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65 Commits

Author SHA1 Message Date
Jeffrey Morgan
f3b476c592 build: add -O3 optimization to CGO flags (#13877)
CGO_CFLAGS and CGO_CXXFLAGS were being set without optimization flags,
which overrides Go's default -O2 and results in unoptimized C++ code.

This caused significant performance degradation in release builds
compared to local `go build` which uses the default optimization.

- build_darwin.sh: add -O3 to CGO_CFLAGS and CGO_CXXFLAGS exports
- Dockerfile: preserve CGO_CFLAGS/CGO_CXXFLAGS from build args instead
  of overwriting them
- app/README.md: update documentation to include -O3
2026-01-24 10:55:38 -08:00
Parth Sareen
5267d31d56 docs: ollama launch (#13852) 2026-01-23 23:18:50 -08:00
Stillhart
b44f56319f README: Update the "Ollama for ruby" to the most popular and maintained ruby gem. (#13855)
* update README ruby link

the ollama-ai ruby gem is vastly less popular and seems unmaintained
https://rubygems.org/gems/ollama-ai

the defacto standard with the most downloads in the ruby ecosystem is ruby_llm
https://rubygems.org/gems/ruby_llm

I would link to that to avoid complication and guarantee feature compatibility with ollama.

* Update gem link ruby_llm from website to GitHub

ollama links mostly to github, not project websites, hence link to ruby_llm github.
2026-01-24 01:24:52 -05:00
Jeffrey Morgan
0209c268bb llama: fix CUDA MMA errors in release build (#13874) 2026-01-23 20:10:04 -08:00
Jeffrey Morgan
912d984346 llama: fix fattn-tile shared memory overflow on sm_50/52 (#13872)
Use nthreads=128 for ncols=4 configurations in flash attention tile
kernel to reduce shared memory usage below 48KB limit on Maxwell
architectures (sm_50/52).

With nthreads=256 and ncols=4, np=2 which caused shared memory to
exceed 48KB. With nthreads=128 and ncols=4, np=1 keeps shared memory
under the limit.
2026-01-23 19:22:32 -08:00
Parth Sareen
aae6ecbaff cmd: rename ollama config to ollama launch (#13871) 2026-01-23 18:40:40 -08:00
Jeffrey Morgan
64737330a4 Re-apply "model: add MLA absorption for glm4moelite" with fix (#13870)
The nvidia_fp32 config for (576, 512) head sizes had nbatch_fa=32,
which caused zero-sized arrays when computing array dimensions:
  nbatch_fa / (np * warp_size) = 32 / (2 * 32) = 0

This resulted in CUDA compilation failures on CUDA 12 (Windows and
Linux arm64):
- "static assertion failed with nbatch_fa % (np*warp_size) != 0"
- "the size of an array must be greater than zero"

Fix by changing nbatch_fa from 32 to 64 for all (576, 512) configs
in the nvidia_fp32 function, matching the nvidia_fp16 and AMD configs.
2026-01-23 18:40:28 -08:00
Jeffrey Morgan
2eda97f1c3 Revert "model: add MLA absorption for glm4moelite (#13810)" (#13869)
This reverts commit 1044b0419a.
2026-01-23 17:14:15 -08:00
Jeffrey Morgan
66831dcf70 x/imagegen: fix image editing support (#13866)
- Fix panic in ollama show for image gen models (safe type assertion)
- Add vision capability for Flux2KleinPipeline models at create time
- Flatten transparent PNG images onto white background for better results
2026-01-23 15:37:17 -08:00
Jeffrey Morgan
1044b0419a model: add MLA absorption for glm4moelite (#13810)
* model: add MLA absorption for glm4moelite

Split the combined KV_B tensor into separate K_B and V_B tensors
during conversion, enabling MLA (Multi-head Latent Attention)
absorption which compresses the KV cache for improved efficiency.

* ggml: enable MLA flash attention for GLM-4.7-flash

Add support for gqa_ratio 4 in MLA flash attention kernels. GLM-4.7-flash
uses head size 576 with gqa_ratio 4, which was previously only supported
for gqa_ratio 16 (DeepSeek).

Metal changes:
- Enable head size 576 for flash attention
- Increase simdgroups to 8 for large heads (>=512)
- Add case 8 kernel dispatch for 8 simdgroups

CUDA changes:
- Add gqa_ratio 4 support for head 576/512
- Add tile configs for (576, 512, 4) and (576, 512, 8)
- Add MMA config cases for ncols 4
- Add template instances for ncols2=4

* model: add compatibility validation for glm4moelite architecture
2026-01-23 14:47:42 -08:00
Parth Sareen
771d9280ec cmd: ollama config fix droid model name configuration (#13856) 2026-01-23 11:44:22 -08:00
Jeffrey Morgan
862bc0a3bf x/imagegen: respect stream=false in /api/generate (#13853)
When stream=false is set for image generation requests, return a single
JSON response instead of streaming multiple ndjson progress updates.
2026-01-22 22:16:39 -08:00
Jeffrey Morgan
c01608b6a1 x/imagegen: add image edit capabilities (#13846) 2026-01-22 20:35:08 -08:00
Parth Sareen
199c41e16e cmd: ollama config command to help configure integrations to use Ollama (#13712) 2026-01-22 20:17:11 -08:00
Jeffrey Morgan
3b3bf6c217 x/imagegen: replace memory estimation with actual weight size (#13848)
Remove static VRAM estimation (EstimateVRAM, CheckMemoryRequirements)
which wasn't helpful. Instead, report the actual tensor weight size
from the manifest for ollama ps.

