fix(practice): 获取报告时自动生成不存在的报告

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/app/api/v1/practice.py

@@ -896,7 +896,53 @@ async def get_practice_report(
         report = result.scalar_one_or_none()
         
         if not report:
-            raise HTTPException(status_code=404, detail="分析报告不存在，请先生成报告")
+            # 报告不存在，自动生成
+            logger.info(f"报告不存在，自动生成: session_id={session_id}")
+            
+            # 查询对话历史
+            result = await db.execute(
+                select(PracticeDialogue).where(
+                    PracticeDialogue.session_id == session_id
+                ).order_by(PracticeDialogue.sequence)
+            )
+            dialogue_list = result.scalars().all()
+            
+            if not dialogue_list:
+                raise HTTPException(status_code=404, detail="没有对话记录，无法生成报告")
+            
+            # 构建对话历史
+            dialogue_history = [
+                {"role": "user" if d.speaker == "user" else "assistant", "content": d.content}
+                for d in dialogue_list
+            ]
+            
+            # 调用分析服务
+            from app.services.practice_analysis_service import PracticeAnalysisService
+            import json
+            
+            practice_analysis_service = PracticeAnalysisService()
+            analysis_result = await practice_analysis_service.analyze(dialogue_history, db=db)
+            
+            if not analysis_result.success:
+                raise HTTPException(status_code=500, detail=f"分析失败: {analysis_result.error}")
+            
+            analysis_data = analysis_result.to_dict()
+            
+            # 保存报告
+            report = PracticeReport(
+                session_id=session_id,
+                total_score=analysis_data.get("overall_score", 0),
+                score_breakdown=analysis_data.get("score_breakdown", []),
+                ability_dimensions=analysis_data.get("ability_dimensions", []),
+                dialogue_review=analysis_data.get("dialogue_review", []),
+                suggestions=analysis_data.get("suggestions", []),
+                summary=analysis_data.get("summary", ""),
+                raw_response=json.dumps(analysis_data, ensure_ascii=False)
+            )
+            db.add(report)
+            await db.commit()
+            await db.refresh(report)
+            logger.info(f"报告自动生成成功: session_id={session_id}, 总分={report.total_score}")
         
         # 3. 查询完整对话记录（从数据库）
         result = await db.execute(