qwenasr-qwen36-voxcmp2 base model. -2026/05/14 night

llm_server/test.py

@@ -0,0 +1,148 @@
+#!/usr/bin/env python3
+"""
+语音服务功能测试：ASR 识别 + TTS 合成
+"""
+import requests
+import json
+import os
+import sys
+import time
+
+HOST = "http://127.0.0.1:8100"
+
+def test_health():
+    """1. 健康检查"""
+    print("=" * 50)
+    print("📋 健康检查")
+    print("=" * 50)
+    resp = requests.get(f"{HOST}/health")
+    print(f"状态码: {resp.status_code}")
+    print(f"模型列表: {resp.json()}")
+    assert resp.status_code == 200
+    assert "asr" in resp.json()["models"]
+    assert "tts" in resp.json()["models"]
+    print("✅ 健康检查通过\n")
+
+def test_asr(audio_path=None):
+    """2. 测试语音识别"""
+    print("=" * 50)
+    print("🎤 语音识别测试")
+    print("=" * 50)
+    
+    if audio_path is None:
+        # 如果没有本地音频，下载一个公开示例
+        import tempfile
+        audio_path = tempfile.mktemp(suffix=".wav")
+        url = "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-ASR-Repo/asr_zh.wav"
+        print(f"下载测试音频: {url}")
+        import subprocess
+        subprocess.run(["wget", "-q", url, "-O", audio_path], check=True)
+    
+    print(f"音频文件: {audio_path}")
+    with open(audio_path, "rb") as f:
+        resp = requests.post(f"{HOST}/asr", files={"file": f})
+    
+    print(f"状态码: {resp.status_code}")
+    result = resp.json()
+    print(f"识别结果: {result.get('text', 'N/A')}")
+    assert resp.status_code == 200
+    assert len(result.get("text", "")) > 0
+    print("✅ 语音识别通过\n")
+    return result["text"]
+
+def test_tts(text="(激动地说)你好世界，这是一段测试语音", output="test_output.wav"):
+    """3. 测试语音合成"""
+    print("=" * 50)
+    print("🔊 语音合成测试")
+    print("=" * 50)
+    print(f"合成文本: {text}")
+    
+    start_time = time.time()
+    resp = requests.get(f"{HOST}/tts", params={"text": text})
+    elapsed = time.time() - start_time
+    
+    print(f"状态码: {resp.status_code}")
+    print(f"耗时: {elapsed:.2f}秒")
+    
+    if resp.status_code == 200:
+        with open(output, "wb") as f:
+            f.write(resp.content)
+        file_size = os.path.getsize(output) / 1024  # KB
+        print(f"音频已保存: {output} ({file_size:.1f} KB)")
+    else:
+        print(f"错误: {resp.text}")
+    
+    assert resp.status_code == 200
+    assert os.path.exists(output)
+    print("✅ 语音合成通过\n")
+
+def test_asr_english():
+    """4. 测试英文识别"""
+    print("=" * 50)
+    print("🌍 英文识别测试")
+    print("=" * 50)
+    
+    import tempfile
+    audio_path = tempfile.mktemp(suffix=".wav")
+    url = "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-ASR-Repo/asr_en.wav"
+    print(f"下载英文测试音频: {url}")
+    import subprocess
+    subprocess.run(["wget", "-q", url, "-O", audio_path], check=True)
+    
+    with open(audio_path, "rb") as f:
+        resp = requests.post(f"{HOST}/asr", files={"file": f})
+    
+    print(f"状态码: {resp.status_code}")
+    result = resp.json()
+    print(f"识别结果: {result.get('text', 'N/A')}")
+    assert resp.status_code == 200
+    assert len(result.get("text", "")) > 0
+    print("✅ 英文识别通过\n")
+
+def test_tts_long_text():
+    """5. 测试长文本合成"""
+    print("=" * 50)
+    print("📜 长文本合成测试")
+    print("=" * 50)
+    
+    long_text = """人工智能是计算机科学的一个分支，它企图了解智能的实质，
+    并生产出一种新的能以人类智能相似的方式做出反应的智能机器，
+    该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等。"""
+    
+    print(f"文本长度: {len(long_text)} 字")
+    start_time = time.time()
+    resp = requests.get(f"{HOST}/tts", params={"text": long_text})
+    elapsed = time.time() - start_time
+    
+    print(f"状态码: {resp.status_code}")
+    print(f"耗时: {elapsed:.2f}秒")
+    
+    if resp.status_code == 200:
+        output = "test_long_output.wav"
+        with open(output, "wb") as f:
+            f.write(resp.content)
+        file_size = os.path.getsize(output) / 1024
+        print(f"音频已保存: {output} ({file_size:.1f} KB)")
+    
+    assert resp.status_code == 200
+    print("✅ 长文本合成通过\n")
+
+if __name__ == "__main__":
+    print("\n" + "🚀 开始测试语音服务".center(50, "="))
+    print(f"服务地址: {HOST}\n")
+    
+    try:
+        test_health()
+        
+        # 可选：用自己的音频文件测试
+        # test_asr("/path/to/your/audio.wav")
+        test_asr()
+        test_asr_english()
+        
+        test_tts()
+        test_tts_long_text()
+        
+        print("\n" + "🎉 所有测试通过！".center(50, "="))
+    except Exception as e:
+        print(f"\n❌ 测试失败: {e}")
+        sys.exit(1)