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update:优化测试工具目录结构

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hrz
2025-08-16 10:09:36 +08:00
parent 9b5e4eb9b7
commit e70415690c
8 changed files with 58 additions and 753 deletions
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README.md
+1 -2
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@@ -227,8 +227,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
| 工具名称 | 位置 | 使用方法 | 功能说明 |
|:---:|:---|:---:|:---:|
| 音频交互测试工具 | main》xiaozhi-server》test》test_page.html | 使用谷歌浏览器直接打开 | 测试音频播放和接收功能，验证Python端音频处理是否正常 |
| 模型响应测试工具1 | main》xiaozhi-server》performance_tester.py | 执行 `python performance_tester.py` | 测试ASR(语音识别)、LLM(大模型)、TTS(语音合成)三个核心模块的响应速度 |
| 模型响应测试工具2 | main》xiaozhi-server》performance_tester_vllm.py | 执行 `python performance_tester_vllm.py` | 测试VLLM(视觉模型)的响应速度 |
| 模型响应测试工具 | main》xiaozhi-server》performance_tester.py | 执行 `python performance_tester.py` | 测试ASR(语音识别)、LLM(大模型)、VLLM(视觉模型)、TTS(语音合成)三个核心模块的响应速度 |
> 💡 提示：测试模型速度时，只会测试配置了密钥的模型。
docs/performance_tester.md
+1 -1
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@@ -21,7 +21,7 @@ VLLM:
ASR:
```
4.在main/xiaozhi-server目录下运行performance_text_tool.py:
4.在main/xiaozhi-server目录下运行performance_tester.py:
```
python performance_test_tool.py
```
main/xiaozhi-server/performance_test_tool.py → main/xiaozhi-server/performance_tester.py
+23 -11
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@@ -2,21 +2,28 @@ import os
import importlib.util
import asyncio
print("使用前请根据doc/performance_texter.md的说明准备配置。")
def list_performance_text_modules():
performance_text_dir = os.path.join(os.path.dirname(__file__), "performance_text")
print("使用前请根据doc/performance_testerer.md的说明准备配置。")
def list_performance_tester_modules():
performance_tester_dir = os.path.join(
os.path.dirname(__file__), "performance_tester"
)
modules = []
for file in os.listdir(performance_text_dir):
for file in os.listdir(performance_tester_dir):
if file.endswith(".py"):
modules.append(file[:-3])
return modules
async def load_and_execute_module(module_name):
module_path = os.path.join(os.path.dirname(__file__), "performance_text", f"{module_name}.py")
module_path = os.path.join(
os.path.dirname(__file__), "performance_tester", f"{module_name}.py"
)
spec = importlib.util.spec_from_file_location(module_name, module_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
if hasattr(module, "main"):
main_func = module.main
if asyncio.iscoroutinefunction(main_func):
@@ -26,24 +33,28 @@ async def load_and_execute_module(module_name):
else:
print(f"模块 {module_name} 中没有找到 main 函数。")
def get_module_description(module_name):
module_path = os.path.join(os.path.dirname(__file__), "performance_text", f"{module_name}.py")
module_path = os.path.join(
os.path.dirname(__file__), "performance_tester", f"{module_name}.py"
)
spec = importlib.util.spec_from_file_location(module_name, module_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return getattr(module, "description", "暂无描述")
def main():
modules = list_performance_text_modules()
modules = list_performance_tester_modules()
if not modules:
print("performance_text 目录中没有可用的性能测试工具。")
print("performance_tester 目录中没有可用的性能测试工具。")
return
print("可用的性能测试工具：")
for idx, module in enumerate(modules, 1):
description = get_module_description(module)
print(f"{idx}. {module} - {description}")
try:
choice = int(input("请选择要调用的性能测试工具编号：")) - 1
if 0 <= choice < len(modules):
@@ -53,5 +64,6 @@ def main():
except ValueError:
