The ZeroEval TypeScript SDK provides automatic tracing for popular AI libraries through the wrap() function.
OpenAI
Wrap your OpenAI client to automatically trace all API calls:
import { OpenAI } from 'openai';
import * as ze from 'zeroeval';
ze.init();
const openai = ze.wrap(new OpenAI());
// Chat completions are automatically traced
const completion = await openai.chat.completions.create({
model: 'gpt-4',
messages: [{ role: 'user', content: 'Hello!' }]
});
// Streaming is also automatically traced
const stream = await openai.chat.completions.create({
model: 'gpt-4',
messages: [{ role: 'user', content: 'Tell me a story' }],
stream: true
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content || '');
}
Supported Methods
The OpenAI integration automatically traces:
chat.completions.create() (streaming and non-streaming)embeddings.create()images.generate(), images.edit(), images.createVariation()audio.transcriptions.create(), audio.translations.create()
Vercel AI SDK
Wrap the Vercel AI SDK module to trace all AI operations:
import * as ai from 'ai';
import { openai } from '@ai-sdk/openai';
import * as ze from 'zeroeval';
ze.init();
const wrappedAI = ze.wrap(ai);
// Text generation
const { text } = await wrappedAI.generateText({
model: openai('gpt-4'),
prompt: 'Write a haiku about coding'
});
// Streaming
const { textStream } = await wrappedAI.streamText({
model: openai('gpt-4'),
messages: [{ role: 'user', content: 'Hello!' }]
});
for await (const delta of textStream) {
process.stdout.write(delta);
}
// Structured output
import { z } from 'zod';
const { object } = await wrappedAI.generateObject({
model: openai('gpt-4'),
schema: z.object({
name: z.string(),
age: z.number()
}),
prompt: 'Generate a random person'
});
Supported Methods
The Vercel AI SDK integration automatically traces:
generateText(), streamText()generateObject(), streamObject()embed(), embedMany()generateImage()transcribe()generateSpeech()
LangChain / LangGraph
Use the callback handler for LangChain and LangGraph applications:
import {
ZeroEvalCallbackHandler,
setGlobalCallbackHandler
} from 'zeroeval/langchain';
// Option 1: Set globally (recommended)
setGlobalCallbackHandler(new ZeroEvalCallbackHandler());
// All chain invocations are now automatically traced
const result = await chain.invoke({ topic: 'AI' });
import { ZeroEvalCallbackHandler } from 'zeroeval/langchain';
// Option 2: Per-invocation
const handler = new ZeroEvalCallbackHandler();
const result = await chain.invoke(
{ topic: 'AI' },
{ callbacks: [handler] }
);
Auto-Detection
The wrap() function automatically detects which client you’re wrapping:
import { OpenAI } from 'openai';
import * as ai from 'ai';
import * as ze from 'zeroeval';
ze.init();
// Automatically detected as OpenAI client
const openai = ze.wrap(new OpenAI());
// Automatically detected as Vercel AI SDK
const wrappedAI = ze.wrap(ai);
If ze.init() hasn’t been called and ZEROEVAL_API_KEY is set in your environment, the SDK will automatically initialize when you first use wrap().
Using with Prompts
The integrations automatically extract ZeroEval metadata from prompts created with ze.prompt():
import { OpenAI } from 'openai';
import * as ze from 'zeroeval';
ze.init();
const openai = ze.wrap(new OpenAI());
// Create a version-tracked prompt
const systemPrompt = await ze.prompt({
name: 'customer-support',
content: 'You are a helpful customer support agent for {{company}}.',
variables: { company: 'TechCorp' }
});
// The integration automatically:
// 1. Extracts the prompt metadata
// 2. Links the completion to the prompt version
// 3. Patches the model if one is bound to the prompt version
const response = await openai.chat.completions.create({
model: 'gpt-4', // May be replaced by bound model
messages: [
{ role: 'system', content: systemPrompt },
{ role: 'user', content: 'I need help with my order' }
]
});
