Pythongpt4o_demo.py
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import os
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import json
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import time
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import openai
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from pydantic import BaseModel
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client = openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"])
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# ── 1. Structured Outputs with Pydantic ────────────────────────────
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class TechStack(BaseModel):
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    languages: list[str]
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    frameworks: list[str]
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    databases: list[str]
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    cloud: list[str]
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response = client.beta.chat.completions.parse(
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    model="gpt-4o-mini",
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    messages=[{
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        "role": "user",
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        "content": "What tech stack does Netflix likely use? List specific technologies.",
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    }],
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    response_format=TechStack,
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)
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stack = response.choices[0].message.parsed
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print("=== Structured Output ===")
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print(f"Languages: {stack.languages}")
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print(f"Databases: {stack.databases}")
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# ── 2. Streaming with TTFT measurement ─────────────────────────────
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print("\n=== Streaming ===")
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start = time.perf_counter()
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ttft = None
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full_response = []
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stream = client.chat.completions.create(
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    model="gpt-4o-mini",
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    messages=[{"role": "user", "content": "Write a short poem about machine learning."}],
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    max_tokens=150,
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    stream=True,
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)
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for chunk in stream:
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    delta = chunk.choices[0].delta.content
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    if delta:
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        if ttft is None:
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            ttft = (time.perf_counter() - start) * 1000
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        full_response.append(delta)
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        print(delta, end="", flush=True)
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total = (time.perf_counter() - start) * 1000
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print(f"\nTTFT: {ttft:.0f}ms, Total: {total:.0f}ms")
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# ── 3. Parallel Function Calling ───────────────────────────────────
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tools = [
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    {
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        "type": "function",
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        "function": {
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            "name": "get_stock_price",
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            "description": "Get current stock price",
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            "parameters": {
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                "type": "object",
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                "properties": {"ticker": {"type": "string"}},
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                "required": ["ticker"],
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            },
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        },
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    },
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    {
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        "type": "function",
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        "function": {
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            "name": "get_news",
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            "description": "Get latest news for a company",
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            "parameters": {
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                "type": "object",
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                "properties": {"company": {"type": "string"}},
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                "required": ["company"],
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            },
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        },
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    },
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]
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response = client.chat.completions.create(
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    model="gpt-4o-mini",
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    messages=[{"role": "user", "content": "Get AAPL stock price and latest Apple news"}],
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    tools=tools,
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    tool_choice="auto",
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)
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print("\n=== Parallel Tool Calls ===")
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if response.choices[0].finish_reason == "tool_calls":
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    for tc in response.choices[0].message.tool_calls:
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        print(f"Tool: {tc.function.name}({tc.function.arguments})")
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