"""Use EDEN through the local training engine instead of Transformers.

This loads a checkpoint produced by the EDEN trainer (a .pt file) and runs the
same enhancement pipeline used during development. Set EDEN_HOME so the engine
can find the tokenizer under $EDEN_HOME/eden_system/data/tokenizer.json.

Run from the repository root:

    EDEN_HOME=/path/to/workspace python examples/use_locally.py /path/to/best.pt
"""

import os
import sys
from pathlib import Path

# Make the repository root importable when running this script directly.
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from eden import enhance_text, load_model_for_inference

checkpoint = Path(sys.argv[1]) if len(sys.argv) > 1 else None
model, tokenizer, config, device = load_model_for_inference(checkpoint, force_cpu=True)

for rough in [
    "i relly wnt this sentance to sound more profesional",
    "their are alot of reasons why this dont work proper",
]:
    print("rough   :", rough)
    print("polished:", enhance_text(rough, model, tokenizer, config, device))
    print()