rag-optimization

A deterministic, zero-dependency prompt-pruning layer for long-running LLM conversations — expires stale tool state, collapses duplicate context, and proves it never drops a fact a later turn still depends on.

RAG parameter sweep and evaluation toolkit — a practical way to test how different vector databases, embedding models, chunking strategies, and retrieval methods perform across your own RAG setup. Built to help you move from guesswork to evidence, with support for any vector database.

Biological code organization system with 1,029+ production-ready snippets - 95% token reduction for Claude/GPT with AI-powered discovery & offline packs

GraphRAG entity co-occurrence and relational knowledge subgraph extraction engine for agentic RAG

GraphRAG entity co-occurrence and relational knowledge subgraph extraction engine for agentic RAG

VecRecall 是一个进化版的 AI 长期记忆系统， v2.0 在纯向量检索之上，叠加 LLM 认知层（写入时自动抽取实体/关系/摘要/话题 + 语义去重）、时序知识图谱、遗忘曲线与主动蒸馏、多跳向量+图谱混合检索与静态加密，并把嵌入升级为「零依赖 subword 词法 + 多语言语义模型」双层。内置可复现评测集（21 组中英混合 query）中，召回率（R@5）达到 语义嵌入 100% / 零依赖词法 76.2%，为 AI Agent 提供更精准、更高效的上下文记忆支持。

3,300 practical techniques to cut LLM token usage by up to 90% — 300 core principles + 3,000 context-specific applications.

Find the questions your RAG pipeline will fail on, before your users do.

Notion RAG on notes from Notion repo. Using optimization for speed up. See READme for more

Official repository for AIO.CORE: The autonomous protocol for AI Optimization (AIO). Eliminates Semantic Drift and Context Fragmentation in LLMs through high-density vector indexing.

Official Data Node for the Tu Mapa IA technical ecosystem. Features machine-readable manifests (llms.txt) and RAG-optimized entity data for 530+ curated AI tools across 23 professional verticals. Managed under the FixGeo Protocol.

BetterRAG: Powerful RAG evaluation toolkit for LLMs. Measure, analyze, and optimize how your AI processes text chunks with precision metrics. Perfect for RAG systems, document processing, and embedding quality assessment.

Declarative Self-Improving Framework for Auto-Prompt Optimization and LLM Program Compilation.

Technical framework for Generative Engine Optimization (GEO) and Share of Synthesis (SoS). Defines the 6-node Immutable Graph for latent space indexing.

This repo contains the full pipeline for my Master's thesis at Yerevan State University (YSU), developed as part of the Data Science for Business master's program. The goal of this project is to build an end-to-end Retrieval-Augmented Generation (RAG) system using semantic search, LLMs, and fine-tuned embeddings on Armenian banks’ financial PDFs.

CPU-optimized RAG pipeline reducing latency 2.7× (247ms → 92ms). Implements caching, filtering, quantization for production. Complete with FastAPI, Docker, benchmarks, investor materials. The engineering showcase that sells itself.

Autonomous LLM Citation Graph & Generative Engine Optimization (GEO) Arbitrage Engine. Reverse-engineers Perplexity, ChatGPT Search, and Gemini RAG retrieval topologies via semantic entity triplification and eigenvector citation centrality.