OpenAI Agents SDK (Python)

Use this skill when developing AI agents using OpenAI Agents SDK (openai-agents package).

Quick Reference

Installation

pip install openai-agents

Environment Variables

# OpenAI (direct)
OPENAI_API_KEY=sk-...
LLM_PROVIDER=openai

# Azure OpenAI (via LiteLLM)
LLM_PROVIDER=azure
AZURE_API_KEY=...
AZURE_API_BASE=https://your-resource.openai.azure.com
AZURE_API_VERSION=2024-12-01-preview

Basic Agent

from agents import Agent, Runner

agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
    model="gpt-5.2",  # or "gpt-5", "gpt-5.2-nano"
)

# Synchronous
result = Runner.run_sync(agent, "Tell me a joke")
print(result.final_output)

# Asynchronous
result = await Runner.run(agent, "Tell me a joke")

Key Patterns

| Pattern | Purpose | |---------|---------| | Basic Agent | Simple Q&A with instructions | | Azure/LiteLLM | Azure OpenAI integration | | AgentOutputSchema | Strict JSON validation with Pydantic | | Function Tools | External actions (@function_tool) | | Streaming | Real-time UI (Runner.run_streamed) | | Handoffs | Specialized agents, delegation | | Agents as Tools | Orchestration (agent.as_tool) | | LLM as Judge | Iterative improvement loop | | Guardrails | Input/output validation | | Sessions | Automatic conversation history | | Multi-Agent Pipeline | Multi-step workflows |

Reference Documentation

For detailed information, see:

• agents.md - Agent creation, Azure/LiteLLM integration
• tools.md - Function tools, hosted tools, agents as tools
• structured-output.md - Pydantic output, AgentOutputSchema
• streaming.md - Streaming patterns, SSE with FastAPI
• handoffs.md - Agent delegation
• guardrails.md - Input/output validation
• sessions.md - Sessions, conversation history
• patterns.md - Multi-agent workflows, LLM as judge, tracing

Official Documentation

• Docs: https://openai.github.io/openai-agents-python/
• Examples: https://github.com/openai/openai-agents-python/tree/main/examples