OpenAI API — Developer Overview, Mid-2026 – Community Presentation

Creator prompt

The idea behind this presentation

Create a 10-slide developer-focused presentation titled "OpenAI API — Developer Overview, Mid-2026". Design: Documentation-inspired dark developer theme. Background near-black ( #0d0d0d), primary text off-white ( #ececec), accent in teal-green ( #10a37f). Headings in Inter Display or Space Grotesk, body in Inter, all code in JetBrains Mono inside rounded dark code blocks ( #1a1a1a) with syntax highlighting (green strings, blue keywords, gray comments). Endpoint paths shown with a "POST" method badge in a small green pill. Each slide has a narrow sidebar strip showing the section name, like docs navigation. Tables with thin borders for comparisons. Code blocks are the primary visual element — render them large and readable, max ~12 lines each. Slide 1 — Title: "OpenAI API — Developer Overview" · "Models, endpoints, and patterns · Mid-2026". Code block: bash curl https://api.openai.com/v1/responses \ -H "Authorization: Bearer $OPENAI_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "gpt-5.5", "input": "Hello, world" }' Slide 2 — Platform at a glance: List the main surfaces: Responses API (primary interface), Chat Completions (compatible standard), Realtime API (voice/audio over WebRTC, WebSocket, SIP), Embeddings, Images, Batch, Administration. Small code strip showing the endpoint paths: POST /v1/responses POST /v1/chat/completions POST /v1/embeddings POST /v1/images/generations POST /v1/batches Slide 3 — Model lineup: Comparison table: GPT-5.5 (production recommendation; flagship ~$5 in / $30 out per 1M tokens, ~1M context, 128K max output), GPT-5.4 + mini/nano variants, gpt-image-2 / gpt-image-1, GPT-Realtime-2 for voice, embeddings models, open-weight Apache 2.0 models. Footnote: older GPT-5 and o3 snapshots deprecated December 2026. Slide 4 — Authentication & setup: python # pip install openai import os from openai import OpenAI client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) response = client.responses.create( model="gpt-5.5", input="Explain vector embeddings in one sentence." ) print(response.output_text) Notes: standard keys for app requests, Admin keys for org endpoints, workload identity federation for short-lived tokens. Slide 5 — The Responses API: Request anatomy — model, input, optional tools and state. Code block: python response = client.responses.create( model="gpt-5.5", input=[ {"role": "user", "content": "Summarize this contract clause..."} ], previous_response_id=last_id # server-side conversation state ) Callout: no need to resend full history — state is carried by previous_response_id. Slide 6 — Tool use: Function calling with JSON schemas plus built-in tools (web search, code execution). Code block: python tools = [{ "type": "function", "name": "get_weather", "description": "Get current weather for a city", "parameters": { "type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"] } }] response = client.responses.create( model="gpt-5.5", input="Weather in Kathmandu?", tools=tools ) Slide 7 — Structured outputs & streaming: Two code blocks side by side. Left: python response = client.responses.create( model="gpt-5.5", input="Extract name and date from: ...", text={"format": { "type": "json_schema", "name": "extraction", "schema": { "type": "object", "properties": { "name": {"type": "string"}, "date": {"type": "string"} }, "required": ["name", "date"] } }} ) Right: python stream = client.responses.create( model="gpt-5.5", input="Write a haiku about APIs.", stream=True ) for event in stream: if event.type == "response.output_text.delta": print(event.delta, end="") Slide 8 — Cost optimization: Four tactics with a one-line code hint each: prompt caching (24h retention default for non-ZDR orgs), Batch API for discounted async jobs, model tiering (route simple tasks to gpt-5.4-mini / nano), snapshot pinning: python model="gpt-5.5" # alias, moves over time model="gpt-5.5-2026-05" # pinned snapshot, stable behavior Slide 9 — Deprecations & migration: Timeline: DALL·E and Realtime Beta removed May 2026 → Sora 2 video endpoints removed September 2026 → older GPT-5/o3 snapshots removed December 2026 → legacy audio/transcription models removed January 2027. Guidance: pin snapshots, watch the changelog, run evals before switching models. Slide 10 — Getting started: Three-step path: get an API key → first Responses call → add tools and structured outputs. Links: developers.openai.com docs, API reference, changelog, deprecations page.

OpenAI API — Developer Overview, Mid-2026 – Community Presentation | Presenton