Best AI tools for< Format Tables >

MD Editor is an AI-powered markdown editor designed for tech writers to supercharge their writing workflows. It offers intelligent suggestions, formatting assistance, and code highlighting to streamline the writing process. With features like AI Brainstorm Ideas, Generate code & images, Rewrite text & Explain Code, and more, MD Editor aims to enhance productivity and improve the quality of technical writing. Users can manage articles, drafts, and ideas in one place, customize their writing experience, and sync articles across devices. The platform also supports exporting articles to various formats and publishing to multiple platforms.

Tablesmith is a free, privacy-first, and intuitive spreadsheet automation tool that allows users to build reusable data flows, effortlessly sort, filter, group, format, or split data across files/sheets based on cell values. It is designed to be easy to learn and use, with a focus on privacy and cross-platform compatibility. Tablesmith also offers an AI autofill feature that suggests and fills in information based on the user's prompt.

SQLPilot is an AI-first SQL editor that leverages artificial intelligence to help users quickly generate complex SQL queries. The tool supports multiple GPT models, offers SQL autocomplete, ensures privacy and security by not storing user data, and allows users to download query results in CSV format. With SQLPilot, users can write prompts in natural language, mention required tables, and let the AI model generate the query with all the necessary context. Testimonials from users highlight the tool's efficiency, accuracy, and time-saving capabilities in database management.

Wonder Tales Blog is a website that allows users to create personalized fairy tales for children. The website features a variety of templates and illustrations that can be used to create unique stories. The stories can be read in audio format or downloaded as PDFs. Wonder Tales Blog also offers a variety of resources for parents and educators, including tips on how to use fairy tales to teach children valuable life lessons.

Fabularis is an AI-powered platform that creates personalized children's books tailored to each child's unique characteristics. By inputting basic details, the system crafts a narrative that resonates personally with the child, sparking joy, wonder, and belief in their potential. The platform offers a range of AI-crafted children's book examples, allowing users to choose the values they wish to emphasize and edit the stories to give them a personal touch. Users can enjoy their unique storybook in PDF format or opt to purchase a physical version. Fabularis stands out for its total personalization, premium illustrations, and educational value, making reading a captivating and personal journey for young readers.

RTutor is an AI tool that leverages OpenAI's powerful large language models to translate natural language into R or Python code for data analysis. Users can upload data files in various formats and request analysis in plain English, receiving results in minutes. The tool is designed for traditional statistics data analysis, where rows represent observations and columns represent variables. RTutor offers a user-friendly interface for exploring data, generating basic plots, and refining analysis through natural language prompts.

AI Subtraction Learning Helper is an AI tool designed to assist students in learning subtraction through printable subtraction tables, charts, and worksheets. The application provides free resources in various formats, including PDF and JPG, to enhance math learning for children from Kindergarten to 4th Grade. It offers colored subtraction charts, number decomposition solutions, and subtraction games to make learning engaging and effective. Parents and teachers can use the tool to customize practice sessions and track students' progress in mastering fundamental subtraction concepts.

Tablepad is an AI-powered data analytics tool that allows users to upload, view, and query data effortlessly. With Tablepad, users can generate insights and create charts without the need for coding skills. The tool supports various file formats and offers automated visual insights by generating graphs and charts based on plain English questions. Tablepad simplifies data exploration and visualization, making it easy for users to uncover valuable insights from their data.

Format Magic is a one-click formatting platform powered by AI that transforms plain text into beautifully formatted documents within seconds. Users can select a template, paste their text, and let the AI automatically apply headings and styles to create professional resumes or documents effortlessly. The platform offers easy-to-use tools for quick and efficient formatting, making it a valuable resource for individuals looking to enhance the visual appeal of their written content.

Resumy is an AI-powered resume builder that uses OpenAI's GPT-4 natural language processing model to generate polished and effective resumes. It analyzes a user's work experience, skills, and achievements to create a professional-looking resume in minutes. Resumy also offers proven templates and personalized help from resume writing experts.

Letterfy is an AI-powered cover letter generator that helps job seekers create high-quality cover letters quickly and easily. With Letterfy, you can generate a professional cover letter in minutes, tailored to the specific job you're applying for. Letterfy's AI technology analyzes your resume and LinkedIn profile to identify your skills and experience, and then generates a cover letter that highlights your most relevant qualifications. You can also customize your cover letter with your own personal touch, and download it in PDF format.

Editby is an AI-powered content creation tool that helps users create SEO-optimized content that ranks on Google and social media. It offers a range of features to help users create high-quality content, including AI-powered recommendations, trending content suggestions, and plagiarism detection. Editby also integrates with a variety of platforms, making it easy to publish content anywhere you need it.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Socialite AI is an AI tool that allows users to convert any content into a different format. It offers a simple and efficient way to transform text, images, or other media types with ease. The tool is designed to streamline the process of content conversion, making it accessible to users with varying technical skills. Socialite AI aims to enhance productivity and creativity by providing a versatile platform for content transformation.

