Files
ely-eye/backend/tests/test_asr.py
T
ZacharyZhang-NY 709104e809 Make the speech numbers reproducible instead of merely printed
A review of 5289cb4 found the ASR report was not honest arithmetic:

- "audio s" was the last segment's end, not the media length. The real
  container durations are 88.93 / 109.18 / 60.07 s, so the report understated
  the audio by 48 s and every speed cell was wrong.
- Decoding was unpinned, so a rerun was a new draw: WER moved 0.242 to 0.262
  and one video moved 0.278 to 0.583. Greedy single-temperature decoding with
  no carry-over now answers the same way twice, and the harness runs the pass
  twice to show it.
- The report claimed its WER was an upper bound. It is not a bound in either
  direction: a caption that drops words also hides words the model dropped.
  The denominators (201 / 296 / 36 reference words) are printed instead.
- "66 speech atoms" was bench-side arithmetic. The store now says 80 audio
  atoms carrying 563 word timestamps, read back after a real ingest.

Same silent-skip bug in a second place: a text file over max_text_file_bytes
returned an empty batch with no reason. It raises FileTooLarge with its size,
and a walk records that refusal like any other.

Also fixed from the same review: the Go search tool never published the audio
modality, cli_senses carried a second json_dump, the no-audio-track branch had
a test that fed it markdown, _seconds was an empty wrapper, and the docstring
quoted a speed no report measured.

Gate root cause: bench/tests imports the bench package by name with no root
conftest, so bare pytest could not collect it at all. pythonpath in pyproject
fixes both launch styles; 212 tests pass either way.

Verification: 212 passed (bare pytest and python -m pytest), ruff clean,
mypy clean on the six touched files with a cold cache, repo-wide mypy 24/6
unchanged from HEAD, pyright 0 errors on the touched files, go build/vet/test
and gofmt clean.
2026-10-07 22:23:33 -04:00

