Files
bookapp/ai_blueprint.md
Mike Wichers 1f01fedf00 Auto-commit: v2.9 — Fix background task hangs (OAuth headless guard, SQLite timeouts, log touch)
- ai/setup.py: Added threading import; OAuth block now detects background/headless
  threads and skips run_local_server to prevent indefinite blocking. Logs a clear
  warning and falls back to ADC for Vertex AI. Token file only written when creds
  are not None.
- web/tasks.py: All sqlite3.connect() calls now use timeout=30, check_same_thread=False.
  OperationalError on the initial status update is caught and logged via utils.log.
  generate_book_task now touches initial_log immediately so the UI polling endpoint
  always finds an existing file even if the worker crashes on the next line.
- ai_blueprint.md: Bumped to v2.9; Section 12.D sub-items 1-3 marked ; item 13
  added to summary.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-21 10:50:00 -05:00

20 KiB

AI Context Optimization Blueprint (v2.9)

This blueprint outlines architectural improvements for how AI context is managed during the writing process. The goal is to provide the AI (Claude/Gemini) with better, highly-targeted context upfront, which will dramatically improve first-draft quality and reduce the reliance on expensive, time-consuming quality checks and rewrites (currently up to 5 attempts).

0. Model Selection & Review (New Step)

Current Process: Model selection logic exists in ai/setup.py (which determines optimal models based on API queries and fallbacks to defaults like gemini-2.0-flash), and the models are instantiated in ai/models.py. The active selection is cached in data/model_cache.json and viewed via templates/system_status.html.

Actionable Review Steps: Every time a change is made to this blueprint or related files, the following steps must be completed to review the models, update the version, and ensure changes are saved properly:

  1. Check the System Status UI: Navigate to /system/status in the web application. This UI displays the "AI Model Selection" and "All Models Ranked".
  2. Verify Cache (data/model_cache.json): Check this file to see the currently cached models for the roles (logic, writer, artist).
  3. Review Selection Logic (ai/setup.py): Examine select_best_models() to understand the criteria and prompt used for model selection (e.g., favoring gemini-2.x over 1.5, using Flash for speed and Pro for complex reasoning).
  4. Force Refresh: Use the "Refresh & Optimize" button in the System Status UI or call ai.init_models(force=True) to force a re-evaluation of available models from the Google API and update the cache.
  5. Update Version & Commit: Ensure the ai_blueprint.md version is bumped and a git commit is made reflecting the changes.

1. Context Trimming & Relevance Filtering (The "Less is More" Approach)

Current Problem: story/writer.py injects the entire list of characters (chars_for_writer) into the prompt for every chapter. As the book grows, this wastes tokens, dilutes the AI's attention, and causes hallucinations where random characters appear in scenes they don't belong in.

Solution:

  • Dynamic Character Injection: Only inject characters who are explicitly mentioned in the chapter's scene_beats, plus the POV character. (Implemented v1.5.0)
  • RAG for Lore/Locations: Lightweight retrieval system implemented — chapter beats tagged with locations/key_items, lore index built via update_lore_index in bible_tracker.py, only relevant entries injected per chapter. (Implemented v2.5 — see Section 8)

2. Structured "Story So Far" (State Management)

Current Problem: prev_sum is likely a growing narrative blob. prev_content is truncated blindly to 2000 tokens, which might chop off the actual ending of the previous chapter (the most important part for continuity).

Solution:

  • Smart Truncation: Instead of truncating prev_content blindly, take the last 1000 tokens of the previous chapter, ensuring the immediate hand-off (where characters are standing, what they just said) is perfectly preserved. (Implemented v1.5.0 via utils.truncate_to_tokens tail logic)
  • Thread Tracking: Story So Far refactored into structured story_state.json via story/state.pyactive_threads, immediate_handoff (3 sentences), and resolved_threads; injected as structured prompt context in engine.py, replacing the raw summary blob. (Implemented v2.5 — see Section 9)

3. Pre-Flight Scene Expansion (Fixing it before writing)

Current Problem: The system relies heavily on evaluate_chapter_quality to catch bad pacing, missing beats, or "tell not show" errors. This causes loops of rewriting.

Solution:

  • Beat Expansion Step: Before sending the prompt to the model_writer, use an inexpensive, fast model to expand the scene_beats into a "Director's Treatment." This treatment explicitly outlines the sensory details, emotional shifts, and entry/exit staging for the chapter. (Implemented v2.0 — expand_beats_to_treatment in story/writer.py)

4. Enhanced Bible Tracker (Stateful World)

Current Problem: bible_tracker.py updates character clothing, descriptors, and speech styles, but does not track location states, time of day, or inventory/items.

