feat: add batch inference API (Classify, BatchGenerate)

Add ClassifyResult, BatchResult types and Classify/BatchGenerate methods
to TextModel for batched prefill-only and autoregressive inference.
Add WithLogits option for returning raw vocab logits.

Co-Authored-By: Virgil <virgil@lethean.io>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

inference.go

@@ -40,6 +40,18 @@ type Message struct {
 	Content string
 }
 
+// ClassifyResult holds the output for a single prompt in a batch classification.
+type ClassifyResult struct {
+	Token  Token     // Sampled/greedy token at last prompt position
+	Logits []float32 // Raw vocab-sized logits (only when WithLogits is set)
+}
+
+// BatchResult holds the output for a single prompt in batch generation.
+type BatchResult struct {
+	Tokens []Token // All generated tokens for this prompt
+	Err    error   // Per-prompt error (context cancel, OOM, etc.)
+}
+
 // TextModel generates text from a loaded model.
 type TextModel interface {
 	// Generate streams tokens for the given prompt.
@@ -49,6 +61,15 @@ type TextModel interface {
 	// The model applies its native chat template.
 	Chat(ctx context.Context, messages []Message, opts ...GenerateOption) iter.Seq[Token]
 
+	// Classify runs batched prefill-only inference. Each prompt gets a single
+	// forward pass and the token at the last position is sampled. This is the
+	// fast path for classification tasks (e.g. domain labelling).
+	Classify(ctx context.Context, prompts []string, opts ...GenerateOption) ([]ClassifyResult, error)
+
+	// BatchGenerate runs batched autoregressive generation. Each prompt is
+	// decoded up to MaxTokens. Returns all generated tokens per prompt.
+	BatchGenerate(ctx context.Context, prompts []string, opts ...GenerateOption) ([]BatchResult, error)
+
 	// ModelType returns the architecture identifier (e.g. "gemma3", "qwen3", "llama3").
 	ModelType() string
 

options.go

@@ -2,12 +2,13 @@ package inference
 
 // GenerateConfig holds generation parameters.
 type GenerateConfig struct {
-	MaxTokens   int
-	Temperature float32
-	TopK        int
-	TopP        float32
-	StopTokens  []int32
+	MaxTokens     int
+	Temperature   float32
+	TopK          int
+	TopP          float32
+	StopTokens    []int32
 	RepeatPenalty float32
+	ReturnLogits  bool // Return raw logits in ClassifyResult (default false)
 }
 
 // DefaultGenerateConfig returns sensible defaults.
@@ -51,6 +52,11 @@ func WithRepeatPenalty(p float32) GenerateOption {
 	return func(c *GenerateConfig) { c.RepeatPenalty = p }
 }
 
+// WithLogits requests raw logits in ClassifyResult. Off by default to save memory.
+func WithLogits() GenerateOption {
+	return func(c *GenerateConfig) { c.ReturnLogits = true }
+}
+
 // ApplyGenerateOpts builds a GenerateConfig from options.
 func ApplyGenerateOpts(opts []GenerateOption) GenerateConfig {
 	cfg := DefaultGenerateConfig()