import json
import os


def seed_face_embeddings():
    """
    Script (Template) pour générer les embeddings Face-ReID (CCIP)
    pour tous les personnages du catalogue.
    """
    print("🚀 Initializing Face Embedding Pipeline (deepghs/ccip)...")

    # In a real environment, we would load the model
    # model_id = "deepghs/ccip"
    # processor = AutoProcessor.from_pretrained(model_id)
    # model = AutoModel.from_pretrained(model_id)

    data_path = "data/processed/filtered_characters.json"
    if not os.path.exists(data_path):
        print("❌ Character data not found.")
        return

    with open(data_path, "r", encoding="utf-8") as f:
        characters = json.load(f)

    print(f"🧬 Processing {len(characters)} characters...")

    # Simulation du traitement pour le prototype
    for char in characters[:50]:  # Limité pour l'exemple
        char["id"]
        img_url = char.get("image")

        if img_url:
            # logic: download img -> detect face -> embed face
            # embedding = model.get_embeddings(img)
            # embeddings_map[char_id] = embedding.tolist()
            pass

    # Save to artifacts
    output_path = "data/artifacts/latent_space_character_visual_vibe.json"
    # with open(output_path, 'w') as f:
    #    json.dump(embeddings_map, f)

    print(f"✅ Face latent space prepared at {output_path}")


if __name__ == "__main__":
    seed_face_embeddings()