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4 Commits

Author SHA1 Message Date
Mike Wichers
d75186cb29 Auto-commit: v2.7 Series Continuity & Book Number Awareness 
- story/planner.py: enrich() and plan_structure() now extract series_metadata
  and inject a SERIES_CONTEXT block (Book X of Y in series Z, with position-aware
  guidance) into prompts when is_series is true.
- story/writer.py: write_chapter() builds and injects the same SERIES_CONTEXT
  into the chapter draft prompt; passes series_context to evaluate_chapter_quality().
- story/editor.py: evaluate_chapter_quality() accepts optional series_context
  parameter and injects it into METADATA so arc pacing is evaluated relative to
  the book's position in the series.
- ai_blueprint.md: Section 11 marked complete (v2.7), summary updated.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-21 01:51:35 -05:00
Mike Wichers
b1bce1eb55 Blueprint v2.3: AI-isms filter, Deep POV mandate, genre-specific writing rules 
- story/style_persona.py: Expanded default ai_isms list with 20+ modern AI phrases
  (delved, mined, neon-lit, bustling, a wave of, etched in, etc.) and added
  filter_words (wondered, seemed, appeared, watched, observed, sensed)
- story/editor.py: Stricter evaluate_chapter_quality rubric — added
  DEEP_POV_ENFORCEMENT block with automatic fail conditions for filter word
  density and summary mode; strengthened criterion 5 scoring thresholds
- story/writer.py: Added get_genre_instructions() helper with genre-specific
  mandates for Thriller, Romance, Fantasy, Sci-Fi, Horror, Historical, and
  General Fiction; added DEEP_POV_MANDATE block banning summary mode and
  filter words; expanded AVOID AI-ISMS banned phrase list

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-21 01:19:56 -05:00
Mike Wichers
db70ad81f7 Blueprint v1.0.4: Implemented AI Context Optimization & Token Management 
- core/utils.py: Added estimate_tokens(), truncate_to_tokens(), get_ai_cache(), set_ai_cache(), make_cache_key() utilities
- story/writer.py: Applied truncate_to_tokens() to prev_content (2000 tokens) and prev_sum (600 tokens) context injections
- story/editor.py: Applied truncate_to_tokens() to summary (1000t), last_chapter_text (800t), eval text (7500t), propagation contexts (2500t/3000t)
- web/routes/persona.py: Added MD5-keyed in-memory cache for persona analyze endpoint; truncated sample_text to 750 tokens
- ai/models.py: Added pre-dispatch payload size estimation with 30k-token warning threshold

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-20 23:30:39 -05:00
Mike Wichers
f7099cc3e4 v2.0.0: Modularize project into single-responsibility packages 
Replaced monolithic modules/ package with a clean architecture:

- core/       config.py, utils.py
- ai/         models.py (ResilientModel), setup.py (init_models)
- story/      planner.py, writer.py, editor.py, style_persona.py, bible_tracker.py
- marketing/  cover.py, blurb.py, fonts.py, assets.py
- export/     exporter.py
- web/        app.py (Flask factory), db.py, helpers.py, tasks.py, routes/{auth,project,run,persona,admin}.py
- cli/        engine.py (run_generation), wizard.py (BookWizard)

Flask routes split into 5 Blueprints; all templates updated with blueprint-
prefixed url_for() calls. Dockerfile and docker-compose updated to use
web.app entry point and new package paths.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-20 22:20:53 -05:00