Best AI tools for< Create Requirements >

PaceAI is an AI assistant designed for IT professionals to generate, analyze, and simplify software documentation on IT projects. It uses advanced generative AI models to understand the user's vision, analyze requirements, and automatically generate clear, concise software documentation tailored to the project's needs. With 35+ powerful AI tools, PaceAI assists in every phase of the project, from planning to deployment.

Spellmint is an AI-powered team planning tool that revolutionizes the way teams collaborate and plan. It offers cutting-edge planning tools for decision-making, product planning, marketing strategy, growth planning, design articulation, technical documentation, financial planning, legal planning, and HR processes. With Spellmint, users can streamline their planning processes, generate actionable insights, and create comprehensive plans with ease and efficiency.

The website offers a range of products related to product management, design sprint frameworks, and integrations like ChatGPT Product Co-Pilot for Slack. It provides resources and tools for product managers and teams to enhance their product development process. Users can find templates, frameworks, and integrations to streamline their product management workflow and improve collaboration.

ChatPRD is an AI Copilot for Product Work that helps product managers, VPs, founders, and teams without product managers to create great product requirements documents efficiently. It acts as an AI Chief Product Officer, providing feedback, coaching, and generating PRDs from simple ideas. The tool aims to save time, improve productivity, and enhance the quality of product management work.

Delibr is a document-writing solution with generative AI baked in. Through interviewing and coaching over 500 product leaders, we've learned what's important and used it to train our AI. Delibr offers a range of AI-enhanced product templates, including PRDs, user personas, and strategy documents. Each template is designed to help you create high-quality documents that stand out. Delibr also includes an AI Copilot assistant that can review your documents, suggest impactful changes, and offer insights on comments. With Delibr, you can save time writing requirements, organize your ideas, and track your progress. Delibr is trusted by product teams around the world, including Storytel, Nectarine Health, RunaHR, and DecisionLink.

BotGPT is a 24/7 custom AI chatbot assistant for websites. It offers a data-driven ChatGPT that allows users to create virtual assistants from their own data. Users can easily upload files or crawl their website to start asking questions and deploy a custom chatbot on their website within minutes. The platform provides a simple and efficient way to enhance customer engagement through AI-powered chatbots.

Userdoc is a software requirements management tool that uses AI to help teams gather, organize, and maintain their requirements. It offers a variety of features to help teams streamline the requirements process, including AI-powered scoping, detailed user story and acceptance criteria generation, persona management, user journey mapping, and integrations with popular project management tools. Userdoc is designed to help teams save time, improve communication, and build better software.

BetterWaifu is an AI tool that serves as an NSFW AI Generator and Imageboard. It is designed to create high-quality hentai images based on user preferences. The tool boasts of understanding user requirements accurately to generate desired content. BetterWaifu offers a range of features and functionalities to enhance the user experience in creating explicit content. The platform is committed to providing a safe and private environment for users to explore their creative desires.

Coverler is an AI-powered cover letter generator that helps job seekers create unique and tailored cover letters for every job application. With Coverler, you can simply provide your resume and the job description, and the AI will generate a cover letter that highlights your relevant skills and experience, and matches the specific requirements of the job you're applying for. Coverler's AI technology ensures that your cover letter is not only unique and relevant, but also error-free and well-written.

SlideAI is an AI-powered presentation generator that helps users create professional and engaging presentations in minutes. It utilizes advanced AI technology to generate unique content tailored to specific needs, saving time and effort. With SlideAI, users can automatically generate headings, bullet points, and search for relevant images to create compelling slides. The AI algorithms ensure that the generated content is unique and tailored specifically to the presentation topic and requirements. SlideAI leverages state-of-the-art generative models to produce high-quality content for PowerPoint presentations.

Ultimaps is an AI-powered map visualization tool designed for humans to create color-coded interactive maps in seconds. Users can import data from Excel, Google Spreadsheet, or Notion, or instruct the AI to build a map based on their requirements. The tool allows users to add drawings, change colors and fonts, and easily download, share, or embed the maps. Ultimaps offers features like automatic color-coding based on imported data, customization options, auto-saving of visualizations, and the ability to create interactive maps without any coding. It is a user-friendly platform suitable for various mapping needs.

Docuopia is an AI-powered document assistant that helps teams write better documents, faster. With Docuopia, you can generate product requirements, help docs, and wikis in minutes, using AI technology. Docuopia also offers real-time collaboration, version control, and personalized optimization, making it the perfect tool for teams of all sizes.