PDFMerse is an AI-powered data extraction tool that revolutionizes how users handle document data. It allows users to effortlessly extract information from PDFs with precision, saving time and enhancing workflow. With cutting-edge AI technology, PDFMerse automates data extraction, ensures data accuracy, and offers versatile output formats like CSV, JSON, and Excel. The tool is designed to dramatically reduce processing time and operational costs, enabling users to focus on higher-value tasks.

LogoliveryAI is a free AI-powered logo generator that allows users to create logos in SVG format. The platform is easy to use and provides users with a variety of customization options. LogoliveryAI is perfect for entrepreneurs, small businesses, and anyone else who needs a professional-looking logo.

Watto AI is a platform that offers Conversational AI solutions to businesses, allowing them to build AI voice agents without the need for coding. The platform enables users to collect leads, automate customer support, and facilitate natural interactions through AI voice bots. Watto AI caters to various industries and scenarios, providing human-like conversational AI for mystery shopping, top-quality customer support, and restaurant assistance.

Mp3Converter AI is an online audio converter tool powered by AI technology. It allows users to convert various audio formats such as WAV, FLAC, and AAC to MP3 effortlessly. The tool provides high-quality audio conversions quickly and efficiently, making it a versatile solution for all audio conversion needs. With a user-friendly interface and batch conversion feature, Mp3Converter AI ensures a seamless experience for converting music files to MP3 format.

ListenMonster is a free video caption generator tool that provides unmatched speech-to-text accuracy. It allows users to generate automatic subtitles in English and other languages, export transcription files, remove background noise, and customize video captions. ListenMonster supports multiple export options, pre-made templates, and smart editing features. The tool is cost-effective, offers instant results, and can generate subtitles in 99 languages. It also features automatic language detection, a smart subtitle editor, and flexible export options.

Humanize AI is a free AI humanizer tool that helps users bypass AI detection by transforming text into authentic and original content undetectable by most detectors. It offers fast and easy humanization process, high-quality rewriting, and original outputs. The tool is designed to boost content creation productivity and ensure readability, free from grammatical errors. Humanize AI is a trustworthy solution for content creators looking to create unique and plagiarism-free content.

Unity Catalog is an open and interoperable catalog for data and AI, supporting multi-format tables, unstructured data, and AI assets. It offers plugin support for extensibility and interoperates with Delta Sharing protocol. The catalog is fully open with OpenAPI spec and OSS implementation, providing unified governance for data and AI with asset-level access control enforced through REST APIs.

AIO Launcher Scripts is a collection of Lua scripts that can be used with AIO Launcher to enhance its functionality. These scripts can be used to create widget scripts, search scripts, and side menu scripts. They provide various functions such as displaying text, buttons, progress bars, charts, and interacting with app widgets. The scripts can be used to customize the appearance and behavior of the launcher, add new features, and interact with external services.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

T-MAC is a kernel library that directly supports mixed-precision matrix multiplication without the need for dequantization by utilizing lookup tables. It aims to boost low-bit LLM inference on CPUs by offering support for various low-bit models. T-MAC achieves significant speedup compared to SOTA CPU low-bit framework (llama.cpp) and can even perform well on lower-end devices like Raspberry Pi 5. The tool demonstrates superior performance over existing low-bit GEMM kernels on CPU, reduces power consumption, and provides energy savings. It achieves comparable performance to CUDA GPU on certain tasks while delivering considerable power and energy savings. T-MAC's method involves using lookup tables to support mpGEMM and employs key techniques like precomputing partial sums, shift and accumulate operations, and utilizing tbl/pshuf instructions for fast table lookup.

Chat Nio is a next-generation AI one-stop solution that provides a rich and user-friendly interface for interacting with various AI models. It offers features such as AI chat conversation, rich format compatibility, markdown support, message menu support, multi-platform adaptation, dialogue memory, full-model file parsing, full-model DuckDuckGo online search, full-screen large text editing, model marketplace, preset support, site announcements, preference settings, internationalization support, and a rich admin system. Chat Nio also boasts a powerful channel management system that utilizes a self-developed channel distribution algorithm, supports multi-channel management, is compatible with multiple formats, allows for custom models, supports channel retries, enables balanced load within the same channel, and provides channel model mapping and user grouping. Additionally, Chat Nio offers forwarding API services that are compatible with multiple formats in the OpenAI universal format and support multiple model compatible layers. It also provides a custom build and install option for highly customizable deployments. Chat Nio is an open-source project licensed under the Apache License 2.0 and welcomes contributions from the community.

