platform.openai.com

Generate spoken audio from text with the OpenAI /v1/audio/speech text-to-speech endpoint

Transcribe an audio file with the OpenAI /v1/audio/transcriptions endpoint, including timestamps or diarization

Handle OpenAI API rate limits and transient errors robustly: read the rate-limit headers, retry only the right status codes with backoff and jitter, and understand tier limits

Cut OpenAI API cost and latency with prompt caching: structure prompts for cache hits, set prompt_cache_key, and read cache metrics from the usage object

Run a long OpenAI Responses API call in background mode, poll or stream its progress, resume an interrupted stream, and cancel it

Use OpenAI reasoning models on the Responses API: tune reasoning effort, request summaries, account for reasoning tokens, and carry reasoning items across turns including encrypted content

Run bulk OpenAI inference at a discount with the Batch API: build the JSONL, upload it, create and poll the batch, and reconcile output and error files

Send images to the OpenAI Responses API for vision analysis by URL, base64, or file_id, and generate images with the image_generation tool

Connect a remote MCP server as a tool on the OpenAI Responses API, restrict the exposed tool surface, and handle the approval flow safely

Connect a remote MCP server as a tool on the OpenAI Responses API, restrict the exposed tool surface, and handle the approval flow safely

Run Python in a sandboxed container with the OpenAI code_interpreter tool on the Responses API, pass input files, and download files the model generates

Create an OpenAI vector store, ingest files, and use the file_search tool on the Responses API to return answers grounded in your own documents with file citations

Enable OpenAI's hosted web_search tool on a Responses API call, restrict it by domain and location, and render the required inline citations

Use Structured Outputs with a strict JSON Schema on the OpenAI Responses API via text.format, and handle model refusals distinctly from parse failures

Stream an OpenAI Responses API call over server-sent events, dispatch on the semantic event types such as response.output_text.delta, and detect completion or failure mid-stream

Manage multi-turn conversation state on the OpenAI Responses API using previous_response_id, the store parameter, and the Conversations API, accounting for retention and zero-data-retention constraints

Create an OpenAI Responses API request with custom function tools and run the tool-call loop correctly: parse function_call items, execute the tool, and submit function_call_output on the next turn

Migrate an existing OpenAI Chat Completions integration to the Responses API: convert messages to input, read output_text instead of choices[0].message.content, and update tool and structured-output schemas

Distinguish genuine AI crawler traffic (GPTBot, ClaudeBot, PerplexityBot, etc.) from spoofed user agents, and apply differentiated robots.txt directives

Configure robots.txt directives that allow AI shopping and search-agent crawlers (e.g. OAI-SearchBot, PerplexityBot, Amazonbot) onto product pages while blocking pure AI-training crawlers from the same paths

Build a WebRTC voice session with the OpenAI Realtime API using ephemeral client secrets

Create and run an OpenAI Evals API evaluation with a custom grader