Best AI tools for< wine marketing manager >

**e-label.io** is a software platform that helps wineries create and manage electronic labels for their wines. The platform is designed to be easy to use, even for users with no prior experience with e-labeling. With e-label.io, wineries can quickly and easily create e-labels that comply with the EU Wine Labelling Regulation (2021/2117). The platform offers a variety of features to help wineries create and manage their e-labels, including: * **Upload nutritional information and ingredients:** Wineries can upload their lab results and choose the ingredients used in their wines. e-label.io will take care of the rest, generating an e-label that complies with the EU Wine Labelling Regulation. * **Create and download the E-Label:** Once the nutritional information and ingredients have been uploaded, wineries can create and download their e-label. The e-label can be downloaded in a variety of formats, including PDF, PNG, and JPG. * **Apply the QR code and lean back:** Wineries can incorporate the e-label/QR code into their wine labels, brochures, and sales displays to ensure compliance and safety. e-label.io is a valuable tool for wineries that want to comply with the EU Wine Labelling Regulation. The platform is easy to use, affordable, and provides wineries with the tools they need to create and manage their e-labels.

GrapeGPT is a personal sommelier in your pocket. It uses AI technology to understand your taste and suggest the best wine for your meal. Simply take a picture of your wine list and have a conversation with GrapeGPT. It will chat with you about the best wine for your meal. GrapeGPT has completely changed how people choose wine. It's like having a sommelier in your pocket!

Vinetribe is a personalized wine recommendation service that connects users with local wine shops and wine creators. The platform offers a curated selection of wines based on the user's preferences and provides information on each wine, including tasting notes, food pairings, and availability at local stores. Vinetribe aims to make wine more accessible and enjoyable for everyone, regardless of their level of wine knowledge.

Sommify is an AI sommelier that helps companies sell wine through memorable experiences. It solves the problem of customers not knowing which wine to choose by providing them with personalized recommendations based on their needs. Sommify's AI is built on 20+ years of wine expertise and has been trained on 60k wines and 1.5mil recipes. It can automate wine pairing, generate data to help customers make purchase decisions, and help customers find the right wine for their needs. Sommify is trusted by Tesco and other technological pioneers in the industry. Its solution has been shown to increase the average bottle cost added to cart by 50% during pilots. 95% of the 1k+ people interviewed in the Netherlands, US, and UK would like Sommify's solutions to be a part of their purchase experience.

Menu Mystic is a web-based tool that helps users understand restaurant menus. It uses AI and image recognition to scan and interpret dishes, providing comprehensive explanations, wine pairings, and dessert recommendations. The tool is free to use, with paid plans offering additional features like unlimited scans and personalized recommendations.

LafTools is a privacy-first, self-hosted, fully open source toolbox designed for programmers. It offers a wide range of tools, including code generation, translation, encryption, compression, data analysis, and more. LafTools is highly integrated with a productive UI and supports full GPT-alike functionality. It is available as Docker images and portable edition, with desktop edition support planned for the future.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

AIDE is a machine learning code generation agent that can generate solutions for machine learning tasks from natural language descriptions. It has the following features: 1. **Instruct with Natural Language**: Describe your problem or additional requirements and expert insights, all in natural language. 2. **Deliver Solution in Source Code**: AIDE will generate Python scripts for the **tested** machine learning pipeline. Enjoy full transparency, reproducibility, and the freedom to further improve the source code! 3. **Iterative Optimization**: AIDE iteratively runs, debugs, evaluates, and improves the ML code, all by itself. 4. **Visualization**: We also provide tools to visualize the solution tree produced by AIDE for a better understanding of its experimentation process. This gives you insights not only about what works but also what doesn't. AIDE has been benchmarked on over 60 Kaggle data science competitions and has demonstrated impressive performance, surpassing 50% of Kaggle participants on average. It is particularly well-suited for tasks that require complex data preprocessing, feature engineering, and model selection.

