Custom agents

🔧 Windows driver updater - Automatic driver detection, download & installation tool

Speed up your RAG by performing cosine similarity parallel on your CPU Cores

Persistent memory for AI agents. Local SQLite, hybrid retrieval, zero-config OpenClaw plugin.

A chat bot for the Faculty of Sciences and Technologies of Tangier. Using both RAG and finetuning as separate models.

Local fine-tuning, pre-training and RAG for LLMs

RAG FAQ assistant in C# using Ollama for local AI-powered, context-aware Q&A with chat history.

Curated List of Research Papers

A RAG built for medical queries ( in 12 hours for a hackathon )

Semnet efficiently constructs graph structures from embeddings, enabling graph-based analysis and operations over large collections embedded texts, images, and more.

Working demos built with SuperDoc - document RAG, AI redlining, and more.

LLM is a very powerful tool. It often performs more than required (hallucinations) and may tend to generate output in a pattern it finds best. We need RAG to harness the power of LLM in a controlled manner. In this work we implement a simple RAG system with Codegemma and an in-memory Vector Database.

Generating embedding for 1000s of PDF Documents, in Qdrant using FastEmbed with distributed Computing in Ray

Nifty 50 Companies Annual Reports Companion.

"GAIA Agent: An AI system automating solutions for the GAIA benchmark with tools for reasoning, code execution, data interpretation, and multimodal tasks."

Gradio Chatbot application that uses retrieval-augmented generation (RAG) to answer questions about my professional experience and my resume. The chatbot is designed to retrieve relevant information from a resume and generate intelligent responses using large language models (LLMs).

An AI Lawyer Assistant platform designed to provide intelligent legal consultation and assistance (Tunisian law). The platform features a RAG-based AI chatbot, an OAuth authentication system & a community forum

Our AI Financial Advisor is designed to revolutionize how users interact with financial and investment data by integrating advanced AI techniques. At the core of our application is a sophisticated model that employs embeddings and RAG to provide accurate and insightful responses to user queries.

Multimodal-VideoRAG: Using BridgeTower Embeddings and Large Vision Language Models

The Agriculture Assistant is an LLM-powered system aiding farmers with agricultural advice. It has Frontend (React), Backend (Python), and RAG subsystems, supporting text/image/audio input, Mandarin audio output, and knowledge retrieval via vector databases.

Solution for AI Action Summit Hackathon 2025 | Intelligent AI agent on emergency lines to assist call center operators, optimize waiting times, and provide immediate responses to urgent situations.

LilRag — A lightweight Retrieval-Augmented Generation (RAG) framework for building custom Q&A systems.

SCIST x SCAICT Camp 2026 聯合寒訓 AI 系列課程 - 教材與原始碼

Local Embedding models benchmark tool & result

Local legal AI for EU directives & regulations. Fully offline, no API calls.

App for Hyland Content Lake

Welcome to the Mixtral 8x7B offloading demo repository! This project aims to demonstrate the seamless execution of Mixtral-8x7B models on Colab or consumer desktops.

AI for Active Reading - Hackathon Winner!

CustomKB transforms your documents into AI-powered, searchable knowledgebases with state-of-the-art embedding models, vector search, and language models to deliver contextually relevant answers from your data.

About A simple RAG (Retrieval-Augmented Generation) app built with Streamlit. Upload PDFs, ask questions, and get context-aware answers using Qdrant and Hugging Face Transformers.

A hands-on security lab demonstrating how to poison a Retrieval-Augmented Generation (RAG) system by injecting malicious data into its vector database. Learn RAG architecture, attack surfaces, poisoning techniques, detection methods, and mitigation strategies through a practical, lightweight demo.

A journalist that knows lots of news about AI!📰💻

This is RAG Modules Repo. This includes various modules in the RAG ecosystem.

AIVO is an AI-based qualitative research suite designed to find and extract relevant information from custom data store for a smooth and efficient qualitative research experience using generative AI. Enabling innovate search operations like RAG, RFG, Batch Processing, Serialized Search, etc.

