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

VecRecall 是一个改进版的 AI 长期记忆系统。它基于对原版 MemPalace 的深度分析重新构建，核心设计理念是将“信息检索”与“信息组织”彻底解耦。 通过纯向量检索路径和独立的 SQLite UI 层，VecRecall 在保持灵活组织的同时，将召回率（R@5）从原版的 84% 提升至 96.6%+，为 AI Agent 提供更精准、更高效的上下文记忆支持。

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.

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.

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.