Best AI tools for< Create Recipes >

UnrealMeal.ai is a revolutionary AI-powered platform that transforms the culinary experience. Our cutting-edge technology empowers users to create mouthwatering dishes with ease, explore a vast recipe library, and receive personalized recommendations based on their preferences. With UnrealMeal.ai, home cooks and professional chefs alike can unlock their culinary potential and embark on a delightful gastronomic journey.

Let's Foodie is the ultimate resource for foodies across the globe. It provides a free AI recipe generator that can turn any list of ingredients into a recipe instantly. The website also features a variety of articles on cooking techniques, methods, FAQs, and ingredients. Users can search for anything foodie-related using the search box. The website also includes a section on top comparisons, where users can compare different ingredients, dishes, and cooking methods.

MealsAI is an AI-powered recipe generator that helps users create delicious and unique meals with just a few clicks. With MealsAI, users can specify their dietary restrictions, ingredients on hand, and desired cooking time, and the AI will generate a personalized recipe that meets their needs. MealsAI also offers a variety of pre-made recipes that users can browse and share. Whether you're a beginner cook or a seasoned chef, MealsAI can help you create amazing meals that everyone will enjoy.

Shapemate is a WhatsApp chatbot that helps users with their health and fitness goals. It can track workouts, calories, and body fat percentage, and generate recipes and workouts. Shapemate is an all-in-one solution for nutrition and fitness, and it's available 24/7.

Flavorish is an AI-powered cooking assistant that helps users create delicious meals with ease. It offers a range of features to simplify the cooking process, including AI-powered recipe generation, smart shopping lists, recipe storage, and offline mode. With Flavorish, users can save time, reduce food waste, and explore new cuisines with confidence.

Reel2Recipe is an AI-powered tool that helps you create recipes from videos. Simply upload a video of your favorite dish, and Reel2Recipe will generate a step-by-step recipe for you. You can also search for recipes by ingredient, cuisine, or dietary restriction.

MealsAI is an AI-powered platform that allows users to create, share, and discover delicious recipes effortlessly. By leveraging the power of AI, users can generate unique recipes tailored to their dietary restrictions and ingredient availability. The platform eliminates the need for traditional cookbooks and provides endless possibilities for meal creation. MealsAI aims to simplify the cooking process and inspire culinary creativity through innovative recipe generation.

ScanMyKitchen is an AI-powered application designed to help users create delicious meals using ingredients from their fridge. The app offers a variety of traditional and AI-powered recipe suggestions, customizable filters based on diet preferences, and alternative recipes for flexibility. Users can also utilize the camera scanning feature to scan ingredients and access recipe text or video tutorials. The mission of ScanMyKitchen is to inspire users to cook delicious meals, reduce food waste, save money, and benefit the planet. The app aims to simplify the cooking process and provide a seamless experience for users without the need for sign-ups.

Recipeasy is an AI-powered recipe generator that helps users create easy and delicious meals. The website offers a Recipe Builder where users can input what they are making, for how many people, and dietary preferences such as vegan, vegetarian, gluten-free, dairy-free, nut-free, and kosher. The AI algorithm then generates a customized recipe based on the inputs provided. Recipeasy is designed to simplify the cooking process and provide users with quick and tasty meal ideas. The platform is user-friendly and suitable for both experienced cooks and beginners.

Crumb is an AI food generator application that helps users create unique and delicious recipes by transforming their available ingredients. Users can simply dictate their ingredients to the AI tool, which then generates recipes to inspire everyday cooking and reduce food waste. With a variety of recipe ideas and tips available on the blog, Crumb aims to make cooking more creative and convenient for users.

TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. It enables a data & learning flywheel for LLMs by unifying inference, observability, optimization, and experimentation. The platform includes a high-performance model gateway, structured schema-based inference, observability, experimentation, and data warehouse for analytics. TensorZero Recipes optimize prompts and models, and the platform supports experimentation features and GitOps orchestration for deployment.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects. * These are built using LanceDB, a free, open-source, serverless vectorDB that **requires no setup**. * It **integrates into python data ecosystem** so you can simply start using these in your existing data pipelines in pandas, arrow, pydantic etc. * LanceDB has **native Typescript SDK** using which you can **run vector search** in serverless functions! This repository is divided into 3 sections: - Examples - Get right into the code with minimal introduction, aimed at getting you from an idea to PoC within minutes! - Applications - Ready to use Python and web apps using applied LLMs, VectorDB and GenAI tools - Tutorials - A curated list of tutorials, blogs, Colabs and courses to get you started with GenAI in greater depth.

pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.

