OpenAI Batch API in Python: Cut Cost on Offline LLM Eval Runs

Professor Py: AI Engineering · Beginner ·🛠️ AI Tools & Apps ·2mo ago

About this lesson

OpenAI Batch API in Python: run cost-effective offline LLM evaluations and bulk regression tests. Learn a practical workflow to queue JSONL prompts, upload via the Files API, launch Responses batch jobs, poll progress, and compute hit-rate accuracy for reproducible scoring. Tools covered: OpenAI Batch API, Files API, Responses endpoint, Python (io, json) and the OpenAI client. Subscribe for hands-on AI engineering tutorials on scalable, cheaper model evaluation and scoring pipelines. #OpenAI #BatchAPI #Python #LLM #AIEvaluation #AIEngineering

Original Description

OpenAI Batch API in Python: run cost-effective offline LLM evaluations and bulk regression tests. Learn a practical workflow to queue JSONL prompts, upload via the Files API, launch Responses batch jobs, poll progress, and compute hit-rate accuracy for reproducible scoring. Tools covered: OpenAI Batch API, Files API, Responses endpoint, Python (io, json) and the OpenAI client. Subscribe for hands-on AI engineering tutorials on scalable, cheaper model evaluation and scoring pipelines. #OpenAI #BatchAPI #Python #LLM #AIEvaluation #AIEngineering
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