# 创建知识库
POST /api/rag/knowledge-bases/
{
    "name": "技术文档库",
    "description": "存储技术相关文档",
    "permission": "private",
    "parser_config": {...},
    "embed_id": "bge-m3"
}

# 获取知识库列表
GET /api/rag/knowledge-bases/

# 批量上传文档
POST /api/rag/upload/
{
    "files": [file1, file2, ...],
    "knowledge_base_id": "kb-uuid"
}

# 文档操作
PUT /api/rag/documents/{document_id}/
{
    "action": "start_parse"  # start_parse, stop_parse, delete, refresh
}

# 创建LLM模板
POST /api/llm/llm-templates/
{
    "template_name": "OpenAI GPT",
    "template_code": "openai",
    "llm_template_config": [...]
}

# 创建LLM实例
POST /api/llm/llm-instances/
{
    "llm_template_id": "template-uuid",
    "llm_config": {
        "url": "https://api.openai.com",
        "api_key": "your-api-key"
    }
}

# 配置用户模型
POST /api/llm/llm-model-user-configs/
{
    "configure_list": [
        {
            "llm_instance_id": "instance-uuid",
            "llm_model_id": "model-uuid",
            "config_type": "CHAT",
            "config_value": "gpt-3.5-turbo"
        }
    ]
}

# 用户注册（仅超级用户）
POST /api/users/register/
{
    "username": "newuser",
    "email": "[email protected]",
    "password": "password123"
}

# 用户登录
POST /api/users/login/
{
    "username": "username",
    "password": "password"
}

class KnowledgeBaseViewModel:
    def __init__(self, user):
        self.user = user
    
    def create_knowledge_base(self, data: Dict[str, Any]) -> KnowledgeBase:
        """创建知识库的业务逻辑"""
        pass
    
    def get_queryset(self, is_swagger_fake_view: bool = False):
        """根据用户权限过滤查询集"""
        pass

class RAGComponentFactory:
    def get_default_vector_database(self, index_name: str) -> ElasticsearchVectors:
        """获取向量数据库实例"""
        pass
    
    def get_default_file_storage(self) -> FileStorage:
        """获取文件存储实例"""
        pass

class MinerUWorkflow(ParserWorkflow):
    def execute(self, doc_id: str, doc_info: Dict[str, Any], ...):
        """执行文档处理工作流"""
        # 1. 初始化
        # 2. 获取文件内容
        # 3. 解析文件
        # 4. 提取块信息
        # 5. 处理向量化
        # 6. 更新状态
        pass