完善会话报告与消息撤回控制

新增 AI 案例推理方案报告字段，支持方案追加到当前报告；增加会话消息成对撤回接口并记录审计日志；扩展流式响应消息标识，支持前端停止生成与撤回处理。

app/api/v1/conversations.py

@@ -74,6 +74,22 @@ async def send_conversation_message(
     )
 
 
+@router.delete("/{conversation_id}/messages/{message_id}", response_model=ApiResponse[ConversationData])
+async def withdraw_conversation_message(
+    conversation_id: int,
+    message_id: int,
+    session: DatabaseSession,
+    current_user: Annotated[UserAccount, Depends(require_permission("risk.assess", operate=True))],
+) -> ApiResponse[ConversationData]:
+    return ApiResponse(
+        data=await ConversationService(session).withdraw_turn(
+            conversation_id,
+            message_id,
+            current_user,
+        )
+    )
+
+
 @router.post("/{conversation_id}/stream")
 async def stream_conversation_message(
     conversation_id: int,

app/schemas/risk_prediction.py

@@ -85,6 +85,24 @@ class SimilarCase(ApiSchema):
     similarity: float | None = None
 
 
+class AiSolutionRisk(ApiSchema):
+    level: str
+    title: str
+    detail: str
+
+
+class AiSolutionReport(ApiSchema):
+    title: str = "AI 案例推理生成"
+    confidence: str | None = None
+    analysis_base: str | None = None
+    standard_fallback_enabled: bool = False
+    standards: list[StandardJudgment] = Field(default_factory=list)
+    similar_cases: list[SimilarCase] = Field(default_factory=list)
+    risks: list[AiSolutionRisk] = Field(default_factory=list)
+    suggestions: list[str] = Field(default_factory=list)
+    warning: str | None = None
+
+
 class RiskAssessmentResult(ApiSchema):
     subject_id: str
     score: float
@@ -99,6 +117,7 @@ class RiskAssessmentResult(ApiSchema):
     dimension_scores: list[RiskDimensionScore] = Field(default_factory=list)
     similar_cases: list[SimilarCase] = Field(default_factory=list)
     ai_suggestions: list[str] = Field(default_factory=list)
+    ai_solution_cards: list[AiSolutionReport] = Field(default_factory=list)
 
 
 class ModelInfo(ApiSchema):

app/services/conversations.py

@@ -7,11 +7,18 @@ from collections.abc import AsyncGenerator, Sequence
 from datetime import UTC, date, datetime, timedelta
 from typing import Any, Literal
 
-from sqlalchemy import func, or_, select
+from sqlalchemy import delete, func, or_, select
 
 from app.core.exceptions import AppException
 from app.domain.risk_engine import BaselineRiskEngine, IndicatorValue, RiskLevel
-from app.models.entities import AnomalyCase, Conversation, ConversationMessage, StandardRule, UserAccount
+from app.models.entities import (
+    AnomalyCase,
+    Conversation,
+    ConversationMessage,
+    OperationAudit,
+    StandardRule,
+    UserAccount,
+)
 from app.repositories.conversations import ConversationRepository
 from app.schemas.conversation import (
     ConversationData,
@@ -202,7 +209,10 @@ class ConversationService:
         await self.session.flush()
         await self.session.commit()
 
-        yield {"type": "start", "data": {"conversationId": conversation.id}}
+        yield {
+            "type": "start",
+            "data": {"conversationId": conversation.id, "messageId": user_message.id},
+        }
         try:
             semantics = await self.llm.extract_semantics(
                 text,
@@ -567,6 +577,7 @@ class ConversationService:
             if hasattr(self, "session")
             else None
         )
+
         has_order_data = bool(cooperation_count)
         cooperation_display = cooperation_count if has_order_data else None
         problems = await self._top_anomaly_types(
@@ -614,6 +625,46 @@ class ConversationService:
             "dataAvailable": has_order_data,
         }
 
+    async def withdraw_turn(
+        self,
+        conversation_id: int,
+        message_id: int,
+        user: UserAccount,
+    ) -> ConversationData:
+        """Delete one user turn and its immediately paired assistant reply."""
+
+        conversation = await self.repository.get_for_user(conversation_id, user.id)
+        if conversation is None:
+            raise AppException("对话不存在或无权访问", code=404, status_code=404)
+        message = next((item for item in conversation.messages if item.id == message_id), None)
+        if message is None or message.role != "user":
+            raise AppException("只能撤回用户消息", code=422, status_code=422)
+        messages = sorted(conversation.messages, key=lambda item: (item.created_at, item.id))
+        index = messages.index(message)
+        ids = [message.id]
+        if index + 1 < len(messages) and messages[index + 1].role == "assistant":
+            ids.append(messages[index + 1].id)
+        await self.session.execute(
+            delete(ConversationMessage).where(ConversationMessage.id.in_(ids))
+        )
+        conversation.updated_at = datetime.now(UTC)
+        self.session.add(
+            OperationAudit(
+                actor_user_id=user.id,
+                actor_emp_no=user.emp_no,
+                action="conversation.withdraw",
+                resource_type="conversation_message",
+                resource_id=str(message_id),
+                audit_metadata={"deleted_message_ids": ids},
+            )
+        )
+        await self.session.flush()
+        page = await self.repository.get_page_for_user(conversation_id, user.id, limit=20, offset=0)
+        if page is None:
+            raise AppException("对话读取失败", code=500, status_code=500)
+        persisted, page_messages, total = page
+        return self._data(persisted, messages=page_messages, total=total, offset=0)
+
     async def _material_card(self, text: str, semantics: dict[str, Any]) -> dict[str, Any]:
         material = self._first_match(text, ("软管", "泵头", "瓶体", "瓶子", "彩盒", "铝瓶", "喷头", "PET"))
         material = material or self._semantic_text(semantics, "packaging") or "未指定物料"
@@ -790,7 +841,10 @@ class ConversationService:
             ),
             "standardFallbackEnabled": standard_fallback_enabled,
             "standards": [self._standard_dict(item) for item in standards[:4]],
-            "similarCases": [item.case.model_dump(mode="json", by_alias=False) for item in similar_cases],
+            "similarCases": [
+                item.case.model_dump(mode="json", by_alias=False)
+                for item in similar_cases
+            ],
             "risks": risks,
             "suggestions": suggestions,
             "warning": "以上方案由 AI 推理生成，实际执行前请咨询品控部门确认。",