Run Pipe Agent Chat with Pipe API Keys

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
	if (!process.env.PIPE_API_KEY) {
		console.log(`PIPE_API_KEY is not set in the environment variables get it from https://langbase.com/pipes`);
	}
	else {
		const {stream, threadId, rawResponse} = await langbase.pipes.run({
			stream: true,
			rawResponse: true,
			apiKey: process.env.PIPE_API_KEY!,
			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();