Best AI tools for< prepare project documentation >

The AI Assistant is a tool that helps business analysts and UI/UX designers to analyze text, and to generate mockup forms, SQL script and UML diagrams. It is designed to automate some part of analysts and UI/UX designers day-to-day work relating to text. The AI Assistant can extract information from natural language to build an information system, structure information by category and build project metadata in accordance with industry best practice, generate prototypes of visual project diagrams, database and business process diagrams, analyze of statement and requirements for completeness, and assist in the preparation of project documentation by automating the formation of standard texts.

BandoFacile is an AI-powered solution designed for companies and consultants to simplify the process of accessing facilitated finance. By leveraging artificial intelligence, BandoFacile streamlines the preparation of funding applications, saving time and money for users. The platform offers virtual assistance, automation of document compilation, personalized document generation, and human support to ensure high-quality results. With updated lists of available funding opportunities and the ability to receive completed documentation within 48 hours, BandoFacile aims to make the finance application process stress-free and efficient.

StudentAI.app is an AI-powered platform that provides students, graduates, and professionals with a comprehensive suite of tools and resources to enhance their academic and career journeys. With over 100 AI-powered tools, 24/7 access to AI tutors, and a dedicated team of experts, StudentAI.app empowers users to master homework, research, job searches, scholarship applications, mock interviews, essay writing, and much more. The platform is designed to be user-friendly and accessible, with a focus on providing personalized support and guidance to help users achieve their goals.

timeOS is an AI productivity companion that captures and summarizes your day, organizes all relevant information within the right tool, and proactively surfaces the knowledge you need, when you need it. It leverages AI to bypass non-essential meetings, provides detailed reports of missed events, and offers automatic notes without a bot. The platform seamlessly integrates actionable insights into your workflow, syncs with various tools, and offers multilingual support for clear communication. With a security-first approach, timeOS ensures user-controlled data privacy and encrypted storage of meeting summaries.

Fellow is an AI-powered meeting management software that helps teams have more productive and effective meetings. It offers a range of features to help with meeting preparation, engagement, follow-up, and analysis. Fellow integrates with a variety of productivity tools and offers a variety of templates and resources to help teams get the most out of their meetings.

Supermanage AI is an AI-powered tool designed to streamline and enhance the 1-on-1 meeting experience for managers. It provides insightful snapshots by distilling information from public Slack channels, enabling managers to have more meaningful conversations with team members. The tool aims to improve team dynamics, engagement, and overall performance by offering valuable insights and support.

AI Interview Answers Generator is an innovative tool designed to assist individuals in acing their job interviews by providing real-time voice transcription, instant optimal solutions, and industry-specific knowledge base. The tool acts as a virtual copilot during interviews, ensuring users have access to relevant and up-to-date information to stand out among other candidates. With cutting-edge AI technology, users can confidently navigate through technical questions and showcase their skills effectively.

Coursera is an online learning platform that offers courses, specializations, and degrees from top universities and companies. It provides a wide range of subjects, including business, computer science, data science, and more. Coursera also offers a variety of tools and resources to help learners succeed, such as interactive exercises, quizzes, and discussion forums.

Tech Jobs London is a job board that connects talented individuals with top companies in London's tech industry. The platform provides job opportunities in a range of fields such as software development, data analysis, and network administration.

Everlaw is a cloud-native ediscovery software that transforms the approach to litigation and investigations with advanced technology. It simplifies complex legal work for law firms, corporations, and government agencies by providing powerful analytics, machine learning tools, and generative AI. Everlaw enables legal teams to focus on substantive work, capture near-instant insights in ediscovery data, and collaborate effectively for trial preparation. The software offers rapid release cycles, thoughtful design, and an exceptional user experience to empower users to do more than ever before.

Hiration is an advanced online resume builder and career platform powered by ChatGPT AI technology. It offers a range of tools to help users create professional resumes, cover letters, and optimize their LinkedIn profiles. With AI-powered resume review and interview preparation features, Hiration aims to revolutionize the job search process by providing tailored guidance and resources to showcase one's best self. Users can access a suite of services to enhance their job application materials and increase their chances of landing their dream job.

MasterInterview is your ultimate AI interview coach, designed to help you master job-specific interviews through interactive sessions. Backed by industry experts and powered by advanced GPT-4 technology, the platform offers personalized feedback, tailored interview questions, and virtual interview sessions with a fox avatar. With comprehensive feedback and revised answers, MasterInterview aims to assist candidates in landing their dream jobs effectively and efficiently.