UDF + AI-Q + TTD DR + IaaC (AWS EKS and NIMs) + AG-UI + CopilotKit

An agentic graph-based Retrieval-Augmented Generation (RAG) system for querying PDFs and the web, built with LangGraph, Gemini LLM, ChromaDB, and Streamlit. Features intelligent multi-node workflows for ingestion, retrieval, web search, and reasoning.

Titan-Memory , it is a memory system that is not only for memory, but it also has built-in safety guardrails, circuit-breakers, semantic adapters, and drift protection. Everything you need to run Agents safely. Built-in.

A clean and simple implementation of Retrieval Augmented Generation (RAG) to enhanced LLaMA chat model to answer questions from a private knowledge base. We use Tesla user manuals to build the knowledge base, and use open-source embedding and Cross-Encoders reranking models from Sentence Transformers in this project.

AI-powered security log analysis platform using RAG and LLMs

Course material for the DSD bootcamp on combining large language models with vector databases.

RAG based QA system based on domain knowledge from local PDFs, useful for reviewing for exams and interviews :)

Open-source AI Plant detection that provides fast and accurate response.

Implement a Retrieval-Augmented Generation (RAG) workflow using Vertex AI RAG Engine and Gemini 2.0 Flash on Google Cloud.

A LangGraph-powered fantasy RPG engine that builds an agentic world while utilizing tool-calling, retrieval-augmented generation (RAG), and dynamic summarization for efficient token usage. Players interact with evolving storylines, NPCs, inventory, and game logic through a language model acting as the game master.

知识库RAG项目

A Retrieval-Augmented Generation (RAG) chatbot built in Python using embeddings, PostgreSQL with pgvector, and Hugging Face language models. This project allows a chatbot to answer user queries by retrieving relevant information from a corpus of text documents.

Local AI memory system for Node.js — verbatim storage, semantic search, knowledge graph, MCP server. Port of the Python MemPalace.

🧠 Local-first RAG index that watches your files and serves MCP semantic search

A curated collection of papers, frameworks, tools, and resources on Retrieval-Augmented Generation (RAG). Maintained for students of the Text Mining and Data Visualization course as a starting point for thesis research.

Lets you ask question about topics in video and gives summary of the YouTube video.

Chat with your database. Locally. VS Code extension for exploring and understanding schemas and stored procedures using local LLMs. SQL Server · PostgreSQL · MySQL. Zero cloud dependency.

A graph-first, embedded multi-model database engine

Secure FedRAG framework for distributed health data search and knowledge exchange

LearnAbility is a comprehensive learning platform designed to provide an accessible, personalized, and inclusive educational experience for all users—especially underserved communities and students with disabilities.

Demo showing how the Trustworthy Language Model add reliability to LLM outputs and improves RAG, agents, and data enrichment worfklows. can be used to improve fine-tuning of LLMs, accuracy of LLM outputs, and smart routing for RAG and agents.

Nancy's RAG backend and HTTP API/MCP server connectors.

The living wiki that writes itself.

AI RAG that teaches you what is going on in Ghana's parliament

Multimodal emotion assistant with visual emotion analysis, Qwen realtime voice interaction, and local RAG knowledge base.

Starter project for creating an API endpoint that performs web searches, scrapes results, and generates answers using LLM.

RAG with LLM agents for SQL & graph databases

A vanilla from scratch Retrieval Augmented Generation (RAG) implementation that includes a web interface to control it.

🧠 [ACM-TORS] A Resource for Multi-Modal Learning in Visual RAGs

Memory module for LLMs and Agents with MCP

A FastMCP based mcp server for weaviate, deployable using uvx.

RATE: An LLM-Powered Retrieval Augmented Generation Technology-Extraction Pipeline

POMA AI cli - integrate poma into your pipeline. Optimised for agent use.

