Ziran LLM Wiki

Build deep topic knowledge bases through conversational AI, based on Karpathy's LLM Wiki methodology. Like tending a digital garden, your wiki grows naturally through dialogue — and Feynman learning verifies that you actually understand what you know.

Features

• Conversational knowledge ingestion — chat with AI to ingest raw materials and extract atomic knowledge points automatically
• Structured knowledge base — auto-creates topic directories with index pages, knowledge pages, organization profiles, and changelogs
• Three core workflows — Ingest (process raw materials), Query (search knowledge), Lint (quality check & maintenance)
• Smart indexing — automatically updates cross-references, keyword indexes, and relationship graphs when knowledge is created
• Previewed batch ingestion — scan multiple raw files, review the plan, then explicitly confirm execution; persisted batches recover after restart
• Time-scoped batch planning — ingest only files added or changed today / this week / this month, or cap a batch to the configured size (default 20), instead of re-planning the whole library
• Content deduplication — file fingerprints skip unchanged materials; "already ingested" history is tracked so you never process the same file twice
• Open files from chat — say "打开能力圈" and the matching knowledge page opens directly in Obsidian
• Feynman learning coach — explain a topic by voice or text and verify each claim against knowledge-base evidence
• Pluggable transcription — Groq, local Whisper, Cloudflare Workers AI, Google Speech-to-Text, or a custom OpenAI-compatible endpoint
• Memory & context — AI retains long-term memory, user preferences, and work logs across sessions
• Conflict tracking — detects and records knowledge conflicts instead of overwriting existing content
• Multiple themes — Dark Blue, Warm Light, Obsidian Red, Lavender, Forest Green
• Privacy-aware — raw materials are read-only, page content is append-only, and audio retention is off by default

Requirements

• Obsidian v1.8.0+ (desktop)
• An OpenAI-compatible API (OpenAI, DeepSeek, SiliconFlow, Ollama, or any compatible endpoint)
• An API key for the provider you choose (the plugin itself is free and open source)

Installation

From GitHub Releases

1. Download main.js, manifest.json, and styles.css from the latest release.
2. Copy them to <vault>/.obsidian/plugins/ziran-llm-wiki/.
3. Enable Ziran LLM Wiki in Obsidian → Settings → Community plugins.

With BRAT (for testing)

1. Install the BRAT plugin.
2. Add iamxiaoming-gif/ziran-llm-wiki to the beta plugin list.
3. Reload Obsidian.

Getting Started

1. Open Settings → Ziran LLM Wiki and configure your model:
   • Provider (OpenAI compatible / DeepSeek / SiliconFlow / Ollama / ...)
   • API Base URL
   • API Key
   • Model name
2. Click the 💬 ribbon icon (or run the "打开 LLM Wiki 知识库助手" command) to open the assistant.
3. In the chat, say "初始化知识库" to create the knowledge base structure.
4. Put raw material files into 00-原始资料/ (grouped by category folders).
5. Say "摄取今天新增的资料" (ingest today's files), "批量摄取" (plan a batch), or "查询知识" (ask questions).

Batch Ingestion

• Planning is read-only: review the plan (batch ID, pending / skipped / changed / failed counts) and confirm before anything is processed.
• A batch processes up to the configured number of files per run (default 20), then pauses; say "继续摄取" to continue.
• Say "摄取今天 / 本周 / 本月的资料" and the plan only includes files modified in that window.
• Completed files are tracked by content fingerprint in <knowledge-base>/30-维护记录/摄取任务.json; unchanged files are skipped automatically.

Feynman Learning

1. Open the 🎓 Feynman view (ribbon icon or command).
2. Configure a transcription provider if you want voice explanations (Groq, local Whisper, Cloudflare Workers AI, Google Speech-to-Text, or a custom OpenAI-compatible endpoint).
3. Explain a topic aloud or in text; each claim is checked against knowledge-base evidence and you get a learning report.

Safety Rules

The plugin enforces strict safety rules to protect your knowledge:

• Read-only raw materials — 00-原始资料/ is never modified, overwritten, or deleted
• Atomic knowledge points — each concept gets its own page
• Append-only pages — existing content can only be extended, never replaced
• Conflict recording — contradictions are logged, not silently resolved

Development

npm install
npm run build   # outputs main.js

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License

MIT © iamxiaoming-gif