tomevault-io 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
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