Best AI tools for< Experiment Setup >

Local AI Playground (local.ai) is an AI management, verification, and inferencing tool that allows users to experiment with AI offline and in private without the need for a GPU. It is a native app designed to simplify the AI process, offering features such as CPU inferencing, model management, and digest verification. The tool is memory efficient and compact, with upcoming features including GPU inferencing and custom sorting. Users can start a local streaming server for AI inferencing in just 2 clicks, making it a versatile and user-friendly AI application.

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.

AI Product Shot is an innovative AI tool that enables users to create professional product ads quickly and effortlessly. With AI Product Shot, users can experiment with various product shots, generate photorealistic concepts, and create stunning product ads that drive conversions. The tool eliminates the need for a physical studio setup, allowing brands to bring their products to life with ease. AI Product Shot offers studio-quality results, transforming basic background product shots into professional assets in minutes. Users can train custom AI models, experiment with different environments and lighting, and produce unique product images with unlimited creativity.

Sacred is a tool to configure, organize, log and reproduce computational experiments. It is designed to introduce only minimal overhead, while encouraging modularity and configurability of experiments. The ability to conveniently make experiments configurable is at the heart of Sacred. If the parameters of an experiment are exposed in this way, it will help you to: keep track of all the parameters of your experiment easily run your experiment for different settings save configurations for individual runs in files or a database reproduce your results In Sacred we achieve this through the following main mechanisms: Config Scopes are functions with a @ex.config decorator, that turn all local variables into configuration entries. This helps to set up your configuration really easily. Those entries can then be used in captured functions via dependency injection. That way the system takes care of passing parameters around for you, which makes using your config values really easy. The command-line interface can be used to change the parameters, which makes it really easy to run your experiment with modified parameters. Observers log every information about your experiment and the configuration you used, and saves them for example to a Database. This helps to keep track of all your experiments. Automatic seeding helps controlling the randomness in your experiments, such that they stay reproducible.

More Views AI is an AI tool designed to help YouTube content creators increase their view count by testing different video settings. The tool uses artificial intelligence to analyze video titles, suggest variations, and run A/B tests to determine the best-performing title. It offers features such as automatic A/B toggling, performance tracking, views optimization, AI-generated title suggestions, and thumbnail testing. Users can connect their YouTube account, set up experiments in seconds, and let the algorithm optimize their video titles to attract more views.

Google Labs is a website that showcases experimental AI tools and technology developed by Google. These tools are designed to help users explore the potential of AI in various fields, including creativity, productivity, and education. Some of the featured tools include: - **LABS.GOOGLE**: A platform for experimenting with the future of AI, including tools for creating images from text, generating music, and writing scripts for home automation. - **NotebookLM**: A personalized AI collaborator designed to help users with their thinking and writing. - **Say What You See**: A tool that helps users learn the art of prompting and improving their image-reading skills. - **Help Me Script**: A tool that turns text into home automation scripts for Google Home. - **ImageFX**: A tool that transforms text into images, allowing users to explore endless possibilities. - **Gen AI in Chrome**: A tool that creates themes with AI, organizes tabs, and helps users write more confidently on the web. - **MusicFX**: A tool that describes a musical idea and brings it to life. - **Duet AI**: A tool that helps users create, write, visualize, and organize in new ways with collaborative AI tools in Google Workspace. - **TextFX**: A tool that supercharges the writing process with AI-powered language tools.

AI Test Kitchen is a website that provides a variety of AI-powered tools for creative professionals. These tools can be used to generate images, music, and text, as well as to explore different creative concepts. The website is designed to be a place where users can experiment with AI and learn how to use it to enhance their creative process.

Kameleoon is an AI-driven A/B testing platform and personalization tool designed to optimize web experiences through experimentation and feature management. It offers a single platform with AI-powered conversion capabilities, strong security features, and powerful integrations. Kameleoon caters to a wide range of industries, including E-commerce, Retail, Travel, Automotive, Financial Services, Media, Healthcare, and B2B SaaS. The platform enables users to run experiments, personalize content, manage features, and analyze real-time data to enhance user experiences and drive growth.

