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.

Code Genius is an AI code generator designed to enhance developers' coding experience by offering real-time code analysis, intelligent suggestions, and code improvements. It can generate unit tests, provide clear code documentation, and streamline workflow. The tool aims to optimize code, save time, and improve efficiency for developers worldwide.

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.

TolyGPT is an AI-powered chatbot that is designed to read an entire codebase and generate documentation. It is specifically trained on the Solana validator codebase, allowing users to ask questions about how the validator works. The core of TolyGPT is open source as Autodoc, and it is powered by the GPT-3.5 model. Users can apply to have TolyGPT work on their own codebase and stay updated by following Sam Hogan.

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.

SOAP Note AI is an AI-powered tool designed to generate HIPAA-compliant, fast, and efficient SOAP notes and progress notes for various healthcare specialties such as Telehealth, 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, AI Scribe session recordings, or telehealth sessions into comprehensive SOAP notes in minutes, reducing daily documentation time. SOAP Note AI is loved by healthcare professionals for its accuracy, time-saving capabilities, and reduction of errors in note-taking. The tool offers specialized SOAP notes for different healthcare professions, ensuring detailed and precise documentation. It also provides features like AI Scribe, Dictation, Telehealth integration, note history access, instant feedback, and various pricing plans to suit different needs.

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.

OpenSpace is an AI-powered reality intelligence platform that provides complete visual records of construction projects, enabling efficient project management. It uses Spatial AI technology to automate site capture and simplify documentation, helping teams save time, increase productivity, and reduce risks. With features like field notes, mobile app, and quick image mapping, OpenSpace streamlines workflows for QA/QC, RFIs, and punch lists. The platform offers clear visual proof of site conditions, reducing rework and insurance costs. OpenSpace is known for its reliability, speed, and power, making it a trusted solution for industry leaders in construction.

ChatWP is an AI chatbot designed to provide direct answers to WordPress-related questions. It is trained on official WordPress documentation to ensure accurate and truthful responses. Users can interact with the chatbot to get help with various WordPress queries, making it a valuable tool for website owners and developers.

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.

The website page displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::4wq5g-1718736845999-777f28b346ca) for reference. Users are advised to consult the documentation for further information and troubleshooting.

The website displays a '404: NOT_FOUND' error message indicating that the requested deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::lmmss-1741279839229-d64d8958cb1b'. Users are directed to refer to the documentation for further information and troubleshooting.

Popp is an AI-driven recruitment solution that revolutionizes talent acquisition by making hiring faster, fairer, and more human. The platform offers seamless integrations with leading ATS platforms, pre-trained AI assistants, and data-driven insights to streamline the recruitment process. Popp empowers recruiters to manage higher volumes of candidates while improving the candidate experience, all at a fraction of the cost. By automating pre-screening conversations and providing personalized AI assistance, Popp helps reduce time-to-hire, increase hiring efficiency, and enhance candidate satisfaction.

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.

Stagehand is an AI web browsing framework that simplifies and extends web automation using three simple APIs: act, extract, and observe. It aims to provide a lightweight, configurable framework without complex abstractions, allowing users to automate web tasks reliably. The tool generates Playwright code based on atomic instructions provided by the user, enabling natural language-driven web automation. Stagehand is open source, maintained by the Browserbase team, and supports different models and model providers for flexibility in automation tasks.

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.

Scrapling is a high-performance, intelligent web scraping library for Python that automatically adapts to website changes while significantly outperforming popular alternatives. For both beginners and experts, Scrapling provides powerful features while maintaining simplicity. It offers features like fast and stealthy HTTP requests, adaptive scraping with smart element tracking and flexible selection, high performance with lightning-fast speed and memory efficiency, and developer-friendly navigation API and rich text processing. It also includes advanced parsing features like smart navigation, content-based selection, handling structural changes, and finding similar elements. Scrapling is designed to handle anti-bot protections and website changes effectively, making it a versatile tool for web scraping tasks.

Kollektiv is a Retrieval-Augmented Generation (RAG) system designed to enable users to chat with their favorite documentation easily. It aims to provide LLMs with access to the most up-to-date knowledge, reducing inaccuracies and improving productivity. The system utilizes intelligent web crawling, advanced document processing, vector search, multi-query expansion, smart re-ranking, AI-powered responses, and dynamic system prompts. The technical stack includes Python/FastAPI for backend, Supabase, ChromaDB, and Redis for storage, OpenAI and Anthropic Claude 3.5 Sonnet for AI/ML, and Chainlit for UI. Kollektiv is licensed under a modified version of the Apache License 2.0, allowing free use for non-commercial purposes.

EOLE is an open language modeling toolkit based on PyTorch. It aims to provide a research-friendly approach with a comprehensive yet compact and modular codebase for experimenting with various types of language models. The toolkit includes features such as versatile training and inference, dynamic data transforms, comprehensive large language model support, advanced quantization, efficient finetuning, flexible inference, and tensor parallelism. EOLE is a work in progress with ongoing enhancements in configuration management, command line entry points, reproducible recipes, core API simplification, and plans for further simplification, refactoring, inference server development, additional recipes, documentation enhancement, test coverage improvement, logging enhancements, and broader model support.

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.

Ragpi is an open-source AI assistant that answers questions using your documentation, GitHub issues, and READMEs. It combines LLMs with intelligent search to provide relevant, documentation-backed answers through a simple API. It supports multiple providers like OpenAI, Ollama, and Deepseek, and has built-in integrations with Discord and Slack. Ragpi builds knowledge bases from docs, GitHub issues, and READMEs, with an agentic RAG system for dynamic document retrieval. It has an API-first design with Docker deployment.

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.

Codename Goose is an open-source, extensible AI agent designed to provide functionalities beyond code suggestions. Users can install, execute, edit, and test with any LLM. The tool aims to enhance the coding experience by offering advanced features and capabilities. Stay updated for the upcoming 1.0 release scheduled by the end of January 2025. Explore the v0.X documentation available on the project's GitHub pages.

Describer is a tool that analyzes codebases using AI to generate architectural overviews, documentation, explanations, bug reports, and more. It scans all files in a directory and uses Google's Gemini AI to provide insights such as markdown architectural overviews, codebase summaries, code pattern analysis, codebase structure documentation, bug identification, and test idea generation. The tool respects .gitignore rules by default but allows users to include/exclude specific files or patterns for analysis.

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

Supavec is an open-source tool that serves as an alternative to Carbon.ai. It allows users to build powerful RAG applications using any data source and at any scale. The tool is designed to provide a simple API endpoint for easy integration and usage. Supavec is built with Next.js, Supabase, Tailwind CSS, Bun, and Upstash, offering a robust and flexible solution for application development. Users can refer to the API documentation for detailed information on how to utilize the tool effectively.

LMCache is a serving engine extension designed to reduce time to first token (TTFT) and increase throughput, particularly in long-context scenarios. It stores key-value caches of reusable texts across different locations like GPU, CPU DRAM, and Local Disk, allowing the reuse of any text in any serving engine instance. By combining LMCache with vLLM, significant delay savings and GPU cycle reduction are achieved in various large language model (LLM) use cases, such as multi-round question answering and retrieval-augmented generation (RAG). LMCache provides integration with the latest vLLM version, offering both online serving and offline inference capabilities. It supports sharing key-value caches across multiple vLLM instances and aims to provide stable support for non-prefix key-value caches along with user and developer documentation.

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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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