Customer Support Bot Example

This example demonstrates building an automated customer support bot using the AgenticAI Framework.

Enterprise-Ready Pattern

Part of 400+ modules with 237 enterprise features including multi-tenant support, compliance guardrails, and advanced monitoring.

Overview

The customer support bot combines LLMs, guardrails, and monitoring to provide helpful, policy-compliant responses to customer inquiries.

Key Features

• Polite and professional responses
• Guardrails for data privacy
• Real-time monitoring
• Context-aware assistance

Code

```python from agenticaiframework.agents import Agent from agenticaiframework.tasks import Task from agenticaiframework.llms import LLMManager from agenticaiframework.guardrails import Guardrail from agenticaiframework.monitoring import Monitor

Example: Automated Customer Support Bot

if name == "main": # Initialize components llm = LLMManager() llm.register_model("gpt-4", lambda prompt, kwargs: f"[Simulated GPT-4 Support Response to: {prompt}]") llm.set_active_model("gpt-4") guardrail = Guardrail(rules=["Be polite", "Do not provide personal data", "Stay on topic"]) monitor = Monitor()

# Create agent
support_agent = Agent(
    name="CustomerSupportBot",
    llm=llm,
    guardrail=guardrail,
    monitor=monitor
)

# Define task
support_task = Task(
    description="Respond to a customer asking about the refund policy for defective products.",
    expected_output="A polite, clear explanation of the refund policy."
)

# Run task
result = support_agent.run_task(support_task)

# Output result
logger.info("=== Customer Support Response ===")
logger.info(result)