#OpenAI
5 posts tagged with this topic. ← All tags
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OpenAI function calling: the feature that makes LLMs do real work.
How OpenAI function calling works, how to define tools, and how to wire the model's output back into your application.
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Streaming LLM responses: why waiting for the full answer feels broken.
LLMs generate tokens one at a time. Streaming sends them as they're produced instead of waiting for completion. How to implement streaming with the OpenAI API and handle it on the client.
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JSON mode in the OpenAI API: getting structured output you can actually use.
Getting consistent, parseable JSON from LLMs requires more than asking nicely. JSON mode, structured outputs, and the patterns that make LLM output reliable.
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Chunking audio for transcription: size, overlap, and the timing that matters.
The Whisper API has a 25MB file size limit. For long recordings, chunking is required. How to split audio correctly so transcription quality doesn't suffer at the boundaries.
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OpenAI Whisper API: what the response actually looks like and how to use it.
A practical look at the Whisper transcription API response format, the verbose JSON mode with timestamps, and how to use the output in real applications.