Feature/ontology class clean (#249)
* [add] Complete ontology engineering feature implementation * [add] Add ontology feature integration and validation utilities * [add] Add OWL validator and validation utilities * [fix] Add missing render_ontology_extraction_prompt function * [fix]Add dependencies, fix functionality
This commit is contained in:
乐力齐
@@ -45,6 +45,7 @@ from . import (
|
||||
home_page_controller,
|
||||
memory_perceptual_controller,
|
||||
memory_working_controller,
|
||||
ontology_controller,
|
||||
)
|
||||
|
||||
# 创建管理端 API 路由器
|
||||
@@ -90,5 +91,6 @@ manager_router.include_router(implicit_memory_controller.router)
|
||||
manager_router.include_router(memory_perceptual_controller.router)
|
||||
manager_router.include_router(memory_working_controller.router)
|
||||
manager_router.include_router(file_storage_controller.router)
|
||||
manager_router.include_router(ontology_controller.router)
|
||||
|
||||
__all__ = ["manager_router"]
|
||||
|
||||
964
api/app/controllers/ontology_controller.py
Normal file
964
api/app/controllers/ontology_controller.py
Normal file
@@ -0,0 +1,964 @@
|
||||
"""本体提取API控制器
|
||||
|
||||
本模块提供本体提取系统的RESTful API端点。
|
||||
|
||||
Endpoints:
|
||||
POST /api/memory/ontology/extract - 提取本体类
|
||||
POST /api/memory/ontology/export - 导出OWL文件
|
||||
POST /api/memory/ontology/scene - 创建本体场景
|
||||
PUT /api/memory/ontology/scene/{scene_id} - 更新本体场景
|
||||
DELETE /api/memory/ontology/scene/{scene_id} - 删除本体场景
|
||||
GET /api/memory/ontology/scene/{scene_id} - 获取单个场景
|
||||
GET /api/memory/ontology/scenes - 获取场景列表
|
||||
POST /api/memory/ontology/class - 创建本体类型
|
||||
PUT /api/memory/ontology/class/{class_id} - 更新本体类型
|
||||
DELETE /api/memory/ontology/class/{class_id} - 删除本体类型
|
||||
GET /api/memory/ontology/class/{class_id} - 获取单个类型
|
||||
GET /api/memory/ontology/classes - 获取类型列表
|
||||
"""
|
||||
|
||||
import logging
|
||||
import tempfile
|
||||
from typing import Dict, Optional
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Header
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.core.error_codes import BizCode
|
||||
from app.core.logging_config import get_api_logger
|
||||
from app.core.response_utils import fail, success
|
||||
from app.db import get_db
|
||||
from app.dependencies import get_current_user
|
||||
from app.models.user_model import User
|
||||
from app.services.memory_base_service import Translation_English
|
||||
from app.core.memory.models.ontology_models import OntologyClass
|
||||
from typing import List
|
||||
from app.schemas.ontology_schemas import (
|
||||
ExportRequest,
|
||||
ExportResponse,
|
||||
ExtractionRequest,
|
||||
ExtractionResponse,
|
||||
SceneCreateRequest,
|
||||
SceneUpdateRequest,
|
||||
SceneResponse,
|
||||
SceneListResponse,
|
||||
ClassCreateRequest,
|
||||
ClassUpdateRequest,
|
||||
ClassResponse,
|
||||
ClassListResponse,
|
||||
)
|
||||
from app.schemas.response_schema import ApiResponse
|
||||
from app.services.ontology_service import OntologyService
|
||||
from app.core.memory.llm_tools.openai_client import OpenAIClient
|
||||
from app.core.memory.utils.validation.owl_validator import OWLValidator
|
||||
from app.services.model_service import ModelConfigService
|
||||
|
||||
|
||||
api_logger = get_api_logger()
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(
|
||||
prefix="/memory/ontology",
|
||||
tags=["Ontology"],
|
||||
)
|
||||
|
||||
|
||||
async def translate_ontology_classes(
|
||||
classes: List[OntologyClass],
|
||||
model_id: str
|
||||
) -> List[OntologyClass]:
|
||||
"""翻译本体类列表
|
||||
|
||||
将本体类的中文字段翻译为英文，包括：
|
||||
- name_chinese: 中文名称
|
||||
- description: 描述
|
||||
- examples: 示例列表
|
||||
|
||||
Args:
|
||||
classes: 本体类列表
|
||||
model_id: LLM模型ID，用于翻译
|
||||
|
||||
Returns:
|
||||
List[OntologyClass]: 翻译后的本体类列表
|
||||
"""
|
||||
translated_classes = []
|
||||
|
||||
for ontology_class in classes:
|
||||
# 创建类的副本，避免修改原对象
|
||||
translated_class = ontology_class.model_copy(deep=True)
|
||||
|
||||
# 翻译 name_chinese 字段
|
||||
if translated_class.name_chinese:
|
||||
try:
|
||||
translated_class.name_chinese = await Translation_English(
|
||||
model_id,
|
||||
translated_class.name_chinese
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to translate name_chinese: {e}")
|
||||
# 保留原文
|
||||
|
||||
# 翻译 description 字段
|
||||
if translated_class.description:
|
||||
try:
|
||||
translated_class.description = await Translation_English(
|
||||
model_id,
|
||||
translated_class.description
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to translate description: {e}")
|
||||
# 保留原文
|
||||
|
||||
# 翻译 examples 列表
|
||||
if translated_class.examples:
|
||||
translated_examples = []
|
||||
for example in translated_class.examples:
|
||||
try:
|
||||
translated_example = await Translation_English(
|
||||
model_id,
|
||||
example
|
||||
)
|
||||
translated_examples.append(translated_example)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to translate example: {e}")
|
||||
translated_examples.append(example) # 保留原文
|
||||
translated_class.examples = translated_examples
|
||||
|
||||
translated_classes.append(translated_class)
|
||||
|
||||
return translated_classes
|
||||
|
||||
|
||||
def _get_ontology_service(
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user),
|
||||
llm_id: str = None
|
||||
) -> OntologyService:
|
||||
"""获取OntologyService实例的依赖注入函数
|
||||
|
||||
指定的llm_id获取LLM配置,创建OpenAIClient和OntologyService实例。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
llm_id: 可选的LLM模型ID,如果提供则使用指定模型,否则使用工作空间默认模型
|
||||
|
||||
Returns:
|
||||
OntologyService: 本体提取服务实例
|
||||
|
||||
Raises:
|
||||
HTTPException: 如果无法获取LLM配置
|
||||
"""
|
||||
try:
|
||||
import uuid
|
||||
|
||||
# 必须提供llm_id
|
||||
if not llm_id:
