feat: apply new agent naming standards
Expanding abbreviations to remove ambiguity, simplifying agent names to reduce repetition. ref: N25B-257
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import numpy as np
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from control_backend.agents.perception.transcription_agent.speech_recognizer import (
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OpenAIWhisperSpeechRecognizer,
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SpeechRecognizer,
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)
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def test_estimate_max_tokens():
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"""Inputting one minute of audio, assuming 450 words per minute and adding a 10 token padding,
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expecting 610 tokens."""
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audio = np.empty(shape=(60 * 16_000), dtype=np.float32)
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actual = SpeechRecognizer._estimate_max_tokens(audio)
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assert actual == 610
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assert isinstance(actual, int)
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def test_get_decode_options():
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"""Check whether the right decode options are given under different scenarios."""
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audio = np.empty(shape=(60 * 16_000), dtype=np.float32)
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# With the defaults, it should limit output length based on input size
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recognizer = OpenAIWhisperSpeechRecognizer()
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options = recognizer._get_decode_options(audio)
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assert "sample_len" in options
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assert isinstance(options["sample_len"], int)
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# When explicitly enabled, it should limit output length based on input size
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recognizer = OpenAIWhisperSpeechRecognizer(limit_output_length=True)
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options = recognizer._get_decode_options(audio)
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assert "sample_len" in options
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assert isinstance(options["sample_len"], int)
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# When disabled, it should not limit output length based on input size
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assert "sample_rate" not in options
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