Production Agent Framework Guide

Mastering the OpenAI Agents SDK

Build production multi-agent systems with explicit agent transfers (handoffs), safety guardrails, structured function tools, and built-in OpenTelemetry tracing.

Agent Handoffs

Seamlessly transfer execution control and conversation state from a triage agent to specialist agents (e.g. Code Agent, Billing Agent).

Safety Guardrails

Enforce strict input validation and output safety checks before tools execute or responses stream back to users.

OpenTelemetry Tracing

Inspect every agent hop, tool payload, and model reasoning step natively with OpenTelemetry standards.

Multi-Agent Handoff Implementation

The Python snippet below demonstrates creating a Triage Agent that routes customer support requests to a specialized Refund Agent or Tech Support Agent.

from agents import Agent, Runner, handoff
from pydantic import BaseModel

# 1. Define Tools & Models
class RefundRequest(BaseModel):
    user_id: str
    amount: float

def process_refund(request: RefundRequest) -> str:
    return f"Refund of ${request.amount} processed for user {request.user_id}."

# 2. Define Specialist Agents
refund_agent = Agent(
    name="Refund Specialist",
    instructions="You handle processing customer refunds accurately.",
    tools=[process_refund]
)

tech_agent = Agent(
    name="Tech Support Specialist",
    instructions="You assist users with technical troubleshooting and bug reports."
)

# 3. Define Triage Agent with Handoff Targets
triage_agent = Agent(
    name="Triage Agent",
    instructions="Route the user to Tech Support or Refund Specialist based on query.",
    handoffs=[refund_agent, tech_agent]
)

# 4. Execute Multi-Agent Delegation Loop
if __name__ == "__main__":
    result = Runner.run_sync(
        triage_agent,
        "I need a $50 refund for my last invoice."
    )
    print(f"Final Response: {result.final_output}")
    print(f"Executing Agent: {result.active_agent.name}")

Production Guardrails & Telemetry

Before deploying agents into production environments, hook input and output guardrail functions:

✔ Input PII Redaction Guardrails to cleanse user prompts before LLM inference.
✔ Output Schema Enforcement using Pydantic models to guarantee valid JSON returns.
✔ Max Handoff Limits (e.g. max 5 agent hops) to prevent infinite delegation loops.