Popular GitHub Repositories for Webscraping

LLM based autonomous agent that conducts deep local and web research on any topic and generates a long report with citations.

A Powerful web scraper powered by LLM | OpenAI, Gemini & Ollama

? Experimental library for scraping websites using OpenAI's GPT API.

Lightweight library for scraping web-sites with LLMs

This AI Smart Speaker uses speech recognition, TTS (text-to-speech), and STT (speech-to-text) to enable voice and vision-driven conversations, with additional web search capabilities via OpenAI and Langchain agents.

A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.

Lego AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements.

LLM OSINT is a proof-of-concept method of using LLMs to gather information from the internet and then perform a task with this information.

Turn Webpage to LLM friendly input text. Similar to Firecrawl and Jina Reader API. Makes RAG, AI web scraping, image & webpage links extraction easy.

Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.

This repository contains code that automates chat interactions with ChatGPT using Selenium and ChromeDriver. ChatGPT is a large language model that can engage in conversations and provide responses to user inputs. With this code, you can have automated and interactive chats with ChatGPT right from your Python environment.

ScrapeGPT is a RAG-based Telegram bot designed to scrape and analyze websites, then answer questions based on the scraped content. The bot utilizes Retrieval Augmented Generation and webscraping to return natural language answers to the user's queries.

GPT4-powered Slack bot that can scrape URL contents

Predict stock price based on financial news feeds

State of the art object detection in real-time using YOLOV3 algorithm. Augmented with a process that allows easy training of the classifier as a plug & play solution . Provides alert if an item in an alert list is detected.

NLP-10 k report Sentiment Analysis

A powerful tool that leverages Cursor AI and MCP (Model Context Protocol) to easily generate web scrapers for various types of websites.

NLP parser using NER and TDD

The project is a simple sentiment analysis using NLP. The project in written in python with Jupyter notebook. It shows how to do text preprocessing (removing of bad words, stop words, lemmatization, tokenization). It further shows how to save a trained model, and use the model in a real life suitation. The machine learning model used here is k-Nearest Neighbor which is used to build the model. Various performance evaluation techniques are used, and they include confusion matrix, and Scikit-learn libraries classification report which give the accuracy, precision, recall and f1- score preformance of the model. The target values been classified are positive and negative review.