[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-75126":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":37,"readmeContent":38,"aiSummary":39,"trendingCount":16,"starSnapshotCount":16,"syncStatus":40,"lastSyncTime":41,"discoverSource":42},75126,"rocketride-server","rocketride-org\u002Frocketride-server","rocketride-org","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\u002FPython SDKs, and Docker deployment.","",null,"C++",3802,1229,4,107,0,6,65,492,18,103.27,"MIT License",false,"develop",true,[27,28,29,30,31,32,33,34,35,36],"ai","cpp","data-pipeline","data-processing","machine-learning","mcp","python","sdk","typescript","vscode-extension","2026-06-12 04:01:17","\u003Cdiv align=\"center\">\n\n\u003Ca href=\"https:\u002F\u002Frocketride.org\">\n  \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Fbanner-root.png\" alt=\"RocketRide\" width=\"100%\">\n\u003C\u002Fa>\n\n\u003Cp>\n  Open-source, developer-native AI pipeline tool.\u003Cbr\u002F>\n  Build, debug, and deploy production AI workflows - without leaving your IDE.\n\u003C\u002Fp>\n\n\u003Cp>\n\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Ficon-cpp.png\" alt=\"C++\" \u002F>  \n\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Ficon-python.png\" alt=\"Python\" \u002F>  \n\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Ficon-typescript.png\" alt=\"TypeScript\" \u002F>\n\u003C\u002Fp>\n\n\u003Cp>\n 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.\n\u003C\u002Fp>\n\n\u003Cp>\n  \u003Ca href=\"https:\u002F\u002Frocketride.org\">Home\u003C\u002Fa> |\n  \u003Ca href=\"https:\u002F\u002Fdocs.rocketride.org\u002F\">Documentation\u003C\u002Fa> |\n  \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Frocketride\u002F\">Python SDK\u003C\u002Fa> |\n  \u003Ca href=\"https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Frocketride\">TypeScript SDK\u003C\u002Fa> |\n  \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Frocketride-mcp\u002F\">MCP Server\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Frocketride-org\u002Frocketride-server\u002Factions\u002Fworkflows\u002Fci.yml\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Frocketride-org\u002Frocketride-server\u002Factions\u002Fworkflows\u002Fci.yml\u002Fbadge.svg\" alt=\"CI\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Frocketride-org\u002Frocketride-server\u002Freleases\u002Ftag\u002Fserver-v3.1.0\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRuntime-v3.1.0-5f2167?logo=data:image\u002Fsvg%2bxml;base64,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\" alt=\"Engine v3.1.0\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002F9hr3tdZmEG\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-Join-370b7a?logo=discord&logoColor=white\" alt=\"Discord\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Frocketride-org\u002Frocketride-server\u002Fblob\u002Fdevelop\u002FLICENSE\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-MIT-41b6e6\" alt=\"MIT License\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Fscreenshot-ide.png\" alt=\"Build and run AI pipelines inside your IDE\" width=\"100%\">\n\n_Design, test, and ship complex AI workflows from a visual canvas, right where you write code._\n\n\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Fscreenshot-sdk.png\" alt=\"Integrate real AI solutions using a simple SDK\" width=\"100%\">\n\n_Drop pipelines into any Python or TypeScript app with a few lines of code, no infrastructure glue required._\n\n\u003C\u002Fdiv>\n\n## Features\n\n| Feature                           | Description                                                                                                                                                                                                                          |\n| :-------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| **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. |\n| **High-Performance C++ Runtime**  | Native multithreading purpose-built for the throughput demands of AI and data workloads. No bottlenecks, no compromises for production scale.                                                                                        |\n| **50+ 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.                                                    |\n| **Multi-Agent Workflows**         | Built-in CrewAI and LangChain support. Chain agents, share memory across pipeline runs, and manage multi-step reasoning at scale.                                                                                                    |\n| **Coding Agent Ready**            | RocketRide auto-detects your coding agent — Claude, Cursor, and more. Build, modify, and deploy pipelines through natural language.                                                                                                  |\n| **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.                                                                                  |\n| **Zero Dependency Headaches**     | Python environments, C++ toolchains, Java\u002FTika, and all node dependencies managed automatically. Clone, build, run — no manual setup.                                                                                                |\n| **One-Click Deploy**              | Run on Docker, on-prem, or RocketRide Cloud (coming soon). Production-ready architecture from day one — not retrofitted from a demo.                                                                                                 |\n\n## Quick Start\n\n1. Install the extension for your IDE. Search for RocketRide in the extension marketplace:\n\n   \u003Cp align=\"center\">\n     \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Finstall.png\" alt=\"Install RocketRide extension\">\n   \u003C\u002Fp>\n\n   \u003Csub>[Not seeing your IDE? Open an issue](https:\u002F\u002Fgithub.com\u002Frocketride-org\u002Frocketride-server\u002Fissues\u002Fnew) · [Download directly](https:\u002F\u002Fopen-vsx.org\u002Fextension\u002FRocketRide\u002Frocketride)\u003C\u002Fsub>\n\n2. Click the RocketRide extension in your IDE\n\n3. Deploy a server - you'll be prompted on how you want to run the server. Choose the option that fits your setup:\n\n   - **Local (Recommended)** - This pulls the server directly into your IDE without any additional setup.\n   - **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).\n\n## Building Your First Pipe\n\n1. 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.\n\n2. 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:\u002F\u002Fdocs.rocketride.org\u002F).\n\n3. 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:\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Ffirst_pipe.gif\" alt=\"Pipeline canvas example\" width=\"100%\">\n\u003C\u002Fp>\n\n4. You can run a pipeline from the canvas by pressing the ▶ button on the source node or from the `Connection Manager` directly.\n\n5. Deploy your pipelines on your own infrastructure.\n\n   - **Docker** - Download the RocketRide server image and create a container. Requires [Docker](https:\u002F\u002Fdocs.docker.com\u002Fget-docker\u002F) to be installed.\n\n     ```bash\n     docker pull ghcr.io\u002Frocketride-org\u002Frocketride-engine:latest\n     docker create --name rocketride-engine -p 5565:5565 ghcr.io\u002Frocketride-org\u002Frocketride-engine:latest\n     ```\n\n   - **Local Deployment** - Download your preferred runtime as a standalone process from the **Deploy** page in the `Connection Manager`.\n\n6. Run your pipelines as standalone processes or integrate them into your existing [Python](https:\u002F\u002Fdocs.rocketride.org\u002Fsdk\u002Fpython-sdk) and [TypeScript\u002FJS](https:\u002F\u002Fdocs.rocketride.org\u002Fsdk\u002Fnode-sdk) applications utilizing our SDK.\n\n## Observability\n\nSelecting 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.\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Frocketride-org\u002Frocketride-server\u002Fdevelop\u002Fimages\u002Ftracing.gif\" alt=\"Pipeline observability and tracing\">\n\u003C\u002Fp>\n\n## Contributors\n\nRocketRide 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.\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Frocketride-org\u002Frocketride-server\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg alt=\"contributors\" src=\"https:\u002F\u002Fcontrib.rocks\u002Fimage?repo=rocketride-org\u002Frocketride-server&columns=16\" width=\"100%\" \u002F>\n\u003C\u002Fa>\n\n---\n\n\u003Cp align=\"center\">Made with ♥ in SF & EU\u003C\u002Fp>\n","RocketRide 是一个高性能的AI流水线引擎，具有C++核心和超过50个可由Python扩展的节点。其核心功能包括支持13种以上的模型提供商、8种以上的向量数据库以及代理编排，允许用户在IDE中构建、调试和扩展LLM工作流。该项目提供了VS Code扩展、TypeScript\u002FPython SDKs及Docker部署方案，特别适合需要高效处理数据管道并进行机器学习或AI应用开发的场景。通过定义为JSON格式的便携式管道，开发者可以在本地基础设施上实现从实时数据处理到多模态AI搜索等多种任务。",2,"2026-06-11 03:52:25","high_star"]