| |
| """Offline end-to-end test for the harness. |
| |
| Builds a synthetic dataset with the SAME schema as |
| modulate/entity-transcription-benchmark (id, subset, transcript, entities, |
| entity_types, entity_tiers, entity_offsets, n_entities, duration_s, audio), |
| stands up a fake STT endpoint, and runs the real CLIs against the real |
| matcher_v5. No network and no API keys required. |
| |
| python test_harness.py |
| """ |
|
|
| from __future__ import annotations |
|
|
| import io |
| import json |
| import os |
| import shutil |
| import subprocess |
| import sys |
| import tempfile |
| import threading |
| import time |
| from http.server import BaseHTTPRequestHandler, HTTPServer |
|
|
| import numpy as np |
|
|
| HERE = os.path.dirname(os.path.abspath(__file__)) |
|
|
| |
| CLIPS = [ |
| ("c001", "Nadia Boulanger taught in Paris", |
| ["Nadia Boulanger", "Paris"], ["PERSON", "GPE"], ["A", "A"], "synthetic", |
| "nadia boulanger taught in paris"), |
| ("c002", "Addenbrooke's Hospital is in Cambridge", |
| ["Addenbrooke's Hospital", "Cambridge"], ["ORG", "GPE"], ["A", "B"], "meetings", |
| "addenbrookes hospital is in cambridge"), |
| ("c003", "The Mapuche live in Chile", |
| ["Mapuche", "Chile"], ["NORP", "GPE"], ["A", "A"], "belebele", |
| "the mapoochay live in chilly"), |
| ("c004", "Ikeda visited Osaka", |
| ["Ikeda", "Osaka"], ["PERSON", "GPE"], ["A", "B"], "synthetic", |
| "ikeda visited osaka"), |
| ("c005", "nothing named here at all", [], [], [], "meetings", |
| "nothing named here at all"), |
| ("c006", "Trivial mention of London", |
| ["London"], ["GPE"], ["B"], "belebele", |
| "trivial mention of london"), |
| ] |
|
|
|
|
| class FakeSTT(BaseHTTPRequestHandler): |
| order: list[str] = [] |
| served = 0 |
|
|
| def do_POST(self): |
| self.rfile.read(int(self.headers.get("Content-Length", 0))) |
| if self.headers.get("Authorization") != "Bearer test-key-123": |
| self.send_response(401) |
| self.end_headers() |
| self.wfile.write(b'{"error":"bad key"}') |
| return |
| cls = type(self) |
| body = json.dumps({"result": {"transcript": cls.order[cls.served % len(cls.order)]}}).encode() |
| cls.served += 1 |
| self.send_response(200) |
| self.send_header("Content-Type", "application/json") |
| self.send_header("Content-Length", str(len(body))) |
| self.end_headers() |
| self.wfile.write(body) |
|
|
| def log_message(self, *args): |
| pass |
|
|
|
|
| def build_dataset(path: str) -> None: |
| import soundfile as sf |
| from datasets import Audio, Dataset |
|
|
| rng = np.random.default_rng(0) |
| rows: dict[str, list] = {k: [] for k in ( |
| "audio", "id", "subset", "transcript", "entities", "entity_types", |
| "n_entities", "duration_s", "entity_tiers", "entity_offsets")} |
| for clip_id, text, entities, types, tiers, subset, _ in CLIPS: |
| buf = io.BytesIO() |
| sf.write(buf, rng.normal(0, 0.01, 8000).astype(np.float32), 16000, |
| format="WAV", subtype="PCM_16") |
| rows["audio"].append({"bytes": buf.getvalue(), "path": f"{clip_id}.wav"}) |
| rows["id"].append(f"named_entities-{subset}-{clip_id}") |
| rows["subset"].append(subset) |
| rows["transcript"].append(text) |
| |
| rows["entities"].append(json.dumps(entities)) |
| rows["entity_types"].append(json.dumps(types)) |
| rows["entity_tiers"].append(json.dumps(tiers)) |
| rows["n_entities"].append(len(entities)) |
| rows["duration_s"].append(0.5) |
