From 599b3cded704d254168ef644589a33afd581597a Mon Sep 17 00:00:00 2001 From: jeremygan2021 Date: Wed, 11 Mar 2026 21:08:47 +0800 Subject: [PATCH] tingwu_new --- backend/ai_services/bailian_service.py | 54 ++++++++++++++- backend/ai_services/services.py | 93 +++----------------------- 2 files changed, 62 insertions(+), 85 deletions(-) diff --git a/backend/ai_services/bailian_service.py b/backend/ai_services/bailian_service.py index b9ecef5..442beb5 100644 --- a/backend/ai_services/bailian_service.py +++ b/backend/ai_services/bailian_service.py @@ -93,6 +93,54 @@ class BailianService: except Exception as e: logger.error(f"AI Evaluation failed: {e}") evaluation.status = AIEvaluation.Status.FAILED - evaluation.error_message = str(e) - evaluation.save() - return evaluation + evaluation.error_message = str(e) + evaluation.save() + return evaluation + + def summarize_task(self, task): + """ + 使用 AI 模型总结转写和章节数据 + """ + if not self.client: + logger.error("DashScope client not initialized") + return + + try: + summary_data = json.dumps(task.summary_data or {}, ensure_ascii=False) + chapters_data = json.dumps(task.auto_chapters_data or {}, ensure_ascii=False) + + prompt = f""" +你是一个专业的会议摘要和内容分析助手。请根据以下提供的“总结原始数据”和“章节原始数据”，生成一个结构清晰、专业且易于阅读的 Markdown 格式总结。 + +要求： +1. 包含一个总体的“核心摘要”。 +2. 包含一个详细的“内容大纲”。 +3. 如果有问答或对话信息，请包含“关键问答”或“发言人观点”。 +4. 包含一个带有时间戳的“章节回顾”，格式为 [HH:MM:SS] 标题。 +5. 语言简练，重点突出。 + +总结原始数据： +{summary_data} + +章节原始数据： +{chapters_data} +""" + messages = [ + {'role': 'system', 'content': '你是一个专业的文档总结助手。请直接返回 Markdown 格式的内容，不要包含任何引导性文字。'}, + {'role': 'user', 'content': prompt} + ] + + completion = self.client.chat.completions.create( + model="qwen-turbo", + messages=messages, + temperature=0.7 + ) + + ai_summary = completion.choices[0].message.content + if ai_summary: + task.summary = ai_summary + task.save() + logger.info(f"AI summary generated for task {task.id}") + + except Exception as e: + logger.error(f"Failed to generate AI summary: {e}") diff --git a/backend/ai_services/services.py b/backend/ai_services/services.py index 0c485d7..3f8053a 100644 --- a/backend/ai_services/services.py +++ b/backend/ai_services/services.py @@ -272,63 +272,8 @@ class AliyunTingwuService: # 提取文本 (MindMapSummary) # 结构: {"MindMapSummary": [{"Title": "...", "Topic": [...]}]} - summary_text = [] + # 移除了原先的 summary_text 拼接逻辑 - # 1. 优先提取段落标题和摘要 - if 'ParagraphTitle' in summarization: - summary_text.append(f"### {summarization['ParagraphTitle']}") - if 'ParagraphSummary' in summarization: - summary_text.append(summarization['ParagraphSummary']) - summary_text.append("") # 空行分隔 - - # 2. 提取思维导图作为大纲 - def parse_mindmap_topic(topic_list, level=0): - indent = " " * level - for topic in topic_list: - title = topic.get('Title', '') - if title: - summary_text.append(f"{indent}- {title}") - - sub_topics = topic.get('Topic', []) - if sub_topics: - parse_mindmap_topic(sub_topics, level + 1) - - if 'MindMapSummary' in summarization: - summary_text.append("### 内容大纲") - parse_mindmap_topic(summarization['MindMapSummary']) - summary_text.append("") - - # 3. 提取对话总结 (ConversationalSummary) - if 'ConversationalSummary' in summarization and isinstance(summarization['ConversationalSummary'], list): - summary_text.append("### 对话总结") - for conv in summarization['ConversationalSummary']: - speaker = conv.get('SpeakerName', '发言人') - summary = conv.get('Summary', '') - if summary: - summary_text.append(f"- **{speaker}**: {summary}") - summary_text.append("") - - # 4. 提取问答总结 (QuestionsAnsweringSummary) - if 'QuestionsAnsweringSummary' in summarization and isinstance(summarization['QuestionsAnsweringSummary'], list): - summary_text.append("### 问答回顾") - for qa in summarization['QuestionsAnsweringSummary']: - question = qa.get('Question', '') - answer = qa.get('Answer', '') - if question and answer: - summary_text.append(f"**Q: {question}**") - summary_text.append(f"A: {answer}") - summary_text.append("") - - # 兼容旧逻辑：如果上述都为空，尝试 Text 或 Headline - if not summary_text: - if 'Text' in summarization: - summary_text.append(summarization['Text']) - elif 'Headline' in summarization: - summary_text.append(summarization['Headline']) - - if summary_text: - task.summary = "\n".join(summary_text) - # --- C. 处理章节 (AutoChapters) --- auto_chapters = get_data_field(task_result, 'AutoChapters') or get_data_field(data_obj, 'AutoChapters') or [] @@ -346,34 +291,18 @@ class AliyunTingwuService: # 保存原始数据 task.auto_chapters_data = auto_chapters - # 将章节信息追加到 summary - if auto_chapters and isinstance(auto_chapters, list): - if summary_text: - summary_text.append("\n\n### 章节速览") - else: - summary_text.append("### 章节速览") - - for chapter in auto_chapters: - headline = chapter.get('Headline', '') - summary = chapter.get('Summary', '') - start_time = chapter.get('Start', 0) - - # 格式化时间戳 (毫秒 -> HH:MM:SS) - seconds = int(start_time / 1000) - m, s = divmod(seconds, 60) - h, m = divmod(m, 60) - time_str = f"{h:02d}:{m:02d}:{s:02d}" - - chapter_text = f"- [{time_str}] {headline}" - if summary: - chapter_text += f"\n {summary}" - summary_text.append(chapter_text) - - if summary_text: - task.summary = "\n".join(summary_text) - + # 保存任务，确保原始数据已写入数据库 task.save() + # 调用大模型生成总结 (如果 summary_data 或 auto_chapters_data 存在) + if task.summary_data or task.auto_chapters_data: + try: + from .bailian_service import BailianService + bailian_service = BailianService() + bailian_service.summarize_task(task) + except Exception as e: + logger.error(f"Failed to trigger AI summarization: {e}") + # 4. 自动触发 AI 评估 (如果任务首次成功且有启用的模板) if previous_status != 'SUCCEEDED' and task.status == 'SUCCEEDED' and task.transcription: self.trigger_ai_evaluations(task)