#!/usr/bin/env python3 """ wash_mj_heroes.py — Wash MJ hero images through NBP for photorealistic conversion. ADR-M05: MJ illustrations need "washing" to strip stylized textures and convert to photorealistic rendering before they become permanent identity refs. Uses NBP (Gemini 3 Pro) at temperature 0.4 for tight adherence to facial structure. JT must approve washed versions before they replace originals. Usage: python -m tools.wash_mj_heroes --dry-run python -m tools.wash_mj_heroes --character JINX --input path/to/mj_hero.png --project tartarus python -m tools.wash_mj_heroes --character JINX --input path/to/mj_hero.png """ import argparse import logging import os import sys from pathlib import Path from typing import Optional sys.path.insert(0, str(Path(__file__).parent.parent)) from recoil.core.paths import PIPELINE_ROOT # noqa: F401 from recoil.core.model_profiles import get_model from recoil.core.prompt_config import get_constant NBP_MODEL = get_model("production", "image") NBP_COST = 0.134 def _build_wash_prompt() -> str: """Build the MJ wash prompt from prompt_config casting constants.""" camera = get_constant("casting", "casting_camera") background = get_constant("casting", "casting_background") texture = get_constant("casting", "casting_texture_human") anti_airbrush = get_constant("casting", "casting_anti_airbrush") return ( f"Diegetic frame: {texture} Recreate this exact " f"person's facial structure, haircut, and features perfectly. " f"Photographic reality, {camera} lens, {background}. " f"{anti_airbrush} Render as a living human actor standing " f"on a movie set with cinematic lighting." ) logger = logging.getLogger("starsend.wash_mj_heroes") def wash_hero( character: str, input_path: Path, dry_run: bool = False, ) -> Optional[dict]: """Wash a single MJ hero image through NBP. Args: character: Character ID (e.g. JINX). input_path: Path to MJ hero image. dry_run: If True, show prompt without API call. Returns: Dict with {character, input, output, cost} or None on failure. """ if not input_path.exists(): logger.error(f"Input image not found: {input_path}") return None # Output goes alongside the original with _washed suffix stem = input_path.stem ext = input_path.suffix output_path = input_path.parent / f"{stem}_washed{ext}" if output_path.exists(): logger.info(f" Washed version already exists: {output_path}") return {"character": character, "input": str(input_path), "output": str(output_path), "cost": 0} if dry_run: logger.info(f" [DRY RUN] {character}: Would wash {input_path.name}") logger.info(f" [DRY RUN] Prompt: {_build_wash_prompt()[:100]}...") logger.info(f" [DRY RUN] Output: {output_path}") return {"character": character, "input": str(input_path), "output": None, "cost": 0} # Call NBP with MJ image + wash prompt washed_bytes = _generate_nbp_wash(input_path) if washed_bytes is None: logger.error(f" Wash failed for {character}") return None output_path.write_bytes(washed_bytes) logger.info(f" Washed: {output_path} ({len(washed_bytes) / 1024:.0f} KB)") logger.info(f" ** JT must approve before this becomes a permanent identity ref **") return { "character": character, "input": str(input_path), "output": str(output_path), "cost": NBP_COST, } def _generate_nbp_wash(input_path: Path) -> Optional[bytes]: """Generate washed version via NBP at temperature 0.4.""" try: from google import genai from google.genai import types except ImportError: logger.error("google-genai SDK not installed") return None api_key = os.environ.get("GEMINI_API_KEY") or os.environ.get("GOOGLE_API_KEY") if not api_key: logger.error("GEMINI_API_KEY not set") return None client = genai.Client(api_key=api_key) # Load MJ hero image image_bytes = input_path.read_bytes() mime = "image/jpeg" if input_path.suffix.lower() in (".jpg", ".jpeg") else "image/png" parts = [ types.Part.from_bytes(data=image_bytes, mime_type=mime), types.Part(text="[CHARACTER REFERENCE — RECREATE EXACTLY]"), types.Part(text=_build_wash_prompt()), ] try: response = client.models.generate_content( model=NBP_MODEL, contents=parts, config=types.GenerateContentConfig( temperature=0.4, # Low temp for tight adherence response_modalities=["IMAGE", "TEXT"], image_config=types.ImageConfig( aspect_ratio="9:16", ), ), ) except Exception as e: logger.error(f"NBP API error: {e}") return None if response and response.candidates: for candidate in response.candidates: if candidate.content and candidate.content.parts: for part in candidate.content.parts: if hasattr(part, "inline_data") and part.inline_data: return part.inline_data.data return None def main(): parser = argparse.ArgumentParser( description="Wash MJ hero images through NBP for photorealistic conversion (ADR-M05)" ) parser.add_argument("--character", required=False, help="Character ID (e.g. JINX)") parser.add_argument("--input", required=False, help="Path to MJ hero image") parser.add_argument("--project", default=None, help="Project name") parser.add_argument("--dry-run", action="store_true") args = parser.parse_args() logging.basicConfig(level=logging.INFO, format="%(asctime)s %(message)s", datefmt="%H:%M:%S") if args.character and args.input: result = wash_hero( character=args.character, input_path=Path(args.input).expanduser(), dry_run=args.dry_run, ) if result: cost = result.get("cost", 0) print(f"\nDone: {result.get('output', '(dry run)')}, ${cost:.3f}") else: print("\nFailed.") sys.exit(1) else: if args.dry_run: print("[DRY RUN] No --character or --input specified.") print("Usage: python -m tools.wash_mj_heroes --character JINX --input path/to/hero.png") print("Would wash MJ illustrations → photorealistic via NBP ($0.134/image)") else: parser.print_help() if __name__ == "__main__": main()