print("请输入有效的数字。")
if __name__ == "__main__":
main()
main/xiaozhi-server/performance_text/performance_tester_asr.py → main/xiaozhi-server/performance_tester/performance_tester_asr.py
+6 -26
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@@ -7,50 +7,30 @@ from typing import Dict
import aiohttp
from tabulate import tabulate
from core.utils.asr import create_instance as create_stt_instance
from config.settings import load_config
# 设置全局日志级别为WARNING，抑制INFO级别日志
logging.basicConfig(level=logging.WARNING)
description = "语音识别模型性能测试"
class ASRPerformanceTester:
def __init__(self):
self.config = self._load_config_from_data_dir()
self.config = load_config()
self.test_wav_list = self._load_test_wav_files()
self.results = {"stt": {}}
# 调试日志
print(f"[DEBUG] 加载的ASR配置: {self.config.get('ASR', {})}")
print(f"[DEBUG] 音频文件数量: {len(self.test_wav_list)}")
def _load_config_from_data_dir(self) -> Dict:
"""从 data 目录加载所有 .config.yaml 文件的配置"""
config = {"ASR": {}}
data_dir = os.path.join(os.getcwd(), "data")
print(f"[DEBUG] 扫描配置文件目录: {data_dir}")
for root, _, files in os.walk(data_dir):
for file in files:
if file.endswith(".config.yaml"):
file_path = os.path.join(root, file)
try:
with open(file_path, "r", encoding="utf-8") as f:
import yaml
file_config = yaml.safe_load(f)
# 兼容大小写的 ASR/asr 配置
asr_config = file_config.get("ASR") or file_config.get("asr")
if asr_config:
config["ASR"].update(asr_config)
print(f"[DEBUG] 从 {file_path} 加载 ASR 配置成功")
except Exception as e:
print(f" 加载配置文件 {file_path} 失败: {str(e)}")
return config
def _load_test_wav_files(self) -> list:
"""加载测试用的音频文件（添加路径调试）"""
wav_root = os.path.join(os.getcwd(), "config", "assets")
print(f"[DEBUG] 音频文件目录: {wav_root}")
test_wav_list = []
if os.path.exists(wav_root):
file_list = os.listdir(wav_root)
print(f"[DEBUG] 找到音频文件: {file_list}")
main/xiaozhi-server/performance_text/performance_tester_llm.py → main/xiaozhi-server/performance_tester/performance_tester_llm.py
+4 -19
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@@ -8,14 +8,17 @@ import yaml
import aiohttp
from tabulate import tabulate
from core.utils.llm import create_instance as create_llm_instance
from config.settings import load_config
# 设置全局日志级别为 WARNING，抑制 INFO 级别日志
logging.basicConfig(level=logging.WARNING)
description = "大语言模型性能测试"
class LLMPerformanceTester:
def __init__(self):
self.config = self._load_config()
self.config = load_config()
self.test_sentences = self.config.get("module_test", {}).get(
"test_sentences",
[
@@ -26,24 +29,6 @@ class LLMPerformanceTester:
)
self.results = {}
def _load_config(self) -> Dict:
"""从 data/.config.yaml 加载配置"""
config = {}
config_file_path = os.path.join(os.getcwd(), "data", ".config.yaml")
print(f"[DEBUG] 加载配置文件: {config_file_path}")
if not os.path.exists(config_file_path):
print(f"[DEBUG] 配置文件 {config_file_path} 不存在")
return config
try:
with open(config_file_path, "r", encoding="utf-8") as f:
config = yaml.safe_load(f)
print(f"[DEBUG] 从 {config_file_path} 加载配置成功")
except Exception as e:
print(f"加载配置文件 {config_file_path} 失败: {str(e)}")
return config
async def _check_ollama_service(self, base_url: str, model_name: str) -> bool:
"""异步检查 Ollama 服务状态"""
async with aiohttp.ClientSession() as session:
main/xiaozhi-server/performance_text/performance_tester_tts.py → main/xiaozhi-server/performance_tester/performance_tester_tts.py
+19 -35
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@@ -8,14 +8,17 @@ from tabulate import tabulate
# 确保从 core.utils.tts 导入 create_tts_instance
from core.utils.tts import create_instance as create_tts_instance