- Remove memory estimation check from runner startup
- Remove EstimateVRAM, CheckMemoryRequirements, modelVRAMEstimates
- Add TotalTensorSize() to get actual weight size from manifest
- Use weight size for Server.vramSize instead of estimates

Note: This is better than showing 0 or inaccurate estimates, but the
weight size is a drastic underestimation of actual memory usage since
it doesn't account for activations, intermediate tensors, or MLX
overhead. Future work should query real-time memory from MLX
(e.g., MetalGetActiveMemory) for accurate reporting.
2026-01-22 18:32:41 -08:00
Parth Sareen
f52c21f457 fix: handle Enter key pressed during model loading (#13839) 2026-01-22 18:32:02 -08:00
Jeffrey Morgan
b5d0f72f16 x/imagegen: remove qwen_image and qwen_image_edit models (#13827)
Remove the Qwen image generation and image editing model packages
to clean up the codebase. These models will be reintroduced later.

- Delete x/imagegen/models/qwen_image/ (10 files)
- Delete x/imagegen/models/qwen_image_edit/ (5 files)
- Remove related CLI flags and imports from cmd/engine/main.go
- Update comments in cache/step.go to remove Qwen-specific references
2026-01-21 13:37:08 -08:00
Patrick Devine
148a1be0a3 Clean up the manifest and modelpath (#13807) 2026-01-21 11:46:17 -08:00
next-n
d6dd430abd x/imagegen: respect OLLAMA_MODELS for manifests and blobs (#13797) 2026-01-20 13:01:52 -08:00
Daniel Hiltgen
ae78112c50 test: add lfm2.5-thinking coverage (#13802) 2026-01-20 12:57:02 -08:00
Jeffrey Morgan
01cf7445f3 model: add lfm2 architecture and LFM2.5-1.2B-Thinking support (#13792)
Co-Authored-By: TommyBoiss <165361500+TommyBoiss@users.noreply.github.com>
2026-01-20 12:20:53 -08:00
Jeffrey Morgan
31085d5e53 fix: use api.GenerateRequest for image generation test (#13793)
Remove non-existent x/imagegen/api import and use the standard
api.GenerateRequest/GenerateResponse with the Image field instead.
2026-01-20 03:23:31 -08:00
Daniel Hiltgen
c42e9d244f test: add image gen test case (#13698)
* test: fix type regression in tools test.

* test: add image gen integration test
2026-01-19 16:01:31 -08:00
Devon Rifkin
e98b5e8b4e /api/show: default to empty model_info (#13785)
For `/api/show`, a fully missing `model_info` field trips up various
integrators (including a recent Android Studio integration).

The primary source of missing info tends to come from models with a
remote that are also missing other data. It seems better to me to return
an empty `model_info` than making up some other fields within
`model_info` (like saying the architecture is `remote` or something like
that). So this does slightly change `/api/show`'s behavior that possibly
someone is relying on, but it seems more important to ensure the field
is always there (from a quick sampling integrations seem to be robust to
missing fields _within_ it).

Fixes: https://github.com/ollama/ollama/issues/13783
2026-01-19 15:26:17 -08:00
Jeffrey Morgan
68e00c7c36 fix: prevent image generation models from loading during deletion (#13781)
Move the unload check (empty prompt + KeepAlive=0) before the image
generation model dispatch in GenerateHandler. This prevents models like
flux from being loaded into memory just to be immediately unloaded when
running `ollama rm`.

Also fix a bug in DeleteHandler where `args[0]` was used instead of
`arg` in the delete loop, causing only the first model to be unloaded
when deleting multiple models.
2026-01-19 12:48:34 -08:00
Jeffrey Morgan
4f138a1749 model: add Glm4MoeLiteForCausalLM architecture to support GLM-4.7-Flash (#13779) 2026-01-19 12:47:17 -08:00
Jeffrey Morgan
03bf241c33 x/imagegen: add FP4 quantization support for image generation models (#13773)
Add --quantize fp4 support to ollama create for image generation models
(flux2, z-image-turbo), using MLX's affine 4-bit quantization.