|
||||
logger.error(f"llm_id is required but not provided - user: {current_user.id}")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="必须提供llm_id参数"
|
||||
)
|
||||
|
||||
logger.info(f"Using specified LLM model: {llm_id}")
|
||||
|
||||
# 验证llm_id格式
|
||||
try:
|
||||
model_id = uuid.UUID(llm_id)
|
||||
except ValueError:
|
||||
logger.error(f"Invalid llm_id format: {llm_id}")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="无效的LLM模型ID格式"
|
||||
)
|
||||
|
||||
# 获取指定的模型配置
|
||||
try:
|
||||
model_config = ModelConfigService.get_model_by_id(db=db, model_id=model_id)
|
||||
except Exception as e:
|
||||
logger.error(f"Model {llm_id} not found: {str(e)}")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"找不到指定的LLM模型: {llm_id}"
|
||||
)
|
||||
|
||||
# 检查是否为组合模型
|
||||
if hasattr(model_config, 'is_composite') and model_config.is_composite:
|
||||
logger.error(f"Model {llm_id} is a composite model, which is not supported for ontology extraction")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="本体提取不支持使用组合模型，请选择单个模型"
|
||||
)
|
||||
|
||||
# 验证模型配置了API密钥
|
||||
if not model_config.api_keys:
|
||||
logger.error(f"Model {llm_id} has no API key configuration")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="指定的LLM模型没有配置API密钥"
|
||||
)
|
||||
|
||||
api_key_config = model_config.api_keys[0]
|
||||
|
||||
logger.info(
|
||||
f"Using specified model - user: {current_user.id}, "
|
||||
f"model_id: {llm_id}, model_name: {api_key_config.model_name}"
|
||||
)
|
||||
|
||||
# 创建模型配置对象
|
||||
from app.core.models.base import RedBearModelConfig
|
||||
|
||||
llm_model_config = RedBearModelConfig(
|
||||
model_name=api_key_config.model_name,
|
||||
provider=model_config.provider if hasattr(model_config, 'provider') else "openai",
|
||||
api_key=api_key_config.api_key,
|
||||
base_url=api_key_config.api_base,
|
||||
max_retries=3,
|
||||
timeout=60.0
|
||||
)
|
||||
|
||||
# 创建OpenAI客户端
|
||||
llm_client = OpenAIClient(model_config=llm_model_config)
|
||||
|
||||
# 创建OntologyService
|
||||
service = OntologyService(llm_client=llm_client, db=db)
|
||||
|
||||
logger.debug(
|
||||
f"OntologyService created successfully - "
|
||||
f"user: {current_user.id}, model: {api_key_config.model_name}"
|
||||
)
|
||||
|
||||
return service
|
||||
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create OntologyService: {str(e)}", exc_info=True)
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail=f"创建本体提取服务失败: {str(e)}"
|
||||
)
|
||||
|
||||
|
||||
@router.post("/extract", response_model=ApiResponse)
|
||||
async def extract_ontology(
|
||||
request: ExtractionRequest,
|
||||
language_type: str = Header(default="zh", alias="X-Language-Type"),
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""提取本体类
|
||||
|
||||
从场景描述中提取符合OWL规范的本体类。
|
||||
提取结果仅返回给前端，不会自动保存到数据库。
|
||||
前端可以从返回结果中选择需要的类型，然后调用 /class 接口创建类型。
|
||||
支持中英文切换，通过 X-Language-Type Header 指定语言。
|
||||
|
||||
Args:
|
||||
request: 提取请求,包含scenario、domain、llm_id和scene_id
|
||||
language_type: 语言类型，'zh'（中文）或 'en'（英文），默认 'zh'
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含提取结果的响应
|
||||
|
||||
Response format:
|
||||
{
|
||||
"code": 200,
|
||||
"msg": "本体提取成功",
|
||||
"data": {
|
||||
"classes": [
|
||||
{
|
||||
"id": "147d9db50b524a9e909e01a753d3acdd",
|
||||
"name": "Patient",
|
||||
"name_chinese": "患者",
|
||||
"description": "在医疗机构中接受诊疗、护理或健康管理的个体",
|
||||
"examples": ["糖尿病患者", "术后康复患者", "门诊初诊患者"],
|
||||
"parent_class": null,
|
||||
"entity_type": "Person",
|
||||
"domain": "Healthcare"
|
||||
},
|
||||
...
|
||||
],
|
||||
"domain": "Healthcare",
|
||||
"extracted_count": 7
|
||||
}
|
||||
}
|
||||
"""
|
||||
api_logger.info(
|
||||
f"Ontology extraction requested by user {current_user.id}, "
|
||||
f"scenario_length={len(request.scenario)}, "
|
||||
f"domain={request.domain}, "
|
||||
f"llm_id={request.llm_id}, "
|
||||
f"scene_id={request.scene_id}, "
|
||||
f"language_type={language_type}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建OntologyService实例,传入llm_id
|
||||
service = _get_ontology_service(
|
||||
db=db,
|
||||
current_user=current_user,
|
||||
llm_id=request.llm_id
|
||||
)
|
||||
|
||||
# 调用服务层执行提取，传入scene_id和workspace_id
|
||||
result = await service.extract_ontology(
|
||||
scenario=request.scenario,
|
||||
domain=request.domain,
|
||||
scene_id=request.scene_id,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
# ===== 新增：翻译逻辑 =====
|
||||
# 如果需要英文，则翻译数据
|
||||
if language_type != 'zh':
|
||||
api_logger.info(f"Translating extraction result to English")
|
||||
|
||||
# 翻译 classes 列表
|
||||
result.classes = await translate_ontology_classes(
|
||||
result.classes,
|
||||
request.llm_id
|
||||
)
|
||||
|
||||
# 翻译 domain 字段
|
||||
if result.domain:
|
||||
try:
|
||||
result.domain = await Translation_English(
|
||||
request.llm_id,
|
||||
result.domain
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to translate domain: {e}")
|
||||
# 保留原文
|
||||
# ===== 翻译逻辑结束 =====
|
||||
|
||||
# 构建响应
|
||||
response = ExtractionResponse(
|
||||
classes=result.classes,
|
||||
domain=result.domain,
|
||||
extracted_count=len(result.classes)
|
||||
)
|
||||
|
||||
api_logger.info(
|
||||
f"Ontology extraction completed, extracted {len(result.classes)} classes, "
|
||||
f"saved to scene {request.scene_id}, language={language_type}"
|
||||
)
|
||||
|
||||
return success(data=response.model_dump(), msg="本体提取成功")
|
||||
|
||||
except ValueError as e:
|
||||
# 验证错误 (400)
|
||||
api_logger.warning(f"Validation error in extraction: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
# 运行时错误 (500)
|
||||
api_logger.error(f"Runtime error in extraction: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "本体提取失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
