Best AI tools for< Generate Tables >

MonkeeMath is an AI tool designed to scrape comments from Reddit and Stocktwits that mention stock tickers. It utilizes ChatGPT to analyze the sentiment of these comments, determining whether they are bullish or bearish on the outlook of the mentioned stocks. The data collected is then used to generate charts and tables displayed on the website. Users can create an account to view predictions and participate in a prediction mini-game to earn a spot on the MonkeeMath user leaderboard.

PlotGPT is a data analyst that is available 24/7. It can help you with a variety of tasks, including data analysis, data visualization, and report generation. PlotGPT is easy to use and can be accessed from any device with an internet connection.

Hepta AI is an AI-powered statistics tool designed for scientific research. It simplifies the process of statistical analysis by allowing users to easily input their data and receive comprehensive results, including tables, graphs, and statistical analysis. With a focus on accuracy and efficiency, Hepta AI aims to streamline the research process for scientists and researchers, providing valuable insights and data visualization. The tool offers a user-friendly interface and advanced AI algorithms to deliver precise and reliable statistical outcomes.

SheetAI is an AI tool integrated into Google Sheets that allows users to describe tasks in plain English and automate them using AI-driven functions. It simplifies copywriting, generates insights, creates lists and tables, and fills in empty spaces with AI magic. Trusted by universities, companies, and professionals, SheetAI revolutionizes the Google Sheets experience by providing a suite of powerful AI functions to enhance productivity and efficiency.

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.

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.

xPDF AI by PDFChat is a personal AI assistant designed for PDF files. It offers advanced features to analyze tables, figures, and text from PDF documents, providing users with instant answers and insights. The AI assistant uses a chat interface for effortless interaction and is capable of summarizing PDF files, retrieving relevant figures, processing tables intelligently, and performing accurate calculations. Users can also benefit from voice chat, advanced search tools, performance analytics, report generation, and document assistance. With over 10,000 users trusting the platform, PDFChat aims to revolutionize document analysis and enhance productivity.

RegexMy is an AI-powered platform that offers solutions for file translation, localization, summarization, and reporting. The platform is designed with cutting-edge technology to enhance document and data handling efficiency, accuracy, and convenience. Users can leverage AI tools to streamline various tasks and benefit from features like Files AI Assistant, Regex Playground, and XPath Playground.

Defog.ai provides fine-tuned AI models for enterprise SQL. It helps businesses speed up data analyses in SQL, Python, and R with AI assistants and agents tailored for their business - without sharing their data. Defog.ai's key features include the ability to ask questions of data in natural language, get results when needed, integrate with any SQL database or data warehouse, automatically visualize data as tables and charts, and fine-tune on your metadata to give results you can trust.

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.

Productify.ai is an AI-powered content generation tool that helps businesses create engaging and accurate product descriptions, features, benefits, SEO tags, and more. It is designed to help businesses increase their store's sales by generating high-quality marketing content quickly and easily. Productify.ai offers a range of features, including the ability to generate detailed product descriptions, short descriptions, headlines, SEO keywords, product categories, and FAB (features, attributes, and benefits) lists. It also includes tools for rewriting and summarizing text, translating text into multiple languages, and extracting data from tables and images.

Hogwarts AI empowers users to effortlessly build dashboards and unlock valuable data insights without the need for SQL or complex data analytics tools. Trained on a vast repository of queries and patterns, Hogwarts AI seamlessly transforms product data into intuitive charts and summaries. Its diverse data integration capabilities allow for effortless connection to various sources, including Postgres, Snowflake, Salesforce, Stripe, and even Excel tables. The AI Copilot feature enables users to create visually compelling charts with text in minutes, eliminating the need for SQL and DAX queries. Hogwarts AI also provides intelligent chart recommendations to facilitate deeper insights and enables the generation of shareable charts for product documentation and executive reviews.

Flowscript is a revolutionary app development platform that empowers users to build fully functional web applications using plain English. Its AI-powered engine instantly converts requirements specified in plain English into applications with robust business rules, data models, and secure workflows. With Flowscript, anyone can become a developer and streamline their workflows, getting more done in less time. It offers features like AI-powered workflows, data tables with relations, dynamic form generation, engagement and interaction tools, and secure data storage options.

CreateBookAI is an AI-powered platform that allows users to easily create personalized children's books in just minutes. Users can design and customize fully illustrated books for any occasion, with inspiring tales and life lessons. The platform offers total ownership of the generated books, including selling rights and copyright. CreateBookAI provides a user-friendly experience, enabling users to generate books quickly and effortlessly.

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.

Tableau Augmented Analytics is a class of analytics powered by artificial intelligence (AI) and machine learning (ML) that expands a human’s ability to interact with data at a contextual level. It uses AI to make analytics accessible so that more people can confidently explore and interact with data to drive meaningful decisions. From automated modeling to guided natural language queries, Tableau's augmented analytics capabilities are powerful and trusted to help organizations leverage their growing amount of data and empower a wider business audience to discover insights.

