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Overview

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Nodes are the building blocks of a RocketRide pipeline. A pipeline is a directed graph, and each node is one component that does one job: call a model, embed text, query a vector store, parse a document, or run a tool. You wire nodes together and the engine runs them.

This page explains how a node is structured on disk and how the runtime loads and executes it, then catalogs every node that ships with the toolchain, grouped by type.

Anatomy of a node

Each built-in node is a directory under nodes/src/nodes/<name>/. A node is its service manifest plus an implementation and its documentation:

nodes/src/nodes/llm_openai/
services.json # the manifest: identity, class type, capabilities, config schema
IGlobal.py # node-level lifecycle: config validation, dependency loading
IInstance.py # per-instance behaviour: what the node does each invocation
*_client.py # provider/client implementation detail
requirements.txt # Python dependencies, installed on demand
<name>.svg # canvas icon
README.md # co-located documentation (rendered as this node's page)

The services.json manifest is the contract the engine reads. Its key fields:

FieldPurpose
titleDisplay name on the canvas and in this catalog.
protocolThe node's URL scheme, e.g. llm_openai://.
classTypeThe kind of work the node does (llm, store, tool, …). Governs how it wires into the graph.
capabilitiesFlags that change engine behaviour, e.g. invoke.
registerHow the engine registers the node: filter (transforms data in the graph) or endpoint (an edge connector).
node / pathThe runtime (python) and module (nodes.llm_openai) the engine instantiates.
prefixPrefix swapped when converting between URLs and module paths.
descriptionProse shown in the editor.
configThe configuration schema: the fields a pipeline author fills in.

A node's public contract is its classType, config schema, and the input/output lanes it supports. The pipeline JSON reference documents how a node is referenced from a .pipe file (id, provider, config, input).

How the runtime runs a node

  1. Discovery & registration. On startup the engine scans every services*.json and registers a factory keyed by protocol/prefix. The register value decides whether the node is a filter in the graph or an endpoint connector at its edge.
  2. Instantiation. When a pipeline references a provider, the engine instantiates the implementation named by node and path. IGlobal runs once per node definition (it validates config and loads requirements.txt on demand); IInstance carries the per-invocation behaviour.
  3. Wiring. The classType determines how the node connects. Data nodes exchange data through lanes; agent, tool, llm, and memory nodes participate in control connections (see Agents & tools).
  4. Execution. The engine drives the graph from sources to targets, passing each node's output along its lanes. capabilities flags toggle engine features such as invoke. See the execution model for how data flows.

Because behaviour lives in provider + config, swapping which model or store a pipeline uses is a config edit, not a code change.

Node types

126 nodes across 21 types. Every node declares a class type in its manifest; the catalog below is grouped by it.

Sources

Bring data into a pipeline: webhooks, chat, file and database readers, and cloud connectors.

NodeDescription
ChatA user interface component that provides a web-based chat experience.
Drag & DropA user interface component that provides a web-based dropper experience.
Telegram BotA Telegram Bot source node that receives messages from users via the Telegram Bot API.
ToolsA source component that transfers no data: it exists to host tool nodes.
WebhookA user interface component that provides a web-based chat experience.
WebhookA source component that listens for incoming HTTP requests and accepts uploaded documents or data from external systems or processes.

LLMs

Call large language models for generation, chat, summarization, and reasoning across many providers.

NodeDescription
Amazon BedrockA component that connects to Amazon Bedrock, providing access to a range of foundation models from leading AI providers through a unified AWS interface.
AnthropicA component that integrates with Anthropic's Claude models for natural language understanding and generation.
Baidu QianfanA component that connects to Baidu Qianfan ERNIE large language models through Qianfan's OpenAI-compatible chat-completions API.
DeepseekA component that connects to DeepSeek’s large language models for advanced natural language processing.
GeminiA component that connects to Gemini models for advanced natural language processing.
GMI CloudA component that connects to GMI Cloud's large language models for advanced natural language processing.
Kimi (Moonshot)A component that connects to Moonshot AI's Kimi large language models for advanced natural language processing.
MiniMaxA component that connects to MiniMax's large language models for advanced natural language processing.
Mistral AIA component that connects to Mistral AI's advanced language models for natural language processing.
OllamaA component that integrates with locally-hosted language models through Ollama.
OpenAIA component that connects to OpenAI's latest GPT models for advanced natural language processing.
OpenAI-Compatible APIA component that connects to any OpenAI-compatible API endpoint for language model inference.
PerplexityA component that connects to Perplexity AI's Sonar models for advanced natural language processing with real-time web search capabilities.
QwenA component that connects to Alibaba Cloud's Qwen large language models via the DashScope API.
xAIA component that integrates with xAI's Grok language models for intelligent text generation and analysis.

Vision & Image

Analyze and transform images: vision models, OCR, thumbnails, cleanup, and accessibility descriptions.