# 未知错误 (500)
|
||||
api_logger.error(f"Unexpected error in extraction: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "本体提取失败", str(e))
|
||||
|
||||
|
||||
@router.post("/export", response_model=ApiResponse)
|
||||
async def export_owl(
|
||||
request: ExportRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""导出OWL文件
|
||||
|
||||
将提取的本体类导出为OWL文件,支持多种格式。
|
||||
导出操作不需要LLM,只使用OWL验证器和Owlready2库。
|
||||
|
||||
Args:
|
||||
request: 导出请求,包含classes、format和include_metadata
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含OWL文件内容的响应
|
||||
|
||||
Supported formats:
|
||||
- rdfxml: 标准OWL RDF/XML格式(完整)
|
||||
- turtle: Turtle格式(可读性好)
|
||||
- ntriples: N-Triples格式(简单)
|
||||
- json: JSON格式(简化,只包含类信息)
|
||||
|
||||
Response format:
|
||||
{
|
||||
"code": 200,
|
||||
"msg": "OWL文件导出成功",
|
||||
"data": {
|
||||
"owl_content": "...",
|
||||
"format": "rdfxml",
|
||||
"classes_count": 7
|
||||
}
|
||||
}
|
||||
"""
|
||||
api_logger.info(
|
||||
f"OWL export requested by user {current_user.id}, "
|
||||
f"classes_count={len(request.classes)}, "
|
||||
f"format={request.format}, "
|
||||
f"include_metadata={request.include_metadata}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 验证格式
|
||||
valid_formats = ["rdfxml", "turtle", "ntriples", "json"]
|
||||
if request.format not in valid_formats:
|
||||
api_logger.warning(f"Invalid export format: {request.format}")
|
||||
return fail(
|
||||
BizCode.BAD_REQUEST,
|
||||
"不支持的导出格式",
|
||||
f"format必须是以下之一: {', '.join(valid_formats)}"
|
||||
)
|
||||
|
||||
# JSON格式直接导出,不需要OWL验证
|
||||
if request.format == "json":
|
||||
owl_validator = OWLValidator()
|
||||
owl_content = owl_validator.export_to_owl(
|
||||
world=None,
|
||||
format="json",
|
||||
classes=request.classes
|
||||
)
|
||||
|
||||
response = ExportResponse(
|
||||
owl_content=owl_content,
|
||||
format=request.format,
|
||||
classes_count=len(request.classes)
|
||||
)
|
||||
|
||||
api_logger.info(
|
||||
f"JSON export completed, content_length={len(owl_content)}"
|
||||
)
|
||||
|
||||
return success(data=response.model_dump(), msg="OWL文件导出成功")
|
||||
|
||||
# 创建临时文件路径
|
||||
with tempfile.NamedTemporaryFile(
|
||||
mode='w',
|
||||
suffix='.owl',
|
||||
delete=False
|
||||
) as tmp_file:
|
||||
output_path = tmp_file.name
|
||||
|
||||
# 导出操作不需要LLM,直接使用OWL验证器
|
||||
owl_validator = OWLValidator()
|
||||
|
||||
# 验证本体类
|
||||
logger.debug("Validating ontology classes")
|
||||
is_valid, errors, world = owl_validator.validate_ontology_classes(
|
||||
classes=request.classes,
|
||||
)
|
||||
|
||||
if not is_valid:
|
||||
logger.warning(
|
||||
f"OWL validation found {len(errors)} issues during export: {errors}"
|
||||
)
|
||||
# 继续导出,但记录警告
|
||||
|
||||
if not world:
|
||||
error_msg = "Failed to create OWL world for export"
|
||||
logger.error(error_msg)
|
||||
return fail(BizCode.INTERNAL_ERROR, "创建OWL世界失败", error_msg)
|
||||
|
||||
# 导出OWL文件
|
||||
logger.info(f"Exporting to {request.format} format")
|
||||
owl_content = owl_validator.export_to_owl(
|
||||
world=world,
|
||||
output_path=output_path,
|
||||
format=request.format,
|
||||
classes=request.classes
|
||||
)
|
||||
|
||||
# 构建响应
|
||||
response = ExportResponse(
|
||||
owl_content=owl_content,
|
||||
format=request.format,
|
||||
classes_count=len(request.classes)
|
||||
)
|
||||
|
||||
api_logger.info(
|
||||
f"OWL export completed, format={request.format}, "
|
||||
f"content_length={len(owl_content)}"
|
||||
)
|
||||
|
||||
return success(data=response.model_dump(), msg="OWL文件导出成功")
|
||||
|
||||
except ValueError as e:
|
||||
# 验证错误 (400)
|
||||
api_logger.warning(f"Validation error in export: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
# 运行时错误 (500)
|
||||
api_logger.error(f"Runtime error in export: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "OWL文件导出失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
# 未知错误 (500)
|
||||
api_logger.error(f"Unexpected error in export: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "OWL文件导出失败", str(e))
|
||||
|
||||
|
||||
# ==================== 本体场景管理接口 ====================
|
||||
|
||||
@router.post("/scene", response_model=ApiResponse)
|
||||
async def create_scene(
|
||||
request: SceneCreateRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""创建本体场景
|
||||
|
||||
在当前工作空间下创建新的本体场景。
|
||||
|
||||
Args:
|
||||
request: 场景创建请求
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含创建的场景信息
|
||||
"""
|
||||
api_logger.info(
|
||||
f"Scene creation requested by user {current_user.id}, "
|
||||
f"name={request.scene_name}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建OntologyService实例（不需要LLM）
|
||||
from app.core.memory.llm_tools.openai_client import OpenAIClient
|
||||
from app.core.models.base import RedBearModelConfig
|
||||
|
||||
# 创建一个空的LLM配置（场景管理不需要LLM）
|
||||
dummy_config = RedBearModelConfig(
|
||||
model_name="dummy",
|
||||
provider="openai",
|
||||
api_key="dummy",
|
||||
base_url="https://api.openai.com/v1"
|
||||
)
|
||||
llm_client = OpenAIClient(model_config=dummy_config)
|
||||
service = OntologyService(llm_client=llm_client, db=db)
|
||||
|
||||
# 调用服务层创建场景
|
||||
scene = service.create_scene(
|
||||
scene_name=request.scene_name,
|
||||
scene_description=request.scene_description,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
# 构建响应
|
||||
# 动态计算 type_num
|
||||
type_num = len(scene.classes) if scene.classes else 0
|
||||
|
||||
response = SceneResponse(
|
||||
scene_id=scene.scene_id,
|
||||
scene_name=scene.scene_name,
|
||||
scene_description=scene.scene_description,
|
||||
type_num=type_num,
|
||||
workspace_id=scene.workspace_id,
|
||||
created_at=scene.created_at,
|
||||
updated_at=scene.updated_at,
|
||||
classes_count=type_num
|
||||
)
|
||||
|
||||
