97 lines
3.0 KiB
Python
97 lines
3.0 KiB
Python
#!/usr/bin/env python3
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"""
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测试 DashScope ASR 功能
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"""
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import os
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from dotenv import load_dotenv
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# 加载环境变量
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load_dotenv()
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def test_dashscope_asr():
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"""测试 DashScope ASR"""
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try:
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from dashscope.audio.asr import Transcription
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import dashscope
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api_key = os.getenv('DASHSCOPE_API_KEY')
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if not api_key:
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print("❌ 未配置 DASHSCOPE_API_KEY")
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return False
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dashscope.api_key = api_key
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print(f"🔧 DashScope API Key: {api_key[:20]}...")
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# 使用一个公开的测试音频 URL
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test_url = "https://hello12312312.oss-cn-hangzhou.aliyuncs.com/voice_call/test_access.mp3"
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print(f"🎵 测试 URL: {test_url}")
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# 测试不同的模型
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models = [
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'paraformer-v2',
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'paraformer-realtime-v2',
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'whisper-1'
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]
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for model in models:
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try:
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print(f"\n🔍 测试模型: {model}")
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task_response = Transcription.async_call(
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model=model,
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file_urls=[test_url]
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)
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print(f"📊 任务响应状态: {task_response.status_code}")
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print(f"📋 任务响应: {task_response}")
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if task_response.status_code == 200:
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task_id = task_response.output.task_id
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print(f"✅ 任务创建成功: {task_id}")
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# 等待结果
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print(f"⏳ 等待识别结果...")
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result = Transcription.wait(task=task_id)
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print(f"📊 识别结果状态: {result.status_code}")
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print(f"📋 识别结果: {result}")
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if result.status_code == 200:
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print(f"✅ 模型 {model} 识别成功！")
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return True
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else:
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print(f"❌ 模型 {model} 识别失败")
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else:
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print(f"❌ 模型 {model} 任务创建失败")
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except Exception as e:
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print(f"❌ 模型 {model} 测试异常: {e}")
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continue
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return False
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except ImportError:
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print("❌ dashscope 模块未安装，请运行: pip install dashscope")
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return False
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except Exception as e:
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print(f"❌ 测试失败: {e}")
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return False
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def main():
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print("🚀 开始测试 DashScope ASR...")
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if test_dashscope_asr():
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print("🎉 DashScope ASR 测试成功！")
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else:
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print("💥 DashScope ASR 测试失败！")
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print("\n🔧 可能的原因:")
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print("1. API Key 无效或余额不足")
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print("2. 模型名称不正确")
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print("3. 文件格式不支持")
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print("4. 网络连接问题")
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if __name__ == "__main__":
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main() |