Run Pipe Agent Streaming

import 'dotenv/config';
import {getRunner, Langbase} from 'langbase';

const langbase = new Langbase({
	apiKey: process.env.LANGBASE_API_KEY!,
});

async function main() {
	await createSummaryAgent();

	// Get readable stream
	const {stream, threadId, rawResponse} = await langbase.pipes.run({
		stream: true,
		name: 'summary-agent',
		rawResponse: true,
		messages: [
			{
				role: 'user', 
				content:  'Who is an AI Engineer?'
			}
		]
	});


	// Convert the stream to a stream runner.
	const runner = getRunner(stream);

	// Method 1: Using event listeners
	runner.on('connect', () => {
		console.log('Stream started.\n');
	});

	runner.on('content', content => {
		process.stdout.write(content);
	});

	runner.on('end', () => {
		console.log('\nStream ended.');
	});

	runner.on('error', error => {
		console.error('Error:', error);
	});
}

/**
 * Creates a summary agent pipe if it doesn't already exist.
 *
 * This function checks if a pipe with the name 'summary-agent' exists in the system.
 * If the pipe doesn't exist, it creates a new private pipe with a system message
 * configuring it as a helpful assistant.
 *
 * @async
 * @returns {Promise<void>} A promise that resolves when the operation is complete
 * @throws {Error} Logs any errors encountered during the creation process
 */
async function createSummaryAgent() {
    try {
        await langbase.pipes.create({
            name: 'summary-agent',
			upsert: true,
            status: 'private',
            messages: [
                {
                    role: 'system',
                    content: 'You are a helpful assistant that help users summarize text.',
                },
            ],
        });
    } catch (error) {
        console.error('Error creating summary agent:', error);
    }
}

main();