NodeDescription
Accessibility DescribeAn accessibility-focused image analysis node that generates scene descriptions optimized for blind and visually impaired users.
CleanupA component that processes an image, cleans it up for OCR tasks by converting to gray scale, removing noise, deskewing, and enhancing contrast.
Gemini VisionA component that connects to Google Gemini's vision-capable models for image analysis, OCR, visual understanding, and scene description.
Mistral VisionA component that connects to Mistral AI's vision-capable models for image analysis, OCR, and visual understanding tasks.
OCRA component that extracts machine-readable text from images and scanned documents using optical character recognition.
Ollama VisionA component that connects to locally-hosted open-source vision models through Ollama for image analysis, description, and visual understanding tasks.
OpenAI VisionA component that connects to OpenAI's vision-capable models for image analysis, OCR, visual understanding, and scene description.
ThumbnailA processing component that creates thumbnails from input images.

Audio

Work with audio: transcription, text-to-speech, and playback.

NodeDescription
PlayerThe Audio Player component plays audio through the system’s default audio output device, including the audio track from video content.
Text To SpeechConverts incoming text into speech using Kokoro-82M (local KPipeline or --modelserver KokoroLoader).
TranscribeThe Audio transcribe component recieves audio or video and transcribes into text.

Video

Process video: frame extraction, embeddings, and video understanding.

NodeDescription
Frame GrabberA component that extracts frames from video files and outputs them as image data.
TwelveLabsSends a video to TwelveLabs along with instructions and returns the generated text response.

Text

Operate on text: summarization, extraction, named-entity recognition, and anonymization.

NodeDescription
Anomaly DetectorA pipeline monitoring component that detects anomalies in numeric output values using statistical methods.
AnonymizeA filter component that identifies and masks sensitive information in text data.
Answers to DocumentsAn adapter component that turns model/agent answers into embeddable documents.
Currency Convert (Explicit)An opt-in currency converter for the audit-grade financial extraction suite.
Data ExtractorA component that processes unstructured or semi-structured text and extracts structured data in a tabular format.
DictionaryA processing component that analyzes documents to extract a dictionary of key terms and phrases.
Fact ExtractorThe extraction brain.
Named Entity RecognitionA text processing component that identifies and extracts named entities from text using state-of-the-art transformer models.
Normalize FactsA deterministic fact normalizer for the audit-grade financial extraction suite.
PromptA transformation component that takes multiple inputs and merges them into a single question with a configurable prompt.
QuestionA transformation component that takes input text and encapsulates it as a Question object without modification.
Schema ValidateA guard node for the audit-grade financial extraction suite.
Summarization: LLMA processing component that analyzes document content to extract concise summaries, key points, and named entities.

Embeddings

Turn text, images, or video into vectors for semantic search and retrieval.

NodeDescription
ImageA processing component that generates vector embeddings from image content using advanced computer vision models.
OpenAI (Embedding)A component that transforms text into numerical vector representations using advanced embedding models.
TransformerA component that transforms text into numerical vector representations using advanced embedding models.
VideoA processing component that generates vector embeddings from video content by extracting frames at configurable intervals and encoding them using vision models such as CLIP.

Rerank

Reorder retrieved results by relevance to a query.

NodeDescription
Cohere RerankA reranking component powered by Cohere's Rerank API that improves search quality by reordering retrieved documents based on their relevance to a given query.

Query external search providers and the web.

NodeDescription
Exa SearchA direct Exa web search node.

Vector Stores

Store and query embeddings for retrieval: Qdrant, Pinecone, Milvus, Chroma, and more.

NodeDescription
Astra DBA vector database component for Astra DB, enabling efficient storage and retrieval of vector embeddings.
ChromaA vector database component for Chroma, enabling efficient storage and retrieval of vector embeddings.
ElasticsearchA vector database component for Elasticsearch, enabling efficient storage and retrieval of vector embeddings.
ElasticsearchA vector database component for Elasticsearch, enabling efficient storage and retrieval of vector embeddings.
File SystemFile system node.
MilvusA vector database component for Milvus, enabling efficient storage, indexing, and retrieval of vector embeddings.
MongoDB AtlasA vector database component for MongoDB Atlas, enabling efficient storage and retrieval of vector embeddings using MongoDB's native vector search capabilities.
OpenSearchAn OpenSearch node that supports classic BM25 search and vector search for ingestion and retrieval workflows.
PineconeA component that connects to the Pinecone vector database for storing and retrieving high-dimensional embeddings.
PostgreSQL (pgvector)A component that enhances PostgreSQL with vector similarity search capabilities through the pgvector extension.
QdrantA vector database component for Qdrant, enabling efficient storage and retrieval of vector embeddings.
RocketRide VectorA RocketRide-managed vector store backed by PostgreSQL + pgvector.
WeaviateA component that stores vector embeddings in a Weaviate instance for semantic search and retrieval.

Databases

Read from and write to relational and graph databases.

NodeDescription
Aparavi AQLQueries the Aparavi data governance platform using AQL (Aparavi Query Language).
ClickHouseA ClickHouse component that answers natural-language questions by translating them into SQL and executing them against the database, returning rows as a table, text, or structured answers.
MySQLA processing component that takes structured table data and inserts it into a MySQL database.
PostgreSQLA processing component that takes structured table data and inserts it into a PostgreSQL database.
RocketRide SQLA RocketRide-managed relational database.

