Best AI tools for< Parse Data With Regex >

Rgx.tools is an AI-powered text-to-regex generator that helps users create regular expressions quickly and easily. It is a wrapper around OpenAI's gpt-3.5-chat model, which generates clean, readable, and efficient regular expressions based on user input. Rgx.tools is designed to make the process of writing regular expressions less painful and more accessible, even for those with limited experience.

FormX.ai is an AI-powered data extraction and conversion tool that automates the process of extracting data from physical documents and converting it into digital formats. It supports a wide range of document types, including invoices, receipts, purchase orders, bank statements, contracts, HR forms, shipping orders, loyalty member applications, annual reports, business certificates, personnel licenses, and more. FormX.ai's pre-configured data extraction models and effortless API integration make it easy for businesses to integrate data extraction into their existing systems and workflows. With FormX.ai, businesses can save time and money on manual data entry and improve the accuracy and efficiency of their data processing.

JADBio is an automated machine learning (AutoML) platform designed to accelerate biomarker discovery and drug development processes. It offers a no-code solution that automates the discovery of biomarkers and interprets their role based on research needs. JADBio can parse multi-omics data, including genomics, transcriptome, metagenome, proteome, metabolome, phenotype/clinical data, and images, enabling users to efficiently discover valuable insights. The platform is purpose-built for various conditions such as cancer, immune, endocrine, metabolic system, chronic diseases, aging, infectious diseases, and mental health, offering solutions for early biomarker discovery, drug repurposing, lead identification, compound optimization, trial monitoring, and response to treatment. JADBio is trusted by partners in precision health & medicine and is continuously evolving to disrupt drug discovery times and costs at all stages.

Extracta.ai is an AI data extraction tool for documents and images that automates data extraction processes with easy integration. It allows users to define custom templates for extracting structured data without the need for training. The platform can extract data from various document types, including invoices, resumes, contracts, receipts, and more, providing accurate and efficient results. Extracta.ai ensures data security, encryption, and GDPR compliance, making it a reliable solution for businesses looking to streamline document processing.

Daxtra is an AI-powered recruitment technology tool designed to help staffing and recruiting professionals find, parse, match, and engage the best candidates quickly and efficiently. The tool offers a suite of products that seamlessly integrate with existing ATS or CRM systems, automating various recruitment processes such as candidate data loading, CV/resume formatting, information extraction, and job matching. Daxtra's solutions cater to corporates, vendors, job boards, and social media partners, providing a comprehensive set of developer components to enhance recruitment workflows.

NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Thanks to a hands-on guide introducing programming fundamentals alongside topics in computational linguistics, plus comprehensive API documentation, NLTK is suitable for linguists, engineers, students, educators, researchers, and industry users alike.

Imaginary Programming is an AI tool that allows frontend developers to leverage OpenAI's GPT engine to add human-like intelligence to their code effortlessly. By defining function prototypes in TypeScript, developers can access GPT's capabilities without the need for AI model training. The tool enables users to extract structured data, generate text, classify data based on intent or emotion, and parse unstructured language. Imaginary Programming is designed to help developers tackle new challenges and enhance their projects with AI intelligence.

Airparser is an AI-powered email and document parser tool that revolutionizes data extraction by utilizing the GPT parser engine. It allows users to automate the extraction of structured data from various sources such as emails, PDFs, documents, and handwritten texts. With features like automatic extraction, export to multiple platforms, and support for multiple languages, Airparser simplifies data extraction processes for individuals and businesses. The tool ensures data security and offers seamless integration with other applications through APIs and webhooks.

GoAudience is a custom audience platform that leverages AI to help brands find new customers based on their credit card spending history. It integrates easily with Meta and is effective across all categories. The platform offers features such as AI-powered audience creation, real-time consumer spending data, plug-and-play simplicity, enterprise precision at SMB pricing, and the ability to pause subscriptions anytime. GoAudience enables users to create top-performing custom audiences, track performance, measure ROI, and present results easily. It aims to provide targeting that is always on target by building custom audience lists from real-time consumer spending data. The platform prioritizes user privacy by securely transmitting data and deleting raw data after transmission.

