refactoring of the graphs

Author: VinciGit00

examples/openai/custom_graph_openai.py

@@ -69,12 +69,13 @@
         rag_node,
         generate_answer_node,
     ],
-    edges={
+    edges=[
         (robot_node, fetch_node),
         (fetch_node, parse_node),
         (parse_node, rag_node),
         (rag_node, generate_answer_node)
-    },
+    ],
+    entry_point=robot_node
 )
 
 # ************************************************

manual deployment/commit_and_push_with_tests.sh

@@ -13,6 +13,8 @@ pylint pylint scrapegraphai/**/*.py scrapegraphai/*.py tests/**/*.py
 
 cd tests
 
+poetry install
+
 # Run pytest
 if ! pytest; then
     echo "Pytest failed. Aborting commit and push."

scrapegraphai/graphs/base_graph.py

@@ -11,29 +11,29 @@ class BaseGraph:
     BaseGraph manages the execution flow of a graph composed of interconnected nodes.
 
     Attributes:
-        nodes (dict): A dictionary mapping each node's name to its corresponding node instance.
-        edges (dict): A dictionary representing the directed edges of the graph where each 
+        nodes (list): A dictionary mapping each node's name to its corresponding node instance.
+        edges (list): A dictionary representing the directed edges of the graph where each
                       key-value pair corresponds to the from-node and to-node relationship.
         entry_point (str): The name of the entry point node from which the graph execution begins.
 
     Methods:
-        execute(initial_state): Executes the graph's nodes starting from the entry point and 
+        execute(initial_state): Executes the graph's nodes starting from the entry point and
                                 traverses the graph based on the provided initial state.
 
     Args:
         nodes (iterable): An iterable of node instances that will be part of the graph.
-        edges (iterable): An iterable of tuples where each tuple represents a directed edge 
+        edges (iterable): An iterable of tuples where each tuple represents a directed edge
                           in the graph, defined by a pair of nodes (from_node, to_node).
         entry_point (BaseNode): The node instance that represents the entry point of the graph.
     """
 
-    def __init__(self, nodes: list, edges: dict, entry_point: str):
+    def __init__(self, nodes: list, edges: list, entry_point: str):
         """
         Initializes the graph with nodes, edges, and the entry point.
         """
 
-        self.nodes = {node.node_name: node for node in nodes}
-        self.edges = self._create_edges(edges)
+        self.nodes = nodes
+        self.edges = self._create_edges({e for e in edges})
         self.entry_point = entry_point.node_name
 
         if nodes[0].node_name != entry_point.node_name:
@@ -58,8 +58,8 @@ def _create_edges(self, edges: list) -> dict:
 
     def execute(self, initial_state: dict) -> dict:
         """
-        Executes the graph by traversing nodes starting from the entry point. The execution 
-        follows the edges based on the result of each node's execution and continues until 
+        Executes the graph by traversing nodes starting from the entry point. The execution
+        follows the edges based on the result of each node's execution and continues until
         it reaches a node with no outgoing edges.
 
         Args:
@@ -68,6 +68,7 @@ def execute(self, initial_state: dict) -> dict:
         Returns:
             dict: The state after execution has completed, which may have been altered by the nodes.
         """
+        print(self.nodes)
         current_node_name = self.nodes[0]
         state = initial_state
 

scrapegraphai/graphs/script_creator_graph.py

@@ -1,4 +1,4 @@
-""" 
+"""
 Module for creating the smart scraper
 """
 from .base_graph import BaseGraph
@@ -57,17 +57,17 @@ def _create_graph(self):
         )
 
         return BaseGraph(
-            nodes={
+            nodes=[
                 fetch_node,
                 parse_node,
                 rag_node,
                 generate_scraper_node,
-            },
-            edges={
+            ],
+            edges=[
                 (fetch_node, parse_node),
                 (parse_node, rag_node),
                 (rag_node, generate_scraper_node)
-            },
+            ],
             entry_point=fetch_node
         )
 

scrapegraphai/graphs/search_graph.py

@@ -11,6 +11,7 @@
 )
 from .abstract_graph import AbstractGraph
 
+
 class SearchGraph(AbstractGraph):
     """ 
     Module for searching info on the internet
@@ -49,19 +50,19 @@ def _create_graph(self):
         )
 
         return BaseGraph(
-            nodes={
+            nodes=[
                 search_internet_node,
                 fetch_node,
                 parse_node,
                 rag_node,
                 generate_answer_node,
-            },
-            edges={
+            ],
+            edges=[
                 (search_internet_node, fetch_node),
                 (fetch_node, parse_node),
                 (parse_node, rag_node),
                 (rag_node, generate_answer_node)
-            },
+            ],
             entry_point=search_internet_node
         )
 

scrapegraphai/graphs/smart_scraper_graph.py

@@ -1,4 +1,4 @@
-""" 
+"""
 Module for creating the smart scraper
 """
 from .base_graph import BaseGraph
@@ -59,11 +59,12 @@ def _create_graph(self):
                 rag_node,
                 generate_answer_node,
             ],
-            edges={
+            edges=[
                 (fetch_node, parse_node),
                 (parse_node, rag_node),
                 (rag_node, generate_answer_node)
-            }
+            ],
+            entry_point=fetch_node
         )
 
     def run(self) -> str:

scrapegraphai/graphs/speech_graph.py

@@ -62,19 +62,19 @@ def _create_graph(self):
         )
 
         return BaseGraph(
-            nodes={
+            nodes=[
                 fetch_node,
                 parse_node,
                 rag_node,
                 generate_answer_node,
                 text_to_speech_node
-            },
-            edges={
+            ],
+            edges=[
                 (fetch_node, parse_node),
                 (parse_node, rag_node),
                 (rag_node, generate_answer_node),
                 (generate_answer_node, text_to_speech_node)
-            },
+            ],
             entry_point=fetch_node
         )