Vedashriii/cognitive-load-predictor

1"""2verify_setup.py3Run this after pip install -r requirements.txt to confirm everything is working.4"""5 6print("Checking installations...\n")7checks = []8 9def check(name, fn):10    try:11        result = fn()12        checks.append((name, result, "OK"))13    except Exception as e:14        checks.append((name, str(e)[:40], "FAIL"))15 16check("torch",                  lambda: __import__("torch").__version__)17check("transformers",           lambda: __import__("transformers").__version__)18check("sklearn",                lambda: __import__("sklearn").__version__)19check("numpy",                  lambda: __import__("numpy").__version__)20check("pandas",                 lambda: __import__("pandas").__version__)21check("youtube-transcript-api", lambda: __import__("youtube_transcript_api") and "installed")22check("fastapi",                lambda: __import__("fastapi").__version__)23check("uvicorn",                lambda: __import__("uvicorn").__version__)24check("streamlit",              lambda: __import__("streamlit").__version__)25check("plotly",                 lambda: __import__("plotly").__version__)26check("requests",               lambda: __import__("requests").__version__)27check("tqdm",                   lambda: __import__("tqdm").__version__)28 29print(f"{'Library':<28} {'Version':<25} Status")30print("-" * 62)31for lib, version, status in checks:32    symbol = "✓" if status == "OK" else "✗"33    print(f"{symbol}  {lib:<26} {version:<25} {status}")34 35# PyTorch smoke test36print("\n--- PyTorch smoke test ---")37import torch38x = torch.tensor([1.0, 2.0, 3.0])39print(f"Tensor: {x}")40print(f"GPU (CUDA) available : {torch.cuda.is_available()}")41print(f"GPU (MPS)  available : {torch.backends.mps.is_available()}")42 43failed = [c for c in checks if c[2] == "FAIL"]44if failed:45    print(f"\n⚠  {len(failed)} package(s) failed. Run: pip install -r requirements.txt")46else:47    print("\n✓  All packages OK. Ready to run the project!")48