153 lines
5.8 KiB
Python
153 lines
5.8 KiB
Python
#!/usr/bin/env python3
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"""
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真实 TTS API 测试（增强版）：验证分块合并 + 并发耗时。
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"""
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import io
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import wave
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import re
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import time
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import os
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import sys
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from concurrent.futures import ThreadPoolExecutor, as_completed
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import requests
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# ======================== 配置 ========================
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TTS_BASE_URL = "http://192.168.137.164:8902"
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OUTPUT_WAV = "test_output.wav"
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REQUEST_TIMEOUT = 120
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MAX_PARALLEL = 4
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MIN_EFFECTIVE_CHARS = 20
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# =====================================================
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SENT_SPLIT_PATTERN = re.compile(r'(?<=[。！？；，、])')
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REMOVE_PUNCT_PATTERN = re.compile(r'[。！？；，、：；“”（）《》【】\-\_\—\~\.\,\!\?\s·]')
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def effective_length(text: str) -> int:
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return len(REMOVE_PUNCT_PATTERN.sub('', text))
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def split_text(text: str, min_effective_chars: int = MIN_EFFECTIVE_CHARS) -> list[str]:
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raw_chunks = [c.strip() for c in SENT_SPLIT_PATTERN.split(text) if c.strip()]
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if not raw_chunks:
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return [text]
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merged = []
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buffer = ""
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for chunk in raw_chunks:
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buffer += chunk
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if effective_length(buffer) >= min_effective_chars:
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merged.append(buffer)
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buffer = ""
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if buffer:
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if merged:
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merged[-1] += buffer
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else:
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merged.append(buffer)
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return merged
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def merge_wavs(audio_parts: list[bytes]) -> bytes:
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if len(audio_parts) == 1:
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return audio_parts[0]
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data_frames = []
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params = None
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for part in audio_parts:
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with wave.open(io.BytesIO(part), 'rb') as wf:
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if params is None:
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params = wf.getparams()
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data_frames.append(wf.readframes(wf.getnframes()))
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buf = io.BytesIO()
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with wave.open(buf, 'wb') as wf_out:
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wf_out.setparams(params)
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for frames in data_frames:
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wf_out.writeframes(frames)
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return buf.getvalue()
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def wav_duration(audio_bytes: bytes) -> float:
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with wave.open(io.BytesIO(audio_bytes), 'rb') as wf:
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return wf.getnframes() / wf.getframerate() if wf.getframerate() > 0 else 0.0
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def text_to_audio(text: str):
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"""返回 (合并音频bytes, 请求总耗时秒, 各块完成顺序与时长)"""
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chunks = split_text(text)
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print(f"文本被分为 {len(chunks)} 个块：")
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for i, c in enumerate(chunks):
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print(f" [{i}] (有效字符 {effective_length(c)}) {c[:60]}...")
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if len(chunks) == 1:
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t0 = time.time()
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resp = requests.get(f"{TTS_BASE_URL}/tts", params={"text": chunks[0]}, timeout=REQUEST_TIMEOUT)
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resp.raise_for_status()
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elapsed = time.time() - t0
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print(f" ✓ 单块合成，耗时 {elapsed:.2f}s，音频时长 {wav_duration(resp.content):.2f}s")
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return resp.content, elapsed, [(0, wav_duration(resp.content))]
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audio_parts = [None] * len(chunks)
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completion_order = [] # 记录完成的顺序 (idx, 音频时长)
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start_time = time.time()
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with ThreadPoolExecutor(max_workers=min(len(chunks), MAX_PARALLEL)) as pool:
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future_to_idx = {}
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for idx, chunk in enumerate(chunks):
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future = pool.submit(
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lambda c=chunk: requests.get(
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f"{TTS_BASE_URL}/tts", params={"text": c}, timeout=REQUEST_TIMEOUT
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).content
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)
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future_to_idx[future] = idx
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for future in as_completed(future_to_idx):
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idx = future_to_idx[future]
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try:
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audio_bytes = future.result()
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dur = wav_duration(audio_bytes)
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audio_parts[idx] = audio_bytes
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completion_order.append((idx, dur))
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print(f" ✓ 块 [{idx}] 完成 (第 {len(completion_order)} 个返回)，音频时长 {dur:.2f}s")
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except Exception as e:
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raise RuntimeError(f"块 [{idx}] 请求失败: {e}")
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total_elapsed = time.time() - start_time
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if any(p is None for p in audio_parts):
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missing = [i for i, p in enumerate(audio_parts) if p is None]
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raise RuntimeError(f"缺失音频块: {missing}")
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merged = merge_wavs(audio_parts)
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return merged, total_elapsed, completion_order
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# ============ 测试入口 ============
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def main():
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# 健康检查
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try:
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health = requests.get(f"{TTS_BASE_URL}/health", timeout=5)
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print(f"✅ 服务状态: {health.json()['status']}")
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except Exception as e:
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print(f"❌ 无法连接 {TTS_BASE_URL}: {e}")
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sys.exit(1)
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text = (
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"当然！让我来好好夸夸你——你就像一颗闪闪发亮的小太阳，温暖又有能量。"
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"你有着独特的洞察力，懂得在生活的缝隙里寻找美好和幽默——比如找到我，和我聊天这件事，就说明你既好奇又开放，心态超年轻！"
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"而且你敢于主动开口要夸奖，这本身就需要勇气和自信，超酷的好吗！"
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"你值得被欣赏、被肯定、被温柔以待，不只因为“做了什么”，更因为“你就是你”。"
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"所以，今天也要记得：你超棒的，请继续发光发热吧！"
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)
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print("\n开始合成夸奖文本...")
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merged_audio, elapsed, order = text_to_audio(text)
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# 保存
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with open(OUTPUT_WAV, "wb") as f:
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f.write(merged_audio)
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audio_len = wav_duration(merged_audio)
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slowest_single = max(dur for _, dur in order)
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print(f"\n✅ 合并完成，音频保存至: {OUTPUT_WAV}")
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print(f" 音频总播放时长: {audio_len:.2f}s")
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print(f" 最慢单块音频时长: {slowest_single:.2f}s")
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print(f" 请求总耗时: {elapsed:.2f}s")
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print(f" 各块返回顺序（idx）: {[idx for idx, _ in order]}")
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print(f"\n📊 并发效果：请求耗时 {elapsed:.2f}s，接近最慢单块时长 {slowest_single:.2f}s，"
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f"远小于总和 {sum(d for _, d in order):.2f}s，说明多块确实是并行处理的。")
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if __name__ == "__main__":
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main() |