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f00d0dc f11d8c5 f00d0dc bdd5681 f11d8c5 bdd5681 f00d0dc bdd5681 7d8e415 676be16 f11d8c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 | from simpliscribe.benchmark import load_cases
from simpliscribe.benchmark import load_case_bundle
from simpliscribe.benchmark import evaluate_quality_gates
from simpliscribe.benchmark import run_case
from simpliscribe.benchmark import run_benchmark
from simpliscribe.benchmark import score_case
import pandas as pd
import pytest
def test_score_case_counts_matching_fields():
case = {
"id": "case-1",
"label": "Simple case",
"raw_text": "Paracetamol 650 tab od 5 days",
"expected_medications": [
{
"name": "Paracetamol",
"type": "Tablet",
"dosage": "650 mg",
"frequency": "once daily",
"duration": "5 days",
}
],
}
actual = [
{
"name": "Paracetamol",
"type": "Tablet",
"dosage": "650 mg",
"frequency": "once daily",
"duration": "5 days",
}
]
result = score_case(case, actual)
assert result.matched_fields == 5
assert result.total_fields == 5
assert result.score == 1.0
def test_run_benchmark_returns_summary(tmp_path):
cases_path = tmp_path / "cases.json"
cases_path.write_text(
"""
[
{
"id": "case-1",
"label": "Simple once-daily tablet",
"raw_text": "Paracetamol 650 tab od 5 days",
"expected_medications": [
{
"name": "Paracetamol",
"type": "Tablet",
"dosage": "650 mg",
"frequency": "once daily",
"duration": "5 days"
}
]
}
]
""".strip(),
encoding="utf-8",
)
cases = load_cases(cases_path)
result = run_benchmark(cases)
assert result["case_count"] == 1
assert result["success_count"] == 1
assert result["failure_count"] == 0
assert result["cases"][0]["label"] == "Simple once-daily tablet"
assert result["cases"][0]["actual"][0]["frequency"] == "once daily"
def test_run_benchmark_preserves_capsule_and_bedtime_in_mixed_case(tmp_path):
cases_path = tmp_path / "cases.json"
cases_path.write_text(
"""
[
{
"id": "case-2",
"label": "Two-line mixed medicines",
"raw_text": "Amoxycillin 500 cap bd 5 days\\nCetirizine 10 tab hs 3 days",
"expected_medications": [
{
"name": "Amoxycillin",
"type": "Capsule",
"dosage": "500 mg",
"frequency": "twice daily",
"duration": "5 days"
},
{
"name": "Cetirizine",
"type": "Tablet",
"dosage": "10 mg",
"frequency": "at bedtime",
"duration": "3 days"
}
]
}
]
""".strip(),
encoding="utf-8",
)
cases = load_cases(cases_path)
result = run_benchmark(cases)
assert result["average_score"] == 1.0
assert result["cases"][0]["actual"][0]["type"] == "Capsule"
assert result["cases"][0]["actual"][1]["frequency"] == "at bedtime"
def test_run_case_returns_failed_score_when_inference_errors(monkeypatch):
case = {
"id": "case-error",
"label": "Broken case",
"raw_text": "Broken OCR text",
"expected_medications": [
{"name": "Paracetamol", "type": "Tablet", "dosage": "650 mg", "frequency": "once daily", "duration": "5 days"}
],
}
def fake_structure_medications(_: str):
raise RuntimeError("Synthetic benchmark failure")
monkeypatch.setattr("simpliscribe.benchmark.structure_medications", fake_structure_medications)
result = run_case(case, retries=0)
assert result.score == 0.0
assert result.error == "Synthetic benchmark failure"
def test_run_case_supports_file_based_ocr(monkeypatch, tmp_path):
image_path = tmp_path / "sample.png"
image_path.write_bytes(b"mock-image")
case = {
"id": "case-file",
"label": "File-based case",
"file_path": "sample.png",
"expected_medications": [
{
"name": "Paracetamol",
"type": "Tablet",
"dosage": "650 mg",
"frequency": "once daily",
"duration": "5 days",
}
],
}
monkeypatch.setattr("simpliscribe.benchmark.extract_ocr_text", lambda path: "Paracetamol 650 tab od 5 days")
result = run_case(case, base_dir=tmp_path, retries=0)
assert result.source_kind == "file"
assert result.source_path == "sample.png"
assert result.raw_text == "Paracetamol 650 tab od 5 days"
assert result.actual[0]["frequency"] == "once daily"
def test_load_cases_supports_parquet_ground_truth(tmp_path):
parquet_path = tmp_path / "synthetic.parquet"
dataframe = pd.DataFrame(
[
{
"ground_truth": "<s_ocr> doctor_name: Dr. A medications: - Paracetamol 650 mg - Take once daily - Cetirizine 10 mg - At bedtime signature: Dr. A </s>"
}
]
)
dataframe.to_parquet(parquet_path)
cases = load_cases(parquet_path)
assert len(cases) == 1
assert cases[0]["raw_text"] == "Paracetamol 650 mg Take once daily\nCetirizine 10 mg At bedtime"
assert cases[0]["expected_medications"][0]["name"] == "Paracetamol"
assert cases[0]["expected_medications"][0]["dosage"] == "650 mg"
assert cases[0]["expected_medications"][0]["frequency"] == "once daily"
assert cases[0]["expected_medications"][1]["frequency"] == "at bedtime"
def test_load_cases_supports_parquet_ground_truth_without_signature(tmp_path):
parquet_path = tmp_path / "synthetic_no_signature.parquet"
dataframe = pd.DataFrame(
[
{
