Best AI tools for< Set Constraints >

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 comprehensive online platform that simplifies the process of setting up a new business by handling all necessary filings and generating custom legal documents. With a focus on efficiency and user-friendliness, BetterLegal ensures that your company becomes official in just 2 business days. The platform offers a one-stop-shop solution for entrepreneurs, providing essential services such as state formation filing, EIN processing, operating agreements, and more. By streamlining the business setup process, BetterLegal aims to empower entrepreneurs to start and grow their companies with ease.

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 offers smarter maps with descriptive navigation. Users can set out on a smarter exploration voyage by articulating their search criteria and witnessing AI map seamlessly assembling high-quality results prioritized for human comprehension. The application provides real-time search guides to enhance the user experience.

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.

Refinder is an AI-powered universal search and assistant designed for work. It helps users connect, search, and utilize their company's data efficiently. With Refinder, users can easily search across all their organization's apps and data, get trustworthy answers, and streamline integrations without the need for maintenance. The tool aims to address the challenges of information overload, data fragmentation, and low productivity faced by modern businesses.

Lingvanex is a cloud-based machine translation and speech recognition platform that provides businesses with a variety of tools to translate text, documents, and speech in over 100 languages. The platform is powered by artificial intelligence (AI) and machine learning (ML) technologies, which enable it to deliver high-quality translations that are both accurate and fluent. Lingvanex also offers a variety of features that make it easy for businesses to integrate translation and speech recognition into their workflows, including APIs, SDKs, and plugins for popular programming languages and platforms.

AutoPod is a suite of plug-ins for Adobe Premiere Pro that automates many of the time-consuming tasks involved in editing video podcasts and shows. With AutoPod, you can save hours of editing time each week, and get a finished edit that is ready to be published.

Coginiti is a collaborative analytics platform and tools designed for SQL developers, data scientists, engineers, and analysts. It offers capabilities such as AI assistant, data mesh, database & object store support, powerful query & analysis, and share & reuse curated assets. Coginiti empowers teams and organizations to manage collaborative practices, data efficiency, and deliver trusted data products faster. The platform integrates modular analytic development, collaborative versioned teamwork, and a data quality framework to enhance productivity and ensure data reliability. Coginiti also provides an AI-enabled virtual analytics advisor to boost team efficiency and empower data heroes.

AI Elections Accord is a tech accord aimed at combating the deceptive use of AI in the 2024 elections. It sets expectations for managing risks related to deceptive AI election content on large-scale platforms. The accord focuses on prevention, provenance, detection, responsive protection, evaluation, public awareness, and resilience to safeguard the democratic process. It emphasizes collective efforts, education, and the development of defensive tools to protect public debate and build societal resilience against deceptive AI content.

Fairlearn is a Python package designed to help developers assess and mitigate fairness issues in artificial intelligence (AI) systems. It provides mitigation algorithms and metrics for model assessment. Fairlearn focuses on two types of harms: allocation harms and quality-of-service harms. The package follows the group fairness approach, aiming to identify groups at risk of experiencing harms and ensuring comparable behavior across these groups. Fairlearn consists of metrics for assessing model impacts and algorithms for mitigating unfairness in various AI tasks under different fairness definitions.

ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

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

AI Verify is an AI governance testing framework and software toolkit that validates the performance of AI systems against a set of internationally recognised principles through standardised tests. AI Verify is consistent with international AI governance frameworks such as those from European Union, OECD and Singapore. It is a single integrated toolkit that operates within an enterprise environment. It can perform technical tests on common supervised learning classification and regression models for most tabular and image datasets. It however does not define AI ethical standards and does not guarantee that any AI system tested will be free from risks or biases or is completely safe.

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.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

Pearl is a production-ready Reinforcement Learning AI agent library open-sourced by the Applied Reinforcement Learning team at Meta. It enables researchers and practitioners to develop Reinforcement Learning AI agents that prioritize cumulative long-term feedback over immediate feedback and can adapt to environments with limited observability, sparse feedback, and high stochasticity. Pearl offers a diverse set of unique features for production environments, including dynamic action spaces, offline learning, intelligent neural exploration, safe decision making, history summarization, and data augmentation.

Acte is a framework designed to build GUI-like tools for AI Agents. It aims to address the issues of cognitive load and freedom degrees when interacting with multiple APIs in complex scenarios. By providing a graphical user interface (GUI) for Agents, Acte helps reduce cognitive load and constraints interaction, similar to how humans interact with computers through GUIs. The tool offers APIs for starting new sessions, executing actions, and displaying screens, accessible via HTTP requests or the SessionManager class.

The `mystic` framework provides a collection of optimization algorithms and tools that allow the user to robustly solve hard optimization problems. It offers fine-grained power to monitor and steer optimizations during the fit processes. Optimizers can advance one iteration or run to completion, with customizable stop conditions. `mystic` optimizers share a common interface for easy swapping without writing new code. The framework supports parameter constraints, including soft and hard constraints, and provides tools for scientific machine learning, uncertainty quantification, adaptive sampling, nonlinear interpolation, and artificial intelligence. `mystic` is actively developed and welcomes user feedback and contributions.

