Best AI tools for< Run Prompts >

Knit is an AI playground for prompt designers. It provides professional prompt editors with various models, including GPT-4-turbo/vision, Claude-3, Gemini-pro, and more. Users can store, edit, and run their prompts in Knit. It also offers project management features, allowing users to organize prompts with projects, set up projects for different use cases, and collaborate with team members. Knit supports different kinds of models, including OpenAI, Claude, Azure OpenAI, and plans to support more in the future. It allows users to control API parameters, export code instantly, and provides security features such as encryption and version control.

Dora is a no-code 3D animated website design platform that allows users to create stunning 3D and animated visuals without writing a single line of code. With Dora, designers, freelancers, and creative professionals can focus on what they do best: designing. The platform is tailored for professionals who prioritize design aesthetics without wanting to dive deep into the backend. Dora offers a variety of features, including a drag-and-connect constraint layout system, advanced animation capabilities, and pixel-perfect usability. With Dora, users can create responsive 3D and animated websites that translate seamlessly across devices.

Dora is an AI-powered platform that enables users to create 3D animated websites without the need for coding. It caters to designers, freelancers, and creative professionals who seek to design visually captivating websites effortlessly. With Dora, users can craft mesmerizing 3D and animated visuals that are responsive and seamlessly translate across devices. The platform is designed for professionals who prioritize design aesthetics and offers a no-code experience for those transitioning from other design tools. Dora leverages advanced AI algorithms to generate, customize, and deploy stunning landing pages, revolutionizing the web design process.

Lumora is an AI tool designed to help users efficiently manage, optimize, and test prompts for various AI platforms. It offers features such as prompt organization, enhancement, testing, and development. Lumora aims to improve prompt outcomes and streamline prompt management for teams, providing a user-friendly interface and a playground for experimentation. The tool also integrates with various AI models for text, image, and video generation, allowing users to optimize prompts for better results.

Vidura is a prompt management system integrated with multiple AI systems, designed to enhance the Generative AI experience. Users can compose, organize, share, and export AI prompts efficiently. The platform offers features like categorizing prompts, built-in templates, prompt history audit, dynamic prompting, and community sharing. Vidura aims to simplify the process of generating text and image responses with AI, making it accessible and user-friendly for a wider audience.

GPT Prompt Tuner is an AI tool designed to enhance ChatGPT prompts by generating variations and running conversations in parallel. It aims to streamline the process of prompt engineering, offering users the ability to customize prompts, receive AI-generated variations, and engage in multiple ChatGPT conversations simultaneously. The tool provides flexible subscription plans, including options for monthly, yearly, and enterprise usage. With a focus on improving prompt quality and efficiency, GPT Prompt Tuner empowers users to optimize their interactions with ChatGPT.

AI Art Generator is an online platform that leverages state-of-the-art Stable Diffusion technology to quickly turn users' imaginations into amazing artistic creations with just simple text prompts. Users can create unique images by providing text descriptions, and the AI model generates original artworks in seconds. The platform allows anyone to easily create stunning AI-generated artworks without needing artistic skills or training. AI Art Generator aims to provide a seamless and creative experience for users to explore the future of art through advanced technology.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Reflect is an AI-powered test automation tool that revolutionizes the way end-to-end tests are created, executed, and maintained. By leveraging Generative AI, Reflect eliminates the need for manual coding and provides a seamless testing experience. The tool offers features such as no-code test automation, visual testing, API testing, cross-browser testing, and more. Reflect aims to help companies increase software quality by accelerating testing processes and ensuring test adaptability over time.

Stablematic is a web-based platform that allows users to run Stable Diffusion and other machine learning models without the need for local setup or hardware limitations. It provides a user-friendly interface, pre-installed plugins, and dedicated GPU resources for a seamless and efficient workflow. Users can generate images and videos from text prompts, merge multiple models, train custom models, and access a range of pre-trained models, including Dreambooth and CivitAi models. Stablematic also offers API access for developers and dedicated support for users to explore and utilize the capabilities of Stable Diffusion and other machine learning models.

Langtail is a platform that helps developers build, test, and deploy AI-powered applications. It provides a suite of tools to help developers debug prompts, run tests, and monitor the performance of their AI models. Langtail also offers a community forum where developers can share tips and tricks, and get help from other users.

PromptPoint Playground is an AI tool designed to help users design, test, and deploy prompts quickly and efficiently. It enables teams to create high-quality LLM outputs through automatic testing and evaluation. The platform allows users to make non-deterministic prompts predictable, organize prompt configurations, run automated tests, and monitor usage. With a focus on collaboration and accessibility, PromptPoint Playground empowers both technical and non-technical users to leverage the power of large language models for prompt engineering.

