How to Stream AI Responses Token by Token in Python Using OpenAI API

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Most AI applications wait for a model to finish generating before displaying output, which can make longer responses feel sluggish to users. Streaming addresses this by rendering each response chunk as it arrives, improving perceived performance. In Python, this is achieved by passing stream=True to the OpenAI client's chat completions method and iterating over the returned chunks. The pattern works with any OpenAI-compatible API endpoint, and sensitive values like API keys and model names should be stored in environment variables for portability. Developers are advised to handle edge cases such as empty chunks, connection failures, and interrupted streams before deploying this approach in production.

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