GenAIScript is a scripting environment designed to facilitate file ingestion, prompt development, and structured data extraction. Users can define metadata and model configurations, specify data sources, and define tasks to extract specific information. The tool provides a convenient way to analyze files and extract desired content in a structured format. It offers a user-friendly interface for working with data and automating data extraction processes, making it suitable for various data processing tasks.

Bee is an easy and high efficiency ORM framework that simplifies database operations by providing a simple interface and eliminating the need to write separate DAO code. It supports various features such as automatic filtering of properties, partial field queries, native statement pagination, JSON format results, sharding, multiple database support, and more. Bee also offers powerful functionalities like dynamic query conditions, transactions, complex queries, MongoDB ORM, cache management, and additional tools for generating distributed primary keys, reading Excel files, and more. The newest versions introduce enhancements like placeholder precompilation, default date sharding, ElasticSearch ORM support, and improved query capabilities.

FLUTE (Flexible Lookup Table Engine for LUT-quantized LLMs) is a tool designed for uniform quantization and lookup table quantization of weights in lower-precision intervals. It offers flexibility in mapping intervals to arbitrary values through a lookup table. FLUTE supports various quantization formats such as int4, int3, int2, fp4, fp3, fp2, nf4, nf3, nf2, and even custom tables. The tool also introduces new quantization algorithms like Learned Normal Float (NFL) for improved performance and calibration data learning. FLUTE provides benchmarks, model zoo, and integration with frameworks like vLLM and HuggingFace for easy deployment and usage.

Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

Bee is an ORM framework that provides easy and high-efficiency database operations, allowing developers to focus on business logic development. It supports various databases and features like automatic filtering, partial field queries, pagination, and JSON format results. Bee also offers advanced functionalities like sharding, transactions, complex queries, and MongoDB ORM. The tool is designed for rapid application development in Java, offering faster development for Java Web and Spring Cloud microservices. The Enterprise Edition provides additional features like financial computing support, automatic value insertion, desensitization, dictionary value conversion, multi-tenancy, and more.

**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.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

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.

QANTA is a system and dataset for question answering tasks. It provides a script to download datasets, preprocesses questions, and matches them with Wikipedia pages. The system includes various datasets, training, dev, and test data in JSON and SQLite formats. Dependencies include Python 3.6, `click`, and NLTK models. Elastic Search 5.6 is needed for the Guesser component. Configuration is managed through environment variables and YAML files. QANTA supports multiple guesser implementations that can be enabled/disabled. Running QANTA involves using `cli.py` and Luigi pipelines. The system accesses raw Wikipedia dumps for data processing. The QANTA ID numbering scheme categorizes datasets based on events and competitions.

LLM-RGB is a repository containing a collection of detailed test cases designed to evaluate the reasoning and generation capabilities of Language Learning Models (LLMs) in complex scenarios. The benchmark assesses LLMs' performance in understanding context, complying with instructions, and handling challenges like long context lengths, multi-step reasoning, and specific response formats. Each test case evaluates an LLM's output based on context length difficulty, reasoning depth difficulty, and instruction compliance difficulty, with a final score calculated for each test case. The repository provides a score table, evaluation details, and quick start guide for running evaluations using promptfoo testing tools.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

The Pipe is a multimodal-first tool for feeding files and web pages into vision-language models such as GPT-4V. It is best for LLM and RAG applications that require a deep understanding of tricky data sources. The Pipe is available as a hosted API at thepi.pe, or it can be set up locally.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

The ultimate VBA mentor for office automation and learning.

Text-based Excel assistant, provides table results as text only

Scientific English-Chinese translator with markdown table output.

Your article formatting expert with Word download link feature.

I turn citation details into formatted tables.

Portuguese OCR for medical test coding, outputs in table format.

I have a sheetload of skills! Expert in Excel and VBA coding!

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A helpful LaTeX assistant offering guidance and practical examples.

Friendly Markdown text conversion.

Assists with PDF and template formatting for a professional look.

I generate top 10 PLG strategies in a table format

I find classical music career opportunities in table format.

Updates on CVEs from GitHub repo in table format.

Gathers and presents info on global wars in a table format with donation options.

Creates casual-toned video ideas and shot lists in table format.

Write what you'd like researched. Get information in a table format.

LaTeX paper writing assistant and PDF formatter

Overleaf GPT is an interactive assistant for writing detailed Overleaf documents. Overleaf GPT writes complete LaTeX reports, tailored to the user’s requirements. This GPT starts with conceptualizing the structure to iteratively developing the content and providing best-practice formatting in LaTeX.

Premium quality file conversion service, versatile and precise.