React Summit

React Summit 2024

Today's Workshop introduced large language models (LLMs) and their implementation using C. The training process involves compressing a large amount of text into parameters, resulting in a lossy approximation. LLMs generate text based on their training, but the generated content may include hallucinations or partially correct answers. Fine tuning and reinforcement learning stages improve the performance of LLMs. In the context of Grafana, LLMs are used for tasks such as generating titles and descriptions, understanding flame graph profiling data, and generating pizza names.

Join Nathan in this hands-on session where you will first learn at a high level what large language models (LLMs) are and how they work. Then dive into an interactive coding exercise where you will implement LLM functionality into a basic example application. During this exercise you will get a feel for key skills for working with LLMs in your own applications such as prompt engineering and exposure to OpenAI's API. After this session you will have insights around what LLMs are and how they can practically be used to improve your own applications. Table of contents: - Interactive demo implementing basic LLM powered features in a demo app- Discuss how to decide where to leverage LLMs in a product- Lessons learned around integrating with OpenAI / overview of OpenAI API- Best practices for prompt engineering- Common challenges specific to React (state management :D / good UX practices)

Llms Workshop: What They Are and How to Leverage Them

Nathan Marrs

Haris Rozajac

In this Talk, the speaker demonstrates how to create an AI chat bot that can answer questions based on information it was never trained on. They build a basic RAG pipeline in just five minutes using live coding. The speaker also shows how to create embeddings and a vector database, set up a vector search index and endpoint, and modify the chat route to enhance the chat bot's capabilities. The program is run and tested, and the Talk concludes with an invitation to join a workshop for more information.

Explore the integration of OpenAI's GPT into React applications to create dynamic, intelligent user interfaces. This session offers practical insights into leveraging GPT's powerful NLP capabilities for chatbots, content generation, and personalized user experiences. Dive into the technical setup with Next.js 14, LangChain, Vercel's AI SDK, and MongoDB's Vector Search to optimize and customize your applications. Join us to transform your React projects with AI.

OpenAI in React: Integrating GPT with Your React Application

Jesse Hall

JS Nation

JSNation 2024

The workshop explores leveraging LLMs and generative AI with JavaScript, focusing on incorporating AI in JavaScript, leveraging TensorFlow.js for ML, and using AI models and backend technologies. It covers using TensorFlow.js toxicity model, Transformers JS with WebWorkers, and building AI applications with existing models. The workshop also delves into prompt engineering for zero-shot prompts and implementing few-shot prompting. It concludes with exploring fuchsia prompts and embeddings, prompt engineering, and context awareness, and offline usage with TensorFlow embeddings.

Today every developer is using LLMs in different forms and shapes, from ChatGPT to code assistants like GitHub CoPilot. Following this, lots of products have introduced embedded AI capabilities, and in this workshop we will make LLMs understandable for web developers. And we'll get into coding your own AI-driven application. No prior experience in working with LLMs or machine learning is needed. Instead, we'll use web technologies such as JavaScript, React which you already know and love while also learning about some new libraries like OpenAI, Transformers.js

Leveraging LLMs to Build Intuitive AI Experiences With JavaScript

Roy Derks

Shivay Lamba

C3 Dev Festival

C3 Dev Festival 2024

Today's workshop introduced the concept of LLMs and their potential to free up time for software engineers. It discussed setting up LLMs to chat with proprietary data, utilizing retrieval augmented generation for small chats, and building a speaker recommendation application using this approach. The workshop also addressed concerns about running data on OpenAI and explored the process of splitting and storing data in a vector database. It concluded with the deployment of an end-to-end application using Genesio and invited attendees to provide feedback and stay in touch.

Feeling the limitations of LLMs? They can be creative, but sometimes lack accuracy or rely on outdated information. In this workshop, we’ll break down the process of building and easily deploying a Retrieval-Augmented Generation system. This approach enables you to leverage the power of LLMs with the added benefit of factual accuracy and up-to-date information.

Can LLMs Learn? Let’s Customize an LLM to Chat With Your Own Data

Andreia Ocanoaia

React Day Berlin

React Day Berlin 2023

Today's workshop focuses on AI for front-end developers and building with Lengtchain JS. Participants will learn how to create a custom MyGPT application, explore prompt engineering and retrieval, and use local data sets. The workshop covers creating a handler function, turning a text area into a controlled component, and rendering a message component on the screen. Participants will also learn about prompt templates, few-shot prompting, and setting up a vector database. The workshop concludes with information on staying in touch and accessing the beta version of a course based on the workshop.

Today every developer is using LLMs in different forms and shapes. Lots of products have introduced embedded AI capabilities, and in this workshop you’ll learn how to build your own AI application. No experience in building LLMs or machine learning is needed. Instead, we’ll use web technologies such as JavaScript, React and GraphQL which you already know and love.

Building AI Applications for the Web

React Summit US

React Summit US 2023

AI is revolutionizing application development and can enhance React applications. Advancements in AI include batch AI, real-time AI, and generative AI. Language models have limitations in accessing real-time data. Retrieval Augmented Generation (RAG) uses vectors to enhance language models. Vector search capabilities improve GPT models by providing up-to-date information and access to private data. Technologies like Next.js, OpenAI, Lankchain, Versel AI SDK, and MongoDB are used to build smarter React apps. An AI-powered documentation site can be built using custom data and vector search. The talk concludes by emphasizing the importance of integrating AI seamlessly into user-centric platforms like React-based projects.

In this talk, attendees will learn how to integrate OpenAI's GPT-4 language model into their React applications, exploring practical use cases and implementation strategies to enhance user experience and create intelligent, interactive applications.

OpenAI in React: Integrating GPT-4 with Your React Application

React Advanced

React Advanced 2023

This Workshop focuses on implementing software using the SDK and API layer, with a focus on JavaScript and React development. It covers topics such as advancements in AI and language models, unlocking language user interfaces, generative AI, large language models and hallucinations, prompt engineering, improving model performance, developing prompts and an iterative approach, prompt development and management, interesting use cases, using the playground and understanding tokens, streaming text and JSON, exploring example implementations, fine-tuning and use cases, limitations and emerging architectures, working with documents and LangChain, embeddings, agents, and development tools, scraping data and fine-tuning, and using LLM for data transformation.

In this workshop we'll take a tour of applied AI from the perspective of front end developers, zooming in on the emerging best practices when it comes to working with LLMs to build great products. This workshop is based on learnings from working with the OpenAI API from its debut last November to build out a working MVP which became PowerModeAI (A customer facing ideation and slide creation tool). In the workshop they'll be a mix of presentation and hands on exercises to cover topics including: - GPT fundamentals- Pitfalls of LLMs- Prompt engineering best practices and techniques- Using the playground effectively- Installing and configuring the OpenAI SDK- Approaches to working with the API and prompt management- Implementing the API to build an AI powered customer facing application- Fine tuning and embeddings- Emerging best practice on LLMOps

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