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Openai cheat sheet & developer notes

Openai cheat sheet and 1 curated developer notes — core concepts, patterns, and interview prep. Maintained by the DevRecall team.

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01 · Openai

OpenAI API

OpenAI API. Chat Completions. import OpenAI from 'openai'; const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY }); // Basic completion const response = await openai.chat.completions.create({ model: 'gpt-4o', m…

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Concepts to know for Openai

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Prompt Injection: Why LLM Apps Obey the Wrong TextWhy text an LLM reads can override your instructions, how indirect injection turns tools into exfiltration paths, and which defences actually contain it.Intermediate·14 minLLM Tool Calling and Agent LoopsThe model never runs your code: it asks for a tool call, your app validates and executes it, and a loop with budgets turns that into an agent you can trust.Intermediate·14 minRAG: Retrieval-Augmented GenerationHow RAG fetches permitted, fresh text and puts it in the prompt so an LLM answers with citations, and why chunking and retrieval decide the quality.Intermediate·14 minContext Windows and Token Budgets for LLMsWhat a token is, why the context window is the only memory an LLM has, and how to budget, trim and cache prompts so long conversations stay fast and cheap.Intermediate·13 minEmbeddings and Vector SearchHow text becomes a vector whose distance tracks meaning, why exact search does not scale, and how HNSW and IVF indexes trade recall for speed and memory.Intermediate·14 minEvaluating LLM Outputs: Evals, Graders and JudgesWhy assertEquals cannot test an LLM feature, how a golden dataset plus graders catches regressions, and where LLM-as-judge, statistics and CI gates fit.Intermediate·14 min

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