Best AI tools for< Provide Documentation >

Norby AI is a website chatbot that provides automated customer support 24/7. It is designed to be easy to use, with no setup or coding required. Simply copy and paste a snippet of code onto your website, and Norby will be up and running. Norby can answer questions about your products or services, provide documentation, and even handle FAQs. It is a great way for startups, personal brands, and small companies to automate their customer support and provide a better experience for their customers.

The pplx-api is an AI tool designed to provide documentation and examples for blazingly fast LLM inference. It offers a reference for developers to integrate AI capabilities into their applications efficiently. The tool focuses on enhancing natural language processing tasks by leveraging advanced models and algorithms. Users can access detailed guides, API references, changelogs, and engage in discussions related to AI technologies.

Blaze SQL AI is an AI Data Analytics chatbot and SQL generator that helps non-technical users and teams turn questions into data insights. It allows users to make their teams more informed and save time by using AI for Data Analysis on their SQL Database. Blaze SQL AI can write SQL code, run queries, visualize data, and provide database documentation. It is trusted by innovative teams and offers a private desktop version for secure data connections. The tool is designed to help users easily interact with their databases using natural language and generate complex SQL queries with the help of AI technology.

ExplainIt is an AI-powered chatbot that can be integrated with your documentation to provide interactive and accurate answers to users' questions. It is designed to enhance the customer experience by making documentation more accessible and engaging. With ExplainIt, you can create a ChatGPT-powered chatbot in seconds, without the need for any coding or technical expertise.

MedReport AI is an AI-powered healthcare solution that specializes in generating efficient medical reports for healthcare providers. The application utilizes advanced AI technology to transform existing notes into Medicare updates, progress notes, discharge summaries, referrals, and more instantly. It aims to streamline the reporting process, reduce documentation time, and improve efficiency in delivering patient care. MedReport AI is trusted by healthcare providers in Australia for its ability to cut administrative time significantly and provide accurate clinical documentation.

Mintlify is a modern documentation platform that helps businesses create beautiful, engaging, and user-friendly documentation. It is designed to be easy to use and maintain, and it offers a variety of features to help businesses improve their user engagement and conversions. Mintlify is used by a variety of companies, from fast-growing startups to large enterprises.

Augmedix is a leading provider of AI-powered medical documentation solutions for healthcare systems, physician practices, and hospitals. Its products, including Augmedix Go, Augmedix Live, Augmedix Go Assist, and Augmedix Prep, leverage ambient AI technology to convert natural clinician-patient conversations into structured medical notes in real time. Augmedix aims to enhance the clinician-patient relationship by reducing documentation burden, improving productivity, and increasing patient satisfaction.

AskMyDocs.ai is an AI tool designed to save time and money on customer and employee support by allowing users to ask questions and get precise, instant answers straight from their documentation sources. The tool offers various integrations with platforms like Zendesk, Gitbook, Sitemap, PDF, and Slack, enabling users to transform their knowledge base into an intelligent resource. AskMyDocs.ai provides features such as resource savings calculator, integrations with multiple platforms, and a chatbot for quick and precise responses. The tool offers different pricing plans catering to different business sizes and needs, with options for custom features and support SLAs.

Oncora Medical is a healthcare technology company that provides software and data solutions to oncologists and cancer centers. Their products are designed to improve patient care, reduce clinician burnout, and accelerate clinical discoveries. Oncora's flagship product, Oncora Patient Care, is a modern, intelligent user interface for oncologists that simplifies workflow, reduces documentation burden, and optimizes treatment decision making. Oncora Analytics is an adaptive visual and backend software platform for regulatory-grade real world data analytics. Oncora Registry is a platform to capture and report quality data, treatment data, and outcomes data in the oncology space.

Archbee is a full circle documentation platform that uses generative AI to provide instant answers from documentation. It allows teams to create, maintain, and host documentation efficiently. With features like Write Assist, Custom Blocks, and real-time collaboration, Archbee streamlines the documentation process and enhances team productivity. The platform offers customized templates for user-friendly experiences and seamless integration with GitHub for content management. Archbee enables users to publish, share, and secure knowledge on their domain, providing comprehensive support for user onboarding and developer queries.

SOAP Note AI is an AI-powered tool designed to generate HIPAA-compliant, fast, and efficient SOAP notes for various healthcare professions including Physical Therapy, Occupational Therapy, Nursing, Mental Health, SLP, Dentistry, Podiatry, Massage, Acupuncture, Chiropractic, Veterinary, and Pharmacy. The tool helps healthcare professionals convert shorthand notes, audio dictations, or AI Scribe session recordings into comprehensive SOAP notes in minutes, reducing daily documentation time. SOAP Note AI is loved by therapists, nurse practitioners, social workers, and other healthcare professionals for its accuracy, time-saving capabilities, and HIPAA compliance.

