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Blocks

Blocks are the building components you connect together to create AI workflows. Think of them as specialized modules that each handle a specific task—from chatting with AI models to making API calls or processing data.

Core Block Types​

Klyntos provides seven core block types that handle the essential functions of AI workflows:

Processing Blocks​

  • Agent - Chat with AI models (OpenAI, Anthropic, Google, local models)
  • Function - Run custom JavaScript/TypeScript code
  • API - Connect to external services via HTTP requests

Logic Blocks​

  • Condition - Branch workflow paths based on boolean expressions
  • Router - Use AI to intelligently route requests to different paths
  • Evaluator - Score and assess content quality using AI

Output Blocks​

  • Response - Format and return final results from your workflow

How Blocks Work​

Each block has three main components:

Inputs: Data coming into the block from other blocks or user input Configuration: Settings that control how the block behaves Outputs: Data the block produces for other blocks to use

Receive Input: Block receives data from connected blocks or user input

Process: Block processes the input according to its configuration

Output Results: Block produces output data for the next blocks in the workflow

Connecting Blocks​

You create workflows by connecting blocks together. The output of one block becomes the input of another:

  • Drag to connect: Drag from an output port to an input port
  • Multiple connections: One output can connect to multiple inputs
  • Branching paths: Some blocks can route to different paths based on conditions

Common Patterns​

Sequential Processing​

Connect blocks in a chain where each block processes the output of the previous one:

User Input → Agent → Function → Response

Conditional Branching​

Use Condition or Router blocks to create different paths:

User Input → Router → Agent A (for questions)
                   → Agent B (for commands)

Quality Control​

Use Evaluator blocks to assess and filter outputs:

Agent → Evaluator → Condition → Response (if good)
                              → Agent (retry if bad)

Block Configuration​

Each block type has specific configuration options:

All Blocks:

  • Input/output connections
  • Error handling behavior
  • Execution timeout settings

AI Blocks (Agent, Router, Evaluator):

  • Model selection (OpenAI, Anthropic, Google, local)
  • API keys and authentication
  • Temperature and other model parameters
  • System prompts and instructions

Logic Blocks (Condition, Function):

  • Custom expressions or code
  • Variable references
  • Execution environment settings

Integration Blocks (API, Response):

  • Endpoint configuration
  • Headers and authentication
  • Request/response formatting