High-accuracy PDF-to-Markdown OCR API using LLMs with vision capabilities. Features parallel processing, batching, and auto-retry logic for scalable extraction.

A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents.

RAG boilerplate with semantic/propositional chunking, hybrid search (BM25 + dense), LLM reranking, query enhancement agents, CrewAI orchestration, Qdrant vector search, Redis/Mongo sessioning, Celery ingestion pipeline, Gradio UI, and an evaluation suite (Hit-Rate, MRR, hybrid configs).

A python module library that simplifies RAG through abstraction

The implementation of Test Time Diffusion paper by Google with some tweaks to run on 24gb gpu

AI travel planner with 7 specialized agents, RAG, and tool-calling. Built with CrewAI & LangChain. Generates personalized itineraries with flights, hotels, activities, and cultural tips. Production-ready Python codebase.

The Audited Context Generation (ACG) Protocol prevents AI hallucinations with a dual-layer system. The UGVP layer links every fact to a precise source for verification. The RSVP layer audits the AI's logical reasoning when combining facts. This creates a fully transparent, machine-auditable trail for both source and logical integrity.

An intelligent customer support system powered by LangGraph and LangChain that uses Retrieval-Augmented Generation (RAG) to provide accurate, context-aware responses to customer queries. Built with FastAPI, FAISS, and multi-stage validation for production-ready deployment.

Production-ready Chainlit RAG application with Pinecone pipeline offering all Groq and OpenAI Models, to chat with your documents.

Token-Oriented Object Notation (TOON) is an LLM-optimized data serialization format implemented in Python.

Advanced RAG Pipelines and Evaluation

When retrieval outperforms generation: Dense evidence retrieval for scalable fake news detection - LDK 2025

🛡️ Web3 Guardian is a comprehensive security suite for Web3 that combines browser extension and backend services to provide real-time transaction analysis, smart contract auditing, and risk assessment for decentralized applications (dApps).

A stateful AI agent framework powered by the Cognitive Lattice to solve complex tasks with persistent memory and reliable tool orchestration.

Demo LLM (RAG pipeline) web app running locally using docker-compose. LLM and embedding models are consumed as services from OpenAI.

Teaching Tool: Local RAG and LLM Chat over Logseq with LlamaIndex + Ollama + Chroma

Advanced RAG Pipelines optimized with DSPy

This repo is for advanced RAG systems, each branch will represent a project based on RAG.

Project Agora: An expert system for the Google ADK, powered by a hierarchical multi-agent framework to automate code generation, architecture, and Q&A.