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A semantic web scraping and summarization toolkit.

Project description

vibescraper

vibescraper is a Python utility that generates an AI summary of web results based on a search query.


How it works

  • Web Search: Searched the web using search engine API.
  • Semantic Chunking: Extracts html from each url in the search results, then divides the html page content into meaningful chunks.
  • Embedding Generation: Generate vector embeddings for each chunk using openai embedding models.
  • Similarity Search: Find the most relevant content chunks for a given search query.
  • AI Summarization: Generates concise summaries of relevant content, then combines all summaries into a combined summary.
  • JSON Export: Saves results and summaries as JSON files for easy inspection or downstream use.

Installation

Install via pip (from PyPI):

pip install vibescraper

Or install locally with Poetry:

poetry install

NOTE: You need either a Beave or Google search API key to use this, as well as an open AI API key.

to import the keys into config.py after installing run: check-api-keys

in your python project env.


Requirements

  • Python 3.12+
  • OpenAI API key (for embedding and summarization)
  • Other dependencies: numpy, requests, beautifulsoup4, pandas, sqlalchemy, openai, tiktoken, google-api-python-client, html5lib

Usage

  • Install the package into your python project, then import the vibe_search function
from vibescraper import vibe_search

ai_summary = await vibe_search(query='What is the state of the software development job market in 2025?', domain_count=10, text_model='gpt-4o')

Environment Variables

You must set your OpenAI API key (and either a Google or Brave yea keys) as environment variables


License

MIT License


Contributing

Pull requests and issues are welcome!


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