Codex
156 lines
3.8 KiB
Python
156 lines
3.8 KiB
Python
"""
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节点注册中心
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"""
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import logging
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from typing import Dict, List, Optional, Type
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from .base import BaseNode
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logger = logging.getLogger(__name__)
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class NodeRegistry:
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"""
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节点注册中心
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管理所有工作流节点的注册和获取
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"""
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_nodes: Dict[str, Type[BaseNode]] = {}
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@classmethod
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def register(cls, node_class: Type[BaseNode]) -> Type[BaseNode]:
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"""
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注册节点（可作为装饰器使用）
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Args:
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node_class: 节点类
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Returns:
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节点类
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"""
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node_type = node_class.node_type
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if not node_type:
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raise ValueError(f'Node {node_class.__name__} must have a node_type')
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cls._nodes[node_type] = node_class
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logger.info(f'Registered AI workflow node: {node_type}')
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return node_class
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@classmethod
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def get(cls, node_type: str) -> Optional[Type[BaseNode]]:
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"""
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获取节点类
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Args:
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node_type: 节点类型
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Returns:
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节点类或 None
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"""
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return cls._nodes.get(node_type)
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@classmethod
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def create_instance(cls, node_type: str, config: Dict = None) -> Optional[BaseNode]:
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"""
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创建节点实例
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Args:
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node_type: 节点类型
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config: 节点配置
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Returns:
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节点实例或 None
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"""
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node_class = cls.get(node_type)
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if not node_class:
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logger.warning(f'Unknown node type: {node_type}')
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return None
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return node_class(config=config)
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@classmethod
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def get_all_schemas(cls) -> List[Dict]:
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"""
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获取所有节点 Schema
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Returns:
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节点 Schema 列表
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"""
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return [node.get_schema() for node in cls._nodes.values()]
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@classmethod
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def get_schemas_by_category(cls) -> Dict[str, List[Dict]]:
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"""
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按分类获取节点 Schema
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Returns:
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按分类分组的节点 Schema
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"""
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result = {}
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for node in cls._nodes.values():
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category = node.node_category
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if category not in result:
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result[category] = []
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result[category].append(node.get_schema())
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return result
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@classmethod
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def get_all_types(cls) -> List[str]:
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"""
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获取所有已注册的节点类型
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Returns:
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节点类型列表
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"""
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return list(cls._nodes.keys())
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# 自动加载所有内置节点
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def _load_builtin_nodes():
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"""加载所有内置节点"""
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required_modules = [
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'start_node',
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'end_node',
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'condition_node',
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'template_node',
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'parallel_node',
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'merge_node',
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]
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optional_modules = [
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'llm_node',
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'code_node',
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'http_node',
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'variable_node',
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'database_node',
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'dialog_nodes',
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'intent_node',
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'loop_node',
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'subflow_node',
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'text_to_sql_node',
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'snowflake_cortex_node',
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'knowledge_retrieval_node',
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]
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from importlib import import_module
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for module_name in required_modules:
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import_module(f'{__package__}.builtin.{module_name}')
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for module_name in optional_modules:
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try:
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import_module(f'{__package__}.builtin.{module_name}')
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except ImportError as e:
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logger.warning(
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'Skipped optional AI workflow node module %s because dependencies are unavailable: %s',
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module_name,
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e,
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)
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# 延迟加载
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try:
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_load_builtin_nodes()
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except ImportError as e:
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logger.warning(f'Failed to load some builtin nodes: {e}')
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