Changes:
- Add fp4 to validation in CreateImageGenModel
- Add FP4 case to quantizeTensor (group_size=32, bits=4, affine mode)
- Add GetQuantization() to WeightSource interface for dynamic params
- Update LoadLinearLayer to use quantization params from model metadata
2026-01-19 00:54:54 -08:00
Jeffrey Morgan
a887406c24 x/imagegen: add preliminary support for FLUX.2-klein model (#13772) 2026-01-18 22:30:49 -08:00
Jeffrey Morgan
d51e95ba7e server: prevent image generation models from reloading on every request (#13771)
The loadImageGen function was not setting Options on the runnerRef,
causing needsReload() to always return true (since it checks if
runner.Options == nil). This resulted in the image generation
subprocess being killed and restarted for every request.
2026-01-18 20:50:04 -08:00
Jeffrey Morgan
3d01f2aa34 parsers: refactor Nemotron parser to reuse Qwen3Coder for tool calls (#13764)
Simplify Nemotron3NanoParser by delegating tool call parsing to
Qwen3CoderParser instead of duplicating the parsing logic. The
Nemotron parser now only handles the thinking state machine and
transitions to Qwen3CoderParser for content and tool call parsing.

This also fixes an issue where tool calls without </think> would
cause the parser to get stuck in thinking mode.
2026-01-17 18:28:52 -08:00
Jeffrey Morgan
634c416645 Add experimental image generation fields to /api/generate (#13753)
Request fields (experimental):
- width: image width (max 4096)
- height: image height (max 4096)
- steps: denoising steps
- seed: random seed

Response fields (experimental):
- images: base64-encoded generated images
- completed: current step progress
- total: total steps

Other changes:
- Fix lifecycle bug where image models wouldn't unload (refCount issue)
- Fix "headers already written" error on Ctrl+C during streaming
- Add gin middleware for OpenAI /v1/images/generations compatibility
- Update CLI to use /api/generate with progress bar
- Add preload support in interactive mode
2026-01-17 18:27:41 -08:00
Michael
57de86cc61 docs: update claude code docs (#13757)
* docs: update claude code docs
2026-01-16 22:41:34 -08:00
Daniel Hiltgen
12719b6e87 MLX - dynamic loading of mlx-c (#13735)
* MLX - dynamic loading of mlx-c

Create a wrapper layer to indirect the dependency on mlx-c so
the main ollama binary does not have a load-time dependency on mlx-c, mlx, and on linux, cuda.  Lazy load the library via dlopen
so we can adjust the path to ensure the dependencies are found
and fail gracefully if not present.

* review comments

* fix broken tests
2026-01-16 16:34:22 -08:00
Patrick Devine
a077d996e3 Fix create and show commands for experimental models (#13741)
* x: make `ollama create --experimental` import from safetensors

This change allows pulling in safetensors models into the new experimental model format, and also
fixes the `ollama show` command to be able to correctly display the model information.

* gofumpt the linter

* gofumpt the linter again

* validate the model name
2026-01-16 14:31:55 -08:00
Jeffrey Morgan
c23d5095de x/imagegen: clean up image generation code (#13725) 2026-01-16 12:19:25 -08:00
Bruce MacDonald
7601f0e93e server: reject unexpected auth hosts (#13738)
Added validation to ensure auth redirects stay on the same host as the original request. The fix is a single check in getAuthorizationToken comparing the realm URL's host against the request host. Added tests for the auth flow.

Co-Authored-By: Gecko Security <188164982+geckosecurity@users.noreply.github.com>

* gofmt

---------

Co-authored-by: Gecko Security <188164982+geckosecurity@users.noreply.github.com>
2026-01-16 14:10:36 -05:00
Eva H
aad3f03890 app: allow macOS app to terminate during system shutdown (#13737) 2026-01-16 09:05:04 -05:00
Gyungrai Wang
55d0b6e8b9 integration: fix tools_test.go for ToolCallFunctionArguments API change (#13731) 2026-01-15 16:08:09 -08:00
Devon Rifkin
38eac40d56 openai: tweak v1/responses to conform better (#13736)
* openai: tweak v1/responses to conform better

* openai: provide better error for image URLs

* lint
2026-01-15 15:46:36 -08:00
Jeffrey Morgan
80f3f1bc25 readme: add instructions to build with MLX (#13733) 2026-01-15 11:03:52 -08:00
Parth Sareen
b1a0db547b docs: add env var needed for claude code in docs (#13721) 2026-01-15 10:11:00 -08:00
Parth Sareen
75d7b5f926 cmd: enable multi-line input and shift enter (#13694) 2026-01-14 17:52:46 -08:00
vincent d warmerdam
349d814814 docs: add marimo integration (#13326)
* docs added

* fix title

* add marimo to docs.json

---------

Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2026-01-14 17:37:38 -08:00
Yuhong Sun
c8743031e0 docs: add onyx integration (#13135)
* Ready for team review

* Update docs/integrations/onyx.mdx

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

* update docs.json

---------

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2026-01-14 17:32:05 -08:00
Jeffrey Morgan
4adb9cf4bb scripts: fix macOS auto-update signature verification failure (#13713)
Add --norsrc flag to ditto commands when creating Ollama-darwin.zip
to exclude AppleDouble resource fork files (._* files) from the archive.

