You can access the Jev AI Agent Trace Evaluator — Score LLM Traces programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = { "records": [{
9            "id": "trace-1",
10            "text": "Request: explain refund policy. Tool result: policy allows refund within 30 days. Answer: refunds are available within 30 days.",
11        }] }
12
13# Run the Actor and wait for it to finish
14run = client.actor("alaudinburki/jev-agent-trace-evaluator").call(run_input=run_input)
15
16# Fetch and print Actor results from the run's dataset (if there are any)
17print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
18for item in client.dataset(run.default_dataset_id).iterate_items():
19    print(item)
20
21# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

AI Agent Trace Evaluator - Jev API in Python

The Apify API client for Python is the official library that allows you to use Jev AI Agent Trace Evaluator — Score LLM Traces API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Jev AI Agent Trace Evaluator — Score LLM Traces API in JavaScript

Jev AI Agent Trace Evaluator — Score LLM Traces API through CLI

Jev AI Agent Trace Evaluator — Score LLM Traces OpenAPI definition

Jev AI Agent Trace Evaluator — Score LLM Traces API

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