ChenTaHung/HTML-Text-Parser
This project is designed to extract text from documents and prepare it for processing by Large Language Models (LLM). Implemented a feature to store and utilize text style information, enabling the program to identify and segment content based on potential headers and titles.
This tool helps you prepare long HTML documents, like financial reports or research papers, for analysis by AI models (Large Language Models). It takes an HTML file as input, extracts all the text while preserving crucial formatting like headings and bolding, and then intelligently breaks it into smaller, meaningful segments. This is ideal for researchers, analysts, or content strategists who need to feed structured, manageable text from web content into AI for tasks like summarization, information extraction, or question answering.
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Use this if you need to process extensive HTML content with an AI model and want to ensure that important structural cues like headings and emphasized text are recognized and used to create logical, manageable chunks.
Not ideal if your primary goal is simple text extraction without needing to preserve formatting for AI processing, or if your documents rely heavily on external CSS files for styling.
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HTML
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Last pushed
Nov 17, 2024
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