The mlx.metallib file has extended attributes, which causes ditto to
include a ._mlx.metallib AppleDouble file in the zip. Since this file
is not part of the code signature seal, macOS rejects the bundle during
auto-update verification with:

  "a sealed resource is missing or invalid"
  "file added: .../._mlx.metallib"

The --norsrc flag prevents ditto from preserving resource forks and
extended attributes, ensuring only signed files are included in the
release archive.
2026-01-14 07:48:10 -08:00
Daniel Hiltgen
74f475e735 Revert "Documentation edits made through Mintlify web editor" (#13688)
This reverts commit c6d4c0c7f2.

Merge after 0.14.0 ships for the updated Linux documentation.
2026-01-14 07:42:34 -08:00
Maternion
875cecba74 docs: update default context window size to 4096 tokens (#13709) 2026-01-14 01:01:28 -08:00
Josh Daniel Bañares
7d411a4686 docs: update web search param in examples (#13711) 2026-01-14 00:38:39 -08:00
Daniel Hiltgen
02a2401596 mlx: bundle openblas dependency (#13706) 2026-01-13 15:29:47 -08:00
Daniel Hiltgen
e4b488a7b5 CI: dedup cuda libraries to reduce payload size (#13704) 2026-01-13 11:25:31 -08:00
Daniel Hiltgen
98079ddd79 ci: add missing mlx components to release build (#13702) 2026-01-13 09:13:09 -08:00
Jeffrey Morgan
d70942f47b x/imagegen/cli: skip local model check (#13699) 2026-01-12 22:38:10 -08:00
Jeffrey Morgan
58e4701557 scripts: increase notarization timeout to 20m (#13697)
The 100MB mlx.metallib file significantly increased the app bundle size,
causing Apple's notarization service to timeout with the previous 10m limit.
2026-01-12 20:38:38 -08:00
Jeffrey Morgan
dbf47ee55a cmake: use CMAKE_SYSTEM_PROCESSOR instead of CMAKE_OSX_ARCHITECTURES for mlx.metallib install (#13696)
The CMake condition for installing mlx.metallib checks
CMAKE_OSX_ARCHITECTURES, but this variable is only set when explicitly
passed - not auto-detected. The arm64 build was missing this flag,
causing the metallib to not be installed, which then caused codesign
to fail on the unexpanded glob pattern.
2026-01-12 20:05:11 -08:00
Jeffrey Morgan
af7ea6e96e x/imagegen: install mlx.metallib and fix macOS rpath handling, add mlx library directories to LD_LIBRARY_PATH (#13695)
- Install mlx.metallib for arm64 builds (required for Metal GPU acceleration)
- Apply rpath settings to all macOS builds, not just x86_64
- Add CMAKE_BUILD_WITH_INSTALL_RPATH to avoid install_name_tool errors
- Update build_darwin.sh to copy, sign, and package the metallib
2026-01-12 19:03:11 -08:00
Jeffrey Morgan
8f1e0140e7 x/imagegen: fix mlx build in Dockerfile and macOS build script (#13693) 2026-01-12 15:52:43 -08:00
Parth Sareen
35c3c9e3c2 anthropic: allow non-thinking models when using Anthropic API (#13692) 2026-01-12 15:13:26 -08:00
Parth Sareen
d06acbcb19 x/cmd: enable web search and web fetch with flag (#13690) 2026-01-12 13:59:40 -08:00
Jeffrey Morgan
9667c2282f x/imagegen: add naive TeaCache and FP8 quantization support (#13683)
TeaCache:
- Timestep embedding similarity caching for diffusion models
- Polynomial rescaling with configurable thresholds
- Reduces transformer forward passes by ~30-50%

FP8 quantization:
- Support for FP8 quantized models (8-bit weights with scales)
- QuantizedMatmul on Metal, Dequantize on CUDA
- Client-side quantization via ollama create --quantize fp8

Other bug fixes:
- Fix `/api/show` API for image generation models
- Server properly returns model info (architecture, parameters, quantization)
- Memory allocation optimizations
- CLI improvements for image generation
2026-01-12 13:45:22 -08:00
Jeffrey Morgan
a937a68317 server: fix slow 'ollama rm' of models with many layers (#13680)
RemoveLayers was calling Manifests() for each layer to check if it was
shared with other models. For models with many blobs (e.g., tensor
models), this caused O(N*M) manifest reads.

Now loads manifests once and builds a set of in-use digests.
2026-01-12 13:17:48 -08:00
Parth Sareen
2185112d84 x/cmd: connect /set flags to behavior in experimental mode (#13684) 2026-01-12 00:40:44 -08:00
Parth Sareen
91926601dc x: add missing /set, /show, /load, /save commands to experimental mode (#13682) 2026-01-11 23:12:31 -08:00
Jeffrey Morgan
361d6c16c2 x/imagegen/transfer: fix timeout and progress reporting (#13679)
Removes 5-minute HTTP client timeout that caused "context deadline
exceeded" errors on large file downloads. Stall detection (10s)
already handles unresponsive connections.

