Open Bboyjie opened 4 days ago
Hey there, @Bboyjie! I'm here to help you with any bugs, questions, or contributions you have. Let's tackle this issue together!
You can use the MarkdownElementNodeParser
independently without needing an actual LLM or api_key
by using a mock LLM. Here's how you can set it up:
from llama_index.legacy.llms import MockLLM
from llama_index.legacy.node_parser.relational.markdown_element import (
MarkdownElementNodeParser,
)
node_parser = MarkdownElementNodeParser(llm=MockLLM())
By using MockLLM()
, you can bypass the requirement for an LLM or api_key
, allowing the MarkdownElementNodeParser
to function independently [1].
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@dosu. Hello,
I am working with Markdown parsers and would like to understand the differences between MarkdownNodeParser and MarkdownElementNodeParser. Specifically, I am curious about the following:
What are the main differences between MarkdownNodeParser and MarkdownElementNodeParser? Is MarkdownElementNodeParser an extension or specialization of MarkdownNodeParser, or are they completely separate implementations? Given that I have Markdown text extracted from PDF documents, which of these parsers should I use, and how should I use them effectively? Any insights or guidance would be greatly appreciated!
Thank you very much for your help!
The MarkdownNodeParser
and MarkdownElementNodeParser
serve different purposes in the LlamaIndex codebase:
MarkdownNodeParser:
TextNode
objects from parsed sections, optionally including metadata, and can display progress for large documents [1][2].MarkdownElementNodeParser:
Regarding their relationship, there is no information indicating that MarkdownElementNodeParser
is an extension or specialization of MarkdownNodeParser
. They appear to be separate implementations designed for different parsing needs.
For Markdown text extracted from PDF documents, the choice between these parsers depends on your specific requirements:
MarkdownNodeParser
if you need to focus on splitting documents based on headers and managing metadata.MarkdownElementNodeParser
if you need to handle various markdown elements like tables and require more detailed parsing of document structure.Choose the parser that aligns best with your document structure and parsing needs.
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@dosu. Hello,
I am working on parsing Markdown text that has been extracted from PDF documents with the goal of reconstructing the original document structure. Specifically, I want to split the Markdown text by headings to restore the chapter structure of the PDF. For each section corresponding to a heading, I want to extract different elements, such as tables, and process them accordingly. My aim is to parse the PDF at different levels of granularity and hierarchy.
Given this objective, how can I effectively utilize MarkdownNodeParser and MarkdownElementNodeParser to achieve this? Are there other methods or tools that would be more suitable for processing a list of documents (Documents)?
Any advice or guidance would be greatly appreciated!
Thank you very much for your help!
To achieve your goal of reconstructing the original document structure from Markdown text extracted from PDFs, you can effectively utilize both MarkdownNodeParser
and MarkdownElementNodeParser
as follows:
MarkdownNodeParser:
MarkdownElementNodeParser:
Approach:
MarkdownNodeParser
to split the document into sections based on headings. This will help you organize the text into a hierarchical structure.MarkdownElementNodeParser
to extract and process specific elements like tables, lists, and code blocks.Additional Tools:
This approach allows you to effectively parse and reconstruct the document structure while handling various Markdown elements.
To continue talking to Dosu, mention @dosu.
@dosu. To achieve your goal of reconstructing the original document structure from Markdown text extracted from PDFs, you can effectively utilize both MarkdownNodeParser and MarkdownElementNodeParser,Give me some code examples。
To reconstruct the original document structure from Markdown text extracted from PDFs using both MarkdownNodeParser
and MarkdownElementNodeParser
, you can follow these steps with the provided code examples:
MarkdownNodeParser
to Split by Headings:from llama_index.core.node_parser.file.markdown import MarkdownNodeParser
# Sample Markdown text
markdown_text = """
# Chapter 1
This is the introduction.
## Section 1.1
Details about section 1.1.
## Section 1.2
Details about section 1.2.
# Chapter 2
This is another chapter.
"""
# Initialize the MarkdownNodeParser
node_parser = MarkdownNodeParser()
# Parse the document into nodes
nodes = node_parser.get_nodes_from_node(markdown_text)
# Print the nodes
for node in nodes:
print(f"Header: {node.metadata.get('Header_1', 'No Header')}")
print(f"Content: {node.text}\n")
MarkdownElementNodeParser
to Extract Elements:from llama_index.legacy.node_parser.relational.markdown_element import MarkdownElementNodeParser
# Sample Markdown text with a table
markdown_text_with_table = """
# Chapter 1
This is the introduction.
| Column 1 | Column 2 |
|----------|----------|
| Value 1 | Value 2 |
| Value 3 | Value 4 |
"""
# Initialize the MarkdownElementNodeParser
element_parser = MarkdownElementNodeParser()
# Extract elements from the document
elements = element_parser.extract_elements(markdown_text_with_table)
# Print the extracted elements
for element in elements:
if element['type'] == 'table':
print("Table found:")
print(element['content'])
else:
print(f"Text: {element['content']}\n")
Approach:
MarkdownNodeParser
to split the document into sections based on headings. This will help you organize the text into a hierarchical structure.MarkdownElementNodeParser
to extract and process specific elements like tables, lists, and code blocks.These examples demonstrate how to use both parsers to handle different aspects of Markdown text processing, allowing you to reconstruct the document structure and extract detailed elements.
To continue talking to Dosu, mention @dosu.
Question Validation
Question
Hello, I am currently using MarkdownElementNodeParser and have encountered an issue. Although I am using Tongyi LLMs, they do not support it well. When I set llm to None, the system requires an api_key. Could someone please advise on how to use MarkdownElementNodeParser independently without needing an api_key ? Thank you very much for your help!