Vopmo AI is an AI tool designed to help users master interview video pitches and increase their chances of getting hired. The platform offers services such as creating AI avatars for job interviews, video pitch creation, interview preparation, and post-response introductions. Users can mimic their future selves in job interviews through a simple, swift, and secure process. Vopmo AI guarantees satisfaction and offers unlimited revisions within a specified timeframe. The platform also provides helpful information on shipping, order processing, delivery, revisions, liability, and customer support.

Rezi is an AI-powered resume builder that helps users create professional resumes in minutes. It offers a range of features, including AI-powered content writing, keyword targeting, and real-time content analysis. Rezi also provides users with access to a library of resume templates and examples. The platform is trusted by over 2 million job seekers and has a 62.18% interview rate.

Accomplishments.ai is an AI-powered tool designed to assist individuals in crafting compelling employee comments for their annual performance reviews. By leveraging OpenAI GPT-3 Turbo technology, the tool generates personalized summaries of accomplishments based on user-provided information. Users can input their achievements, and the tool transforms them into impactful statements highlighting their contributions and achievements. Accomplishments.ai aims to simplify the process of self-promotion and help users effectively communicate their value to secure raises and promotions.

Saasguru is a comprehensive Salesforce skilling and certification platform that empowers individuals to launch or advance their Salesforce careers. It offers a wide range of learning resources, including live classes, mock exams, projects, and personalized mentorship, to help learners develop a strong foundation in Salesforce and prepare for certification exams. Saasguru also provides job readiness support, connecting learners with potential employers and providing interview preparation assistance.

Link is a Decision Intelligence platform that offers Agile Applied AI and Machine Learning solutions. The platform provides workshops on AI/ML/DI, Decision Intelligence Solutions, and Assured Agile AI Resources. Users can access live model galleries, blogs, news, and learn about Decision Intelligence Models. Link aims to help business leaders prepare for the AI paradigm shift by offering tools and resources for understanding and applying artificial intelligence effectively.

InboxChat is an AI-powered email management tool that helps users sort, chat, and summarize their emails. It integrates with Google Accounts and offers a range of features to streamline email workflow, including: - Chat with Your Inbox: Draft emails, summarize lengthy threads, and organize data in tables. - Automate your workflow: Create automations to organize incoming emails, extract important data, create tasks, and prepare automated responses. - Quick skim: See emails at a glance with concise, customizable summaries. - Thread Summary: Get to-the-point summaries of all email threads. - Email Summaries: Quickly skim through emails. - Contact History: Access a summarized timeline of interactions with each contact. - Smart Contact Groups: Auto-tag contacts into manageable groups.

Labellerr is a data labeling software that helps AI teams prepare high-quality labels 99 times faster for Vision, NLP, and LLM models. The platform offers automated annotation, advanced analytics, and smart QA to process millions of images and thousands of hours of videos in just a few weeks. Labellerr's powerful analytics provides full control over output quality and project management, making it a valuable tool for AI labeling partners.

Bloks is a personal assistant that helps you maximize every interaction. It gathers all the information you need to come prepared to meetings with zero effort, automatically transcribes and summarizes meetings, and identifies and organizes your action items. Bloks also has a ChatGPT-like relationship intelligence that gives you detailed meeting insights and relationship progress summaries.

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.

The 100 Days in AI repository provides a comprehensive roadmap for individuals to learn Artificial Intelligence over a period of 100 days. It covers topics ranging from basic programming in Python to advanced concepts in AI, including machine learning, deep learning, and specialized AI topics. The repository includes daily tasks, resources, and exercises to ensure a structured learning experience. By following this roadmap, users can gain a solid understanding of AI and be prepared to work on real-world AI projects.

Translate texts in manga/images. Some manga/images will never be translated, therefore this project is born. * Image/Manga Translator * Samples * Online Demo * Disclaimer * Installation * Pip/venv * Poetry * Additional instructions for **Windows** * Docker * Hosting the web server * Using as CLI * Setting Translation Secrets * Using with Nvidia GPU * Building locally * Usage * Batch mode (default) * Demo mode * Web Mode * Api Mode * Related Projects * Docs * Recommended Modules * Tips to improve translation quality * Options * Language Code Reference * Translators Reference * GPT Config Reference * Using Gimp for rendering * Api Documentation * Synchronous mode * Asynchronous mode * Manual translation * Next steps * Support Us * Thanks To All Our Contributors :

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

Sycamore is a conversational search and analytics platform for complex unstructured data, such as documents, presentations, transcripts, embedded tables, and internal knowledge repositories. It retrieves and synthesizes high-quality answers through bringing AI to data preparation, indexing, and retrieval. Sycamore makes it easy to prepare unstructured data for search and analytics, providing a toolkit for data cleaning, information extraction, enrichment, summarization, and generation of vector embeddings that encapsulate the semantics of data. Sycamore uses your choice of generative AI models to make these operations simple and effective, and it enables quick experimentation and iteration. Additionally, Sycamore uses OpenSearch for indexing, enabling hybrid (vector + keyword) search, retrieval-augmented generation (RAG) pipelining, filtering, analytical functions, conversational memory, and other features to improve information retrieval.

