47afddfd73
- 新增 ObjectPickerOverlay 组件，支持点击图片拾取物品 - 新增 /api/pick-object API，调用 Qwen-VL 识别物品 - Canvas Store 扩展拾取模式状态管理 - ImageNode 工具栏新增拾取按钮 - CanvasChatPanel 集成物品标签，发送时自动构建精准prompt - 图片压缩至 600px 以内加速 AI 分析 - 物品名称限制 8 字，位置固定 4 字标准词库
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Chat SDK
Chat SDK is a free, open-source template built with Next.js and the AI SDK that helps you quickly build powerful chatbot applications.
Read Docs · Features · Model Providers · Deploy Your Own · Running locally
Features
- Next.js App Router
- Advanced routing for seamless navigation and performance
- React Server Components (RSCs) and Server Actions for server-side rendering and increased performance
- AI SDK
- Unified API for generating text, structured objects, and tool calls with LLMs
- Hooks for building dynamic chat and generative user interfaces
- Supports xAI (default), OpenAI, Fireworks, and other model providers
- shadcn/ui
- Styling with Tailwind CSS
- Component primitives from Radix UI for accessibility and flexibility
- Data Persistence
- Neon Serverless Postgres for saving chat history and user data
- Vercel Blob for efficient file storage
- Auth.js
- Simple and secure authentication
Model Providers
This template uses the Vercel AI Gateway to access multiple AI models through a unified interface. The default configuration includes xAI models (grok-2-vision-1212, grok-3-mini) routed through the gateway.
AI Gateway Authentication
For Vercel deployments: Authentication is handled automatically via OIDC tokens.
For non-Vercel deployments: You need to provide an AI Gateway API key by setting the AI_GATEWAY_API_KEY environment variable in your .env.local file.
With the AI SDK, you can also switch to direct LLM providers like OpenAI, Anthropic, Cohere, and many more with just a few lines of code.
Deploy Your Own
You can deploy your own version of the Next.js AI Chatbot to Vercel with one click:
Running locally
You will need to use the environment variables defined in .env.example to run Next.js AI Chatbot. It's recommended you use Vercel Environment Variables for this, but a .env file is all that is necessary.
Note: You should not commit your
.envfile or it will expose secrets that will allow others to control access to your various AI and authentication provider accounts.
- Install Vercel CLI:
npm i -g vercel - Link local instance with Vercel and GitHub accounts (creates
.verceldirectory):vercel link - Download your environment variables:
vercel env pull
pnpm install
pnpm db:migrate # Setup database or apply latest database changes
pnpm dev
Your app template should now be running on localhost:3000.