Seer is a service that provides AI capabilities to Sentry by running inference on Sentry issues and providing user insights. It is currently in early development and not yet compatible with self-hosted Sentry instances. The tool requires access to internal Sentry resources and is intended for internal Sentry employees. Users can set up the environment, download model artifacts, integrate with local Sentry, run evaluations for Autofix AI agent, and deploy to a sandbox staging environment. Development commands include applying database migrations, creating new migrations, running tests, and more. The tool also supports VCRs for recording and replaying HTTP requests.

**Description:** PromptFuzz is an automated tool that generates high-quality fuzz drivers for libraries via a fuzz loop constructed on mutating LLMs' prompts. The fuzz loop of PromptFuzz aims to guide the mutation of LLMs' prompts to generate programs that cover more reachable code and explore complex API interrelationships, which are effective for fuzzing. **Features:** * **Multiply LLM support** : Supports the general LLMs: Codex, Inocder, ChatGPT, and GPT4 (Currently tested on ChatGPT). * **Context-based Prompt** : Construct LLM prompts with the automatically extracted library context. * **Powerful Sanitization** : The program's syntax, semantics, behavior, and coverage are thoroughly analyzed to sanitize the problematic programs. * **Prioritized Mutation** : Prioritizes mutating the library API combinations within LLM's prompts to explore complex interrelationships, guided by code coverage. * **Fuzz Driver Exploitation** : Infers API constraints using statistics and extends fixed API arguments to receive random bytes from fuzzers. * **Fuzz engine integration** : Integrates with grey-box fuzz engine: LibFuzzer. **Benefits:** * **High branch coverage:** The fuzz drivers generated by PromptFuzz achieved a branch coverage of 40.12% on the tested libraries, which is 1.61x greater than _OSS-Fuzz_ and 1.67x greater than _Hopper_. * **Bug detection:** PromptFuzz detected 33 valid security bugs from 49 unique crashes. * **Wide range of bugs:** The fuzz drivers generated by PromptFuzz can detect a wide range of bugs, most of which are security bugs. * **Unique bugs:** PromptFuzz detects uniquely interesting bugs that other fuzzers may miss. **Usage:** 1. Build the library using the provided build scripts. 2. Export the LLM API KEY if using ChatGPT or GPT4. 3. Generate fuzz drivers using the `fuzzer` command. 4. Run the fuzz drivers using the `harness` command. 5. Deduplicate and analyze the reported crashes. **Future Works:** * **Custom LLMs suport:** Support custom LLMs. * **Close-source libraries:** Apply PromptFuzz to close-source libraries by fine tuning LLMs on private code corpus. * **Performance** : Reduce the huge time cost required in erroneous program elimination.

Language Models is a Python package that provides building blocks to explore large language models with as little as 512MB of RAM. It simplifies the usage of large language models from Python, ensuring all inference is performed locally to keep data private. The package includes features such as text completions, chat capabilities, code completions, external text retrieval, semantic search, and more. It outperforms Hugging Face transformers for CPU inference and offers sensible default models with varying parameters based on memory constraints. The package is suitable for learners and educators exploring the intersection of large language models with modern software development.

LMQL is a programming language designed for large language models (LLMs) that offers a unique way of integrating traditional programming with LLM interaction. It allows users to write programs that combine algorithmic logic with LLM calls, enabling model reasoning capabilities within the context of the program. LMQL provides features such as Python syntax integration, rich control-flow options, advanced decoding techniques, powerful constraints via logit masking, runtime optimization, sync and async API support, multi-model compatibility, and extensive applications like JSON decoding and interactive chat interfaces. The tool also offers library integration, flexible tooling, and output streaming options for easy model output handling.

LLM for Unity enables seamless integration of Large Language Models (LLMs) within the Unity engine, allowing users to create intelligent characters for immersive player interactions. The tool supports major LLM models, runs locally without internet access, offers fast inference on CPU and GPU, and is easy to set up with a single line of code. It is free for both personal and commercial use, tested on Unity 2021 LTS, 2022 LTS, and 2023. Users can build multiple AI characters efficiently, use remote servers for processing, and customize model settings for text generation.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

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.

The devdocs-to-llm repository is a work-in-progress tool that aims to convert documentation from DevDocs format to Long Language Model (LLM) format. This tool is designed to streamline the process of converting documentation for use with LLMs, making it easier for developers to leverage large language models for various tasks. By automating the conversion process, developers can quickly adapt DevDocs content for training and fine-tuning LLMs, enabling them to create more accurate and contextually relevant language models.

Lumos is a Chrome extension powered by a local LLM co-pilot for browsing the web. It allows users to summarize long threads, news articles, and technical documentation. Users can ask questions about reviews and product pages. The tool requires a local Ollama server for LLM inference and embedding database. Lumos supports multimodal models and file attachments for processing text and image content. It also provides options to customize models, hosts, and content parsers. The extension can be easily accessed through keyboard shortcuts and offers tools for automatic invocation based on prompts.

Write your GPT instructions, context, persona, constraints. The more detailed the better.

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.

Your expert assistant for Google Calendar and gmail tasks, integrated with Zapier (works with free plan). Supports: list, add, update events to calendar, send gmail. You will be prompted to configure zapier actions when set up initially. Conversation data is not used for openai training.