Best AI tools for< Find Pages >

Remember is an AI-powered browsing history enhancement tool that revolutionizes the way users interact with their web browsing data. By leveraging AI technology, Remember allows users to search their browsing history using natural language, sync data across devices, and ensure privacy by storing data locally. The tool offers transparent pricing plans and aims to provide a seamless browsing experience for users seeking to effortlessly manage and recall their online activities.

MyEmailExtractor is a free email extractor tool that helps you find and save emails from web pages to a CSV file. It's a great way to quickly increase your leads and grow your business. With MyEmailExtractor, you can extract emails from any website, including search engine results pages (SERPs), social media sites, and professional networking sites. The extracted emails are accurate and up-to-date, and you can export them to a CSV file for easy use.

Zomory is an AI-powered knowledge search tool that allows users to search their Notion workspace with lightning-fast speed. It features natural language understanding, Slack integration, conversational interface, page search, and enterprise-level security. Zomory aims to revolutionize the way users find information by providing instant and accurate search results, eliminating the need for exact keywords. With Zomory 2.0 on the horizon, users can expect an enhanced search experience with exclusive beta access available.

Locus is a free browser extension that uses natural language processing to help users quickly find information on any web page. It allows users to search for specific terms or concepts using natural language queries, and then instantly jumps to the relevant section of the page. Locus also integrates with AI-powered tools such as GPT-3.5 to provide additional functionality, such as summarizing text and generating code. With Locus, users can save time and improve their productivity when reading and researching online.

Joby.ai is an AI-powered job search engine that directly scans 500,000 jobs in real-time from company pages. It uses AI technology to find every company and job that is actively hiring on the internet. Users can search for jobs based on various criteria like job title, keywords, location, experience, date posted, salary range, and more. The platform also offers advanced search capabilities, exact keyword search, and the ability to exclude keywords for more precise results. Joby.ai aims to help users find hidden job opportunities that may not be available on traditional job search platforms like LinkedIn or Indeed, ensuring that all listings are current and actively hiring.

Peeksta is a powerful dropshipping product research tool designed to assist e-commerce entrepreneurs in discovering the best products to sell for their online businesses. It uses advanced algorithms and data analysis to provide insights into trending and profitable products, simplifying the product research process and making it easier for users to identify high-potential items. With features such as AI-powered landing page builders, a curated list of winning products, Facebook and TikTok ad analysis, and in-depth store research, Peeksta empowers users to make informed decisions and optimize their product strategies for success.

Page Pilot AI is a tool that helps e-commerce store owners create high-converting product pages and ad copy using artificial intelligence. It offers features such as product page generation, ad creative generation, and access to winning products. With Page Pilot AI, users can save time and money by automating the product testing phase and launching products faster.

xPage is an AI-powered landing page generator that helps e-commerce businesses create high-converting landing pages in seconds. With xPage, you can transform your product details or AliExpress link into a captivating landing page within seconds. xPage offers a variety of templates to choose from, so you can find the perfect one to captivate your audience and enhance your brand presence. xPage is also easy to use, with an intuitive design that makes it accessible to users of all skill levels. No coding or design expertise is required.

Glitching is an AI-powered dropshipping platform that helps users find winning products, create high-converting product pages, and run effective ads. With Glitching, users can automate their dropshipping business and start making money online quickly and easily.

ABtesting.ai is an AI-powered A/B testing software that helps businesses optimize their landing pages for conversions. It uses GPT-3 to generate automated text suggestions for headlines, copy, and call to actions, saving businesses time and effort. The software also automatically chooses the best combinations of elements to show to users, boosting conversion rates in the process. ABtesting.ai is easy to use and requires no manual work, making it a great option for businesses of all sizes.

Keyword Catcher is a powerful SERP analysis and keyword research tool that makes it easy to gain actionable insights from Google results. With Keyword Catcher, you can quickly and easily generate hundreds of long-tail keywords, filter your results to only include the keywords that you know you can rank for, and get a comprehensive view of the SERPs to understand the dynamics of keyword rankings. Keyword Catcher also includes a number of AI-powered features, such as AI-generated post outlines, that can help you to create high-quality content that ranks well in search results.

The website appears to be displaying a '403 Forbidden' error, which typically means that the user is not authorized to access the requested page. This error is often caused by incorrect permissions on the server or a misconfiguration in the website's settings. The message 'openresty' suggests that the website may be using the OpenResty web platform, which is based on NGINX and Lua programming language. Users encountering this error should contact the website administrator for assistance in resolving the issue.