ChatGPT for Outlook is an AI tool that integrates the power of ChatGPT into Microsoft Outlook, allowing users to run ChatGPT on emails to generate summaries, highlights, and important information. Users can create custom prompts, process entire emails or specific parts, manage multiple configurations, and improve email efficiency. Blueberry Consultants, the developer, offers custom versions for businesses and teams, enabling users to resell the tool with unique prompts. The tool enhances productivity and information management within Outlook, leveraging AI technology for email processing and organization.

Sink In is a cloud-based platform that provides access to Stable Diffusion AI image generation models. It offers a variety of models to choose from, including majicMIX realistic, MeinaHentai, AbsoluteReality, DreamShaper, and more. Users can generate images by inputting text prompts and selecting the desired model. Sink In charges $0.0015 for each 512x512 image generated, and it offers a 99.9% reliability guarantee for images generated in the last 30 days.

Lunary is an AI developer platform designed to bring AI applications to production. It offers a comprehensive set of tools to manage, improve, and protect LLM apps. With features like Logs, Metrics, Prompts, Evaluations, and Threads, Lunary empowers users to monitor and optimize their AI agents effectively. The platform supports tasks such as tracing errors, labeling data for fine-tuning, optimizing costs, running benchmarks, and testing open-source models. Lunary also facilitates collaboration with non-technical teammates through features like A/B testing, versioning, and clean source-code management.

Robopic™ is an AI photo generator tool that allows users to create beautiful AI photos and videos without the need for a camera. Users can upload their selfies to generate AI avatars, take AI photos in any pose or action, and create AI videos from these photos. Robopic™ stands out for its high photorealism, resolution, and ability to maintain ethnicity in the generated images. With a variety of preset photo packs available, users can easily create customized images without the hassle of writing prompts or setting parameters. Overall, Robopic™ offers a cost-effective and convenient solution for conducting photo shoots using AI technology.

Alice is a desktop application that provides access to advanced AI models like GPT-4, Perplexity, Claude 3, and others. It offers a user-friendly interface with features such as keyboard shortcuts, pre-built prompts (Snippets), and the ability to run automations within other applications. Alice is designed to enhance productivity and streamline tasks by providing quick access to AI-powered assistance.

PromptLoop is an AI-powered web scraping and data extraction platform that allows users to run AI automation tasks on lists of data with a simple file upload. It enables users to crawl company websites, categorize entities, and conduct research tasks at a fraction of the cost of other alternatives. By leveraging unique company data from spreadsheets, PromptLoop enables the creation of custom AI models tailored to specific needs, facilitating the extraction of valuable insights from complex information.

Promptchan AI is an AI tool that serves as an NSFW AI Generator. It requires JavaScript to be enabled to run the app. The tool focuses on maintaining character consistency, allowing pro users to use characters for recurring themes.

Magnet is an AI coding assistant that helps product teams fix issues, share AI threads, and organize projects. It integrates with Linear, GitHub, and Notion, and provides auto-suggested files and code files for personalized and accurate AI recommendations. Magnet also offers prompt templates to help users get started and suggests quick fixes for bugs or enhancements.

LLM is a CLI utility and Python library for interacting with Large Language Models, both via remote APIs and models that can be installed and run on your own machine. It allows users to run prompts from the command-line, store results in SQLite, generate embeddings, and more. The tool supports self-hosted language models via plugins and provides access to remote and local models. Users can install plugins to access models by different providers, including models that can be installed and run on their own device. LLM offers various options for running Mistral models in the terminal and enables users to start chat sessions with models. Additionally, users can use a system prompt to provide instructions for processing input to the tool.

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

AIConfig is a framework that makes it easy to build generative AI applications for production. It manages generative AI prompts, models and model parameters as JSON-serializable configs that can be version controlled, evaluated, monitored and opened in a local editor for rapid prototyping. It allows you to store and iterate on generative AI behavior separately from your application code, offering a streamlined AI development workflow.

org-ai is a minor mode for Emacs org-mode that provides access to generative AI models, including OpenAI API (ChatGPT, DALL-E, other text models) and Stable Diffusion. Users can use ChatGPT to generate text, have speech input and output interactions with AI, generate images and image variations using Stable Diffusion or DALL-E, and use various commands outside org-mode for prompting using selected text or multiple files. The tool supports syntax highlighting in AI blocks, auto-fill paragraphs on insertion, and offers block options for ChatGPT, DALL-E, and other text models. Users can also generate image variations, use global commands, and benefit from Noweb support for named source blocks.

Instruct2Act is a framework that utilizes Large Language Models to map multi-modal instructions to sequential actions for robotic manipulation tasks. It generates Python programs using the LLM model for perception, planning, and action. The framework leverages foundation models like SAM and CLIP to convert high-level instructions into policy codes, accommodating various instruction modalities and task demands. Instruct2Act has been validated on robotic tasks in tabletop manipulation domains, outperforming learning-based policies in several tasks.

