96 lines
2.9 KiB
Python
96 lines
2.9 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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测试大语言模型API功能
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"""
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import os
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import requests
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import json
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def test_llm_api():
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"""测试大语言模型API"""
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# 检查API密钥
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api_key = os.environ.get("ARK_API_KEY")
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if not api_key:
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print("❌ 未设置 ARK_API_KEY 环境变量")
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return False
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print(f"✅ API密钥已设置: {api_key[:20]}...")
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# API配置
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api_url = "https://ark.cn-beijing.volces.com/api/v3/chat/completions"
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model = "doubao-1-5-pro-32k-250115"
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# 测试消息
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test_message = "你好，请简单介绍一下自己"
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try:
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print("🤖 测试大语言模型API...")
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}"
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}
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data = {
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"model": model,
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"messages": [
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{
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"role": "system",
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"content": "你是一个智能助手，请根据用户的语音输入提供有帮助的回答。保持回答简洁明了。"
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},
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{
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"role": "user",
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"content": test_message
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}
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]
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}
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response = requests.post(api_url, headers=headers, json=data, timeout=30)
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print(f"📡 HTTP状态码: {response.status_code}")
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if response.status_code == 200:
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result = response.json()
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print("✅ API调用成功")
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if "choices" in result and len(result["choices"]) > 0:
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llm_response = result["choices"][0]["message"]["content"]
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print(f"💬 AI回复: {llm_response}")
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# 显示完整响应结构
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print("\n📋 完整响应结构:")
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print(json.dumps(result, indent=2, ensure_ascii=False))
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return True
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else:
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print("❌ 响应格式错误")
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print(f"响应内容: {response.text}")
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return False
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else:
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print(f"❌ API调用失败: {response.status_code}")
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print(f"响应内容: {response.text}")
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return False
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except requests.exceptions.RequestException as e:
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print(f"❌ 网络请求失败: {e}")
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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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if __name__ == "__main__":
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print("🧪 测试大语言模型API功能")
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print("=" * 50)
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success = test_llm_api()
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if success:
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print("\n✅ 大语言模型功能测试通过！")
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print("🚀 现在可以运行完整的语音助手系统了")
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else:
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print("\n❌ 大语言模型功能测试失败")
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print("🔧 请检查API密钥和网络连接") |