Best AI tools for< Parse Files >

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.

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.

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.

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.

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.

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

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.

AIaW is a next-generation LLM client with full functionality, lightweight, and extensible. It supports various basic functions such as streaming transfer, image uploading, and latex formulas. The tool is cross-platform with a responsive interface design. It supports multiple service providers like OpenAI, Anthropic, and Google. Users can modify questions, regenerate in a forked manner, and visualize conversations in a tree structure. Additionally, it offers features like file parsing, video parsing, plugin system, assistant market, local storage with real-time cloud sync, and customizable interface themes. Users can create multiple workspaces, use dynamic prompt word variables, extend plugins, and benefit from detailed design elements like real-time content preview, optimized code pasting, and support for various file types.

model.nvim is a tool designed for Neovim users who want to utilize AI models for completions or chat within their text editor. It allows users to build prompts programmatically with Lua, customize prompts, experiment with multiple providers, and use both hosted and local models. The tool supports features like provider agnosticism, programmatic prompts in Lua, async and multistep prompts, streaming completions, and chat functionality in 'mchat' filetype buffer. Users can customize prompts, manage responses, and context, and utilize various providers like OpenAI ChatGPT, Google PaLM, llama.cpp, ollama, and more. The tool also supports treesitter highlights and folds for chat buffers.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

Chat Nio is a next-generation AIGC one-stop business solution that combines the advantages of frontend-oriented lightweight deployment projects with powerful API distribution systems. It offers rich model support, beautiful UI design, complete Markdown support, multi-theme support, internationalization support, text-to-image support, powerful conversation sync, model market & preset system, rich file parsing, full model internet search, Progressive Web App (PWA) support, comprehensive backend management, multiple billing methods, innovative model caching, and additional features. The project aims to address limitations in conversation synchronization, billing, file parsing, conversation URL sharing, channel management, and API call support found in existing AIGC commercial sites, while also providing a user-friendly interface design and C-end features.

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) ::=