2bc8c1b87d
Adapt typing/voice surfaces for iPad width and height, add the system globe key and last-input editing flow, harden host-only Rime deployment, and remove clipboard voice commands. Bump build to 61.
224 lines
8.4 KiB
Python
224 lines
8.4 KiB
Python
#!/usr/bin/env python3
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"""Replay complete production prompts against an explicit quality corpus.
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This is deliberately separate from XCTest:
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- XCTest protects deterministic prompt assembly and local fallbacks.
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- this script sends the *complete* system prompt and complete user payload to
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the configured LLM, then records objective contract checks plus every output
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for human quality review.
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It covers dictation polish: the user message is the user's outbound draft.
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Questions must stay questions and never be answered.
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Usage:
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python3 Scripts/llm_full_prompt_quality_eval.py --profile smoke
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python3 Scripts/llm_full_prompt_quality_eval.py --profile full --samples 2
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"""
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import argparse
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import concurrent.futures
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import hashlib
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import importlib.util
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import json
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import re
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import time
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from collections import Counter, defaultdict
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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FIXTURES = ROOT / "Scripts" / "fixtures" / "llm_quality_matrix.json"
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QUESTION_EVAL = ROOT / "Scripts" / "polish_question_guard_eval.py"
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def load_question_eval():
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spec = importlib.util.spec_from_file_location("question_eval", QUESTION_EVAL)
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if spec is None or spec.loader is None:
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raise SystemExit(f"Cannot load {QUESTION_EVAL}")
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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return module
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Q = load_question_eval()
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def is_english(text: str) -> bool:
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letters = len(re.findall(r"[A-Za-z]", text))
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cjk = len(re.findall(r"[\u3400-\u9fff]", text))
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return letters >= 12 and letters > cjk * 2
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def objective_checks(case: dict, output: str, protocol: str) -> list[str]:
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"""Checks only facts we can evaluate deterministically.
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Passing these checks means “no detected contract breach”, not “excellent
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writing”. The report deliberately keeps the raw output for a Cursor-agent
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and human sample review.
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"""
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failures: list[str] = []
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normalized = output.strip()
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if not normalized:
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return ["empty_output"]
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if case.get("must_remain_question") and not Q.is_question_draft(normalized):
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failures.append("question_lost_or_answered")
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for token in case.get("required_all", []):
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if token not in normalized:
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failures.append(f"missing:{token}")
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for alternatives in case.get("required_one_of", []):
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if not any(token in normalized for token in alternatives):
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failures.append("missing_one_of:" + "|".join(alternatives))
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if case.get("required_any") and not any(
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token in normalized for token in case["required_any"]
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):
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failures.append("missing_any:" + "|".join(case["required_any"]))
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for token in case.get("forbidden_any", []):
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if token in normalized:
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failures.append(f"forbidden:{token}")
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for token in case.get("forbidden_exact", []):
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if normalized.casefold() == token.casefold():
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failures.append(f"forbidden_exact:{token}")
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if pattern := case.get("must_match_regex"):
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if not re.search(pattern, normalized, re.DOTALL):
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failures.append(f"format_mismatch:{pattern}")
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if case.get("language") == "en":
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if not is_english(normalized):
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failures.append("expected_english_output")
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if case.get("target_language_only") and re.search(r"[\u3400-\u9fff]", normalized):
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failures.append("intermediate_non_english_output")
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return failures
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def prompt_fingerprint(system: str, user: str) -> dict:
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return {
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"system_chars": len(system),
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"user_chars": len(user),
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"system_sha256": hashlib.sha256(system.encode()).hexdigest()[:16],
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"user_sha256": hashlib.sha256(user.encode()).hexdigest()[:16],
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}
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def normal_job(case: dict, style_id: str, intensity: str) -> dict:
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text = case["input"]
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system = Q.build_prompt(style_id, intensity, text)
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# This mirrors normal dictation after the local skip gate. Skip outputs are
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# recorded instead of being sent, just like PolishingService.
