OpenAI Agents Integration Guide

pip install openai-agents

pip install 'openai-agents[voice]'

import os

# Set APIpie as the provider
os.environ["OPENAI_API_KEY"] = "your-apipie-api-key"
os.environ["OPENAI_BASE_URL"] = "https://apipie.ai/v1"

# Optional: Configure default model
os.environ["OPENAI_MODEL"] = "gpt-4o"  # Use any model available on APIpie

import os
from agents import Agent, Runner

# Configure APIpie
os.environ["OPENAI_API_KEY"] = "your-apipie-api-key"
os.environ["OPENAI_BASE_URL"] = "https://apipie.ai/v1"

# Create a simple agent
agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant specializing in Python programming.",
    model="gpt-4o",  # Use any model available on APIpie
)

# Run the agent
result = Runner.run_sync(
    agent,
    "Explain how to use list comprehensions in Python with some examples."
)

print(result.final_output)

import os
import asyncio
from agents import Agent, Runner

# Configure APIpie
os.environ["OPENAI_API_KEY"] = "your-apipie-api-key"
os.environ["OPENAI_BASE_URL"] = "https://apipie.ai/v1"

# Create specialized agents
python_agent = Agent(
    name="Python Expert",
    instructions="You are an expert Python programmer. Provide detailed, technically accurate information about Python programming.",
    model="gpt-4o",
)

javascript_agent = Agent(
    name="JavaScript Expert",
    instructions="You are an expert JavaScript programmer. Provide detailed, technically accurate information about JavaScript programming.",
    model="gpt-4o",
)

# Create a triage agent that can hand off to specialists
triage_agent = Agent(
    name="Programming Triage",
    instructions="Determine if the user is asking about Python or JavaScript and hand off to the appropriate expert agent.",
    model="gpt-4o-mini",  # Use a lighter model for triage
    handoffs=[python_agent, javascript_agent],
)

async def main():
    # Run the agent system
    result = await Runner.run(
        triage_agent,
        "What's the difference between list comprehensions in Python and array methods in JavaScript?"
    )
    print(result.final_output)

if __name__ == "__main__":
    asyncio.run(main())

import os
import asyncio
from agents import Agent, Runner, function_tool

# Configure APIpie
os.environ["OPENAI_API_KEY"] = "your-apipie-api-key"
os.environ["OPENAI_BASE_URL"] = "https://apipie.ai/v1"

# Define a function tool for weather information
@function_tool
def get_weather(city: str, country: str = "US") -> str:
    """Get the current weather for a city.

    Args:
        city: The name of the city
        country: The country code (default: US)

    Returns:
        Current weather information
    """
    # In a real implementation, you would call a weather API
    return f"The weather in {city}, {country} is currently sunny and 72°F."

# Create an agent with the weather tool
weather_agent = Agent(
    name="Weather Assistant",
    instructions="You help users get weather information for different locations.",
    model="gpt-4o-mini",
    tools=[get_weather],
)

async def main():
    result = await Runner.run(
        weather_agent,
        "What's the weather like in Tokyo, Japan?"
    )
    print(result.final_output)

if __name__ == "__main__":
    asyncio.run(main())

import os
import asyncio
from agents import Agent, Runner
from agents.guardrails import InputGuardrail, OutputGuardrail

# Configure APIpie
os.environ["OPENAI_API_KEY"] = "your-apipie-api-key"
os.environ["OPENAI_BASE_URL"] = "https://apipie.ai/v1"

# Define guardrails
class ProfanityInputGuardrail(InputGuardrail):
    async def validate(self, input_text: str) -> bool:
        profanity_list = ["bad_word1", "bad_word2"]  # Define your list of prohibited words
        for word in profanity_list:
            if word in input_text.lower():
                self.failure_reason = f"Input contains prohibited word: {word}"
                return False
        return True

class FactualOutputGuardrail(OutputGuardrail):
    async def validate(self, output_text: str) -> bool:
        if "definitely" in output_text.lower() and "always" in output_text.lower():
            self.failure_reason = "Output contains overgeneralizations"
            return False
        return True

# Create an agent with guardrails
agent = Agent(
    name="Guarded Assistant",
    instructions="You provide helpful information about science topics.",
    model="gpt-4o",
    input_guardrails=[ProfanityInputGuardrail()],
    output_guardrails=[FactualOutputGuardrail()],
)

async def main():
    try:
        result = await Runner.run(
            agent,
            "Tell me about the solar system."
        )
        print(result.final_output)
    except Exception as e:
        print(f"Guardrail triggered: {e}")

if __name__ == "__main__":
    asyncio.run(main())

import os
import asyncio
from typing import List
from pydantic import BaseModel
from agents import Agent, Runner

# Configure APIpie
os.environ["OPENAI_API_KEY"] = "your-apipie-api-key"
os.environ["OPENAI_BASE_URL"] = "https://apipie.ai/v1"

# Define a structured output type
class MovieRecommendation(BaseModel):
    title: str
    year: int
    director: str
    genre: str
    description: str

class MovieRecommendations(BaseModel):
    recommendations: List[MovieRecommendation]
    reasoning: str

# Create an agent with structured output
movie_agent = Agent(
    name="Movie Recommender",
    instructions="You recommend movies based on user preferences.",
    model="gpt-4o",
    output_type=MovieRecommendations,
)

async def main():
    result = await Runner.run(
        movie_agent,
        "Recommend three sci-fi movies similar to Interstellar."
    )

    # Access structured data
    for i, movie in enumerate(result.final_output.recommendations, 1):
        print(f"Recommendation {i}:")
        print(f"  Title: {movie.title}")
        print(f"  Year: {movie.year}")
        print(f"  Director: {movie.director}")
        print(f"  Genre: {movie.genre}")
        print(f"  Description: {movie.description}")

    print(f"\nReasoning: {result.final_output.reasoning}")

if __name__ == "__main__":
    asyncio.run(main())