291 lines
10 KiB
Python

"""Speech memories: what a recording becomes, and what happens when no model is configured."""
from __future__ import annotations
import wave
from pathlib import Path
from typing import Any, cast
import numpy as np
import pytest
from ely_eye import ingestion_media as media_module
from ely_eye.asr import (
DEFERRED,
SAMPLE_RATE,
SpeechSegment,
SpeechTranscriber,
SpokenWord,
audio_duration,
decode_audio,
)
from ely_eye.config import Settings
from ely_eye.db import Database
from ely_eye.ingestion import IngestionService, UnsupportedFile
from ely_eye.ingestion_common import FileTooLarge
from ely_eye.ocr import OcrResult
from ely_eye.schemas import Modality
WORDS = (
SpokenWord(word="钥匙", start=0.58, end=0.9, confidence=0.91),
SpokenWord(word="抽屉", start=1.02, end=1.4, confidence=0.77),
)
SEGMENTS = (
SpeechSegment(text="钥匙在抽屉里", start=0.58, end=1.4, words=WORDS, confidence=0.84),
SpeechSegment(text="", start=9.0, end=9.5, words=(), confidence=0.0),
)
class FakeTranscriber:
"""Stands in for whisper so the test asserts the shape we build from its answer."""
def __init__(
self,
segments: tuple[SpeechSegment, ...] = SEGMENTS,
available: bool = True,
error: Exception | None = None,
) -> None:
self.segments = segments
self._available = available
self.error = error
self.calls: list[Path] = []
def available(self) -> bool:
return self._available
def transcribe(self, path: Path) -> list[SpeechSegment]:
self.calls.append(path)
if self.error is not None:
raise self.error
return list(self.segments)
class FakeEncoded:
def tobytes(self) -> bytes:
return b"png-bytes"
class FakeCapture:
"""One frame, two frames of metadata: enough for the video reader to reach the speech step."""
def __init__(self, _path: str) -> None:
self.released = False
def isOpened(self) -> bool:
return True
def get(self, property_id: int) -> float:
return 1.0 if property_id == media_module.cv2.CAP_PROP_FPS else 2.0
def set(self, _property_id: int, _value: float) -> None:
return None
def read(self) -> tuple[bool, Any]:
return True, np.zeros((4, 4, 3), dtype=np.uint8)
def release(self) -> None:
self.released = True
class FakeCv2:
CAP_PROP_FPS = 5
CAP_PROP_FRAME_COUNT = 7
CAP_PROP_POS_FRAMES = 1
VideoCapture = FakeCapture
@staticmethod
def imencode(_suffix: str, _frame: Any) -> tuple[bool, FakeEncoded]:
return True, FakeEncoded()
def _settings(tmp_path: Path, asr_model_dir: Path | None = None, max_text_file_bytes: int = 10_000_000) -> Settings:
return Settings(home=tmp_path / "home", asr_model_dir=asr_model_dir, max_text_file_bytes=max_text_file_bytes)
def _service(
tmp_path: Path,
transcriber: Any,
*,
asr_model_dir: Path | None = None,
max_text_file_bytes: int = 10_000_000,
) -> tuple[IngestionService, Database]:
settings = _settings(tmp_path, asr_model_dir=asr_model_dir, max_text_file_bytes=max_text_file_bytes)
settings.ensure_dirs()
database = Database(settings)
service = IngestionService(settings=settings, database=database)
service.transcriber = cast(SpeechTranscriber, transcriber)
return service, database
def _audio(tmp_path: Path, name: str = "keynote.mp3") -> Path:
path = tmp_path / name
path.write_bytes(b"not really mp3")
return path
def test_a_recording_becomes_memories_pointed_at_the_instant_each_word_was_said(
tmp_path: Path,
) -> None:
service, database = _service(tmp_path, FakeTranscriber())
response = service.ingest_path(_audio(tmp_path))
assert response.atom_count == 1, "the empty segment must not become a memory"
atom = database.list_atoms()[0]
assert atom.modality is Modality.audio
assert atom.text == "钥匙在抽屉里"
assert atom.source.endswith("#t=0.580")
assert atom.atom_id.endswith(":speech:0000000580")
assert atom.layout is not None and atom.layout.frame_second == pytest.approx(0.58)
assert atom.metadata["start_seconds"] == pytest.approx(0.58)
assert atom.metadata["end_seconds"] == pytest.approx(1.4)
assert [(word["word"], word["start"]) for word in atom.metadata["words"]] == [("钥匙", 0.58), ("抽屉", 1.02)]
assert atom.trust.model == pytest.approx(0.84), "the model's own confidence is the trust it earned"
def test_a_recording_without_a_model_is_recorded_and_says_why(tmp_path: Path) -> None:
service, database = _service(tmp_path, FakeTranscriber(available=False))
response = service.ingest_path(_audio(tmp_path))
assert response.source_count == 1, "the file is known even when nothing was heard"
assert response.atom_count == 0
assert database.list_sources()[0].metadata["speech"] == DEFERRED
assert response.skipped == [], "a file we have a reader for is not a skipped file"
def test_a_broken_model_leaves_a_note_instead_of_a_corpse(tmp_path: Path) -> None:
service, _database = _service(tmp_path, FakeTranscriber(error=ValueError("ctranslate2 is gone")))
response = service.ingest_path(_audio(tmp_path))
