Best AI tools for< Parse Pdf Files >

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.

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.

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.

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.

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.

Robo Rat is an AI-powered tool designed for business document digitization. It offers a smart and affordable resume parsing API that supports over 50 languages, enabling quick conversion of resumes into actionable data. The tool aims to simplify the hiring process by providing speed and accuracy in parsing resumes. With advanced AI capabilities, Robo Rat delivers highly accurate and intelligent resume parsing solutions, making it a valuable asset for businesses of all sizes.

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.

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.

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.

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.

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 insights for various conditions such as cancer, immune system disorders, chronic diseases, infectious diseases, and mental health.

FileGPT is a powerful GPT-AI application designed to enhance your workflow by providing quick and accurate responses to your queries across various file formats. It allows users to interact with different types of files, extract text from handwritten documents, and analyze audio and video content. With FileGPT, users can say goodbye to endless scrolling and searching, and hello to a smarter, more intuitive way of working with their documents.

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.

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.

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.

Behnevis is a Persian (Farsi) keyboard, editor, and speech-to-text tool. It allows users to convert Persian written in English letters (Pinglish or Finglish) to the Persian language script. Users can also convert Persian speech to text using the tool. Behnevis offers a paid premium plan with additional features, but the legacy two-part interface is still available for free without limitations.

The AI Resume Screening & CV Scanning platform is a cutting-edge tool designed to streamline the recruitment process by automating the initial screening of resumes and matching candidates with job requirements. By leveraging artificial intelligence algorithms, the platform efficiently analyzes resumes, identifies key qualifications, and matches candidates with suitable job openings. This innovative solution helps recruiters save time, improve efficiency, and enhance the overall hiring process.

RSS to Tweet is an AI-powered tool that helps you automate your Twitter marketing by generating unique, ready-to-post tweets from your RSS feeds. It uses ChatGPT to create engaging and informative tweets that will help you reach a wider audience and grow your Twitter following.

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.

AIP Community Registry is a collection of community-built applications and projects leveraging Palantir's AIP Platform. It showcases real-world implementations from developers using AIP in production. The registry features various solutions demonstrating practical implementations and integration patterns across different use cases.

Open Parse is a Python library for visually discerning document layouts and chunking them effectively. It is designed to fill the gap in open-source libraries for handling complex documents. Unlike text splitting, which converts a file to raw text and slices it up, Open Parse visually analyzes documents for superior LLM input. It also supports basic markdown for parsing headings, bold, and italics, and has high-precision table support, extracting tables into clean Markdown formats with accuracy that surpasses traditional tools. Open Parse is extensible, allowing users to easily implement their own post-processing steps. It is also intuitive, with great editor support and completion everywhere, making it easy to use and learn.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.

The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of `unstructured` revolve around streamlining and optimizing the data processing workflow for LLMs. `unstructured` modular functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

PDFMathTranslate is a tool designed for translating scientific papers and conducting bilingual comparisons. It preserves formulas, charts, table of contents, and annotations. The tool supports multiple languages and diverse translation services. It provides a command-line tool, interactive user interface, and Docker deployment. Users can try the application through online demos. The tool offers various installation methods including command-line, portable, graphic user interface, and Docker. Advanced options allow users to customize translation settings. Additionally, the tool supports secondary development through APIs for Python and HTTP. Future plans include parsing layout with DocLayNet based models, fixing page rotation and format issues, supporting non-PDF/A files, and integrating plugins for Zotero and Obsidian.

