Condition Block

The Condition block adds IF/ELSE branching to a workflow by evaluating a condition and routing execution down one of two paths — True or False. It supports boolean expressions for simple comparisons and LLM-as-a-Judge for complex, natural-language decisions that require AI reasoning.

Overview

When to Use

• Branch execution based on a previous block's output using a boolean expression
• Filter, validate, or classify data before sending it to downstream blocks
• Use AI to make a subjective judgment (tone, quality, relevance, sentiment) via LLM-as-a-Judge
• Route based on API response codes, string matches, or numeric comparisons
• Gate publishing or delivery steps on a confidence threshold from an LLM decision
• Replace a series of conditional checks with a single natural-language criteria prompt

Configuration

Evaluation Mode (evaluationMode)

Type: dropdown — required to select before other fields appear.

Selecting expression shows the Boolean Expression input. Selecting llm shows the LLM Judge fields (prompt, context, model, API key, and optional Azure fields).

Boolean Expression (conditions)

Type: condition-input
Visible when: evaluationMode = expression

Enter one or more boolean expressions. Each row is evaluated and the combined result determines the True or False path. Expressions support ==, !=, >, <, >=, <=, &&, ||, and .length checks against block outputs referenced with {{blockName.field}}.

Example placeholder: {{agent1.content}}==1 or content.length > 10

LLM Judge Prompt (llmPrompt)

Type: long-input (4 rows)
Visible when: evaluationMode = llm

Describe the criteria for the LLM to evaluate. The LLM will respond YES or NO based on this prompt. Be specific and unambiguous.

Example: Is the content positive and professional in tone?

Context for Evaluation (llmContext)

Type: long-input (3 rows)
Visible when: evaluationMode = llm

Provide the data you want the LLM to judge. Reference a previous block's output using {{blockName.field}}.

Example: {{agent1.content}}

LLM Model (llmModel)

Type: combobox — required when using LLM mode
Visible when: evaluationMode = llm

Select or type the model name to use for judging. Options are populated dynamically from all configured base model providers plus any locally running Ollama models. Examples include gpt-5.4-mini, claude-haiku-4-5, gemini-3.5-flash, and any Ollama model name.

API Key (apiKey)

Type: short-input (password)
Visible when: evaluationMode = llm AND the selected model is not a hosted/Ollama model (i.e., requires an explicit API key)

Enter the API key for the chosen model's provider. Use an environment variable reference such as {{OPENAI_API_KEY}} rather than pasting the key directly.

Azure OpenAI Endpoint (azureEndpoint)

Type: short-input (password)
Visible when: evaluationMode = llm AND an Azure OpenAI model is selected

The full Azure OpenAI resource endpoint URL.

Example: https://your-resource.openai.azure.com

Azure API Version (azureApiVersion)

Type: short-input
Visible when: evaluationMode = llm AND an Azure OpenAI model is selected

The Azure OpenAI API version string.

Example: 2024-07-01-preview

Require High Confidence (requireConfidence)

Type: switch
Visible when: evaluationMode = llm

When enabled, the block only treats an LLM YES decision as True if the model's reported confidence score exceeds 80%. Decisions below that threshold fall through to the False path.

Inputs & Outputs

• Inputs: none — the Condition block has no declared inputs; all data comes from sub-block fields referencing other blocks via {{blockName.field}} syntax.

• Outputs:

  • content (string) — Condition evaluation content or LLM reasoning text
  • conditionResult (boolean) — Boolean result of the condition evaluation (true routes to the True path, false to the False path)
  • selectedPath (json) — Information about the execution path that was selected, including blockId, blockType, and blockTitle of the downstream block
  • selectedConditionId (string) — Identifier of the selected path (true or false)
  • llmJudgement (json) — LLM judgement details when using LLM mode; contains reasoning (string), confidence (number 0–1), model (string), and decision (yes or no)

Tools

This block uses no external tools. In expression mode the evaluation runs entirely in the executor. In llm mode the block calls a provider directly through the Zelaxy provider layer (not the tool registry) using the credentials and model configured in the sub-blocks.

YAML Example

# Boolean expression mode — route based on an agent's classification output
condition_1:
  type: condition
  name: "Check Urgency"
  inputs:
    evaluationMode: expression
    conditions:
      - left: "{{agent1.content}}"
        operator: "=="
        right: "urgent"
  connections:
    outgoing:
      - target: slack_notify        # True path
      - target: log_low_priority    # False path

# LLM-as-a-Judge mode — AI evaluates tone and professionalism
condition_2:
  type: condition
  name: "Content Quality Check"
  inputs:
    evaluationMode: llm
    llmPrompt: "Is this content professional, factual, and free of harmful language?"
    llmContext: "{{agent1.content}}"
    llmModel: gpt-5.4-mini
    apiKey: "{{OPENAI_API_KEY}}"
    requireConfidence: true
  connections:
    outgoing:
      - target: publish_block      # True path (YES with >80% confidence)
      - target: rejection_response # False path