Merge branch 'release/v0.2.6' into develop

* release/v0.2.6:
  fix(web): ontology class default tag bugfix
  fix(version): Version 0.2.6 Release Notes
  fix(web): chat file delete bugfix
  feat: support model load balancing and add message_id to API responses
  feat: support model load balancing and add message_id to API responses
  [changes] Work space isolation
  [add] Recently, memory activities have adopted Redis caching.
  [changes] Work space isolation
  [add] Recently, memory activities have adopted Redis caching.
  fix(web): upload add loading
  [changes] The enumeration check has been changed to a string.
  [changes] The enumeration check has been changed to a string.
  feat(web): http-request add headers variable
  fix(workflow): ensure file messages are written to messages in non-stream mode
  fix(workflow): fix Dify compatibility issues
  [changes] Memory write completion active failure interest cache
  feat(workflow): support multimodal context
  [changes] AI review and correction of code
  [add] Semantic pruning is unified with the ontology engineering scenario.
  feat(chat): add message_id field to chat API response

api/app/schemas/conversation_schema.py

@@ -86,6 +86,7 @@ class ChatResponse(BaseModel):
     """聊天响应（非流式）"""
     conversation_id: uuid.UUID
     message: str
+    message_id: str
     usage: Optional[Dict[str, Any]] = None
     elapsed_time: Optional[float] = None
 

api/app/schemas/memory_config_schema.py

@@ -417,6 +417,7 @@ class MemoryConfig:
     
     # Ontology scene association
     scene_id: Optional[UUID] = None
+    ontology_classes: Optional[list] = field(default=None)
     
     def __post_init__(self):
         """Validate configuration after initialization."""

api/app/schemas/memory_storage_schema.py

@@ -232,14 +232,15 @@ class ConfigParamsCreate(BaseModel):  # 创建配置参数模型（仅 body，
     # 本体场景关联（可选）
     scene_id: Optional[uuid.UUID] = Field(None, description="本体场景ID（UUID），关联ontology_scene表")
     
+    # 语义剪枝场景（由 service 层根据 scene_id 自动推导，值为关联场景的 scene_name，前端无需传入）
+    pruning_scene: Optional[str] = Field(None, description="语义剪枝场景，由 scene_id 对应的 scene_name 自动填充")
+    
     # 模型配置字段（可选，用于手动指定或自动填充）
     llm_id: Optional[str] = Field(None, description="LLM模型配置ID")
     embedding_id: Optional[str] = Field(None, description="嵌入模型配置ID")
     rerank_id: Optional[str] = Field(None, description="重排序模型配置ID")
     reflection_model_id: Optional[str] = Field(None, description="反思模型ID，默认与llm_id一致")
     emotion_model_id: Optional[str] = Field(None, description="情绪分析模型ID，默认与llm_id一致")
-
-
 class ConfigParamsDelete(BaseModel):  # 删除配置参数模型（请求体）
     model_config = ConfigDict(populate_by_name=True, extra="forbid")
     # config_name: str = Field("配置名称", description="配置名称（字符串）")
@@ -274,8 +275,8 @@ class ConfigUpdateExtracted(BaseModel):  # 更新记忆萃取引擎配置参数
 
     # 剪枝配置：与 runtime.json 中 pruning 段对应
     pruning_enabled: Optional[bool] = Field(None, description="是否启动智能语义剪枝")
-    pruning_scene: Optional[Literal["education", "online_service", "outbound"]] = Field(
-        None, description="智能剪枝场景：education/online_service/outbound"
+    pruning_scene: Optional[str] = Field(
+        None, description="智能剪枝场景：education/online_service/outbound 或本体工程自定义场景"
     )
     pruning_threshold: Optional[float] = Field(
         None, ge=0.0, le=0.9, description="智能语义剪枝阈值（0-0.9）"