GPT4Free is a free playground for experimenting with ChatGPT without the hassle of APIs, logins, or restrictions. It offers a wide range of features, including a prompt library, organized chats, import/export functionality, customizable model parameters, and multiple language support. GPT4Free also provides access to GPT Reverse Proxy, allowing users to interact with GPT4 & GPT3.5 and GPT4 Vision from anywhere in the world.

Aim is an open-source experiment tracker that logs your training runs, enables a beautiful UI to compare them, and an API to query them programmatically. It integrates seamlessly with your favorite tools.

LABS.GOOGLE is a platform where users can experiment with the future of AI through various tools and applications. It offers a wide range of AI-powered features and experiences, from visual artists reimagining classic works to transforming text into images and videos. Users can explore AI in different domains such as music, writing, education, and more. The platform aims to showcase the potential of AI technology and its applications in everyday life.

MusicGen AI is a free and advanced AI music generation tool developed by Meta. It utilizes a single Language Model (LM) to create high-quality music based on text descriptions, melodies, or audio prompts. MusicGen operates by encoding music into compressed tokens, which are then used to generate the music samples. It can produce music in various formats, including mono and stereo. MusicGen AI offers a range of features, including melody conditioning, text-conditional generation, audio-prompted generation, advanced model architecture, flexible generation modes, unconditional generation, extensive training dataset, and customizable generation process.

Heatseeker is an AI-powered market experimentation tool that helps businesses predict customer preferences, conduct feature tests, and generate value propositions. It enables users to answer critical growth questions about market, audience, and product features through AI-powered experiments. Heatseeker provides insights into market trends, competitor analysis, and helps in making data-driven decisions. The platform offers curated recommendations, competitive intelligence, and continuous testing for refining strategies. It automates ad campaign generation, data collection, and provides recommendations for launching new products. Heatseeker is designed to help businesses optimize their marketing efforts and improve their product offerings.

Outfit Anyone AI is a groundbreaking virtual try-on technology developed by the Institute for Intelligent Computing at Alibaba Group. It revolutionizes the virtual fashion experience by offering ultra-high quality and realistic try-on experiences for any clothing on any person. The platform utilizes advanced AI models to process images of clothing and models, ensuring lifelike results that consider factors like pose and body shape. With a focus on inclusivity, versatility, and animation support, Outfit Anyone AI aims to redefine the way users explore fashion.

CustomerGlu is a gamification platform designed to supercharge app growth through in-app monetization. It offers a variety of gamified user journeys to enhance activation, retention, and user delight. With features like ready templates, personalized recommendations, surveys, and engagement challenges, CustomerGlu helps businesses improve key metrics and build stronger relationships with users. The platform enables quick idea-to-launch with over 50 templates, real-time reporting, personalization, and seamless integration with existing tools. CustomerGlu is trusted by growth teams for its proven results in boosting conversions, retention rates, and engagement levels.

Generate is an experiment to generate data from LLM. It is now deprecated.

Synthace is a digital experiment platform designed for R&D teams in the life science industry. It allows users to design and run powerful experiments in the lab, automatically build structured data, and gain insights without the need for coding. The platform centralizes bioprocess data, reduces human error, and enables confident protocol reproducibility.

RBG AI Drop #001 is an AI tool that allows users to interact with a virtual version of Justice Ruth Bader Ginsburg. Users can ask her any YES/NO question and receive a response. The tool is designed as an experiment to engage users in a unique and interactive way. By signing up, users can be the first to receive future AI drops and continue the experience.

Change Clothes AI is an innovative AI-powered online tool that revolutionizes the way we try on clothes. By utilizing cutting-edge AI algorithms, the application analyzes user photos and garment images to seamlessly create realistic images of individuals wearing new outfits. With a user-friendly interface and hyperrealistic results, Change Clothes AI eliminates the guesswork in online shopping, allowing users to visualize themselves in different styles effortlessly. The application offers a free trial and aims to provide a fun and functional experience for exploring endless outfit possibilities.

UpTrain is a full-stack LLMOps platform designed to help users with all their production needs, from evaluation to experimentation to improvement. It offers diverse evaluations, automated regression testing, enriched datasets, and precision metrics to enhance the development of LLM applications. UpTrain is built for developers, by developers, and is compliant with data governance needs. It provides cost efficiency, reliability, and open-source core evaluation framework. The platform is suitable for developers, product managers, and business leaders looking to enhance their LLM applications.

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.