Fixes progress bar total going down on resume by calculating total
from all blobs upfront and reporting already-downloaded bytes
as completed immediately.
2026-01-11 15:33:53 -08:00
Patrick Devine
7e2496e88e Fix cmake install command in README (#13678)
Update installation command for MLX component in README.
2026-01-11 13:16:42 -08:00
WhatToPutHere
5b84e29882 docs: fix troubleshooting page (#13674)
Updated the link in the log output description to point to the correct troubleshooting guide format.
2026-01-11 00:58:07 -08:00
257 changed files with 32214 additions and 16127 deletions

View File

@@ -13,7 +13,7 @@ body:
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. See [Troubleshooting Guide](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) for details.
description: Please copy and paste any relevant log output. See [Troubleshooting Guide](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.mdx#how-to-troubleshoot-issues) for details.
render: shell
validations:
required: false

View File

@@ -372,13 +372,17 @@ jobs:
outputs: type=local,dest=dist/${{ matrix.os }}-${{ matrix.arch }}
cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
cache-to: type=inline
- name: Deduplicate CUDA libraries
run: |
./scripts/deduplicate_cuda_libs.sh dist/${{ matrix.os }}-${{ matrix.arch }}
- run: |
for COMPONENT in bin/* lib/ollama/*; do
case "$COMPONENT" in
bin/ollama) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
bin/ollama*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/*.so*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/cuda_v*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/vulkan*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/mlx*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/cuda_jetpack5) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
lib/ollama/cuda_jetpack6) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
lib/ollama/rocm) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;

View File

@@ -48,9 +48,10 @@ if((CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_OSX_ARCHITECTURES MATCHES "arm64")
set(GGML_CPU_ALL_VARIANTS ON)
endif()
if (CMAKE_OSX_ARCHITECTURES MATCHES "x86_64")
if(APPLE)
set(CMAKE_BUILD_RPATH "@loader_path")
set(CMAKE_INSTALL_RPATH "@loader_path")
set(CMAKE_BUILD_WITH_INSTALL_RPATH ON)
endif()
set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
@@ -189,13 +190,21 @@ if(MLX_ENGINE)
install(TARGETS mlx mlxc
RUNTIME_DEPENDENCIES
DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
PRE_INCLUDE_REGEXES cublas cublasLt cudart nvrtc cudnn nccl
PRE_INCLUDE_REGEXES cublas cublasLt cudart nvrtc nvrtc-builtins cudnn nccl openblas gfortran
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
)
# Install the Metal library for macOS arm64 (must be colocated with the binary)
# Metal backend is only built for arm64, not x86_64
if(APPLE AND CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
install(FILES ${CMAKE_BINARY_DIR}/_deps/mlx-build/mlx/backend/metal/kernels/mlx.metallib
DESTINATION ${OLLAMA_INSTALL_DIR}
COMPONENT MLX)
endif()
# Manually install cudart and cublas since they might not be picked up as direct dependencies
if(CUDAToolkit_FOUND)
file(GLOB CUDART_LIBS

View File

@@ -32,7 +32,7 @@ ENV PATH=/${VULKANVERSION}/x86_64/bin:$PATH
FROM --platform=linux/arm64 almalinux:8 AS base-arm64
# install epel-release for ccache
RUN yum install -y yum-utils epel-release \
&& dnf install -y clang ccache \
&& dnf install -y clang ccache git \
&& yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo
ENV CC=clang CXX=clang++
@@ -149,6 +149,7 @@ COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
COPY x/ml/backend/mlx x/ml/backend/mlx
COPY go.mod go.sum .
COPY MLX_VERSION .
RUN curl -fsSL https://golang.org/dl/go$(awk '/^go/ { print $2 }' go.mod).linux-$(case $(uname -m) in x86_64) echo amd64 ;; aarch64) echo arm64 ;; esac).tar.gz | tar xz -C /usr/local
ENV PATH=/usr/local/go/bin:$PATH
RUN go mod download
@@ -156,11 +157,6 @@ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'MLX CUDA 13' -DBLAS_INCLUDE_DIRS=/usr/include/openblas -DLAPACK_INCLUDE_DIRS=/usr/include/openblas \
&& cmake --build --parallel ${PARALLEL} --preset 'MLX CUDA 13' \
&& cmake --install build --component MLX --strip --parallel ${PARALLEL}
COPY . .
ARG GOFLAGS="'-ldflags=-w -s'"
ENV CGO_ENABLED=1
ARG CGO_CFLAGS
ARG CGO_CXXFLAGS
FROM base AS build
WORKDIR /go/src/github.com/ollama/ollama
@@ -169,12 +165,16 @@ RUN curl -fsSL https://golang.org/dl/go$(awk '/^go/ { print $2 }' go.mod).linux-
ENV PATH=/usr/local/go/bin:$PATH
RUN go mod download
COPY . .
# Clone mlx-c headers for CGO (version from MLX_VERSION file)
RUN git clone --depth 1 --branch "$(cat MLX_VERSION)" https://github.com/ml-explore/mlx-c.git build/_deps/mlx-c-src
ARG GOFLAGS="'-ldflags=-w -s'"
ENV CGO_ENABLED=1
ARG CGO_CFLAGS
ARG CGO_CXXFLAGS
ENV CGO_CFLAGS="${CGO_CFLAGS} -I/go/src/github.com/ollama/ollama/build/_deps/mlx-c-src"
ENV CGO_CXXFLAGS="${CGO_CXXFLAGS}"
RUN --mount=type=cache,target=/root/.cache/go-build \
go build -trimpath -buildmode=pie -o /bin/ollama .
go build -tags mlx -trimpath -buildmode=pie -o /bin/ollama .
FROM --platform=linux/amd64 scratch AS amd64
# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/

