refactor(schema): 修改 LLMResponse 中 API 响应内容的字段名称

- 将 LLMResponse 类中的 response_content 字段重命名为 content
- 更新字段类型从 dict 改为 str，以更准确地表示响应内容
- 在 reasoning.py 中相应地修改了调用 LLMResponse 时的参数

schema/dataset_generation.py

@@ -33,7 +33,7 @@ class LLMResponse(SQLModel):
     )
     response_id: str = Field(..., description="响应的唯一ID")
     tokens_usage: TokensUsage = Field(default_factory=TokensUsage, description="token使用信息")
-    response_content: dict = Field(default_factory=dict, description="API响应的内容")
+    content: str = Field(default_factory=dict, description="API响应的内容")
     total_duration: float = Field(default=0.0, description="请求的总时长，单位为秒")
     llm_parameters: Optional[LLMParameters] = Field(default=None, description="LLM参数")
 

tools/reasoning.py

@@ -68,7 +68,7 @@ async def call_openai_api(llm_request: LLMRequest, rounds: int = 1, llm_paramete
             llm_request.response.append(LLMResponse(
                 response_id=response.id,
                 tokens_usage=tokens_usage,
-                response_content={"content": response.choices[0].message.content},
+                content = response.choices[0].message.content,
                 total_duration=duration,
                 llm_parameters=llm_parameters
             ))
@@ -79,7 +79,7 @@ async def call_openai_api(llm_request: LLMRequest, rounds: int = 1, llm_paramete
             
             llm_request.response.append(LLMResponse(
                 response_id=f"error-round-{i+1}",
-                response_content={"error": str(e)},
+                content={"error": str(e)},
                 total_duration=duration
             ))
             if llm_request.error is None:
@@ -120,4 +120,4 @@ if __name__ == "__main__":
     print(f"\n3次调用结果 - 总耗时: {result.total_duration:.2f}s")
     print(f"总token使用: prompt={result.total_tokens_usage.prompt_tokens}, completion={result.total_tokens_usage.completion_tokens}")
     for i, resp in enumerate(result.response, 1):
-        print(f"响应{i}: {resp.response_content}")
+        print(f"响应{i}: {resp.content}")