repo for using LLMs as a librarian to classify documents and extract type-specific metadata from them before filing them into an OpenSearch database and a vector store run by RAGatouille/Byaldi using a Flask server I wrote.

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A chatbot that recommends books based on the user’s interests, using RAG over ChromaDB. It responds via OpenAI GPT, can read the recommendation/summary in a specific voice (text-to-speech, TTS), supports Dark/Light/Custom themes, and can generate a representative image for the book.

Librarian is a MCP Server that allows any LLM with a compatible MCP client to query for information on Wikipedia

Librarian is a RAG-assisted LLM application that allows any user to query their own documents at large scale and low cost.

Librarian AI — модульный агент знаний с поддержкой GPT, Yandex, DeepSeek и локальных LLM. Извлекает информацию из текстов и документов, строит графы знаний, поддерживает CLI, Web, Telegram. Подходит для OSINT, юристов, аналитиков и автотренировки моделей.

LLM Librarian

Your LLM librarian

A simple app that recommends books based on user input

Use an LLM to organize ebooks

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knowledge-base manager, data conversationalist

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A powerful and flexible command-line tool to automatically organize and manage your ebook collection using an Ollama LLM and python.

An LLM based personal librarian

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LLM Wiki Agents — classification, librarian, lint agents using codebridge

Ghost Librarian — ultra-lightweight local-LLM RAG engine with Context Distillation

A LLM powered librarian that responsibly manages a library for Hackerspace members

An AI librarian project using large language models (LLMs) to provide accurate Q&A responses

Karpathy LLM Knowledge Base as an OpenClaw agent skill — active librarian loop for AI agents

LLM-Wiki: A self-evolving personal knowledge base pattern. Unlike RAG, it uses LLMs to incrementally build and maintain a persistent, interlinked Markdown wiki. The LLM is the librarian; Obsidian is the IDE; the Wiki is the codebase.

# LLM Wiki: Project Specification This repository contains the reference implementation of the **LLM-Wiki Pattern**. It is a system for building self-governing, compounding knowledge bases where the LLM serves as the Librarian and the human as the Architect.

An AI-powered voice librarian that listens to a user, finds relevant books from a local database using LLM-generated SQL, and replies with spoken recommendations.