Retrieval-Augmented Generation (RAG) based Chatbot framework to provide personalized medical information retrieval for remote patients in the Healthcare 5.0 era.

It is a chatbot for question and answering using RAG based on LLM

WhisperMesh is an advanced chatbot that integrates voice and text interactions, delivering personalized responses through LLM models and a sophisticated vector database. Leveraging the RAG framework from Haystack, it ensures engaging, data-driven conversations that adapt to your preferred style.