#!/usr/bin/env python3
"""Small, fully synthetic vision smoke test for the isolated A/B servers."""
import argparse
import base64
import json
import pathlib
import time

from measure import request


def main():
    p = argparse.ArgumentParser()
    p.add_argument("--base", required=True)
    p.add_argument("--model", required=True)
    p.add_argument("--output", type=pathlib.Path, required=True)
    p.add_argument("--go", action="store_true")
    args = p.parse_args()
    if not args.go:
        p.error("Inference requires explicit --go")
    image = pathlib.Path(__file__).with_name("assets") / "vision-fixture.png"
    url = "data:image/png;base64," + base64.b64encode(image.read_bytes()).decode("ascii")
    prompt = "Was ist links und was ist rechts im Bild? Nenne Form und Farbe beider Objekte."
    payload = {"model": args.model, "stream": False, "temperature": 0,
               "reasoning_effort": "none", "max_tokens": 512,
               "messages": [{"role": "user", "content": [
                   {"type": "text", "text": prompt},
                   {"type": "image_url", "image_url": {"url": url}}]}]}
    result = {"model": args.model, "prompt": prompt, "expected":
              "Links ein roter Kreis, rechts ein blaues Quadrat.",
              "started": time.time(), "response": request(args.base, None, payload)}
    args.output.parent.mkdir(parents=True, exist_ok=True)
    args.output.write_text(json.dumps(result, ensure_ascii=False, indent=2) + "\n")
    print(result["response"]["content"])


if __name__ == "__main__":
    main()