My first Multi-Modal RAG pipeline....Dummy version

Analyzing the performance of Mamba-based vs. Transformer-based Retrieval Augmented Language Models over increasing k number of chunks retrieved.

Autonomous multi-agent framework for self-correcting image synthesis using 'Think → Generate → Critique → Refine' cycles with Gemini 3.1 and SDXL.

Root Cause Analysis of Task Plans implemented using BehaviorTrees using ChatGPT

Allows you to merge search results from multiple search engines using the reciprocal rank fusion algorithm.

Ask AI for Your Docs & Websites. Open-source, RAG-powered AI assistant that answers from your content. Embed anywhere in minutes.

A Retrieval-Augmented Generation (RAG) system for automating Security Operations Center (SOC) log analysis. This project combines NLP techniques with vector search to process security logs, enabling semantic querying and visualization through an interactive Streamlit interface.

CodeMap is a CLI tool that generates optimized markdown docs and streamline Git workflows.

针对有旅行意愿，但是没有时间规划行程，或在旅途中想要获得帮助建议等问题，开发了一个基于Spring AI框架的智能旅游咨询平台。项目采用RAG检索增强生成技术构建专业知识库，通过Tool Calling、MCP协议集成多种外部工具服务，实现具备自主规划能力的AI Agent智能体，为用户提供旅行方面困惑的咨询服务。

Hardware-Accelerated Cryptographic RAG System — GPU simulation of SHA-256 hash engine with AES-256-GCM encryption and Merkle tree integrity. NOT real ASIC hardware.

Generalized, Offline-First Multimodal AI System

NLP (Natural Language Processing)

A Visual and Interactive tool to learn and explore Hybrid RAG (Vector + Graph DBs) and Agentic RAG systems.

A production-quality real-time messaging app built with React Native (Expo), Cloudflare Workers, and Durable Objects, featuring edge-native AI capabilities with RAG and multi-step agents.

My personal notes, code and projects of the Udacity Generative AI Nanodegree.

A library to calculate similarity scores between two collections of text sequences encoded using transformer models for bitext mining, dense retrieval, retrieval-based classification, and retrieval-augmented generation (RAG).

A fully offline NLP pipeline for extracting, chunking, embedding, querying, summarizing, and translating research documents using local LLMs. Inspired by the fictional mystery of Dr. X, the system supports multi-format files, local RAG-based Q&A, Arabic translation, and ROUGE-based summarization — all without cloud dependencies.

This project demonstrates a production-ready RAG application for Alfresco using Spring AI.

Self-Reflective Question Answering for Biomedical Reasoning

All things Essential For my Learning Curve in LLM

The CMR system is a sophisticated memory-enhanced language model architecture that enables contextual memory reweaving for improved performance on long-context tasks.

Versatile LLM Tool Use (Function Calling) package for Laravel, compatible with all LLMs, enabling LLM to execute actual code functions (unlike LLMs' built-in capabilities).

AI search and chat for the LessWrong forum

Chat with your GitHub repository using RAG and Elasticsearch as a Vector Database

LLM with RAG example for querying URLs or PDFs with Ollama and Gradio/Flask

Mimicking Apple Intelligence, this project enables on-device Retrieval-Augmented Generation across all your Apple devices with zero cloud dependence.

A Retrieval-Augmented Generation (RAG) system using Vector and Graph Database

Local-first cognitive memory runtime for AI agents

RAG implentation in Golang with Milvus DB as example.

An adaptive chunking methodology for lecture videos using CLIP embeddings and SSIM to construct multimodal chunks for enhanced RAG performance.

RAG tool by Gemini File Search

learning generative models

RAG-Enhanced-NCERT-Tutor is an AI-powered tutor for NCERT curriculum, using Retrieval-Augmented Generation (RAG) to provide accurate and contextually relevant answers. It integrates retrieval techniques with a language model to enhance learning by offering detailed explanations and resources based on real-time queries from NCERT materials.