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rocketride-org/rocketride-server · source
Snapshot 0 · 2026-11-04T12:47:28Z · Python · MIT
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aa087a8a60b9b07de39ea8c1a59849c3067956b20b68068049c5d163b3ff391eGitHub description at capture
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.
README at capture
<div align="center">
<a href="https://rocketride.org">
<img src="docs/public/assets/poster.png" alt="RocketRide: Open Source AI Pipeline Tool" width="100%">
</a>
<p>
<strong>RocketRide is the open source AIDE: the AI Development Environment.</strong><br/>
Build, deploy and harness production-ready AI solutions at light speed, all within your IDE or using the CLI in your terminal.
</p>
<p>
<img src="docs/public/assets/icon-cpp.png" alt="C++" />
<img src="docs/public/assets/icon-python.png" alt="Python" />
<img src="docs/public/assets/icon-typescript.png" alt="TypeScript" />
</p>
<p>
Your code editor just became the AIDE. RocketRide turns the classic IDE you already use into a full <strong>AI Development Environment</strong>: 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. <strong>It's the harness for everything behind your AI applications, not just the agents, but the whole stack beneath them.</strong>
</p>
<p>
Under the hood, RocketRide is an open source data pipeline builder and runtime built for AI and ML workloads. With 100+ pipeline nodes spanning 15+ LLM providers, 9 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.
</p>
<p>
<a href="https://rocketride.org">Home</a> |
<a href="https://docs.rocketride.org/">Documentation</a> |
<a href="https://pypi.org/project/rocketride/">Python SDK</a> |
<a href="https://www.npmjs.com/package/rocketride">TypeScript SDK</a> |
<a href="https://docs.rocketride.org/connect/mcp/http">MCP Server</a> |
<a href="https://marketplace.visualstudio.com/items?itemName=RocketRide.rocketride">VS Code Marketplace</a> |
<a href="https://open-vsx.org/extension/RocketRide/rocketride">Open VSX Registry</a>
</p>
<p>
<a href="https://github.com/rocketride-org/rocketride-server/actions/workflows/ci.yml"><img src="https://github.com/rocketride-org/rocketride-server/actions/workflows/ci.yml/badge.svg" alt="CI"></a>
<a href="https://github.com/rocketride-org/rocketride-server/releases"><img src="https://img.shields.io/github/v/release/rocketride-org/rocketride-server?filter=server-v*&label=Runtime&color=5f2167&logo=data:image/svg%2bxml;base64,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" alt="Runtime version"></a>
<a href="https://discord.gg/PMXrtenMsY"><img src="https://img.shields.io/badge/Discord-Join-370b7a?logo=discord&logoColor=white" alt="Discord"></a>
<a href="https://github.com/rocketride-org/rocketride-server/blob/develop/LICENSE"><img src="https://img.shields.io/badge/License-MIT-41b6e6" alt="MIT License"></a>
</p>
<img src="docs/public/assets/pipeline-example.png" alt="Build and run AI pipelines inside your IDE" width="100%">
_Design, test, and ship complex AI workflows from a visual canvas, right where you write code._
<img src="docs/public/assets/sdk-example.png" alt="Integrate real AI solutions using a simple SDK" width="100%">
_Drop pipelines into any Python or TypeScript app with a few lines of code, no infrastructure glue required._
</div>
## Where to start
<table>
<tr>
<td width="50%" valign="top" align="left"><strong>Run it locally</strong><br/><br/>Install the extension, pick <strong>Local</strong>, and run a pipeline on your own machine. Nothing to sign up for.<br/><br/><a href="#quick-start"><strong>Quick Start →</strong></a></td>
<td width="50%" valign="top" align="left"><strong>Shipping your first AI feature?</strong><br/><br/>Start from what you already know: a working pipeline in three steps, no API keys.<br/><br/><a href="#your-first-ai-feature"><strong>Start here →</strong></a></td>
</tr>
<tr>
<td valign="top" align="left"><strong>Want to contribute?</strong><br/><br/>Claim an issue with one comment, add a node in Python, or fix the docs you're reading.<br/><br/><a href="#contributing"><strong>Contributing →</strong></a></td>
<td valign="top" align="left"><strong>Want to run it without ops?</strong><br/><br/>We operate the engine; your <code>.pipe</code> runs unchanged, with nothing to provision.<br/><br/><a href="#rocketride-cloud-now-live"><strong>RocketRide Cloud →</strong></a></td>
</tr>
</table>
**Open source, MIT.** The whole engine is MIT-licensed and OSI-compliant. No enterprise edition, nothing behind a paywall.