Catty.AI is an AI-driven platform that provides personalized and interactive learning experiences for children aged 2-12. It offers a wide range of captivating topics, including science, history, mathematics, and more, presented through engaging fairytales, illustrations, and narrations. Catty.AI prioritizes the well-being of children, ensuring that all content is age-appropriate, safe, and respectful of diverse cultures and beliefs.

Stories by AI is a website that offers unique tales written, illustrated, and narrated with AI. It has over 5,000 subscribers and provides a platform for users to explore AI-generated content.

AskCSV is a revolutionary AI-powered tool that empowers you to unlock valuable insights from your CSV files. Simply ask any question about your data, and AskCSV will provide you with instant, accurate answers and visualizations. Your data remains completely secure, processed directly in your browser's memory without any server uploads. With AskCSV, you can effortlessly analyze your data, identify trends, make informed decisions, and gain a deeper understanding of your business.

LitRPG Adventures Workshop is a website that provides a variety of AI-powered RPG tools and a growing library of tabletop RPG content. With over 3 dozen advanced tabletop RPG generators, members get instant access to fantasy RPG generators powered by GPT-3.5, GPT-4, and DALLE-3 from OpenAI. The website also offers a vast library of pre-generated fantasy character backstories, monsters, spells, dungeons, taverns, and much more.

This repository is a collection of papers on Tabular Large Language Models (LLMs) specialized for processing tabular data. It includes surveys, models, and applications related to table understanding tasks such as Table Question Answering, Table-to-Text, Text-to-SQL, and more. The repository categorizes the papers based on key ideas and provides insights into the advancements in using LLMs for processing diverse tables and fulfilling various tabular tasks based on natural language instructions.

Omniscient is an advanced AI Platform offered as a SaaS, empowering projects with cutting-edge artificial intelligence capabilities. Seamlessly integrating with Next.js 14, React, Typescript, and APIs like OpenAI and Replicate, it provides solutions for code generation, conversation simulation, image creation, music composition, and video generation.

VedAstro is an open-source Vedic astrology tool that provides accurate astrological predictions and data. It offers a user-friendly website, a chat API, an open API, a JavaScript SDK, a Swiss Ephemeris API, and a machine learning table generator. VedAstro is free to use and is constantly being updated with new features and improvements.

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.

TableLLM is a large language model designed for efficient tabular data manipulation tasks in real office scenarios. It can generate code solutions or direct text answers for tasks like insert, delete, update, query, merge, and chart operations on tables embedded in spreadsheets or documents. The model has been fine-tuned based on CodeLlama-7B and 13B, offering two scales: TableLLM-7B and TableLLM-13B. Evaluation results show its performance on benchmarks like WikiSQL, Spider, and self-created table operation benchmark. Users can use TableLLM for code and text generation tasks on tabular data.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

Enchanted is an open-source, Ollama-compatible app for macOS and iOS that allows users to work with privately hosted models such as Llama 2, Mistral, Vicuna, Starling, and more. It provides a user-friendly interface for interacting with these models, making it easy to generate text, translate languages, write different kinds of creative content, and more. The app is designed to be secure and private, ensuring that user data is protected. It also offers a range of features such as dark/light mode, conversation history, markdown support, voice prompts, and image attachments.

RAG Me Up is a generic framework that enables users to perform Retrieve and Generate (RAG) on their own dataset easily. It consists of a small server and UIs for communication. Best run on GPU with 16GB vRAM. Users can combine RAG with fine-tuning using LLaMa2Lang repository. The tool allows configuration for LLM, data, LLM parameters, prompt, and document splitting. Funding is sought to democratize AI and advance its applications.

PremSQL is an open-source library designed to help developers create secure, fully local Text-to-SQL solutions using small language models. It provides essential tools for building and deploying end-to-end Text-to-SQL pipelines with customizable components, ideal for secure, autonomous AI-powered data analysis. The library offers features like Local-First approach, Customizable Datasets, Robust Executors and Evaluators, Advanced Generators, Error Handling and Self-Correction, Fine-Tuning Support, and End-to-End Pipelines. Users can fine-tune models, generate SQL queries from natural language inputs, handle errors, and evaluate model performance against predefined metrics. PremSQL is extendible for customization and private data usage.

This repository is an awesome list dedicated to resources for using Large Language Models (LLMs) to generate JSON or other structured outputs. It includes terminology explanations, hosted and local models, Python libraries, blog articles, videos, Jupyter notebooks, and leaderboards related to LLMs and JSON generation. The repository covers various aspects such as function calling, JSON mode, guided generation, and tool usage with different providers and models.

