LibreAI / Entwickler-Tools / rocketride-server

// devtools · rocketride-org/rocketride-server

rocketride-server

rocketride-server ist ein Open-Source-Projekt aus der Kategorie Entwickler-Tools von rocketride-org (rocketride-org/rocketride-server auf GitHub). Es hat 17.818 Sterne auf GitHub und 7.606 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 8. Oktober 2026 auf GitHub aktualisiert.

A high-performance AI pipeline engine - build LLM workflows as portable .pipe files

★ 17,8 Tsd. Sterne⑂ 7,6 Tsd. ForksMITaktualisiert Okt 2026

Auf GitHub ansehen ↗

▦ Visual — das README dieses Projekts enthält keinen einbettbaren Screenshot,
darum hier ein Platzhalter. Die Anleitung unten ist trotzdem vollständig.

// projektdaten

Projektdaten

Repository: rocketride-org/rocketride-server
GitHub-Sterne: 17.818
Forks: 7.606
Lizenz: MIT
Zuletzt auf GitHub aktualisiert: 8. Oktober 2026
Kategorie: Entwickler-Tools
Eintragstyp: Vollständige Installationsanleitung

// so funktioniert es

So funktioniert es

Sketch your first pipeline
Decide the flow - source, an LLM node, a response - for one concrete AI feature.
Get RocketRide
Install the Python or TypeScript SDK and the VS Code extension for visual building and debugging.
Add a model key
Drop an llm node into the pipeline and add one provider API key.
Run your first pipe
Execute the pipeline locally, inspect it with the built-in observability, then deploy the same file anywhere.

// funktionen

Warum es so beliebt ist

C++ pipeline engine

A high-performance core executes pipelines built from 50+ extensible nodes.

Visual building and debugging

Design and debug workflows from your IDE with the included VS Code extension.

Many providers and vector DBs

Connects 13+ model providers and 8+ vector databases as pipeline nodes.

Agent orchestration

Pipelines can include agent nodes with tools alongside RAG and data-processing nodes.

Portable pipelines

The same .pipe file runs on Cloud, on-prem, or as a local process in your IDE with zero lock-in.

Built-in observability

Inspect pipeline runs while developing and in production.

// selbst ausführen

Führe es selbst aus

Clone the repository

Get the source code from GitHub and enter the project directory.

git clone https://github.com/rocketride-org/rocketride-server.git
cd rocketride-server

Install the SDK
Add RocketRide to your Python project (a TypeScript SDK is also published on npm).
```
pip install rocketride
```
Build your first pipe
Follow the README's first-pipe walkthrough: source, an llm node with one API key, and a response.
```
# Follow 'Your first AI feature' in the README, then try examples/rag-pipeline.pipe
```

// anwendungsfälle

Was du damit bauen kannst

Ship a document Q&A feature using the included RAG pipeline example
Prototype an LLM workflow visually, then embed it in a Python service
Move a pipeline from laptop to on-prem servers without rewriting it
Standardize how a team builds and observes AI features

// häufige fragen

Häufige Fragen

Who maintains this project?

It is maintained by the RocketRide project (rocketride-org) on GitHub.

Is it free to use?

The on-prem engine is free and MIT licensed. RocketRide Cloud is a paid managed hosting option with the same portable pipelines.

Does it need a paid API key?

Pipelines that call hosted models need your own provider API keys; local components such as a local Qdrant instance can run without them.

How does it compare to alternatives?

Compared with code-only frameworks, RocketRide is a visual, engine-based approach with portable pipeline files and IDE debugging; compared with hosted workflow tools, the same pipelines also run fully on-prem.

How do I get started?

Run pip install rocketride, install the VS Code extension, and build the README's first pipe with one LLM node.

// weiter entdecken

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Hol dir rocketride-server

Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.

Auf GitHub ansehen ↗← Mehr Tools: Entwickler-Tools