structured output
FDE interview questions tagged structured output, across every topic.
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Concepts behind "structured output"
The curriculum that explains the ideas these questions test.
Core
Constrained DecodingConstrained decoding forces a model's output to match a schema or grammar by masking the logits at each step so the model can only sample tokens the grammar still allows. It guarantees structurally valid output (JSON, SQL, a fixed enum) at a small latency cost, which is why FDE loops reach for it the moment a pipeline depends on parseable model output.🧠 Foundations of LLMs & GenAISign in
Core
Tool / Function CallingTool calling is how a language model reaches outside itself: it emits a structured request (a tool name plus JSON arguments) that your application executes and feeds back. The model is only as capable as the tools you give it and as reliable as your validation, because the arguments it produces are model output and must never be trusted blindly.🤖 Retrieval & AgentsSign in
Advanced
Structured Output and Schema ValidationThe moment a model's output feeds another system, prose is a liability and a schema is the contract. Constrained decoding makes malformed JSON impossible; validation with something like Pydantic catches the errors that are still valid JSON, which are the ones that reach production.🧠 Foundations of LLMs & GenAI🔒 Premium