api_logger.info(f"Scene created successfully: {scene.scene_id}")
|
||||
|
||||
return success(data=response.model_dump(), msg="场景创建成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in scene creation: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in scene creation: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "场景创建失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in scene creation: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "场景创建失败", str(e))
|
||||
|
||||
|
||||
@router.put("/scene/{scene_id}", response_model=ApiResponse)
|
||||
async def update_scene(
|
||||
scene_id: str,
|
||||
request: SceneUpdateRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""更新本体场景
|
||||
|
||||
更新指定场景的信息，只能更新当前工作空间下的场景。
|
||||
|
||||
Args:
|
||||
scene_id: 场景ID
|
||||
request: 场景更新请求
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含更新后的场景信息
|
||||
"""
|
||||
api_logger.info(
|
||||
f"Scene update requested by user {current_user.id}, "
|
||||
f"scene_id={scene_id}"
|
||||
)
|
||||
|
||||
try:
|
||||
from uuid import UUID
|
||||
|
||||
# 验证UUID格式
|
||||
try:
|
||||
scene_uuid = UUID(scene_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid scene_id format: {scene_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的场景ID格式")
|
||||
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建OntologyService实例
|
||||
from app.core.memory.llm_tools.openai_client import OpenAIClient
|
||||
from app.core.models.base import RedBearModelConfig
|
||||
|
||||
dummy_config = RedBearModelConfig(
|
||||
model_name="dummy",
|
||||
provider="openai",
|
||||
api_key="dummy",
|
||||
base_url="https://api.openai.com/v1"
|
||||
)
|
||||
llm_client = OpenAIClient(model_config=dummy_config)
|
||||
service = OntologyService(llm_client=llm_client, db=db)
|
||||
|
||||
# 调用服务层更新场景
|
||||
scene = service.update_scene(
|
||||
scene_id=scene_uuid,
|
||||
scene_name=request.scene_name,
|
||||
scene_description=request.scene_description,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
# 构建响应
|
||||
# 动态计算 type_num
|
||||
type_num = len(scene.classes) if scene.classes else 0
|
||||
|
||||
response = SceneResponse(
|
||||
scene_id=scene.scene_id,
|
||||
scene_name=scene.scene_name,
|
||||
scene_description=scene.scene_description,
|
||||
type_num=type_num,
|
||||
workspace_id=scene.workspace_id,
|
||||
created_at=scene.created_at,
|
||||
updated_at=scene.updated_at,
|
||||
classes_count=type_num
|
||||
)
|
||||
|
||||
api_logger.info(f"Scene updated successfully: {scene_id}")
|
||||
|
||||
return success(data=response.model_dump(), msg="场景更新成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in scene update: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in scene update: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "场景更新失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in scene update: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "场景更新失败", str(e))
|
||||
|
||||
|
||||
@router.delete("/scene/{scene_id}", response_model=ApiResponse)
|
||||
async def delete_scene(
|
||||
scene_id: str,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""删除本体场景
|
||||
|
||||
删除指定场景及其所有关联类型，只能删除当前工作空间下的场景。
|
||||
|
||||
Args:
|
||||
scene_id: 场景ID
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 删除结果
|
||||
"""
|
||||
api_logger.info(
|
||||
f"Scene deletion requested by user {current_user.id}, "
|
||||
f"scene_id={scene_id}"
|
||||
)
|
||||
|
||||
try:
|
||||
from uuid import UUID
|
||||
|
||||
# 验证UUID格式
|
||||
try:
|
||||
scene_uuid = UUID(scene_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid scene_id format: {scene_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的场景ID格式")
|
||||
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建OntologyService实例
|
||||
from app.core.memory.llm_tools.openai_client import OpenAIClient
|
||||
from app.core.models.base import RedBearModelConfig
|
||||
|
||||
dummy_config = RedBearModelConfig(
|
||||
model_name="dummy",
|
||||
provider="openai",
|
||||
api_key="dummy",
|
||||
base_url="https://api.openai.com/v1"
|
||||
)
|
||||
llm_client = OpenAIClient(model_config=dummy_config)
|
||||
service = OntologyService(llm_client=llm_client, db=db)
|
||||
|
||||
# 调用服务层删除场景
|
||||
success_flag = service.delete_scene(
|
||||
scene_id=scene_uuid,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
api_logger.info(f"Scene deleted successfully: {scene_id}")
|
||||
|
||||
return success(data={"deleted": success_flag}, msg="场景删除成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in scene deletion: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in scene deletion: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "场景删除失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in scene deletion: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "场景删除失败", str(e))
|
||||
|
||||
|
||||
@router.get("/scenes", response_model=ApiResponse)
|
||||
async def get_scenes(
|
||||
workspace_id: Optional[str] = None,
|
||||
scene_name: Optional[str] = None,
|
||||
page: Optional[int] = None,
|
||||
pagesize: Optional[int] = None,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""获取场景列表（支持模糊搜索和全量查询，全量查询支持分页）
|
||||
|
||||
根据是否提供 scene_name 参数，执行不同的查询：
|
||||
- 提供 scene_name：进行模糊搜索，返回匹配的场景列表（支持分页）
|
||||
- 不提供 scene_name：返回工作空间下的所有场景（支持分页）
|
||||
|
||||
支持中文和英文的模糊匹配，不区分大小写。
|
||||
|
||||
Args:
|
||||
workspace_id: 工作空间ID（可选，默认当前用户工作空间）
|
||||
scene_name: 场景名称关键词（可选，支持模糊匹配）
|
||||
page: 页码（可选，从1开始）
|
||||
pagesize: 每页数量（可选）
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含场景列表和分页信息
|
||||
|
||||
Examples:
|
||||
- 模糊搜索（不分页）：GET /scenes?workspace_id=xxx&scene_name=医疗
|
||||
输入 "医疗" 可以匹配到 "医疗场景"、"智慧医疗"、"医疗管理系统" 等
|
||||
- 模糊搜索（分页）：GET /scenes?workspace_id=xxx&scene_name=医疗&page=1&pagesize=10
|
||||
返回匹配 "医疗" 的第1页，每页10条数据
