Blame for scripts/clone_login.py

#!/usr/bin/env python3
"""Thin CLI over demoprep_app.portal.login_clone — for local testing only.

The real path is the background job build_demo_from_brief starts for
demo_type="tse" (mcp_server.py), which calls the same clone_login(). This wrapper
runs capture + generation for one site and leaves everything on disk for review:

    python scripts/clone_login.py https://www.example.com --company "Example" \
        --use-case "Retail Sales" --out /tmp/clones/example

    <out>/capture/screen-*.png        the real site, as the model saw it
    <out>/clone/shots/*-render-*.png  the clone, rendered
    <out>/clone/app/                  a pristine template with the clone in place
                                      (cd there and `npx vite` to click through it)
    <out>/clone/result.json           rounds, tokens, timings, why it failed if it did

Needs ANTHROPIC_API_KEY (read from .env) and Playwright's Chromium
(`playwright install chromium`).
"""
from __future__ import annotations

import argparse
import sys
from pathlib import Path

REPO = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(REPO))

from dotenv import load_dotenv  # noqa: E402

from demoprep_app.portal.login_clone import clone_login  # noqa: E402


def main() -> None:
    ap = argparse.ArgumentParser(description="Clone a prospect homepage as a portal login page.")
    ap.add_argument("url")
    ap.add_argument("--company", required=True)
    ap.add_argument("--use-case", default="Analytics")
    ap.add_argument("--out", required=True, help="directory for the capture, renders and result")
    ap.add_argument("--model", default=None, help="defaults to CLONE_LOGIN_MODEL or DEFAULT_LLM_MODEL")
    args = ap.parse_args()
    load_dotenv(REPO / ".env")

    res = clone_login(args.url, args.company, args.use_case, args.out, model=args.model,
                      on_progress=lambda m: print(f"  {m}", flush=True))
    print(f"{'OK' if res.ok else 'NO CLONE'}  {res.reason}")
    print(f"  {res.seconds}s, {res.rounds} round(s), model {res.model}, tokens in {res.input_tokens} "
          f"(+{res.cache_read_tokens} cached read, {res.cache_write_tokens} cache write) / out {res.output_tokens}")
    for p in res.preview:
        print(f"  preview: {p}")
    sys.exit(0 if res.ok else 1)


if __name__ == "__main__":
    main()