1
MLX_VERSION Normal file
View File

@@ -0,0 +1 @@
v0.4.1

View File

@@ -48,7 +48,7 @@ ollama run gemma3
## Model library
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library "ollama model library")
Here are some example models that can be downloaded:
@@ -79,7 +79,7 @@ Here are some example models that can be downloaded:
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Granite-3.3 | 8B | 4.9GB | `ollama run granite3.3` |
| Granite-3.3 | 8B | 4.9GB | `ollama run granite3.3` |
> [!NOTE]
> You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
@@ -260,6 +260,38 @@ Finally, in a separate shell, run a model:
./ollama run llama3.2
```
## Building with MLX (experimental)
First build the MLX libraries:
```shell
cmake --preset MLX
cmake --build --preset MLX --parallel
cmake --install build --component MLX
```
When building with the `-tags mlx` flag, the main `ollama` binary includes MLX support for experimental features like image generation:
```shell
go build -tags mlx .
```
Finally, start the server:
```
./ollama serve
```
### Building MLX with CUDA
When building with CUDA, use the preset "MLX CUDA 13" or "MLX CUDA 12" to enable CUDA with default architectures:
```shell
cmake --preset 'MLX CUDA 13'
cmake --build --preset 'MLX CUDA 13' --parallel
cmake --install build --component MLX
```
## REST API
Ollama has a REST API for running and managing models.
@@ -290,6 +322,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
### Web & Desktop
- [Onyx](https://github.com/onyx-dot-app/onyx)
- [Open WebUI](https://github.com/open-webui/open-webui)
- [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat)
- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
@@ -421,7 +454,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) (AI collaborative workspace with Ollama, cross-platform and self-hostable)
- [Lumina](https://github.com/cushydigit/lumina.git) (A lightweight, minimal React.js frontend for interacting with Ollama servers)
- [Tiny Notepad](https://pypi.org/project/tiny-notepad) (A lightweight, notepad-like interface to chat with ollama available on PyPI)
- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.)
- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.)
- [GPTranslate](https://github.com/philberndt/GPTranslate) (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.)
- [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
- [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
@@ -493,7 +526,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
### Database
- [pgai](https://github.com/timescale/pgai) - PostgreSQL as a vector database (Create and search embeddings from Ollama models using pgvector)
- [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md)
- [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md)
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps)
- [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama)
- [Kangaroo](https://github.com/dbkangaroo/kangaroo) (AI-powered SQL client and admin tool for popular databases)
@@ -525,7 +558,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [LiteLLM](https://github.com/BerriAI/litellm)
- [OllamaFarm for Go](https://github.com/presbrey/ollamafarm)
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
- [Ollama for Ruby](https://github.com/crmne/ruby_llm)
- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
- [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp)
- [Ollama4j for Java](https://github.com/ollama4j/ollama4j)
@@ -636,6 +669,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [llama.cpp](https://github.com/ggml-org/llama.cpp) project founded by Georgi Gerganov.
### Observability
- [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native integration to Ollama.
- [Lunary](https://lunary.ai/docs/integrations/ollama) is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing.
- [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics.
@@ -644,4 +678,5 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.
### Security
- [Ollama Fortress](https://github.com/ParisNeo/ollama_proxy_server)

View File

@@ -165,7 +165,7 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
return nil
}
const maxBufferSize = 512 * format.KiloByte
const maxBufferSize = 8 * format.MegaByte
func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
var buf io.Reader

View File

@@ -127,6 +127,20 @@ type GenerateRequest struct {
// each with an associated log probability. Only applies when Logprobs is true.
// Valid values are 0-20. Default is 0 (only return the selected token's logprob).
TopLogprobs int `json:"top_logprobs,omitempty"`
// Experimental: Image generation fields (may change or be removed)
// Width is the width of the generated image in pixels.
// Only used for image generation models.
Width int32 `json:"width,omitempty"`