|
||||
- 全量查询（不分页）：GET /scenes?workspace_id=xxx
|
||||
返回工作空间下的所有场景
|
||||
- 全量查询（分页）：GET /scenes?workspace_id=xxx&page=1&pagesize=10
|
||||
返回第1页，每页10条数据
|
||||
|
||||
Notes:
|
||||
- 分页参数 page 和 pagesize 必须同时提供
|
||||
- page 从1开始，pagesize 必须大于0
|
||||
- 返回格式：{"items": [...], "page": {"page": 1, "pagesize": 10, "total": 100, "hasnext": true}}
|
||||
- 不分页时，page 字段为 null
|
||||
"""
|
||||
from app.controllers.ontology_secondary_routes import scenes_handler
|
||||
return await scenes_handler(workspace_id, scene_name, page, pagesize, db, current_user)
|
||||
|
||||
|
||||
# ==================== 本体类型管理接口 ====================
|
||||
|
||||
@router.post("/class", response_model=ApiResponse)
|
||||
async def create_class(
|
||||
request: ClassCreateRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""创建本体类型
|
||||
|
||||
在指定场景下创建新的本体类型。
|
||||
|
||||
Args:
|
||||
request: 类型创建请求
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含创建的类型信息
|
||||
"""
|
||||
from app.controllers.ontology_secondary_routes import create_class_handler
|
||||
return await create_class_handler(request, db, current_user)
|
||||
|
||||
|
||||
@router.put("/class/{class_id}", response_model=ApiResponse)
|
||||
async def update_class(
|
||||
class_id: str,
|
||||
request: ClassUpdateRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""更新本体类型
|
||||
|
||||
更新指定类型的信息，只能更新当前工作空间下场景的类型。
|
||||
|
||||
Args:
|
||||
class_id: 类型ID
|
||||
request: 类型更新请求
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含更新后的类型信息
|
||||
"""
|
||||
from app.controllers.ontology_secondary_routes import update_class_handler
|
||||
return await update_class_handler(class_id, request, db, current_user)
|
||||
|
||||
|
||||
@router.delete("/class/{class_id}", response_model=ApiResponse)
|
||||
async def delete_class(
|
||||
class_id: str,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""删除本体类型
|
||||
|
||||
删除指定类型，只能删除当前工作空间下场景的类型。
|
||||
|
||||
Args:
|
||||
class_id: 类型ID
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 删除结果
|
||||
"""
|
||||
from app.controllers.ontology_secondary_routes import delete_class_handler
|
||||
return await delete_class_handler(class_id, db, current_user)
|
||||
|
||||
|
||||
@router.get("/classes", response_model=ApiResponse)
|
||||
async def get_classes(
|
||||
scene_id: str,
|
||||
class_name: Optional[str] = None,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""获取类型列表（支持模糊搜索和全量查询）
|
||||
|
||||
根据是否提供 class_name 参数，执行不同的查询：
|
||||
- 提供 class_name：进行模糊搜索，返回匹配的类型列表
|
||||
- 不提供 class_name：返回场景下的所有类型
|
||||
|
||||
支持中文和英文的模糊匹配，不区分大小写。
|
||||
返回结果包含场景的基本信息（scene_name 和 scene_description）。
|
||||
|
||||
Args:
|
||||
scene_id: 场景ID（必填）
|
||||
class_name: 类型名称关键词（可选，支持模糊匹配）
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含类型列表和场景信息
|
||||
|
||||
Examples:
|
||||
- 模糊搜索：GET /classes?scene_id=xxx&class_name=患者
|
||||
输入 "患者" 可以匹配到 "患者"、"患者信息"、"门诊患者" 等
|
||||
- 全量查询：GET /classes?scene_id=xxx
|
||||
返回场景下的所有类型
|
||||
|
||||
Response Format:
|
||||
{
|
||||
"total": 3,
|
||||
"scene_id": "xxx",
|
||||
"scene_name": "医疗场景",
|
||||
"scene_description": "用于医疗领域的本体建模",
|
||||
"items": [...]
|
||||
}
|
||||
"""
|
||||
from app.controllers.ontology_secondary_routes import classes_handler
|
||||
return await classes_handler(scene_id, class_name, db, current_user)
|
||||
|
||||
|
||||
@router.get("/class/{class_id}", response_model=ApiResponse)
|
||||
async def get_class(
|
||||
class_id: str,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""获取单个本体类型
|
||||
|
||||
根据类型ID获取类型的详细信息，只能查询当前工作空间下场景的类型。
|
||||
|
||||
Args:
|
||||
class_id: 类型ID
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
|
||||
Returns:
|
||||
ApiResponse: 包含类型详细信息
|
||||
|
||||
Response Format:
|
||||
{
|
||||
"code": 0,
|
||||
"msg": "查询成功",
|
||||
"data": {
|
||||
"class_id": "xxx",
|
||||
"class_name": "患者",
|
||||
"class_description": "在医疗机构中接受诊疗的个体",
|
||||
"scene_id": "xxx",
|
||||
"created_at": "2026-01-29T10:00:00",
|
||||
"updated_at": "2026-01-29T10:00:00"
|
||||
}
|
||||
}
|
||||
"""
|
||||
from app.controllers.ontology_secondary_routes import get_class_handler
|
||||
return await get_class_handler(class_id, db, current_user)
|
||||
611
api/app/controllers/ontology_secondary_routes.py
Normal file
611
api/app/controllers/ontology_secondary_routes.py
Normal file
@@ -0,0 +1,611 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""本体场景和类型路由（续）
|
||||
|
||||
由于主Controller文件较大，将剩余路由放在此文件中。
|
||||
"""
|
||||
|
||||
from uuid import UUID
|
||||
from typing import Optional
|
||||
|
||||
from fastapi import Depends
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.core.error_codes import BizCode
|
||||
from app.core.logging_config import get_api_logger
|
||||
from app.core.response_utils import fail, success
|
||||
from app.db import get_db
|
||||
from app.dependencies import get_current_user
|
||||
from app.models.user_model import User
|
||||
from app.schemas.ontology_schemas import (
|
||||
SceneResponse,
|
||||
SceneListResponse,
|
||||
PaginationInfo,
|
||||
ClassCreateRequest,
|
||||
ClassUpdateRequest,
|
||||
ClassResponse,
|
||||
ClassListResponse,
|
||||
ClassBatchCreateResponse,
|
||||
)
|
||||
from app.schemas.response_schema import ApiResponse
|
||||
from app.services.ontology_service import OntologyService
|
||||
from app.core.memory.llm_tools.openai_client import OpenAIClient
|
||||
from app.core.models.base import RedBearModelConfig
|
||||
|
||||
|
||||
api_logger = get_api_logger()
|
||||
|
||||
|
||||
def _get_dummy_ontology_service(db: Session) -> OntologyService:
|
||||
"""获取OntologyService实例（不需要LLM）
|
||||
|
||||
场景和类型管理不需要LLM，创建一个dummy配置。
|
||||
"""
|
||||
dummy_config = RedBearModelConfig(
|
||||
model_name="dummy",
|
||||
provider="openai",
|
