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Hooks

Intercept and modify agent behavior at various lifecycle points. Unlike callbacks (which are for UI events), hooks can intercept, modify, or block tool execution.

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Quick Start

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Simplest Usage

from praisonaiagents import Agent
from praisonaiagents.hooks import add_hook

# Register hooks with simple string events
@add_hook('before_tool')
def log_tools(event_data):
    print(f"Tool: {event_data.tool_name}")
    # No return needed - defaults to allow

@add_hook('before_tool')
def security_check(event_data):
    if "delete" in event_data.tool_name.lower():
        return "Delete operations blocked"  # String = deny with reason
    # No return = allow

# Agent automatically uses registered hooks
agent = Agent(
    name="SecureAssistant",
    instructions="You are a helpful assistant."
)

agent.start("Help me organize my files")
Tip: Hook returns are simple:
  • None or no return → Allow
  • False → Deny
  • "reason" → Deny with custom message

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Agent-Centric Usage

from praisonaiagents import Agent
from praisonaiagents.hooks import HookRegistry, HookEvent, HookResult, BeforeToolInput

# Create a hook registry
registry = HookRegistry()

# Log all tool calls
@registry.on(HookEvent.BEFORE_TOOL)
def log_tools(event_data: BeforeToolInput) -> HookResult:
    print(f"Tool: {event_data.tool_name}")
    return HookResult.allow()

# Block dangerous operations
@registry.on(HookEvent.BEFORE_TOOL)
def security_check(event_data: BeforeToolInput) -> HookResult:
    if "delete" in event_data.tool_name.lower():
        return HookResult.deny("Delete operations blocked")
    return HookResult.allow()

# Agent with hooks - intercepts tool calls
agent = Agent(
    name="SecureAssistant",
    instructions="You are a helpful assistant.",
    hooks=registry
)

agent.start("Help me organize my files")

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Hook Events

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Core Events

EventTriggerUse Case
BEFORE_TOOLBefore tool executionSecurity checks, logging
AFTER_TOOLAfter tool executionResult logging, validation
BEFORE_AGENTBefore agent runsSetup, initialization
AFTER_AGENTAfter agent completesCleanup, reporting
BEFORE_LLMBefore LLM API callRequest modification, logging
AFTER_LLMAfter LLM API responseResponse logging, validation
SESSION_STARTWhen session startsSession initialization
SESSION_ENDWhen session endsSession cleanup
ON_ERRORWhen an error occursError handling, recovery
ON_RETRYBefore a retry attemptRetry logic, backoff

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Extended Events

EventTriggerUse Case
USER_PROMPT_SUBMITWhen user submits a promptInput validation, logging
NOTIFICATIONWhen notification is sentAlert routing, logging
SUBAGENT_STOPWhen subagent completesSubagent result handling
SETUPOn initialization/maintenanceSystem setup, config loading
BEFORE_COMPACTIONBefore context compactionPre-compaction hooks
AFTER_COMPACTIONAfter context compactionPost-compaction validation
MESSAGE_RECEIVEDWhen message is receivedMessage preprocessing
MESSAGE_SENDINGBefore message is sentMessage modification
MESSAGE_SENTAfter message is sentDelivery confirmation
GATEWAY_STARTWhen gateway startsGateway initialization
GATEWAY_STOPWhen gateway stopsGateway cleanup
TOOL_RESULT_PERSISTBefore tool result storageResult modification

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Hook Decisions

DecisionDescription
allowAllow the operation to proceed
denyDeny the operation with a reason
blockBlock the operation silently
askPrompt for user confirmation

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CLI Commands

praisonai hooks list                    # List registered hooks
praisonai hooks test before_tool        # Test hooks for an event
praisonai hooks run "echo test"         # Run a command hook
praisonai hooks validate hooks.json     # Validate configuration

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Low-level API Reference

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HookRegistry Direct Usage

from praisonaiagents.hooks import (
    HookRegistry, HookRunner, HookEvent, HookResult,
    BeforeToolInput
)

# Create a hook registry
registry = HookRegistry()

# Log all tool calls
@registry.on(HookEvent.BEFORE_TOOL)
def log_tools(event_data: BeforeToolInput) -> HookResult:
    print(f"Tool: {event_data.tool_name}")
    return HookResult.allow()

