tingwu_new

backend/ai_services/admin.py

@@ -1,16 +1,16 @@
 from django.contrib import admin
 from unfold.admin import ModelAdmin as UnfoldModelAdmin
 from unfold.admin import StackedInline as UnfoldStackedInline
-from .models import TranscriptionTask, AIEvaluation
+from .models import TranscriptionTask, AIEvaluation, AIEvaluationTemplate
 
 class AIEvaluationInline(UnfoldStackedInline):
     model = AIEvaluation
     extra = 0
-    can_delete = False
-    verbose_name = "AI评估"
-    verbose_name_plural = "AI评估"
-    readonly_fields = ['created_at', 'updated_at', 'raw_response', 'reasoning']
-    fields = ('score', 'evaluation', 'model_selection', 'prompt', 'reasoning', 'status', 'error_message')
+    can_delete = True
+    verbose_name = "AI评估结果"
+    verbose_name_plural = "AI评估结果"
+    readonly_fields = ['created_at', 'updated_at', 'raw_response', 'reasoning', 'template']
+    fields = ('template', 'score', 'evaluation', 'model_selection', 'prompt', 'reasoning', 'status', 'error_message')
 
 @admin.register(TranscriptionTask)
 class TranscriptionTaskAdmin(UnfoldModelAdmin):
@@ -20,17 +20,23 @@ class TranscriptionTaskAdmin(UnfoldModelAdmin):
     readonly_fields = ['id', 'created_at', 'updated_at', 'task_id']
     inlines = [AIEvaluationInline]
 
+@admin.register(AIEvaluationTemplate)
+class AIEvaluationTemplateAdmin(UnfoldModelAdmin):
+    list_display = ['name', 'model_selection', 'is_active', 'created_at']
+    list_filter = ['is_active', 'model_selection', 'created_at']
+    search_fields = ['name', 'prompt']
+
 @admin.register(AIEvaluation)
 class AIEvaluationAdmin(UnfoldModelAdmin):
-    list_display = ['id', 'task', 'score', 'status', 'model_selection', 'created_at']
-    list_filter = ['status', 'model_selection', 'created_at']
+    list_display = ['id', 'task', 'template', 'score', 'status', 'model_selection', 'created_at']
+    list_filter = ['status', 'model_selection', 'created_at', 'template']
     search_fields = ['task__id', 'evaluation', 'reasoning']
     readonly_fields = ['id', 'created_at', 'updated_at', 'raw_response']
     fieldsets = (
         (None, {
-            'fields': ('task', 'status', 'score', 'evaluation')
+            'fields': ('task', 'template', 'status', 'score', 'evaluation')
         }),
-        ('配置', {
+        ('配置快照', {
             'fields': ('model_selection', 'prompt'),
             'classes': ('collapse',),
         }),

backend/ai_services/migrations/0005_aievaluationtemplate_alter_aievaluation_options_and_more.py

@@ -0,0 +1,55 @@
+# Generated by Django 6.0.1 on 2026-03-11 13:00
+
+import django.db.models.deletion
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('ai_services', '0004_remove_transcriptiontask_evaluation_and_more'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='AIEvaluationTemplate',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('name', models.CharField(help_text='例如：销售话术评分、逻辑性分析', max_length=100, verbose_name='模板名称')),
+                ('model_selection', models.CharField(default='qwen-plus', help_text='例如: qwen-plus, qwen-turbo, qwen-max', max_length=50, verbose_name='模型选择')),
+                ('prompt', models.TextField(default='你是一个专业的评分助手。请根据提供的转写内容，对内容质量、逻辑清晰度、语言表达等方面进行综合评分（0-100分），并给出详细的评语。请以JSON格式返回，包含"score"和"evaluation"字段。', help_text='用于指导AI评分的提示词', verbose_name='评分提示词')),
+                ('is_active', models.BooleanField(default=True, help_text='启用后，新的转写任务完成后将自动使用此模板进行评估', verbose_name='是否启用')),
+                ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='创建时间')),
+                ('updated_at', models.DateTimeField(auto_now=True, verbose_name='更新时间')),
+            ],
+            options={
+                'verbose_name': 'AI评估模板',
+                'verbose_name_plural': 'AI评估模板',
+                'ordering': ['-created_at'],
+            },
+        ),
+        migrations.AlterModelOptions(
+            name='aievaluation',
+            options={'ordering': ['-created_at'], 'verbose_name': 'AI评估结果', 'verbose_name_plural': 'AI评估结果'},
+        ),
+        migrations.AlterField(
+            model_name='aievaluation',
+            name='model_selection',
+            field=models.CharField(default='qwen-plus', max_length=50, verbose_name='模型选择'),
+        ),
+        migrations.AlterField(
+            model_name='aievaluation',
+            name='prompt',
+            field=models.TextField(verbose_name='评分提示词'),
+        ),
+        migrations.AlterField(
+            model_name='aievaluation',
+            name='task',
+            field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='ai_evaluations', to='ai_services.transcriptiontask', verbose_name='关联任务'),
+        ),
+        migrations.AddField(
+            model_name='aievaluation',
+            name='template',
+            field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='evaluations', to='ai_services.aievaluationtemplate', verbose_name='使用的模板'),
+        ),
+    ]

backend/ai_services/models.py

@@ -43,25 +43,8 @@ class TranscriptionTask(models.Model):
         return f"{self.id} - {self.get_status_display()}"
 
