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87 lines
3.0 KiB
Python
87 lines
3.0 KiB
Python
"""
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ParseNode Module
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"""
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from typing import List, Optional
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.document_transformers import Html2TextTransformer
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from ..utils.logging import get_logger
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from .base_node import BaseNode
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class ParseNode(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__(
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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 = "Parse",
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):
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super().__init__(node_name, "node", input, output, 1, node_config)
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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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self.parse_html = (
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True if node_config is None else node_config.get("parse_html", True)
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)
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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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self.logger.info(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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text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
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chunk_size=self.node_config.get("chunk_size", 4096),
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chunk_overlap=0,
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)
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# Parse the document
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docs_transformed = input_data[0]
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if self.parse_html:
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docs_transformed = Html2TextTransformer().transform_documents(input_data[0])
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docs_transformed = docs_transformed[0]
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chunks = text_splitter.split_text(docs_transformed.page_content)
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state.update({self.output[0]: chunks})
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return state
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