wt is a command-line tool written in Go that extracts meaningful text content from web pages. It fetches a given URL, processes the HTML content, and outputs clean text by excluding unwanted elements like navigation menus, footers, headers, and advertisements. The tool is designed with sensible defaults but allows customization through command-line options.

• Extracts the main content from web pages using the go-readability library.
• Filters out unwanted elements based on HTML tags and attributes.
• Configurable minimum text length threshold.
• Customizable include and exclude tags.
• Designed for easy integration with other tools via piping.
• Can be used to preprocess text for AI applications like Fabric AI.

Ensure you have Go installed (version 1.17 or later).

# Clone the repository
git clone https://github.com/copyleftdev/wt.git

# Navigate to the project directory
cd wt

# Download dependencies
go get ./...

# Build the application
go build -o wt ./cmd

./wt [options] <URL>

• -include: Comma-separated list of HTML tags to include. Defaults to common content tags if not specified.
• -exclude: Comma-separated list of HTML tags to exclude. Defaults to non-content tags if not specified.
• -minlength: Minimum length of text blocks to include (default: 50).

Extract text from a web page using default settings:

./wt https://example.com

Include only specific tags in the extraction:

./wt -include "p,h1,h2" https://example.com

Exclude certain tags from the extraction:

./wt -exclude "div,span" https://example.com

Include only text blocks longer than a specified length:

./wt -minlength 20 https://example.com

Fine-tune the extraction by combining include, exclude, and minimum length options:

./wt -include "p,h1,h2,h3" -exclude "nav,footer,header" -minlength 10 https://example.com

Pipe the extracted text to another command-line tool or script:

./wt https://example.com | another_program

Use wt to preprocess text before feeding it into Fabric AI:

./wt https://example.com | fabric-ai process

• Content Extraction: Quickly extract the main content of a web page, such as articles or blog posts, while removing ads, navigation links, and other extraneous elements.
• SEO and Content Analysis: Analyze the textual content of web pages for SEO purposes, keyword density, and content quality without the distraction of non-content elements.
• Web Scraping: Automate the collection of textual data from web pages to build datasets for machine learning models or research.
• Preprocessing for AI Applications: Preprocess text before using it in natural language processing (NLP) tasks or feeding it into AI models, such as for sentiment analysis, summarization, or categorization.
• Data Mining: Extract meaningful text data from websites for data mining or analytical purposes, such as market research, competitive analysis, or trend identification.
• Accessibility Enhancement: Create accessible versions of web content by stripping out unnecessary HTML elements and focusing on the main content, which can be converted to formats like Braille, speech, or plain text.
• Integration with Automation Tools: Seamlessly integrate with automation scripts and tools to process and handle web content in a standardized format, aiding in tasks like monitoring, alerting, and reporting.
• Research and Archival: Use for archiving web content, retaining only the meaningful text while eliminating unwanted elements, thus saving storage and improving readability.

1. Fetches the Web Page: Uses http.Get to retrieve the HTML content from the provided URL.
2. Extracts Main Content: Utilizes the go-readability library to parse and extract the main article content.
3. Parses HTML Content: Processes the extracted HTML to build a parse tree.
4. Filters Content:
   • Tag Filtering: Includes or excludes content based on specified HTML tags.
   • Attribute Filtering: Skips elements with unwanted class, id, or role attributes.
   • Content Length Threshold: Ignores text blocks shorter than a specified length (default is 50 characters).
5. Outputs Clean Text: Prints the extracted and filtered text to the console or pipes it to another program.

The tool uses sensible defaults for include and exclude tags but allows customization:

• Default Include Tags:

  article, section, p, h1, h2, h3, h4, h5, h6, li, blockquote, pre, code, td, th
  

• Default Exclude Tags:

  script, style, nav, footer, header, aside, form, noscript, iframe, input, button, select, label, option, link, meta, figure, figcaption, dialog, menu, svg, canvas, video, audio, embed, object, and more.
  

You can set the -minlength option to control the minimum length of text blocks to include in the output. The default is 50 characters, but this can be adjusted based on your requirements.

Contributions are welcome! Feel free to open issues or submit pull requests on the GitHub repository.

This project is licensed under the MIT License.

For questions or support, please contact copyleftdev.