from config.settings import load_config
# 设置全局日志级别为 WARNING
logging.basicConfig(level=logging.WARNING)
description = "非流式语音合成性能测试"
class TTSPerformanceTester:
def __init__(self):
self.config = self._load_config_from_data_dir()
self.config = load_config()
self.test_sentences = self.config.get("module_test", {}).get(
"test_sentences",
[
@@ -26,27 +29,6 @@ class TTSPerformanceTester:
)
self.results = {}
def _load_config_from_data_dir(self) -> Dict:
"""从 data 目录加载所有 .config.yaml 文件的配置"""
config = {"TTS": {}}
data_dir = os.path.join(os.getcwd(), "data")
print(f"[DEBUG] 扫描配置文件目录: {data_dir}")
for root, _, files in os.walk(data_dir):
for file in files:
if file.endswith(".config.yaml"):
file_path = os.path.join(root, file)
try:
with open(file_path, "r", encoding="utf-8") as f:
file_config = yaml.safe_load(f)
tts_config = file_config.get("TTS")
if tts_config:
config["TTS"].update(tts_config)
print(f"[DEBUG] 从 {file_path} 加载 TTS 配置成功")
except Exception as e:
print(f"加载配置文件 {file_path} 失败: {str(e)}")
return config
async def _test_tts(self, tts_name: str, config: Dict) -> Dict:
"""测试单个TTS模块的性能"""
try:
@@ -107,19 +89,19 @@ class TTSPerformanceTester:
table = []
for name, data in self.results.items():
if data["errors"] == 0:
table.append([
name,
f"{data['avg_time']:.3f}秒/句",
len(self.test_sentences[:3])
])
table.append(
[name, f"{data['avg_time']:.3f}秒/句", len(self.test_sentences[:3])]
)
print("\nTTS性能测试结果:")
print(tabulate(
table,
headers=["TTS模块", "平均耗时", "测试句子数"],
tablefmt="github",
colalign=("left", "right", "right")
))
print(
tabulate(
table,
headers=["TTS模块", "平均耗时", "测试句子数"],
tablefmt="github",
colalign=("left", "right", "right"),
)
)
async def run(self):
"""执行测试"""
@@ -136,7 +118,7 @@ class TTSPerformanceTester:
# 并发执行测试
results = await asyncio.gather(*tasks)
# 保存有效结果
for result in results:
if result["errors"] == 0:
@@ -145,11 +127,13 @@ class TTSPerformanceTester:
# 打印结果
self._print_results()
#为了performance_tester.py的调用需求
# 为了performance_tester.py的调用需求
async def main():
tester = TTSPerformanceTester()
await tester.run()
if __name__ == "__main__":
tester = TTSPerformanceTester()
asyncio.run(tester.run())
main/xiaozhi-server/performance_text/performance_tester_vllm.py → main/xiaozhi-server/performance_tester/performance_tester_vllm.py
+4 -8
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@@ -3,24 +3,20 @@ import asyncio
import logging
import statistics
import base64
import yaml
from typing import Dict
from tabulate import tabulate
from core.utils.vllm import create_instance
from config.settings import load_config
# 设置全局日志级别为WARNING，抑制INFO级别日志
logging.basicConfig(level=logging.WARNING)
description = "视觉识别模型性能测试"
class AsyncVisionPerformanceTester:
def __init__(self):
# 从data/.config.yaml读取配置
config_path = os.path.join("data", ".config.yaml")
if not os.path.exists(config_path):
raise FileNotFoundError(f"配置文件 {config_path} 不存在")
with open(config_path, "r", encoding="utf-8") as f:
self.config = yaml.safe_load(f) or {}
self.config = load_config()
self.test_images = [
"../../docs/images/demo1.png",
main/xiaozhi-server/performance_text/performance_tester.py
-651
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@@ -1,651 +0,0 @@
import asyncio
import logging
import os
import statistics
import time
from typing import Dict
import yaml
import aiohttp
from tabulate import tabulate
from core.utils.asr import create_instance as create_stt_instance
from core.utils.llm import create_instance as create_llm_instance