 
-class AIEvaluation(models.Model):
-    class Status(models.TextChoices):
-        PENDING = 'PENDING', _('等待中')
-        PROCESSING = 'PROCESSING', _('生成中')
-        COMPLETED = 'COMPLETED', _('已完成')
-        FAILED = 'FAILED', _('失败')
-
-    task = models.OneToOneField(
-        TranscriptionTask, 
-        on_delete=models.CASCADE, 
-        related_name='ai_evaluation',
-        verbose_name=_('关联任务')
-    )
-    
-    # 评分与评语
-    score = models.IntegerField(verbose_name=_('AI评分'), blank=True, null=True, help_text=_('0-100分'))
-    evaluation = models.TextField(verbose_name=_('AI评语'), blank=True, null=True)
-    
-    # 配置选项 (可在Admin中设置)
+class AIEvaluationTemplate(models.Model):
+    name = models.CharField(verbose_name=_('模板名称'), max_length=100, help_text=_('例如：销售话术评分、逻辑性分析'))
     model_selection = models.CharField(
         verbose_name=_('模型选择'), 
         max_length=50, 
@@ -73,6 +56,53 @@ class AIEvaluation(models.Model):
         default='你是一个专业的评分助手。请根据提供的转写内容，对内容质量、逻辑清晰度、语言表达等方面进行综合评分（0-100分），并给出详细的评语。请以JSON格式返回，包含"score"和"evaluation"字段。',
         help_text=_('用于指导AI评分的提示词')
     )
+    is_active = models.BooleanField(verbose_name=_('是否启用'), default=True, help_text=_('启用后，新的转写任务完成后将自动使用此模板进行评估'))
+    
+    created_at = models.DateTimeField(verbose_name=_('创建时间'), auto_now_add=True)
+    updated_at = models.DateTimeField(verbose_name=_('更新时间'), auto_now=True)
+
+    class Meta:
+        verbose_name = _('AI评估模板')
+        verbose_name_plural = _('AI评估模板')
+        ordering = ['-created_at']
+
+    def __str__(self):
+        return self.name
+
+
+class AIEvaluation(models.Model):
+    class Status(models.TextChoices):
+        PENDING = 'PENDING', _('等待中')
+        PROCESSING = 'PROCESSING', _('生成中')
+        COMPLETED = 'COMPLETED', _('已完成')
+        FAILED = 'FAILED', _('失败')
+
+    task = models.ForeignKey(
+        TranscriptionTask, 
+        on_delete=models.CASCADE, 
+        related_name='ai_evaluations',
+        verbose_name=_('关联任务')
+    )
+    template = models.ForeignKey(
+        AIEvaluationTemplate,
+        on_delete=models.SET_NULL,
+        null=True,
+        blank=True,
+        related_name='evaluations',
+        verbose_name=_('使用的模板')
+    )
+    
+    # 评分与评语
+    score = models.IntegerField(verbose_name=_('AI评分'), blank=True, null=True, help_text=_('0-100分'))
+    evaluation = models.TextField(verbose_name=_('AI评语'), blank=True, null=True)
+    
+    # 记录当时的配置 (快照)
+    model_selection = models.CharField(
+        verbose_name=_('模型选择'), 
+        max_length=50, 
+        default='qwen-plus'
+    )
+    prompt = models.TextField(verbose_name=_('评分提示词'))
     
     # 原始数据与推理
     raw_response = models.JSONField(verbose_name=_('原始响应'), blank=True, null=True, help_text=_('大模型返回的完整JSON'))
@@ -90,9 +120,9 @@ class AIEvaluation(models.Model):
     updated_at = models.DateTimeField(verbose_name=_('更新时间'), auto_now=True)
 
     class Meta:
-        verbose_name = _('AI智能评估')
-        verbose_name_plural = _('AI智能评估')
+        verbose_name = _('AI评估结果')
+        verbose_name_plural = _('AI评估结果')
         ordering = ['-created_at']
 
     def __str__(self):
-        return f"Evaluation for Task {self.task.id}"
+        return f"Evaluation for Task {self.task.id} ({self.template.name if self.template else 'Custom'})"