"ground_truth": "<s_ocr> doctor_name: Dr. A medications: - Paracetamol 650 mg - Take once daily </s>"
}
]
)
dataframe.to_parquet(parquet_path)
cases = load_cases(parquet_path)
assert len(cases) == 1
assert cases[0]["expected_medications"] == [
{
"name": "Paracetamol",
"type": "",
"dosage": "650 mg",
"frequency": "once daily",
"duration": "N/A",
}
]
def test_load_cases_preserves_hyphenated_medication_names(tmp_path):
parquet_path = tmp_path / "synthetic_hyphenated.parquet"
dataframe = pd.DataFrame(
[
{
"ground_truth": "<s_ocr> medications: - Co-trimoxazole 500/125 mg - Take twice daily signature: Dr. A </s>"
}
]
)
dataframe.to_parquet(parquet_path)
cases = load_cases(parquet_path)
assert len(cases) == 1
assert cases[0]["expected_medications"][0]["name"] == "Co-Trimoxazole"
assert cases[0]["expected_medications"][0]["dosage"] == "500/125 mg"
assert cases[0]["expected_medications"][0]["frequency"] == "twice daily"
def test_load_cases_supports_complex_dosage_formats(tmp_path):
parquet_path = tmp_path / "synthetic_complex_dosage.parquet"
dataframe = pd.DataFrame(
[
{
"ground_truth": "<s_ocr> medications: - Ambroxol 5 mg/5 ml - As directed signature: Dr. A </s>"
}
]
)
dataframe.to_parquet(parquet_path)
cases = load_cases(parquet_path)
assert len(cases) == 1
assert cases[0]["expected_medications"][0]["name"] == "Ambroxol"
assert cases[0]["expected_medications"][0]["dosage"] == "5 mg/5 ml"
assert cases[0]["expected_medications"][0]["frequency"] == "Refer to prescription"
def test_score_case_penalizes_extra_medications():
expected = {
"name": "Cetirizine",
"type": "Tablet",
"dosage": "10 mg",
"frequency": "once daily",
"duration": "5 days",
}
extra = {**expected, "name": "Paracetamol"}
result = score_case({"id": "extra-drug", "expected_medications": [expected]}, [expected, extra])
assert result.matched_fields == 5
assert result.total_fields == 10
assert result.score == 0.5
assert result.actual_count == 2
def test_score_case_does_not_score_unspecified_expected_fields():
case = {"id": "name-only", "expected_medications": [{"name": "Cetirizine"}]}
actual = [{
"name": "Cetirizine",
"type": "Tablet",
"dosage": "10 mg",
"frequency": "once daily",
"duration": "5 days",
}]
result = score_case(case, actual)
assert result.matched_fields == 1
assert result.total_fields == 1
assert result.score == 1.0
def test_score_case_matches_medications_independent_of_order():
cetirizine = {"name": "Cetirizine", "dosage": "10 mg", "frequency": "at bedtime"}
paracetamol = {"name": "Paracetamol", "dosage": "650 mg", "frequency": "once daily"}
result = score_case(
{"id": "reordered", "expected_medications": [cetirizine, paracetamol]},
[paracetamol, cetirizine],
)
assert result.matched_fields == 6
assert result.total_fields == 6
assert result.score == 1.0
assert result.field_results[0]["actual_medication_index"] == 1
def test_load_versioned_golden_bundle(tmp_path):
path = tmp_path / "golden.json"
path.write_text(
'{"schema_version":"1.0","dataset":"test-set","cases":['
'{"id":"case-1","raw_text":"Example","expected_medications":[]}]}',
encoding="utf-8",
)
metadata, cases = load_case_bundle(path)
assert metadata["schema_version"] == "1.0"
assert metadata["dataset"] == "test-set"
assert cases[0]["id"] == "case-1"
def test_load_versioned_golden_bundle_rejects_duplicate_ids(tmp_path):
path = tmp_path / "golden.json"
path.write_text(
'{"schema_version":"1.0","cases":['
'{"id":"duplicate","expected_medications":[]},'
'{"id":"duplicate","expected_medications":[]}]}',
encoding="utf-8",
)
with pytest.raises(ValueError, match="Duplicate benchmark case id"):
load_case_bundle(path)
def test_run_benchmark_reports_detection_field_and_safety_metrics(monkeypatch):
cases = [
{
"id": "positive",
"raw_text": "positive",
"expected_medications": [{"name": "A", "dosage": "10 mg", "requires_review": True}],
},
{"id": "negative", "raw_text": "negative", "expected_medications": []},
{"id": "unreadable", "raw_text": "unreadable", "expected_rejection": True, "expected_medications": []},
]
outputs = {
"positive": {"medications": [{"name": "A", "dosage": "10 mg", "requires_review": True}]},
"negative": {"medications": [{"name": "Hallucination"}]},
"unreadable": {"medications": []},
}
monkeypatch.setattr("simpliscribe.benchmark.structure_medications", lambda text: outputs[text])
result = run_benchmark(cases)
detection = result["metrics"]["medication_detection"]
assert detection == {
"true_positives": 1,
"false_positives": 1,
"false_negatives": 0,
"precision": 0.5,
"recall": 1.0,
"f1": 0.6667,
"hallucination_rate": 0.5,
}
assert result["metrics"]["field_accuracy"]["dosage"]["accuracy"] == 1.0
assert result["metrics"]["review_flag_recall"] == 1.0
assert result["metrics"]["unreadable_rejection_rate"] == 1.0
assert evaluate_quality_gates(result, 0.7, 0.4)
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