ClearML is a suite of tools designed to streamline the machine learning workflow. It includes an experiment manager, MLOps/LLMOps, data management, and model serving capabilities. ClearML is open-source and offers a free tier hosting option. It supports various ML/DL frameworks and integrates with Jupyter Notebook and PyCharm. ClearML provides extensive logging capabilities, including source control info, execution environment, hyper-parameters, and experiment outputs. It also offers automation features, such as remote job execution and pipeline creation. ClearML is designed to be easy to integrate, requiring only two lines of code to add to existing scripts. It aims to improve collaboration, visibility, and data transparency within ML teams.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

NanoFlow is a throughput-oriented high-performance serving framework for Large Language Models (LLMs) that consistently delivers superior throughput compared to other frameworks by utilizing key techniques such as intra-device parallelism, asynchronous CPU scheduling, and SSD offloading. The framework proposes nano-batching to schedule compute-, memory-, and network-bound operations for simultaneous execution, leading to increased resource utilization. NanoFlow also adopts an asynchronous control flow to optimize CPU overhead and eagerly offloads KV-Cache to SSDs for multi-round conversations. The open-source codebase integrates state-of-the-art kernel libraries and provides necessary scripts for environment setup and experiment reproduction.

ICE-Score is a tool designed to instruct large language models to evaluate code. It provides a minimum viable product (MVP) for evaluating generated code snippets using inputs such as problem, output, task, aspect, and model. Users can also evaluate with reference code and enable zero-shot chain-of-thought evaluation. The tool is built on codegen-metrics and code-bert-score repositories and includes datasets like CoNaLa and HumanEval. ICE-Score has been accepted to EACL 2024.

Lightning Lab is a public template for artificial intelligence and machine learning research projects using Lightning AI's PyTorch Lightning. It provides a structured project layout with modules for command line interface, experiment utilities, Lightning Module and Trainer, data acquisition and preprocessing, model serving APIs, project configurations, training checkpoints, technical documentation, logs, notebooks for data analysis, requirements management, testing, and packaging. The template simplifies the setup of deep learning projects and offers extras for different domains like vision, text, audio, reinforcement learning, and forecasting.

The discourse-chatbot is an original AI chatbot for Discourse forums that allows users to converse with the bot in posts or chat channels. Users can customize the character of the bot, enable RAG mode for expert answers, search Wikipedia, news, and Google, provide market data, perform accurate math calculations, and experiment with vision support. The bot uses cutting-edge Open AI API and supports Azure and proxy server connections. It includes a quota system for access management and can be used in RAG mode or basic bot mode. The setup involves creating embeddings to make the bot aware of forum content and setting up bot access permissions based on trust levels. Users must obtain an API token from Open AI and configure group quotas to interact with the bot. The plugin is extensible to support other cloud bots and content search beyond the provided set.

FastTrackML is an experiment tracking server focused on speed and scalability, fully compatible with MLFlow. It provides a user-friendly interface to track and visualize your machine learning experiments, making it easy to compare different models and identify the best performing ones. FastTrackML is open source and can be easily installed and run with pip or Docker. It is also compatible with the MLFlow Python package, making it easy to integrate with your existing MLFlow workflows.

ClearML Server is a backend service infrastructure for ClearML, facilitating collaboration and experiment management. It includes a web app, RESTful API, and file server for storing images and models. Users can deploy ClearML Server using Docker, AWS EC2 AMI, or Kubernetes. The system design supports single IP or sub-domain configurations with specific open ports. ClearML-Agent Services container allows launching long-lasting jobs and various use cases like auto-scaler service, controllers, optimizer, and applications. Advanced functionality includes web login authentication and non-responsive experiments watchdog. Upgrading ClearML Server involves stopping containers, backing up data, downloading the latest docker-compose.yml file, configuring ClearML-Agent Services, and spinning up docker containers. Community support is available through ClearML FAQ, Stack Overflow, GitHub issues, and email contact.

