L88 – An Agentic Local RAG Knowledge Engine (Looking for Feedback & Contributors)

Hi everyone 👋 I recently built L88 , an experimental agentic RAG (Retrieval-Augmented Generation) knowledge engine designed to run locally and explore structured AI reasoning pipelines. The project focuses on combining retrieval systems, LLM orchestration, and modern web architecture into a unified platform for querying and interacting with knowledge. GitHub Repository: https://github.com/Hundred-Trillion/L88-Full What the Project Does L88 allows users to upload and interact with knowledge sources using a multi-step AI reasoning pipeline. Instead of a simple prompt → response system, the project uses a structured workflow where queries pass through multiple stages before generating an answer. This makes the system more flexible for experimenting with agentic AI workflows and retrieval-based reasoning. Core Idea The goal of the project is to experiment with a multi-stage RAG pipeline built with modern tooling. The system orchestrates different reasoning steps such as routing, query anal