from core.utils.tts import create_instance as create_tts_instance
# 设置全局日志级别为WARNING，抑制INFO级别日志
logging.basicConfig(level=logging.WARNING)
description = "基础性能测试工具"
class AsyncPerformanceTester:
def __init__(self):
# 从data/.config.yaml读取配置
config_path = os.path.join("data", ".config.yaml")
if not os.path.exists(config_path):
raise FileNotFoundError(f"配置文件 {config_path} 不存在")
with open(config_path, "r", encoding="utf-8") as f:
self.config = yaml.safe_load(f) or {}
self.test_sentences = self.config.get("module_test", {}).get(
"test_sentences",
[
"你好，请介绍一下你自己",
"What's the weather like today?",
"请用100字概括量子计算的基本原理和应用前景",
],
)
self.test_wav_list = []
self.wav_root = r"config/assets"
for file_name in os.listdir(self.wav_root):
file_path = os.path.join(self.wav_root, file_name)
# 检查文件大小是否大于300KB
if os.path.getsize(file_path) > 300 * 1024: # 300KB = 300 * 1024 bytes
with open(file_path, "rb") as f:
self.test_wav_list.append(f.read())
self.results = {"llm": {}, "tts": {}, "stt": {}, "combinations": []}
async def _check_ollama_service(self, base_url: str, model_name: str) -> bool:
"""异步检查Ollama服务状态"""
async with aiohttp.ClientSession() as session:
try:
# 检查服务是否可用
async with session.get(f"{base_url}/api/version") as response:
if response.status != 200:
print(f"🚫 Ollama服务未启动或无法访问: {base_url}")
return False
# 检查模型是否存在
async with session.get(f"{base_url}/api/tags") as response:
if response.status == 200:
data = await response.json()
models = data.get("models", [])
if not any(model["name"] == model_name for model in models):
print(
f"🚫 Ollama模型 {model_name} 未找到，请先使用 ollama pull {model_name} 下载"
)
return False
else:
print(f"🚫 无法获取Ollama模型列表")
return False
return True
except Exception as e:
print(f"🚫 无法连接到Ollama服务: {str(e)}")
return False
async def _test_tts(self, tts_name: str, config: Dict) -> Dict:
"""异步测试单个TTS性能"""
try:
logging.getLogger("core.providers.tts.base").setLevel(logging.WARNING)
token_fields = ["access_token", "api_key", "token"]
if any(
field in config
and any(x in config[field] for x in ["你的", "placeholder"])
for field in token_fields
):
print(f"⏭️ TTS {tts_name} 未配置access_token/api_key，已跳过")
return {"name": tts_name, "type": "tts", "errors": 1}
module_type = config.get("type", tts_name)
tts = create_tts_instance(module_type, config, delete_audio_file=True)
print(f"🎵 测试 TTS: {tts_name}")
tmp_file = tts.generate_filename()
await tts.text_to_speak("连接测试", tmp_file)
if not tmp_file or not os.path.exists(tmp_file):
print(f"❌ {tts_name} 连接失败")
return {"name": tts_name, "type": "tts", "errors": 1}
total_time = 0
test_count = len(self.test_sentences[:2])
for i, sentence in enumerate(self.test_sentences[:2], 1):
start = time.time()
tmp_file = tts.generate_filename()
await tts.text_to_speak(sentence, tmp_file)
duration = time.time() - start
total_time += duration
if tmp_file and os.path.exists(tmp_file):
print(f"✓ {tts_name} [{i}/{test_count}]")
else:
print(f"✗ {tts_name} [{i}/{test_count}]")
return {"name": tts_name, "type": "tts", "errors": 1}
return {
"name": tts_name,
"type": "tts",
"avg_time": total_time / test_count,
"errors": 0,
}
except Exception as e:
print(f"⚠️ {tts_name} 测试失败: {str(e)}")
return {"name": tts_name, "type": "tts", "errors": 1}
async def _test_stt(self, stt_name: str, config: Dict) -> Dict:
"""异步测试单个STT性能"""
try:
logging.getLogger("core.providers.asr.base").setLevel(logging.WARNING)
token_fields = ["access_token", "api_key", "token"]
if any(
field in config
and any(x in config[field] for x in ["你的", "placeholder"])
