A modular framework for building and deploying Retrieval-Augmented Generation (RAG) systems with built-in evaluation and monitoring.

Turn any LLM into a self-extending knowledge agent powered by a graph-structured memory - complete with PDF-to-graph ingestion, budget-aware optimisation, and dual-engine orchestration.

RAG Gateway Service 🚪🤖: FastAPI gateway that auto-detects query topics using OpenAI embeddings 🧠🔍 and routes requests to topic-specific RAG agents 🎯, with fallback support and Docker-ready 🚀🐳.

Four Tests Standard (4TS) - Vendor-neutral specification for verifiable AI governance

Training Data Generator for SPLADE Model Fine-tuning

This repository covers extensive tutorials on how to integrate LangSmith with LangChain with LangGraph to incorporate observability, monitoring, alerting, evaluation, etc. within complex LLM workflows and applications.

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).

Production-grade RAG system for Singapore government documents with OpenAI integration

A comprehensive Asset Administrative Shell (AAS) data modeling platform for Quality Infrastructure systems. Features AASX package processing, digital twin management, AI-powered analytics with RAG, and multi-format data transformation capabilities.

Decision-level observability for LLM pipelines, making system behavior explainable even when no outputs exist.

⚡ Generate dynamic CRUD and Auth routes effortlessly with FastAPI Auto Routes for SQLModel—no repetitive boilerplate needed.

AI_Security_Engineers_Roadmap