Best AI tools for< Build Off Base >
20 - AI tool Sites
Voice AI Note
Voice AI Note is a web-based application that allows users to quickly and easily create voice notes using advanced AI. With Voice AI Note, you can create voice notes that are fluent, accurate, and sound natural. The application is easy to use and requires no prior experience with AI or voice recording. Simply enter the text you want to convert to speech, and Voice AI Note will do the rest.
Kapa.ai
Kapa.ai is an AI documentation assistant that provides instant AI answers to technical questions. It turns knowledge bases into reliable AI assistants powered by large language models, helping organizations improve user experience by eliminating response waiting time and identifying documentation gaps. The platform offers off-the-shelf integrations, feedback loop for improved answers, and automatic updates to stay current with changes in documentation.
Tremello
Tremello is a market research platform that uses AI to deliver off-market data. It combines a leading AI engine with human experts to provide bespoke intelligence delivered directly to the user's inbox. Tremello's AI analyzes relationships, identifies patterns, and considers the broader context, delivering meaningful and actionable insights on top of a base human layer. It leverages a diverse range of data sources, including public and private databases, industry reports, social media archives, company websites, and government filings, ensuring a complete and comprehensive picture of the research subject.
Athena Intelligence
Athena Intelligence is an AI-native analytics platform and artificial employee designed to accelerate analytics workflows by offering enterprise teams co-pilot and auto-pilot modes. Athena learns your workflow as a co-pilot, allowing you to hand over controls to her for autonomous execution with confidence. With Athena, everyone in your enterprise has access to a data analyst, and she doesn't take days off. Simple integration to your Enterprise Data Warehouse Chat with Athena to query data, generate visualizations, analyze enterprise data and codify workflows. Athena's AI learns from existing documentation, data and analyses, allowing teams to focus on creating new insights. Athena as a platform can be used collaboratively with co-workers or Athena, with over 100 users in the same report or whiteboard environment concurrently making edits. From simple queries and visualizations to complex industry specific workflows, Athena enables you with SQL and Python-based execution environments.
Facet
Facet is a cutting-edge generative imagery tool that helps creative professionals focus on what matters. It provides creative assistance without trading off artistic control. Facet helps overcome time and resource constraints that prevent trying out ideas. It offers an intuitive image generation experience with more than just text prompts, including image references, automatic prompt variations, and even custom models trained on the user's exact aesthetic. Facet allows users to train a custom model using their own images in minutes, generating endless assets in their exact vision. Users can add image references to any prompt, instantly getting images that adhere to their subject or style. Facet provides a collaborative canvas for users to riff with teammates and build off of each other's prompts and ideas.
Clerkie
Clerkie is a powerful debt repayment and optimization platform that offers a full-service automation solution powered by machine learning and human expertise. It helps lenders, both big and small, to manage and optimize their loan portfolios efficiently. With features like smart payment experience, AI-driven repayment strategies, real-time reporting, and easy integration, Clerkie ensures a seamless and secure experience for lenders and borrowers alike.
Luma Dream Machine
Luma Dream Machine is an AI video generator tool that creates high-quality, realistic videos from text and images. It is a scalable and efficient transformer model trained directly on videos, capable of generating physically accurate and eventful shots. The tool aims to build a universal imagination engine, enabling users to bring their creative visions to life effortlessly.
Datumbox
Datumbox is a machine learning platform that offers a powerful open-source Machine Learning Framework written in Java. It provides a large collection of algorithms, models, statistical tests, and tools to power up intelligent applications. The platform enables developers to build smart software and services quickly using its REST Machine Learning API. Datumbox API offers off-the-shelf Classifiers and Natural Language Processing services for applications like Sentiment Analysis, Topic Classification, Language Detection, and more. It simplifies the process of designing and training Machine Learning models, making it easy for developers to create innovative applications.
Rize
Rize is an AI productivity coach that uses time tracking to improve your focus and build better work habits. It analyzes your activity to advise you in real-time on when to focus, when to take breaks, and when you're getting off track. Rize provides you with the tools to deepen your ability to focus, including app & website blocking, focus music, a more flexible Pomodoro timer, and in-depth, personalized metrics. It also helps you build better work habits by alerting you at the ideal time to take a break and offering screen-blocking features to ensure these breaks are truly effective.
prOFphet
prOFphet is an AI chatbot designed specifically for OnlyFans creators. It helps creators automate their messaging, build relationships with fans, and increase their earnings. prOFphet uses natural language processing to generate messages that sound like they come from the creator, so fans feel like they are having a real conversation. The chatbot also remembers conversations, so creators can pick up where they left off without missing a beat. prOFphet is easy to use and integrates seamlessly with OnlyFans. Creators can simply connect their OnlyFans account to prOFphet and start using the chatbot right away.
Prisms
Prisms is a no-code platform for building AI-powered apps. It allows users to harness the power of AI without having to write any code. Prisms is built on top of Large Language models including GPT3, DALL-E, and Stable Diffusion. Users can connect the pieces in Prisms to stack together data sources, user inputs, and off-the-shelf building blocks to create their own AI-powered apps. Prisms also makes it easy to deploy AI-powered apps directly from the platform with its pre-built UI. Alternatively, users can build their own frontend and use Prisms as a backend for their AI logic.
