153 lines
4.5 KiB
Python
153 lines
4.5 KiB
Python
"""
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应答 TTS 波形磁盘缓存：文案与 TTS 配置未变时跳过逐条合成，加快启动。
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缓存目录：项目根下 cache/ack_tts_pcm/
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"""
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from __future__ import annotations
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import hashlib
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import json
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from pathlib import Path
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from typing import Dict, List, Optional, Tuple
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import numpy as np
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from voice_drone.core.configuration import SYSTEM_TTS_CONFIG
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# 与 src/core/configuration.py 一致：src/core/tts_ack_cache.py -> parents[2]
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_PROJECT_ROOT = Path(__file__).resolve().parents[2]
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ACK_PCM_CACHE_DIR = _PROJECT_ROOT / "cache" / "ack_tts_pcm"
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MANIFEST_NAME = "manifest.json"
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CACHE_FORMAT = 1
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def _tts_signature() -> dict:
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tts = SYSTEM_TTS_CONFIG or {}
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return {
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"model_dir": str(tts.get("model_dir", "")),
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"model_name": str(tts.get("model_name", "")),
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"voice": str(tts.get("voice", "")),
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"speed": round(float(tts.get("speed", 1.0)), 6),
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"sample_rate": int(tts.get("sample_rate", 24000)),
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}
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def compute_ack_pcm_fingerprint(
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unique_phrases: List[str],
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*,
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global_text: Optional[str] = None,
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mode_phrases: bool = True,
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) -> str:
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"""文案 + TTS 签名变化则指纹变，磁盘缓存失效。"""
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payload = {
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"cache_format": CACHE_FORMAT,
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"tts": _tts_signature(),
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"mode_phrases": mode_phrases,
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}
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if mode_phrases:
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payload["phrases"] = sorted(unique_phrases)
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else:
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payload["global_text"] = (global_text or "").strip()
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raw = json.dumps(payload, sort_keys=True, ensure_ascii=False)
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return hashlib.sha256(raw.encode("utf-8")).hexdigest()
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def _phrase_file_stem(fingerprint: str, phrase: str) -> str:
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h = hashlib.sha256(fingerprint.encode("utf-8"))
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h.update(b"\0")
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h.update(phrase.encode("utf-8"))
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return h.hexdigest()[:40]
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def _load_one_npz(path: Path) -> Optional[Tuple[np.ndarray, int]]:
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try:
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z = np.load(path, allow_pickle=False)
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audio = np.asarray(z["audio"], dtype=np.float32).squeeze()
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sr = int(np.asarray(z["sr"]).reshape(-1)[0])
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if audio.size == 0 or sr <= 0:
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return None
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return (audio, sr)
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except Exception:
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return None
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def load_cached_phrases(
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unique_phrases: List[str],
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fingerprint: str,
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) -> Tuple[Dict[str, Tuple[np.ndarray, int]], List[str]]:
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"""
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从磁盘加载与 fingerprint 匹配的缓存。
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Returns:
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(已加载的 phrase -> (audio, sr), 仍需合成的 phrase 列表)
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"""
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out: Dict[str, Tuple[np.ndarray, int]] = {}
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if not unique_phrases:
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return {}, []
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cache_dir = ACK_PCM_CACHE_DIR
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manifest_path = cache_dir / MANIFEST_NAME
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if not manifest_path.is_file():
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return {}, list(unique_phrases)
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try:
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with open(manifest_path, "r", encoding="utf-8") as f:
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manifest = json.load(f)
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except Exception:
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return {}, list(unique_phrases)
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if int(manifest.get("format", 0)) != CACHE_FORMAT:
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return {}, list(unique_phrases)
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if manifest.get("fingerprint") != fingerprint:
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return {}, list(unique_phrases)
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files: Dict[str, str] = manifest.get("files") or {}
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missing: List[str] = []
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for phrase in unique_phrases:
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fname = files.get(phrase)
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if not fname:
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missing.append(phrase)
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continue
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path = cache_dir / fname
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if not path.is_file():
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missing.append(phrase)
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continue
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loaded = _load_one_npz(path)
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if loaded is None:
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missing.append(phrase)
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continue
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out[phrase] = loaded
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return out, missing
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def persist_phrases(fingerprint: str, phrase_pcm: Dict[str, Tuple[np.ndarray, int]]) -> None:
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"""写入/更新整包 manifest 与各句 npz（覆盖同名 manifest）。"""
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if not phrase_pcm:
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return
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cache_dir = ACK_PCM_CACHE_DIR
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cache_dir.mkdir(parents=True, exist_ok=True)
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files: Dict[str, str] = {}
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for phrase, (audio, sr) in phrase_pcm.items():
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stem = _phrase_file_stem(fingerprint, phrase)
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fname = f"{stem}.npz"
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path = cache_dir / fname
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audio = np.asarray(audio, dtype=np.float32).squeeze()
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np.savez_compressed(path, audio=audio, sr=np.array([int(sr)], dtype=np.int32))
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files[phrase] = fname
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manifest = {
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"format": CACHE_FORMAT,
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"fingerprint": fingerprint,
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"files": files,
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}
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tmp = cache_dir / (MANIFEST_NAME + ".tmp")
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with open(tmp, "w", encoding="utf-8") as f:
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json.dump(manifest, f, ensure_ascii=False, indent=0)
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tmp.replace(cache_dir / MANIFEST_NAME)
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