Onfido is a digital identity verification provider that helps businesses verify the identities of their customers online. It offers a range of products and services, including document verification, biometric verification, data verification, and fraud detection. Onfido's solutions are used by businesses in a variety of industries, including financial services, gaming, healthcare, and retail.

AiPassportPhotos is an AI-backed online photo tool that allows users to create biometric photos for passports, visas, IDs, driver's licenses, and more with ease and convenience. The tool leverages AI technology to generate compliant photos quickly, saving time and money for individuals and businesses. Users can upload their photos, crop them to the required size, and receive a printable template for various document types. AiPassportPhotos ensures 100% acceptance of photos by intelligently examining them, making it a cost-effective and efficient solution for all photo needs.

Viggle AI is a cutting-edge platform that allows users to effortlessly transform text into stunning 3D character animations. Powered by advanced JST-1 technology, this tool bridges the gap between professionals and hobbyists, offering a user-friendly interface for creating high-quality animations. With features like physics-based realism, community support, and a Discord server for collaboration, Viggle AI revolutionizes the animation creation process. Users can access the platform instantly via the web, join the vibrant creator community, and leverage the Viggle Bot for streamlined animation workflows.

WriteMyPrd is an AI tool designed to make writing Product Requirements Documents (PRDs) easier and faster. It utilizes ChatGPT Olvy 3.0 to speed up feedback analysis by 10x, helping users get started with writing their PRDs efficiently. The tool assists in providing basic information and features a user-friendly interface for defining requirements and collecting user feedback.

MetaGPT is an advanced AI tool that leverages the power of natural language processing to generate human-like text. It uses the latest deep learning models to understand and produce text in various styles and tones. With MetaGPT, users can easily create content for articles, essays, emails, and more with just a few clicks. The tool is designed to assist writers, marketers, students, and anyone looking to enhance their writing productivity and creativity.

TeamCreate AI is an AI tool that allows users to build their dream AI team in minutes. It offers AI co-workers that can be customized for various roles in Sales, Marketing, Finance, Product, Support, Operations, and more. Users can assign tasks, connect AI workers to 200+ apps and tools, and communicate via Slack and email. TeamCreate AI aims to help businesses scale rapidly without financial constraints and time-consuming recruitment processes.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Jobed is an AI-powered job description generator that helps users create tailored job descriptions quickly and efficiently. By leveraging artificial intelligence technology, Jobed streamlines the process of crafting job postings for various industries and job categories. Users can simply input their requirements and preferences, and Jobed will generate a comprehensive job description that meets their needs. With Jobed, businesses and recruiters can save time and effort in creating job listings, ensuring that they attract the right candidates for the position.

horde-engine is a wrapper around ComfyUI designed to run inference pipelines visually designed in the ComfyUI GUI. It enables users to design inference pipelines in ComfyUI and then call them programmatically, maintaining compatibility with the existing horde implementation. The library provides features for processing Horde payloads, initializing the library, downloading and validating models, and generating images based on input data. It also includes custom nodes for preprocessing and tasks such as face restoration and QR code generation. The project depends on various open source projects and bundles some dependencies within the library itself. Users can design ComfyUI pipelines, convert them to the backend format, and run them using the run_image_pipeline() method in hordelib.comfy.Comfy(). The project is actively developed and tested using git, tox, and a specific model directory structure.

This repository showcases how to build a simple LLM-based chatbot for answering questions based on documents using retrieval augmented generation (RAG) technique. It also provides guidance on deploying the chatbot using Podman or on the OpenShift Container Platform. The workshop associated with this repository introduces participants to LLMs & RAG concepts and demonstrates how to customize the chatbot for specific purposes. The software stack relies on open-source tools like streamlit, LlamaIndex, and local open LLMs via Ollama, making it accessible for GPU-constrained environments.

MLE-Agent is an intelligent companion designed for machine learning engineers and researchers. It features autonomous baseline creation, integration with Arxiv and Papers with Code, smart debugging, file system organization, comprehensive tools integration, and an interactive CLI chat interface for seamless AI engineering and research workflows.

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

This repository provides a tool to create an AI chatbot clone of yourself using your WhatsApp chats as training data. It utilizes the Torchtune library for finetuning and inference. The code includes preprocessing of WhatsApp chats, finetuning models, and chatting with the AI clone via a command-line interface. Supported models are Llama3-8B-Instruct and Mistral-7B-Instruct-v0.2. Hardware requirements include approximately 16 GB vRAM for QLoRa Llama3 finetuning with a 4k context length. The repository addresses common issues like adjusting parameters for training and preprocessing non-English chats.