Indexify is an open-source engine for building fast data pipelines for unstructured data (video, audio, images, and documents) using reusable extractors for embedding, transformation, and feature extraction. LLM Applications can query transformed content friendly to LLMs by semantic search and SQL queries. Indexify keeps vector databases and structured databases (PostgreSQL) updated by automatically invoking the pipelines as new data is ingested into the system from external data sources. **Why use Indexify** * Makes Unstructured Data **Queryable** with **SQL** and **Semantic Search** * **Real-Time** Extraction Engine to keep indexes **automatically** updated as new data is ingested. * Create **Extraction Graph** to describe **data transformation** and extraction of **embedding** and **structured extraction**. * **Incremental Extraction** and **Selective Deletion** when content is deleted or updated. * **Extractor SDK** allows adding new extraction capabilities, and many readily available extractors for **PDF**, **Image**, and **Video** indexing and extraction. * Works with **any LLM Framework** including **Langchain**, **DSPy**, etc. * Runs on your laptop during **prototyping** and also scales to **1000s of machines** on the cloud. * Works with many **Blob Stores**, **Vector Stores**, and **Structured Databases** * We have even **Open Sourced Automation** to deploy to Kubernetes in production.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

Cortex is a tool that simplifies and accelerates the process of creating applications utilizing modern AI models like chatGPT and GPT-4. It provides a structured interface (GraphQL or REST) to a prompt execution environment, enabling complex augmented prompting and abstracting away model connection complexities like input chunking, rate limiting, output formatting, caching, and error handling. Cortex offers a solution to challenges faced when using AI models, providing a simple package for interacting with NL AI models.

MegaParse is a powerful and versatile parser designed to handle various types of documents such as text, PDFs, Powerpoint presentations, and Word documents with no information loss. It is fast, efficient, and open source, supporting a wide range of file formats. MegaParse ensures compatibility with tables, table of contents, headers, footers, and images, making it a comprehensive solution for document parsing.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

ShortcutsBench is a project focused on collecting and analyzing workflows created in the Shortcuts app, providing a dataset of shortcut metadata, source files, and API information. It aims to study the integration of large language models with Apple devices, particularly focusing on the role of shortcuts in enhancing user experience. The project offers insights for Shortcuts users, enthusiasts, and researchers to explore, customize workflows, and study automated workflows, low-code programming, and API-based agents.

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.

A simple and convenient interface for using various neural network models. Users can interact with LLM using text, voice, and image input to generate images, videos, 3D objects, music, and audio. The tool supports a wide range of models for different tasks such as image generation, video generation, audio file separation, voice conversion, and more. Users can also view files from the outputs directory in a gallery, download models, change application settings, and check system sensors. The goal of the project is to create an easy-to-use application for utilizing neural network models.

Use the OpenAI API with Ruby! 🤖🩵 Stream text with GPT-4, transcribe and translate audio with Whisper, or create images with DALL·E... Hire me | 🎮 Ruby AI Builders Discord | 🐦 Twitter | 🧠 Anthropic Gem | 🚂 Midjourney Gem ## Table of Contents * Ruby OpenAI * Table of Contents * Installation * Bundler * Gem install * Usage * Quickstart * With Config * Custom timeout or base URI * Extra Headers per Client * Logging * Errors * Faraday middleware * Azure * Ollama * Counting Tokens * Models * Examples * Chat * Streaming Chat * Vision * JSON Mode * Functions * Edits * Embeddings * Batches * Files * Finetunes * Assistants * Threads and Messages * Runs * Runs involving function tools * Image Generation * DALL·E 2 * DALL·E 3 * Image Edit * Image Variations * Moderations * Whisper * Translate * Transcribe * Speech * Errors * Development * Release * Contributing * License * Code of Conduct

ScreenAgent is a project focused on creating an environment for Visual Language Model agents (VLM Agent) to interact with real computer screens. The project includes designing an automatic control process for agents to interact with the environment and complete multi-step tasks. It also involves building the ScreenAgent dataset, which collects screenshots and action sequences for various daily computer tasks. The project provides a controller client code, configuration files, and model training code to enable users to control a desktop with a large model.

I parse questions and answers from images into code blocks.

This helps parse and use NERO LARP rules data.

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.

A handy JSON utility agent

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。

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

Expert in teaching Pydantic with clear, accessible explanations.

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

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。

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

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

A Latin language tutor

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

A specialist in crafting and explaining regex patterns.

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

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

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

Expert in purses, handbags, and accessories.

Je te parle des pervers narcissique. Je t'informe de leurs traits et de leur comportement. Je t'aide à reconnaitre les signes d'une relation toxique.