MediaAI is a repository containing lectures and materials for Aalto University's AI for Media, Art & Design course. The course is a hands-on, project-based crash course focusing on deep learning and AI techniques for artists and designers. It covers common AI algorithms & tools, their applications in art, media, and design, and provides hands-on practice in designing, implementing, and using these tools. The course includes lectures, exercises, and a final project based on students' interests. Students can complete the course without programming by creatively utilizing existing tools like ChatGPT and DALL-E. The course emphasizes collaboration, peer-to-peer tutoring, and project-based learning. It covers topics such as text generation, image generation, optimization, and game AI.

Uni-MoE is a MoE-based unified multimodal model that can handle diverse modalities including audio, speech, image, text, and video. The project focuses on scaling Unified Multimodal LLMs with a Mixture of Experts framework. It offers enhanced functionality for training across multiple nodes and GPUs, as well as parallel processing at both the expert and modality levels. The model architecture involves three training stages: building connectors for multimodal understanding, developing modality-specific experts, and incorporating multiple trained experts into LLMs using the LoRA technique on mixed multimodal data. The tool provides instructions for installation, weights organization, inference, training, and evaluation on various datasets.

llmc is an off-the-shell tool designed for compressing LLM, leveraging state-of-the-art compression algorithms to enhance efficiency and reduce model size without compromising performance. It provides users with the ability to quantize LLMs, choose from various compression algorithms, export transformed models for further optimization, and directly infer compressed models with a shallow memory footprint. The tool supports a range of model types and quantization algorithms, with ongoing development to include pruning techniques. Users can design their configurations for quantization and evaluation, with documentation and examples planned for future updates. llmc is a valuable resource for researchers working on post-training quantization of large language models.

FarmVibes.AI is a repository focused on developing multi-modal geospatial machine learning models for agriculture and sustainability. It enables users to fuse various geospatial and spatiotemporal datasets, such as satellite imagery, drone imagery, and weather data, to generate robust insights for agriculture-related problems. The repository provides fusion workflows, data preparation tools, model training notebooks, and an inference engine to facilitate the creation of geospatial models tailored for agriculture and farming. Users can interact with the tools via a local cluster, REST API, or a Python client, and the repository includes documentation and notebook examples to guide users in utilizing FarmVibes.AI for tasks like harvest date detection, climate impact estimation, micro climate prediction, and crop identification.

NekoImageGallery is an online AI image search engine that utilizes the Clip model and Qdrant vector database. It supports keyword search and similar image search. The tool generates 768-dimensional vectors for each image using the Clip model, supports OCR text search using PaddleOCR, and efficiently searches vectors using the Qdrant vector database. Users can deploy the tool locally or via Docker, with options for metadata storage using Qdrant database or local file storage. The tool provides API documentation through FastAPI's built-in Swagger UI and can be used for tasks like image search, text extraction, and vector search.

Lhotse is a Python library designed to make speech and audio data preparation flexible and accessible. It aims to attract a wider community to speech processing tasks by providing a Python-centric design and an expressive command-line interface. Lhotse offers standard data preparation recipes, PyTorch Dataset classes for speech tasks, and efficient data preparation for model training with audio cuts. It supports data augmentation, feature extraction, and feature-space cut mixing. The tool extends Kaldi's data preparation recipes with seamless PyTorch integration, human-readable text manifests, and convenient Python classes.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

llama_cpp.rb provides Ruby bindings for the llama.cpp, a library that allows you to use the Llama language model in your Ruby applications. Llama is a large language model that can be used for a variety of natural language processing tasks, such as text generation, translation, and question answering. This gem is still under development and may undergo many changes in the future.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

Ragtacts is a Clojure library that allows users to easily interact with Large Language Models (LLMs) such as OpenAI's GPT-4. Users can ask questions to LLMs, create question templates, call Clojure functions in natural language, and utilize vector databases for more accurate answers. Ragtacts also supports RAG (Retrieval-Augmented Generation) method for enhancing LLM output by incorporating external data. Users can use Ragtacts as a CLI tool, API server, or through a RAG Playground for interactive querying.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

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