--- title: Maxim description: Evaluate & Observe LLM applications with Maxim --- # Maxim Observability [Maxim AI](https://getmaxim.ai) streamlines AI application development and deployment by applying traditional software best practices to non-deterministic AI workflows. Our evaluation and observability tools help teams maintain quality, reliability, and speed throughout the AI application lifecycle. Maxim integrates with the AI SDK to provide: - Automatic Observability – Adds tracing, logging, and metadata to AI SDK calls with a simple wrapper. - Unified Model Wrapping – Supports OpenAI, Anthropic, and Google etc. models uniformly. - Custom Metadata & Tagging – Enables attaching trace names, tags, and session IDs to track usage. - Streaming & Structured Output Support – Handles streaming responses and structured outputs seamlessly. # Setting up Maxim with the AI SDK ## Requirements ``` "ai" "@ai-sdk/openai" "@ai-sdk/anthropic" "@ai-sdk/google" "@maximai/maxim-js" ``` ## Environment Variables ``` MAXIM_API_KEY= MAXIM_LOG_REPO_ID= OPENAI_API_KEY= ANTHROPIC_API_KEY= ``` ## Initialize Logger ```javascript import { Maxim } from '@maximai/maxim-js'; async function initializeMaxim() { const apiKey = process.env.MAXIM_API_KEY || ''; if (!apiKey) { throw new Error( 'MAXIM_API_KEY is not defined in the environment variables', ); } const maxim = new Maxim({ apiKey }); const logger = await maxim.logger({ id: process.env.MAXIM_LOG_REPO_ID || '', }); if (!logger) { throw new Error('Logger is not available'); } return { maxim, logger }; } ``` ## Wrap AI SDK Models with Maxim ```javascript import { openai } from '@ai-sdk/openai'; import { wrapMaximAISDKModel } from '@maximai/maxim-js/vercel-ai-sdk'; const model = wrapMaximAISDKModel(openai('gpt-5'), logger); ``` ## Make LLM calls using wrapped models ```javascript import { generateText } from 'ai'; import { openai } from '@ai-sdk/openai'; import { wrapMaximAISDKModel } from '@maximai/maxim-js/vercel-ai-sdk'; const model = wrapMaximAISDKModel(openai('gpt-5'), logger); // Generate text with automatic logging const response = await generateText({ model: model, prompt: 'Write a haiku about recursion in programming.', temperature: 0.8, system: 'You are a helpful assistant.', }); console.log('Response:', response.text); ``` ## Working with Different AI SDK Functions The wrapped model works seamlessly with all Vercel AI SDK functions: ### **Structured Output** ```javascript import { generateText, Output } from 'ai'; import { z } from 'zod'; const response = await generateText({ model: model, prompt: 'Generate a user profile for John Doe', output: Output.object({ schema: z.object({ name: z.string(), age: z.number(), email: z.string().email(), interests: z.array(z.string()), }), }), }); console.log(response.output); ``` ### **Stream Text** ```javascript import { streamText } from 'ai'; const { textStream } = await streamText({ model: model, prompt: 'Write a short story about space exploration', system: 'You are a creative writer', }); for await (const textPart of textStream) { process.stdout.write(textPart); } ``` ## Custom Metadata and Tracing ### **Using Custom Metadata** ```javascript import { MaximVercelProviderMetadata } from '@maximai/maxim-js/vercel-ai-sdk'; const response = await generateText({ model: model, prompt: 'Hello, how are you?', providerOptions: { maxim: { traceName: 'custom-trace-name', traceTags: { type: 'demo', priority: 'high', }, } as MaximVercelProviderMetadata, }, }); ``` ### **Available Metadata Fields** **Entity Naming:** - `sessionName` - Override the default session name - `traceName` - Override the default trace name - `spanName` - Override the default span name - `generationName` - Override the default LLM generation name **Entity Tagging:** - `sessionTags` - Add custom tags to the session `(object: {key: value})` - `traceTags` - Add custom tags to the trace `(object: {key: value})` - `spanTags` - Add custom tags to span `(object: {key: value})` - `generationTags` - Add custom tags to LLM generations `(object: {key: value})` **ID References:** - `sessionId` - Link this trace to an existing session - `traceId` - Use a specific trace ID - `spanId` - Use a specific span ID ![Maxim Demo](https://cdn.getmaxim.ai/public/images/maxim_vercel.gif) ## Streaming Support ```javascript import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; import { wrapMaximAISDKModel, MaximVercelProviderMetadata } from '@maximai/maxim-js/vercel-ai-sdk'; const model = wrapMaximAISDKModel(openai('gpt-5'), logger); const { textStream } = await streamText({ model: model, prompt: 'Write a story about a robot learning to paint.', system: 'You are a creative storyteller', providerOptions: { maxim: { traceName: 'Story Generation', traceTags: { type: 'creative', format: 'streaming' }, } as MaximVercelProviderMetadata, }, }); for await (const textPart of textStream) { process.stdout.write(textPart); } ``` ## Multiple Provider Support ```javascript import { openai } from '@ai-sdk/openai'; import { anthropic } from '@ai-sdk/anthropic'; import { google } from '@ai-sdk/google'; import { wrapMaximAISDKModel } from '@maximai/maxim-js/vercel-ai-sdk'; // Wrap different provider models const openaiModel = wrapMaximAISDKModel(openai('gpt-5'), logger); const anthropicModel = wrapMaximAISDKModel( anthropic('claude-3-5-sonnet-20241022'), logger, ); const googleModel = wrapMaximAISDKModel(google('gemini-pro'), logger); // Use them with the same interface const responses = await Promise.all([ generateText({ model: openaiModel, prompt: 'Hello from OpenAI' }), generateText({ model: anthropicModel, prompt: 'Hello from Anthropic' }), generateText({ model: googleModel, prompt: 'Hello from Google' }), ]); ``` ## Next.js Integration ### **API Route Example** ```javascript // app/api/chat/route.js import { streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; import { wrapMaximAISDKModel, MaximVercelProviderMetadata } from '@maximai/maxim-js/vercel-ai-sdk'; import { Maxim } from "@maximai/maxim-js"; const maxim = new Maxim({ apiKey }); const logger = await maxim.logger({ id: process.env.MAXIM_LOG_REPO_ID }); const model = wrapMaximAISDKModel(openai('gpt-5'), logger); export async function POST(req) { const { messages } = await req.json(); const result = await streamText({ model: model, messages, system: 'You are a helpful assistant', providerOptions: { maxim: { traceName: 'Chat API', traceTags: { endpoint: '/api/chat', type: 'conversation' }, } as MaximVercelProviderMetadata, }, }); return result.toAIStreamResponse(); } ``` ### **Client-side Integration** ```javascript // components/Chat.jsx import { useChat } from 'ai/react'; export default function Chat() { const { messages, input, handleInputChange, handleSubmit } = useChat({ api: '/api/chat', }); return (

{messages.map(m => (

{m.role}: {m.content}

))}

); } ``` ## Learn more - After setting up Maxim tracing for the Vercel AI SDK, you can explore other Maxim platform capabilities: - Prompt Management: Version, manage, and dynamically apply prompts across environments and agents. - Evaluations: Run automated and manual evaluations on traces, generations, and full agent trajectories. - Simulations: Test agents in real-world scenarios with simulated multi-turn interactions and workflows. For further details, checkout Vercel AI SDK's [Maxim integration documentation](https://www.getmaxim.ai/docs/sdk/typescript/integrations/vercel/vercel).