A no-fluff guide to getting started with the OpenAI API. Covers core concepts, multi-turn chat, structured output, streaming, function calling, and error handling with real Python code you can use today.
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GPT-4 function calling is the cleanest interface between natural language and your code — but most developers underuse it. This guide covers schemas, parallel calls, structured extraction, robust error handling, and the production patterns that separate demos from real systems.
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Streaming LLM responses isn't just a visual trick — it's a foundational architecture decision. Learn how to implement real-time token streaming in Python and JavaScript, avoid production gotchas, and instrument the metrics that actually matter.
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Tool-calling changes everything about how you write prompts. Discover five production-ready patterns for agentic prompt engineering—from system prompt blueprints to goal anchoring—that stop agents from drifting, looping, and hallucinating tool calls.
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Keyword search misses too much. Here's how to build a working semantic search system with embeddings in under 100 lines of Python — with real code you can run today.
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