Best AI tools for< Set Tables >

Craft is a versatile productivity application designed to help users organize, create, style, and share documents seamlessly. It offers a user-friendly interface for note-taking, to-do lists, document organization, and more. Craft provides powerful features such as folders and spaces for organization, tasks and reminders with push alerts, AI-powered summarization and translation, whiteboards for visual brainstorming, and support for multiple languages. Users can enjoy a native user experience on various devices, with features like drag-and-drop media, customizable backgrounds, tables, and rich formatting options. Craft also emphasizes privacy, offline mode, slash commands for quick access, and smart links for rich previews. The application aims to enhance productivity and creativity by providing a comprehensive platform for digital organization and collaboration.

Petal is a document analysis platform powered by generative AI technology. It allows users to chat with their documents, providing fully sourced and reliable answers by linking to their own knowledge bases. Users can train AI on their documents to support their work, ensuring centralized knowledge management and document synchronization. Petal offers features such as automatic metadata extraction, file deduplication, and collaboration tools to enhance productivity and streamline workflows for researchers, faculty, and industry experts.

Base64.ai is an automated document processing API that offers a leading no-code AI solution for understanding documents, photos, and videos. It provides a comprehensive set of features for document processing across various industries, with a strong focus on accuracy, security, and extensibility. Base64.ai is designed to streamline document automation processes and improve data extraction efficiency.

StudyShift is a revolutionary collaborative productivity tool specifically designed for students. It is made to make students more efficient and productive. It works everywhere, whether on a PC, tablet, or mobile device. With StudyShift, students can set their study goals and track their progress efficiently. They can also manage their assignments, create documents, collaborate with others, and manage their tasks. StudyShift also includes an AI tutor that can answer questions on any subject. It is a revolutionary suite of productivity tools and apps for learners that works everywhere, whether on a PC, tablet, or mobile device.

LearnMate is a revolutionary AI-integrated productivity app designed for students. It offers collaborative tools for study goal setting, assignment and task management, note-taking, and more. The app utilizes cutting-edge AI technology to enhance the learning experience and productivity of students. LearnMate is accessible on various devices, allowing seamless progress tracking and data synchronization across PCs, tablets, and mobile devices. With features like AI tutor assistance, assignment management, task lists, study notes creation, and more, LearnMate aims to revolutionize the way students study and excel in their academic endeavors.

Neural Concept is an end-to-end platform for high-performance engineering teams, powered by a leading proprietary 3D AI core. It accelerates product development and innovation with industry-leading 3D deep-learning and simulation capabilities. The platform works with various CAE and CAD softwares, offering 3D visual feedback, collaborative environment, and LLM guidance to boost engineers' impact. Neural Concept is used by engineering companies to design and deliver better products faster, bringing AI-designed products to market up to 75% faster.

TestFit is a real estate feasibility platform that uses AI to help developers, architects, contractors, and brokers evaluate deals and make better decisions. It provides real-time insights into design, cost, and constructability, and integrates with a variety of other software tools. TestFit can help users save time and money, and make more informed decisions about their real estate projects.

TestFit is a real estate feasibility platform that helps users maximize site potential and get the right deals done faster. It uses real-time AI for rapid iterations, allowing users to evaluate deals in hours instead of weeks. TestFit also integrates with other software, such as Revit and Enscape, to streamline the design and documentation process.

BetterLegal is a one-stop-shop for setting up a new business quickly and efficiently. With no confusing options, the platform handles all necessary filings and generates custom legal documents, making your company official in just 2 business days. It offers state formation filing, EIN (Tax ID) processing, operating agreement or bylaws creation, express processing, registered agent service, compliance service, permit & license searches, and more. BetterLegal is designed to simplify the business formation process and provide essential services for entrepreneurs and small business owners.

Fable Fiesta is an AI-powered writing assistant that helps writers and creators overcome writer's block and unleash their creativity. With its AI story generator, dynamic world and character generator, and intelligent AI plot generator, Fable Fiesta provides the tools to create compelling narratives, thrilling adventures, seductive love stories, and more. Whether you're an author, a screenwriter, or a creative enthusiast, Fable Fiesta can help you write your next bestseller.

AI Map is an innovative AI tool that provides users with smarter maps and descriptive navigation. By leveraging artificial intelligence technology, users can articulate their search criteria and receive high-quality results prioritized for human comprehension. The application aims to enhance the exploration experience by offering real-time search guides. AI Map is designed to revolutionize the way people navigate and discover new places.

