## File: README.md ## RocketRide Cloud  `NOW LIVE` | **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: ```bash ROCKETRIDE_URI=https://api.rocketride.ai ROCKETRIDE_AUTH=your-api-token ``` ## On-Prem  `FREE & MIT` | **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: ```bash ROCKETRIDE_URI=ws://localhost:5565 ``` ## 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. | | **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: [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) 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). ## 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: 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 ``` - **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/sdk/python-sdk) and [TypeScript/JS](https://docs.rocketride.org/sdk/node-sdk) 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. ## 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. --- --- ## File: docs/README.md # Development Environment Setup This guide walks you through setting up a local development environment for the RocketRide Engine. ## Prerequisites | Tool | Version | Notes | | ----------------- | ------------- | -------------------------------------------------------------- | | **Node.js** | 18+ | Runtime for the build system and TypeScript clients | | **pnpm** | 8+ | Package manager (`npm install pnpm`) | | **Python** | 3.10+ | Required for pipeline nodes, AI modules, and the Python SDK | | **C++ toolchain** | C++17-capable | Required only when building the engine from source (see below) | | **Git** | 2.x | Source control | ### C++ toolchain details (engine builds only) - **macOS** -- Xcode Command Line Tools (`xcode-select --install`) - **Linux** -- GCC 10+ or Clang 13+ (`sudo apt install build-essential cmake`) - **Windows** -- Visual Studio 2019+ with the "Desktop development with C++" workload > Most contributors do **not** need the C++ toolchain. The builder downloads a pre-built engine binary by default. ## Clone and Install ```bash git clone https://github.com/rocketride-org/rocketride-server.git cd rocketride-server pnpm install ``` ## Environment Configuration If the repository contains a `.env.template` or `.env.example` file, copy it: ```bash cp .env.template .env # or .env.example ``` Edit `.env` and fill in the values relevant to your setup (API keys, model endpoints, etc.). If no template exists, you can skip this step -- most functionality works with defaults. ## Building The project uses a unified build system. See [README-builder.md](../README-builder.md) for full details. ```bash # Show all available commands ./builder --help # Full project build (downloads pre-built engine + all modules) ./builder build # Build only the C++ engine ./builder server:build # Build specific modules ./builder nodes:build ./builder vscode:build ./builder client-typescript:build client-python:build ``` ### Build output | Directory | Contents | | --------------- | ----------------------------- | | `build/` | Temporary build artifacts | | `dist/` | Final distributable outputs | | `dist/server/` | Engine executable and runtime | | `dist/clients/` | Client library packages | | `dist/vscode/` | VS Code extension (`.vsix`) | ## Running ### Start the server After building, the engine executable is located in `dist/server/`. Run it directly: ```bash ./dist/server/engine ai/eaas.py ``` ### Connect the VS Code extension 1. Build the extension: `./builder vscode:build` 2. Install the generated `.vsix` from `dist/vscode/` in VS Code 3. Click the RocketRide icon in the sidebar and connect to your running server For VS Code extension development details, see [README-vscode.md](../README-vscode.md). ## Testing ```bash # Run all tests ./builder test # C++ engine tests only ./builder server:test # Python tests only (nodes, AI, clients) ./builder nodes:test ./builder ai:test ./builder client-python:test # TypeScript tests only ./builder client-typescript:test # Other module tests ./builder client-mcp:test ``` For information on writing and running node-level tests, see [README-node-testing.md](../README-node-testing.md). ## Further Reading - [Build System](../README-builder.md) -- declarative build system reference - [Engine Reference](../README-engine.md) -- C++ engine architecture, CLI options, task types - [Pipeline Nodes](../README-nodes.md) -- writing and extending pipeline nodes - [VS Code Extension](../README-vscode.md) -- extension development - [Pre-commit Hooks](../README-pre-commit-hooks.md) -- code quality automation - [Contributing Guide](../../CONTRIBUTING.md) -- contribution workflow and code style