Maxim Integration for Vercel
Requirements
"ai"
"@ai-sdk/openai"
"@ai-sdk/anthropic"
"@ai-sdk/google"
"@maximai/maxim-js"
Maxim supports both AI SDK 5 and AI SDK 6. The integration works seamlessly with either version.
Environment Variables
MAXIM_API_KEY=
MAXIM_LOG_REPO_ID=
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
Initialize Logger
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
import { openai } from '@ai-sdk/openai';
import { wrapMaximAISDKModel } from '@maximai/maxim-js/vercel-ai-sdk';
const model = wrapMaximAISDKModel(openai('gpt-4'), logger);
Make LLM Calls Using Wrapped Models
import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai';
import { wrapMaximAISDKModel } from '@maximai/maxim-js/vercel-ai-sdk';
const model = wrapMaximAISDKModel(openai('gpt-4'), 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:
Generate Object
import { generateObject } from 'ai';
import { z } from 'zod';
const response = await generateObject({
model: model,
prompt: 'Generate a user profile for John Doe',
schema: z.object({
name: z.string(),
age: z.number(),
email: z.string().email(),
interests: z.array(z.string()),
}),
});
console.log(response.object);
Stream Text
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);
}
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,
},
});
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
Streaming Support
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-4'), 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
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-4'), 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
// 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-4'), 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
// components/Chat.jsx
import { useChat } from 'ai/react';
export default function Chat() {
const { messages, input, handleInputChange, handleSubmit } = useChat({
api: '/api/chat',
});
return (
<div>
{messages.map((m) => (
<div key={m.id}>
<strong>{m.role}:</strong> {m.content}
</div>
))}
<form onSubmit={handleSubmit}>
<input value={input} onChange={handleInputChange} placeholder="Say something..." />
<button type="submit">Send</button>
</form>
</div>
);
}
Resources