Skillate is an AI Recruitment Platform that offers advanced decision-making engine to make hiring easy, fast, and transparent. It provides solutions such as AI Powered Matching Engine, Chatbot Screening, Resume Parser, Auto Interview Scheduler, and more to automate and improve the recruitment process. Skillate helps in intelligent hiring, enhancing candidate experience, utilizing people analytics, and promoting diversity and inclusion in recruitment practices.

Resume Screening AI is an AI application designed to help recruiters, hiring managers, and HR managers screen resumes in bulk efficiently and accurately. By leveraging AI algorithms, the tool automates the screening process, saving time and improving the quality of hire. It offers benefits such as time and cost savings, improved accuracy, enhanced objectivity, and a better candidate experience. The tool uses end-to-end encryption for data security and stores resume file fingerprints and parsed text for easy retrieval. With a focus on optimizing the recruitment process, Resume Screening AI is a transformative solution for businesses looking to attract and identify the most suitable candidates.

HrFlow.ai is an API-first company and the leading AI-powered HR data automation platform. The company helps +1000 customers (HR software vendors, Staffing agencies, large employers, and headhunting firms) to thrive in a high-volume and high-frequency labor market. The platform provides a complete and fully integrated suite of HR data processing products based on the analysis of hundreds of millions of career paths worldwide -- such as Parsing API, Tagging API, Embedding API, Searching API, Scoring API, and Upskilling API. It also offers a catalog of +200 connectors to build custom scenarios that can automate any business logic.

Explosion is a software company specializing in developer tools and tailored solutions for AI, Machine Learning, and Natural Language Processing (NLP). They are the makers of spaCy, one of the leading open-source libraries for advanced NLP. The company offers consulting services and builds developer tools for various AI-related tasks, such as coreference resolution, dependency parsing, image classification, named entity recognition, and more.

Eden AI is an AI tool designed to make AI easy for product builders. It allows users to orchestrate multiple AI models to fit their business needs. The platform offers a wide range of AI technologies such as Generative AI, Image Analysis, Text Analysis, Video Content Analysis, OCR/Document Parsing, and Speech Transcription. Users can access various AI APIs, build workflows, and integrate AI models seamlessly. Eden AI aims to simplify the process of building AI solutions for businesses by providing standardized APIs, easy integration, and cost-effective solutions.

AI Resume Tailor is an AI-powered application designed to help job seekers create customized resumes tailored to each job description. It offers features such as resume parsing, AI-powered resume building, PDF formatting, privacy protection, and ATS-friendly templates. The platform ensures that users can easily create professional resumes that stand out to potential employers, increasing their chances of getting hired.

TripsFlow is an intelligent itinerary management application that automates the organization of travel plans. By forwarding flight and hotel booking emails, the app parses the data to create a comprehensive itinerary from various travel platforms. TripsFlow offers dynamic flight reminders and centralizes itinerary viewing, enhancing travel efficiency and saving users time and effort.

Parsio is an AI-powered document parser that can extract structured data from PDFs, emails, and other documents. It uses natural language processing to understand the context of the document and identify the relevant data points. Parsio can be used to automate a variety of tasks, such as extracting data from invoices, receipts, and emails.

Whitetable is an AI tool that simplifies the hiring process by providing intelligent AI APIs for ultra-fast and optimal hiring. It offers features such as Resume Parsing API, Question API, Ranking API, and Evaluation API to streamline the recruitment process. Whitetable also provides a free AI-powered job search platform and an AI-powered ATS to help companies find the right candidates faster. With a focus on eliminating bias and improving efficiency, Whitetable is shaping the AI-driven future of hiring.

LightFeed is an automated news hub powered by LLM technology that allows users to track, filter, and summarize news from any public website. It offers automated daily updates that can be viewed in a browser, email, or RSS format. Users can create their own news hub with a 10-day free trial and no credit card required. LightFeed employs LLMs like GPT-3.5-turbo and Llama 3 to parse, filter, and summarize web pages into structured and readable feeds. The platform also supports customization of news feeds based on user preferences and provides options for automation and scheduling.

Pare is an AI-powered platform designed to help individuals grow and manage their personal LinkedIn brand with ease. It offers features such as content scheduling, prompt library, AI-powered content creation, and personalized branding suggestions. With simple pricing and seamless brand management, Pare aims to boost engagement effortlessly for its users.