assert response.source_count == 1
assert response.atom_count == 0
assert response.sources[0].metadata["speech"] == "failed: ctranslate2 is gone"
def test_a_video_learns_what_was_said_in_it(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
service, database = _service(tmp_path, FakeTranscriber())
monkeypatch.setattr(media_module, "cv2", FakeCv2())
monkeypatch.setattr(media_module, "read_text_from_image", lambda path: OcrResult("", 0.0, []))
video = tmp_path / "talk.mp4"
video.write_bytes(b"not really mp4")
service.ingest_path(video)
modalities = {atom.modality for atom in database.list_atoms()}
assert Modality.video_frame in modalities
assert Modality.audio in modalities, "a silent OCR of frames misses everything that was spoken"
assert database.list_sources()[0].metadata["speech"] == "1 segments of speech"
def test_a_file_we_cannot_read_fails_when_it_was_named_explicitly(tmp_path: Path) -> None:
service, _database = _service(tmp_path, FakeTranscriber(available=False))
mystery = tmp_path / "mystery.xyz"
mystery.write_text("nope", encoding="utf-8")
with pytest.raises(UnsupportedFile, match="no reader for .xyz"):
service.ingest_path(mystery)
def test_a_walk_records_what_it_refused_to_read(tmp_path: Path) -> None:
service, database = _service(tmp_path, FakeTranscriber(available=False))
folder = tmp_path / "shelf"
folder.mkdir()
(folder / "note.md").write_text("# 钥匙放在抽屉里\n", encoding="utf-8")
(folder / "mystery.bin").write_bytes(b"\x00\x01")
response = service.ingest_path(folder)
assert response.atom_count > 0, "the readable file is still ingested"
assert [item.path for item in response.skipped] == [str(folder / "mystery.bin")]
assert "no reader for .bin" in response.skipped[0].reason
assert database.atom_count() == response.atom_count
def test_the_transcriber_names_the_snapshot_it_wants(tmp_path: Path) -> None:
without = SpeechTranscriber(_settings(tmp_path))
assert not without.available()
with pytest.raises(SystemExit, match="ELY_EYE_ASR_MODEL_DIR"):
without.transcribe(_audio(tmp_path))
empty = tmp_path / "snapshot"
empty.mkdir()
half = SpeechTranscriber(_settings(tmp_path, asr_model_dir=empty))
assert not half.available()
with pytest.raises(SystemExit, match="holds no model.bin"):
half.transcribe(_audio(tmp_path))
def _video_only(path: Path) -> Path:
"""A real mp4 with a video stream and no audio track, written by the decoder we already ship."""
import av
with av.open(str(path), "w") as container:
stream = container.add_stream("mpeg4", rate=10)
stream.width, stream.height, stream.pix_fmt = 64, 64, "yuv420p"
for _ in range(5):
frame = av.VideoFrame.from_ndarray(np.zeros((64, 64, 3), dtype=np.uint8), format="rgb24")
for packet in stream.encode(frame):
container.mux(packet)
for packet in stream.encode():
container.mux(packet)
return path
def test_a_file_with_no_audio_track_says_so(tmp_path: Path) -> None:
video = _video_only(tmp_path / "silent.mp4")
with pytest.raises(ValueError, match="the file holds no audio track"):
decode_audio(video)
def test_an_audio_track_with_no_frames_says_so(tmp_path: Path) -> None:
silent = tmp_path / "silent.wav"
with wave.open(str(silent), "wb") as writer:
writer.setnchannels(1)
writer.setsampwidth(2)
writer.setframerate(SAMPLE_RATE)
with pytest.raises(ValueError, match="the audio track is empty"):
decode_audio(silent)
def test_a_walk_records_a_file_over_the_size_cap(tmp_path: Path) -> None:
service, database = _service(tmp_path, FakeTranscriber(available=False), max_text_file_bytes=32)
folder = tmp_path / "shelf"
folder.mkdir()
(folder / "note.md").write_text("# 钥匙放在抽屉里\n", encoding="utf-8")
(folder / "huge.json").write_text('{"钥匙": "抽屉"}' * 4, encoding="utf-8")
response = service.ingest_path(folder)
assert response.atom_count > 0, "the small file is still ingested"
assert [item.path for item in response.skipped] == [str(folder / "huge.json")]
assert "over max_text_file_bytes=32" in response.skipped[0].reason
assert database.atom_count() == response.atom_count
def test_an_explicit_file_over_the_size_cap_fails_loudly(tmp_path: Path) -> None:
service, _database = _service(tmp_path, FakeTranscriber(available=False), max_text_file_bytes=16)
huge = tmp_path / "huge.json"
huge.write_text('{"钥匙": "抽屉"}' * 4, encoding="utf-8")
with pytest.raises(FileTooLarge, match="over max_text_file_bytes=16"):
service.ingest_path(huge)
def test_the_container_duration_is_the_media_length(tmp_path: Path) -> None:
video = _video_only(tmp_path / "silent.mp4")
assert audio_duration(video) == pytest.approx(0.5, abs=0.05)
def test_a_text_file_cannot_be_decoded(tmp_path: Path) -> None:
markdown = tmp_path / "notes.md"
markdown.write_text("# 钥匙\n", encoding="utf-8")
with pytest.raises(ValueError, match="the audio cannot be decoded"):
decode_audio(markdown)