Solution:

  • Expanded update_tracking to include current_location, time_of_day, and held_items. (Implemented v1.5.0)
  • This explicit "Scene State" is passed to the writer prompt so the AI doesn't have to guess if it's day or night, or if a character is still holding a specific artifact from two chapters ago. (Implemented v1.5.0)

5. UI/UX: Asynchronous Model Optimization (Refresh & Optimize)

Current Problem: Clicking "Refresh & Optimize" in templates/system_status.html submits a form that blocks the UI and results in a full page refresh. This creates a clunky, blocking experience.

Solution:

  • Frontend (templates/system_status.html): Converted the <form> submission into an asynchronous AJAX fetch() call with a spinner and disabled button state during processing. (Implemented v2.2)
  • Backend (web/routes/admin.py): Updated the optimize_models route to detect AJAX requests and return a JSON status response instead of performing a hard redirect. (Implemented v2.2)

6. Eliminating AI-Isms and Enforcing Genre Authenticity (v2.3)

Current Problem: Despite the existing style_guidelines.json and basic prompts, the AI writing often falls back on predictable phrases ("testament to," "shiver down spine," "a sense of") and lacks true human-like voice, especially failing to deeply adapt to specific genre conventions.

Solution & Implementation Plan:

  1. Genre-Specific Instructions: story/writer.py now calls get_genre_instructions(genre) to inject genre-tailored mandates (Thriller, Romance, Fantasy, Sci-Fi, Horror, Historical, General Fiction) into every draft prompt. (Implemented v2.3)
  2. Deep POV Mandate: The draft prompt in story/writer.py includes a DEEP_POV_MANDATE block that explicitly bans summary mode and all filter words, with concrete rewrite examples. (Implemented v2.3)
  3. Prose Filter Enhancements: The default ai_isms list in story/style_persona.py expanded from 12 to 33+ banned phrases. (Implemented v2.3)
  4. Enforce Show, Don't Tell via Evaluation: story/editor.py evaluate_chapter_quality now includes a DEEP_POV_ENFORCEMENT block with automatic fail conditions for filter word density and summary mode. (Implemented v2.3)

7. Regular Maintenance of AI-Isms (Continuous Improvement) — v2.4

Current Problem: AI models evolve, and new overused phrases regularly emerge. The static list in data/style_guidelines.json will become outdated. The refresh_style_guidelines() function already exists in story/style_persona.py but has no UI or scheduled trigger.

Solution & Implementation Plan:

  1. Admin UI Trigger: Added "Refresh Style Rules" button to templates/system_status.html using the same async AJAX spinner pattern as "Refresh & Optimize". (Implemented v2.4)
  2. Backend Route: Added /admin/refresh-style-guidelines route in web/routes/admin.py that calls style_persona.refresh_style_guidelines(model_logic) and returns JSON status with counts. (Implemented v2.4)
  3. Logging: Route logs the updated counts to data/app.log via utils.log. (Implemented v2.4)

8. Lore & Location Context Retrieval (RAG-Lite) — v2.5

Current Problem: The remaining half of Section 1 — prev_sum and the style_block carry all world-building as a monolithic blob. Locations, artifacts, and lore details not relevant to the current chapter waste tokens and dilute the AI's focus, causing it to hallucinate setting details or ignore established world rules.

Solution & Implementation Plan:

  1. Tag Beats with Locations/Items: Chapter schema supports optional locations and key_items arrays. story/writer.py reads these from the chapter dict. (Implemented v2.5)
  2. Lore Index in Bible: Added update_lore_index(folder, chapter_text, current_lore) to story/bible_tracker.py. Index is stored in tracking_lore.json and loaded into tracking['lore']. (Implemented v2.5)
  3. Retrieval in write_chapter: story/writer.py matches chapter locations/key_items against the lore index and injects a LORE_CONTEXT block into the prompt. (Implemented v2.5)
  4. Fallback: If chapter has no locations/key_items or lore index is empty, lore_block is empty and behaviour is unchanged. (Implemented v2.5)
  5. Engine Wiring: cli/engine.py loads tracking_lore.json on resume, calls update_lore_index after each chapter, and saves to tracking_lore.json. (Implemented v2.5)

9. Structured "Story So Far" — Thread Tracking — v2.5

Current Problem: The remaining half of Section 2 — prev_sum is a growing unstructured narrative blob. As chapters accumulate, the AI receives an ever-longer wall of prose-summary as context, which dilutes attention, buries the most important recent state, and causes continuity drift.

