Build AI Applications
Build and deploy ambitious AI applications to Cloudflare’s global network. For more Cloudflare video content, check out our YouTube channel.
Reference architectures
Diagrams, design patterns, and detailed best practices to help you generate solutions with Cloudflare products.
- Automatic captioning for video uploads: By integrating automatic speech recognition technology into video platforms, content creators, publishers, and distributors can reach a broader audience, including individuals with hearing impairments or those who prefer to consume content in different languages.
- Composable AI architecture: The architecture diagram illustrates how AI applications can be built end-to-end on Cloudflare, or single services can be integrated with external infrastructure and services.
- Content-based asset creation: Combining text-generation models with text-to-image models can lead to powerful AI systems capable of generating visual content based on input prompts. This integration can be achieved through a collaborative framework where a text-generation model generates prompts for the text-to-image model based on input text.
- Multi-vendor AI observability and control: By shifting features such as rate limiting, caching, and error handling to the proxy layer, organizations can apply unified configurations across services and inference service providers.
- Retrieval Augmented Generation (RAG): Retrieval-Augmented Generation (RAG) is an innovative approach in natural language processing that integrates retrieval mechanisms with generative models to enhance text generation.
Demo apps
- Phoney AI: This application uses Cloudflare Workers AI, Twilio, and AssemblyAI. Your phone is an input and output device.
- Image Model Streamlit starters: Collection of Streamlit applications that are making use of Cloudflare Workers AI.
- Vanilla JavaScript Chat Application using Cloudflare Workers AI: A web based chat interface built on Cloudflare Pages that allows for exploring Text Generation models on Cloudflare Workers AI. Design is built using tailwind.
- Whatever-ify: Turn yourself into…whatever. Take a photo, get a description, generate a scene and character, then generate an image based on that calendar.
- Comically Bad Art Generation: This app uses the wonderful Python UI Framework Streamlit and Cloudflare Workers AI.
- Chatflare: A web based chat interface built on Cloudflare Pages that allows for exploring Text Generation models on Cloudflare Workers AI. Design is built using tailwind.
Tutorials
Step-by-step guides to help you build and learn.
- Choose the Right Text Generation Model: There's a wide range of text generation models available through Workers AI. In an effort to aid you in your journey of finding the right model, this notebook will help you get to know your options in a speed dating type of scenario.
- Create a fine-tuned OpenAI model with R2: In this tutorial, you will use the OpenAI API and Cloudflare R2 to create a fine-tuned model .
- Build a Retrieval Augmented Generation (RAG) AI: This guide will instruct you through setting up and deploying your first application with Cloudflare AI. You will build a fully-featured AI-powered application, using tools like Workers AI, Vectorize, D1, and Cloudflare Workers.
- Recommend products on e-commerce sites using Workers AI and Stripe: E-commerce and media sites often work on increasing the average transaction value to boost profitability. One of the strategies to increase the average transaction value is “cross-selling,” which involves recommending related products. Cloudflare offers a range of products designed to build mechanisms for retrieving data related to the products users are viewing or requesting. In this tutorial, you will experience developing functionalities necessary for cross-selling by creating APIs for …
- Explore Code Generation Using DeepSeek Coder Models: Explore how you can use AI models to generate code and work more efficiently.
- Deploy a Worker that connects to OpenAI via AI Gateway: In this tutorial, you will learn how to deploy a Worker that makes calls to OpenAI through AI Gateway. AI Gateway helps you better observe and control your AI applications with more analytics, caching, rate limiting, and logging.
- Explore Workers AI Models Using a Jupyter Notebook: This notebook explores the Workers AI REST API using Python and the requests library.
- Fine Tune Models With AutoTrain from HuggingFace: Fine tuning an AI model gives you the opportunity to add additional training data to the model. Workers AI allows for Low-Rank Adaptation, LoRA, adapters that will allow you to finetune our models.
- OpenAI GPT function calling with JavaScript and Cloudflare Workers: In this tutorial, you will build a project that leverages OpenAI’s function calling feature, available in OpenAI’s latest Chat Completions API models.
Customer spotlights
Explore case studies on AI companies building on Cloudflare.
Code examples
Examples ready to copy and paste.
- Stream OpenAI API Responses: Use the OpenAI v4 SDK to stream responses from OpenAI.