MCPcopy
hub / github.com/langflow-ai/langflow / dump

Method dump

src/lfx/src/lfx/graph/graph/base.py:241–265  ·  view source on GitHub ↗
(
        self, name: str | None = None, description: str | None = None, endpoint_name: str | None = None
    )

Source from the content-addressed store, hash-verified

239 return json.dumps(graph_dict, indent=4, sort_keys=True)
240
241 def dump(
242 self, name: str | None = None, description: str | None = None, endpoint_name: str | None = None
243 ) -> GraphDump:
244 if self.raw_graph_data != {"nodes": [], "edges": []}:
245 data_dict = self.raw_graph_data
246 else:
247 # we need to convert the vertices and edges to json
248 nodes = [node.to_data() for node in self.vertices]
249 edges = [edge.to_data() for edge in self.edges]
250 self.raw_graph_data = {"nodes": nodes, "edges": edges}
251 data_dict = self.raw_graph_data
252 graph_dict: GraphDump = {
253 "data": data_dict,
254 "is_component": len(data_dict.get("nodes", [])) == 1 and data_dict["edges"] == [],
255 }
256 if name:
257 graph_dict["name"] = name
258 elif name is None and self.flow_name:
259 graph_dict["name"] = self.flow_name
260 if description:
261 graph_dict["description"] = description
262 elif description is None and self.description:
263 graph_dict["description"] = self.description
264 graph_dict["endpoint_name"] = str(endpoint_name)
265 return graph_dict
266
267 def add_nodes_and_edges(self, nodes: list[NodeData], edges: list[EdgeData]) -> None:
268 self._vertices = nodes

Calls 2

to_dataMethod · 0.45
getMethod · 0.45