> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bindai.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# 06.4 conditions

# Conditions

Condition nodes allow a workflow to make decisions at runtime.

Instead of always following the same execution path, a condition evaluates the current workflow context and chooses the next branch based on the result.

Conditions make workflows dynamic and responsive to changing inputs.

***

# What is a Condition?

A condition evaluates a predicate that returns either **True** or **False**.

Conceptually:

```text id="cond1" theme={null}
Workflow Context

↓

Condition

↙       ↘

True     False
```

Only one branch continues execution.

***

# Why Use Conditions?

Without conditions, every workflow follows a fixed sequence.

With conditions, workflows can:

* make business decisions
* validate data
* choose different agents
* skip unnecessary steps
* handle success and failure differently

***

# Branching Logic

A condition creates two possible execution paths.

```text id="cond2" theme={null}
Agent

↓

Condition

↙           ↘

Approved    Rejected
```

Each branch may continue with completely different workflow logic.

***

# Condition Predicate

A condition uses a predicate function.

Conceptually:

```python id="cond3" theme={null}
lambda context: True
```

The predicate examines the workflow context and returns a Boolean value.

***

# Using Workflow Variables

Conditions commonly evaluate workflow variables.

Example:

```text id="cond4" theme={null}
Variables

approved = True

↓

Condition

↓

Approved Branch
```

Variables are usually created by previous workflow nodes.

***

# Example

A support agent determines whether a request should be approved.

```text id="cond5" theme={null}
Support Agent

↓

approved = True

↓

Condition

↓

Approval Workflow
```

If approval is denied:

```text id="cond6" theme={null}
Support Agent

↓

approved = False

↓

Condition

↓

Rejection Workflow
```

***

# Common Uses

Condition nodes are useful for:

* approval decisions
* confidence thresholds
* validation results
* user permissions
* payment status
* inventory availability
* workflow routing

***

# Multiple Decisions

Complex workflows often contain several condition nodes.

```text id="cond7" theme={null}
Agent

↓

Condition

↓

Tool

↓

Condition

↓

End
```

Each decision influences the remaining execution path.

***

# Condition vs Prompt Logic

Instead of asking a language model to decide what should happen next inside a prompt, BindAI separates orchestration from reasoning.

| Prompt Logic           | Condition Node    |
| ---------------------- | ----------------- |
| Hidden in prompt       | Explicit workflow |
| Difficult to debug     | Easy to inspect   |
| Mixed responsibilities | Clear separation  |
| Hard to reuse          | Reusable          |

This separation makes workflows easier to maintain.

***

# Context Access

Condition predicates have access to the workflow context.

Conceptually:

```text id="cond8" theme={null}
Workflow Context

↓

Variables

↓

Condition

↓

Next Branch
```

This allows decisions to be based on results produced anywhere earlier in the workflow.

***

# Chaining Conditions

Conditions can be chained together.

```text id="cond9" theme={null}
Condition A

↓

Condition B

↓

Condition C
```

This allows workflows to model increasingly sophisticated decision trees.

***

# Error Handling

Conditions should evaluate predictable values.

If required variables are missing, consider:

* providing default values
* validating input before the condition
* handling unexpected states explicitly

Keeping predicates simple improves reliability.

***

# Best Practices

* Keep predicates small and readable.
* Base decisions on workflow variables rather than prompt text.
* Avoid embedding business logic inside agents.
* Use descriptive variable names.
* Keep branches easy to understand.
* Prefer several simple conditions over one complex predicate.

***

# Summary

Condition nodes provide branching logic for BindAI workflows.

By evaluating workflow context and selecting the appropriate execution path, conditions enable workflows to adapt dynamically while keeping business logic separate from language model reasoning.