## Features
| Feature | Description |
| :-------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Rocket Builder** | Drag, connect, and configure nodes visually, 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. |
| **100+ Pipeline Nodes** | 15+ LLM providers, 9 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](https://cloud.rocketride.ai/). 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:
<p align="center">
<img src="docs/public/assets/install-extension.png" alt="Install RocketRide extension">
</p>
<sub>[Not seeing your IDE? Open an issue](https://github.com/rocketride-org/rocketride-server/issues/new) · [Download directly](https://open-vsx.org/extension/RocketRide/rocketride)</sub>
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](CONTRIBUTING.md#getting-started).
## Your first AI feature
_Whether you build web apps, integrate APIs, or run backend services, you already have the mental model._
| You already know | Same idea in RocketRide |
| :-- | :-- |
| A route that receives a request | A **source node**: `webhook`, `chat`, or `dropper` (file drop) |
| Middleware chained in order | **Nodes**, wired together on a canvas. Most are Python you can open and read |
| The response you return | A **response** node |
| Config in git, like a Dockerfile | The `.pipe` file: plain JSON, diffable, reviewable |
| Calling a service from your app | The Python or TypeScript SDK: one call in, one result out |
**Three steps, no API keys:**
1. **Run it locally.** Follow the [Quick Start](#quick-start) and pick **Local** when asked. That's the whole install.
2. **Open a working pipeline.** Open [`examples/document-processor.pipe`](examples/document-processor.pipe) in your IDE. Give it a PDF or an image and it pulls out the text (including text inside images), finds names, addresses and other personal data, and returns a cleaned copy. It runs on local models, so nothing leaves your machine. Press ▶ on the source node to start it. Its source is a `webhook`, so it waits for input — step 3 is how you send some.
3. **Call it from your code.** The pipeline is now a function your service can call. Run it from the folder you opened in your IDE: the extension writes the engine's connection details into a `.env` there, and the SDK reads them automatically. Run it from anywhere else and the client falls back to RocketRide Cloud instead.
```bash
pip install rocketride
```
```python
import asyncio
from rocketride import RocketRideClient
async def main():
async with RocketRideClient() as client:
run = await client.use(filepath='examples/document-processor.pipe')
out = await client.send(
run['token'], 'Alice Smith, 12 Elm St, Springfield.', objinfo={'name': 'note.txt'}, mimetype='text/plain'
)
print(out)
await client.terminate(run['token'])
asyncio.run(main())
```
TypeScript works the same way: [`npm install rocketride`](https://www.npmjs.com/package/rocketride) · [SDK docs](https://docs.rocketride.org/clients/typescript)
**Next steps, one at a time:**
- **Add a model.** Drop an `llm_*` node between the source and the response and add one API key. Same pipeline, now with an LLM in the loop.
- **Search by meaning.** [`examples/rag-pipeline.pipe`](examples/rag-pipeline.pipe) is the standard "ask questions about my documents" pattern. Needs one LLM key and a vector database ([Qdrant](https://qdrant.tech/) can run locally).
- **Give it tools.** An **agent** node is an LLM allowed to call other nodes in a loop until it's done. [`examples/agent-workflow.pipe`](examples/agent-workflow.pipe) shows the shape.
<details>
<summary><strong>Words you'll see, translated</strong></summary>
| Term | What it means here |
| :-- | :-- |
| **Pipeline** | A request handler built from steps, saved as a `.pipe` JSON file |
| **Node** | One step. Providers (OpenAI, Anthropic…), tools (GitHub, Slack…), stores, parsers |
| **Embedding** | Turning text into a list of numbers so "similar meaning" becomes "nearby numbers" |
| **Vector database** | A store that finds records by meaning instead of exact match |
| **RAG** | Retrieve the relevant documents first, then ask the model with them in context |
| **Agent** | An LLM that can call tools and nodes repeatedly until the task is done |
| **OCR / NER / PII** | Read text out of images / find names, dates, organisations / detect personal data |
| **Chunking** | Splitting long documents into pieces small enough to embed and retrieve |
</details>
## 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](https://docs.rocketride.org/).
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:
<p align="center">
<img src="docs/public/assets/first_pipe.gif" alt="Pipeline canvas example" width="100%">
</p>
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](https://docs.docker.com/get-docker/) to be installed.
