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Conditional branching lets you create dynamic workflows that take different paths based on runtime conditions. Use the if: pattern to evaluate variables and route execution accordingly.

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Quick Start

from praisonaiagents import AgentFlow, WorkflowContext, StepResult
from praisonaiagents.workflows import if_

def approve(ctx: WorkflowContext) -> StepResult:
    return StepResult(output="Approved!")

def reject(ctx: WorkflowContext) -> StepResult:
    return StepResult(output="Rejected!")

workflow = AgentFlow(
    steps=[
        if_(
            condition="{{score}} >= 70",
            then_steps=[approve],
            else_steps=[reject]
        )
    ],
    variables={"score": 85}
)
result = workflow.start("Evaluate")
# Output: "Approved!"

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Condition Syntax

Numeric Comparisons

>, <, >=, <=, ==, !=

String Equality

==, != for exact matches

Contains Check

in or contains keywords

Boolean Values

true, false for flags

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Numeric Comparisons

Compare numbers using standard operators: 
# Greater than
if_(condition="{{score}} > 80", then_steps=[...])

# Less than or equal
if_(condition="{{count}} <= 10", then_steps=[...])

# Equal
if_(condition="{{age}} == 18", then_steps=[...])

# Not equal
if_(condition="{{status_code}} != 200", then_steps=[...])

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String Equality

Match exact string values: 
# String equals
if_(
    condition="{{status}} == approved",
    then_steps=[process_approved],
    else_steps=[process_pending]
)

# String not equals
if_(
    condition="{{tier}} != free",
    then_steps=[premium_features]
)

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Contains Check

Check if a string contains a substring: 
# Using 'in' keyword
if_(
    condition="error in {{message}}",
    then_steps=[handle_error],
    else_steps=[continue_normal]
)

# Using 'contains' keyword
if_(
    condition="{{response}} contains success",
    then_steps=[celebrate]
)

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Nested Property Access

Access nested object properties: 
workflow = AgentFlow(
    steps=[
        if_(
            condition="{{user.subscription.tier}} == premium",
            then_steps=[premium_service]
        )
    ],
    variables={
        "user": {
            "name": "Alice",
            "subscription": {"tier": "premium"}
        }
    }
)

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If Without Else

The else_steps parameter is optional. If omitted, nothing happens when the condition is false: 
# Only send notification if opted in
workflow = AgentFlow(
    steps=[
        if_(
            condition="{{notify}} == true",
            then_steps=[send_notification]
            # No else - just skip if false
        ),
        continue_workflow  # Always runs
    ],
    variables={"notify": "true"}
)

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If Inside Loop

Combine conditional branching with loops for per-item decisions: 
from praisonaiagents import AgentFlow, WorkflowContext, StepResult
from praisonaiagents.workflows import if_, loop

def vip_service(ctx: WorkflowContext) -> StepResult:
    customer = ctx.variables.get("customer", {})
    return StepResult(output=f"VIP service for {customer['name']}")

def standard_service(ctx: WorkflowContext) -> StepResult:
    customer = ctx.variables.get("customer", {})
    return StepResult(output=f"Standard service for {customer['name']}")

workflow = AgentFlow(
    steps=[
        loop(
            steps=[
                if_(
                    condition="{{customer.tier}} == premium",
                    then_steps=[vip_service],
                    else_steps=[standard_service]
                )
            ],
            over="customers",
            var_name="customer"
        )
    ],
    variables={
        "customers": [
            {"name": "Alice", "tier": "premium"},
            {"name": "Bob", "tier": "standard"},
            {"name": "Charlie", "tier": "premium"}
        ]
    }
)
workflow.start("Assign services")

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Nested Conditions

Create decision trees with nested if statements: 
workflow = AgentFlow(
    steps=[
        if_(
            condition="{{tier}} == premium",
            then_steps=[
                # Nested condition for premium users
                if_(
                    condition="{{spend}} > 10000",
                    then_steps=[vip_treatment],
                    else_steps=[regular_premium]
                )
            ],
            else_steps=[basic_support]
        )
    ],
    variables={"tier": "premium", "spend": 15000}
)

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API Reference

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if_() Function

def if_(
    condition: str,
    then_steps: List[Any],
    else_steps: Optional[List[Any]] = None
) -> If
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condition
string
required
Condition expression with {{variable}} placeholders
​
then_steps
list
required
Steps to execute when condition is true
​
else_steps
list
Steps to execute when condition is false (optional)

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If Class

from praisonaiagents.workflows import If

conditional = If(
    condition="{{score}} > 80",
    then_steps=[approve],
    else_steps=[reject]
)

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MAX_NESTING_DEPTH

from praisonaiagents.workflows import MAX_NESTING_DEPTH

print(MAX_NESTING_DEPTH)  # 5
Nested conditions count toward the maximum nesting depth of 5 levels.

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Best Practices

Make conditions readable: {{user.is_verified}} == true is clearer than {{v}} == 1
Handle missing variables gracefully - undefined variables evaluate to empty strings
Each branch should do one thing well. Complex logic should be in separate functions.
Always test both the true and false paths of your conditions

Nested Workflows

Combine patterns for complex pipelines

Workflow Routing

Route based on output content

Workflow Loops

Iterate over collections

YAML Workflows

Define workflows in YAML format