for field in token_fields
):
print(f"⏭️ STT {stt_name} 未配置access_token/api_key，已跳过")
return {"name": stt_name, "type": "stt", "errors": 1}
module_type = config.get("type", stt_name)
stt = create_stt_instance(module_type, config, delete_audio_file=True)
stt.audio_format = "pcm"
print(f"🎵 测试 STT: {stt_name}")
text, _ = await stt.speech_to_text(
[self.test_wav_list[0]], "1", stt.audio_format
)
if text is None:
print(f"❌ {stt_name} 连接失败")
return {"name": stt_name, "type": "stt", "errors": 1}
total_time = 0
test_count = len(self.test_wav_list)
for i, sentence in enumerate(self.test_wav_list, 1):
start = time.time()
text, _ = await stt.speech_to_text([sentence], "1", stt.audio_format)
duration = time.time() - start
total_time += duration
if text:
print(f"✓ {stt_name} [{i}/{test_count}]")
else:
print(f"✗ {stt_name} [{i}/{test_count}]")
return {"name": stt_name, "type": "stt", "errors": 1}
return {
"name": stt_name,
"type": "stt",
"avg_time": total_time / test_count,
"errors": 0,
}
except Exception as e:
print(f"⚠️ {stt_name} 测试失败: {str(e)}")
return {"name": stt_name, "type": "stt", "errors": 1}
async def _test_llm(self, llm_name: str, config: Dict) -> Dict:
"""异步测试单个LLM性能"""
try:
# 对于Ollama，跳过api_key检查并进行特殊处理
if llm_name == "Ollama":
base_url = config.get("base_url", "http://localhost:11434")
model_name = config.get("model_name")
if not model_name:
print(f"🚫 Ollama未配置model_name")
return {"name": llm_name, "type": "llm", "errors": 1}
if not await self._check_ollama_service(base_url, model_name):
return {"name": llm_name, "type": "llm", "errors": 1}
else:
if "api_key" in config and any(
x in config["api_key"] for x in ["你的", "placeholder", "sk-xxx"]
):
print(f"🚫 跳过未配置的LLM: {llm_name}")
return {"name": llm_name, "type": "llm", "errors": 1}
# 获取实际类型（兼容旧配置）
module_type = config.get("type", llm_name)
llm = create_llm_instance(module_type, config)
# 统一使用UTF-8编码
test_sentences = [
s.encode("utf-8").decode("utf-8") for s in self.test_sentences
]
# 创建所有句子的测试任务
sentence_tasks = []
for sentence in test_sentences:
sentence_tasks.append(
self._test_single_sentence(llm_name, llm, sentence)
)
# 并发执行所有句子测试
sentence_results = await asyncio.gather(*sentence_tasks)
# 处理结果
valid_results = [r for r in sentence_results if r is not None]
if not valid_results:
print(f"⚠️ {llm_name} 无有效数据，可能配置错误")
return {"name": llm_name, "type": "llm", "errors": 1}
first_token_times = [r["first_token_time"] for r in valid_results]
response_times = [r["response_time"] for r in valid_results]
# 过滤异常数据
mean = statistics.mean(response_times)
stdev = statistics.stdev(response_times) if len(response_times) > 1 else 0
filtered_times = [t for t in response_times if t <= mean + 3 * stdev]
if len(filtered_times) < len(test_sentences) * 0.5:
print(f"⚠️ {llm_name} 有效数据不足，可能网络不稳定")
return {"name": llm_name, "type": "llm", "errors": 1}
return {
"name": llm_name,
"type": "llm",
"avg_response": sum(response_times) / len(response_times),
"avg_first_token": sum(first_token_times) / len(first_token_times),
"std_first_token": (
statistics.stdev(first_token_times)
if len(first_token_times) > 1
else 0
),
"std_response": (
statistics.stdev(response_times) if len(response_times) > 1 else 0
),
"errors": 0,
}
except Exception as e:
print(f"LLM {llm_name} 测试失败: {str(e)}")
return {"name": llm_name, "type": "llm", "errors": 1}
async def _test_single_sentence(self, llm_name: str, llm, sentence: str) -> Dict:
"""测试单个句子的性能"""
try:
print(f"📝 {llm_name} 开始测试: {sentence[:20]}...")
