Best AI tools for< Find New Libraries >
20 - AI tool Sites
Intel Gaudi AI Accelerator Developer
The Intel Gaudi AI accelerator developer website provides resources, guidance, tools, and support for building, migrating, and optimizing AI models. It offers software, model references, libraries, containers, and tools for training and deploying Generative AI and Large Language Models. The site focuses on the Intel Gaudi accelerators, including tutorials, documentation, and support for developers to enhance AI model performance.
NextThreeBooks.com
NextThreeBooks.com is an AI-powered book recommendation service that provides personalized suggestions based on your reading preferences. Share your preferences, tell us about yourself, and receive three carefully curated book suggestions with detailed explanations. We use GPT-3 to provide personalized book suggestions tailored to your reading preferences. Find your next favorite read with ease!
BooksAI
BooksAI is an AI-powered tool that provides book summaries, recommendations, and more. With over 40 million book summaries available, BooksAI makes it easy to discover new books and learn about your favorites. BooksAI's summaries are concise and easy to understand, making them perfect for busy professionals, students, and anyone who wants to learn more about the world's greatest books.
The StoryGraph
The StoryGraph is a book tracking and recommendation app that uses machine learning to help users find books they'll enjoy. It offers a variety of features, including personalized recommendations, mood-based browsing, and social features like book clubs and reading buddies. The StoryGraph is a great tool for anyone who loves to read and wants to discover new books.
Find your next book
Find your next book is an AI-powered librarian that provides personalized book recommendations based on your preferences. It uses advanced algorithms to analyze your reading history, interests, and other factors to suggest books that you're likely to enjoy. The platform offers a wide range of genres and authors to choose from, making it easy to find your next favorite read.
AI Bookstore
AI Bookstore is a website that uses AI to help users find books that they want to read. Users can ask the AI questions about what they are looking for, and the AI will recommend books that match their criteria. The AI can also generate personalized recommendations based on a user's reading history.
BookAbout
BookAbout is a revolutionary platform for book lovers that utilizes the latest AI technology to help users discover their next favorite book. With a database of over 500,000 books, BookAbout aims to make the book searching experience enjoyable and effortless. Users can say goodbye to traditional methods of searching for books and hello to a new way of finding their next literary adventure. The platform is constantly updated with the latest books and improved search algorithms to enhance user experience.
BookSurfAi
BookSurfAi is an AI-powered book recommendation tool that helps users discover their next favorite book. By leveraging artificial intelligence technology, the application provides personalized reading suggestions based on individual preferences and reading habits. BookSurfAi aims to enhance the reading experience by offering tailored recommendations that cater to each user's unique tastes and interests. With a user-friendly interface, BookSurfAi makes it easy for book lovers to explore new literary works and expand their reading horizons.
Book Bot
Book Bot is an online platform that provides book recommendations based on user preferences. Users can input their favorite genres, authors, or books, and the AI algorithm behind Book Bot will suggest personalized reading lists. The platform also offers book reviews, summaries, and the option to connect with other book lovers. Book Bot aims to enhance the reading experience by helping users discover new titles and connect with a community of readers.
ResearchRabbit
ResearchRabbit is a research tool that helps researchers discover and organize academic papers. It uses artificial intelligence to recommend papers that are relevant to a researcher's interests and to visualize networks of papers and co-authorships. ResearchRabbit also allows researchers to collaborate on collections of papers and to share their findings with others.
OpenRead
OpenRead is an AI-powered research tool that helps users discover, understand, and organize scientific literature. It offers a variety of features to make research more efficient and effective, including semantic search, AI summarization, and note-taking tools. OpenRead is designed to help researchers of all levels, from students to experienced professionals, save time and improve their research outcomes.
AcademicID
AcademicID is an AI-powered platform that helps students and researchers discover and access academic resources. It provides a comprehensive database of academic papers, journals, and other resources, as well as tools to help users organize and manage their research. AcademicID also offers a variety of features to help users collaborate with others and share their research findings.
Read This Twice
Read This Twice is a website dedicated to recommending books worth reading twice. The platform curates book recommendations from notable figures like Barack Obama, Bill Gates, Oprah Winfrey, and others. The database is continuously expanding with verified recommendations linked to the original sources. Users can explore various reading lists, discover new books, and receive personalized recommendations through an AI-driven assistant named 'Sona.'
Dr.Oracle
Dr.Oracle is a personal AI research assistant that helps you find and understand the latest research in your field. With Dr.Oracle, you can search for research papers, track your favorite authors, and get personalized recommendations for new research. Dr.Oracle is the perfect tool for students, researchers, and anyone who wants to stay up-to-date on the latest research in their field.