Zenbots is a Zendesk AI chatbot that provides dedicated Zendesk support with access to all of your Zendesk support articles. It is designed to speed up operations, assist agents, or even let customers solve problems on their own. Zenbots can be integrated into existing workflows with just a few clicks and can be set up in under 24 hours. It offers a free 7-day trial.

ChatWP is an AI chatbot designed to provide direct answers to WordPress-related questions. It is trained on official WordPress documentation to offer accurate and truthful responses. Users can interact with the chatbot to get help with various WordPress queries, ensuring a seamless support experience.

CodeAI is an advanced AI tool designed to optimize the development process for coders of all levels. It offers cutting-edge AI capabilities to enhance coding efficiency, provide real-time feedback, automate tasks like generating commit messages and updating changelogs, and boost productivity. CodeAI supports multiple programming languages and is suitable for individual developers, small teams, and professionals working on various projects.

The website offers a free VS Code extension that enhances the user experience with MUI (Material-UI) by providing in-IDE documentation, copilot assistance, and direct feedback features. Users can chat with the MUI documentation, get AI-driven responses, search and navigate documentation within the code editor, and provide feedback seamlessly. The extension aims to streamline the development process for MUI enthusiasts and improve overall productivity.

EntBot.ai is an AI-powered chatbot builder designed for websites, catering to enterprise applications by offering product guides and developer documentations. It provides exceptional response quality with over 95% accuracy in practice. The chatbot can reduce client wait times, achieve higher customer satisfaction, and offer 24/7 service coverage with fewer support staff. EntBot.ai empowers users to sell or assist customers, supports multilingual interactions, and integrates seamlessly with messaging apps and websites. It offers no-code integration capabilities with platforms like Discord and Slack, making it a versatile tool for businesses.

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Corti is an AI-powered platform that provides real-time decision support, automates documentation and coding, and improves the productivity of patient encounters. It is used by healthcare professionals to enhance the experience of both healthcare professionals and their patients.

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This repository serves as a platform for coordinating ecosystem-wide work related to free-threading topics in Python. It aims to track, understand, and provide documentation for common issues across multiple libraries. Specific project-related issues should be reported in the respective project's issue tracker. For detailed documentation on free-threading topics, visit py-free-threading.github.io.

Only Train Once (OTO) is an automatic, architecture-agnostic DNN training and compression framework that allows users to train a general DNN from scratch or a pretrained checkpoint to achieve high performance and slimmer architecture simultaneously in a one-shot manner without fine-tuning. The framework includes features for automatic structured pruning and erasing operators, as well as hybrid structured sparse optimizers for efficient model compression. OTO provides tools for pruning zero-invariant group partitioning, constructing pruned models, and visualizing pruning and erasing dependency graphs. It supports the HESSO optimizer and offers a sanity check for compliance testing on various DNNs. The repository also includes publications, installation instructions, quick start guides, and a roadmap for future enhancements and collaborations.

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

A collection of LLM services you can self host via docker or modal labs to support your applications development. The goal is to provide docker containers or modal labs deployments of common patterns when using LLMs and endpoints to integrate easily with existing codebases using the openai api. It supports GPT4all's embedding api, JSONFormer api for chat completion, Cross Encoders based on sentence transformers, and provides documentation using MkDocs.

Atomic Agents is a modular and extensible framework designed for creating powerful applications. It follows the principles of Atomic Design, emphasizing small and single-purpose components. Leveraging Pydantic for data validation and serialization, the framework offers a set of tools and agents that can be combined to build AI applications. It depends on the Instructor package and supports various APIs like OpenAI, Cohere, Anthropic, and Gemini. Atomic Agents is suitable for developers looking to create AI agents with a focus on modularity and flexibility.

ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.

API Improvement Proposals (AIPs) are design documents that provide high-level, concise documentation for API development at Google. The goal of AIPs is to serve as the source of truth for API-related documentation and to facilitate discussion and consensus among API teams. AIPs are similar to Python's enhancement proposals (PEPs) and are organized into different areas within Google to accommodate historical differences in customs, styles, and guidance.

The Hume AI Python SDK allows users to integrate Hume APIs directly into their Python applications. Users can access complete documentation, quickstart guides, and example notebooks to get started. The SDK is designed to provide support for Hume's expressive communication platform built on scientific research. Users are encouraged to create an account at beta.hume.ai and stay updated on changes through Discord. The SDK may undergo breaking changes to improve tooling and ensure reliable releases in the future.