DataDreamer is a powerful open-source Python library designed for prompting, synthetic data generation, and training workflows. It is simple, efficient, and research-grade, allowing users to create prompting workflows, generate synthetic datasets, and train models with ease. The library is built for researchers, by researchers, focusing on correctness, best practices, and reproducibility. It offers features like aggressive caching, resumability, support for bleeding-edge techniques, and easy sharing of datasets and models. DataDreamer enables users to run multi-step prompting workflows, generate synthetic datasets for various tasks, and train models by aligning, fine-tuning, instruction-tuning, and distilling them using existing or synthetic data.

AI on OpenShift is a site providing installation recipes, patterns, and demos for AI/ML tools and applications used in Data Science and Data Engineering projects running on OpenShift. It serves as a comprehensive resource for developers looking to deploy AI solutions on the OpenShift platform.

The Vector Cookbook is a collection of recipes and sample application starter kits for building AI applications with LLMs using PostgreSQL and Timescale Vector. Timescale Vector enhances PostgreSQL for AI applications by enabling the storage of vector, relational, and time-series data with faster search, higher recall, and more efficient time-based filtering. The repository includes resources, sample applications like TSV Time Machine, and guides for creating, storing, and querying OpenAI embeddings with PostgreSQL and pgvector. Users can learn about Timescale Vector, explore performance benchmarks, and access Python client libraries and tutorials.

This repository provides resources, demos, and recipes for working with Large Language Models (LLMs) on OpenShift using OpenShift AI or Open Data Hub. It includes instructions for deploying inference servers for LLMs, such as vLLM, Hugging Face TGI, Caikit-TGIS-Serving, and Ollama. Additionally, it offers guidance on deploying serving runtimes, such as vLLM Serving Runtime and Hugging Face Text Generation Inference, in the Single-Model Serving stack of Open Data Hub or OpenShift AI. The repository also covers vector databases that can be used as a Vector Store for Retrieval Augmented Generation (RAG) applications, including Milvus, PostgreSQL+pgvector, and Redis. Furthermore, it provides examples of inference and application usage, such as Caikit, Langchain, Langflow, and UI examples.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

Mistral AI SDK for Kotlin Multiplatform (KMP) allows communication with Mistral API to get AI models, start a chat with the assistant, and create embeddings. The library is based on Mistral API documentation and built with Kotlin Multiplatform and Ktor client library. Sample projects like ZeChat showcase the capabilities of Mistral AI SDK. Users can interact with different Mistral AI models through ZeChat apps on Android, Desktop, and Web platforms. The library is not yet published on Maven, but users can fork the project and use it as a module dependency in their apps.

Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate Language Model Models (LLMs) and LLM applications. It brings Benchmarking and Red-Teaming together to assist AI developers, compliance teams, and AI system owners in assessing LLM performance. Moonshot can be accessed through various interfaces including User-friendly Web UI, Interactive Command Line Interface, and seamless integration into MLOps workflows via Library APIs or Web APIs. It offers features like benchmarking LLMs from popular model providers, running relevant tests, creating custom cookbooks and recipes, and automating Red Teaming to identify vulnerabilities in AI systems.

ScrapeGraphAI is a Python library that uses Large Language Models (LLMs) and direct graph logic to create web scraping pipelines for websites, documents, and XML files. It allows users to extract specific information from web pages by providing a prompt describing the desired data. ScrapeGraphAI supports various LLMs, including Ollama, OpenAI, Gemini, and Docker, enabling users to choose the most suitable model for their needs. The library provides a user-friendly interface through its `SmartScraper` class, which simplifies the process of building and executing scraping pipelines. ScrapeGraphAI is open-source and available on GitHub, with extensive documentation and examples to guide users. It is particularly useful for researchers and data scientists who need to extract structured data from web pages for analysis and exploration.

The fsdp_qlora repository provides a script for training Large Language Models (LLMs) with Quantized LoRA and Fully Sharded Data Parallelism (FSDP). It integrates FSDP+QLoRA into the Axolotl platform and offers installation instructions for dependencies like llama-recipes, fastcore, and PyTorch. Users can finetune Llama-2 70B on Dual 24GB GPUs using the provided command. The script supports various training options including full params fine-tuning, LoRA fine-tuning, custom LoRA fine-tuning, quantized LoRA fine-tuning, and more. It also discusses low memory loading, mixed precision training, and comparisons to existing trainers. The repository addresses limitations and provides examples for training with different configurations, including BnB QLoRA and HQQ QLoRA. Additionally, it offers SLURM training support and instructions for adding support for a new model.

This plugin extends and creates `a`/`i` textobjects in Neovim. It enhances some builtin textobjects (like `a(`, `a)`, `a'`, and more), creates new ones (like `a*`, `a`, `af`, `a?`, and more), and allows the user to create their own (like based on treesitter, and more). It supports dot-repeat, `v:count`, different search methods, consecutive application, and customization via Lua patterns or functions. It has builtins for brackets, quotes, function call, argument, tag, user prompt, and any punctuation/digit/whitespace character.