LangStream is a tool for natural language processing tasks, providing a CLI for easy installation and usage. Users can try sample applications like Chat Completions and create their own applications using the developer documentation. It supports running on Kubernetes for production-ready deployment, with support for various Kubernetes distributions and external components like Apache Kafka or Apache Pulsar cluster. Users can deploy LangStream locally using minikube and manage the cluster with mini-langstream. Development requirements include Docker, Java 17, Git, Python 3.11+, and PIP, with the option to test local code changes using mini-langstream.

WordLlama is a fast, lightweight NLP toolkit optimized for CPU hardware. It recycles components from large language models to create efficient word representations. It offers features like Matryoshka Representations, low resource requirements, binarization, and numpy-only inference. The tool is suitable for tasks like semantic matching, fuzzy deduplication, ranking, and clustering, making it a good option for NLP-lite tasks and exploratory analysis.

This repository contains the official codebase for Bittensor Subnet 1 (SN1) v1.0.0+, released on 22nd January 2024. It defines an incentive mechanism to create a distributed conversational AI for Subnet 1. Validators and miners are based on large language models (LLM) using internet-scale datasets and goal-driven behavior to drive human-like conversations. The repository requires python3.9 or higher and provides compute requirements for running validators and miners. Users can run miners or validators using specific commands and are encouraged to run on the testnet before deploying on the main network. The repository also highlights limitations and provides resources for understanding the architecture and methodology of SN1.

This project provides a proof of concept for deploying a scalable, serverless LLM Generative AI inference engine on AWS Lambda. It leverages the llama.cpp project to enable the usage of more accessible CPU and RAM configurations instead of limited and expensive GPU capabilities. By deploying a container with the llama.cpp converted models onto AWS Lambda, this project offers the advantages of scale, minimizing cost, and maximizing compute availability. The project includes AWS CDK code to create and deploy a Lambda function leveraging your model of choice, with a FastAPI frontend accessible from a Lambda URL. It is important to note that you will need ggml quantized versions of your model and model sizes under 6GB, as your inference RAM requirements cannot exceed 9GB or your Lambda function will fail.

RecAI is a project that explores the integration of Large Language Models (LLMs) into recommender systems, addressing the challenges of interactivity, explainability, and controllability. It aims to bridge the gap between general-purpose LLMs and domain-specific recommender systems, providing a holistic perspective on the practical requirements of LLM4Rec. The project investigates various techniques, including Recommender AI agents, selective knowledge injection, fine-tuning language models, evaluation, and LLMs as model explainers, to create more sophisticated, interactive, and user-centric recommender systems.

**RVC_CLI: Retrieval-based Voice Conversion Command Line Interface** This command-line interface (CLI) provides a comprehensive set of tools for voice conversion, enabling you to modify the pitch, timbre, and other characteristics of audio recordings. It leverages advanced machine learning models to achieve realistic and high-quality voice conversions. **Key Features:** * **Inference:** Convert the pitch and timbre of audio in real-time or process audio files in batch mode. * **TTS Inference:** Synthesize speech from text using a variety of voices and apply voice conversion techniques. * **Training:** Train custom voice conversion models to meet specific requirements. * **Model Management:** Extract, blend, and analyze models to fine-tune and optimize performance. * **Audio Analysis:** Inspect audio files to gain insights into their characteristics. * **API:** Integrate the CLI's functionality into your own applications or workflows. **Applications:** The RVC_CLI finds applications in various domains, including: * **Music Production:** Create unique vocal effects, harmonies, and backing vocals. * **Voiceovers:** Generate voiceovers with different accents, emotions, and styles. * **Audio Editing:** Enhance or modify audio recordings for podcasts, audiobooks, and other content. * **Research and Development:** Explore and advance the field of voice conversion technology. **For Jobs:** * Audio Engineer * Music Producer * Voiceover Artist * Audio Editor * Machine Learning Engineer **AI Keywords:** * Voice Conversion * Pitch Shifting * Timbre Modification * Machine Learning * Audio Processing **For Tasks:** * Convert Pitch * Change Timbre * Synthesize Speech * Train Model * Analyze Audio

Aimeos Base abstraction layer is a tool designed to provide a solid foundation for building e-commerce applications. It offers a comprehensive set of functionalities and features that simplify the development process and enhance the performance of online stores. The abstraction layer abstracts common e-commerce functionalities, such as product management, order processing, and customer management, allowing developers to focus on business logic implementation rather than low-level technical details. With a strong emphasis on modularity and extensibility, Aimeos Base enables developers to create scalable and customizable e-commerce solutions that meet specific business requirements. The tool is well-documented and actively maintained by the Aimeos community, ensuring reliability and continuous improvement.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=