🚀 feat(graph): add from_payload class method to Graph class

🚀 feat(utils.py): import extract_input_variables_from_prompt from langflow.interface.utils
The `from_payload` class method is added to the `Graph` class to create a graph from a payload. This method takes a dictionary as input and returns a `Graph` object. The `extract_input_variables_from_prompt` function is imported from `langflow.interface.utils` to extract input variables from a prompt. This function is used in other parts of the codebase to extract input variables from prompts.

src/backend/langflow/graph/graph/base.py

@@ -24,6 +24,27 @@ class Graph:
         self._edges = edges
         self._build_graph()
 
+    @classmethod
+    @classmethod
+    def from_payload(cls, payload: Dict) -> "Graph":
+        """
+        Creates a graph from a payload.
+
+        Args:
+            payload (Dict): The payload to create the graph from.
+
+        Returns:
+            Graph: The created graph.
+        """
+        if "data" in payload:
+            payload = payload["data"]
+        try:
+            nodes = payload["nodes"]
+            edges = payload["edges"]
+            return cls(nodes, edges)
+        except KeyError as exc:
+            raise ValueError("Invalid payload") from exc
+
     def _build_graph(self) -> None:
         """Builds the graph from the nodes and edges."""
         self.nodes = self._build_vertices()

src/backend/langflow/graph/utils.py

@@ -1,6 +1,7 @@
-import re
 from typing import Any, Union
 
+from langflow.interface.utils import extract_input_variables_from_prompt
+
 
 def validate_prompt(prompt: str):
     """Validate prompt."""
@@ -15,11 +16,6 @@ def fix_prompt(prompt: str):
     return prompt + " {input}"
 
 
-def extract_input_variables_from_prompt(prompt: str) -> list[str]:
-    """Extract input variables from prompt."""
-    return re.findall(r"{(.*?)}", prompt)
-
-
 def flatten_list(list_of_lists: list[Union[list, Any]]) -> list:
     """Flatten list of lists."""
     new_list = []