- Fix evaluate dimensions to match template file:
definition_precision, source_grounding, domain_placement,
vsm_relevance, explanatory_value (was domain_relevance,
discipline_alignment, conceptual_clarity)
- Add VSM background context to evaluation prompt so LLM can
score vsm_relevance without macro injection
- Fix model_name bug: was sending literal "default" to API (HTTP 400)
- Refactor run_entity_evaluation to write files incrementally via
callback rather than all at once after the batch — long runs are
now resumable if interrupted
- Add incremental skip in CLI: entities with existing eval files
are skipped automatically on re-run (acts as resume)
- Add eval-summary command: reads all eval files, shows per-dimension
means, optionally writes per_entity_mean to metrics.yaml
- Fix record_check_results to merge rather than overwrite metrics.yaml
so per_entity_mean survives subsequent check runs
- Add per_entity_mean viability threshold (min: 3.5) to infospace.yaml
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- SourcePipeline: retry split_entities stage once when 0 entity delimiters
are found (free-tier models intermittently return short non-formatted
responses); save raw LLM response to <stage>-raw.md alongside prompts
- Return None (pause pipeline) rather than writing empty view file when
no entities found after max retries
- _http.py: wrap json.JSONDecodeError in LLMAPIError with body preview
- extract-entities.md: add explicit H2-heading format example to Output
Format section to prevent models from using inline "Section:" format
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Restructure entity storage from per-chapter subdirectories to a flat
canonical set in output/entities/. Each entity exists as a single file;
duplicates across chapters are detected by slug collision and skipped
(first occurrence wins). Chapter views use {{ include }} transclusion
to reference shared entity files.
Add @{existing_entities} macro to extract-entities template so the LLM
knows which entities already exist and focuses on genuinely new ones.
Refactor _call_llm() from _execute_llm() for callers that handle their
own file I/O. 41 unique entities from 4 chapters (2 duplicates removed).
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>
