Why should I use streaming for LLM responses?

Streaming prevents Worker memory buffering issues, reduces time-to-first-token for the user, and avoids execution timeout errors on long-form content.

What is Cloudflare Workers AI?

It is a serverless GPU inference platform that allows you to run machine learning models, like LLMs and image generators, directly on Cloudflare’s global network without managing infrastructure.

How does this skill help with AI rate limits?

The skill provides patterns for implementing retry logic with exponential backoff and using AI Gateway to manage quotas, caching, and request logging.

Can I use the OpenAI SDK with this skill?

Yes, the skill includes reference implementations and configuration guides for using the OpenAI SDK and Vercel AI SDK with Cloudflare's AI endpoints.

Which models are supported by this skill?

It supports a wide range of production models including Llama 3.1 (8B/70B), DeepSeek-R1, Flux-1, Stable Diffusion, and BGE text embeddings.

Cloudflare Workers AI

Name: Cloudflare Workers AI
Author: secondsky

bysecondsky

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Cloud Infrastructure

Integrates serverless GPU inference into Cloudflare Workers for high-performance LLMs, image generation, and text embeddings.

About

Cloudflare Workers AI provides a production-ready knowledge domain for developers building AI-powered applications directly on the edge. It enables seamless integration of open-source models like Llama 3.1, DeepSeek, and Flux for tasks ranging from real-time chat streaming to vector embeddings and RAG architectures. This skill is essential for optimizing AI performance, managing rate limits, and implementing cost-effective inference using Cloudflare's global network and AI Gateway integration.

Key Features

Advanced RAG integration workflows with Vectorize and BGE embeddings
Production-ready patterns for text-to-image and vision-based models
AI Gateway configuration for response caching, logging, and cost tracking
Serverless GPU inference for LLMs including Llama, Mistral, and DeepSeek
Optimized streaming response implementation for low-latency user interfaces
21 GitHub stars

Use Cases

Generating photorealistic images and captions within serverless workflows
Building real-time AI chatbots with low-latency edge streaming
Implementing high-accuracy semantic search using vector embeddings

About

Key Features

Advanced RAG integration workflows with Vectorize and BGE embeddings
Production-ready patterns for text-to-image and vision-based models
AI Gateway configuration for response caching, logging, and cost tracking
Serverless GPU inference for LLMs including Llama, Mistral, and DeepSeek
Optimized streaming response implementation for low-latency user interfaces
21 GitHub stars

Use Cases

Generating photorealistic images and captions within serverless workflows
Building real-time AI chatbots with low-latency edge streaming
Implementing high-accuracy semantic search using vector embeddings