AI tools for ai dating
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AI Dating Coach
AI Dating Coach is an AI-powered application designed to help individuals improve their dating skills and success on dating apps. It offers personalized coaching, practice conversations, and gamified learning to enhance communication skills and boost confidence in the dating world. The application combines data-driven insights with gamification elements to provide tailored advice, strategies, and real-time feedback to users. With features like smart recommendations, profile analysis, and app-specific strategies, AI Dating Coach aims to transform users' dating experiences through AI-powered coaching and chat simulations.

Blush
Blush is an AI-powered dating simulator that helps users learn and practice relationship skills in a safe and fun environment. It offers a judgment-free space to refine relationship skills, engage with different personalities, practice communication skills, and receive personalized guidance. Users can experiment with different approaches to flirting and communication, gain a better understanding of relationships, and explore their desires safely. Blush allows users to meet potential matches with unique personalities and relationship styles, providing emotional support and companionship. The application aims to empower users to navigate real-world relationship dynamics with confidence and authenticity.

Dippy
Dippy is an AI-powered chatbot app that provides users with personalized AI companions. Users can choose from a variety of AI companions, each with their own unique personality and interests. Dippy can be used for a variety of purposes, including companionship, therapy, and dating. The app is available for download on the App Store.

LoveGenius Sidekick
LoveGenius Sidekick is an AI-powered dating assistant designed to help you craft captivating pickup lines, generate witty replies, optimize your dating profile, and provide engaging questions to spark meaningful conversations. With Sidekick, you can elevate your dating game, increase your chances of getting matches, and land more dates.

Wingman
Wingman is an AI dating coach application that offers personalized dating advice to straight men. It provides services such as chatbot coaching, profile optimization, and conversation feedback to help users improve their dating game and increase their chances of finding meaningful connections. Wingman prioritizes user privacy by ensuring all interactions are fully anonymized, and it continuously updates its memory bank to provide tailored advice. The application is currently in beta phase and offers complimentary access to invited users, with plans to introduce a free trial version upon official launch.

Iris Dating
Iris Dating is an AI dating application that leverages artificial intelligence to match and date online. The app uses AI to understand users' preferences and present them with matches based on mutual attraction. By decoding the science of attraction, Iris Dating aims to revolutionize online dating by providing users with more meaningful and successful relationships.

DirtyTalking.ai
DirtyTalking.ai is a premier platform dedicated to providing comprehensive reviews, insights, and guides on AI applications that specialize in seductive, engaging, and personalized adult conversations. The platform offers a safe, private, and customizable way to explore fantasies and enhance sexual wellness through engaging dialogue. Users can find expert reviews, top-rated apps, user guides, tips, and stay up-to-date with the latest news and trends in the dirty talk AI scene. DirtyTalking.ai represents a thrilling advancement in the world of adult conversation, offering a unique and innovative way to connect and communicate.

Charmr AI
Charmr is the ultimate AI texting assistant application designed to enhance user's dating experience. The application provides personalized pick-up lines and flirty messages based on user input, aiming to improve communication and interactions in the dating scene. Charmr AI ensures data security and functionality while offering a user-friendly interface for seamless user experience. With a commitment to safeguarding personal data and privacy, Charmr AI incorporates strict measures to protect user information. The application is governed by Terms and Conditions that outline user responsibilities, limitations, and rights, ensuring a transparent and secure environment for users.

DateGPT
Dein KI-basierter Dating-Berater für charmante Kommunikation und viele Matches (für Tinder, Bumble, WhatsApp, ... & mit deinem Schreibstil)

DateMate
Your friendly AI assistant for voice-based dating, offering personalized tips, safety advice, and fun interactions.

Chanakya GPT
From dating dilemmas to office strategies and financial finesse, let's solve it all with Chanakya's age-old wisdom sprinkled into today's dynamic world!

redcache-ai
RedCache-ai is a memory framework designed for Large Language Models and Agents. It provides a dynamic memory framework for developers to build various applications, from AI-powered dating apps to healthcare diagnostics platforms. Users can store, retrieve, search, update, and delete memories using RedCache-ai. The tool also supports integration with OpenAI for enhancing memories. RedCache-ai aims to expand its functionality by integrating with more LLM providers, adding support for AI Agents, and providing a hosted version.

ai-collective-tools
ai-collective-tools is an open-source community dedicated to creating a comprehensive collection of AI tools for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools and resources across various categories such as 3D, Agriculture, Art, Audio Editing, Avatars, Chatbots, Code Assistant, Cooking, Copywriting, Crypto, Customer Support, Dating, Design Assistant, Design Generator, Developer, E-Commerce, Education, Email Assistant, Experiments, Fashion, Finance, Fitness, Fun Tools, Gaming, General Writing, Gift Ideas, HealthCare, Human Resources, Image Classification, Image Editing, Image Generator, Interior Designing, Legal Assistant, Logo Generator, Low Code, Models, Music, Paraphraser, Personal Assistant, Presentations, Productivity, Prompt Generator, Psychology, Real Estate, Religion, Research, Resume, Sales, Search Engine, SEO, Shopping, Social Media, Spreadsheets, SQL, Startup Tools, Story Teller, Summarizer, Testing, Text to Speech, Text to Image, Transcriber, Travel, Video Editing, Video Generator, Weather, Writing Generator, and Other Resources.

