UnisKB/apps/application/flow/common.py

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# coding=utf-8
"""
@project: MaxKB
@Author
@file common.py
@date2024/12/11 17:57
@desc:
"""
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from typing import List, Dict
from django.db.models import QuerySet
from django.utils.translation import gettext as _
from rest_framework.exceptions import ErrorDetail, ValidationError
from common.exception.app_exception import AppApiException
from common.utils.common import group_by
from models_provider.models import Model
from models_provider.tools import get_model_credential
from tools.models.tool import Tool
end_nodes = ['ai-chat-node', 'reply-node', 'function-node', 'function-lib-node', 'application-node',
'image-understand-node', 'speech-to-text-node', 'text-to-speech-node', 'image-generate-node',
'variable-assign-node']
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class Answer:
def __init__(self, content, view_type, runtime_node_id, chat_record_id, child_node, real_node_id,
reasoning_content):
self.view_type = view_type
self.content = content
self.reasoning_content = reasoning_content
self.runtime_node_id = runtime_node_id
self.chat_record_id = chat_record_id
self.child_node = child_node
self.real_node_id = real_node_id
def to_dict(self):
return {'view_type': self.view_type, 'content': self.content, 'runtime_node_id': self.runtime_node_id,
'chat_record_id': self.chat_record_id,
'child_node': self.child_node,
'reasoning_content': self.reasoning_content,
'real_node_id': self.real_node_id}
class NodeChunk:
def __init__(self):
self.status = 0
self.chunk_list = []
def add_chunk(self, chunk):
self.chunk_list.append(chunk)
def end(self, chunk=None):
if chunk is not None:
self.add_chunk(chunk)
self.status = 200
def is_end(self):
return self.status == 200
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class Edge:
def __init__(self, _id: str, _type: str, sourceNodeId: str, targetNodeId: str, **keywords):
self.id = _id
self.type = _type
self.sourceNodeId = sourceNodeId
self.targetNodeId = targetNodeId
for keyword in keywords:
self.__setattr__(keyword, keywords.get(keyword))
class Node:
def __init__(self, _id: str, _type: str, x: int, y: int, properties: dict, **kwargs):
self.id = _id
self.type = _type
self.x = x
self.y = y
self.properties = properties
for keyword in kwargs:
self.__setattr__(keyword, kwargs.get(keyword))
class EdgeNode:
edge: Edge
node: Node
def __init__(self, edge, node):
self.edge = edge
self.node = node
class Workflow:
"""
节点列表
"""
nodes: List[Node]
"""
线列表
"""
edges: List[Edge]
"""
节点id:node
"""
node_map: Dict[str, Node]
"""
节点id:当前节点id上面的所有节点
"""
up_node_map: Dict[str, List[EdgeNode]]
"""
节点id:当前节点id下面的所有节点
"""
next_node_map: Dict[str, List[EdgeNode]]
def __init__(self, nodes: List[Node], edges: List[Edge]):
self.nodes = nodes
self.edges = edges
self.node_map = {node.id: node for node in nodes}
self.up_node_map = {key: [EdgeNode(edge, self.node_map.get(edge.sourceNodeId)) for
edge in edges] for
key, edges in
group_by(edges, key=lambda edge: edge.targetNodeId).items()}
self.next_node_map = {key: [EdgeNode(edge, self.node_map.get(edge.targetNodeId)) for edge in edges] for
key, edges in
group_by(edges, key=lambda edge: edge.sourceNodeId).items()}
def get_node(self, node_id):
"""
根据node_id 获取节点信息
@param node_id: node_id
@return: 节点信息
"""
return self.node_map.get(node_id)
def get_up_edge_nodes(self, node_id) -> List[EdgeNode]:
"""
根据节点id 获取当前连接前置节点和连线
@param node_id: 节点id
@return: 节点连线列表
"""
return self.up_node_map.get(node_id)
def get_next_edge_nodes(self, node_id) -> List[EdgeNode]:
"""
根据节点id 获取当前连接目标节点和连线
@param node_id: 节点id
@return: 节点连线列表
"""
return self.next_node_map.get(node_id)
def get_up_nodes(self, node_id) -> List[Node]:
"""
根据节点id 获取当前连接前置节点
@param node_id: 节点id
@return: 节点列表
"""
return [en.node for en in self.up_node_map.get(node_id)]
def get_next_nodes(self, node_id) -> List[Node]:
"""
根据节点id 获取当前连接目标节点
@param node_id: 节点id
@return: 节点列表
"""
return [en.node for en in self.next_node_map.get(node_id, [])]