sentence_start = time.time()
first_token_received = False
first_token_time = None
async def process_response():
nonlocal first_token_received, first_token_time
for chunk in llm.response(
"perf_test", [{"role": "user", "content": sentence}]
):
if not first_token_received and chunk.strip() != "":
first_token_time = time.time() - sentence_start
first_token_received = True
print(f"✓ {llm_name} 首个Token: {first_token_time:.3f}s")
yield chunk
response_chunks = []
async for chunk in process_response():
response_chunks.append(chunk)
response_time = time.time() - sentence_start
print(f"✓ {llm_name} 完成响应: {response_time:.3f}s")
if first_token_time is None:
first_token_time = (
response_time # 如果没有检测到first token，使用总响应时间
)
return {
"name": llm_name,
"type": "llm",
"first_token_time": first_token_time,
"response_time": response_time,
}
except Exception as e:
print(f"⚠️ {llm_name} 句子测试失败: {str(e)}")
return None
def _generate_combinations(self):
"""生成最佳组合建议"""
valid_llms = [
k
for k, v in self.results["llm"].items()
if v["errors"] == 0 and v["avg_first_token"] >= 0.05
]
valid_tts = [k for k, v in self.results["tts"].items() if v["errors"] == 0]
valid_stt = [k for k, v in self.results["stt"].items() if v["errors"] == 0]
# 找出基准值
min_first_token = (
min([self.results["llm"][llm]["avg_first_token"] for llm in valid_llms])
if valid_llms
else 1
)
min_tts_time = (
min([self.results["tts"][tts]["avg_time"] for tts in valid_tts])
if valid_tts
else 1
)
min_stt_time = (
min([self.results["stt"][stt]["avg_time"] for stt in valid_stt])
if valid_stt
else 1
)
for llm in valid_llms:
for tts in valid_tts:
for stt in valid_stt:
# 计算相对性能分数（越小越好）
llm_score = (
self.results["llm"][llm]["avg_first_token"] / min_first_token
)
tts_score = self.results["tts"][tts]["avg_time"] / min_tts_time
stt_score = self.results["stt"][stt]["avg_time"] / min_stt_time
# 计算稳定性分数（标准差/平均值，越小越稳定）
llm_stability = (
self.results["llm"][llm]["std_first_token"]
/ self.results["llm"][llm]["avg_first_token"]
)
# 综合得分（考虑性能和稳定性）
# LLM得分： 性能权重(70%) + 稳定性权重(30%)
llm_final_score = llm_score * 0.7 + llm_stability * 0.3
# 总分 = LLM得分(70%) + TTS得分(30%) + STT得分(30%)
total_score = (
llm_final_score * 0.7 + tts_score * 0.3 + stt_score * 0.3
)
self.results["combinations"].append(
{
"llm": llm,
"tts": tts,
"stt": stt,
"score": total_score,
"details": {
"llm_first_token": self.results["llm"][llm][
"avg_first_token"
],
"llm_stability": llm_stability,
"tts_time": self.results["tts"][tts]["avg_time"],
