35fc0a088c
- VoiceFrame dataclass: label, confidence, speaker_id, shift_magnitude, timestamp - MockVoiceIO: async generator of synthetic frames on a timer (CF_VOICE_MOCK=1) - ContextClassifier: passthrough stub wrapping VoiceIO; _enrich() hook for real classifiers - make_io() factory: mock mode auto-detected from env, raises NotImplementedError for real audio - cf-voice-demo CLI entry point for quick smoke-testing - 12 tests passing; editable install via pip install -e ../cf-voice
43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
# cf_voice/models.py — VoiceFrame API contract
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#
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# This module is MIT licensed. All consumers (Linnet, Osprey, etc.)
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# import VoiceFrame from here so the shape is consistent across the stack.
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from __future__ import annotations
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from dataclasses import dataclass, field
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@dataclass
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class VoiceFrame:
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"""
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A single annotated moment in a voice stream.
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Produced by cf_voice.io (audio capture) and enriched by cf_voice.context
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(tone classification, speaker diarization).
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Fields
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------
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label Tone annotation, e.g. "Warmly impatient" or "Deflecting".
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Generic by default; Elcor-style prefix format is an
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easter egg surfaced by the product UI, not set here.
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confidence 0.0–1.0. Below ~0.5 the annotation is speculative.
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speaker_id Ephemeral local label ("speaker_a", "speaker_b").
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Not tied to identity — resets each session.
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shift_magnitude Delta from the previous frame's tone, 0.0–1.0.
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High values indicate a meaningful register shift.
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timestamp Session-relative seconds since capture started.
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"""
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label: str
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confidence: float
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speaker_id: str
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shift_magnitude: float
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timestamp: float
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def is_reliable(self, threshold: float = 0.6) -> bool:
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"""Return True when confidence meets the given threshold."""
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return self.confidence >= threshold
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def is_shift(self, threshold: float = 0.3) -> bool:
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"""Return True when shift_magnitude indicates a meaningful register change."""
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return self.shift_magnitude >= threshold
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