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Components (sometimes called Processors or Nodes) are the fundamental executable blocks inside a Workflow Definition. Each component adheres to a specific Interface (e.g., genai.chat.openai) which dictates its input ports, output ports, routing logic, and functional behavior. Below is an overview of the supported taxonomy of component interfaces natively powered by BlobHub.

Component Taxonomy

Flow Control (flow.*)

These handle the fundamental initiation and termination of the logic loop.
  • flow.start: The absolute entry point of the execution.
  • flow.end: A terminal endpoint resolving the execution gracefully.
  • flow.goto: A redirect node pointing to another discrete location.

Data Variables (data.*)

Static blocks providing statically typed constants injected dynamically into the runtime graph.
  • data.integer: Hardcodes a number.
  • data.message: Hardcodes a rich semantic AI message prompt.
  • data.messages: Hardcodes conversation history arrays.

Logic (logic.*)

Control branching, data manipulation, and programming logic.
  • logic.code: Escapes the interface into raw Python sandboxes (See Code Component).
  • logic.generic_provider: Injects generic authenticated API blocks.
  • logic.for: Loops over input arrays.
  • logic.sleep: Pauses execution dynamically.
  • logic.insert: Injects dynamic text strings into payload templates.

Generative AI Chat (genai.chat.*)

High-level native integrations to industry-leading Large Language Models.
  • genai.chat.openai: Connects to OpenAI models (GPT-4o, etc).
  • genai.chat.anthropic: Connects to Anthropic (Claude 3.5 Sonnet, etc).
  • genai.chat.gemini: Connects to Google Gemini integrations.
  • genai.chat: Abstract router delegating to arbitrary endpoints based on payloads.

Generative AI Agents (genai.agent.*)

Recursive execution loops allowing LLMs to invoke tools autonomously.
  • genai.agent.basic: Implements a standard reasoning and execution (ReAct) agent looping wrapper mapping tools natively to workflow functions.

Vector Database (database.vector.*)

Semantic search integrations natively wired to external retrieval-augmented generation (RAG) providers.
  • database.vector.pinecone: Direct Pinecone ingestion and search.
  • database.vector.ingest: Abstract interface pushing embeddings.
  • database.vector.retrieve: Abstract interface pulling similarity searches.

The Web (web.*)

Fetching, scraping, and dynamically parsing the actual internet.
  • web.scrape: General HTML fetching.
  • web.scrape.firecrawl: Sophisticated headless browser scraping via Firecrawl.
  • web.search: General SERP queries.
  • web.search.tavily: Web synthesis and targeted searching via Tavily.

Text Processing (text.*)

Splitting and parsing text.
  • text.chunk: Breaks down giant documents into smaller token-ready vectors for database storage.
  • text.render_template: Parses Jinja templates with dynamic arguments.