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+"""
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+Qwen LLM provider using OpenAI SDK.
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+"""
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+
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+import os
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+import logging
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+from typing import Any, Callable, Dict, List, Optional
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+from openai import AsyncOpenAI
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+
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+# 这里的导入根据你的项目结构调整
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+from .usage import TokenUsage
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+from .pricing import PricingCalculator
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+
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+logger = logging.getLogger(__name__)
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+
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+# 2026 推荐：如果 qwen3.5-plus 报 404，请先用 qwen-plus 测试
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+# 阿里有时要求兼容模式下的 ID 必须是特定的字符串
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+DEFAULT_QWEN_MODEL = "qwen-plus"
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+
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+def create_qwen_llm_call(
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+ model: str = DEFAULT_QWEN_MODEL,
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+ base_url: Optional[str] = None,
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+ api_key: Optional[str] = None,
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+) -> Callable:
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+ """
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+ Create a Qwen LLM call function using the OpenAI SDK.
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+ """
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+ # 获取配置
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+ # 注意：使用 OpenAI SDK 时，base_url 必须包含到 /v1
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+ api_key = api_key or os.getenv("QWEN_API_KEY")
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+ base_url = base_url or os.getenv("QWEN_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1")
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+
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+ if not api_key:
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+ raise ValueError("QWEN_API_KEY is required")
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+
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+ # 初始化 OpenAI 异步客户端
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+ # SDK 会自动处理 /chat/completions 的拼接
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+ client = AsyncOpenAI(
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+ api_key=api_key,
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+ base_url=base_url
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+ )
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+
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+ pricing_calc = PricingCalculator()
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+
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+ async def llm_call(
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+ messages: List[Dict[str, Any]],
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+ model: str = model,
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+ tools: Optional[List[Dict]] = None,
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+ temperature: float = 0.7,
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+ max_tokens: int = 4096,
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+ **kwargs
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+ ) -> Dict[str, Any]:
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+
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+ try:
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+ response = await client.chat.completions.create(
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+ model=model,
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+ messages=messages,
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+ tools=tools,
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+ temperature=temperature,
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+ max_tokens=max_tokens,
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+ **kwargs
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+ )
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+
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+ # 获取内容
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+ content = response.choices[0].message.content or ""
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+
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+ # --- 关键修正位置 ---
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+ # 将 Pydantic 对象转换为原始 Dict 列表，这样 runner.py 的 .get() 才不会报错
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+ tool_calls = None
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+ if response.choices[0].message.tool_calls:
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+ tool_calls = [
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+ tc.model_dump() for tc in response.choices[0].message.tool_calls
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+ ]
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+ # ------------------
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+
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+ usage = TokenUsage(
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+ input_tokens=response.usage.prompt_tokens,
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+ output_tokens=response.usage.completion_tokens,
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+ )
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+
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+ cost = pricing_calc.calculate_cost(model=model, usage=usage)
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+
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+ return {
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+ "content": content,
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+ "tool_calls": tool_calls, # 现在这里是 List[Dict] 了
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+ "prompt_tokens": usage.input_tokens,
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+ "completion_tokens": usage.output_tokens,
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+ "reasoning_tokens": getattr(response.usage, "reasoning_tokens", 0),
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+ "finish_reason": response.choices[0].finish_reason,
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+ "cost": cost,
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+ "usage": usage,
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+ }
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+
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+ except Exception as e:
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+ logger.error(f"Qwen SDK Call Failed: {str(e)}")
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+ raise
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+
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+ return llm_call
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guantao