3.4 KiB
3.4 KiB
title, topic, data_type, complexity, point_count, source_language, user_language
| title | topic | data_type | complexity | point_count | source_language | user_language |
|---|---|---|---|---|---|---|
| llm-wiki-sync Circular Flow | technical | cycle | moderate | 7 | zh | en |
Main Topic
A cyclical knowledge management pipeline that transforms raw notes into structured wiki pages through continuous LLM-powered ingestion, extraction, and reuse.
Learning Objectives
After viewing this infographic, the viewer will understand:
- The continuous circular flow of llm-wiki-sync from raw notes to reusable knowledge
- The key extraction outputs: Summary, Claims, Entities, Concepts, Connections
- How feedback and reuse complete the cycle back to new raw material
Target Audience
- Knowledge Level: Intermediate technical audience
- Context: Developers and knowledge workers interested in AI-powered knowledge management
- Expectations: Clear understanding of the llm-wiki-sync pipeline and its cyclical nature
Content Type Analysis
- Data Structure: Cyclic process with recurring steps
- Key Relationships: Raw → Ingest → Extract → Source Page → Graph/Site → Reuse → Raw (feedback loop)
- Visual Opportunities: Circular flow with nodes for each stage, arrows showing direction, center concept
Key Data Points (Verbatim)
Core Pipeline Steps
- Raw Note - Original document in raw/ folder
- Ingest - LLM analyzes and extracts structured information
- Extract - Summary, Claims, Quotes, Entities, Concepts, Connections
- Source Page - Structured wiki/sources/ page with frontmatter
- Graph & Site - graph.json and Quartz static site generation
- Reuse - Synthesize, query, create new content from structured knowledge
- Feedback Loop - New raw notes created from reused knowledge
Extraction Outputs
- Summary: 核心主题, 问题域, 方法/机制, 结论/价值
- Key Claims: Verifiable assertions extracted from text
- Key Entities: LaunchDarkly, HP, Christian Dior, etc.
- Key Concepts: RTO, RPO, Feature Flag, Kill Switch, Gradual Rollout
- Connections: depends_on, enables, provides relationships
Key Quotes
- "RTO is about speed: how fast you get back online. RPO is about data: how much you can afford to lose."
- "Deploy != Release. Feature flags change this. You can deploy code to production without releasing it to users."
Layout × Style Signals
- Content type: cycle → circular-flow
- Tone: technical educational → chalkboard
- Audience: developers → clear, legible, professional
- Complexity: moderate → balanced density with clear visual hierarchy
Design Instructions (from user input)
- Layout: circular-flow (NOT linear - must emphasize recurring cycle)
- Style: chalkboard (dark background, hand-drawn chalk accents)
- Aspect: 16:9 landscape
- Language: English
- Circular flow showing: raw note -> ingest -> extract -> source page -> graph/static site -> reuse/feedback -> knowledge base
- Include core extraction outputs as recurring nodes/callouts
- Keep text concise and legible
- Dark chalkboard background with hand-drawn chalk accents
- Avoid clutter, make cycle visually clear and publication-ready
Recommended Combinations
- circular-flow + chalkboard (Recommended): Perfect match for cycle/process content with chalkboard aesthetic
- hub-spoke + technical-schematic: For emphasizing central concepts with technical precision
- bento-grid + craft-handmade: For multiple topic overview with friendly handmade feel