```bash
docker pull ghcr.io/rocketride-org/rocketride-engine:latest
docker create --name rocketride-engine -p 5565:5565 ghcr.io/rocketride-org/rocketride-engine:latest
docker start rocketride-engine
```
- **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](https://cloud.rocketride.ai/). Same portable pipeline JSON, zero infrastructure to run, from prototype to production. [Get started](https://cloud.rocketride.ai/)
6. Run your pipelines as standalone processes or integrate them into your existing [Python](https://docs.rocketride.org/clients/python) and [TypeScript/JS](https://docs.rocketride.org/clients/typescript) 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.
<p align="center">
<img src="docs/public/assets/tracing.gif" alt="Pipeline observability and tracing">
</p>
## Documentation
Everything on [docs.rocketride.org](https://docs.rocketride.org/) is built from the [`docs/`](docs/) tree in this repo, split by audience. [`docs/README.md`](docs/README.md) is the full map; the short version:
| Looking for | Start at |
|---|---|
| Using RocketRide: quickstart, concepts, guides, cloud, self-hosting | [`docs/public/product/`](docs/public/product/) (the site, page for page) |
| SDK guides | [TypeScript](docs/public/typescript/) · [Python](docs/public/python/) · [MCP](docs/public/mcp/) |
| Building your own client on the engine protocol | [`docs/public/product/connect/websocket/`](docs/public/product/connect/websocket/) |
| Contributing: setup, builder, engine internals, node authoring | [`docs/development/`](docs/development/index.md) |
| Node catalog | each node's `README.md` under [`nodes/src/nodes/`](nodes/src/nodes) |
| Apps: VS Code extension and the shell UIs | each app's own folder under [`apps/`](apps/); how they fit the monorepo in [`docs/development/apps/`](docs/development/apps/index.md) |
| Pointing an AI assistant at RocketRide | [`docs/agents/`](docs/agents/README.md) |
Repo-wide contributor rules live in [AGENTS.md](AGENTS.md).
## Contributing
**Good places to start**
- **Claim an issue with one comment.** Comment `/assign` on any open issue and it's yours. No permissions or membership needed.
- **Good first issues** are labelled [`good first issue`](https://github.com/rocketride-org/rocketride-server/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22); `help wanted` marks bigger ones we'd like a hand with.
- **Add a node.** Every node is a small Python package under [`nodes/src/nodes/`](nodes/src/nodes). A new provider, tool, or store makes a good first contribution. Guide: [Adding a New Node](docs/development/nodes/index.md#adding-a-new-node).
- **Fix what you just read.** Docs PRs are welcome, including this README.
**How it works**
- Fork, branch as `<type>/RR-<issue>-<short-description>`, open a PR against `develop`, link the issue. Full process, style guides, and test commands: [CONTRIBUTING.md](CONTRIBUTING.md).
- One build tool for the whole monorepo: `./builder` manages the C++ toolchain, Python environments, and Java/Tika for you. Clone, build, run.
- Roles and decisions: [GOVERNANCE.md](GOVERNANCE.md) · Releases: [RELEASE.md](RELEASE.md) · Security reports: [SECURITY.md](SECURITY.md) · Questions: [Discussions](https://github.com/rocketride-org/rocketride-server/discussions), [Discord](https://discord.gg/PMXrtenMsY), [SUPPORT.md](.github/SUPPORT.md)
<div align="center">
## Two ways to run RocketRide
_Let us handle the infrastructure, or own every layer._
<br/>
<table>
<tr>
<td width="50%" valign="top" align="left"><strong>ROCKETRIDE CLOUD</strong> · <code>NOW LIVE</code></td>
<td width="50%" valign="top" align="left"><strong>ON-PREM</strong></td>
</tr>
<tr>
<td valign="top" align="left"><strong>Let us run it, zero ops</strong><br/><br/>The fastest way to get started. We operate the engine; you point a client at the endpoint and build. The same <code>.pipe</code> file runs unchanged, with no infrastructure to provision, from prototype to production.</td>
<td valign="top" align="left"><strong>Run it yourself, free</strong><br/><br/>Docker, on-prem, or local. Full control and data residency. Open source, MIT, no lock-in, ever.</td>
</tr>
<tr>
<td align="center"><a href="https://cloud.rocketride.ai/"><strong>Get Started</strong></a></td>