# Block dangerous operations
@registry.on(HookEvent.BEFORE_TOOL)
def security_check(event_data: BeforeToolInput) -> HookResult:
    if "delete" in event_data.tool_name.lower():
        return HookResult.deny("Delete operations blocked")
    return HookResult.allow()

# Execute hooks
runner = HookRunner(registry)
result = runner.run(HookEvent.BEFORE_TOOL, event_data)

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Shell Command Hooks

Register external scripts as hooks: 
from praisonaiagents.hooks import HookRegistry, HookEvent

registry = HookRegistry()

# Run external validator before file writes
registry.register_command_hook(
    event=HookEvent.BEFORE_TOOL,
    command="python /path/to/file_validator.py",
    matcher="write_*"  # Only for tools starting with write_
)

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Matcher Patterns

from praisonaiagents.hooks import HookRegistry, HookEvent, HookResult

registry = HookRegistry()

# Match specific tools
registry.register_function_hook(
    event=HookEvent.BEFORE_TOOL,
    func=my_hook,
    matcher="write_file"  # Exact match
)

# Match with wildcard
registry.register_function_hook(
    event=HookEvent.BEFORE_TOOL,
    func=my_hook,
    matcher="file_*"  # Matches file_read, file_write, etc.
)

# Match multiple patterns
registry.register_function_hook(
    event=HookEvent.BEFORE_TOOL,
    func=my_hook,
    matcher=["read_*", "write_*"]  # Multiple patterns
)

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Configuration File

Create .praison/hooks.json in your project: 
{
  "enabled": true,
  "timeout": 30,
  "hooks": {
    "pre_write_code": "./scripts/lint.sh",
    "post_write_code": [
      "./scripts/format.sh",
      "./scripts/git-add.sh"
    ],
    "pre_run_command": {
      "command": "./scripts/validate-command.sh",
      "timeout": 60,
      "enabled": true,
      "block_on_failure": true,
      "pass_input": true
    }
  }
}

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LLM Hooks

Intercept LLM API calls for logging, modification, or validation: 
from praisonaiagents import Agent
from praisonaiagents.hooks import HookRegistry, HookEvent, HookResult, BeforeLLMInput, AfterLLMInput

registry = HookRegistry()

@registry.on(HookEvent.BEFORE_LLM)
def log_llm_request(event_data: BeforeLLMInput) -> HookResult:
    """Log LLM requests before they are sent."""
    print(f"LLM Request: {len(event_data.messages)} messages")
    print(f"Model: {event_data.model}")
    return HookResult.allow()

@registry.on(HookEvent.AFTER_LLM)
def log_llm_response(event_data: AfterLLMInput) -> HookResult:
    """Log LLM responses after they are received."""
    print(f"LLM Response: {len(event_data.response)} chars")
    print(f"Tokens used: {event_data.usage}")
    return HookResult.allow()

agent = Agent(
    name="MonitoredAgent",
    instructions="You are helpful.",
    hooks=registry
)

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Error and Retry Hooks

Handle errors and customize retry behavior: 
from praisonaiagents.hooks import OnErrorInput, OnRetryInput

@registry.on(HookEvent.ON_ERROR)
def handle_error(event_data: OnErrorInput) -> HookResult:
    """Handle errors during agent execution."""
    print(f"Error occurred: {event_data.error}")
    print(f"Context: {event_data.context}")
    # Log to external service, send alert, etc.
    return HookResult.allow()

@registry.on(HookEvent.ON_RETRY)
def handle_retry(event_data: OnRetryInput) -> HookResult:
    """Customize retry behavior."""
    print(f"Retry attempt {event_data.attempt} of {event_data.max_retries}")
    if event_data.attempt > 2:
        return HookResult.deny("Too many retries")
    return HookResult.allow()

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Best Practices

  1. Keep hooks lightweight - Hooks run synchronously, avoid heavy operations
  2. Use matchers - Only run hooks for relevant tools
  3. Return early - Return allow quickly for non-matching cases
  4. Log decisions - Log why hooks deny operations for debugging
  5. Handle errors - Wrap hook logic in try/except to avoid breaking agents

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See Also