Text classification with grammar-constrained JSON output using a GGUF language model.

1. Defines a JSON schema with allowed labels (positive, negative, neutral) and a confidence score
2. Converts the schema to a grammar state machine via grammar.Convert
3. Loads a GGUF model via inference.LoadFile
4. Prompts the model to classify the input text
5. Uses inference.WithGrammar to constrain output to valid JSON matching the schema

The grammar constraint guarantees the model output is always valid JSON with the correct structure, eliminating the need for fragile string parsing or retry loops.

go build -o classification ./examples/classification/

# Classify sentiment
./classification --model path/to/model.gguf --text "I love this product!"
# Output: {"label":"positive","confidence":0.95}

./classification --model path/to/model.gguf --text "The package arrived damaged."
# Output: {"label":"negative","confidence":0.87}

# With GPU
./classification --model path/to/model.gguf --device cuda --text "It was okay I guess."