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c641d5f | 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 | from tools.audio import (
answer_from_transcript,
format_transcript_items,
transcribe_audio,
)
def test_asr_uses_explicit_credentials_and_model(tmp_path, monkeypatch):
audio = tmp_path / "audio.mp3"
audio.write_bytes(b"audio")
observed = {}
class Client:
def __init__(self, **kwargs):
observed.update(kwargs)
def automatic_speech_recognition(self, audio, model):
observed["audio"] = audio
observed["model"] = model
return type("Result", (), {"text": "spoken words"})()
monkeypatch.setattr("tools.audio.InferenceClient", Client)
assert (
transcribe_audio(audio, token="env-token", model_id="whisper") == "spoken words"
)
assert observed["token"] == "env-token" and observed["model"] == "whisper"
assert observed["audio"] == b"audio"
def test_transcript_item_formatting():
assert (
format_transcript_items("Alphabetical comma-separated list", ["pear", "apple"])
== "apple, pear"
)
def test_deterministic_transcript_extraction():
pages = "Read page 245, page 197, and pages 132, 133 and 134."
assert answer_from_transcript("page numbers ascending", pages) == (
"132, 133, 134, 197, 245"
)
recipe = (
"In a saucepan, combine ripe strawberries, granulated sugar, freshly squeezed "
"lemon juice and cornstarch. Remove from heat and stir in a dash of pure vanilla "
"extract."
)
assert answer_from_transcript("alphabetize the ingredients", recipe) == (
"cornstarch, freshly squeezed lemon juice, granulated sugar, pure vanilla extract, "
"ripe strawberries"
)
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