MailEcho is an AI-powered email inbox filtering and cleaning service that helps users keep their inboxes free of promotional and sales emails. It uses AI to monitor your email inbox and automatically archives all promotional and sales emails. This keeps your inbox clean and ensures you never miss an important email.

GetBotz is an AI-powered content creation and blog management platform that helps businesses automate their blogging process. With GetBotz, businesses can publish 50+ SEO-optimized articles on their blog every month without any manual effort. The platform uses a combination of natural language processing, machine learning, and SEO data to generate high-quality, engaging content that is tailored to the specific needs of each business. GetBotz also offers a range of features to help businesses manage their blog, including keyword research, article scheduling, and social media integration.

Jason AI is a conversational AI assistant designed specifically for B2B sales professionals. It automates outreach sequences, handles prospect responses, and books meetings, freeing up sales reps to focus on closing deals. Jason AI uses advanced natural language processing (NLP) to understand the context of conversations and respond in a personalized and engaging way. It integrates with popular CRM and email platforms, making it easy to use and manage.

eCommerce ChatGPT Prompts Generator is a tool that helps eCommerce marketers create high-quality prompts for ChatGPT. With over 2 million pre-built prompts, users can quickly and easily generate content for all their eCommerce marketing needs, including product descriptions, social media posts, email campaigns, and more. The tool also offers a variety of customization options, so users can tailor their prompts to their specific needs.

Quick, Draw! is a game built with machine learning. You draw, and a neural network tries to guess what you're drawing. Of course, it doesn't always work. But the more you play with it, the more it will learn. So far we have trained it on a few hundred concepts, and we hope to add more over time. We made this as an example of how you can use machine learning in fun ways.

Codlixe is an AI-powered application designed to help users balance their life goals and journal effectively. With the assistance of AI, users can set goals that bring balance to various areas of their lives and receive journaling prompts to kickstart their writing journey. The application tracks and categorizes goals, provides suggestions for goal setting based on progress analysis, and offers journaling prompts to inspire users. Codlixe aims to be a growth companion for users, guiding them towards a more balanced and fulfilling life.

This website provides a comprehensive suite of free marketing tools that can be utilized to enhance your website, blog, or online business. The toolset encompasses SEO tools, AI tools, keyword research, image optimization, face generation, social media and advertising tools, and more. By leveraging these tools, you can analyze your web pages, elevate your SEO score, and bolster your marketing initiatives.

Socra is an AI-powered platform designed to assist individuals in achieving their goals. It provides personalized guidance, helps users plan and track their progress, and offers tools to build habits and break bad ones. Socra's AI capabilities include natural language processing, machine learning, and computer vision, enabling it to understand users' goals, provide tailored recommendations, and generate insights to help them stay on track.

HowsThisGoing is an AI-powered application designed to streamline team communication and productivity by enabling users to set up standups in Slack within seconds. The platform offers features such as automatic standups, AI summaries, custom tests, analytics & reporting, and workflow scheduling. Users can easily create workflows, generate AI reports, and track team performance efficiently. HowsThisGoing provides unlimited benefits at a flat price, making it a cost-effective solution for teams of all sizes.

React Native binding of llama.cpp, which is an inference of LLaMA model in pure C/C++. This tool allows you to use the LLaMA model in your React Native applications for various tasks such as text completion, tokenization, detokenization, and embedding. It provides a convenient interface to interact with the LLaMA model and supports features like grammar sampling and mocking for testing purposes.

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

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.

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.

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.

Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

rLLM (relationLLM) is a Pytorch library for Relational Table Learning (RTL) with LLMs. It breaks down state-of-the-art GNNs, LLMs, and TNNs as standardized modules and facilitates novel model building in a 'combine, align, and co-train' way using these modules. The library is LLM-friendly, processes various graphs as multiple tables linked by foreign keys, introduces new relational table datasets, and is supported by students and teachers from Shanghai Jiao Tong University and Tsinghua University.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

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.

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.

Dwata is a desktop application that allows users to chat with any AI model and gain insights from their data. Chats are organized into threads, similar to Discord, with each thread connecting to a different AI model. Dwata can connect to databases, APIs (such as Stripe), or CSV files and send structured data as prompts when needed. The AI's response will often include SQL or Python code, which can be used to extract the desired insights. Dwata can validate AI-generated SQL to ensure that the tables and columns referenced are correct and can execute queries against the database from within the application. Python code (typically using Pandas) can also be executed from within Dwata, although this feature is still in development. Dwata supports a range of AI models, including OpenAI's GPT-4, GPT-4 Turbo, and GPT-3.5 Turbo; Groq's LLaMA2-70b and Mixtral-8x7b; Phind's Phind-34B and Phind-70B; Anthropic's Claude; and Ollama's Llama 2, Mistral, and Phi-2 Gemma. Dwata can compare chats from different models, allowing users to see the responses of multiple models to the same prompts. Dwata can connect to various data sources, including databases (PostgreSQL, MySQL, MongoDB), SaaS products (Stripe, Shopify), CSV files/folders, and email (IMAP). The desktop application does not collect any private or business data without the user's explicit consent.