// Height is the height of the generated image in pixels.
// Only used for image generation models.
Height int32 `json:"height,omitempty"`
// Steps is the number of diffusion steps for image generation.
// Only used for image generation models.
Steps int32 `json:"steps,omitempty"`
}
// ChatRequest describes a request sent by [Client.Chat].
@@ -735,7 +749,7 @@ type ShowResponse struct {
Messages []Message `json:"messages,omitempty"`
RemoteModel string `json:"remote_model,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
ModelInfo map[string]any `json:"model_info,omitempty"`
ModelInfo map[string]any `json:"model_info"`
ProjectorInfo map[string]any `json:"projector_info,omitempty"`
Tensors []Tensor `json:"tensors,omitempty"`
Capabilities []model.Capability `json:"capabilities,omitempty"`
@@ -860,6 +874,20 @@ type GenerateResponse struct {
// Logprobs contains log probability information for the generated tokens,
// if requested via the Logprobs parameter.
Logprobs []Logprob `json:"logprobs,omitempty"`
// Experimental: Image generation fields (may change or be removed)
// Image contains a base64-encoded generated image.
// Only present for image generation models.
Image string `json:"image,omitempty"`
// Completed is the number of completed steps in image generation.
// Only present for image generation models during streaming.
Completed int64 `json:"completed,omitempty"`
// Total is the total number of steps for image generation.
// Only present for image generation models during streaming.
Total int64 `json:"total,omitempty"`
}
// ModelDetails provides details about a model.

View File

@@ -75,9 +75,9 @@ The `-dev` flag enables:
CI builds with Xcode 14.1 for OS compatibility prior to v13. If you want to manually build v11+ support, you can download the older Xcode [here](https://developer.apple.com/services-account/download?path=/Developer_Tools/Xcode_14.1/Xcode_14.1.xip), extract, then `mv ./Xcode.app /Applications/Xcode_14.1.0.app` then activate with:
```
export CGO_CFLAGS=-mmacosx-version-min=12.0
export CGO_CXXFLAGS=-mmacosx-version-min=12.0
export CGO_LDFLAGS=-mmacosx-version-min=12.0
export CGO_CFLAGS="-O3 -mmacosx-version-min=12.0"
export CGO_CXXFLAGS="-O3 -mmacosx-version-min=12.0"
export CGO_LDFLAGS="-mmacosx-version-min=12.0"
export SDKROOT=/Applications/Xcode_14.1.0.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
export DEVELOPER_DIR=/Applications/Xcode_14.1.0.app/Contents/Developer
```

View File

@@ -14,6 +14,7 @@ extern NSString *SystemWidePath;
@interface AppDelegate () <NSWindowDelegate, WKNavigationDelegate, WKUIDelegate>
@property(strong, nonatomic) NSStatusItem *statusItem;
@property(assign, nonatomic) BOOL updateAvailable;
@property(assign, nonatomic) BOOL systemShutdownInProgress;
@end
@implementation AppDelegate
@@ -40,6 +41,13 @@ bool firstTimeRun,startHidden; // Set in run before initialization
}
- (void)applicationDidFinishLaunching:(NSNotification *)aNotification {
// Register for system shutdown/restart notification so we can allow termination
[[[NSWorkspace sharedWorkspace] notificationCenter]
addObserver:self
selector:@selector(systemWillPowerOff:)
name:NSWorkspaceWillPowerOffNotification
object:nil];
// if we're in development mode, set the app icon
NSString *bundlePath = [[NSBundle mainBundle] bundlePath];
if (![bundlePath hasSuffix:@".app"]) {
@@ -278,7 +286,18 @@ bool firstTimeRun,startHidden; // Set in run before initialization
[NSApp activateIgnoringOtherApps:YES];
}
- (void)systemWillPowerOff:(NSNotification *)notification {
// Set flag so applicationShouldTerminate: knows to allow termination.
// The system will call applicationShouldTerminate: after posting this notification.
self.systemShutdownInProgress = YES;
}
- (NSApplicationTerminateReply)applicationShouldTerminate:(NSApplication *)sender {
// Allow termination if the system is shutting down or restarting
if (self.systemShutdownInProgress) {
return NSTerminateNow;
}
// Otherwise just hide the app (for Cmd+Q, close button, etc.)
[NSApp hide:nil];
[NSApp setActivationPolicy:NSApplicationActivationPolicyAccessory];
return NSTerminateCancel;

View File

@@ -35,6 +35,7 @@ import (
"golang.org/x/term"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/cmd/config"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/parser"
@@ -46,8 +47,9 @@ import (
"github.com/ollama/ollama/types/syncmap"
"github.com/ollama/ollama/version"
xcmd "github.com/ollama/ollama/x/cmd"
"github.com/ollama/ollama/x/create"
xcreateclient "github.com/ollama/ollama/x/create/client"
"github.com/ollama/ollama/x/imagegen"
imagegenclient "github.com/ollama/ollama/x/imagegen/client"
)
const ConnectInstructions = "To sign in, navigate to:\n %s\n\n"
@@ -93,14 +95,87 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
p := progress.NewProgress(os.Stderr)
