Passthrough Node

The Passthrough node is the simplest node type. It performs no operations and passes received messages to downstream nodes. By default, it only passes the last message. It is primarily used for graph structure "wire management" optimization and context control.

Configuration

Field	Type	Required	Default	Description
`only_last_message`	bool	No	`true`	Whether to pass only the last message. Set to `false` to pass all messages.

Basic Configuration

yaml

config: {}  # Uses default configuration, only passes the last message

Pass All Messages

yaml

config:
  only_last_message: false  # Pass all received messages

Core Concepts

Pass-through Behavior

Receives all messages passed from upstream
By default, only passes the last message (only_last_message: true)
When only_last_message: false, passes all messages
Does not perform any content processing or transformation

Graph Structure Optimization

The core value of the Passthrough node is not in data processing, but in graph structure optimization ("wire management"):

Makes complex edge connections clearer
Centrally manages outgoing edge configurations (such as keep_message)
Serves as a logical dividing point, improving workflow readability

Key Uses

1. As an Entry Node to Preserve Initial Context

Using Passthrough as the workflow entry node, combined with the keep_message: true edge configuration, ensures that the user's initial task is always preserved in the context and won't be overwritten by subsequent node outputs:

yaml

nodes:
  - id: Task Keeper
    type: passthrough
    config: {}

  - id: Worker A
    type: agent
    config:
      provider: openai
      name: gpt-4o

  - id: Worker B
    type: agent
    config:
      provider: openai
      name: gpt-4o

edges:
  # Distribute tasks from entry, preserving original message
  - from: Task Keeper
    to: Worker A
    keep_message: true  # Preserve initial task context

  - from: Task Keeper
    to: Worker B
    keep_message: true

start: [Task Keeper]

Effect: Both Worker A and Worker B can see the user's original input, not just the output from the previous node.

2. Filtering Redundant Output in Loops

In workflows containing loops, nodes within the loop may produce a large amount of intermediate output. Passing all outputs to subsequent nodes would cause context bloat. Using a Passthrough node allows you to pass only the final result of the loop:

yaml

nodes:
  - id: Iterative Improver
    type: agent
    config:
      provider: openai
      name: gpt-4o
      role: Continuously improve output based on feedback

  - id: Evaluator
    type: agent
    config:
      provider: openai
      name: gpt-4o
      role: |
        Evaluate output quality, reply GOOD or provide improvement suggestions

  - id: Result Filter
    type: passthrough
    config: {}

  - id: Final Processor
    type: agent
    config:
      provider: openai
      name: gpt-4o
      role: Post-process the final result

edges:
  - from: Iterative Improver
    to: Evaluator
  
  # Loop: Return to improvement node when evaluation fails
  - from: Evaluator
    to: Iterative Improver
    condition:
      type: keyword
      config:
        none: [GOOD]
  
  # Loop ends: Filter through Passthrough, only pass the last message
  - from: Evaluator
    to: Result Filter
    condition:
      type: keyword
      config:
        any: [GOOD]
  
  - from: Result Filter
    to: Final Processor

start: [Iterative Improver]
end: [Final Processor]

Effect: Regardless of how many loop iterations occur, Final Processor will only receive the last output from Evaluator (the one indicating quality passed), not all intermediate results.

Other Uses

Placeholder: Reserve node positions during design phase
Conditional branching: Implement routing logic with conditional edges
Debugging observation point: Insert nodes for easy observation in the workflow

Examples

Basic Usage

yaml

nodes:
  - id: Router
    type: passthrough
    config: {}

Conditional Routing

yaml

nodes:
  - id: Classifier
    type: agent
    config:
      provider: openai
      name: gpt-4o
      role: |
        Classify input content, reply TECHNICAL or BUSINESS

  - id: Router
    type: passthrough
    config: {}

  - id: Tech Handler
    type: agent
    config:
      provider: openai
      name: gpt-4o

  - id: Biz Handler
    type: agent
    config:
      provider: openai
      name: gpt-4o

edges:
  - from: Classifier
    to: Router
  - from: Router
    to: Tech Handler
    condition:
      type: keyword
      config:
        any: [TECHNICAL]
  - from: Router
    to: Biz Handler
    condition:
      type: keyword
      config:
        any: [BUSINESS]

Best Practices

Use meaningful node IDs that describe their topological role (e.g., Task Keeper, Result Filter)
When used as an entry node, configure outgoing edges with keep_message: true to preserve context
Use after loops to filter out redundant intermediate output