A modular graph-based Retrieval-Augmented Generation (RAG) system

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry

Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

The PHP Agentic Framework to build production-ready AI driven applications. Connect components (LLMs, vector DBs, memory) to agents that can interact with your data. With its modular architecture it's best suited for building RAG, multi-agent workflows, or business process automations.

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

A modular RAG (Retrieval-Augmented Generation) system with MCP Server architecture. Using Skill to make AI follow each step of the spec and complete the code 100% by AI.

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

An easy-to-use framework for modular RAG

HiGoalVita is a modular, layered, production ready AI RAG suite.

An open source, modular, lightweight, and extensible RAG application stack, designed for anyone and everyone.

A modular, skill-based autonomous Security Operations Center (SOC) agent that monitors OpenSearch/Elasticsearch data, builds RAG-based behavioral memory, and validates real-time anomalies using LLMs.

ARAGOG- Advanced RAG Output Grading. Exploring and comparing various Retrieval-Augmented Generation (RAG) techniques on AI research papers dataset. Includes modular code for easy experimentation and reusability.

A modular Python framework implementing the Model Context Protocol (MCP). It features a standardized client-server architecture over StdIO, integrating LLMs with external tools, real-time weather data fetching, and an advanced RAG (Retrieval-Augmented Generation) system.

Samples showing architectural patterns for Modular RAG using Spring AI and Ollama.

Hector RAG is a modular RAG framework built on PostgreSQL, offering advanced retrieval methods and fusion techniques for AI-driven applications.

This project implements the "Modular RAG" framework using Haystack & Hypster

A GCP native, modular, parallelized Graph RAG implementation.

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

Webis is a modular, plugin-based AI data pipeline that supports data acquisition, cleaning, structured extraction, and RAG generation, solving the upstream supply problem for AI applications.

Scalable Agentic RAG system using Pydantic AI, FastAPI & pgvector. Modular, production-ready foundation for document-based AI apps

A modular framework for building scalable Retrieval-Augmented Generation (RAG) applications. This repository provides a clean separation of concerns, moving beyond simple scripts into a robust, factory-based architecture that supports multiple LLM providers, advanced text processing, and scalable vector storage.

A Kotlin-first LLM toolkit offering unified API for AI models (OpenAI, HuggingFace, DeepSeek, custom) and modular data storage. Features agent-enabled architecture with async RAG capabilities and zero boilerplate.

RAGSkeleton: A foundational, modular framework for building customizable Retrieval-Augmented Generation (RAG) systems across any domain.

A modular, multilingual, and multimodal Retrieval-Augmented Generation (RAG) system tailored for the financial analysis of Public Investment Fund (PIF) annual reports.

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

Nucleus is a modular Rust library for building advanced local AI tools and applications, built-in RAG for private documents, and an extensible plugin system for custom workflows.​

Real AI use cases focused on backend automation, agent-based workflows, RAG pipelines, and system-level integrations using Python, Make, n8n, and local LLMs. Designed to support AI-first product thinking through executable, modular examples built for real systems.

A clean, modular implementation of an Agentic RAG (Retrieval-Augmented Generation) system built with a production-ready architecture.