||||
api_key="dummy",
|
||||
base_url="https://api.openai.com/v1"
|
||||
)
|
||||
llm_client = OpenAIClient(model_config=dummy_config)
|
||||
return OntologyService(llm_client=llm_client, db=db)
|
||||
|
||||
|
||||
# 这些函数将被导入到主Controller中
|
||||
|
||||
async def scenes_handler(
|
||||
workspace_id: Optional[str] = None,
|
||||
scene_name: Optional[str] = None,
|
||||
page: Optional[int] = None,
|
||||
page_size: Optional[int] = None,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""获取场景列表（支持模糊搜索和全量查询，全量查询支持分页）
|
||||
|
||||
当提供 scene_name 参数时，进行模糊搜索（不分页）；
|
||||
当不提供 scene_name 参数时，返回所有场景（支持分页）。
|
||||
|
||||
Args:
|
||||
workspace_id: 工作空间ID（可选，默认当前用户工作空间）
|
||||
scene_name: 场景名称关键词（可选，支持模糊匹配）
|
||||
page: 页码（可选，从1开始，仅在全量查询时有效）
|
||||
page_size: 每页数量（可选，仅在全量查询时有效）
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
"""
|
||||
operation = "search" if scene_name else "list"
|
||||
api_logger.info(
|
||||
f"Scene {operation} requested by user {current_user.id}, "
|
||||
f"workspace_id={workspace_id}, keyword={scene_name}, page={page}, page_size={page_size}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 确定工作空间ID
|
||||
if workspace_id:
|
||||
try:
|
||||
ws_uuid = UUID(workspace_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid workspace_id format: {workspace_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的工作空间ID格式")
|
||||
else:
|
||||
ws_uuid = current_user.current_workspace_id
|
||||
if not ws_uuid:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建Service
|
||||
service = _get_dummy_ontology_service(db)
|
||||
|
||||
# 根据是否提供 scene_name 决定查询方式
|
||||
if scene_name and scene_name.strip():
|
||||
# 验证分页参数（模糊搜索也支持分页）
|
||||
if page is not None and page < 1:
|
||||
api_logger.warning(f"Invalid page number: {page}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "页码必须大于0")
|
||||
|
||||
if page_size is not None and page_size < 1:
|
||||
api_logger.warning(f"Invalid page_size: {page_size}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "每页数量必须大于0")
|
||||
|
||||
# 如果只提供了page或page_size中的一个，返回错误
|
||||
if (page is not None and page_size is None) or (page is None and page_size is not None):
|
||||
api_logger.warning(f"Incomplete pagination params: page={page}, page_size={page_size}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "分页参数page和pagesize必须同时提供")
|
||||
|
||||
# 模糊搜索场景（支持分页）
|
||||
scenes = service.search_scenes_by_name(scene_name.strip(), ws_uuid)
|
||||
total = len(scenes)
|
||||
|
||||
# 如果提供了分页参数，进行分页处理
|
||||
if page is not None and page_size is not None:
|
||||
start_idx = (page - 1) * page_size
|
||||
end_idx = start_idx + page_size
|
||||
scenes = scenes[start_idx:end_idx]
|
||||
|
||||
# 构建响应
|
||||
items = []
|
||||
for scene in scenes:
|
||||
# 获取前3个class_name作为entity_type
|
||||
entity_type = [cls.class_name for cls in scene.classes[:3]] if scene.classes else None
|
||||
# 动态计算 type_num
|
||||
type_num = len(scene.classes) if scene.classes else 0
|
||||
|
||||
items.append(SceneResponse(
|
||||
scene_id=scene.scene_id,
|
||||
scene_name=scene.scene_name,
|
||||
scene_description=scene.scene_description,
|
||||
type_num=type_num,
|
||||
entity_type=entity_type,
|
||||
workspace_id=scene.workspace_id,
|
||||
created_at=scene.created_at,
|
||||
updated_at=scene.updated_at,
|
||||
classes_count=type_num
|
||||
))
|
||||
|
||||
# 构建响应（包含分页信息）
|
||||
if page is not None and page_size is not None:
|
||||
# 计算是否有下一页
|
||||
hasnext = (page * page_size) < total
|
||||
|
||||
pagination_info = PaginationInfo(
|
||||
page=page,
|
||||
pagesize=page_size,
|
||||
total=total,
|
||||
hasnext=hasnext
|
||||
)
|
||||
response = SceneListResponse(items=items, page=pagination_info)
|
||||
else:
|
||||
response = SceneListResponse(items=items)
|
||||
|
||||
api_logger.info(
|
||||
f"Scene search completed: found {len(items)} scenes matching '{scene_name}' "
|
||||
f"in workspace {ws_uuid}, total={total}"
|
||||
)
|
||||
else:
|
||||
# 获取所有场景（支持分页）
|
||||
# 验证分页参数
|
||||
if page is not None and page < 1:
|
||||
api_logger.warning(f"Invalid page number: {page}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "页码必须大于0")
|
||||
|
||||
if page_size is not None and page_size < 1:
|
||||
api_logger.warning(f"Invalid page_size: {page_size}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "每页数量必须大于0")
|
||||
|
||||
# 如果只提供了page或page_size中的一个，返回错误
|
||||
if (page is not None and page_size is None) or (page is None and page_size is not None):
|
||||
api_logger.warning(f"Incomplete pagination params: page={page}, page_size={page_size}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "分页参数page和pagesize必须同时提供")
|
||||
|
||||
scenes, total = service.list_scenes(ws_uuid, page, page_size)
|
||||
|
||||
# 构建响应
|
||||
items = []
|
||||
for scene in scenes:
|
||||
# 获取前3个class_name作为entity_type
|
||||
entity_type = [cls.class_name for cls in scene.classes[:3]] if scene.classes else None
|
||||
# 动态计算 type_num
|
||||
type_num = len(scene.classes) if scene.classes else 0
|
||||
|
||||
items.append(SceneResponse(
|
||||
scene_id=scene.scene_id,
|
||||
scene_name=scene.scene_name,
|
||||
scene_description=scene.scene_description,
|
||||
type_num=type_num,
|
||||
entity_type=entity_type,
|
||||
workspace_id=scene.workspace_id,
|
||||
created_at=scene.created_at,
|
||||
updated_at=scene.updated_at,
|
||||
classes_count=type_num
|
||||
))
|
||||
|
||||
# 构建响应（包含分页信息）
|
||||
if page is not None and page_size is not None:
|
||||
# 计算是否有下一页
|
||||
hasnext = (page * page_size) < total
|
||||
|
||||
pagination_info = PaginationInfo(
|
||||
page=page,
|
||||
pagesize=page_size,
|
||||
total=total,
|
||||
hasnext=hasnext
|
||||
)
|
||||
response = SceneListResponse(items=items, page=pagination_info)
|
||||
else:
|
||||
