Method calc

src/evals/base_evalution.py:23–34

开始计算结果

(self)

            raise BaseException(f"must be ToolModel Class! not {model}")
            
    def calc(self):
        '''开始计算结果'''
        self.predicts = []
        for idx, data in enumerate(self.dataset):
            # if idx >= 5: break
            prompt = self.base_prompt.format(**data)
            answer = data["api_param"]
            predict = self.generate(prompt, self.generate_configs)
            self.predicts.append({"prompt": prompt, "predict": predict, "answer": answer})
        
        metric = self.eval_metric(self.predicts)
        return metric
        
    def generate(self, prompt, generate_configs):
        '''返回结果'''