Quickstart: OpenAI API directly with structured output + timings

quickstart_openai.py

import time
t0 = time.perf_counter()

import json
from pydantic import Field
from openai import OpenAI
from pydantic import BaseModel
from dotenv import load_dotenv

def elapsed(label: str, since: float) -> float:
    now = time.perf_counter()
    print(f"[{now - since:.3f}s] {label}")
    return now

t = elapsed("imports loaded", t0)

load_dotenv()
t = elapsed("dotenv loaded", t0)

class CustomOutputSchema(BaseModel):
    """
    docstring for the custom output schema
    """
    chat_message: str = Field(..., description="The chat message from the agent.")
    suggested_questions: list[str] = Field(..., description="Suggested follow-up questions.")

t = elapsed("CustomOutputSchema defined", t0)

SYSTEM_PROMPT = """You are a helpful assistant.

# Background
- This assistant is knowledgeable, helpful, and suggests follow-up questions.

# Steps
- Analyze the user's input to understand the context and intent.
- Formulate a relevant and informative response.
- Generate 3 suggested follow-up questions for the user.

# Output Instructions
- Provide clear and concise information in response to user queries.
- Conclude each response with 3 relevant suggested questions for the user."""

t = elapsed("system prompt defined", t0)

client = OpenAI()
t = elapsed("OpenAI client initialized", t0)

# No agent initialization step needed — using OpenAI API directly.
t = elapsed("(no agent init needed)", t0)

if __name__ == "__main__":
    user_input = "Tell me about atomic agents framework"
    print(f"\nSending: '{user_input}'")

    t_request = time.perf_counter()
    response = client.responses.parse(
        model="gpt-5-mini",
        instructions=SYSTEM_PROMPT,
        input=[
            {"role": "user", "content": user_input},
        ],
        text_format=CustomOutputSchema,
    )
    parsed = response.output_parsed
    elapsed("client.responses.parse() completed", t_request)
    elapsed("total time since script start", t0)

    print(f"\nAgent: {parsed.chat_message}")
    print("Suggested questions:")
    for question in parsed.suggested_questions:
        print(f"- {question}")