Best AI tools for< Motivation Boosting >

CraveCoach.AI is an AI-powered coaching platform designed to help individuals overcome porn addiction. The platform offers a 90-day program led by an AI coach named Coach Chad, who assists users in breaking harmful habits, boosting confidence, and improving relationships. Through personalized trigger analysis, practical trigger management checklists, empathetic relapse support, daily motivational reminders, and progress streak tracking, CraveCoach.AI aims to support users in their journey towards a healthier, addiction-free lifestyle. The platform emphasizes privacy, structured support processes, and tailored guidance for each user's pace and needs.

Spellpage is an AI-powered to-do list application designed to help users manage their tasks efficiently. Users can write down their tasks and get personal AI assistants to assist them in achieving their goals. The application offers features such as task automation, personalized assistance, motivation, and coaching. Spellpage aims to simplify task management by automating workflows and providing personalized support to users. It is created with love and expertise by the developers Daniel and Irakli.

Gita GPT is the world's first AI-powered spiritual and astrology platform inspired by the wisdom of Bhagavad Gita. It serves as a digital gateway to spiritual knowledge, offering personalized astrology, daily horoscopes, and spiritual companionship. Users can engage in meaningful conversations with AI gurus, access ancient wisdom in a modern context, and receive multilingual support 24/7. The platform aims to boost motivation, enhance time management skills, and deepen work commitment by providing spiritual guidance and insights. Gita GPT is a unique blend of technology and spirituality, designed to support individuals on their spiritual journey.

The website is a minimalist platform that simply displays the word 'Success'. It appears to be a single-page website with no additional content or functionality. The site's purpose seems to be to convey a positive message or concept of success through its simplicity and directness.

Inspiro is an AI-powered tool that helps users find inspirational quotes and generate their own personalized quotes using artificial intelligence technology. The website offers a user-friendly interface where users can easily access a wide range of motivational quotes or create unique quotes tailored to their preferences. With the power of AI, Inspiro provides a seamless experience for those seeking inspiration and motivation in their daily lives.

BurnBacon is an AI-powered fitness and nutrition coaching platform that provides personalized guidance and support to help users achieve their health goals. The platform offers a range of features, including personalized meal and workout plans, AI coaches that provide motivation and support, and evidence-based health insights. BurnBacon is designed to help users get in shape, lose weight, and improve their overall health and well-being.

Tidalflow is an AI-powered personal trainer application that offers personalized workout routines based on individual preferences and performance. It provides expert feedback, tracks progress, and ensures correct exercise form to help users achieve their fitness goals. The app is available 24/7, anywhere, and adapts to users' lifestyles to maintain motivation and consistency. Tidalflow aims to revolutionize the fitness industry by combining AI technology with fitness expertise to deliver tailored workout experiences.

Persado is a leading provider of Generative AI (GenAI) solutions for marketing and customer engagement. Its Motivation AI platform leverages advanced AI, deep learning models, and a vast knowledge base of marketing communications to generate personalized language that motivates customers to engage and act. Persado's AI-powered solutions have been proven to drive significant revenue growth and conversion rate improvements for its customers across various industries, including retail, financial services, travel, and telecommunications.

Speak is a language learning app that focuses on improving speaking skills through interaction with an advanced AI language tutor. The app provides personalized curriculum, on-the-go conversational practice, and motivation to help users achieve fluency quickly. With a 4.8 rating and over 5 million downloads, Speak offers a versatile and interactive platform for language learners of all levels.

FAT2FIT is an AI application that helps users visualize their body transformation using advanced AI technology. The platform allows users to see their future body transformation through AI-assisted visualization, providing motivation and guidance to reach their fitness goals. With over 6,587 AI body transformation photos already created, users can generate their own transformation photos and track their progress. FAT2FIT aims to help individuals become the best version of themselves by leveraging the power of AI technology.

Tinder Glowup is an AI application that uses artificial intelligence to generate pictures of users with abs, providing a quick and easy way to visualize a transformed physique without the need for extensive gym workouts. Users can upload their photos, and the AI model processes them to create custom abs pictures, which are then deleted from the servers after delivery. The application offers a one-time payment pricing plan and ensures secure financial transactions through Stripe. With features like generating 20+ abs pictures, using them as motivation for the gym, and enhancing one's dating profile on platforms like Tinder and Hinge, Tinder Glowup aims to help users improve their appearance and confidence effortlessly.

