agentic-rag-retrieval

Cost saving Cognitive Architecture for AI Agents. Infinite Context. Perfect Recall. Zero Hallucinations.

A self-hosted omni-modal agentic retrieval platform that understands, searches, and explores documents, images, audio, and video through semantic routing, hybrid retrieval, adaptive agents, and traceable citations.

A progressive, script-based journey through Retrieval-Augmented Generation, from basic RAG to agentic, self-reflecting systems. Free-tier cloud stack, zero local model downloads.

📚 Stateful, self-correcting RAG research assistant built with LangGraph & Streamlit. Features hybrid search (dense + BM25), Cohere reranking, Tavily web/arXiv claim verification, session-isolated Qdrant storage, Guardrails AI, DeepEval testing, LangSmith tracing, /btw off-topic channel and AWS Fargate deployment configured with Terraform & CI/CD.

Agentic RAG platform for understanding GitHub repositories using Hybrid Retrieval, Event-Driven Architecture, and Generative AI.

This project is the broad level of AI Search on SQL which provides the visualisation as well from the response on your SQL database based on natural language query

An hybrid RAG system with BM25 + vector search, cross-encoder re-ranking, citation enforcement, and Ragas-based CI evaluation.

Agentic RAG system using LangGraph, FAISS, and Gradio with self-correcting retrieval