from __future__ import annotations from pathlib import Path from shiftedx_bench.models import BenchCase from shiftedx_bench.cli import make_parser from shiftedx_bench.release import sanitize_manifest, sanitize_result_row, scan_public_tree from shiftedx_bench.runner import run_cases from shiftedx_bench.summary import summarize_results from shiftedx_bench.util import read_jsonl class FakeClient: def __init__(self, prompt_tokens=10): self.prompt_tokens = prompt_tokens def complete(self, payload, stream=False): return { "content": '{"answer":7}', "reasoning_content": "", "tool_calls": [], "finish_reason": "stop", "usage": {"prompt_tokens": self.prompt_tokens, "completion_tokens": 5}, "prompt_tokens": self.prompt_tokens, "completion_tokens": 5, "wall_s": 1.0, "ttft_s": 0.2, "end_to_end_tokens_per_second": 5.0, "mtplx_stats": {}, } def test_runner_resumes_and_enforces_server_token_count(tmp_path): case = BenchCase( case_id="c", suite_id="s", lane="long-context", messages=[{"role":"user","content":"x"}], scorer="strict_json_exact", expected={"answer": 7}, metadata={"target_prompt_tokens": 10, "requested_position": .5, "family": "single"}, ) output = tmp_path / "results.jsonl" run_cases([case], client=FakeClient(), model="m", output_path=output) run_cases([case], client=FakeClient(), model="m", output_path=output) rows = read_jsonl(output) assert len(rows) == 1 and rows[0]["passed"] mismatch = tmp_path / "mismatch.jsonl" run_cases([case], client=FakeClient(prompt_tokens=9), model="m", output_path=mismatch) assert not read_jsonl(mismatch)[0]["passed"] def test_summary_separates_scorecards_and_context(): rows = [] for length, passed in [(4096, True), (8192, True), (16384, False)]: rows.append({ "variant":"ar", "lane":"long-context", "case_id":str(length), "passed":passed, "metadata":{"target_prompt_tokens":length,"requested_position":.5,"family":"single"}, "telemetry":{"wall_s":1.0,"ttft_s":.1,"end_to_end_tokens_per_second":10.0}, }) summary = summarize_results(rows, effective_threshold=.9) assert summary["context"]["ar"]["effective_context_length"] == 8192 assert summary["interpretation"]["single_intelligence_score"] is None def test_summary_uses_explicit_baseline_and_reports_regressions(): rows = [ {"variant": "parent", "lane": "quality", "case_id": "a", "passed": True, "metadata": {}, "telemetry": {}}, {"variant": "candidate", "lane": "quality", "case_id": "a", "passed": False, "metadata": {}, "telemetry": {}}, ] summary = summarize_results(rows, baseline_variant="parent") comparison = summary["parity"]["candidate"] assert comparison["baseline"] == "parent" assert not comparison["zero_regression_gate"] assert comparison["regressions"] == [{"case_id": "a", "lane": "quality"}] def test_public_scan_detects_tokens_and_user_paths(tmp_path): clean = tmp_path / "clean" clean.mkdir() (clean / "README.md").write_text("public documentation") assert scan_public_tree(clean)["ok"] fake_token = "h" + "f_" + "abcdefghijklmnopqrstuvwxyz1234" fake_path = "/" + "Users/example/private" (clean / "bad.txt").write_text(fake_token + "\n" + fake_path) result = scan_public_tree(clean) assert not result["ok"] assert {item["issue"] for item in result["failures"]} >= {"Hugging Face access token", "macOS user path"} def test_public_result_export_omits_responses_paths_and_identifiers(): row = { "schema_version": "1.0", "run_id": "private-run", "suite_id": "shiftedx-agentic-v1", "case_id": "repair", "lane": "agentic", "variant": "candidate", "passed": False, "score": 0, "score_max": 1, "error": "FileNotFoundError: /" + "Users/example/private.py", "response": {"content": "private output", "request_id": "request-private"}, "telemetry": { "wall_s": 2.0, "prompt_tokens": 10, "harness_receipts": [{"tool": "read_file"}], "turns": [{"request_id": "private"}], }, "metadata": { "agentic_control_profile": "shiftedx-harness-v1", "agentic_family": "repair_loop", "forbidden_calls": ["delete_file"], }, "request_hash": "a" * 64, } public = sanitize_result_row(row) assert public["error_category"] == "evaluation_error" assert public["telemetry"] == {"wall_s": 2.0, "prompt_tokens": 10} assert public["metadata"] == { "agentic_control_profile": "shiftedx-harness-v1", "agentic_family": "repair_loop", } text = str(public) assert "private" not in text and ("/" + "Users/") not in text and "response" not in public def test_public_manifest_export_keeps_revisions_and_drops_host_state(): manifest = { "run_id": "private", "created_at": "private", "suite_id": "shiftedx-agentic-v1", "benchmark_version": "0.5.0", "model": "local-model", "config_sha256": "a" * 64, "tokenizer_fingerprint": "b" * 64, "planned_cases": 30, "variants": [{ "label": "candidate", "request_overrides": { "reasoning_effort": "medium", "thinking": {"enabled": True}, "private_path": "/" + "Users/example", }, }], "environment": {"platform": "private-host"}, "evaluated_artifact": {"repo_id": "Org/Model", "revision": "c" * 40}, "benchmark_source": {"repo_id": "Shiftedx/shiftedx-bench", "revision": "d" * 40}, "agentic_control_profile": "shiftedx-harness-v1", } public = sanitize_manifest(manifest) assert public["evaluated_artifact"]["revision"] == "c" * 40 assert public["benchmark_source"]["revision"] == "d" * 40 assert public["variants"][0]["request_overrides"] == { "reasoning_effort": "medium", "thinking": {"enabled": True}, } assert "run_id" not in public and "environment" not in public and "model" not in public def test_run_suite_accepts_immutable_post_publish_provenance(): args = make_parser().parse_args([ "run-suite", "--base-url", "http://example.invalid/v1", "--model", "served-model", "--output", "results.jsonl", "--config", "configs/suites-smoke-v1.json", "--suite", "agentic", "--hf-repo", "Org/Model", "--hf-revision", "a" * 40, "--benchmark-revision", "b" * 40, ]) assert args.hf_repo == "Org/Model" assert args.hf_revision == "a" * 40 assert args.benchmark_revision == "b" * 40