LLM APIs & Tooling explicadores.
Olvídate de las docs de 40 páginas. Cada explicador convierte una idea complicada de IA, Claude Code, MCP o cloud en un diagrama animado en vivo que puedes arrastrar, scrubear y romper — para que el concepto te haga clic en minutos, no en horas.
Todos los explicadores de LLM APIs & Tooling
Function Calling: How LLMs Use Your APIs
You describe a function in JSON Schema; the model decides when to call it and produces typed arguments. The bridge from "pretty text" to "real action."
Structured Outputs and JSON Mode: Reliable LLM Responses
Stop parsing prose. Constrain the model's output to a schema and your downstream code stops guessing. The single biggest reliability lever in LLM apps.
LLM Streaming: Why First-Token Latency Beats Total Time
Streaming sends tokens as the model produces them. Total wall-time is similar; perceived speed is dramatically better — and lets you cut off when the answer is good enough.
API Rate Limits, RPM, and TPM Explained
Two budgets you cannot ignore: requests per minute and tokens per minute. Understanding both — and the burst behaviour around them — keeps your prod stable.
LangChain vs LlamaIndex: When to Pick Which
LangChain is the kitchen-sink agent framework. LlamaIndex is the RAG-focused data framework. Same neighbourhood, different specialities.
OpenAI SDK vs Anthropic SDK: API Patterns Compared
Same family of APIs, different shapes. Knowing the differences saves an afternoon of head-scratching when porting code between providers.
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