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.

This repository provides sample applications and tutorials to showcase the power of Amazon Bedrock with Python. It helps Python developers understand how to harness Amazon Bedrock in building generative AI-enabled applications. The resources also demonstrate integration with vector databases using RAG (Retrieval-augmented generation) and services like Amazon Aurora, RDS, and OpenSearch. Additionally, it explores using langchain and streamlit to create effective experimental applications.

Tools4AI is a Java-based Agentic Framework for building AI agents to integrate with enterprise Java applications. It enables the conversion of natural language prompts into actionable behaviors, streamlining user interactions with complex systems. By leveraging AI capabilities, it enhances productivity and innovation across diverse applications. The framework allows for seamless integration of AI with various systems, such as customer service applications, to interpret user requests, trigger actions, and streamline workflows. Prompt prediction anticipates user actions based on input prompts, enhancing user experience by proactively suggesting relevant actions or services based on context.

The ai-playground repository contains code from tutorials presented on the Code AI with Rok YouTube channel. It includes tutorials on using the OpenAI Assistants API v1 beta to build personal math tutors, customer support chatbots, and more. Additionally, there are tutorials on using Gemini Pro API, Snowflake Cortex LLM functions, LlamaIndex chat streaming app, Fetch.ai uAgents, Milvus Standalone, spaCy for NER, and more. The repository aims to provide practical examples and guides for developers interested in AI-related projects and tools.

LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings. The key features of LanceDB include: Production-scale vector search with no servers to manage. Store, query, and filter vectors, metadata, and multi-modal data (text, images, videos, point clouds, and more). Support for vector similarity search, full-text search, and SQL. Native Python and Javascript/Typescript support. Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index(*). Ecosystem integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB, and more on the way. LanceDB's core is written in Rust 🦀 and is built using Lance, an open-source columnar format designed for performant ML workloads.

Cocinero experto que presenta ingredientes en tablas y genera PDFs

Expert in BIGA and Neapolitan pizza dough recipes, focusing on tailored calculations and precise temperature data.

Bilingual chef expert in Portuguese cuisine and recipes.

Expert in crafting homebrew recipes, beer names, beer labels, troubleshooting and downloadable files for BrewFather.

Recipe creator with visual and nutritional insights.

Culinary creator, customizes recipes based on user needs.

Creative Chef for All of Earth's Foodly Delights

Allergy-friendly recipe creator

Futuristic culinary expert offering creative, practical recipes with final visual appeal.

A culinary expert in Indian cuisine and fusion dishes.

Culinary expert for recipe creation, meal planning, and cooking tips.

French cuisine inspired by renowned chefs, focusing on creative, high-quality recipes. 👨‍🍳

I create seasonal meal plans, adaptable to your requests.

Whole Food Plant Based Oil Free Chef

Your GBBO-inspired star baker

Advanced Doughnut Creativity - Doughnut.com

Generates delicious, dietetic recipes with a max of 600 calories per portion.

Expert cook and nutritionist, specializing in low carb recipes with beef.

As a high-class server, I describe dishes with luxury and elegance. Just upload your picture!

AI expert in boosting energy recipes

This GPT brings the vibrant flavors of Indian curry to your kitchen, offering insights into regional specialties, ingredient secrets, and step-by-step culinary guidance for both novice cooks and curry connoisseurs.

Bulk cooking-focused meal planner.

Mixology assistant focused on education and innovation.

Culinary Consultant for Chefs and Cooks, Offering Creative, Expert Advice.

Expert in crafting personalized low FODMAP recipes with representative images. Cross check all ingredients & low FODMAP servings.

A TikTok star creating healthy versions of comfort foods.

I generate creative vegan recipes based on your preferences.

Create JSON recipes for the MV1

A revolutionary food planning tool for sea voyages, ensuring balanced and diverse nutrition based on the length of the journey and the size of the crew.

I specialize in crafting custom cake designs, offering visual representations and tailored recipes according to individual tastes and preferences.

Transforms food photos into detailed recipes.

Elevate your culinary adventures with Salad GPT, your go-to source for crafting delicious and nutritious salads. Discover innovative salad recipes tailored to your preferences, inspiring healthier eating habits one tasty creation at a time.

Creates food recipes in the style of any chef, with tailored culinary tips, lists total nutrient content per serving

A friendly AI that helps create smoothie recipes based on your ingredients.

Develop recipes with a deep knowledge of food and culinary science, the art of gastronomy, as well as a sense of aesthetics.

World-class, intuitive meal planning