Hirebase is an AI-powered job search engine that provides ultra-fresh job market data directly from company pages. It uses AI to scan 100,000 jobs in real-time, ensuring that every job listed is actively hiring on the internet. Users can receive email alerts for new job listings based on their preferences for job title, keywords, location, experience level, date posted, salary range, and more. Hirebase aims to 'unsuckify' the job search process by leveraging AI technology to streamline and enhance the job hunting experience.

SEO Katana is an AI-powered competitor analysis tool designed to help users improve their SEO content and draw traffic from competitors. It provides powerful insights in seconds by analyzing competitor's SEO strategies, identifying top-ranking organic pages, and generating AI blog posts based on competitor content. The tool aims to simplify SEO by offering simple pricing plans and features like content analysis, competitor research, and AI content generation.

The website is a simple error page indicating that the requested page is not found. It is a standard HTTP response code that informs the user that the server could not find the requested resource. The 404 error page is a common occurrence on the web when a user tries to access a page that no longer exists or has been moved.

Sell The Trend is an all-in-one AI-powered dropshipping software that provides users with the tools they need to find winning products, connect with quality suppliers, create high-converting product pages, simplify store management, and promote and grow their store. With Sell The Trend, users can access a database of over 7.32 million products across 83 popular dropshipping niches, get detailed information on product performance, and use predictive AI technology to forecast the success of new products. Sell The Trend also offers a range of tools to help users create high-converting product pages, manage their inventory and orders, and promote their store on social media. With Sell The Trend, users can streamline their dropshipping operations and increase their chances of success.

AI Web Page Analyzer is a free and open-source tool that helps you analyze web pages for SEO. It can check content, keywords, structure, and metatags, and provide recommendations for improving your website's SEO. AI Web Page Analyzer also includes a number of other features, such as SEO optimization, keyword extraction, and content generation.

MemFree is a hybrid AI search tool that allows users to search for information instantly and receive accurate answers from the internet, bookmarks, notes, and documents. With MemFree, users can easily index their bookmarks and web pages with just one click. The tool leverages GPT-4o mini for enhanced search capabilities, making it a powerful and efficient AI application for information retrieval.

Algolia is an AI search tool that provides users with the results they need to see, category and collection pages built by AI, recommendations throughout the user journey, data-enhanced customer experiences through the Merchandising Studio, and insights in one dashboard with Analytics. It offers pre-built UI components for custom journeys and integrates with platforms like Adobe Commerce, BigCommerce, Commercetools, Salesforce CC, and Shopify. Algolia is trusted by various industries such as retail, e-commerce, B2B e-commerce, marketplaces, and media. It is known for its ease of use, speed, scalability, and ability to handle a high volume of queries.

BrowseGPT is a free Chrome extension that uses artificial intelligence to automate your browser. You can give BrowseGPT instructions like "Find a place to stay in Seattle on February 22nd" or "buy a children's book on Amazon", and it will use OpenAI's GPT-3 model to process web pages and issue commands like CLICK, ENTER_TEXT, or NAVIGATE to complete the task for you.

Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.

DaoCloud Enterprise 5.0 Documentation provides detailed information on using DaoCloud, a Certified Kubernetes Service Provider. The documentation covers current and legacy versions, workflow control using GitOps, and instructions for opening a PR and previewing changes locally. It also includes naming conventions, writing tips, references, and acknowledgments to contributors. Users can find guidelines on writing, contributing, and translating pages, along with using tools like MkDocs, Docker, and Poetry for managing the documentation.

Airports is a personal airport/subscription summary repository that provides information on various airport services, including high-end and cost-effective options. Users can find links to different airport websites and subscription services, along with recommendations for reliable and affordable airport options. The repository also includes public service pages for automatic data retrieval and Telegram channels related to airport sharing and discussions. Additionally, users can access subscription services for v2ray and clash links through the repository.

Panel Cleaner is a tool that uses machine learning to find text in images and generate masks to cover it up with high accuracy. It is designed to clean text bubbles without leaving artifacts, avoiding painting over non-text parts, and inpainting bubbles that can't be masked out. The tool offers various customization options, detailed analytics on the cleaning process, supports batch processing, and can run OCR on pages. It supports CUDA acceleration, multiple themes, and can handle bubbles on any solid grayscale background color. Panel Cleaner is aimed at saving time for cleaners by automating monotonous work and providing precise cleaning of text bubbles.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

LLM_Web_search project gives local LLMs the ability to search the web by outputting a specific command. It uses regular expressions to extract search queries from model output and then utilizes duckduckgo-search to search the web. LangChain's Contextual compression and Okapi BM25 or SPLADE are used to extract relevant parts of web pages in search results. The extracted results are appended to the model's output.