Macgence AI Training Data Services
Macgence is an AI training data services platform that offers high-quality off-the-shelf structured training data for organizations to build effective AI systems at scale. They provide services such as custom data sourcing, data annotation, data validation, content moderation, and localization. Macgence combines global linguistic, cultural, and technological expertise to create high-quality datasets for AI models, enabling faster time-to-market across the entire model value chain. With more than 5 years of experience, they support and scale AI initiatives of leading global innovators by designing custom data collection programs. Macgence specializes in handling AI training data for text, speech, image, and video data, offering cognitive annotation services to unlock the potential of unstructured textual data.
GEES
GEES is an all-in-one AI design platform that revolutionizes the design process by offering a comprehensive suite of tools for brainstorming, designing, and hand-off in one file. With GEES AI Assistant, users can generate components and drafts effortlessly, handle diverse design tasks, and elevate workflow efficiency. The platform allows for customized workflows by integrating AI blocks, enabling users to build innovative workflows step by step. GEES supports various design file formats, ensures data security with robust features, and offers a seamless experience from planning to handoff.
DeepScribe
DeepScribe is an AI medical scribe application that leverages advanced speech recognition technology to capture clinical conversations with extreme accuracy. It empowers clinicians and health systems with real-time AI insights, offers customization options to match provider workflows, and ensures trust and safety through features that promote AI transparency. DeepScribe is designed to save time, improve accuracy, drive adoption, and maximize revenue for doctors, hospitals, and health systems. The application is built for enterprise use, allowing users to unlock the power of AI and modernize their patient data strategy.
Unified DevOps platform to build AI applications
This is a unified DevOps platform to build AI applications. It provides a comprehensive set of tools and services to help developers build, deploy, and manage AI applications. The platform includes a variety of features such as a code editor, a debugger, a profiler, and a deployment manager. It also provides access to a variety of AI services, such as natural language processing, machine learning, and computer vision.
Build Chatbot
Build Chatbot is a no-code chatbot builder designed to simplify the process of creating chatbots. It enables users to build their chatbot without any coding knowledge, auto-train it with personalized content, and get the chatbot ready with an engaging UI. The platform offers various features to enhance user engagement, provide personalized responses, and streamline communication with website visitors. Build Chatbot aims to save time for both businesses and customers by making information easily accessible and transforming visitors into satisfied customers.
What should I build next?
The website 'What should I build next?' is a platform designed to help developers generate random development project ideas. It serves as an ultimate resource for developers seeking inspiration for their next project. Users can pick components or randomize to create unique project ideas. The platform offers free credits to active users daily and encourages user engagement. With a user-friendly interface, the website aims to support developers in overcoming creative blocks and kickstarting new projects.
Google Cloud
Google Cloud is a suite of cloud computing services that runs on the same infrastructure as Google. Its services include computing, storage, networking, databases, machine learning, and more. Google Cloud is designed to make it easy for businesses to develop and deploy applications in the cloud. It offers a variety of tools and services to help businesses with everything from building and deploying applications to managing their infrastructure. Google Cloud is also committed to sustainability, and it has a number of programs in place to reduce its environmental impact.
Bubble
Bubble is a no-code application development platform that allows users to build and deploy web and mobile applications without writing any code. It provides a visual interface for designing and developing applications, and it includes a library of pre-built components and templates that can be used to accelerate development. Bubble is suitable for a wide range of users, from beginners with no coding experience to experienced developers who want to build applications quickly and easily.
Gemini
Gemini is a large and powerful AI model developed by Google. It is designed to handle a wide variety of text and image reasoning tasks, and it can be used to build a variety of AI-powered applications. Gemini is available in three sizes: Ultra, Pro, and Nano. Ultra is the most capable model, but it is also the most expensive. Pro is the best performing model for a wide variety of tasks, and it is a good value for the price. Nano is the most efficient model, and it is designed for on-device use cases.
20 - Open Source AI Tools
ainneve
Ainneve is an example game for Evennia, created by the Evennia community as a base for learning and building off of. It is currently in early development stages and undergoing major refactoring. The game provides a starting point for users to explore game systems and world settings, with extensive documentation available. Installation is straightforward, with pre-configured settings and clear instructions for setting up and starting the server. The project welcomes contributions and offers opportunities for users to get involved by checking open issues and joining the community Discord channel. Ainneve is licensed under the BSD license.
skyvern
Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern
chatgpt-universe
ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher
redbox
Redbox is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License. Security measures are in place to ensure user data privacy and considerations are being made to make the core-api secure.
universal
The Universal Numbers Library is a header-only C++ template library designed for universal number arithmetic, offering alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. It tailors arithmetic types to the application's precision and dynamic range, enabling improved application performance and energy efficiency. The library provides fast implementations of special IEEE-754 formats like quarter precision, half-precision, and quad precision, as well as vendor-specific extensions. It supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval, and adaptive-precision integers, rationals, and floats. The library is suitable for AI, DSP, HPC, and HFT algorithms.
llmware
LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.
