Guide AI SDK usage for agents, providers, and React hooks.
npx skills add https://github.com/duwscan/skills-graph --skill ai-sdk-duwscan
Please help me install this Agent Skill. Skill: ai-sdk Source: https://github.com/duwscan/skills-graph/tree/main/.agents/skills/ai-sdk Command: npx skills add https://github.com/duwscan/skills-graph --skill ai-sdk-duwscan
This Skill helps developers build AI-powered features by providing guidance on using the AI SDK, including its functions, providers, and best practices for agent development.
generateText, streamText, ToolLoopAgent, embed, and tool usage.useChat and useCompletion.Use the ai-sdk skill to find out how to use the useChat hook to build a chatbot.
High-intent search queries and answers about installing and using this skill.
To build a chatbot with the useChat hook in React, utilize the AI SDK's framework-specific consumption patterns to manage streaming text generation and chat state. The SDK provides guidance on integrating hooks directly into your application for conversational interfaces.
To generate structured output and use tool calling, implement core AI SDK functions like generateText and streamText. The SDK provides specific patterns for tool usage and structured data extraction during text generation.
Yes, you can use different AI providers like OpenAI, Anthropic, and Google. The AI SDK supports multiple provider integrations, allowing you to switch models while maintaining consistent streaming, tool calling, and embedding functions.
The best way to build a RAG system is using the AI SDK's embed function to generate vector embeddings. The SDK offers agent development patterns and best practices for combining embeddings with text generation to create retrieval-augmented generation applications.
Yes, the AI SDK supports streaming responses for real-time applications through the streamText function. This enables continuous text generation and real-time data delivery, which is essential for building responsive chatbots and interactive AI features.
To create an autonomous agent, implement the ToolLoopAgent pattern provided by the AI SDK. This agent development approach enables continuous tool usage and multi-step reasoning, allowing the AI to interact with external tools until a task is completed.
ChristineThamRoute OpenAI, Anthropic, and Google Gemini requests through Netlify's AI Gateway.
vadimcomanescuBuild LangChain agents and RAG pipelines for LLM applications.
neuron-coreIntegrate vector stores, embeddings, and document loaders into Neuron AI agents.
HouseGarofaloAccess and manage over 100 AI models via the OpenRouter API with Python's OpenAI-compatible client.