Develop AI Functions Example

Develop AI Functions Example is an official skill from Vercel's vercel/ai repository. According to the provider, it helps create, run, and modify examples under examples/ai-functions/src. Those examples validate provider support, demonstrate AI SDK features, and create test fixtures. The skill is therefore development guidance rather than an independent model provider, hosting service, or finished production system. It is intended for people who want to explore the AI SDK in TypeScript projects in a reproducible way or protect library changes with small, focused examples that can be reviewed and rerun.

Purpose and triggers

The official description identifies three central tasks. An example can validate support for a new provider, demonstrate a new feature with a particular provider, or reproduce a bug in an isolated file. Provider-specific options and API response fixtures are also within scope. This boundary matters because the skill should not silently design a complete application, alter unrelated infrastructure, or obtain credentials. It supplies context for the examples directory and supports a focused technical investigation with a visible, reviewable result.

Covered functions

According to the provider, the example area includes non-streaming text generation with generateText, streaming with streamText, structured output through generateObject and streamObject, and agentic workflows using ToolLoopAgent. It also covers single and batch embeddings, image generation, speech generation, transcription, reranking, middleware, provider registry setup, telemetry, complex multi-component examples, reusable tools, and shared utilities. Organizing material by function makes the behavior under test explicit and avoids flat collections of provider files that become difficult to compare.

Structure and workflow

The source recommends grouping examples by function and provider. A basic example should use the name basic.ts, while additional examples use descriptive kebab-case names. According to the provider, every example uses the run wrapper from lib/run.ts. That wrapper loads environment values from a local configuration and provides detailed API error handling. Streaming examples can use the helper for printing the full stream, while print utilities remove undefined values from diagnostic output. A useful example should have a clear prompt, a realistic model identifier, and one central behavior that a reviewer can understand without reconstructing a larger application.

Safety, limits, and E-E-A-T

Examples may call external model providers and process prompts, files, or API responses. Credentials, tokens, private keys, and real personal data do not belong in source code, fixture files, or catalog content. Local execution does not automatically mean that data stays local, because the selected provider and model may process the content. The run wrapper improves error reporting but does not replace privacy review, cost controls, permission checks, or prompt-injection analysis. According to the provider, the skill is practical guidance in the official repository; the primary source and AI SDK documentation remain authoritative for current API details. The repository identifies Apache-2.0 as its license. This entry does not claim that every provider is compatible or that every example is production-ready, and it states no concrete prices. Teams should review current provider documentation, model availability, and account terms before execution.