Find New AI
Find New AI is a comprehensive platform offering a variety of AI tools and efficiency solutions for different purposes such as SEO, content creation, marketing, link building, image manipulation, and more. The website provides reviews, tutorials, and guides on utilizing AI software effectively to enhance productivity and creativity in various domains.
CustomerPing
CustomerPing is an AI tool designed to help businesses find new customers by monitoring online conversations and sending alerts when potential leads are identified. The tool automates the prospecting process, saving time and effort for entrepreneurs. CustomerPing offers a unique approach to customer discovery, allowing users to engage with relevant discussions and build trust with potential customers. With features like Radar Stations, RSS feeds, and personalized notifications, CustomerPing streamlines the customer acquisition process and empowers businesses to connect with their target audience effectively.
ProductHunt AI 2.0
ProductHunt AI 2.0 is a no-BS product finder that makes it super easy to find super-effective products and alternatives on the go with semantic searches. It is 100% free to use and backed by Supervised AI. With ProductHunt AI 2.0, you can build agents like this with no-code, use free open-source AI models, or deploy your own language model.
Infinite Meals
Infinite Meals is a web application that provides users with a new meal idea every day. It is powered by GPT-3.5-Turbo-1106 from Open AI. The application is designed to help users find new and exciting recipes to cook. It offers a variety of features, including the ability to search for recipes by category, ingredient, or cuisine. Users can also save their favorite recipes and create meal plans.
Tapult
Tapult is a platform designed to help users build backlinks and partnerships to grow their website traffic. It simplifies the process of acquiring high-quality backlinks, enhancing website authority, and improving search result rankings. With features like identifying partnership opportunities, streamlining link-building, and connecting with relevant partners, Tapult aims to make the link-building process efficient and effective for bloggers, niche website owners, SaaS/app developers, e-commerce merchants, affiliate marketers, and SEO managers.
Orb Plugins
Orb Plugins offers a suite of AI-powered music production tools designed for composers, producers, and DJs. Their flagship product, Orb Producer 3, assists users in generating chords, melodies, and rhythms, while Orb Synth X provides a state-of-the-art wavetable synthesizer. Orb Orchestra is tailored for composers, enabling them to experiment with new musical ideas and compose efficiently. The plugins are known for their user-friendly interface, seamless DAW integration, and ability to break creative blocks. Many professionals in the music industry use Orb Plugins to enhance their workflow and explore new sonic possibilities.
20 - Open Source AI Tools
free-one-api
Free-one-api is a tool that allows access to all LLM reverse engineering libraries in a standard OpenAI API format. It supports automatic load balancing, Web UI, stream mode, multiple LLM reverse libraries, heartbeat detection mechanism, automatic disabling of unavailable channels, and runtime log recording. The tool is designed to work with the 'one-api' project and 'songquanpeng/one-api' for accessing official interfaces of various LLMs (paid). Contributors are needed to test adapters, find new reverse engineering libraries, and submit PRs.
gptme
GPTMe is a tool that allows users to interact with an LLM assistant directly in their terminal in a chat-style interface. The tool provides features for the assistant to run shell commands, execute code, read/write files, and more, making it suitable for various development and terminal-based tasks. It serves as a local alternative to ChatGPT's 'Code Interpreter,' offering flexibility and privacy when using a local model. GPTMe supports code execution, file manipulation, context passing, self-correction, and works with various AI models like GPT-4. It also includes a GitHub Bot for requesting changes and operates entirely in GitHub Actions. In progress features include handling long contexts intelligently, a web UI and API for conversations, web and desktop vision, and a tree-based conversation structure.
llms-tools
The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.
awesome-ai-tools
Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.
deepdoctection
**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.
oneAPI-samples
The oneAPI-samples repository contains a collection of samples for the Intel oneAPI Toolkits. These samples cover various topics such as AI and analytics, end-to-end workloads, features and functionality, getting started samples, Jupyter notebooks, direct programming, C++, Fortran, libraries, publications, rendering toolkit, and tools. Users can find samples based on expertise, programming language, and target device. The repository structure is organized by high-level categories, and platform validation includes Ubuntu 22.04, Windows 11, and macOS. The repository provides instructions for getting samples, including cloning the repository or downloading specific tagged versions. Users can also use integrated development environments (IDEs) like Visual Studio Code. The code samples are licensed under the MIT license.
