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ai-sdk-handler

Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.

aiskillstore☆ 124 仓库 Stars6 仓库 Forks

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

查看来源 ↗使用指南

技能说明

AI SDK Handler

This skill defines how to implement Large Language Model (LLM) features using the Vercel AI SDK. It covers streaming chat, structured object generation, generative UI, and background agents.

Note: For Image/Video generation (Replicate, Fal.ai), continue to use ai-handler. Use ai-sdk-handler specifically for text, chat, and agentic text/JSON workflows.

When to Use

  • Chatbots: Building interactive chat interfaces (useChat, streamText).
  • Structured Data: Extracting JSON from text (generateObject).
  • Generative UI: Streaming React components directly from the server (streamUI).
  • Agents: Complex, multi-step reasoning tasks (often combined with Inngest).
  • Multimodal: Handling image inputs with text.

Capabilities

1. Streaming Chat
  • Tool: streamText (Server), useChat (Client).
  • Pattern: Create a route handler at src/app/api/chat/route.ts.
  • Auth: Wrap with withAuthRequired to protect the route.
  • UI: Use src/components/chat-ui/ for chat components.
2. Generative UI (RSC)
  • Tool: streamUI (Server).
  • Pattern: Return React components based on tool calls.
  • Use Case: Dashboards that build themselves, dynamic reports.
3. Structured Object Generation
  • Tool: generateObject.
  • Pattern: Define a Zod schema and get strictly typed JSON back.
  • Use Case: Populating database forms, extracting itinerary details, categorizing content.
4. Background Agents (with Inngest)
  • Tool: generateText / generateObject inside Inngest steps.
  • Why: Next.js Server Actions/Routes have timeouts (max 60s usually). Agents taking longer must run in the background.
  • Pattern:
    1. Trigger Inngest event from UI.
    2. Inngest function runs the LLM logic (loops, multi-step).
    3. Store result in DB or notify user.
    4. Docs: AI SDK Agents.

Best Practices

  1. Streaming: Always prefer streaming for text generation > 2 seconds to improve perceived latency.
  2. Auth: Never expose open AI routes. Always verify session.user.id.
  3. Providers: Use @ai-sdk/openai or @ai-sdk/anthropic. Abstract the provider configuration in src/lib/ai/index.ts.
  4. Backpressure: The AI SDK handles this automatically in streamText.
  5. Caching: Use unstable_cache or KV stores if queries are repetitive.
  6. Prompt Engineering: Keep prompts in a dedicated folder or constant file if they are complex.

Documentation & Examples

  • reference.md: Core setup and essential code snippets.
  • examples.md: Exhaustive examples covering:
    1. Basic Chat
    2. Generative UI
    3. Structured Object Generation
    4. Agents & Workflows (Loop Control)
    5. Caching
    6. Streaming Data
    7. Reading UI Streams
    8. Handling Backpressure
    9. Multimodal Chat

使用示例

查看来源仓库中的使用示例与配置说明。

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来源历史

收录时间
2026-01-20
索引更新时间
2026-01-28
Branch
main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

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