# LLM Wiki Monorepo

Agent-native knowledge compiler.
AI agents turn raw documents into persistent, cross-linked Markdown wikis.
No database. No API lock-in. One git clone.

What • Features • Quick Start • Architecture • Packages • Templates • Docs • Credits • License

--- ```bash pip install baissarienterprises-llm-wiki ``` ## What's New in v0.3.0 **Modular architecture.** The Python package has been reorganized from 28 flat modules into 10 domain-organized packages — `core/`, `quality/`, `ingest/`, `providers/`, `graph/`, `search/`, `ops/`, `wiki/`, `research/`, `contracts/`. Every module now answers: what domain owns this? What category within that domain? What specific function? **MCP server modularized.** The 1,287-line `index.ts` is gone. The MCP server is now 20 focused files: per-tool handlers under `tools/`, adapters under `adapters/`, project scanning under `projects/`, path safety under `security/`. All 14 tool names, schemas, and responses preserved byte-for-byte. **Shared TypeScript types.** Canonical `GraphNode`/`GraphEdge` types extracted into `packages/shared-types/` — a single source of truth for 3 packages that previously defined near-identical interfaces independently. **Documentation taxonomy.** Root-level docs reorganized into `docs/architecture/`, `docs/getting-started/`, `docs/reference/`, `docs/legal/`, `docs/release/`. README.md and AGENTS.md kept at root for PyPI packaging and AI agent auto-discovery. **7 pre-existing test failures eliminated.** OpenCode imports fixed. MCP integration tests now match the sidecar response schema. Link suggest optimization added. 472 tests pass (up from 445). ## What is this? LLM Wiki is a **production-grade knowledge engine** that turns raw documents into a living, cross-linked Markdown wiki. Instead of re-retrieving documents on every query (RAG), the system **incrementally builds and maintains** a persistent knowledge base. Sources are compiled once, kept current, and compound over time. It's everything needed to run a self-building wiki in one monorepo: a Python CLI package, an MCP server, a knowledge graph engine with community detection, a Chrome web clipper, a web viewer, an Obsidian plugin, and 20 domain templates — wired through an agent skill that works with any LLM. --- ## Features - **Two-Step Ingest** — LLM analyzes sources first, then generates structured wiki pages. SHA256 caching skips unchanged files. Streaming progress, multi-provider support (OpenAI, Anthropic, DeepSeek), and agent-native mode that needs zero API keys. - **Agent-Native Provider** — route ingest through Hermes, Claude Code, or Codex directly. No external API keys required when running inside an AI agent session.

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