@staticmethod
def new_instance(flow_obj: Dict):
nodes = flow_obj.get('nodes')
edges = flow_obj.get('edges')
nodes = [Node(node.get('id'), node.get('type'), **node)
for node in nodes]
edges = [Edge(edge.get('id'), edge.get('type'), **edge) for edge in edges]
return Workflow(nodes, edges)
def get_start_node(self):
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return self.get_node('start-node')
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def get_search_node(self):
return [node for node in self.nodes if node.type == 'search-dataset-node']
def is_valid(self):
"""
校验工作流数据
"""
self.is_valid_model_params()
self.is_valid_start_node()
self.is_valid_base_node()
self.is_valid_work_flow()
@staticmethod
def is_valid_node_params(node: Node):
from application.flow.step_node import get_node
get_node(node.type)(node, None, None)
def is_valid_node(self, node: Node):
self.is_valid_node_params(node)
if node.type == 'condition-node':
branch_list = node.properties.get('node_data').get('branch')
for branch in branch_list:
source_anchor_id = f"{node.id}_{branch.get('id')}_right"
edge_list = [edge for edge in self.edges if edge.sourceAnchorId == source_anchor_id]
if len(edge_list) == 0:
raise AppApiException(500,
_('The branch {branch} of the {node} node needs to be connected').format(
node=node.properties.get("stepName"), branch=branch.get("type")))
else:
edge_list = [edge for edge in self.edges if edge.sourceNodeId == node.id]
if len(edge_list) == 0 and not end_nodes.__contains__(node.type):
raise AppApiException(500, _("{node} Nodes cannot be considered as end nodes").format(
node=node.properties.get("stepName")))
def is_valid_work_flow(self, up_node=None):
if up_node is None:
up_node = self.get_start_node()
self.is_valid_node(up_node)
next_nodes = self.get_next_nodes(up_node)
for next_node in next_nodes:
self.is_valid_work_flow(next_node)
def is_valid_start_node(self):
start_node_list = [node for node in self.nodes if node.id == 'start-node']
if len(start_node_list) == 0:
raise AppApiException(500, _('The starting node is required'))
if len(start_node_list) > 1:
raise AppApiException(500, _('There can only be one starting node'))
def is_valid_model_params(self):
node_list = [node for node in self.nodes if (node.type == 'ai-chat-node' or node.type == 'question-node')]
for node in node_list:
model = QuerySet(Model).filter(id=node.properties.get('node_data', {}).get('model_id')).first()
if model is None:
raise ValidationError(ErrorDetail(
_('The node {node} model does not exist').format(node=node.properties.get("stepName"))))
credential = get_model_credential(model.provider, model.model_type, model.model_name)
model_params_setting = node.properties.get('node_data', {}).get('model_params_setting')
model_params_setting_form = credential.get_model_params_setting_form(
model.model_name)
if model_params_setting is None:
model_params_setting = model_params_setting_form.get_default_form_data()
node.properties.get('node_data', {})['model_params_setting'] = model_params_setting
if node.properties.get('status', 200) != 200:
raise ValidationError(
ErrorDetail(_("Node {node} is unavailable").format(node.properties.get("stepName"))))
node_list = [node for node in self.nodes if (node.type == 'function-lib-node')]
for node in node_list:
function_lib_id = node.properties.get('node_data', {}).get('function_lib_id')
if function_lib_id is None:
raise ValidationError(ErrorDetail(
_('The library ID of node {node} cannot be empty').format(node=node.properties.get("stepName"))))
f_lib = QuerySet(Tool).filter(id=function_lib_id).first()
if f_lib is None:
raise ValidationError(ErrorDetail(_("The function library for node {node} is not available").format(
node=node.properties.get("stepName"))))
def is_valid_base_node(self):
base_node_list = [node for node in self.nodes if node.id == 'base-node']
if len(base_node_list) == 0:
raise AppApiException(500, _('Basic information node is required'))
if len(base_node_list) > 1:
raise AppApiException(500, _('There can only be one basic information node'))