agentskillexchange Build and debug AI pipelines in an IDE with RocketRide
Use RocketRide to compose, run, observe, and deploy portable AI pipelines from an IDE or CLI across model providers, vector stores, and agent nodes.
Prerequisites
RocketRide IDE extension or RocketRide server, Docker for container deployment, optional Python or TypeScript SDKs
Installation
Use the upstream install or setup path that matches your environment:
- docker pull ghcr.io/rocketride-org/rocketride-engine:latest
- docker create --name rocketride-engine -p 5565:5565 ghcr.io/rocketride-org/rocketride-engine:latest
Requirements and caveats from upstream:
- Python SDK |
- Drop pipelines into any Python or TypeScript app with a few lines of code, no infrastructure glue required.
Basic usage or getting-started notes:
| Visual Pipeline Builder | Drag, connect, and configure nodes in VS Code, no boilerplate. Real-time observability tracks token usage, LLM calls, latency, and execution. Pipelines are portable JSON, version-contro...
Install the extension for your IDE. Search for RocketRide in the extension marketplace:
Extracted from upstream docs: https://raw.githubusercontent.com/rocketride-org/rocketride-server/HEAD/README.md