"stt_time": self.results["stt"][stt]["avg_time"],
},
}
)
# 分数越小越好
self.results["combinations"].sort(key=lambda x: x["score"])
def _print_results(self):
"""打印测试结果"""
llm_table = []
for name, data in self.results["llm"].items():
if data["errors"] == 0:
stability = data["std_first_token"] / data["avg_first_token"]
llm_table.append(
[
name, # 不需要固定宽度，让tabulate自己处理对齐
f"{data['avg_first_token']:.3f}秒",
f"{data['avg_response']:.3f}秒",
f"{stability:.3f}",
]
)
if llm_table:
print("\nLLM 性能排行:\n")
print(
tabulate(
llm_table,
headers=["模型名称", "首字耗时", "总耗时", "稳定性"],
tablefmt="github",
colalign=("left", "right", "right", "right"),
disable_numparse=True,
)
)
else:
print("\n⚠️ 没有可用的LLM模块进行测试。")
tts_table = []
for name, data in self.results["tts"].items():
if data["errors"] == 0:
tts_table.append([name, f"{data['avg_time']:.3f}秒"]) # 不需要固定宽度
if tts_table:
print("\nTTS 性能排行:\n")
print(
tabulate(
tts_table,
headers=["模型名称", "合成耗时"],
tablefmt="github",
colalign=("left", "right"),
disable_numparse=True,
)
)
else:
print("\n⚠️ 没有可用的TTS模块进行测试。")
stt_table = []
for name, data in self.results["stt"].items():
if data["errors"] == 0:
stt_table.append([name, f"{data['avg_time']:.3f}秒"]) # 不需要固定宽度
if stt_table:
print("\nSTT 性能排行:\n")
print(
tabulate(
stt_table,
headers=["模型名称", "合成耗时"],
tablefmt="github",
colalign=("left", "right"),
disable_numparse=True,
)
)
else:
print("\n⚠️ 没有可用的STT模块进行测试。")
if self.results["combinations"]:
print("\n推荐配置组合 (得分越小越好):\n")
combo_table = []
for combo in self.results["combinations"][:]:
combo_table.append(
[
f"{combo['llm']} + {combo['tts']} + {combo['stt']}", # 不需要固定宽度
f"{combo['score']:.3f}",
f"{combo['details']['llm_first_token']:.3f}秒",
f"{combo['details']['llm_stability']:.3f}",
f"{combo['details']['tts_time']:.3f}秒",
f"{combo['details']['stt_time']:.3f}秒",
]
)
print(
tabulate(
combo_table,
headers=[
"组合方案",
"综合得分",
"LLM首字耗时",
"稳定性",
"TTS合成耗时",
"STT合成耗时",
],
tablefmt="github",
colalign=("left", "right", "right", "right", "right", "right"),
disable_numparse=True,
)
)
else:
print("\n⚠️ 没有可用的模块组合建议。")
def _process_results(self, all_results):
"""处理测试结果"""
for result in all_results:
if result["errors"] == 0:
if result["type"] == "llm":
self.results["llm"][result["name"]] = result
elif result["type"] == "tts":
self.results["tts"][result["name"]] = result
elif result["type"] == "stt":
self.results["stt"][result["name"]] = result
else:
pass
async def run(self):
"""执行全量异步测试"""
print("🔍 开始筛选可用模块...")