Macai is a native macOS client for interacting with modern AI tools, such as ChatGPT and Ollama. It features organized chats with custom system messages, system-defined light/dark themes, backup and restore functionality, customizable context size, support for any model with a compatible API, formatted code blocks and tables, multiple chat tabs, CoreData data storage, streamed responses, and automatic chat name generation. Macai is in active development, with contributions welcome.

Groqbook is a streamlit app that quickly generates entire books from a one-line prompt using Llama3 on Groq. It focuses on nonfiction books, generating chapters within seconds by utilizing Llama3-8b and Llama3-70b models. The tool currently uses section titles to create chapter content, with plans to expand to full book context for fiction books. Users can download the book contents in a text file, and the app supports markdown styling with tables and code for an aesthetic book display.

Sailor is a suite of open language models tailored for South-East Asia (SEA), focusing on languages such as Indonesian, Thai, Vietnamese, Malay, and Lao. Developed with careful data curation, Sailor models are designed to understand and generate text across diverse linguistic landscapes of the SEA region. Built from Qwen 1.5, Sailor encompasses models of varying sizes, spanning from 0.5B to 7B versions for different requirements. Benchmarking results demonstrate Sailor's proficiency in tasks such as question answering, commonsense reasoning, reading comprehension, and more in SEA languages.

Groqnotes is a streamlit app that helps users generate organized lecture notes from transcribed audio using Groq's Whisper API. It utilizes Llama3-8b and Llama3-70b models to structure and create content quickly. The app offers markdown styling for aesthetic notes, allows downloading notes as text or PDF files, and strategically switches between models for speed and quality balance. Users can access the hosted version at groqnotes.streamlit.app or run it locally with streamlit by setting up the Groq API key and installing dependencies.

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.

Instruct NER is a solution for complex Named Entity Recognition tasks, including Nested NER, based on modern Large Language Models (LLMs). It provides tools for dataset creation, training, automatic metric calculation, inference, error analysis, and model implementation. Users can create instructions for LLM, build dictionaries with labels, and generate model input templates. The tool supports various entity types and datasets, such as RuDReC, NEREL-BIO, CoNLL-2003, and MultiCoNER II. It offers training scripts for LLMs and metric calculation functions. Instruct NER models like Llama, Mistral, T5, and RWKV are implemented, with HuggingFace models available for adaptation and merging.

A web application to explore the capabilities of Google Maps Platform Route Optimization (GMPRO) for solving vehicle routing problems. Users can interact with the GMPRO data model through forms, tables, and maps to construct scenarios, tune constraints, and visualize routes. The application is intended for exploration purposes only and should not be deployed in production. Users are responsible for billing related to cloud resources and API usage. It is important to understand the pricing models for Maps Platform and Route Optimization before using the application.

A web application to explore the capabilities of Google Maps Platform Route Optimization (GMPRO). It helps users understand the data model and functions of the API by presenting interactive forms, tables, and maps. The tool is intended for exploratory use only and should not be deployed in production. Users can construct scenarios, tune constraint parameters, and visualize routes before implementing their own solutions for integrating Route Optimization into their business processes. The application incurs charges related to cloud resources and API usage, and users should be cautious about generating high usage volumes, especially for large scenarios.

Eidos is an extensible framework for managing personal data in one place. It runs inside the browser as a PWA with offline support. It integrates AI features for translation, summarization, and data interaction. Users can customize Eidos with Prompt extension, JavaScript for Formula functions, TypeScript/JavaScript for data processing logic, and build apps using any framework. Eidos is developer-friendly with API & SDK, and uses SQLite standardization for data tables.

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.

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

Automates DCF Analysis with internet-sourced data and summary table.

Generate SQL Queries Using Your Database, Tailored for Every Skill Level!

Delivers business data in detailed tables.

A GPT pre-trained on duneSQL Farcaster tables, complex examples, and duneSQL syntax. Please reference the dune docs or contact @shoni.eth for errors

I turn citation details into formatted tables.

Cocinero experto que presenta ingredientes en tablas y genera PDFs

根据用户要求生成指定SQL语句

汇总PDF文档及其中的表格的专家

入力した文章をMarkdown形式にコードとして正しく変換してくれます。文章を入力するだけでOKです！更に、読み手が読みやすいようにレイアウトも考えてくれます！途中で止まっても「続けてください」といえば大丈夫です。

Convert application descriptions to consumable DB schemas or create-table SQL statements

Writes a fairytale according to the assignment.

输入需求内容，多个需求逐行显示，前面用1. 2. 3.开始，自动生成软件功能点评估表

I generate top 10 PLG strategies in a table format

A fairy tale generator, creating unique and imaginative stories.

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。

I create RPG scenes with rich details and offer DALL-E images, NPC descriptions, and plot ideas.

Cat tales with a colorful, stylistic flair!

Generates random fantasy names for tabletop RPG games like Dungeons and Dragons

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