An In-depth Exploration of h2oGPTe

This comprehensive learning path takes you from foundational concepts to advanced applications of H2O GPTe, guided by industry experts Andreea Turcu, Greg Fousas, Laurene De Peyrelongue and Audrey Létévé. Learn how to: ▷ Implement AI-powered search and enterprise solutions ▷ Utilize advanced Retrieval-Augmented Generation (RAG) techniques ▷ Develop AI-driven workflows and web apps using the H2O GPTe Python API ▷ The basics of LLM agents, chains & how to integrate LLM agents with H2O Driverless AI Whether you're a data scientist, developer, or business professional, this course equips you with the tools to transform your organization’s data strategies.

Explore the revolutionary H2O LLM Studio Suite, empowering no-code AI development for crafting intuitive and user-friendly solutions. Don't miss this webinar as an opportunity to unravel h2o.ai's pioneering advancements in Generative AI. Discover more about the h2o.ai Enterprise GPTe platform here: https://h2o.ai/platform/enterprise-h2ogpte/

From automating workflows to delivering precise, data-driven insights, Enterprise h2oGPTe, is a powerful AI tool that empowers industries like insurance, banking, and retail to achieve operational excellence and enhance customer satisfaction. Discover more about its advanced capabilities at: https://h2o.ai/

In this introductory video, we explore Enterprise GPTe and its powerful capabilities. Join the Data Scientists Greg Fousas and Laurene De Peyrelongue as they guide you through several key concepts, starting with the user interface (UI) of H2O.ai’s Enterprise GPTe. You will be demonstrated as on how to automate processes using this UI and conclude by showing you how to create and publish an app using H2O Wave, seamlessly integrating the tools and concepts discussed.

In this video, you dive into the concept of end-to-end pipelines within Enterprise GPTe. We will begin by exploring the user interface (UI) of H2O GPTe and its various capabilities. You'll learn how to develop solutions by experimenting with different Large Language Models (LLMs) and prompts. Next, we'll demonstrate how to transition from the UI to production, using the Python API to programmatically call various commands and buttons. Finally, we'll show you how to create and publish an app using H2O Wave, integrating all the functionalities developed.

In this video, you will be introduced to Enterprise H2O GPTe, a versatile platform that integrates various Large Language Models (LLMs), both commercial and open-source. We will demonstrate key features, including the ability to chat with different LLMs and leverage the powerful Retrieval-Augmented Generation (RAG) capability. This feature allows you to upload documents, websites, or even audio files (which are transcribed into documents) and extract information through interactive chats with the tool.

Now, we take a step further into exploring the H2O GPTe platform, focusing on its main elements: Chats, Collections, and Documents. You will learn how to chat with various Large Language Models (LLMs), both commercial and open-source. We will demonstrate how to select and interact with different LLMs, showing the process of asking questions and retrieving information directly from the models. Follow along we explore the capabilities of these LLMs through a practical example involving the theatrical play "Hamilton."

In this video, we break down the basics of RAG, its unique ability to combine real-time data retrieval with language generation, and why it’s a game-changer across industries like finance, healthcare, and insurance. Learn how H2O.ai’s RAG-powered tools, such as Enterprise h2oGPTe, provide accurate, up-to-date insights by seamlessly integrating public and private data sources. Whether you’re looking to enhance decision-making, streamline workflows, or improve compliance, this video offers valuable insights into the future of AI-driven solutions. Explore more about H2O.ai’s cutting-edge AI capabilities: https://h2o.ai/

Learn how H2O.ai’s Enterprise h2oGPTe is revolutionizing data-driven workflows with Retrieval-Augmented Generation (RAG) technology. This video explores how Enterprise h2oGPTe combines real-time data retrieval and AI-generated insights to deliver precise, relevant, and actionable answers tailored to your organization’s needs. From enhancing decision-making in industries like finance, healthcare, and government to enabling dynamic, secure applications, Enterprise h2oGPTe goes beyond traditional AI models. Learn about its advanced features, including VectorDB, embeddings, and adaptive workflows, and see how it can transform your approach to data analysis and content generation. Explore more about H2O.ai’s innovative AI solutions: https://h2o.ai/

Welcome to another Product Update video on Enterprise h2oGPTe. In this video, we introduce H2O’s Retrieval-Augmented Generation (RAG) system, demonstrating how to set up, customize, and use the platform to securely query large language models (LLMs) with private data. We will cover the following topics in this quick 10 minute video: • Setting up and accessing the H2O RAG platform • Data privacy controls and embedding options • Querying data collections with LLMs • Supported file formats and OCR integration Get access to the free-trial environment and use Enterprise h2oGPTe : https://genai.h2o.ai/

Upon familiarising ourselves with the fundamentals, we now explore the advanced capabilities of H2O GPTe, focusing on the use of Collections for document management and querying. You will learn how to upload various sources of information, including web pages, and query them using Large Language Models (LLMs). Once again, we will demonstrate this by importing the Hamilton Wikipedia page and querying it to retrieve detailed information. Discover how Collections can transform and store text in a vector database, enabling more precise and informed responses from LLMs.

In this video, we highlight the reference capability of H2O GPTe when querying documents within Collections. You will learn how the tool provides specific references for information sourced from web pages. We will query the First Act of the Hamilton play and compare responses from using the RAG model versus the standalone LLM. Understand how using RAG provides detailed, sourced information while the standalone LLM gives more generic responses.

We will explore a realistic use case of H2O GPTe RAG by analyzing survey responses. We will proceed by creating a new collection to load text files with survey answers, then use the RAG model to extract key topics. In this video, you will see how the tool refines queries to provide concise and usable information, transforming survey data into actionable insights in a Python list.

In this episode, we dive into some useful features of H2O.ai Enterprise GPT, focusing on Model Selection and Custom Configuration. Discover how you can take control by manually selecting models that best suit your project needs, whether you prioritize speed, cost, or accuracy. We’ll also cover the Default Settings of H2O.ai Enterprise GPT. Gain insights into how these default preferences are established and learn how to adjust them effectively for your most critical projects, ensuring optimal performance and results. Join us to stay updated on the latest state-of-the-art H2O.ai tools, and don’t forget to like and subscribe!

You will be introduced to the freemium version of Enterprise H2O GPTe available at h2o.ai. Discover how users can access a range of applications created with Python API in Enterprise H2O GPTe. ➾ Link to Access Gen AI App Store : https://genai.h2o.ai/appstore You will learn how to sign up and utilize the tool for free, exploring various functionalities while understanding the daily quota limitations while also gaining insights into cost-effective usage examples and user statistics without compromising data security.

This video dives into the power of H2O GPTe's Python API for streamlining and automating your workflows. ○ Effortless Workflow Automation: Learn how to set up and connect to the API securely, enabling seamless integration with Python code. ○ Python Script Power: Discover examples of using Python scripts to manage text files and interact with collections within the tool. ○ Automate Everything: Witness how API calls can initiate chat sessions, gather responses, and compile data into structured outputs. ○ Data Processing Efficiency: Gain insights into leveraging the Python API for efficient data processing and automation.

In this final video, you will discover how to rapidly create web applications using H2O Wave—an open-source framework for Python and R. Follow along as we: ➣ Connect to H2O GPTe via the Python client. ➣ Extract top topics from survey responses. ➣ Visualize results with dynamic charts. ➣ Enable non-technical users to analyze survey data. ➣ Explore prompt engineering for consistent output. ➣ Transform a notebook into a shareable web app. ➣ Dive into an example review analysis app, highlighting Wave app versatility. Happy learning! 🚀🌟