Add experimental MLX backend and engine with imagegen support (#13648)

* WIP - MLX backend with gemma3

* MLX: add cmake and go tag build toggles

To build the new MLX backend code:
  cmake --preset MLX
  cmake --build --preset MLX --parallel
  cmake --install build --component MLX
  go build -tags mlx .

Note: the main.go entrypoint for the MLX engine will change in a follow up commit.

* add experimental image generation runtime

* add experimental image generation runtime

* MLX: wire up cuda build for linux

* MLX: get dependencies correct and dedup

This is still too large for a unified github artifact, but is now "correct" for the mlx_cuda_v13
directory.

* fix relative link bug in dedup

* Add darwin build and readme

* add go build tag for mlx dependent code and wire up build_darwin.sh

* lint cleanup

* macos: build mlx for x86

This will be CPU only.

* cuda build instructions and fix drift from mlx bump

* stale comment

* Delete agent helper doc

* Clean up readme.md

* Revise README for tokenizer clarity and details

Updated README to clarify tokenizer functionality and removed correctness section.

---------

Co-authored-by: jmorganca <jmorganca@gmail.com>

x/model/input/input.go

@@ -0,0 +1,76 @@
+package input
+
+import "github.com/ollama/ollama/x/ml"
+
+// Multimodal is a multimodal embedding or a component of one.
+// For example, it could be a row of an image that can be processed
+// independently.
+type Multimodal struct {
+	// Tensor is the embedding data. Implementations may chose what to
+	// store here or it may be nil if not needed. However, any ml.Tensor
+	// objects must be stored here and not in Data.
+	Tensor ml.Tensor
+
+	// Data is implementation-specific opaque data, such as metadata on how
+	// to layout Tensor. It may be nil if not needed. It may also store larger
+	// objects such as complete images if they are to be processed later.
+	Data any
+}
+
+// Input represents one token in the input stream
+type Input struct {
+	// Token is a single element of text.
+	Token int32
+
+	// Multimodal is represents a non-text element such as an
+	// image (or part of one if the image can be processed in pieces).
+	// It may be used either together with Token or on its own.
+	Multimodal []Multimodal
+
+	// MultimodalHash is a unique representation of the data
+	// stored in Multimodal, used for caching and comparing
+	// equality.
+	MultimodalHash uint64
+
+	// SameBatch forces the following number of tokens to be processed
+	// in a single batch, breaking and extending batches as needed.
+	// Useful for things like images that must be processed in one
+	// shot.
+	SameBatch int
+}
+
+// MultimodalIndex is a multimodal element (such as an image)
+// together with an index into the slice of Inputs with the
+// corresponding token. Note that the index is not the same
+// as the position - to find that use the index with the
+// Positions slice.
+type MultimodalIndex struct {
+	Index      int
+	Multimodal []Multimodal
+}
+
+// Batch contains the inputs for a model forward pass
+type Batch struct {
+	// Inputs is the input tokens, including placeholders for multimodal inputs.
+	Inputs ml.Tensor
+
+	// Outputs are the set of indicies into Inputs for which output data should
+	// be returned.
+	Outputs ml.Tensor
+
+	// TODO maybe not the optimal way to handle this
+	// Offset of final tensor in the final batch
+	Offset int
+
+	// Positions is the position for each Input, relative to its sequence. Equal
+	// in length to Inputs.
+	Positions []int32
+
+	// Sequences is the sequence for each Input. Equal in length to Inputs.
+	Sequences []int
+
+	// Multimodal is a set of multimodal embeddings previously created by
+	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
+	// models or for batches without multimodal elements.
+	Multimodal []MultimodalIndex
+}