{"repo":"Lyra-stellAI/BYO-LLM-WIKI","free":true,"listed":false,"github":"https://github.com/Lyra-stellAI/BYO-LLM-WIKI","clone":"git clone https://github.com/Lyra-stellAI/BYO-LLM-WIKI.git","description":"Build your own LLM-native WIKI (knowledge library). Search, extract, summarize, Q&A with contextual RAG, layered knowledge graph, and reinforced memory. Importantly use selected context to automatically generate skills, empowered by Claude subagents + CodeAct pipeline and gated by human review. **Try Live Demo**: https://byo-wiki-demo.vercel.app","language":"Python","stars":258,"topics":["agentic-ai","autonomous-agents","llm-wiki","deep-agents","langchain","mcp","karpathy-llm-wiki","rag"],"license":null,"category":"ai-agents","readme_excerpt":"Build Your Own WIKI Turn the web, your files, and loose notes into a personal wiki that an LLM agent keeps coherent: search and summarize pages, ingest them into a contextual vector index for grounded, cited Q&A, and grow a layered knowledge graph that de-duplicates entities, builds topics, and writes synthesis pages. One Flask app — web UI, JSON API, and a runner.py CLI. Inspired by LangChain's llm-wiki deep-agents example, but it builds a private, on-disk library instead of syncing to a hub. Local-first : every store is plain JSON/SQLite under data/ ; cloud is opt-in. Features - Agentic knowledge graph — a deepagents agent (local filesystem backend, no cloud sandbox) saves passages, extracts entities and typed relations, canonicalizes duplicates, nests topics, and writes synthesis pages. - Contextual RAG — Anthropic-style contextual retrieval over a two-layer HNSW index (section summaries + chunks), with an LLM re-ranker (precision) or document-aware MMR (multi-doc recall). Answers are grounded and cited. - Memory — a cross-session store recalled before every answer and written back after (observations, 👍/👎, corrections that supersede stale notes); it improves from use, not just ingestion. - Agent skills — turn selected context into a reusable, evaluated skill via a sub-agent pipeline (understand → analyze → author → eval → gate → refine). Authored by the latest Claude in-process or via the Claude Code CLI as a subprocess , scored by a deterministic + rubric panel, and ga","default_branch":null,"files":null,"tree":[],"storefront":"/r/Lyra-stellAI","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Lyra-stellAI/BYO-LLM-WIKI/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}