Trex is a tool that transforms unstructured data into structured data by specifying a regex or context-free grammar. It intelligently restructures data to conform to the defined schema. It offers a Python client for installation and requires an API key obtained by signing up at automorphic.ai. The tool supports generating structured JSON objects based on user-defined schemas and prompts. Trex aims to provide significant speed improvements, structured custom CFG and regex generation, and generation from JSON schema. Future plans include auto-prompt generation for unstructured ETL and more intelligent models.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

The URL/API Source is a plugin for OBS Studio that allows users to add a media source fetching data from a URL or API endpoint and displaying it as text. It supports input and output templating, various request types, output parsing (JSON, XML/HTML, Regex, CSS selectors), live data updating, output styling, and formatting. Future features include authentication, websocket support, more parsing options, request types, and output formats. The plugin is cross-platform compatible and actively maintained by the developer. Users can support the project on GitHub.

Strict JSON is a framework designed to handle JSON outputs with complex structures, fixing issues that standard json.loads() cannot resolve. It provides functionalities for parsing LLM outputs into dictionaries, supporting various data types, type forcing, and error correction. The tool allows easy integration with OpenAI JSON Mode and offers community support through tutorials and discussions. Users can download the package via pip, set up API keys, and import functions for usage. The tool works by extracting JSON values using regex, matching output values to literals, and ensuring all JSON fields are output by LLM with optional type checking. It also supports LLM-based checks for type enforcement and error correction loops.

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

AIL framework is a modular framework to analyze potential information leaks from unstructured data sources like pastes from Pastebin or similar services or unstructured data streams. AIL framework is flexible and can be extended to support other functionalities to mine or process sensitive information (e.g. data leak prevention).

AIL framework is a modular framework to analyze potential information leaks from unstructured data sources like pastes from Pastebin or similar services or unstructured data streams. AIL framework is flexible and can be extended to support other functionalities to mine or process sensitive information (e.g. data leak prevention).

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

The vscode-pddl extension provides comprehensive support for Planning Domain Description Language (PDDL) in Visual Studio Code. It enables users to model planning domains, validate them, industrialize planning solutions, and run planners. The extension offers features like syntax highlighting, auto-completion, plan visualization, plan validation, plan happenings evaluation, search debugging, and integration with Planning.Domains. Users can create PDDL files, run planners, visualize plans, and debug search algorithms efficiently within VS Code.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

SynCode is a novel framework for the grammar-guided generation of Large Language Models (LLMs) that ensures syntactically valid output with respect to defined Context-Free Grammar (CFG) rules. It supports general-purpose programming languages like Python, Go, SQL, JSON, and more, allowing users to define custom grammars using EBNF syntax. The tool compares favorably to other constrained decoders and offers features like fast grammar-guided generation, compatibility with HuggingFace Language Models, and the ability to work with various decoding strategies.

Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

This GPT lets you build PCRE Regular Expressions (for use the RegExp constructor).

Expert in teaching Pydantic with clear, accessible explanations.

我們經常在看 REST API 參考文件，文件中呈現 Request/Response 參數通常都是用表格的形式，開發人員都要手動轉換成 JSON 結構，有點小麻煩，但透過這個 GPT 只要上傳截圖就可以自動產生 JSON 範例與 JSON Schema 結構。

Generates a full & complete Python codebase, after clarifying questions, by following a structured section pattern.

Generates concise, copy-paste code snippets quickly no unnecessary text.

Soy un experto en Google Apps Script que ayuda a los principiantes, hablo principalmente español.

A dual-expert in Pydantic V1 and V2, adept at online research for V2.

This helps parse and use NERO LARP rules data.

I parse questions and answers from images into code blocks.

A handy JSON utility agent

Takes all input into consideration and creates a JSON-appropriate response. Also useful for creating templates.

A specialist in crafting and explaining regex patterns.

Compile instructions from the web and github for bioinformatics applications. Receive line-by-line instructions and commands to get started

ユーザーから入力されたHTMLを読み取り変更に強いXPathを生成します

Experto en educación y evaluación de aprendizajes. Parte de equipo de investigación del proyecto MEICCA

This GPT is able to parse a sentence, provide an appropriate translation of the input text and be able to provide a response explaining the structure of a sentence in japanese.

Turns any software update info into structured changelogs in imperative tense.

the answers is Chinese. 主要分析英语的句子和短语。

A Latin language tutor

Expert in purses, handbags, and accessories.