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ROCKET RIDE
Open-source AI pipeline engine for production workflows
MIT
ABOUT
Building production AI workflows that chain together LLM calls, vector search, document processing, and custom logic typically requires stitching together disparate libraries and managing complex infrastructure. Rocket Ride solves this by providing a visual pipeline builder (VS Code extension), a high-performance C++ runtime, and SDKs for Python, TypeScript, and MCP — all in one open-source platform. Its 85+ pre-built nodes cover LLM providers, vector databases, OCR, NER, chunking, embeddings, and more, all composable as portable JSON pipelines that run on your own infrastructure with no vendor lock-in.
INSTALL
pip install rocketride
npm install rocketrideINTEGRATION GUIDE
1. Build multi-step RAG pipelines that chain document ingestion, chunking, embedding, and LLM querying
2. Create production data processing workflows with OCR, NER, PII anonymization, and structured extraction
3. Orchestrate multi-agent AI workflows combining CrewAI and LangChain agents within pipeline nodes
4. Deploy AI pipelines as callable tools via MCP server for AI assistant integration
5. Run high-throughput batch inference and embedding jobs on the multithreaded C++ runtime
TAGS
pipelinellmworkflowdata-processingvs-codepythoncppai-engineering