<td align="center"><a href="#quick-start"><strong>Quick Start</strong></a></td>
</tr>
</table>
</div>
## RocketRide Cloud <code>NOW LIVE</code>
<div align="center">
### Run pipelines, not infrastructure.
<p>
<strong>With RocketRide Cloud, offload the complex, heavy lifting of production AI.</strong><br/>
Build your pipeline once, in the same portable <code>.pipe</code> format, and we run it, scale it, and keep it fast. No servers, no ops, no rewrite from prototype to production.
</p>
</div>
<table>
<tr>
<td width="50%" valign="top" align="left"><strong>A fraction of the cost</strong><br/><br/>Our model server runs your AI workloads far more efficiently, so you pay a fraction of what standard hosting costs.</td>
<td width="50%" valign="top" align="left"><strong>Collaborate as a team</strong><br/><br/>Work together on shared pipelines. Your whole team builds, runs, and iterates in one place.</td>
</tr>
<tr>
<td valign="top" align="left"><strong>No-hassle infra</strong><br/><br/>We handle everything: servers, scaling, upgrades, uptime. Nothing to provision, nothing to operate.</td>
<td valign="top" align="left"><strong>Higher performance, built-in scale</strong><br/><br/>More throughput on the multithreaded C++ engine, with automatic scalability built in.</td>
</tr>
</table>
<br/>
Connecting takes two lines. Same portable pipeline JSON, now hosted for you:
```bash
ROCKETRIDE_URI=https://api.rocketride.ai
ROCKETRIDE_AUTH=your-api-token
```
<p align="center">
<a href="https://cloud.rocketride.ai/"><strong>Get Started</strong></a> · <a href="https://docs.rocketride.org/operate/cloud">Read the Cloud docs</a>
</p>
## On-Prem <code>FREE & MIT</code>
<div align="center">
### Own every layer.
<p>
<strong>Run the very same engine yourself, wherever your data lives.</strong><br/>
Docker, on-premises, or a local process in your IDE. Full control, full data residency, and zero lock-in. The exact <code>.pipe</code> you build on Cloud runs unchanged on your own hardware.
</p>
</div>
<table>
<tr>
<td width="50%" valign="top" align="left"><strong>Full control and data residency</strong><br/><br/>Your data and model calls never leave your infrastructure. Run it behind your firewall, or fully air-gapped.</td>
<td width="50%" valign="top" align="left"><strong>Open source, MIT</strong><br/><br/>The whole engine is MIT-licensed and OSI-compliant. No enterprise edition, nothing behind a paywall.</td>
</tr>
<tr>
<td valign="top" align="left"><strong>Runs anywhere</strong><br/><br/>Docker, on-premises, bare metal, or local. Scale out to a cluster with the Helm chart when you need to.</td>
<td valign="top" align="left"><strong>The same C++ engine</strong><br/><br/>Identical multithreaded runtime and execution semantics as Cloud. Move a pipeline between them anytime.</td>
</tr>
</table>
<br/>
Point a client at your local engine in one line:
```bash
ROCKETRIDE_URI=ws://localhost:5565
```
<p align="center">
<a href="#quick-start"><strong>Quick Start</strong></a> · <a href="https://docs.rocketride.org/operate/self-hosting">Read the On-Prem docs</a>
</p>
<p align="center">Ready to ship? Deploy your pipeline on <a href="https://cloud.rocketride.ai/">RocketRide Cloud</a>, or run on-prem, free.</p>
## 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](CONTRIBUTING.md) to get started.
<a href="https://github.com/rocketride-org/rocketride-server/graphs/contributors">
<img alt="contributors" src="https://contrib.rocks/image?repo=rocketride-org/rocketride-server&columns=16" width="100%" />
</a>
---
<p align="center">Made with ♥ in SF & EU</p>