Vespa documentation is served using GitHub Project pages with Jekyll. To edit documentation, check out and work off the master branch in this repository. Documentation is written in HTML or Markdown. Use a single Jekyll template _layouts/default.html to add header, footer and layout. Install bundler, then $ bundle install $ bundle exec jekyll serve --incremental --drafts --trace to set up a local server at localhost:4000 to see the pages as they will look when served. If you get strange errors on bundle install try $ export PATH=“/usr/local/opt/[email protected]/bin:$PATH” $ export LDFLAGS=“-L/usr/local/opt/[email protected]/lib” $ export CPPFLAGS=“-I/usr/local/opt/[email protected]/include” $ export PKG_CONFIG_PATH=“/usr/local/opt/[email protected]/lib/pkgconfig” The output will highlight rendering/other problems when starting serving. Alternatively, use the docker image `jekyll/jekyll` to run the local server on Mac $ docker run -ti --rm --name doc \ --publish 4000:4000 -e JEKYLL_UID=$UID -v $(pwd):/srv/jekyll \ jekyll/jekyll jekyll serve or RHEL 8 $ podman run -it --rm --name doc -p 4000:4000 -e JEKYLL_ROOTLESS=true \ -v "$PWD":/srv/jekyll:Z docker.io/jekyll/jekyll jekyll serve The layout is written in denali.design, see _layouts/default.html for usage. Please do not add custom style sheets, as it is harder to maintain.

This repository contains the source code for the Apache Airflow website, including directories for archived documentation versions, landing pages, license templates, and the Sphinx theme. To work on the site locally, users need to install coreutils, Node.js, NPM, and HUGO, and run specific scripts provided in the repository. Contributors can refer to the contributor's guide for detailed instructions on how to contribute to the website.

The Latent Browser is a desktop application designed like a web browser, which hallucinates web search results (the resultds are fictious and are generated by a LLM) and web pages. It is a web application designed to run locally on your machine and is 99% React, Tailwind, TypeScript, and NextJS. The runtime is Tauri, which is written in Rust. The Latent Browser is still under development and some things may be broken when you try it.

WordLift is a plugin that helps online content creators organize posts and pages by adding facts, links, and media to build beautifully structured websites for both humans and search engines. It allows users to create, own, and publish their own knowledge graph, and publishes content as Linked Open Data following Tim Berners-Lee's Linked Data Principles. The plugin supports writers by providing trustworthy and contextual facts, enriching content with images, links, and interactive visualizations, keeping readers engaged with relevant content recommendations, and producing content compatible with schema.org markup for better indexing and display on search engines. It also offers features like creating a personal Wikipedia, publishing metadata to share and distribute content, and supporting content tagging for better SEO.

x-crawl is a flexible Node.js AI-assisted crawler library that offers powerful AI assistance functions to make crawler work more efficient, intelligent, and convenient. It consists of a crawler API and various functions that can work normally even without relying on AI. The AI component is currently based on a large AI model provided by OpenAI, simplifying many tedious operations. The library supports crawling dynamic pages, static pages, interface data, and file data, with features like control page operations, device fingerprinting, asynchronous sync, interval crawling, failed retry handling, rotation proxy, priority queue, crawl information control, and TypeScript support.

AutoNode is a self-operating computer system designed to automate web interactions and data extraction processes. It leverages advanced technologies like OCR (Optical Character Recognition), YOLO (You Only Look Once) models for object detection, and a custom site-graph to navigate and interact with web pages programmatically. Users can define objectives, create site-graphs, and utilize AutoNode via API to automate tasks on websites. The tool also supports training custom YOLO models for object detection and OCR for text recognition on web pages. AutoNode can be used for tasks such as extracting product details, automating web interactions, and more.

Midscene.js is an AI-powered automation SDK that allows users to control web pages, perform assertions, and extract data in JSON format using natural language. It offers features such as natural language interaction, understanding UI and providing responses in JSON, intuitive assertion based on AI understanding, compatibility with public multimodal LLMs like GPT-4o, visualization tool for easy debugging, and a brand new experience in automation development.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=