Jupyter AI connects generative AI with Jupyter notebooks. It provides a user-friendly and powerful way to explore generative AI models in notebooks and improve your productivity in JupyterLab and the Jupyter Notebook. Specifically, Jupyter AI offers: * An `%%ai` magic that turns the Jupyter notebook into a reproducible generative AI playground. This works anywhere the IPython kernel runs (JupyterLab, Jupyter Notebook, Google Colab, Kaggle, VSCode, etc.). * A native chat UI in JupyterLab that enables you to work with generative AI as a conversational assistant. * Support for a wide range of generative model providers, including AI21, Anthropic, AWS, Cohere, Gemini, Hugging Face, NVIDIA, and OpenAI. * Local model support through GPT4All, enabling use of generative AI models on consumer grade machines with ease and privacy.

MCP CLI client is a simple CLI program designed to run LLM prompts and act as an alternative client for Model Context Protocol (MCP). Users can interact with MCP-compatible servers from their terminal, including LLM providers like OpenAI, Groq, or local LLM models via llama. The tool supports various functionalities such as running prompt templates, analyzing image inputs, triggering tools, continuing conversations, utilizing clipboard support, and additional options like listing tools and prompts. Users can configure LLM and MCP servers via a JSON config file and contribute to the project by submitting issues and pull requests for enhancements or bug fixes.

Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.

HebTTS is a language modeling approach to diacritic-free Hebrew text-to-speech (TTS) system. It addresses the challenge of accurately mapping text to speech in Hebrew by proposing a language model that operates on discrete speech representations and is conditioned on a word-piece tokenizer. The system is optimized using weakly supervised recordings and outperforms diacritic-based Hebrew TTS systems in terms of content preservation and naturalness of generated speech.

BTGenBot is a tool that generates behavior trees for robots using lightweight large language models (LLMs) with a maximum of 7 billion parameters. It fine-tunes on a specific dataset, compares multiple LLMs, and evaluates generated behavior trees using various methods. The tool demonstrates the potential of LLMs with a limited number of parameters in creating effective and efficient robot behaviors.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

This repository provides AI tools for developers through Docker containers, enabling agentic workflows. It allows users to create complex workflows using Dockerized tools and Markdown, leveraging various LLM models. The core features include Dockerized tools, conversation loops, multi-model agents, project-first design, and trackable prompts stored in a git repo.

Evals provide a framework for evaluating large language models (LLMs) or systems built using LLMs. We offer an existing registry of evals to test different dimensions of OpenAI models and the ability to write your own custom evals for use cases you care about. You can also use your data to build private evals which represent the common LLMs patterns in your workflow without exposing any of that data publicly.

LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. It allows users to control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy, and LLM testing - through a single YAML configuration file. The toolkit supports basic, intermediate, and advanced usage scenarios, enabling users to run custom experiments, conduct ablation studies, and automate fine-tuning workflows. It provides features for data ingestion, model definition, training, inference, quality assurance, and artifact outputs, making it a comprehensive tool for fine-tuning large language models.

Vivaria is a web application tool designed for running evaluations and conducting agent elicitation research. Users can interact with Vivaria using a web UI and a command-line interface. It allows users to start task environments based on METR Task Standard definitions, run AI agents, perform agent elicitation research, view API requests and responses, add tags and comments to runs, store results in a PostgreSQL database, sync data to Airtable, test prompts against LLMs, and authenticate using Auth0.

PromptAgent is a repository for a novel automatic prompt optimization method that crafts expert-level prompts using language models. It provides a principled framework for prompt optimization by unifying prompt sampling and rewarding using MCTS algorithm. The tool supports different models like openai, palm, and huggingface models. Users can run PromptAgent to optimize prompts for specific tasks by strategically sampling model errors, generating error feedbacks, simulating future rewards, and searching for high-reward paths leading to expert prompts.

Magic_Words is a repository containing code for the paper 'What's the Magic Word? A Control Theory of LLM Prompting'. It implements greedy back generation and greedy coordinate gradient (GCG) to find optimal control prompts (magic words). Users can set up a virtual environment, install the package and dependencies, and run example scripts for pointwise control and optimizing prompts for datasets. The repository provides scripts for finding optimal control prompts for question-answer pairs and dataset optimization using the GCG algorithm.

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

Empirical is a tool that allows you to test different LLMs, prompts, and other model configurations across all the scenarios that matter for your application. With Empirical, you can run your test datasets locally against off-the-shelf models, test your own custom models and RAG applications, view, compare, and analyze outputs on a web UI, score your outputs with scoring functions, and run tests on CI/CD.

TinyLLM is a project that helps build a small locally hosted language model with a web interface using consumer-grade hardware. It supports multiple language models, builds a local OpenAI API web service, and serves a Chatbot web interface with customizable prompts. The project requires specific hardware and software configurations for optimal performance. Users can run a local language model using inference servers like vLLM, llama-cpp-python, and Ollama. The Chatbot feature allows users to interact with the language model through a web-based interface, supporting features like summarizing websites, displaying news headlines, stock prices, weather conditions, and using vector databases for queries.

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