backend/ai_services/serializers.py

@@ -1,18 +1,25 @@
 from rest_framework import serializers
-from .models import TranscriptionTask, AIEvaluation
+from .models import TranscriptionTask, AIEvaluation, AIEvaluationTemplate
+
+class AIEvaluationTemplateSerializer(serializers.ModelSerializer):
+    class Meta:
+        model = AIEvaluationTemplate
+        fields = ['id', 'name', 'model_selection', 'prompt', 'is_active', 'created_at']
 
 class AIEvaluationSerializer(serializers.ModelSerializer):
+    template = AIEvaluationTemplateSerializer(read_only=True)
+    
     class Meta:
         model = AIEvaluation
-        fields = ['id', 'score', 'evaluation', 'model_selection', 'prompt', 'reasoning', 'status', 'error_message', 'created_at', 'updated_at']
+        fields = ['id', 'template', 'score', 'evaluation', 'model_selection', 'prompt', 'reasoning', 'status', 'error_message', 'created_at', 'updated_at']
 
 class TranscriptionTaskSerializer(serializers.ModelSerializer):
-    ai_evaluation = AIEvaluationSerializer(read_only=True)
+    ai_evaluations = AIEvaluationSerializer(many=True, read_only=True)
 
     class Meta:
         model = TranscriptionTask
-        fields = ['id', 'file_url', 'task_id', 'status', 'transcription', 'summary', 'error_message', 'created_at', 'updated_at', 'transcription_data', 'summary_data', 'auto_chapters_data', 'ai_evaluation']
-        read_only_fields = ['id', 'file_url', 'task_id', 'status', 'transcription', 'summary', 'error_message', 'created_at', 'updated_at', 'transcription_data', 'summary_data', 'auto_chapters_data', 'ai_evaluation']
+        fields = ['id', 'file_url', 'task_id', 'status', 'transcription', 'summary', 'error_message', 'created_at', 'updated_at', 'transcription_data', 'summary_data', 'auto_chapters_data', 'ai_evaluations']
+        read_only_fields = ['id', 'file_url', 'task_id', 'status', 'transcription', 'summary', 'error_message', 'created_at', 'updated_at', 'transcription_data', 'summary_data', 'auto_chapters_data', 'ai_evaluations']
 
 class TranscriptionUploadSerializer(serializers.Serializer):
     file = serializers.FileField(help_text="上传的音频文件")

backend/ai_services/services.py

@@ -16,6 +16,8 @@ from django.conf import settings
 
 logger = logging.getLogger(__name__)
 
+from .models import TranscriptionTask, AIEvaluation, AIEvaluationTemplate
+
 class AliyunTingwuService:
     def __init__(self):
         self.access_key_id = settings.ALIYUN_ACCESS_KEY_ID
@@ -157,6 +159,9 @@ class AliyunTingwuService:
         :param task: TranscriptionTask 实例
         :param result: get_task_info 返回的完整 JSON (或 Data 部分)
         """
+        # 记录之前的状态，用于判断是否是首次完成
+        previous_status = task.status
+
         # 1. 提取 Data 对象
         if isinstance(result, dict):
             data_obj = result.get('Data', result)
@@ -269,6 +274,14 @@ class AliyunTingwuService:
         # 结构: {"MindMapSummary": [{"Title": "...", "Topic": [...]}]}
         summary_text = []
         
+        # 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:
@@ -281,13 +294,37 @@ class AliyunTingwuService:
                     parse_mindmap_topic(sub_topics, level + 1)
 
         if 'MindMapSummary' in summarization:
+            summary_text.append("### 内容大纲")
             parse_mindmap_topic(summarization['MindMapSummary'])
-        elif 'Text' in summarization:
-            summary_text.append(summarization['Text'])
-        elif 'Headline' in summarization:
-             summary_text.append(summarization['Headline'])
-        elif 'ParagraphSummary' in summarization:
-             summary_text.append(summarization['ParagraphSummary'])
+            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)
@@ -336,3 +373,37 @@ class AliyunTingwuService:
             task.summary = "\n".join(summary_text)
         
         task.save()
+
+        # 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)
+
+    def trigger_ai_evaluations(self, task):
+        """
+        根据启用的模板自动触发 AI 评估
+        """
+        active_templates = AIEvaluationTemplate.objects.filter(is_active=True)
+        if not active_templates.exists():
+            logger.info("No active AI evaluation templates found.")
+            return
+
+        from .bailian_service import BailianService
+        service = BailianService()
+
+        for template in active_templates:
+            # 创建评估记录
+            evaluation = AIEvaluation.objects.create(
+                task=task,
+                template=template,
+                model_selection=template.model_selection,
+                prompt=template.prompt,
+                status=AIEvaluation.Status.PENDING
+            )
+            
+            # 触发评估 (同步执行，或者放入 Celery 任务)
+            # 这里为了简单直接调用，生产环境建议使用 Celery
+            try:
+                service.evaluate_task(evaluation)
+                logger.info(f"Triggered evaluation {evaluation.id} for template {template.name}")
+            except Exception as e:
+                logger.error(f"Failed to trigger evaluation {evaluation.id}: {e}")