response = SceneListResponse(items=items)
|
||||
|
||||
api_logger.info(f"Scene list retrieved successfully, count={len(items)}, total={total}")
|
||||
|
||||
return success(data=response.model_dump(mode='json'), msg="查询成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in scene {operation}: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in scene {operation}: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "查询失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in scene {operation}: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "查询失败", str(e))
|
||||
|
||||
|
||||
# ==================== 本体类型管理接口 ====================
|
||||
|
||||
async def create_class_handler(
|
||||
request: ClassCreateRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""创建本体类型（统一使用列表形式，支持单个或批量）"""
|
||||
|
||||
# 根据列表长度判断是单个还是批量
|
||||
count = len(request.classes)
|
||||
mode = "single" if count == 1 else "batch"
|
||||
|
||||
api_logger.info(
|
||||
f"Class creation ({mode}) requested by user {current_user.id}, "
|
||||
f"scene_id={request.scene_id}, count={count}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建Service
|
||||
service = _get_dummy_ontology_service(db)
|
||||
|
||||
# 准备类型数据
|
||||
classes_data = [
|
||||
{
|
||||
"class_name": item.class_name,
|
||||
"class_description": item.class_description
|
||||
}
|
||||
for item in request.classes
|
||||
]
|
||||
|
||||
if count == 1:
|
||||
# 单个创建
|
||||
class_data = classes_data[0]
|
||||
ontology_class = service.create_class(
|
||||
scene_id=request.scene_id,
|
||||
class_name=class_data["class_name"],
|
||||
class_description=class_data["class_description"],
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
# 构建单个响应
|
||||
response = ClassResponse(
|
||||
class_id=ontology_class.class_id,
|
||||
class_name=ontology_class.class_name,
|
||||
class_description=ontology_class.class_description,
|
||||
scene_id=ontology_class.scene_id,
|
||||
created_at=ontology_class.created_at,
|
||||
updated_at=ontology_class.updated_at
|
||||
)
|
||||
|
||||
api_logger.info(f"Class created successfully: {ontology_class.class_id}")
|
||||
|
||||
return success(data=response.model_dump(mode='json'), msg="类型创建成功")
|
||||
|
||||
else:
|
||||
# 批量创建
|
||||
created_classes, errors = service.create_classes_batch(
|
||||
scene_id=request.scene_id,
|
||||
classes=classes_data,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
# 构建批量响应
|
||||
items = []
|
||||
for ontology_class in created_classes:
|
||||
items.append(ClassResponse(
|
||||
class_id=ontology_class.class_id,
|
||||
class_name=ontology_class.class_name,
|
||||
class_description=ontology_class.class_description,
|
||||
scene_id=ontology_class.scene_id,
|
||||
created_at=ontology_class.created_at,
|
||||
updated_at=ontology_class.updated_at
|
||||
))
|
||||
|
||||
response = ClassBatchCreateResponse(
|
||||
total=len(classes_data),
|
||||
success_count=len(created_classes),
|
||||
failed_count=len(errors),
|
||||
items=items,
|
||||
errors=errors if errors else None
|
||||
)
|
||||
|
||||
api_logger.info(
|
||||
f"Batch class creation completed: "
|
||||
f"success={len(created_classes)}, failed={len(errors)}"
|
||||
)
|
||||
|
||||
return success(data=response.model_dump(mode='json'), msg="批量创建完成")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in class creation: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in class creation: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "类型创建失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in class creation: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "类型创建失败", str(e))
|
||||
|
||||
|
||||
async def update_class_handler(
|
||||
class_id: str,
|
||||
request: ClassUpdateRequest,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""更新本体类型"""
|
||||
api_logger.info(
|
||||
f"Class update requested by user {current_user.id}, "
|
||||
f"class_id={class_id}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 验证UUID格式
|
||||
try:
|
||||
class_uuid = UUID(class_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid class_id format: {class_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的类型ID格式")
|
||||
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建Service
|
||||
service = _get_dummy_ontology_service(db)
|
||||
|
||||
# 更新类型
|
||||
ontology_class = service.update_class(
|
||||
class_id=class_uuid,
|
||||
class_name=request.class_name,
|
||||
class_description=request.class_description,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
# 构建响应
|
||||
response = ClassResponse(
|
||||
class_id=ontology_class.class_id,
|
||||
class_name=ontology_class.class_name,
|
||||
class_description=ontology_class.class_description,
|
||||
scene_id=ontology_class.scene_id,
|
||||
created_at=ontology_class.created_at,
|
||||
updated_at=ontology_class.updated_at
|
||||
)
|
||||
|
||||
api_logger.info(f"Class updated successfully: {class_id}")
|
||||
|
||||
return success(data=response.model_dump(mode='json'), msg="类型更新成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in class update: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in class update: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "类型更新失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in class update: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "类型更新失败", str(e))
|
||||
|
||||
|
||||
async def delete_class_handler(
|
||||
class_id: str,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""删除本体类型"""
|
||||
api_logger.info(
|
||||
f"Class deletion requested by user {current_user.id}, "
|
||||
f"class_id={class_id}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 验证UUID格式
|
||||
try:
|
||||
class_uuid = UUID(class_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid class_id format: {class_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的类型ID格式")
