ComfyUI-Ethanfel-Prompt-Builder/docs/prompt-architecture-improvement-plan.md

Prompt Architecture Improvement Plan

This is a working research note for organizing the prompt builder around the routing map in docs/prompt-pool-routing-map.md.

Current Branch Additions

The current branch adds two major surfaces:

• SxCP Krea2 Resolution Selector in __init__.py, with README notes.
• Expanded hardcore interaction/manual/action pools in categories/sexual_poses.json, categories/expression_composition_pools.json, prompt_builder.py, and krea_formatter.py.

The map audit currently sees:

• 15 sexual pose subcategories.
• 94 sexual pose item templates.
• 23 expression pools.
• 24 composition pools.
• A new Krea2 resolution node with width/height/API aspect outputs.

Architectural Finding

The project has a good functional map, but ownership is still mixed inside large files:

• prompt_builder.py owns selection, character resolution, role graph logic, camera adaptation, pair assembly, and some final string cleanup.
• krea_formatter.py owns metadata parsing, cast naturalization, sexual action rewriting, POV rewriting, clothing cleanup, camera preservation, fallback parsing, and final prose assembly.
• sdxl_formatter.py owns tag assembly and style/quality presets.
• caption_naturalizer.py owns training-caption prose.
• Category JSON files own scalable pool content, but Python still owns several compatibility and role-graph decisions.

The biggest maintainability risk is not the number of pools. The risk is that selection, semantic rewriting, and final text hygiene are too interleaved. When a prompt has wrong text, it is easy to patch the wrong layer.

First Refactor Boundary

Generic text hygiene now has one home:

• prompt_hygiene.py

It should only handle route-agnostic cleanup:

• whitespace and punctuation normalization;
• empty field-label removal;
• repeated trigger prefix cleanup;
• duplicate comma-list item removal;
• adjacent duplicate sentence cleanup;
• simple dangling connector cleanup.

It must not make semantic decisions such as sexual action positioning, POV geometry, clothing state, or model-specific tag weighting. Those stay in the route-specific owner. It also preserves ordinary words such as composition inside normal sentences; empty field-label cleanup is limited to standalone labels.

Shared hardcore phrase cleanup now has one home:

• hardcore_text_cleanup.py

It owns environment-anchor normalization used by both prompt generation and Krea formatting, including malformed surface joins and bed/sheet/couch anchors that should become model-neutral body-support language. It must stay route-neutral: no Krea prose, no SDXL tags, and no category selection logic.

Current integration points:

• prompt_builder.build_prompt
• prompt_builder.build_insta_of_pair
• krea_formatter.format_krea2_prompt
• sdxl_formatter.format_sdxl_prompt
• caption_naturalizer.naturalize_caption

Target Organization

Generation Layer

Owner: prompt_builder.py plus categories/*.json.

Keep here:

• category/subcategory/item selection;
• seed axis routing;
• character slot/profile resolution;
• scene/expression/composition pool selection;
• role graph creation from structured category axes;
• metadata row construction.

Move or isolate later:

• role graph generation for hardcore interaction categories into a dedicated module, for example hardcore_role_graphs.py;
• category-library loading and inheritance helpers into category_library.py.

Already isolated:

• camera-scene prose and coworking composition adaptation live in scene_camera_adapters.py; prompt_builder.py still owns camera config parsing and row mutation.
• shared hardcore environment-anchor cleanup lives in hardcore_text_cleanup.py and normalizes malformed pool joins before metadata reaches formatter routes.

Pair / Adapter Layer

Owner today: build_insta_of_pair.

Keep here:

• soft/hard row creation;
• continuity policy;
• softcore cast policy;
• pair-level camera routing;
• pair metadata shape.

Improve later:

• make a single pair metadata sanitizer that normalizes softcore_row, hardcore_row, pair prompts, negatives, captions, and camera fields;
• split pair assembly into small functions by phase: build_soft_row, build_hard_row, resolve_pair_camera, resolve_pair_clothing, assemble_pair_metadata.

Krea2 Formatter Path

Owner: krea_formatter.py.

Keep here:

• Krea prose style;
• Krea route orchestration;
• camera-scene preservation;
• fallback text parsing.

Already isolated:

• krea_cast.py owns cast descriptor parsing, cast prose, label joining, and natural label replacement for formatter routes.
• krea_clothing.py owns clothing-state cleanup and action-aware body-access wording for formatter routes.
• krea_action_context.py owns shared action-family predicates, axis context text, climax detection, and detail-density normalization used by action and POV formatter routes.
• krea_pov.py owns POV labels, POV label filtering, and POV camera/composition support text.
• krea_detail.py owns generic detail-clause splitting, deduping, joining, and density limiting for Krea action prose.
• krea_action_positions.py owns non-POV pose anchors, body-arrangement text, rear-entry detection, and action-position phrasing.
• krea_actions.py owns non-POV hardcore action sentence rewriting, item/detail cleanup, and climax detail cleanup.
• krea_pov_actions.py owns POV hardcore action sentence rewriting and first-person body geometry.