ai-driven-dev-community
AI Driven Dev Community is a repository aimed at helping developers become more efficient by utilizing AI tools in their daily coding tasks. It provides a collection of tools, prompts, snippets, and agents for developers to integrate AI into their workflow. The repository is regularly updated with new resources and focuses on best practices for using AI in development work. Users can find tools like Espanso, ChatGPT, GitHub Copilot, and VSCode recommended for enhancing their coding experience. Additionally, the repository offers guidance on customizing AI for developers, installing AI toolbox for software engineers, and contributing to the community through easy steps.
pathway
Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.
max
The Modular Accelerated Xecution (MAX) platform is an integrated suite of AI libraries, tools, and technologies that unifies commonly fragmented AI deployment workflows. MAX accelerates time to market for the latest innovations by giving AI developers a single toolchain that unlocks full programmability, unparalleled performance, and seamless hardware portability.
upgini
Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.
nlp-llms-resources
The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.
cuvs
cuVS is a library that contains state-of-the-art implementations of several algorithms for running approximate nearest neighbors and clustering on the GPU. It can be used directly or through the various databases and other libraries that have integrated it. The primary goal of cuVS is to simplify the use of GPUs for vector similarity search and clustering.
Large-Language-Model-Notebooks-Course
This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.
allms
allms is a versatile and powerful library designed to streamline the process of querying Large Language Models (LLMs). Developed by Allegro engineers, it simplifies working with LLM applications by providing a user-friendly interface, asynchronous querying, automatic retrying mechanism, error handling, and output parsing. It supports various LLM families hosted on different platforms like OpenAI, Google, Azure, and GCP. The library offers features for configuring endpoint credentials, batch querying with symbolic variables, and forcing structured output format. It also provides documentation, quickstart guides, and instructions for local development, testing, updating documentation, and making new releases.
HuggingFaceGuidedTourForMac
HuggingFaceGuidedTourForMac is a guided tour on how to install optimized pytorch and optionally Apple's new MLX, JAX, and TensorFlow on Apple Silicon Macs. The repository provides steps to install homebrew, pytorch with MPS support, MLX, JAX, TensorFlow, and Jupyter lab. It also includes instructions on running large language models using HuggingFace transformers. The repository aims to help users set up their Macs for deep learning experiments with optimized performance.
LocalAIVoiceChat
LocalAIVoiceChat is an experimental alpha software that enables real-time voice chat with a customizable AI personality and voice on your PC. It integrates Zephyr 7B language model with speech-to-text and text-to-speech libraries. The tool is designed for users interested in state-of-the-art voice solutions and provides an early version of a local real-time chatbot.
LLM-Merging
LLM-Merging is a repository containing starter code for the LLM-Merging competition. It provides a platform for efficiently building LLMs through merging methods. Users can develop new merging methods by creating new files in the specified directory and extending existing classes. The repository includes instructions for setting up the environment, developing new merging methods, testing the methods on specific datasets, and submitting solutions for evaluation. It aims to facilitate the development and evaluation of merging methods for LLMs.
surfkit
Surfkit is a versatile toolkit designed for building and sharing AI agents that can operate on various devices. Users can create multimodal agents, share them with the community, run them locally or in the cloud, manage agent tasks at scale, and track and observe agent actions. The toolkit provides functionalities for creating agents, devices, solving tasks, managing devices, tracking tasks, and publishing agents. It also offers integrations with libraries like MLLM, Taskara, Skillpacks, and Threadmem. Surfkit aims to simplify the development and deployment of AI agents across different environments.
model_server
OpenVINO™ Model Server (OVMS) is a high-performance system for serving models. Implemented in C++ for scalability and optimized for deployment on Intel architectures, the model server uses the same architecture and API as TensorFlow Serving and KServe while applying OpenVINO for inference execution. Inference service is provided via gRPC or REST API, making deploying new algorithms and AI experiments easy.
Awesome-Interpretability-in-Large-Language-Models
This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.
20 - OpenAI Gpts
Music
Your go-to assistant for all things music, encompassing theory, creativity, and technology, and spanning from history to the future.
Galactic Librarian
Enthusiastic sci-fi book guide, helps find sci-fi books & avoid spoilers.
Linguist Librarian
I translate books into various languages, focusing on specific chapters.
Harvard Quick Citations
This tool is only useful if you have added new sources to your reference list and need to ensure that your in-text citations reflect these updates. Paste your essay below to get started.
Manga Concierge
A manga expert providing personalized recommendations what you want to read now.
OpenIndex.ai
Chat with all the knowledge, documents and collections contributed to the OpenIndex search engine.
Business Analyst (SaaS)
Your supportive partner in SaaS sales strategy! Helps you find new leads, conducts research, and much more!
Seek
Personalized Product and Brand Discovery Assistant, with a focus on new-age Indian brands.