"""AI-backed sentence explanations for the mobile clients.""" from dataclasses import dataclass import requests class AITutorError(RuntimeError): """Raised when the configured AI service cannot answer a request.""" @dataclass(frozen=True) class AITutor: endpoint: str api_key: str model: str timeout_seconds: float @property def available(self) -> bool: return bool(self.endpoint and self.model) def explain( self, sentence_text: str, *, course_title: str = "", sentence_index: int | None = None, language: str = "", ) -> str: if not self.available: raise AITutorError("AI explanation is not configured.") context = course_title.strip() or "口语训练课程" position = f"第 {sentence_index + 1} 句" if sentence_index is not None else "当前句子" language_note = f"句子语言:{language.strip()}。" if language.strip() else "" system_prompt = ( "你是一位耐心的外语口语老师。请用简体中文讲解用户提供的影视/课程句子。" "先给出自然的中文翻译,再解释关键词、常用搭配或语法要点,并简要说明这句话适合怎样跟读。" "回答使用简明清晰的分段短文,总长度不超过 300 字,不要编造视频里没有的信息。" ) user_prompt = ( f"课程:{context}\n位置:{position}\n{language_note}句子:{sentence_text}" ) headers = {"Content-Type": "application/json"} if self.api_key: headers["Authorization"] = f"Bearer {self.api_key}" try: response = requests.post( self.endpoint, headers=headers, json={ "model": self.model, "messages": [ {"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt}, ], "temperature": 0.3, "stream": False, }, timeout=self.timeout_seconds, ) except requests.RequestException as exc: raise AITutorError("AI service request failed.") from exc if response.status_code < 200 or response.status_code >= 300: raise AITutorError(f"AI service returned HTTP {response.status_code}.") try: body = response.json() explanation = body["choices"][0]["message"]["content"] except (KeyError, IndexError, TypeError, ValueError) as exc: raise AITutorError("AI service returned an unexpected response.") from exc if not isinstance(explanation, str) or not explanation.strip(): raise AITutorError("AI service returned an empty explanation.") return explanation.strip()