#vector-database

Hands-on Generative AI: 15 RAG modules from document loaders to guardrails, plus Papeer — a research paper assistant with citations and claim verification. Also LangGraph workflows and LangSmith tracing.

Collaborative AI memory for engineering teams - share context across Claude Code, Cursor, and teammates

HermesClaw Zero‑Config Sidecar is a lightweight local vector‑memory engine for Hermes and OpenClaw. It runs as a zero‑config sidecar, providing fast embeddings, persistent memory, and instant retrieval for agents and MCP tools. Built for speed, simplicity, and full local control.

Multi-Agent AI Orchestrator 2026 🚀 | YAML, 6+ LLM Providers, ReAct & Swarm

Self-healing RAG on n8n with LLM-as-judge eval, drift detection, investigator agent, and canary A/B deploys.

A reference n8n workflow that turns a folder of business documents into a chat agent that only answers from those documents. Retrieval-augmented, grounded, with refusal when the answer is not in the indexed sources.

🧠 A persistent memory RAG chatbot that never forgets. Uses Phi-3-mini LLM, ChromaDB vector database, and Ebbinghaus memory decay curves.

Agente RAG conversacional sobre IA Generativa con Google Gemini, ChromaDB y LangGraph. Memoria por thread, interfaz Streamlit y base de conocimiento propia. Práctica final del Máster en Data Science e IA.

Chatbot developed during Tata Steel Summer Internship, uses live IoT Telemetry data for various machines and allows users to query and fetch details for the same.

AI-powered research assistant that enables semantic search, question answering, and citation-grounded insights from academic papers using RAG.

AI agent that answers questions about YouTube tutorials and your own codebase — available as a Chrome extension, desktop app, and web app.

Official n8n creator | Production-ready automation workflows: Agentic RAG, multi-KB AI agents, AI governance, and privacy-first local inference. Stack: Ollama · Supabase · LangChain · MCP · Docker · Gemini. fromus.ca/ai-builds

🧠 RepoMind — A RAG-powered chatbot that lets you ask natural-language questions about any GitHub repository, with answers grounded in the actual source code and cited by file & line number.

An AI-powered YouTube Q&A system that lets users chat with video content using RAG pipelines, LangChain, FastAPI, and vector search.

Chat with your PDF documents using RAG. Built with LangChain, FAISS vector store, Groq LLM, and Streamlit. Every answer cites its source.

Federal Acquisition Regulation Retrieval-Augmented Generation (RAG) Chatbot

🤖 An advanced, policy-compliant RAG-powered Internal Knowledge Assistant for TechNova. Built with LangChain, Chroma DB, and Llama 3.3 (Groq). Features strict source grounding, 100% retrieval precision, comprehensive factual citations, automated evaluation pipelines, and a dynamic multi-category Gradio chat interface. 🚀

Agente de RR. HH. con LangGraph, RAG, FAISS, Groq y Llama 3.3 para responder consultas internas, solicitar información adicional y generar tickets de soporte.

AI-powered career intelligence platform built with FastAPI, PostgreSQL, pgvector, and Ollama. Analyze resumes, identify skill gaps, generate learning roadmaps, prepare for interviews, and chat with an intelligent career assistant using Retrieval-Augmented Generation (RAG).

AI-powered PDF Question Answering Chatbot using RAG and Mistral AI

Pragmatic AI Engineering Skills Library for LLMs, RAG, Agents, MCP & Spring AI

Personalized AI assistant capable of handling automated conversations across WhatsApp and Gmail using LLM APIs, Retrieval-Augmented Generation (RAG), semantic search, conversation memory, and real-time information retrieval.

编程导航 2025 年 AI 开发实战新项目，基于 Spring Boot 3 + Java 21 + Spring AI 构建 AI 恋爱大师应用和 ReAct 模式自主规划智能体YuManus，覆盖 AI 大模型接入、Spring AI 核心特性、Prompt 工程和优化、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、AI Agent 开发、Cursor AI 工具等核心知识。用一套教程将程序员必知必会的 AI 技术一网打尽，帮你成为 AI 时代企业的香饽饽，给你的简历和求职大幅增加竞争力。

Production-grade multi-agent AI system with LangGraph supervisor pattern, RAG knowledge base (ChromaDB), and Anthropic Claude — routes queries between specialized triage, scheduling, and eligibility agents

Flowise-based multi-agent AI orchestration system using RAG, OpenAI embeddings, FAISS vector search, and sequential agent workflows for retrieval-grounded content generation and enterprise AI pipeline design.

RAG multi-agente con validación QA anti-alucinaciones (OpenAI + Pinecone + LangChain). Modo offline reproducible.

AI-powered Retrieval-Augmented Generation (RAG) chatbot built with n8n and Google Gemini. Supports PDF upload, semantic search, document question answering, and summarization using vector embeddings.

Production-grade RAG PDF Chatbot built with FastAPI, LangChain, OpenAI GPT-4o, and ChromaDB.

Hands-on implementation of Retrieval-Augmented Generation (RAG) using vector databases, embeddings, semantic search, and Anthropic Claude.

Educational project exploring deterministic RAG and tool-using AI agents with FastAPI, PostgreSQL, pgvector, and OpenAI.

AI-powered medical education system with LangGraph ReAct agent orchestrating 4 custom tools (hybrid RAG, PubMed API, medical calculator, web search). Features research mode for multi-source evidence synthesis. Built with LangChain, Pinecone, Google Gemini. 716 PubMed articles, 222 tests.

Hands-on Generative AI Engineering repository covering LLMs, Prompt Engineering, RAG, Vector Databases, Fine-Tuning, Multimodal AI, AI Agents, LLMOps, Evaluation, Deployment, and production-ready GenAI applications using OpenAI, Hugging Face, LangChain, LangGraph, and modern AI engineering practices.

Digital Garage Enterprise

AI-powered legacy code migration platform that transforms .NET (C#) applications into Java using LangChain, Milvus Vector Database, RAG, validation pipelines, security analysis, and automated project generation.

RAG-based legal AI assistant for grounded question answering over commercial law and policy documents.

Agentic AI framework that drafts FDA cybersecurity SRAs for connected medical devices. Vector DB + Graph DB + MCP + LangGraph pipeline, with human-in-the-loop review. Capstone project — reference device: PMx-100.

Telegram assistant with long-term semantic memory powered by Pinecone and OpenAI

Telegram-бот LARGE с векторной памятью Pinecone: RAG по маркетинговым тезисам Котлера и диджитала. OpenAI embeddings, семантический поиск, aiogram.

Generic, provider-agnostic RAG backend with verified citations. FastAPI + SSE; switchable LLMs (Ollama/Anthropic/OpenAI) and vector stores (Chroma/pgvector); evals, tracing, tests, Docker.