Endurance is a platform designed for runners, swimmers, and cyclists to engage in group training activities with friends or local communities. Users can create or join teams, share structured workouts, and benefit from collective motivation and accountability. The platform aims to make training fun and effective by leveraging the power of group workouts and social connections.

Offthreadr is an AI-powered course platform designed to enhance the learning experience for users on the go. It offers a unique approach to course completion by enabling users to interact with course content, chat for clarification, and receive motivation from a supportive community. With Offthreadr, users can access short course snippets, get instant answers to their questions through AI, and enjoy offthreaded learning to boost their learning outcomes.

BuildWithMuta is an AI tool designed to assist real estate professionals in various tasks. It offers specialized bots such as Real Estate Writer Bot, Motivation Bot, and Invoice Bot to streamline processes and enhance productivity. With advanced AI algorithms, BuildWithMuta provides accurate and efficient solutions tailored to the real estate industry's specific needs.

Teacher AI is a language practice tool that provides personalized speaking practice without the anxiety of interacting with a real person. It is available 24/7 for a fraction of the cost of a human teacher. Teacher AI corrects mistakes, explains grammar, and gets to know the user's learning style. It also tracks progress and provides motivation. Teacher AI is not suitable for complete beginners looking for structured lessons.

Yakkr Growth is an AI-powered platform designed to help streamers grow their online presence effortlessly. The platform automates time-consuming tasks such as creating engaging social media content, optimizing stream titles, generating event ideas, and recommending hashtags. It also offers features like a Growth Dashboard, consultancy calls, mentorship, and a collaborative community to support streamers in achieving their goals. Yakkr Growth aims to save time, boost motivation, and help streamers grow their audience and income by leveraging AI technology.

Storywizard.ai is an AI-powered platform that helps students create and refine their own fully illustrated and editable stories in any of eight languages. It also provides teachers with tools to create and track customized reading and writing assignments. Storywizard.ai is designed to help students improve their literacy skills, engage with fun and educational exercises, and increase their motivation to learn.

STOREE.AI is an AI-powered platform that empowers retail teams with actionable insights and AI agents, serving as trusted extensions in the digital realm. It offers sophisticated AI agents that analyze sales data, inventory levels, and track goal progression to provide tailored insights and motivation for sales teams. The platform integrates unique leadership styles and expertise into decision-making processes, enabling retailers to refine strategies and make relationship-driven decisions.

ChatShitGPT is an AI-powered chatbot application that offers a unique and entertaining experience by allowing users to interact with different personalities such as Pirate, the main guy, and ANGRY. Users can get roasted by AI responses generated by GPT technology, providing a fun and engaging way to chat. The application aims to provide entertainment, motivation, and humor to users through AI-generated conversations. With a user-friendly interface, ChatShitGPT brings a new frontier of entertainment right to your pocket.

AIChat is an AI-powered chatbot that allows users to have conversations, generate images, and access information through text messages. It is designed to be easy to use, with no apps to download or passwords to remember. Users can customize their bot's personality, tone, and response style, and the bot can remember previous conversations. AIChat can be used for a variety of purposes, including companionship, motivation, unbiased advice, health and wellness support, bedtime stories, and life hacks.

Llama-github is a powerful tool that helps retrieve relevant code snippets, issues, and repository information from GitHub based on queries. It empowers AI agents and developers to solve coding tasks efficiently. With features like intelligent GitHub retrieval, repository pool caching, LLM-powered question analysis, and comprehensive context generation, llama-github excels at providing valuable knowledge context for development needs. It supports asynchronous processing, flexible LLM integration, robust authentication options, and logging/error handling for smooth operations and troubleshooting. The vision is to seamlessly integrate with GitHub for AI-driven development solutions, while the roadmap focuses on empowering LLMs to automatically resolve complex coding tasks.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

LLMLingua is a tool that utilizes a compact, well-trained language model to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models, achieving up to 20x compression with minimal performance loss. The tool includes LLMLingua, LongLLMLingua, and LLMLingua-2, each offering different levels of prompt compression and performance improvements for tasks involving large language models.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Recent LLM (Large Language Models)-based CV and multi-modal works.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

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) ::=