CGraph
CGraph is a cross-platform **D** irected **A** cyclic **G** raph framework based on pure C++ without any 3rd-party dependencies. You, with it, can **build your own operators simply, and describe any running schedules** as you need, such as dependence, parallelling, aggregation and so on. Some useful tools and plugins are also provide to improve your project. Tutorials and contact information are show as follows. Please **get in touch with us for free** if you need more about this repository.
searchGPT
searchGPT is an open-source project that aims to build a search engine based on Large Language Model (LLM) technology to provide natural language answers. It supports web search with real-time results, file content search, and semantic search from sources like the Internet. The tool integrates LLM technologies such as OpenAI and GooseAI, and offers an easy-to-use frontend user interface. The project is designed to provide grounded answers by referencing real-time factual information, addressing the limitations of LLM's training data. Contributions, especially from frontend developers, are welcome under the MIT License.
curate-gpt
CurateGPT is a prototype web application and framework for performing general purpose AI-guided curation and curation-related operations over collections of objects. It allows users to load JSON, YAML, or CSV data, build vector database indexes for ontologies, and interact with various data sources like GitHub, Google Drives, Google Sheets, and more. The tool supports ontology curation, knowledge base querying, term autocompletion, and all-by-all comparisons for objects in a collection.
intel-extension-for-tensorflow
Intel® Extension for TensorFlow* is a high performance deep learning extension plugin based on TensorFlow PluggableDevice interface. It aims to accelerate AI workloads by allowing users to plug Intel CPU or GPU devices into TensorFlow on-demand, exposing the computing power inside Intel's hardware. The extension provides XPU specific implementation, kernels & operators, graph optimizer, device runtime, XPU configuration management, XPU backend selection, and options for turning on/off advanced features.
promptflow
**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
AIlice
AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.
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.
h2ogpt
h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.
eidolon
Eidolon is an open-source agent services framework that helps developers design and deploy agent-based services. It simplifies agent deployment, facilitates agent-to-agent communication, and enables painless component customization and upgrades. Eidolon's modular architecture allows developers to easily swap out components, such as language models, reinforcement learning implementations, tools, and more. This flexibility minimizes vendor lock-in and reduces the effort required to upgrade agent components. As the AI landscape rapidly evolves, Eidolon empowers developers to adapt their agents to meet changing requirements.
quick-start-connectors
Cohere's Build-Your-Own-Connector framework allows integration of Cohere's Command LLM via the Chat API endpoint to any datastore/software holding text information with a search endpoint. Enables user queries grounded in proprietary information. Use-cases include question/answering, knowledge working, comms summary, and research. Repository provides code for popular datastores and a template connector. Requires Python 3.11+ and Poetry. Connectors can be built and deployed using Docker. Environment variables set authorization values. Pre-commits for linting. Connectors tailored to integrate with Cohere's Chat API for creating chatbots. Connectors return documents as JSON objects for Cohere's API to generate answers with citations.
aiohttp-client-cache
aiohttp-client-cache is an asynchronous persistent cache for aiohttp client requests, based on requests-cache. It is easy to use, customizable, and persistent, with several storage backends available, including SQLite, DynamoDB, MongoDB, DragonflyDB, and Redis.
langroid-examples
Langroid-examples is a repository containing examples of using the Langroid Multi-Agent Programming framework to build LLM applications. It provides a collection of scripts and instructions for setting up the environment, working with local LLMs, using OpenAI LLMs, and running various examples. The repository also includes optional setup instructions for integrating with Qdrant, Redis, Momento, GitHub, and Google Custom Search API. Users can explore different scenarios and functionalities of Langroid through the provided examples and documentation.
gpdb
Greenplum Database (GPDB) is an advanced, fully featured, open source data warehouse, based on PostgreSQL. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes.
LLMs-from-scratch
This repository contains the code for coding, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book Build a Large Language Model (From Scratch). In _Build a Large Language Model (From Scratch)_, you'll discover how LLMs work from the inside out. In this book, I'll guide you step by step through creating your own LLM, explaining each stage with clear text, diagrams, and examples. The method described in this book for training and developing your own small-but-functional model for educational purposes mirrors the approach used in creating large-scale foundational models such as those behind ChatGPT.
20 - OpenAI Gpts
Build a Brand
Unique custom images based on your input. Just type ideas and the brand image is created.
Beam Eye Tracker Extension Copilot
Build extensions using the Eyeware Beam eye tracking SDK
Business Model Canvas Strategist
Business Model Canvas Creator - Build and evaluate your business model
League Champion Builder GPT
Build your own League of Legends Style Champion with Abilities, Back Story and Splash Art
RenovaTecno
Your tech buddy helping you refurbish or build a PC from scratch, tailored to your needs, budget, and language.
Gradle Expert
Your expert in Gradle build configuration, offering clear, practical advice.
XRPL GPT
Build on the XRP Ledger with assistance from this GPT trained on extensive documentation and code samples.