collective-ai-tools
The 'collective-ai-tools' repository is an open-source community dedicated to curating a comprehensive collection of AI tools and resources for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools across various categories such as 3D modeling, app building, agriculture, art, audio editing, avatars, chatbots, code assistance, cooking, copywriting, crypto, customer support, dating, design assistance, design generation, developer tools, e-commerce, education, email assistance, experiments, fashion, finance, fitness, fun tools, gaming, general writing, gift ideas, healthcare, human resources, image classification, image editing, image generation, interior designing, legal assistance, logo generation, low code development, models, music, paraphrasing, personal assistance, presentations, productivity tools, prompt generation, psychology, real estate, religion, research, resume building, sales, search engine, SEO, shopping, social media, spreadsheets, SQL, startup tools, storytelling, summarization, testing, text-to-speech, text-to-image, transcription, travel, video editing, video generation, writing generation, weather, and other resources.

ai-collection
The ai-collection repository is a collection of various artificial intelligence projects and tools aimed at helping developers and researchers in the field of AI. It includes implementations of popular AI algorithms, datasets for training machine learning models, and resources for learning AI concepts. The repository serves as a valuable resource for anyone interested in exploring the applications of artificial intelligence in different domains.

Top-AI-Tools
Top AI Tools is a comprehensive, community-curated directory that aims to catalog and showcase the most outstanding AI-powered products. This index is not exhaustive, but rather a compilation of our research and contributions from the community.

Sanmill
Sanmill is a free, powerful UCI-like N men's morris program with CUI, Flutter GUI and Qt GUI. Nine men's morris is a strategy board game for two players dating at least to the Roman Empire. The game is also known as nine-man morris , mill , mills , the mill game , merels , merrills , merelles , marelles , morelles , and ninepenny marl in English.

awesome-ai-llm4education
The 'awesome-ai-llm4education' repository is a curated list of papers related to artificial intelligence (AI) and large language models (LLM) for education. It collects papers from top conferences, journals, and specialized domain-specific conferences, categorizing them based on specific tasks for better organization. The repository covers a wide range of topics including tutoring, personalized learning, assessment, material preparation, specific scenarios like computer science, language, math, and medicine, aided teaching, as well as datasets and benchmarks for educational research.

chatWeb
ChatWeb is a tool that can crawl web pages, extract text from PDF, DOCX, TXT files, and generate an embedded summary. It can answer questions based on text content using chatAPI and embeddingAPI based on GPT3.5. The tool calculates similarity scores between text vectors to generate summaries, performs nearest neighbor searches, and designs prompts to answer user questions. It aims to extract relevant content from text and provide accurate search results based on keywords. ChatWeb supports various modes, languages, and settings, including temperature control and PostgreSQL integration.

documentation
Vespa documentation is served using GitHub Project pages with Jekyll. To edit documentation, check out and work off the master branch in this repository. Documentation is written in HTML or Markdown. Use a single Jekyll template _layouts/default.html to add header, footer and layout. Install bundler, then $ bundle install $ bundle exec jekyll serve --incremental --drafts --trace to set up a local server at localhost:4000 to see the pages as they will look when served. If you get strange errors on bundle install try $ export PATH=“/usr/local/opt/[email protected]/bin:$PATH” $ export LDFLAGS=“-L/usr/local/opt/[email protected]/lib” $ export CPPFLAGS=“-I/usr/local/opt/[email protected]/include” $ export PKG_CONFIG_PATH=“/usr/local/opt/[email protected]/lib/pkgconfig” The output will highlight rendering/other problems when starting serving. Alternatively, use the docker image `jekyll/jekyll` to run the local server on Mac $ docker run -ti --rm --name doc \ --publish 4000:4000 -e JEKYLL_UID=$UID -v $(pwd):/srv/jekyll \ jekyll/jekyll jekyll serve or RHEL 8 $ podman run -it --rm --name doc -p 4000:4000 -e JEKYLL_ROOTLESS=true \ -v "$PWD":/srv/jekyll:Z docker.io/jekyll/jekyll jekyll serve The layout is written in denali.design, see _layouts/default.html for usage. Please do not add custom style sheets, as it is harder to maintain.

cognita
Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

Awesome-Segment-Anything
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.

happy-llm
Happy-LLM is a systematic learning tutorial for Large Language Models (LLM) that covers NLP research methods, LLM architecture, training process, and practical applications. It aims to help readers understand the principles and training processes of large language models. The tutorial delves into Transformer architecture, attention mechanisms, pre-training language models, building LLMs, training processes, and practical applications like RAG and Agent technologies. It is suitable for students, researchers, and LLM enthusiasts with programming experience, Python knowledge, and familiarity with deep learning and NLP concepts. The tutorial encourages hands-on practice and participation in LLM projects and competitions to deepen understanding and contribute to the open-source LLM community.

Awesome-LLM-Preference-Learning
The repository 'Awesome-LLM-Preference-Learning' is the official repository of a survey paper titled 'Towards a Unified View of Preference Learning for Large Language Models: A Survey'. It contains a curated list of papers related to preference learning for Large Language Models (LLMs). The repository covers various aspects of preference learning, including on-policy and off-policy methods, feedback mechanisms, reward models, algorithms, evaluation techniques, and more. The papers included in the repository explore different approaches to aligning LLMs with human preferences, improving mathematical reasoning in LLMs, enhancing code generation, and optimizing language model performance.