A chat interface using open source models, eg OpenAssistant or Llama. It is a SvelteKit app and it powers the HuggingChat app on hf.co/chat.

llamafile is a tool that enables users to distribute and run Large Language Models (LLMs) with a single file. It combines llama.cpp with Cosmopolitan Libc to create a framework that simplifies the complexity of LLMs into a single-file executable called a 'llamafile'. Users can run these executable files locally on most computers without the need for installation, making open LLMs more accessible to developers and end users. llamafile also provides example llamafiles for various LLM models, allowing users to try out different LLMs locally. The tool supports multiple CPU microarchitectures, CPU architectures, and operating systems, making it versatile and easy to use.

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

Sparrow is an innovative open-source solution for efficient data extraction and processing from various documents and images. It seamlessly handles forms, invoices, receipts, and other unstructured data sources. Sparrow stands out with its modular architecture, offering independent services and pipelines all optimized for robust performance. One of the critical functionalities of Sparrow - pluggable architecture. You can easily integrate and run data extraction pipelines using tools and frameworks like LlamaIndex, Haystack, or Unstructured. Sparrow enables local LLM data extraction pipelines through Ollama or Apple MLX. With Sparrow solution you get API, which helps to process and transform your data into structured output, ready to be integrated with custom workflows. Sparrow Agents - with Sparrow you can build independent LLM agents, and use API to invoke them from your system. **List of available agents:** * **llamaindex** - RAG pipeline with LlamaIndex for PDF processing * **vllamaindex** - RAG pipeline with LLamaIndex multimodal for image processing * **vprocessor** - RAG pipeline with OCR and LlamaIndex for image processing * **haystack** - RAG pipeline with Haystack for PDF processing * **fcall** - Function call pipeline * **unstructured-light** - RAG pipeline with Unstructured and LangChain, supports PDF and image processing * **unstructured** - RAG pipeline with Weaviate vector DB query, Unstructured and LangChain, supports PDF and image processing * **instructor** - RAG pipeline with Unstructured and Instructor libraries, supports PDF and image processing. Works great for JSON response generation

This repository contains code for building cooperative embodied agents modularly with large language models. The agents are trained to perform tasks in two different environments: ThreeDWorld Multi-Agent Transport (TDW-MAT) and Communicative Watch-And-Help (C-WAH). TDW-MAT is a multi-agent environment where agents must transport objects to a goal position using containers. C-WAH is an extension of the Watch-And-Help challenge, which enables agents to send messages to each other. The code in this repository can be used to train agents to perform tasks in both of these environments.

PyLLMCore is a light-weighted interface with Large Language Models with native support for llama.cpp, OpenAI API, and Azure deployments. It offers a Pythonic API that is simple to use, with structures provided by the standard library dataclasses module. The high-level API includes the assistants module for easy swapping between models. PyLLMCore supports various models including those compatible with llama.cpp, OpenAI, and Azure APIs. It covers use cases such as parsing, summarizing, question answering, hallucinations reduction, context size management, and tokenizing. The tool allows users to interact with language models for tasks like parsing text, summarizing content, answering questions, reducing hallucinations, managing context size, and tokenizing text.

Wine, food, and music pairing connoisseur.

MBTI 성격 유형에 맞는 와인추천 게임을 리딩하고 평가하는 게임 진행자

Comprehensive, personalized wine advice

Argentine wine expert for technical discussions.

Approachable sommelier for wine-food pairing & education

A cultured, French-themed GPT with a flair for wine and leisurely breaks.

Expert in French wines featuring detailed profiles, ideal food pairings, insightful reviews, and the rich history of France's winemaking regions, from Bordeaux to Champagne. Powered by Breebs (www.breebs.com)

提供我照片讓我為你搭配適合的酒款或是餐點，輸入區域我將為你找到購買地方

Expert in pairing a wide range of alcoholic beverages with foods.

stunspot's Fermentation Expert - beer, mead, kimchi, pickles, everything!

Culinary guide for meal and drink choices

Cheese expert; playful tone; finds cheese sources

AI Steak Chef: Personalized Cooking Advice, Perfect Steaks, Recipes, and Pairings

Friendly culinary guide with a dash of Spanish humor, now with dish illustrations.

Assistant cook with a science twist.

All Food Is Ethnic Food: A Tyler Cowen Inspired Dining Guide by Josh Knox