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132 lines
4.5 KiB
Python
132 lines
4.5 KiB
Python
"""
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FetchNode Module
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"""
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import json
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from typing import List, Optional
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import pandas as pd
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from langchain_community.document_loaders import PyPDFLoader
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from langchain_core.documents import Document
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from ..docloaders import ChromiumLoader
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from ..utils.remover import remover
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from .base_node import BaseNode
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class FetchNode(BaseNode):
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"""
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A node responsible for fetching the HTML content of a specified URL and updating
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the graph's state with this content. It uses ChromiumLoader to fetch
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the content from a web page asynchronously (with proxy protection).
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This node acts as a starting point in many scraping workflows, preparing the state
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with the necessary HTML content for further processing by subsequent nodes in the graph.
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Attributes:
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headless (bool): A flag indicating whether the browser should run in headless mode.
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verbose (bool): A flag indicating whether to print verbose output 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 (Optional[dict]): Additional configuration for the node.
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node_name (str): The unique identifier name for the node, defaulting to "Fetch".
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"""
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def __init__(
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self,
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input: str,
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output: List[str],
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node_config: Optional[dict] = None,
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node_name: str = "Fetch",
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):
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super().__init__(node_name, "node", input, output, 1)
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self.headless = (
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True if node_config is None else node_config.get("headless", True)
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)
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self.verbose = (
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False if node_config is None else node_config.get("verbose", False)
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)
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def execute(self, state):
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"""
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Executes the node's logic to fetch HTML content from a specified URL and
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update the state with this content.
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Args:
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state (dict): The current state of the graph. The input keys will be used
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to fetch the correct data types from the state.
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Returns:
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dict: The updated state with a new output key containing the fetched HTML content.
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Raises:
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KeyError: If the input key is not found in the state, indicating that the
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necessary information to perform the operation 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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source = input_data[0]
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if (
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self.input == "json_dir"
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or self.input == "xml_dir"
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or self.input == "csv_dir"
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):
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compressed_document = [
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Document(page_content=source, metadata={"source": "local_dir"})
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]
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# if it is a local directory
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# handling for pdf
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elif self.input == "pdf":
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loader = PyPDFLoader(source)
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compressed_document = loader.load()
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elif self.input == "csv":
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compressed_document = [
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Document(
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page_content=str(pd.read_csv(source)), metadata={"source": "csv"}
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)
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]
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elif self.input == "json":
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f = open(source)
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compressed_document = [
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Document(page_content=str(json.load(f)), metadata={"source": "json"})
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]
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elif self.input == "xml":
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with open(source, "r", encoding="utf-8") as f:
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data = f.read()
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compressed_document = [
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Document(page_content=data, metadata={"source": "xml"})
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]
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elif self.input == "pdf_dir":
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pass
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elif not source.startswith("http"):
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compressed_document = [
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Document(page_content=remover(source), metadata={"source": "local_dir"})
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]
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else:
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loader_kwargs = {}
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if self.node_config is not None:
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loader_kwargs = self.node_config.get("loader_kwargs", {})
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loader = ChromiumLoader([source], headless=self.headless, **loader_kwargs)
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document = loader.load()
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compressed_document = [
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Document(page_content=remover(str(document[0].page_content)))
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]
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state.update({self.output[0]: compressed_document})
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return state |