|
||||
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建Service
|
||||
service = _get_dummy_ontology_service(db)
|
||||
|
||||
# 删除类型
|
||||
success_flag = service.delete_class(
|
||||
class_id=class_uuid,
|
||||
workspace_id=workspace_id
|
||||
)
|
||||
|
||||
api_logger.info(f"Class deleted successfully: {class_id}")
|
||||
|
||||
return success(data={"deleted": success_flag}, msg="类型删除成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in class deletion: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in class deletion: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "类型删除失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in class deletion: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "类型删除失败", str(e))
|
||||
|
||||
|
||||
async def get_class_handler(
|
||||
class_id: str,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""获取单个本体类型"""
|
||||
api_logger.info(
|
||||
f"Get class requested by user {current_user.id}, "
|
||||
f"class_id={class_id}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 验证UUID格式
|
||||
try:
|
||||
class_uuid = UUID(class_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid class_id format: {class_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的类型ID格式")
|
||||
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建Service
|
||||
service = _get_dummy_ontology_service(db)
|
||||
|
||||
# 获取类型（会抛出ValueError如果不存在）
|
||||
ontology_class = service.get_class_by_id(class_uuid, workspace_id)
|
||||
|
||||
# 构建响应
|
||||
response = ClassResponse(
|
||||
class_id=ontology_class.class_id,
|
||||
class_name=ontology_class.class_name,
|
||||
class_description=ontology_class.class_description,
|
||||
scene_id=ontology_class.scene_id,
|
||||
created_at=ontology_class.created_at,
|
||||
updated_at=ontology_class.updated_at
|
||||
)
|
||||
|
||||
api_logger.info(f"Class retrieved successfully: {class_id}")
|
||||
|
||||
return success(data=response.model_dump(mode='json'), msg="查询成功")
|
||||
|
||||
except ValueError as e:
|
||||
# 类型不存在或无权限访问
|
||||
api_logger.warning(f"Validation error in get class: {str(e)}")
|
||||
return fail(BizCode.NOT_FOUND, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in get class: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "查询失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in get class: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "查询失败", str(e))
|
||||
|
||||
|
||||
async def classes_handler(
|
||||
scene_id: str,
|
||||
class_name: Optional[str] = None,
|
||||
db: Session = Depends(get_db),
|
||||
current_user: User = Depends(get_current_user)
|
||||
):
|
||||
"""获取类型列表（支持模糊搜索和全量查询）
|
||||
|
||||
当提供 class_name 参数时，进行模糊搜索；
|
||||
当不提供 class_name 参数时，返回场景下的所有类型。
|
||||
|
||||
Args:
|
||||
scene_id: 场景ID（必填）
|
||||
class_name: 类型名称关键词（可选，支持模糊匹配）
|
||||
db: 数据库会话
|
||||
current_user: 当前用户
|
||||
"""
|
||||
operation = "search" if class_name else "list"
|
||||
api_logger.info(
|
||||
f"Class {operation} requested by user {current_user.id}, "
|
||||
f"keyword={class_name}, scene_id={scene_id}"
|
||||
)
|
||||
|
||||
try:
|
||||
# 验证UUID格式
|
||||
try:
|
||||
scene_uuid = UUID(scene_id)
|
||||
except ValueError:
|
||||
api_logger.warning(f"Invalid scene_id format: {scene_id}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "无效的场景ID格式")
|
||||
|
||||
# 获取当前工作空间ID
|
||||
workspace_id = current_user.current_workspace_id
|
||||
if not workspace_id:
|
||||
api_logger.warning(f"User {current_user.id} has no current workspace")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", "当前用户没有工作空间")
|
||||
|
||||
# 创建Service
|
||||
service = _get_dummy_ontology_service(db)
|
||||
|
||||
# 获取场景信息
|
||||
scene = service.get_scene_by_id(scene_uuid, workspace_id)
|
||||
if not scene:
|
||||
api_logger.warning(f"Scene not found: {scene_id}")
|
||||
return fail(BizCode.NOT_FOUND, "场景不存在", f"未找到ID为 {scene_id} 的场景")
|
||||
|
||||
# 根据是否提供 class_name 决定查询方式
|
||||
if class_name and class_name.strip():
|
||||
# 模糊搜索类型
|
||||
classes = service.search_classes_by_name(class_name.strip(), scene_uuid, workspace_id)
|
||||
else:
|
||||
# 获取所有类型
|
||||
classes = service.list_classes_by_scene(scene_uuid, workspace_id)
|
||||
|
||||
# 构建响应
|
||||
items = []
|
||||
for ontology_class in classes:
|
||||
items.append(ClassResponse(
|
||||
class_id=ontology_class.class_id,
|
||||
class_name=ontology_class.class_name,
|
||||
class_description=ontology_class.class_description,
|
||||
scene_id=ontology_class.scene_id,
|
||||
created_at=ontology_class.created_at,
|
||||
updated_at=ontology_class.updated_at
|
||||
))
|
||||
|
||||
response = ClassListResponse(
|
||||
total=len(items),
|
||||
scene_id=scene_uuid,
|
||||
scene_name=scene.scene_name,
|
||||
scene_description=scene.scene_description,
|
||||
items=items
|
||||
)
|
||||
|
||||
if class_name:
|
||||
api_logger.info(
|
||||
f"Class search completed: found {len(items)} classes matching '{class_name}' "
|
||||
f"in scene {scene_id}"
|
||||
)
|
||||
else:
|
||||
api_logger.info(f"Class list retrieved successfully, count={len(items)}")
|
||||
|
||||
return success(data=response.model_dump(mode='json'), msg="查询成功")
|
||||
|
||||
except ValueError as e:
|
||||
api_logger.warning(f"Validation error in class {operation}: {str(e)}")
|
||||
return fail(BizCode.BAD_REQUEST, "请求参数无效", str(e))
|
||||
|
||||
except RuntimeError as e:
|
||||
api_logger.error(f"Runtime error in class {operation}: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "查询失败", str(e))
|
||||
|
||||
except Exception as e:
|
||||
api_logger.error(f"Unexpected error in class {operation}: {str(e)}", exc_info=True)
|
||||
return fail(BizCode.INTERNAL_ERROR, "查询失败", str(e))
|
||||
Reference in New Issue
Block a user