Integrate a pipeline with an SDK

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Integrate a pipeline with an SDK

Once you have a .pipe file, run it from your own application with the Python or TypeScript SDK. Both connect to a running engine, a local server (ws://localhost:5565) or RocketRide Cloud (https://api.rocketride.ai), start the pipeline with use(), stream data with send(), and stop it with terminate().

If you do not have a .pipe file yet, build one first with the IDE walkthrough.

Python

pip install rocketride

import asyncio
from rocketride import RocketRideClient

async def main():
    async with RocketRideClient(uri='ws://localhost:5565', auth='my-key') as client:
        result = await client.use(filepath='my-first-pipeline.pipe')
        token = result['token']
        out = await client.send(token, 'Hello, pipeline!', objinfo={'name': 'input.txt'}, mimetype='text/plain')
        print(out)
        await client.terminate(token)

asyncio.run(main())

See the Python SDK reference for chat, file uploads, streaming pipes, events, and persist-mode reconnection.

TypeScript

npm install rocketride

import { RocketRideClient } from 'rocketride';

const client = new RocketRideClient({ uri: 'ws://localhost:5565', auth: process.env.ROCKETRIDE_APIKEY! });
await client.connect();
const { token } = await client.use({ filepath: './my-first-pipeline.pipe' });
const result = await client.send(token, 'Hello, pipeline!', { name: 'input.txt' }, 'text/plain');
console.log(result);
await client.terminate(token);
await client.disconnect();

See the TypeScript SDK reference for chat, file uploads, streaming pipes, events, and persist-mode reconnection.

Next

• Pipeline JSON reference: every field of a .pipe file.
• Troubleshooting: what to check when a run does not behave.