Memory

Persist and recall conversational or working state across runs.

NodeDescription
Memory (Internal)Run-scoped keyed memory store exposed as agent tools.
Persistent MemoryA persistent cross-session memory node that retains data across pipeline invocations.

Agents

Autonomous nodes that plan and call tools to accomplish a goal.

NodeDescription
CrewAI AgentStandalone single-agent CrewAI node.
CrewAI AgentStandalone single-agent CrewAI node.
CrewAI ManagerMulti-agent manager using CrewAI hierarchical process.
CrewAI SubagentManaged CrewAI sub-agent.
Deep AgentSingle-agent execution using Deep Agents.
Deep AgentSingle-agent execution using Deep Agents.
DeepAgent SubagentManaged Deep Agent subagent.
LangChainSingle-agent execution using LangChain.
LlamaIndexSingle-agent execution using LlamaIndex's ReAct loop.
RocketRide WaveWave-planning agent built natively on the RocketRide architecture.

Tools

Capabilities an agent or pipeline can invoke: HTTP, shell, code execution, and external APIs.

NodeDescription
ApifyExposes Apify Actors as agent tools.
Bland AIMake and manage AI-powered phone calls via Bland AI.
Chart (Chart.js)Generates Chart.js v4 chart configurations from data using the pipeline LLM.
CogneePersistent semantic memory backed by a Cognee server, exposed as three agent tools.
DaytonaGives agents an isolated Daytona cloud sandbox for running code and shell commands.
DeepLExposes DeepL translation and AI rephrasing as agent tools.
Exa SearchExposes Exa semantic web search as an agent tool.
FirecrawlExposes Firecrawl web-scraping operations as agent tools.
GitExposes local Git repository operations as agent tools.
GitHubExposes GitHub repository operations as agent tools.
HTTP RequestMakes HTTP requests to any API endpoint, like curl for agents.
LaserData MemoryDurable, shared agent memory exposed as tools, backed by LaserData (Apache Iggy) via the Laser SDK.
MCP ClientConnects to the Butterbase MCP server and exposes its backend tools for agent tool-calling.
OuraExposes Oura Ring health data as read-only agent tools.
PipedriveExposes the Pipedrive CRM REST API v1 as agent tools.
Pipeline ToolExposes an inline pipeline as an agent tool.
PythonExecutes Python code in a restricted in-process sandbox via exec().
SlackExposes Slack workspace operations as agent tools.
TavilyExposes Tavily real-time web search as an agent tool.
v0 by VercelA component that connects to Vercel's v0 API to generate React + Tailwind CSS UI components from natural-language prompts.
xTrace MemoryLong-term, shared agent memory exposed as tools, backed by xTrace Memory Manager.

Preprocessors

Prepare and chunk data before embedding or model calls.

NodeDescription
CodeA specialized component designed to parse and tokenize source code.
General TextA preprocessing component that segments large bodies of text into intelligently sized chunks for downstream processing.
LLMA processing component that analyzes document content to extract concise summaries, key points, and named entities and to divide a document for storage into a vector database.

Data

Extract, shape, and route structured data within the pipeline.

NodeDescription
Guild.aiRun Guild.ai agents from a RocketRide pipeline or an agent.
LlamaParseA document parsing component that uses LlamaParse to extract text and structured data from various document formats including PDFs, images, Word documents, Excel spreadsheets, and other formats.
ReductoA parsing component that uses Reducto to extract text and structured data from various document formats including PDFs, images, and other document types.

Guardrails

Validate and constrain inputs and outputs for safety and policy.

NodeDescription
GuardrailsA comprehensive input/output guardrails filter for AI safety.

Outputs

Send results out of the pipeline: responses, files, and external systems.

NodeDescription
Local Text OutputA target component that writes data to the file system.
Text OutputA target component that writes data to the file system.

Infrastructure

Plumbing that supports execution rather than transforming data.

NodeDescription
Remote ProcessingA transport component that forwards data to a remote machine or processing node.
ResponseA component that returns processed answers back to the requesting client.

Graph Databases

Graph Databases nodes.

NodeDescription
ArangoDBA processing component that connects to an ArangoDB multi-model database.
FalkorDBA processing component that connects to a FalkorDB graph database.
HydraDBA database/tool node for HydraDB, a managed graph + memory store.
Neo4JA processing component that connects to a Neo4J graph database.
RocketRide GraphA RocketRide-managed graph database backed by PostgreSQL + Apache AGE.

Other

Nodes that do not fall into a single category above.

NodeDescription
CoreA combined configuration that bundles a preprocessor, embedding model, vector store, and LLM into a single selectable unit.
FingerprinterA processing component that generates a unique fingerprint (hash) of a document's content.
IBM Watson
Parse/Process/EmbedThis component combines document parsing, text preprocessing, and embedding generation in a single node.
ParserA document parsing component that extracts rich content from a wide variety of document types.
VectorizerAn internal filter that chunks incoming text, computes embeddings via the configured embedding component, and writes the resulting documents to the vector store.