Deep dive into Agents SDK from OpenAI

Deep dive into Agents SDK from OpenAI

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AI Summary

Overview

• Deep dive into OpenAI Agents SDK
• Documentation link provided

Key Features

• Abstractions over API calls, making it easier to build AI apps.
• Evolution from previous Swarm SDK.
• Enables lightweight, production-ready agentic applications.

Main Components

• Agents: Primary units doing tasks.
• Handoffs: Built-in functionality for transferring tasks between agents.
• Guard Rails: Type safety and input validation to filter inputs (e.g., ensuring only math-related questions for a math tutor).
• Tracing: Easy tracking of agent workflows via OpenAI dashboard.

Installation

• Install SDK using: pip install open-ai-agents.

Quick Start Example

1. Import the agent and runner:

   from openai_agents import Agent, Runner  

2. Define agents with instructions:

   agent = Agent(name='Math Tutor', instructions='Help with math questions.')  
   runner = Runner()  
   result = runner.run(agent)  

3. Output the result.

Agent Interactions

• A triage agent determines which specialized agent (e.g., math or history tutor) to use based on user questions.
• Handoffs provide context for routing tasks effectively.
• Example of triage routing where a math query is passed to the math tutor.

Guard Rails

• Important for ensuring safety of responses, for example, only accepting valid homework-related questions.
• Uses Pydantic objects for structured outputs and input validation.

Conclusion

• The OpenAI Agents SDK streamlines creating modular AI solutions with built-in functionalities streamlining the development process and increasing robustness.