# 创建所有测试任务
all_tasks = []
# LLM测试任务
if self.config.get("LLM") is not None:
for llm_name, config in self.config.get("LLM", {}).items():
# 检查配置有效性
if llm_name == "CozeLLM":
if any(x in config.get("bot_id", "") for x in ["你的"]) or any(
x in config.get("user_id", "") for x in ["你的"]
):
print(f"⏭️ LLM {llm_name} 未配置bot_id/user_id，已跳过")
continue
elif "api_key" in config and any(
x in config["api_key"] for x in ["你的", "placeholder", "sk-xxx"]
):
print(f"⏭️ LLM {llm_name} 未配置api_key，已跳过")
continue
# 对于Ollama，先检查服务状态
if llm_name == "Ollama":
base_url = config.get("base_url", "http://localhost:11434")
model_name = config.get("model_name")
if not model_name:
print(f"🚫 Ollama未配置model_name")
continue
if not await self._check_ollama_service(base_url, model_name):
continue
print(f"📋 添加LLM测试任务: {llm_name}")
module_type = config.get("type", llm_name)
llm = create_llm_instance(module_type, config)
# 为每个句子创建独立任务
for sentence in self.test_sentences:
sentence = sentence.encode("utf-8").decode("utf-8")
all_tasks.append(
self._test_single_sentence(llm_name, llm, sentence)
)
# TTS测试任务
if self.config.get("TTS") is not None:
for tts_name, config in self.config.get("TTS", {}).items():
token_fields = ["access_token", "api_key", "token"]
if any(
field in config
and any(x in config[field] for x in ["你的", "placeholder"])
for field in token_fields
):
print(f"⏭️ TTS {tts_name} 未配置access_token/api_key，已跳过")
continue
print(f"🎵 添加TTS测试任务: {tts_name}")
all_tasks.append(self._test_tts(tts_name, config))
# STT测试任务
if len(self.test_wav_list) >= 1:
if self.config.get("ASR") is not None:
for stt_name, config in self.config.get("ASR", {}).items():
token_fields = ["access_token", "api_key", "token"]
if any(
field in config
and any(x in config[field] for x in ["你的", "placeholder"])
for field in token_fields
):
print(f"⏭️ ASR {stt_name} 未配置access_token/api_key，已跳过")
continue
print(f"🎵 添加ASR测试任务: {stt_name}")
all_tasks.append(self._test_stt(stt_name, config))
else:
print(f"\n⚠️ {self.wav_root} 路径下没有音频文件，已跳过STT测试任务")
print(
f"\n✅ 找到 {len([t for t in all_tasks if 'test_single_sentence' in str(t)]) / len(self.test_sentences):.0f} 个可用LLM模块"
)
print(
f"✅ 找到 {len([t for t in all_tasks if '_test_tts' in str(t)])} 个可用TTS模块"
)
print(
f"✅ 找到 {len([t for t in all_tasks if '_test_stt' in str(t)])} 个可用STT模块"
)
print("\n⏳ 开始并发测试所有模块...\n")
# 并发执行所有测试任务
all_results = await asyncio.gather(*all_tasks, return_exceptions=True)
# 处理LLM结果
llm_results = {}
for result in [
r
for r in all_results
if r and isinstance(r, dict) and r.get("type") == "llm"
]:
llm_name = result["name"]
if llm_name not in llm_results:
llm_results[llm_name] = {
"name": llm_name,
"type": "llm",
"first_token_times": [],
"response_times": [],
"errors": 0,
}
llm_results[llm_name]["first_token_times"].append(
result["first_token_time"]
)
llm_results[llm_name]["response_times"].append(result["response_time"])
# 计算LLM平均值和标准差
for llm_name, data in llm_results.items():
if len(data["first_token_times"]) >= len(self.test_sentences) * 0.5:
self.results["llm"][llm_name] = {
"name": llm_name,
"type": "llm",
"avg_response": sum(data["response_times"])
/ len(data["response_times"]),
"avg_first_token": sum(data["first_token_times"])
/ len(data["first_token_times"]),
"std_first_token": (
statistics.stdev(data["first_token_times"])
if len(data["first_token_times"]) > 1
else 0
),
"std_response": (
statistics.stdev(data["response_times"])
if len(data["response_times"]) > 1
else 0
),
"errors": 0,
}
# 处理TTS结果
for result in [
r
for r in all_results
if r and isinstance(r, dict) and r.get("type") == "tts"
]:
if result["errors"] == 0:
self.results["tts"][result["name"]] = result
# 处理STT结果
for result in [
r
for r in all_results
if r and isinstance(r, dict) and r.get("type") == "stt"
]:
if result["errors"] == 0:
self.results["stt"][result["name"]] = result
# 生成组合建议并打印结果
print("\n📊 生成测试报告...")
self._generate_combinations()
self._print_results()
async def main():
tester = AsyncPerformanceTester()
await tester.run()
if __name__ == "__main__":
asyncio.run(main())