Comflowyspace is an open-source AI image and video generation tool that aims to provide a more user-friendly and accessible experience than existing tools like SDWebUI and ComfyUI. It simplifies the installation, usage, and workflow management of AI image and video generation, making it easier for users to create and explore AI-generated content. Comflowyspace offers features such as one-click installation, workflow management, multi-tab functionality, workflow templates, and an improved user interface. It also provides tutorials and documentation to lower the learning curve for users. The tool is designed to make AI image and video generation more accessible and enjoyable for a wider range of users.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

BackgroundRemover is a command line tool to remove background from image and video using AI. It requires python >= 3.6, torch, torchvision, and ffmpeg. The tool can be installed via pip or Docker. It offers various options for image and video background removal, including alpha matting and different models. Users can also use it as a library to remove background from images. The project aims to enhance background removal capabilities, improve documentation, add new features like real-time background removal for videos, and provide the ability to use custom models.

PearAI is an AI-powered code editor designed to enhance development by reducing the amount of coding required. It is a fork of VSCode and the main functionality lies within the 'extension/pearai' submodule. Users can contribute to the project by fixing issues, submitting bugs and feature requests, reviewing source code changes, and improving documentation. The tool aims to streamline the coding process and provide an efficient environment for developers to work in.

BaseAI is an AI framework designed for creating declarative and composable AI-powered LLM products. It enables the development of AI agent pipes locally, incorporating agentic tools and memory (RAG). The framework offers a learn guide for beginners to kickstart their journey with BaseAI. For detailed documentation, users can visit baseai.dev/docs. Contributions to BaseAI are encouraged, and interested individuals can refer to the Contributing Guide. The original authors of BaseAI include Ahmad Awais, Ashar Irfan, Saqib Ameen, Saad Irfan, and Ahmad Bilal. Security vulnerabilities can be reported privately via email to [email protected]. BaseAI aims to provide resources for learning AI agent development, utilizing agentic tools and memory.

The llms-txt repository proposes a standardization on using an `/llms.txt` file to provide information to help large language models (LLMs) use a website at inference time. The `llms.txt` file is a markdown file that offers brief background information, guidance, and links to more detailed information in markdown files. It aims to provide concise and structured information for LLMs to access easily, helping users interact with websites via AI helpers. The repository also includes tools like a CLI and Python module for parsing `llms.txt` files and generating LLM context from them, along with a sample JavaScript implementation. The proposal suggests adding clean markdown versions of web pages alongside the original HTML pages to facilitate LLM readability and access to essential information.

DocsGPT is an open-source documentation assistant powered by GPT models. It simplifies the process of searching for information in project documentation by allowing developers to ask questions and receive accurate answers. With DocsGPT, users can say goodbye to manual searches and quickly find the information they need. The tool aims to revolutionize project documentation experiences and offers features like live previews, Discord community, guides, and contribution opportunities. It consists of a Flask app, Chrome extension, similarity search index creation script, and a frontend built with Vite and React. Users can quickly get started with DocsGPT by following the provided setup instructions and can contribute to its development by following the guidelines in the CONTRIBUTING.md file. The project follows a Code of Conduct to ensure a harassment-free community environment for all participants. DocsGPT is licensed under MIT and is built with LangChain.

DaoCloud Enterprise 5.0 Documentation provides detailed information on using DaoCloud, a Certified Kubernetes Service Provider. The documentation covers current and legacy versions, workflow control using GitOps, and instructions for opening a PR and previewing changes locally. It also includes naming conventions, writing tips, references, and acknowledgments to contributors. Users can find guidelines on writing, contributing, and translating pages, along with using tools like MkDocs, Docker, and Poetry for managing the documentation.

ExplainableAI.jl is a Julia package that implements interpretability methods for black-box classifiers, focusing on local explanations and attribution maps in input space. The package requires models to be differentiable with Zygote.jl. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Users can analyze and visualize explanations for model predictions, with support for different XAI methods and customization. The package aims to provide transparency and insights into model decision-making processes, making it a valuable tool for understanding and validating machine learning models.

Distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency. It helps you synthesize data and provide AI feedback to improve the quality of your AI models. With Distilabel, you can: * **Synthesize data:** Generate synthetic data to train your AI models. This can help you to overcome the challenges of data scarcity and bias. * **Provide AI feedback:** Get feedback from AI models on your data. This can help you to identify errors and improve the quality of your data. * **Improve your AI output quality:** By using Distilabel to synthesize data and provide AI feedback, you can improve the quality of your AI models and get better results.

LearnHouse is an open-source platform that allows anyone to easily provide world-class educational content. It supports various content types, including dynamic pages, videos, and documents. The platform is still in early development and should not be used in production environments. However, it offers several features, such as dynamic Notion-like pages, ease of use, multi-organization support, support for uploading videos and documents, course collections, user management, quizzes, course progress tracking, and an AI-powered assistant for teachers and students. LearnHouse is built using various open-source projects, including Next.js, TailwindCSS, Radix UI, Tiptap, FastAPI, YJS, PostgreSQL, LangChain, and React.

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This prompt acts as an expert in AI and a specific field, designing educational and attractive manuals for a defined audience. He specializes in integrating advanced knowledge and NLP techniques to generate high-quality content.

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