Lesson 1743 of 2116
Tool Calling Grammars: How AI Models Produce Reliable Structured Output
Constrained decoding via grammars or finite-state machines guarantees AI tool calls parse correctly.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2constrained decoding
- 3tool calling
- 4grammar
Concept cluster
Terms to connect while reading
Section 1
The premise
Constrained decoding uses a grammar or finite-state machine to mask invalid tokens at each step. The model literally cannot produce malformed JSON or invalid tool calls.
What AI does well here
- Guarantee syntactically valid JSON, XML, or function calls
- Reduce retry loops in agentic systems substantially
- Enable smaller models to do reliable tool calling
What AI cannot do
- Make the model choose the right tool — only ensure valid syntax
- Substitute for evaluation of whether the call accomplishes the goal
- Eliminate the need for runtime validation of business rules
Key terms in this lesson
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