SwanLab is an open-source, lightweight AI experiment tracking tool that provides a platform for tracking, comparing, and collaborating on experiments, aiming to accelerate the research and development efficiency of AI teams by 100 times. It offers a friendly API and a beautiful interface, combining hyperparameter tracking, metric recording, online collaboration, experiment link sharing, real-time message notifications, and more. With SwanLab, researchers can document their training experiences, seamlessly communicate and collaborate with collaborators, and machine learning engineers can develop models for production faster.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

rag-chatbot is a tool that allows users to chat with multiple PDFs using Ollama and LlamaIndex. It provides an easy setup for running on local machines or Kaggle notebooks. Users can leverage models from Huggingface and Ollama, process multiple PDF inputs, and chat in multiple languages. The tool offers a simple UI with Gradio, supporting chat with history and QA modes. Setup instructions are provided for both Kaggle and local environments, including installation steps for Docker, Ollama, Ngrok, and the rag_chatbot package. Users can run the tool locally and access it via a web interface. Future enhancements include adding evaluation, better embedding models, knowledge graph support, improved document processing, MLX model integration, and Corrective RAG.

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.

OptScale is an open-source FinOps and MLOps platform that provides cloud cost optimization for all types of organizations and MLOps capabilities like experiment tracking, model versioning, ML leaderboards.

AIQC is an open source Python package that provides a declarative API for end-to-end MLOps in order to make deep learning more accessible to researchers. It utilizes a SQLite object-relational model for machine learning objects and stacks standardized workflows for various analyses, data types, and libraries. The benefits include a 90% reduction in data wrangling, reproducibility, and no need to install and maintain application and database servers for experiment tracking. AIQC is pip-installable and provides a Dash-Plotly UI for real-time experiment tracking.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

ML-Bench is a tool designed to evaluate large language models and agents for machine learning tasks on repository-level code. It provides functionalities for data preparation, environment setup, usage, API calling, open source model fine-tuning, and inference. Users can clone the repository, load datasets, run ML-LLM-Bench, prepare data, fine-tune models, and perform inference tasks. The tool aims to facilitate the evaluation of language models and agents in the context of machine learning tasks on code repositories.

This repository contains the code for HOLD, a method that jointly reconstructs hands and objects from monocular videos without assuming a pre-scanned object template. It can reconstruct 3D geometries of novel objects and hands, enabling template-free bimanual hand-object reconstruction, textureless object interaction with hands, and multiple objects interaction with hands. The repository provides instructions to download in-the-wild videos from HOLD, preprocess and train on custom videos, a volumetric rendering framework, a generalized codebase for single and two hand interaction with objects, a viewer to interact with predictions, and code to evaluate and compare with HOLD in HO3D. The repository also includes documentation for setup, training, evaluation, visualization, preprocessing custom sequences, and using HOLD on ARCTIC.

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

Assists in designing experiments for your scientific questions

Demystifying Experimentation and Causal Inference with 1-Sided Tests Focus

Upload a court judgment and get back a collection of topical case digests based on the case. Oh - don't trust the "Topic 2210" or similar number, it's random. Also, probably best you not fully trust the output either. We're just playing with the GPT maker. More about us at Jurisage.com.

EXPERIMENT - Friendly expert on NYC dog license data from 2015-2016, with info on names, breeds and boroughs

EXPERIMENT - Friendly guide for navigating Anchorage Municipal Code - Double Check info

An experiment in personal FileMaker guidance from the collective works of lifetime award-winning FileMaker trainer, Cris Ippolite. Not just links to resources, but direct access to 20+ years of custom training curriculum combined with expert AI instruction without the noise of external web links.

Engaging science experiment assistant with humor

Automated AI experiment tool for evaluating prompt strategies.

Dalle + custom corrupted data from every artist in the world. This is an experiment. (beta)

Research assistant for Atomic, Molecular, and Optics Physics

Expert in synthetic neurobiology, brain organoids, and AI applications in neuroscience. Powered by Breebs (www.breebs.com)

Artisan of spirits and guide to cocktail-cuisine harmony.

Quantum Hypothesis，About A New Universal Physical Theory

あなたの写真に基づいてヘアカラーを提案し、製品を紹介します。

Offers styling advice focusing on vintage and retro fashion trends.

Experto en fotografía analógica y técnicas de cuarto oscuro.

Assists in finding the perfect coffee grind size based on grinder and coffee.

A creative chef assistant for generating original recipes.

Assume the role of a MAD SCIENTIST bent on creating the most powerful animal in this turn based creature creator AI battler!

Explore a wide range of shoe styles and learn about design with AI-generated images.