Comprehensive walkthrough covering schema design, prompt templates,
artifact population, pipeline usage, LLM integration, git history
tracking, metrics, and how to complete the remaining 31 chapters.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
All 3 stages (entities, mappings, analysis) auto-generated.
1m53s wall time, 9,478 tokens (real), ~$0.07 est. cost.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Auto-generated mappings and analysis via Claude Code CLI adapter.
Entities were already present from a previous session.
Stats: 5m04s wall time, ~51K estimated tokens, ~$0.35 estimated cost.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements markitect/llm/ package with concrete LLMAdapter implementations:
- OpenRouterAdapter: HTTP via urllib with retry/backoff on 429/5xx
- ClaudeCodeAdapter: subprocess-based Claude CLI with stdin piping
- Factory pattern: create_adapter("openrouter") or create_adapter("claude-code")
- API key resolution chain: constructor > env var > project-root key file
- 42 unit tests, 2 integration tests (gated on API key / CLI availability)
Also adds the infospace-with-history example with Wealth of Nations VSM
analysis pipeline, templates, schemas, source chapters, and processed
output for chapters 1-2. process_chapters.py now supports --provider
and --model flags for automatic LLM-driven processing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