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if Q.should_skip_llm(text, style_id):
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output = text
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error = None
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elapsed = 0.0
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source = "local_skip"
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else:
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started = time.monotonic()
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try:
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temperature = 0.65 if intensity == "heavy" and style_id in Q.FUN_STYLES else 0.1
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output = Q.call(Q.api_key, system, text, temperature=temperature)
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error = None
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except Exception as exc: # noqa: BLE001
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output = ""
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error = str(exc)
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elapsed = round(time.monotonic() - started, 3)
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source = "llm"
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return {
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"protocol": "normal_polish",
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"case_id": case["id"],
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"style": style_id,
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"intensity": intensity,
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"input": text,
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"system_prompt": system,
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"user_payload": text,
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"output": output,
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"source": source,
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"checks": objective_checks(case, output, "normal"),
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"error": error,
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"elapsed_seconds": elapsed,
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"prompt_fingerprint": prompt_fingerprint(system, text),
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}
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def print_summary(results: list[dict]) -> None:
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by_protocol: defaultdict[str, Counter] = defaultdict(Counter)
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by_case: defaultdict[str, Counter] = defaultdict(Counter)
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for result in results:
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status = "pass" if not result["checks"] and not result["error"] else "fail"
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by_protocol[result["protocol"]][status] += 1
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by_case[f"{result['protocol']}:{result['case_id']}"][status] += 1
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print("\nObjective contract summary:")
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for protocol, counts in sorted(by_protocol.items()):
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print(f" {protocol}: pass={counts['pass']} fail={counts['fail']}")
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print("\nCases with a detected breach:")
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failures = 0
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for result in results:
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if result["checks"] or result["error"]:
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failures += 1
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reason = result["checks"] or [f"request_error:{result['error']}"]
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print(
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f" [{result['protocol']} | {result['style']} | {result['case_id']}] "
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f"{', '.join(reason)}\n"
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f" output={result['output']!r}"
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)
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if not failures:
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print(" none")
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def main() -> None:
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parser = argparse.ArgumentParser()
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parser.add_argument("--profile", choices=("smoke", "full"), default="smoke")
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parser.add_argument("--samples", type=int, default=1)
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parser.add_argument("--workers", type=int, default=6)
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parser.add_argument("--output", default=".tmp/llm-full-prompt-quality.json")
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args = parser.parse_args()
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fixtures = json.loads(FIXTURES.read_text())
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key_match = re.search(r'deepseek = "([^"]+)"', Q.KEYFILE.read_text())
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if not key_match:
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raise SystemExit("No DeepSeek key configured for live evaluation.")
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Q.api_key = key_match.group(1)
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if args.profile == "smoke":
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normal_styles = ("builtin.chat", "builtin.dating", "user.emoji-chat")
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normal_cases = fixtures["normal_polish"][:8]
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else:
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normal_styles = tuple(Q.STYLES)
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normal_cases = fixtures["normal_polish"]
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jobs = []
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for _ in range(args.samples):
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for case in normal_cases:
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for style_id in normal_styles:
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for intensity in ("light", "heavy"):
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jobs.append(("normal", case, style_id, intensity))
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print(
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f"Running {len(jobs)} requests: profile={args.profile}, samples={args.samples}; "
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"each request includes the complete production-shaped system and user prompt."
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)
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results: list[dict] = []
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with concurrent.futures.ThreadPoolExecutor(max_workers=args.workers) as pool:
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futures = []
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for protocol, case, style_id, intensity in jobs:
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futures.append(pool.submit(normal_job, case, style_id, intensity))
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for future in concurrent.futures.as_completed(futures):
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result = future.result()
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results.append(result)
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flag = "PASS" if not result["checks"] and not result["error"] else "FAIL"
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print(
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f"[{flag:4}] {result['protocol']:17} {result['style']:16} "
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f"{result['case_id']} -> {result['output']!r}",
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flush=True,
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)
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results.sort(key=lambda item: (
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item["protocol"], item["case_id"], item["style"], item.get("intensity", "")
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))
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destination = ROOT / args.output
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destination.parent.mkdir(parents=True, exist_ok=True)
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destination.write_text(json.dumps(results, ensure_ascii=False, indent=2))
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print_summary(results)
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print(f"\nFull prompts, payloads, outputs, and fingerprints: {destination}")
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if __name__ == "__main__":
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main()
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