* create: add server-side MLX imports and drop GGUF conversion
Support safetensors imports through the MLX create pipeline both locally and on the server, including remote upload/staging, draft layer handling, cancellation propagation, transfer limits, and shared manifest/blob writing.
Limit GGUF create to wrapping existing GGUF inputs into Ollama manifests. Remove the in-tree safetensors-to-GGUF converter, server quantization path, and converter-only dependencies so GGUF conversion and quantization stay in llama.cpp tooling.
Keep the MLX path focused on supported safetensors model creation with validation before MLX work, and expose that flow without the --experimental CLI gate.
* address comments
* add client side gguf create fast path
* address comments
* rebase adjustments
Remove the x/imagegen tree (MLX image generation engine, Flux2/zimage
models, cache, C bindings) and all imagegen integration points:
- server: drop imagegen routes, scheduling, and generate handling
- api/cmd/docs: remove image generation API surface and docs
- middleware/openai: remove image endpoint support
- integration: remove imagegen test suites
- x/create: adopt the rewritten create pipeline from main; drop
imagegen create path (CreateImageGenModel, IsTensorModelDir,
model_index.json detection, Flux2KleinPipeline vision hack)
- retain x/imagegen/manifest (Ollama-store safetensors manifest
loader), still used by x/mlxrunner and x/create/client
- fix Windows MLX dl.dll install, MLX CMake version path, and the
show command after removing safetensors models
This refactors the existing integration tests into 3 priumary groups: fast,
release, and library. It also refines some of the release tests to drop some
of the older models and pick up newer models, while retaining the broad
coverage in the library group.
* test: integration test hardening
Improve reliability on slower systems, and some flakes. Fix
a few logic flaws on the newer tests, general hardening.
* tighten up vision logging
* add new models
* remove some older models - still covered by library scenarios
* create: Clean up experimental paths
This cleans up the experimental features, and adds both unit and integration test coverage to verify no regressions.
* create: preserve config and layer names when creating from safetensors models
When creating a model FROM an existing safetensors model, ModelFormat,
Capabilities, and layer Name fields were lost. ModelFormat stayed empty
because it's only set from GGML layers (which safetensors models lack),
and layer names weren't copied in parseFromModel. This caused derived
models to fail loading ("config.json not found in manifest").
* review comments
Daniel HiltgenandGitHub
Jeffrey MorganandGitHub
Patrick DevineandGitHub