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.

Sycamore is a conversational search and analytics platform for complex unstructured data, such as documents, presentations, transcripts, embedded tables, and internal knowledge repositories. It retrieves and synthesizes high-quality answers through bringing AI to data preparation, indexing, and retrieval. Sycamore makes it easy to prepare unstructured data for search and analytics, providing a toolkit for data cleaning, information extraction, enrichment, summarization, and generation of vector embeddings that encapsulate the semantics of data. Sycamore uses your choice of generative AI models to make these operations simple and effective, and it enables quick experimentation and iteration. Additionally, Sycamore uses OpenSearch for indexing, enabling hybrid (vector + keyword) search, retrieval-augmented generation (RAG) pipelining, filtering, analytical functions, conversational memory, and other features to improve information retrieval.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

Arno's Iptables Firewall (AIF) is a single- & multi-homed firewall script with DSL/ADSL support. It is a free software distributed under the GNU GPL License. The script provides a comprehensive set of configuration files and plugins for setting up and managing firewall rules, including support for NAT, load balancing, and multirouting. It offers detailed instructions for installation and configuration, emphasizing security best practices and caution when modifying settings. The script is designed to protect against hostile attacks by blocking all incoming traffic by default and allowing users to configure specific rules for open ports and network interfaces.

Wandbot is a question-answering bot designed for Weights & Biases documentation. It employs Retrieval Augmented Generation with a ChromaDB backend for efficient responses. The bot features periodic data ingestion, integration with Discord and Slack, and performance monitoring through logging. It has a fallback mechanism for model selection and is evaluated based on retrieval accuracy and model-generated responses. The implementation includes creating document embeddings, constructing the Q&A RAGPipeline, model selection, deployment on FastAPI, Discord, and Slack, logging and analysis with Weights & Biases Tables, and performance evaluation.

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.

LangGraph Expense tracker is a small project that explores the possibilities of LangGraph. It allows users to send pictures of invoices, which are then structured and categorized into expenses and stored in a database. The project includes functionalities for invoice extraction, database setup, and API configuration. It consists of various modules for categorizing expenses, creating database tables, and running the API. The database schema includes tables for categories, payment methods, and expenses, each with specific columns to track transaction details. The API documentation is available for reference, and the project utilizes LangChain for processing expense data.

A culinary guide for dinner recipes, etiquette, and experiences.

Guides in creating a Work Contribution Record Table.

Dream your own LEGO set.

Playful and informative guide on swing sets for outdoor play.

This GPT will help you set and visualize an intention for a spiritual ceremony

Complete set of the 4 (four) volumes of the monumental work by OTTO MARIA CARPEAUX for consultation and study. Inquire in any language.

I create a set of icons for you. @JacquesGariepy

Prepares an exhaustive set of Q/A pairs that can be imported as Anki Flash Cards. Just upload your document and put the number of flashcards you want. No pleasantries required.

I will create a quality data set for a personality AI, just dive into each module by saying the name of it and do so for all the modules. If you find it useful, share it to your friends

Given a set of Parameters, Provides a set of Order Recommendations

Analyzes companies with a stringent set of investment criteria

Immerse yourself in this 16 bit text-based adventure game set in a unique sci-fi universe.

From a song you like generate a new set of Lyrics totally original

Ready, Set, Write (v.1.1.0)

Brainstormer takes in a notion, applies a bunch of perspective agents set to improve it by seeking novelty, and spits out a bunch of improved creative ideas.

Upload an avatar and indicate the costume concept to design the movie character costume concept and set different angles for reference.

Psychology data analysis expert that guides users through structured, step-by-step exploration of a CSV data set. The analysis is based on research questions.

Madness or diesel fumes. You decide. Let me entertain you with this interactive horror game set in the Cthulhu mythos, lovingly illustrated in the style of gritty, cinematic dieselpunk.

Descend into madness, one photograph at a time. Let me entertain you with this interactive horror game set in the Cthulhu mythos, lovingly illustrated in the style of nostalgic Polaroid photos.

Riding waves of madness in the shadows of paradise. Let me entertain you with this interactive horror game set in the Cthulhu mythos, lovingly illustrated in the style of sunkissed surfer postcards.