Refactor graph sorting and cutting functionality
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1 changed files with 27 additions and 7 deletions
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@ -1,5 +1,5 @@
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from collections import defaultdict, deque
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from typing import Dict, Generator, List, Type, Union
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from typing import Dict, Generator, List, Optional, Type, Union
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from langchain.chains.base import Chain
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from langflow.graph.edge.base import ContractEdge
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@ -310,19 +310,39 @@ class Graph:
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)
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return f"Graph:\nNodes: {vertex_ids}\nConnections:\n{edges_repr}"
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def layered_topological_sort(self):
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in_degree = {vertex.id: 0 for vertex in self.vertices} # Initialize in-degrees
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def sort_up_to_vertex(self, vertex_id: str) -> "Graph":
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"""Cuts the graph up to a given vertex."""
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# Get the vertices that are connected to the vertex
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# and the vertex itself
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vertices = [self.get_vertex(vertex_id)]
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for edge in self.get_vertex(edge.target_id).edges:
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vertices.append(self.get_vertex(edge.target_id))
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edges = [edge for vertex in vertices for edge in vertex.edges]
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return self.layered_topological_sort(vertices, edges)
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def layered_topological_sort(
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self,
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vertices: Optional[List[Vertex]] = None,
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edges: Optional[List[ContractEdge]] = None,
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) -> List[List[str]]:
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"""Performs a layered topological sort of the vertices in the graph."""
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if vertices is None:
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vertices = self.vertices
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if edges is None:
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edges = self.edges
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in_degree = {vertex.id: 0 for vertex in vertices} # Initialize in-degrees
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graph = defaultdict(list) # Adjacency list representation
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# Build graph and compute in-degrees
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for edge in self.edges:
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for edge in edges:
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graph[edge.source_id].append(edge.target_id)
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in_degree[edge.target_id] += 1
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# Queue for vertices with no incoming edges
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queue = deque(
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vertex.id for vertex in self.vertices if in_degree[vertex.id] == 0
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)
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queue = deque(vertex.id for vertex in vertices if in_degree[vertex.id] == 0)
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layers = []
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current_layer = 0
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