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rocketride-org/rocketride-server

Python

High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.

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ArtefactosPyPIpip install rocketride-server
README
RocketRide: Open Source AI Pipeline Tool

RocketRide is the open source AIDE: the AI Development Environment.
Build, deploy and harness production-ready AI solutions at light speed, all within your IDE or using the CLI in your terminal.

C++   Python   TypeScript

Your code editor just became the AIDE. RocketRide turns the classic IDE you already use into a full AI Development Environment: one place to compose, debug, observe, and deploy AI runtimes using any model, any tool, any framework, with zero vendor lock-in. Equipped with deep observability and backed by a battle-tested, high-throughput C++ engine, what you build is production-ready the moment it runs. It's the harness for everything behind your AI applications, not just the agents, but the whole stack beneath them.

Under the hood, RocketRide is an open source data pipeline builder and runtime built for AI and ML workloads. With 50+ pipeline nodes spanning 13 LLM providers, 8 vector databases, OCR, NER, and more, pipelines are defined as portable JSON, built visually in VS Code, and executed by a multithreaded C++ runtime. From real-time data processing to multimodal AI search, RocketRide runs entirely on your own infrastructure.

Home | Documentation | Python SDK | TypeScript SDK | MCP Server

CI Runtime version Discord MIT License

Build and run AI pipelines inside your IDE

Design, test, and ship complex AI workflows from a visual canvas, right where you write code.

Integrate real AI solutions using a simple SDK

Drop pipelines into any Python or TypeScript app with a few lines of code, no infrastructure glue required.

Two ways to run RocketRide

Let us handle the infrastructure, or own every layer.


ROCKETRIDE CLOUD  ·  NOW LIVE ON-PREM
Let us run it, zero ops

The fastest way to get started. We operate the engine; you point a client at the endpoint and build. The same .pipe file runs unchanged, with no infrastructure to provision, from prototype to production.
Run it yourself, free

Docker, on-prem, or local. Full control and data residency. Open source, MIT, no lock-in, ever.
Get Started Quick Start

RocketRide Cloud  NOW LIVE

Run pipelines, not infrastructure.

With RocketRide Cloud, offload the complex, heavy lifting of production AI.
Build your pipeline once, in the same portable .pipe format, and we run it, scale it, and keep it fast. No servers, no ops, no rewrite from prototype to production.

A fraction of the cost

Our patent-pending model server runs your AI workloads far more efficiently, so you pay a fraction of what standard hosting costs.
Collaborate as a team

Work together on shared pipelines. Your whole team builds, runs, and iterates in one place.
No-hassle infra

We handle everything: servers, scaling, upgrades, uptime. Nothing to provision, nothing to operate.
Higher performance, built-in scale

More throughput on the multithreaded C++ engine, with automatic scalability built in.

Connecting takes two lines. Same portable pipeline JSON, now hosted for you:

ROCKETRIDE_URI=https://api.rocketride.ai
ROCKETRIDE_AUTH=your-api-token

Get Started   ·   Read the Cloud docs

On-Prem  FREE & MIT

Own every layer.

Run the very same engine yourself, wherever your data lives.
Docker, on-premises, or a local process in your IDE. Full control, full data residency, and zero lock-in. The exact .pipe you build on Cloud runs unchanged on your own hardware.

Full control and data residency

Your data and model calls never leave your infrastructure. Run it behind your firewall, or fully air-gapped.
Open source, MIT

The whole engine is MIT-licensed and OSI-compliant. No enterprise edition, nothing behind a paywall.
Runs anywhere

Docker, on-premises, bare metal, or local. Scale out to a cluster with the Helm chart when you need to.
The same C++ engine

Identical multithreaded runtime and execution semantics as Cloud. Move a pipeline between them anytime.

Point a client at your local engine in one line:

ROCKETRIDE_URI=ws://localhost:5565

Quick Start   ·   Read the On-Prem docs

Features

Feature Description
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-controllable, shareable, and runnable anywhere.
High-Performance C++ Runtime Native multithreading purpose-built for the throughput demands of AI and data workloads. No bottlenecks, no compromises for production scale.
85+ Pipeline Nodes 13 LLM providers, 8 vector databases, OCR, NER, PII anonymization, chunking strategies, embedding models, and more. All nodes are Python-extensible, build and publish your own.
Multi-Agent Workflows Built-in CrewAI and LangChain support. Chain agents, share memory across pipeline runs, and manage multi-step reasoning at scale.
Coding Agent Ready RocketRide auto-detects your coding agent: Claude, Cursor, and more. Build, modify, and deploy pipelines through natural language.
TypeScript, Python & MCP SDKs Integrate pipelines into native apps, expose them as callable tools for AI assistants, or build programmatic workflows into your existing codebase.
Zero Dependency Headaches Python environments, C++ toolchains, Java/Tika, and all node dependencies managed automatically. Clone, build, run, no manual setup.
One-Click Deploy Run on Docker, on-prem, or RocketRide Cloud. Production-ready architecture from day one, not retrofitted from a demo.

Quick Start

  1. Install the extension for your IDE. Search for RocketRide in the extension marketplace:

    Install RocketRide extension

    Not seeing your IDE? Open an issue · Download directly

  2. Click the RocketRide extension in your IDE

  3. Deploy a server - you'll be prompted on how you want to run the server. Choose the option that fits your setup:

    • Local (Recommended) - This pulls the server directly into your IDE without any additional setup.
    • On-Premises - Run the server on your own hardware for full control and data residency. Pull the image and deploy to Docker or clone this repo and build from source.

Building Your First Pipe

  1. All pipelines are recognized with the *.pipe format. Each pipeline and its configuration are JSON objects - but the extension in your IDE will render within our visual builder canvas.

  2. All pipelines begin with a source node: webhook, chat, or dropper. For specific usage, examples, and inspiration on how to build pipelines, check out our guides and documentation.

  3. Connect input lanes and output lanes by type to properly wire your pipeline. Some nodes like agents or LLMs can be invoked as tools for use by a parent node as shown below:

    Pipeline canvas example

  4. You can run a pipeline from the canvas by pressing the ▶ button on the source node or from the Connection Manager directly.

  5. Deploy your pipelines - pick the path that fits:

    • Docker - Download the RocketRide server image and create a container. Requires Docker to be installed.

      docker pull ghcr.io/rocketride-org/rocketride-engine:latest
      docker create --name rocketride-engine -p 5565:5565 ghcr.io/rocketride-org/rocketride-engine:latest
      
    • Local Deployment - Download your preferred runtime as a standalone process from the Deploy page in the Connection Manager.

    • RocketRide Cloud - Skip the setup and ship straight to managed hosting. Same portable pipeline JSON, zero infrastructure to run, from prototype to production. Get started

  6. Run your pipelines as standalone processes or integrate them into your existing Python and TypeScript/JS applications utilizing our SDK.

Observability

Selecting running pipelines allows for in-depth analytics. Trace call trees, token usage, memory consumption, and more to optimize your pipelines before scaling and deploying. Find the models, agents, and tools best fit for your task.

Pipeline observability and tracing

Contributors

RocketRide is built by a growing community of contributors. Whether you've fixed a bug, added a node, improved docs, or helped someone on Discord, thank you. New contributions are always welcome - check out our contributing guide to get started.

contributors

Ready to ship? Deploy your pipeline on RocketRide Cloud, or run on-prem, free.

Made with ♥ in SF & EU

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