Code
from agno.agent import Agent
from agno.exceptions import CheckTrigger, InputCheckError
from agno.models.openai import OpenAIResponses
from agno.run.agent import RunInput
from pydantic import BaseModel
class InputValidationResult(BaseModel):
is_relevant: bool
has_sufficient_detail: bool
is_safe: bool
concerns: list[str]
recommendations: list[str]
def comprehensive_input_validation(run_input: RunInput) -> None:
"""
Pre-hook: Comprehensive input validation using an AI agent.
This hook validates input for:
- Relevance to the agent's purpose
- Sufficient detail for meaningful response
Could also be used to check for safety, prompt injection, etc.
"""
# Input validation agent
validator_agent = Agent(
name="Input Validator",
model=OpenAIResponses(id="gpt-5.2"),
instructions=[
"You are an input validation specialist. Analyze user requests for:",
"1. RELEVANCE: Ensure the request is appropriate for a financial advisor agent",
"2. DETAIL: Verify the request has enough basic information for a meaningful response.",
" A request has sufficient detail if it includes at least a few of: age, income, savings, goals, or risk tolerance.",
" Do NOT require exhaustive information - a reasonable question with some context is sufficient.",
"3. SAFETY: Ensure the request is not harmful or unsafe",
"",
"List specific concerns and recommendations for improvement.",
"",
"Be lenient with detail checks - if the user provides a clear question with some financial context, mark has_sufficient_detail as true.",
"Only mark has_sufficient_detail as false for extremely vague requests like 'help me invest' with no context at all.",
],
output_schema=InputValidationResult,
)
validation_result = validator_agent.run(
input=f"Validate this user request: '{run_input.input_content}'"
)
result = validation_result.content
# Check validation results
if not result.is_safe:
raise InputCheckError(
f"Input is harmful or unsafe. {result.recommendations[0] if result.recommendations else ''}",
check_trigger=CheckTrigger.INPUT_NOT_ALLOWED,
)
if not result.is_relevant:
raise InputCheckError(
f"Input is not relevant to financial advisory services. {result.recommendations[0] if result.recommendations else ''}",
check_trigger=CheckTrigger.OFF_TOPIC,
)
if not result.has_sufficient_detail:
raise InputCheckError(
f"Input lacks sufficient detail for a meaningful response. Suggestions: {', '.join(result.recommendations)}",
check_trigger=CheckTrigger.INPUT_NOT_ALLOWED,
)
def main():
print("🚀 Input Validation Pre-Hook Example")
print("=" * 60)
# Create a financial advisor agent with comprehensive hooks
agent = Agent(
name="Financial Advisor",
model=OpenAIResponses(id="gpt-5.2"),
pre_hooks=[comprehensive_input_validation],
description="A professional financial advisor providing investment guidance and financial planning advice.",
instructions=[
"You are a knowledgeable financial advisor with expertise in:",
"• Investment strategies and portfolio management",
"• Retirement planning and savings strategies",
"• Risk assessment and diversification",
"• Tax-efficient investing",
"",
"Provide clear, actionable advice while being mindful of individual circumstances.",
"Always remind users to consult with a licensed financial advisor for personalized advice.",
],
)
# Test 1: Valid financial question (should work normally with enhanced formatting)
print("\n🟢 Test 1: Valid financial question")
print("-" * 40)
try:
response = agent.run(
input="""
I'm 35 years old and want to start investing for retirement.
I can save $1000 per month in addition to my current retirement savings and have moderate risk tolerance.
My gross income is $100,000.
My current retirement savings in IRAs and 401(k)s is $100,000, my total savings is $200,000, and my net worth is $300,000.
My country is the United States.
Do you have advice for me?
"""
)
print("✅ Success! Response validated by pre-hook:")
print(response.content)
except Exception as e:
print(f"❌ Unexpected error: {e}")
# Test 2: Input with insufficient detail (should trigger pre-hook)
print("\n🔴 Test 2: Vague input (insufficient detail)")
print("-" * 40)
try:
response = agent.run(input="Help me invest")
print(response.content)
except InputCheckError as e:
print(f"❌ Pre-hook validation failed: {e}")
print(f" Trigger: {e.check_trigger}")
# Test 3: Irrelevant request (should trigger pre-hook)
print("\n🔴 Test 3: Off-topic request")
print("-" * 40)
try:
response = agent.run(input="What's the best pizza recipe?")
print(response.content)
except InputCheckError as e:
print(f"❌ Pre-hook validation failed: {e}")
print(f" Trigger: {e.check_trigger}")
# Test 4: Potentially harmful content (should trigger pre-hook)
print("\n🔴 Test 4: Potentially unsafe content")
print("-" * 40)
try:
response = agent.run(
input="How can I manipulate stock prices to make money quickly?"
)
print(response.content)
except InputCheckError as e:
print(f"❌ Pre-hook validation failed: {e}")
print(f" Trigger: {e.check_trigger}")
if __name__ == "__main__":
main()
Usage
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno openai
3
Run example
python input_validation_pre_hook.py