backend/ai_services/views.py

@@ -154,7 +154,7 @@ class TranscriptionTaskViewSet(viewsets.ModelViewSet):
                 }
             }
         },
-        responses={200: AIEvaluationSerializer}
+        responses={200: AIEvaluationSerializer(many=True)}
     )
     def evaluate(self, request, pk=None):
         """
@@ -162,30 +162,63 @@ class TranscriptionTaskViewSet(viewsets.ModelViewSet):
         """
         task = self.get_object()
         
-        # 1. 检查或创建 Evaluation 对象
-        evaluation, created = AIEvaluation.objects.get_or_create(task=task)
+        # 1. 如果有 active template，触发所有 active template
+        # 2. 如果请求体提供了 custom prompt，则创建一个 custom evaluation (no template)
         
-        # 2. 如果请求中有配置，更新配置
+        from .models import AIEvaluationTemplate
+        from .bailian_service import BailianService
+        service = BailianService()
+        
+        evaluations_to_process = []
+        
+        # A. 如果指定了 Prompt/Model，视为手动单次评估
         model_selection = request.data.get('model_selection')
         prompt = request.data.get('prompt')
         
-        updated = False
-        if model_selection:
-            evaluation.model_selection = model_selection
-            updated = True
         if prompt:
-            evaluation.prompt = prompt
-            updated = True
+             # 创建一个不关联 Template 的评估
+            eval, _ = AIEvaluation.objects.get_or_create(
+                task=task,
+                template=None,
+                defaults={
+                    'model_selection': model_selection or 'qwen-plus',
+                    'prompt': prompt
+                }
+            )
+            # 更新配置
+            eval.model_selection = model_selection or eval.model_selection
+            eval.prompt = prompt
+            eval.save()
+            evaluations_to_process.append(eval)
+        else:
+            # B. 否则触发所有 Active Templates
+            active_templates = AIEvaluationTemplate.objects.filter(is_active=True)
+            if not active_templates.exists():
+                return Response({'message': 'No active templates and no custom prompt provided'}, status=status.HTTP_400_BAD_REQUEST)
+                
+            for t in active_templates:
+                eval, _ = AIEvaluation.objects.get_or_create(
+                    task=task,
+                    template=t,
+                    defaults={
+                        'model_selection': t.model_selection,
+                        'prompt': t.prompt
+                    }
+                )
+                # 始终更新为模板最新配置? 或者保留历史? 用户意图似乎是"模版搭好...启用...生成几份"
+                # 这里假设触发时应用模板当前配置
+                eval.model_selection = t.model_selection
+                eval.prompt = t.prompt
+                eval.save()
+                evaluations_to_process.append(eval)
+                
+        # 执行评估
+        for eval_obj in evaluations_to_process:
+            service.evaluate_task(eval_obj)
             
-        if updated:
-            evaluation.save()
-            
-        # 3. 调用 Service 执行评估
-        from .bailian_service import BailianService
-        service = BailianService()
-        service.evaluate_task(evaluation)
-        
-        serializer = AIEvaluationSerializer(evaluation)
+        # 返回该任务的所有评估结果
+        all_evals = AIEvaluation.objects.filter(task=task)
+        serializer = AIEvaluationSerializer(all_evals, many=True)
         return Response(serializer.data)
 
     @action(detail=True, methods=['get'])
@@ -240,6 +273,9 @@ class TranscriptionTaskViewSet(viewsets.ModelViewSet):
             # 调用 Service 进行解析和更新
             service.parse_and_update_task(task, result)
             
+            # 重新获取 task 以包含更新后的关联字段 (如 ai_evaluations)
+            task.refresh_from_db()
+            
             serializer = self.get_serializer(task)
             return Response(serializer.data)
             

backend/config/settings.py

@@ -363,7 +363,12 @@ UNFOLD = {
                         "link": reverse_lazy("admin:ai_services_transcriptiontask_changelist"),
                     },
                     {
-                        "title": "AI 智能评估",
+                        "title": "AI 评估模板",
+                        "icon": "rule",
+                        "link": reverse_lazy("admin:ai_services_aievaluationtemplate_changelist"),
+                    },
+                    {
+                        "title": "AI 评估结果",
                         "icon": "psychology",
                         "link": reverse_lazy("admin:ai_services_aievaluation_changelist"),
                     },