import json import requests from typing import Optional, Dict, List from app.core.config import LLM_CONFIG, QWEN_API_KEY from app.core.database import get_db_connection class LLMService: def __init__(self): self.api_key = QWEN_API_KEY self.model_name = LLM_CONFIG["model_name"] self.api_url = LLM_CONFIG["api_url"] self.system_prompt = LLM_CONFIG["system_prompt"] self.max_tokens = LLM_CONFIG["max_tokens"] self.temperature = LLM_CONFIG["temperature"] self.top_p = LLM_CONFIG["top_p"] def generate_meeting_summary(self, meeting_id: int, user_prompt: str = "") -> Optional[Dict]: """ 生成会议总结 Args: meeting_id: 会议ID user_prompt: 用户额外提示词 Returns: 包含总结内容的字典，如果失败返回None """ try: # 获取会议转录内容 transcript_text = self._get_meeting_transcript(meeting_id) if not transcript_text: return {"error": "无法获取会议转录内容"} # 构建完整提示词 full_prompt = self._build_prompt(transcript_text, user_prompt) # 调用大模型API response = self._call_llm_api(full_prompt) if response: # 保存总结到数据库 summary_id = self._save_summary_to_db(meeting_id, response, user_prompt) return { "summary_id": summary_id, "content": response, "meeting_id": meeting_id } else: return {"error": "大模型API调用失败"} except Exception as e: print(f"生成会议总结错误: {e}") return {"error": str(e)} def _get_meeting_transcript(self, meeting_id: int) -> str: """从数据库获取会议转录内容""" try: with get_db_connection() as connection: cursor = connection.cursor() query = """ SELECT speaker_tag, start_time_ms, end_time_ms, text_content FROM transcript_segments WHERE meeting_id = %s ORDER BY start_time_ms """ cursor.execute(query, (meeting_id,)) segments = cursor.fetchall() if not segments: return "" # 组装转录文本 transcript_lines = [] for speaker_tag, start_time, end_time, text in segments: # 将毫秒转换为分:秒格式 start_min = start_time // 60000 start_sec = (start_time % 60000) // 1000 transcript_lines.append(f"[{start_min:02d}:{start_sec:02d}] 说话人{speaker_tag}: {text}") return "\n".join(transcript_lines) except Exception as e: print(f"获取会议转录内容错误: {e}") return "" def _build_prompt(self, transcript_text: str, user_prompt: str) -> str: """构建完整的提示词""" prompt = f"{self.system_prompt}\n\n" if user_prompt: prompt += f"用户额外要求：{user_prompt}\n\n" prompt += f"会议转录内容：\n{transcript_text}\n\n请根据以上内容生成会议总结：" return prompt def _call_llm_api(self, prompt: str) -> Optional[str]: """调用阿里Qwen3大模型API""" headers = { "Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json" } data = { "model": self.model_name, "input": { "messages": [ { "role": "user", "content": prompt } ] }, "parameters": { "max_tokens": self.max_tokens, "temperature": self.temperature, "top_p": self.top_p, "incremental_output": False } } try: response = requests.post(self.api_url, headers=headers, json=data, timeout=60) response.raise_for_status() result = response.json() # 处理阿里Qwen API的响应格式 if result.get("output") and result["output"].get("text"): return result["output"]["text"] elif result.get("output") and result["output"].get("choices"): return result["output"]["choices"][0]["message"]["content"] else: print(f"API响应格式错误: {result}") return None except requests.exceptions.RequestException as e: print(f"API请求错误: {e}") return None except json.JSONDecodeError as e: print(f"JSON解析错误: {e}") return None except Exception as e: print(f"调用大模型API错误: {e}") return None def _save_summary_to_db(self, meeting_id: int, summary_content: str, user_prompt: str) -> Optional[int]: """保存总结到数据库 - 更新meetings表的summary字段""" try: with get_db_connection() as connection: cursor = connection.cursor() # 更新meetings表的summary字段 update_query = """ UPDATE meetings SET summary = %s WHERE meeting_id = %s """ cursor.execute(update_query, (summary_content, meeting_id)) connection.commit() print(f"成功保存会议总结到meetings表，meeting_id: {meeting_id}") return meeting_id except Exception as e: print(f"保存总结到数据库错误: {e}") return None def get_meeting_summaries(self, meeting_id: int) -> List[Dict]: """获取会议的当前总结 - 从meetings表的summary字段获取""" try: with get_db_connection() as connection: cursor = connection.cursor() query = """ SELECT summary FROM meetings WHERE meeting_id = %s """ cursor.execute(query, (meeting_id,)) result = cursor.fetchone() # 如果有总结内容，返回一个包含当前总结的列表格式（保持API一致性） if result and result[0]: return [{ "id": meeting_id, "content": result[0], "user_prompt": "", # meetings表中没有user_prompt字段 "created_at": None # meetings表中没有单独的总结创建时间 }] else: return [] except Exception as e: print(f"获取会议总结错误: {e}") return [] def get_current_meeting_summary(self, meeting_id: int) -> Optional[str]: """获取会议当前的总结内容 - 从meetings表的summary字段获取""" try: with get_db_connection() as connection: cursor = connection.cursor() query = """ SELECT summary FROM meetings WHERE meeting_id = %s """ cursor.execute(query, (meeting_id,)) result = cursor.fetchone() return result[0] if result and result[0] else None except Exception as e: print(f"获取会议当前总结错误: {e}") return None # 测试代码 if __name__ == '__main__': # 测试LLM服务 test_meeting_id = 38 test_user_prompt = "请重点关注决策事项和待办任务" print("--- 运行LLM服务测试 ---") llm_service = LLMService() # 生成总结 result = llm_service.generate_meeting_summary(test_meeting_id, test_user_prompt) if result.get("error"): print(f"生成总结失败: {result['error']}") else: print(f"总结生成成功，ID: {result.get('summary_id')}") print(f"总结内容: {result.get('content')[:200]}...") # 获取历史总结 summaries = llm_service.get_meeting_summaries(test_meeting_id) print(f"获取到 {len(summaries)} 个历史总结") print("--- LLM服务测试完成 ---")