[OpenSpec 与项目骨架]：完成实施型变更与 Python 基础骨架，包含 OpenSpec 工件、核心模型、配置边界和基础测试

src/owner_voice_pet/models.py

@@ -0,0 +1,159 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Any, Mapping
+
+
+class PipelineState(str, Enum):
+    IDLE = "idle"
+    WAKE_LISTENING = "wake_listening"
+    SPEECH_DETECTING = "speech_detecting"
+    RECORDING = "recording"
+    TRANSCRIBING = "transcribing"
+    THINKING = "thinking"
+    SPEAKING = "speaking"
+    INTERRUPTED = "interrupted"
+    ERROR_RECOVERING = "error_recovering"
+
+
+class ErrorCode(str, Enum):
+    AUDIO_INPUT_DEVICE_MISSING = "AUDIO_INPUT_DEVICE_MISSING"
+    AUDIO_OUTPUT_DEVICE_MISSING = "AUDIO_OUTPUT_DEVICE_MISSING"
+    AUDIO_PERMISSION_DENIED = "AUDIO_PERMISSION_DENIED"
+    AUDIO_STREAM_UNDERRUN = "AUDIO_STREAM_UNDERRUN"
+    AUDIO_FORMAT_UNSUPPORTED = "AUDIO_FORMAT_UNSUPPORTED"
+    CONFIG_MISSING_VALUE = "CONFIG_MISSING_VALUE"
+    WAKE_MODEL_MISSING = "WAKE_MODEL_MISSING"
+    WAKE_MODEL_LOAD_FAILED = "WAKE_MODEL_LOAD_FAILED"
+    WAKE_AUDIO_FORMAT_INVALID = "WAKE_AUDIO_FORMAT_INVALID"
+    VAD_MODEL_LOAD_FAILED = "VAD_MODEL_LOAD_FAILED"
+    VAD_TIMEOUT_NO_SPEECH = "VAD_TIMEOUT_NO_SPEECH"
+    VAD_MAX_RECORDING_REACHED = "VAD_MAX_RECORDING_REACHED"
+    STT_MODEL_MISSING = "STT_MODEL_MISSING"
+    STT_TRANSCRIBE_FAILED = "STT_TRANSCRIBE_FAILED"
+    STT_EMPTY_TRANSCRIPT = "STT_EMPTY_TRANSCRIPT"
+    LLM_API_KEY_MISSING = "LLM_API_KEY_MISSING"
+    LLM_REQUEST_TIMEOUT = "LLM_REQUEST_TIMEOUT"
+    LLM_RATE_LIMITED = "LLM_RATE_LIMITED"
+    LLM_NETWORK_ERROR = "LLM_NETWORK_ERROR"
+    LLM_EMPTY_REPLY = "LLM_EMPTY_REPLY"
+    TTS_MODEL_MISSING = "TTS_MODEL_MISSING"
+    TTS_SYNTHESIS_FAILED = "TTS_SYNTHESIS_FAILED"
+    TTS_EMPTY_AUDIO = "TTS_EMPTY_AUDIO"
+    ASSET_MISSING = "ASSET_MISSING"
+    VALIDATION_FAILED = "VALIDATION_FAILED"
+
+
+@dataclass(slots=True)
+class ProviderError(Exception):
+    code: ErrorCode
+    message: str
+    retryable: bool
+    provider: str
+    stage: str
+
+    def __str__(self) -> str:
+        return f"{self.code.value} [{self.stage}/{self.provider}]: {self.message}"
+
+
+@dataclass(frozen=True, slots=True)
+class AudioFrame:
+    pcm: bytes
+    sample_rate: int
+    channels: int
+    timestamp_ms: int
+    frame_id: int
+    metadata: Mapping[str, Any] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        if self.sample_rate <= 0:
+            raise ValueError("sample_rate must be positive")
+        if self.channels <= 0:
+            raise ValueError("channels must be positive")
+        if self.timestamp_ms < 0:
+            raise ValueError("timestamp_ms must be non-negative")
+        if self.frame_id < 0:
+            raise ValueError("frame_id must be non-negative")
+
+
+@dataclass(frozen=True, slots=True)
+class AudioSegment:
+    pcm: bytes
+    sample_rate: int
+    channels: int
+    start_time_ms: int
+    end_time_ms: int
+    metadata: Mapping[str, Any] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        if self.sample_rate <= 0:
+            raise ValueError("sample_rate must be positive")
+        if self.channels <= 0:
+            raise ValueError("channels must be positive")
+        if self.start_time_ms < 0:
+            raise ValueError("start_time_ms must be non-negative")
+        if self.end_time_ms < self.start_time_ms:
+            raise ValueError("end_time_ms must be >= start_time_ms")
+
+    @property
+    def duration_ms(self) -> int:
+        return self.end_time_ms - self.start_time_ms
+
+
+@dataclass(frozen=True, slots=True)
+class WakeEvent:
+    keyword: str
+    confidence: float
+    timestamp_ms: int
+
+
+@dataclass(frozen=True, slots=True)
+class VadResult:
+    is_speech: bool
+    confidence: float
+    speech_ms: int
+    silence_ms: int
+    end_reason: str | None = None
+
+
+@dataclass(frozen=True, slots=True)
+class Transcript:
+    text: str
+    language: str
+    confidence: float | None
+    duration_ms: int
+    provider: str
+    raw_metadata: Mapping[str, Any] = field(default_factory=dict)
+
+    @property
+    def normalized_text(self) -> str:
+        return self.text.strip()
+
+
+@dataclass(frozen=True, slots=True)
+class Message:
+    role: str
+    content: str
+    created_at: float
+
+
+@dataclass(frozen=True, slots=True)
+class ReplyDelta:
+    text_delta: str
+    is_sentence_boundary: bool = False
+    finish_reason: str | None = None
+
+
+@dataclass(frozen=True, slots=True)
+class PlaybackResult:
+    played: bool
+    duration_ms: int
+    error: ProviderError | None = None
+
+
+@dataclass(frozen=True, slots=True)
+class TransportHealth:
+    input_available: bool
+    output_available: bool
+    message: str = ""