| rows["entity_offsets"].append(json.dumps( |
| [{"start": text.find(e), "end": text.find(e) + len(e), "label": t, "text": e} |
| for e, t in zip(entities, types)])) |
| Dataset.from_dict(rows).cast_column("audio", Audio(decode=False)).save_to_disk(path) |
|
|
|
|
| def run(cmd: list[str], env: dict) -> subprocess.CompletedProcess: |
| return subprocess.run(cmd, cwd=HERE, env={**os.environ, **env}, capture_output=True, text=True) |
|
|
|
|
| def main() -> int: |
| matcher_path = os.path.join(HERE, "matcher_v5.py") |
| if not os.path.exists(matcher_path): |
| print("matcher_v5.py is not next to this script -- copy it in first:") |
| print(" cp ../bench2/matcher_v5.py .") |
| return 2 |
|
|
| sys.path.insert(0, HERE) |
| import matcher_v5 |
|
|
| work = tempfile.mkdtemp(prefix="ebench_") |
| dataset_path = os.path.join(work, "ds") |
| hyps = os.path.join(work, "run.jsonl") |
| failures: list[str] = [] |
|
|
| def check(label: str, ok: bool, detail: str = "") -> None: |
| print(f" [{'ok' if ok else 'FAIL'}] {label}" + (f" -- {detail}" if detail and not ok else "")) |
| if not ok: |
| failures.append(label) |
|
|
| |
| |
| tier_a, tier_all = [], [] |
| for clip_id, _, entities, types, tiers, _, hypothesis in CLIPS: |
| for entity, tier in zip(entities, tiers): |
| outcome = bool(matcher_v5.hit(entity, hypothesis)) |
| tier_all.append(outcome) |
| if tier == "A": |
| tier_a.append(outcome) |
| expect_a_spans, expect_a_hits = len(tier_a), sum(tier_a) |
| expect_all_spans = len(tier_all) |
|
|
| print(f"matcher_v5 self-test: {matcher_v5.validate(verbose=False)} ({len(matcher_v5.CASES)} cases)") |
| print(f"expected tier-A: {expect_a_hits}/{expect_a_spans} spans; all tiers: {expect_all_spans} spans\n") |
|
|
| print("building fixture dataset...") |
| build_dataset(dataset_path) |
|
|
| FakeSTT.order = [c[6] for c in CLIPS] |
| server = HTTPServer(("127.0.0.1", 0), FakeSTT) |
| port = server.server_address[1] |
| threading.Thread(target=server.serve_forever, daemon=True).start() |
| time.sleep(0.2) |
|
|
| base = [ |
| sys.executable, "run_benchmark.py", "--provider", "http", |
| "--endpoint", f"http://127.0.0.1:{port}/stt", "--api-key-env", "TEST_STT_KEY", |
| "--response-path", "result.transcript", "--local-path", dataset_path, "--workers", "1", |
| ] |
| good = {"TEST_STT_KEY": "test-key-123"} |
|
|
| print("collection:") |
| proc = run(base + ["--out", hyps], good) |
| check("run_benchmark exits clean", proc.returncode == 0, proc.stderr[-600:]) |
| check("columns resolved from real schema", |
| "transcript" in proc.stderr and "entity_tiers" in proc.stderr, proc.stderr[:400]) |
| records = [json.loads(l) for l in open(hyps)] if os.path.exists(hyps) else [] |
| check("all 6 clips transcribed by default", len(records) == 6, f"got {len(records)}") |
| check("no failed clips", all(r.get("hypothesis") is not None for r in records)) |
| check("manifest written", os.path.exists(os.path.splitext(hyps)[0] + ".manifest.json")) |
|
|
| print("\nauth failure surfaces:") |
| bad = run(base + ["--out", os.path.join(work, "bad.jsonl")], {"TEST_STT_KEY": "wrong"}) |
| check("bad key does not silently score", bad.returncode != 0 or "401" in bad.stderr) |
|
|
| print("\nresume:") |
| before = len(open(hyps).readlines()) |
| again = run(base + ["--out", hyps], good) |
| check("rerun is a no-op", again.returncode == 0 and len(open(hyps).readlines()) == before) |