Improve later:

• split krea_actions.py by action family once the extracted module is stable;
• add route-level smoke fixtures for representative metadata rows;
• make krea_actions.hardcore_action_sentence dispatch by action family instead of long conditional chains.

SDXL Formatter Path

Owner: sdxl_formatter.py.

Keep here:

• trigger behavior;
• style and quality presets;
• tag ordering;
• weighted explicit tags;
• negative-prompt assembly.

Improve later:

• move presets into data dictionaries or JSON so adding styles does not require editing formatter logic;
• add formatter profiles for Pony, SDXL photo, and flat vector;
• make fallback cleanup use the shared field-label inventory.

Naturalizer Path

Owner: caption_naturalizer.py.

Keep here:

• natural sentence caption assembly;
• training-caption trigger behavior;
• style-tail policy.

Improve later:

• share more metadata readers with Krea without sharing Krea prose;
• add a caption_profile option for concise/dense LoRA caption styles.

Category JSON Path

Owner: categories/*.json.

Keep here:

• scalable prompt pool content;
• named scene/expression/composition pools;
• item templates and axes;
• direct category-specific wording.

Improve later:

• introduce optional family and action_type fields on item templates so Python filters do less keyword guessing;
• add formatter_hint fields only where needed, not globally;
• keep tools/prompt_map_audit.py passing; it now checks referenced expression/composition/scene pools and item-template axes.

Node / UI Path

Owner: __init__.py, loop_nodes.py, web/*.js.

Keep here:

• ComfyUI node input/output declarations;
• widget behavior;
• button actions;
• dynamic input slots.

Improve later:

• split large node classes into files by family;
• keep node display names, return names, and docs in sync through the audit helper;
• add small endpoint tests for profile/accumulator/index-switch routes.

Path-Specific Improvements

Prompt Builder

Near-term:

• Add final row hygiene already done through prompt_hygiene.py.
• Add a metadata smoke checker for representative rows through tools/prompt_smoke.py.
• Normalize every row with one function before JSON serialization.

Medium-term:

• Extract category loading and role graph logic.
• Convert keyword-heavy interaction filtering to template metadata.

Insta/OF Pair

Near-term:

• Normalize pair metadata with one helper.
• Confirm pair prompts, captions, and soft/hard rows carry the same sanitized scene/camera/clothing fields.
• Keep same-room pair continuity synchronized in both assembled prompt text and hardcore_row.scene_text; tools/prompt_smoke.py covers this drift case.

Medium-term:

• Make pair camera and clothing phases explicit subfunctions.
• Add smoke fixtures for same-cast, POV man, explicit nude, and different-camera modes.

Krea2

Near-term:

• Add final prose hygiene already done through prompt_hygiene.py.
• Add smoke coverage through tools/prompt_smoke.py for metadata-driven Krea2 formatting across built-in rows, hardcore rows, same-cast pairs, and POV pairs.
• Cover camera-scene preservation through tools/prompt_smoke.py for single rows, split soft/hard pair cameras, and POV camera-scene routing.
• Cover config-node routing through tools/prompt_smoke.py for category, cast, generation profile, seed lock, camera, location theme, and composition config.
• Cover close foreplay and POV penetration Krea routes so raw labels, invalid surface grammar, normal third-person camera text, and composition punctuation drift are caught.

Medium-term:

• Dispatch action rewriting by action family.
• Continue splitting remaining Krea semantic helpers into smaller modules.

SDXL

Near-term:

• Add final tag hygiene already done through prompt_hygiene.py.
• Add smoke tests for trigger preservation and duplicate tag removal through tools/prompt_smoke.py.

Medium-term:

• Make style/quality presets data-driven.

Naturalizer

Near-term:

• Add final prose hygiene already done through prompt_hygiene.py.
• Verify training captions keep trigger exactly once through tools/prompt_smoke.py.

Medium-term:

• Add caption profiles for training and browsing use cases.

Camera / Scene

Near-term:

• Keep Qwen/orbit as camera source.
• Keep scene-camera adapters scoped by location family.
• Use the memory note in /home/ethanfel/.codex/memories/scene-camera-system.md when editing POV.
• Keep scene_camera_adapters.py as the owner for location-aware camera prose; add new location families there one at a time.

Medium-term:

• Build new adapters one location family at a time.

Invariants To Preserve

• Metadata is the preferred formatter input.
• Prompt Builder should output structured rows even if raw prompt text is rough.
• Krea should fix prose and semantic action readability, not category selection.
• SDXL should produce tag-style output and preserve model triggers as requested.
• Naturalizer should output training-friendly captions without changing the selected content.
• Generic cleanup belongs in prompt_hygiene.py; semantic cleanup belongs in the owning route.

Recommended Next Passes

1. Split krea_actions.py by action family, using krea_cast.py as the pattern for stable import aliases and smoke coverage.
2. Split __init__.py node classes by family after behavior is covered by smoke checks.
3. Add metadata fields such as action_family / position_family to reduce keyword guessing in hardcore filters and formatter dispatch.