Solution & Implementation Plan:

  1. Structured Summary Schema: New story/state.py module. After each chapter, update_story_state() uses model_logic to extract and save story_state.json with active_threads, immediate_handoff (exactly 3 sentences), and resolved_threads. (Implemented v2.5)
  2. Prompt Injection: cli/engine.py calls story_state.format_for_prompt(current_story_state, chapter_beats) before each write_chapter call. The formatted string replaces prev_sum as the context. Falls back to the raw summary blob if no structured state exists yet. (Implemented v2.5)
  3. State Update Step: cli/engine.py calls story_state.update_story_state() after each chapter is written and accepted, saving story_state.json in the book folder. (Implemented v2.5)
  4. Continuity Guard: format_for_prompt() always places IMMEDIATE STORY HANDOFF first, followed by ACTIVE PLOT THREADS. Resolved threads are only included if referenced in the next chapter's beats. (Implemented v2.5)

10. Consistency Report Quick Fix (v2.6)

Current Problem: The templates/consistency_report.html page displays issues found in the manuscript but does not provide a direct action to fix them. It only suggests using the "Read & Edit" or "Modify & Re-run" features.

Solution & Implementation Plan:

  1. Frontend Action: Added "Redo Book" form to templates/consistency_report.html footer with a text input for the revision instruction and a confirmation prompt on submit. (Implemented v2.6)
  2. Backend Route: Added /project/<run_id>/revise_book/<book_folder> route in web/routes/run.py. Route creates a new Run record and queues generate_book_task with the user's instruction as feedback and source_run_id pointing to the original run. The existing bible refinement logic in generate_book_task applies the instruction to the bible before regenerating. (Implemented v2.6)

11. Series Continuity & Book Number Awareness (v2.7)

Current Problem: The system generates books for a series, but the prompts in story/planner.py (specifically enrich and plan_structure) and the writing prompts do not explicitly pass the series_metadata (such as is_series, series_title, book_number, and total_books) to the LLM. The AI doesn't know if it's generating Book 1, Book 2, or Book 3, leading to inconsistent pacing and continuity across a series.

Solution & Implementation Plan:

  1. Planner Prompts Update: Modified enrich() and plan_structure() in story/planner.py to extract bp.get('series_metadata', {}) and inject a SERIES_CONTEXT block — "This is Book X of Y in the Z series" with position-aware guidance (Book 1 = establish, middle books = escalate, final book = resolve) — into the prompt when is_series is true. (Implemented v2.7)
  2. Writer Prompts Update: story/writer.py write_chapter() builds and injects the same SERIES_CONTEXT block into the chapter writing prompt and passes it as series_context to evaluate_chapter_quality() in story/editor.py. editor.py evaluate_chapter_quality() now accepts an optional series_context parameter and injects it into the evaluation METADATA so the editor scores arcs relative to the book's position in the series. (Implemented v2.7)

12. Infrastructure & UI Bug Fixes (v2.8)

Problems Found & Fixed:

A. API Timeout Hangs (Spinning Logs)

The Gemini SDK had no timeout configured on any network call, causing threads to hang indefinitely:

  • ai/models.py generate_content() had no timeout → runs spun forever on API errors.
  • ai/setup.py all three genai.list_models() calls had no timeout → model init could hang.
  • ai/models.py retry handler called init_models(force=True) — a second network call during an existing failure, cascading the hang.

Fixes Applied:

  1. ai/models.py: Added _GENERATION_TIMEOUT = 180 class variable; all generate_content() calls now merge request_options={"timeout": 180}. Removed init_models(force=True) from retry handler. (Implemented v2.8)
  2. ai/setup.py: Added _LIST_MODELS_TIMEOUT = {"timeout": 30} passed to all three genai.list_models() call sites (get_optimal_model, select_best_models, init_models). (Implemented v2.8)

B. Huey Consumer Never Started (Tasks Queued But Never Executed)

web/app.py started the Huey background consumer inside if __name__ == "__main__":, which only runs when the script is executed directly. Under flask run, gunicorn, or any WSGI runner the block is never reached — tasks were queued in queue.db but never processed.

  1. web/app.py: Moved Huey consumer start to module level with a Werkzeug reloader guard (WERKZEUG_RUN_MAIN) and a FLASK_TESTING guard to prevent duplicate/test-time consumers. Consumer runs as a daemon thread. (Implemented v2.8)

C. "Create New Book" Showing Nothing

Three bugs combined to produce a blank page or silent failure when creating a new project:

  1. templates/project_setup.html: {{ s.tropes|join(', ') }} and {{ s.formatting_rules|join(', ') }} raised Jinja2 UndefinedError when AI analysis failed and the fallback dict lacked those keys → 500 blank page. Fixed to {{ (s.tropes or [])|join(', ') }}. (Implemented v2.8)
  2. web/routes/project.py (project_setup_wizard): When model_logic was None, the route silently redirected to the dashboard with a flash the user missed. Now renders the setup form with a complete default suggestions dict (all fields populated, lists as []) and a visible "warning" flash so the user can fill in details manually. (Implemented v2.8)
  3. web/routes/project.py (create_project_final): planner.enrich() was called with the full project bible dict. enrich() reads bp.get('manual_instruction') from the top level (got 'A generic story' fallback — the real concept was in bible['books'][0]['manual_instruction']), and wrote enriched data into a new book_metadata key instead of the bible's books[0]. Fixed to build a proper per-book blueprint, call enrich, and merge characters, plot_beats, and structure_prompt back into the correct bible locations. (Implemented v2.8)

D. "Waiting for logs" / "Preparing environment" Background Task Hangs

The UI gets stuck indefinitely because the background Huey worker thread hangs before emitting the first "Starting Job" log, or fails to connect to the database.

Places that impact this and their fixes:

  1. OAuth Browser Prompt in Background Thread: ai/setup.py — Added import threading; the OAuth block now checks threading.current_thread() is not threading.main_thread(). If running headlessly, run_local_server is skipped, creds is set to None, and a clear warning is logged. Vertex AI falls back to ADC. Token is only written if creds is not None. (Implemented v2.9)

  2. SQLite Database Locking Timeout: web/tasks.py — All sqlite3.connect() calls now use timeout=30, check_same_thread=False. The initial status-update OperationalError is caught and logged via utils.log so it appears in the log file rather than silently disappearing. (Implemented v2.9)

  3. Missing Initial Log File Creation: web/tasks.py generate_book_task — The initial_log path is now open(…, 'a')-touched immediately after construction and before utils.set_log_file(), guaranteeing the file exists for UI polling even if the worker crashes on the very next line. (Implemented v2.9)

Summary of Actionable Changes for Implementation Mode:

  1. Modify writer.py to filter chars_for_writer based on characters named in beats. (Implemented in v1.5.0)
  2. Modify writer.py prev_content logic to extract the tail of the chapter, not a blind slice. (Implemented in v1.5.0 via utils.truncate_to_tokens tail logic)
  3. Update bible_tracker.py to track time of day and location states. (Implemented in v1.5.0)
  4. Add a pre-processing function to expand chapter beats into staging directions before generating the prose draft. (Implemented in v2.0 — expand_beats_to_treatment in story/writer.py)
  5. (v2.2) Update "Refresh & Optimize" action in UI to be an async fetch call with a processing flag instead of a full page reload, and update admin.py to handle JSON responses.
  6. (v2.3) Updated writing prompts and evaluation rubrics across story/writer.py, story/editor.py, and story/style_persona.py to aggressively filter AI-isms, enforce Deep POV via a non-negotiable mandate, add genre-specific writing instructions, and fail chapters that rely on "telling" rather than "showing" via filter-word density checks in the evaluator.
  7. (v2.4) Add "Refresh Style Rules" button to system_status.html and /admin/refresh-style-guidelines route in admin.py. (Implemented v2.4)
  8. (v2.5) Lore & Location RAG-Lite: update_lore_index in bible_tracker.py, tracking_lore.json, lore retrieval in writer.py, wired in engine.py. (Implemented v2.5)
  9. (v2.5) Structured Story State (Thread Tracking): new story/state.py, story_state.json, structured prompt context replacing raw summary blob in engine.py. (Implemented v2.5)
  10. (v2.6) "Redo Book" form in consistency_report.html + revise_book route in run.py that creates a new run with the instruction applied as bible feedback. (Implemented v2.6)
  11. (v2.7) Series Continuity Fix: series_metadata (is_series, series_title, book_number, total_books) injected as SERIES_CONTEXT into story/planner.py (enrich, plan_structure), story/writer.py (write_chapter), and story/editor.py (evaluate_chapter_quality) prompts with position-aware guidance per book number. (Implemented v2.7)
  12. (v2.8) Infrastructure & UI Bug Fixes: API timeouts (180s generation, 30s list_models) in ai/models.py + ai/setup.py; Huey consumer moved to module level with reloader guard in web/app.py; Jinja2 UndefinedError fix for tropes/formatting_rules in project_setup.html; project_setup_wizard now renders form instead of silent redirect when models fail; create_project_final enrich() call fixed to use correct per-book blueprint structure. (Implemented v2.8)
  13. (v2.9) Background Task Hang Fixes: OAuth headless guard in ai/setup.py (skips run_local_server in non-main threads, logs warning, falls back to ADC); SQLite timeout=30, check_same_thread=False on all connections in web/tasks.py; initial log file touched immediately in generate_book_task so UI polling never sees an empty/missing file. (Implemented v2.9)