|
|
| print("\nscoring (tier A, the published protocol):") |
| scored = run([sys.executable, "score_benchmark.py", "--hyps", hyps, |
| "--local-path", dataset_path], {}) |
| check("score_benchmark exits clean", scored.returncode == 0, scored.stderr[-700:]) |
| summary_path = os.path.splitext(hyps)[0] + ".summary.json" |
| summary = json.load(open(summary_path)) if os.path.exists(summary_path) else {} |
| check("summary written", bool(summary)) |
| if summary: |
| check(f"tier-A spans only ({expect_a_spans})", |
| summary["entity_spans"] == expect_a_spans, str(summary.get("entity_spans"))) |
| check(f"hits match direct matcher calls ({expect_a_hits})", |
| summary["entity_hits"] == expect_a_hits, str(summary.get("entity_hits"))) |
| check("tier-B spans excluded", summary["entity_spans"] < expect_all_spans) |
| check("matcher self-test gate = 49/49", |
| summary["matcher_self_test"] == f"{len(matcher_v5.CASES)}/{len(matcher_v5.CASES)}", |
| str(summary.get("matcher_self_test"))) |
| check("WER covers every transcribed clip", summary["clips_with_hypothesis"] == 6) |
| check("WER computed", summary["wer"] is not None) |
| check("subset breakdown present", |
| bool(summary["by_subset"]) and set(summary["by_subset"]) <= {"synthetic", "meetings", "belebele"}) |
| check("provider recorded", summary["provider"] == "http") |
|
|
| hits_csv = os.path.splitext(hyps)[0] + ".hits.csv" |
| check("per-span hits CSV written", os.path.exists(hits_csv)) |
| if os.path.exists(hits_csv): |
| check("hits CSV carries tier column", "tier" in open(hits_csv).readline()) |
|
|
| print("\nscoring (tier all):") |
| every = run([sys.executable, "score_benchmark.py", "--hyps", hyps, "--local-path", dataset_path, |
| "--tier", "all", "--out-prefix", os.path.join(work, "all")], {}) |
| all_summary = os.path.join(work, "all.summary.json") |
| ok = os.path.exists(all_summary) and json.load(open(all_summary))["entity_spans"] == expect_all_spans |
| check(f"tier all scores every span ({expect_all_spans})", every.returncode == 0 and ok, |
| every.stderr[-400:]) |
|
|
| print("\ncompare / diff:") |
| diffed = run([sys.executable, "score_benchmark.py", "--hyps", hyps, "--local-path", dataset_path, |
| "--compare", hits_csv], {}) |
| check("self-diff reports zero disagreements", "disagreements 0" in diffed.stdout, |
| diffed.stdout[-400:]) |
|
|
| print("\nmissing matcher is fatal, not silent:") |
| nomatcher = run([sys.executable, "score_benchmark.py", "--hyps", hyps, |
| "--local-path", dataset_path, "--matcher-path", os.path.join(work, "nope.py")], |
| {}) |
| check("refuses to score without a real matcher path", nomatcher.returncode != 0) |
|
|
| print("\nclip-level tier filter (collection):") |
| a_only = os.path.join(work, "a.jsonl") |
| FakeSTT.served = 0 |
| filt = run(base + ["--tier", "A", "--out", a_only], good) |
| expect_clips = sum(1 for c in CLIPS if "A" in c[4]) |
| check(f"--tier A skips clips with no A span ({expect_clips})", |
| filt.returncode == 0 and len(open(a_only).readlines()) == expect_clips, |
| filt.stderr[-400:]) |
|
|
| server.shutdown() |
| shutil.rmtree(work, ignore_errors=True) |
|
|
| print() |
| if failures: |
| print(f"{len(failures)} FAILED: {failures}") |
| return 1 |
| print("all checks passed") |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| sys.exit(main()) |
|
|