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https://github.com/VinciGit00/Scrapegraph-ai.git
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84 lines
3.1 KiB
Python
84 lines
3.1 KiB
Python
"""
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GraphIterator Module
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"""
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from typing import List, Optional
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import copy
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from tqdm import tqdm
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from .base_node import BaseNode
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class GraphIteratorNode(BaseNode):
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"""
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A node responsible for parsing HTML content from a document.
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The parsed content is split into chunks for further processing.
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This node enhances the scraping workflow by allowing for targeted extraction of
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content, thereby optimizing the processing of large HTML documents.
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Attributes:
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verbose (bool): A flag indicating whether to show print statements during execution.
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Args:
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input (str): Boolean expression defining the input keys needed from the state.
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output (List[str]): List of output keys to be updated in the state.
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node_config (dict): Additional configuration for the node.
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node_name (str): The unique identifier name for the node, defaulting to "Parse".
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"""
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def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None, node_name: str = "GraphIterator"):
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super().__init__(node_name, "node", input, output, 2, node_config)
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self.verbose = False if node_config is None else node_config.get("verbose", False)
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def execute(self, state: dict) -> dict:
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"""
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Executes the node's logic to parse the HTML document content and split it into chunks.
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Args:
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state (dict): The current state of the graph. The input keys will be used to fetch the
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correct data from the state.
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Returns:
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dict: The updated state with the output key containing the parsed content chunks.
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Raises:
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KeyError: If the input keys are not found in the state, indicating that the
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necessary information for parsing the content is missing.
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"""
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if self.verbose:
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print(f"--- Executing {self.node_name} Node ---")
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# Interpret input keys based on the provided input expression
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input_keys = self.get_input_keys(state)
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# Fetching data from the state based on the input keys
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input_data = [state[key] for key in input_keys]
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user_prompt = input_data[0]
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urls = input_data[1]
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graph_instance = self.node_config.get("graph_instance", None)
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if graph_instance is None:
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raise ValueError("Graph instance is required for graph iteration.")
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# set the prompt and source for each url
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graph_instance.prompt = user_prompt
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graphs_instances = []
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for url in urls:
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# make a copy of the graph instance
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copy_graph_instance = copy.copy(graph_instance)
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copy_graph_instance.source = url
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graphs_instances.append(copy_graph_instance)
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# run the graph for each url and use tqdm for progress bar
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graphs_answers = []
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for graph in tqdm(graphs_instances, desc="Processing Graph Instances", disable=not self.verbose):
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result = graph.run()
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graphs_answers.append(result)
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state.update({self.output[0]: graphs_answers})
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return state
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