# PyInstaller spec — GUI V6 (build-prep G3-D).
#
# Produit `Anonymisation.exe` (V6), source de l'installateur Inno
# `installer/Anonymisation.iss` qui génère la cible finale `Anonymisation-Setup.exe`.
#
# Entrée directe : Pseudonymisation_Gui_V6.py (expose main() + --self-test).
# Ne construit AUCUN artefact ici : la génération réelle se fait sur Windows.

import os
from pathlib import Path


block_cipher = None

project_dir = Path(globals().get("SPECPATH", os.getcwd())).resolve()


def _data_entry(relative_path: str, target_dir: str | None = None):
    src = project_dir / relative_path
    if not src.exists():
        return None
    return (str(src), target_dir or relative_path)


datas = []
for relative_path, target_dir in [
    ("config", "config"),
    ("data/bdpm", "data/bdpm"),
    ("data/finess", "data/finess"),
    ("data/insee", "data/insee"),
    ("models/camembert-bio-deid/onnx", "models/camembert-bio-deid/onnx"),
    ("detectors", "detectors"),
    ("scripts", "scripts"),
    ("assets", "assets"),
]:
    entry = _data_entry(relative_path, target_dir)
    if entry is not None:
        datas.append(entry)

for relative_path in [
    "data/stopwords_manuels.txt",
    "data/villes_blacklist.txt",
    "data/dpi_labels_blacklist.txt",
    "data/companion_blacklist.txt",
]:
    entry = _data_entry(relative_path, "data")
    if entry is not None:
        datas.append(entry)

onnxtr_cache_dir = Path(os.environ.get("ONNXTR_CACHE_DIR", Path.home() / ".cache" / "onnxtr"))
required_onnxtr_weights = [
    "db_resnet50-69ba0015.onnx",
    "crnn_vgg16_bn-743599aa.onnx",
]
missing_onnxtr_weights = []
for filename in required_onnxtr_weights:
    src = onnxtr_cache_dir / "models" / filename
    if src.exists():
        datas.append((str(src), "models/onnxtr/models"))
    else:
        missing_onnxtr_weights.append(str(src))
if missing_onnxtr_weights:
    raise FileNotFoundError(
        "Poids OCR OnnxTR manquants pour le build frozen : "
        + ", ".join(missing_onnxtr_weights)
        + ". Précharger OnnxTR (lancer une OCR une fois) ou définir ONNXTR_CACHE_DIR avant PyInstaller."
    )


hiddenimports = [
    # Entrée + package GUI V6
    "Pseudonymisation_Gui_V6",
    "gui_v6",
    "gui_v6.app",
    "gui_v6.theme",
    "gui_v6.license_client",
    "gui_v6.license_store",
    "gui_v6.machine_id",
    "gui_v6.engine_bridge",
    "gui_v6.config_state",
    "gui_v6.processing_runner",
    "gui_v6.tabs",
    "gui_v6.tabs.tab_about",
    "gui_v6.tabs.tab_config",
    "gui_v6.tabs.tab_usage",
    # UI customtkinter
    "customtkinter",
    "darkdetect",
    # Réseau licence
    "requests",
    # Moteur + modules support (inchangés vs V5)
    "anonymizer_core_refactored_onnx",
    "admin_mode",
    "admin_rules",
    "config_defaults",
    "profile_defaults",
    "gui_batch_paths",
    "manual_masking",
    "pdf_mask_designer",
    "format_converter",
    "ner_manager_onnx",
    "camembert_ner_manager",
    "eds_pseudo_manager",
    "gliner_manager",
    "vlm_manager",
    "build_info",
    # OCR OnnxTR (ONNX Runtime, remplace docTR — sans torch ni doctr)
    "onnxtr",
    "onnxtr.io",
    "onnxtr.models",
    "onnxtr.models.detection",
    "onnxtr.models.recognition",
    "onnxtr.utils",
    "onnxtr.utils.data",
    # Dépendances transitives OnnxTR (hiddenimports défensifs vs omission PyInstaller)
    "pyclipper",
    "scipy.cluster.hierarchy",
    "scipy.special",
    "cv2",
    "edsnlp",
    "edsnlp.pipes",
    "edsnlp.pipes.ner",
    "edsnlp.pipes.ner.pseudo",
    "spacy",
    "spacy.lang.fr",
    "gliner",
    "onnxruntime",
    "transformers",
    "tokenizers",
    "pdfplumber",
    "fitz",
    "PIL",
    "yaml",
    "loguru",
    "regex",
    "optimum",
    "optimum.onnxruntime",
    "optimum.pipelines",
    "optimum.modeling_base",
    "optimum.exporters.onnx",
]


a = Analysis(
    [str(project_dir / "Pseudonymisation_Gui_V6.py")],
    pathex=[str(project_dir)],
    datas=datas,
    hiddenimports=hiddenimports,
    cipher=block_cipher,
    noarchive=False,
)
pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)

splash = Splash(
    str(project_dir / "assets" / "splash.png"),
    binaries=a.binaries,
    datas=a.datas,
    text_pos=(60, 195),
    text_size=10,
    text_color="white",
    minify_script=True,
    always_on_top=False,
)

exe = EXE(
    pyz,
    a.scripts,
    splash,
    splash.binaries,
    a.binaries,
    a.zipfiles,
    a.datas,
    [],
    name="Anonymisation",
    debug=False,
    strip=False,
    upx=False,
    console=False,
    icon=str(project_dir / "assets" / "icons" / "app.ico"),
)