rag-systems
Here are 21 public repositories matching this topic...
Language:All
Sort:Most stars
A modular framework for building and deploying Retrieval-Augmented Generation (RAG) systems with built-in evaluation and monitoring.
- Updated
Nov 26, 2025 - Python
Understand and build embedding models, focusing on word and sentence embeddings, dual encoder architectures. Learn to train embedding models using contrastive loss, implement them in semantic search and RAG systems.
- Updated
Aug 21, 2024 - Jupyter Notebook
🤖 Production-ready samples for building multi-modal AI agents that understand images, documents, videos, and text using Amazon Bedrock and Strands Agents. Features Claude integration, MCP tools, streaming responses, and enterprise-grade architecture.
- Updated
Nov 14, 2025 - Jupyter Notebook
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.
- Updated
Jun 15, 2025 - Python
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 🚀🐳.
- Updated
May 21, 2025 - Python
The course provides a comprehensive guide to optimizing retrieval systems in large-scale RAG applications. It covers tokenization, vector quantization, and search optimization techniques to enhance search quality, reduce memory usage, and balance performance in vector search systems.
- Updated
Dec 28, 2024 - Jupyter Notebook
This project implements a Retrieval-Augmented Generation (RAG) based chatbot designed to handle university-related queries using natural language understanding. It combines semantic search with generative AI to provide precise, context-aware answers to students, faculty, and visitors.
- Updated
Jun 22, 2025 - Jupyter Notebook
Experimenting with different kinds of RAGs Systems
- Updated
Aug 25, 2024 - Jupyter Notebook
Four Tests Standard (4TS) - Vendor-neutral specification for verifiable AI governance
- Updated
Feb 11, 2026 - Python
Training Data Generator for SPLADE Model Fine-tuning
- Updated
Apr 13, 2025 - Python
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.
- Updated
Aug 21, 2025 - Python
Advanced Retrieval-Augmented Generation system supporting multimodal document processing (text, tables, images) with multiple reasoning strategies and comprehensive evaluation framework.
- Updated
Jun 18, 2025 - Jupyter Notebook
Production-grade RAG system for Singapore government documents with OpenAI integration
- Updated
Aug 19, 2025 - Python
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).
- Updated
Apr 11, 2025 - Python
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.
- Updated
Sep 12, 2025 - Python
🚀 Complete AI Development Toolkit Template - Add RAG, MCP, and AI assistance to any project in 2 minutes
- Updated
Nov 9, 2025 - JavaScript
Decision-level observability for LLM pipelines, making system behavior explainable even when no outputs exist.
- Updated
Feb 3, 2026 - Python
⚡ Generate dynamic CRUD and Auth routes effortlessly with FastAPI Auto Routes for SQLModel—no repetitive boilerplate needed.
- Updated
Feb 20, 2026 - Python
Implements a Retrieval-Augmented Generation (RAG) system.
- Updated
Feb 6, 2025 - Jupyter Notebook
Improve this page
Add a description, image, and links to therag-systems topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with therag-systems topic, visit your repo's landing page and select "manage topics."