defer p.Stop()
// Validate model name early to fail fast
modelName := args[0]
name := model.ParseName(modelName)
if !name.IsValid() {
return fmt.Errorf("invalid model name: %s", modelName)
}
// Check for --experimental flag for safetensors model creation
experimental, _ := cmd.Flags().GetBool("experimental")
if experimental {
// Get Modelfile content - either from -f flag or default to "FROM ."
var reader io.Reader
filename, err := getModelfileName(cmd)
if os.IsNotExist(err) || filename == "" {
// No Modelfile specified or found - use default
reader = strings.NewReader("FROM .\n")
} else if err != nil {
return err
} else {
f, err := os.Open(filename)
if err != nil {
return err
}
defer f.Close()
reader = f
}
// Parse the Modelfile
modelfile, err := parser.ParseFile(reader)
if err != nil {
return fmt.Errorf("failed to parse Modelfile: %w", err)
}
// Extract FROM path and configuration
var modelDir string
mfConfig := &xcreateclient.ModelfileConfig{}
for _, cmd := range modelfile.Commands {
switch cmd.Name {
case "model":
modelDir = cmd.Args
case "template":
mfConfig.Template = cmd.Args
case "system":
mfConfig.System = cmd.Args
case "license":
mfConfig.License = cmd.Args
}
}
if modelDir == "" {
modelDir = "."
}
// Resolve relative paths based on Modelfile location
if !filepath.IsAbs(modelDir) && filename != "" {
modelDir = filepath.Join(filepath.Dir(filename), modelDir)
}
quantize, _ := cmd.Flags().GetString("quantize")
return xcreateclient.CreateModel(xcreateclient.CreateOptions{
ModelName: modelName,
ModelDir: modelDir,
Quantize: quantize,
Modelfile: mfConfig,
}, p)
}
var reader io.Reader
filename, err := getModelfileName(cmd)
if os.IsNotExist(err) {
if filename == "" {
// No Modelfile found - check if current directory is an image gen model
if imagegen.IsTensorModelDir(".") {
return imagegenclient.CreateModel(args[0], ".", p)
if create.IsTensorModelDir(".") {
quantize, _ := cmd.Flags().GetString("quantize")
return xcreateclient.CreateModel(xcreateclient.CreateOptions{
ModelName: modelName,
ModelDir: ".",
Quantize: quantize,
}, p)
}
reader = strings.NewReader("FROM .\n")
} else {
@@ -133,7 +208,7 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
}
spinner.Stop()
req.Model = args[0]
req.Model = modelName
quantize, _ := cmd.Flags().GetString("quantize")
if quantize != "" {
req.Quantize = quantize
@@ -464,14 +539,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
name := args[0]
// Check if this is a known image generation model (skip Show/Pull)
if imagegen.HasTensorLayers(name) {
if opts.Prompt == "" && !interactive {
return errors.New("image generation models require a prompt. Usage: ollama run " + name + " \"your prompt here\"")
}
return imagegen.RunCLI(cmd, name, opts.Prompt, interactive, opts.KeepAlive)
}
info, err := func() (*api.ShowResponse, error) {
showReq := &api.ShowRequest{Name: name}
info, err := client.Show(cmd.Context(), showReq)
@@ -533,9 +600,18 @@ func RunHandler(cmd *cobra.Command, args []string) error {
return generateEmbedding(cmd, name, opts.Prompt, opts.KeepAlive, truncate, dimensions)
}
// Check if this is an image generation model
if slices.Contains(info.Capabilities, model.CapabilityImage) {
if opts.Prompt == "" && !interactive {
return errors.New("image generation models require a prompt. Usage: ollama run " + name + " \"your prompt here\"")
}
return imagegen.RunCLI(cmd, name, opts.Prompt, interactive, opts.KeepAlive)
}
// Check for experimental flag
isExperimental, _ := cmd.Flags().GetBool("experimental")
yoloMode, _ := cmd.Flags().GetBool("experimental-yolo")
enableWebsearch, _ := cmd.Flags().GetBool("experimental-websearch")
if interactive {
if err := loadOrUnloadModel(cmd, &opts); err != nil {
@@ -565,7 +641,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
// Use experimental agent loop with tools
if isExperimental {
return xcmd.GenerateInteractive(cmd, opts.Model, opts.WordWrap, opts.Options, opts.Think, opts.HideThinking, opts.KeepAlive, yoloMode)
return xcmd.GenerateInteractive(cmd, opts.Model, opts.WordWrap, opts.Options, opts.Think, opts.HideThinking, opts.KeepAlive, yoloMode, enableWebsearch)
}
return generateInteractive(cmd, opts)
@@ -671,7 +747,11 @@ func PushHandler(cmd *cobra.Command, args []string) error {
bar, ok := bars[resp.Digest]
if !ok {
bar = progress.NewBar(fmt.Sprintf("pushing %s...", resp.Digest[7:19]), resp.Total, resp.Completed)
msg := resp.Status
if msg == "" {
msg = fmt.Sprintf("pushing %s...", resp.Digest[7:19])
}
bar = progress.NewBar(msg, resp.Total, resp.Completed)
bars[resp.Digest] = bar
p.Add(resp.Digest, bar)
}
@@ -820,11 +900,11 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
for _, arg := range args {
// Unload the model if it's running before deletion
if err := loadOrUnloadModel(cmd, &runOptions{
Model: args[0],
Model: arg,
KeepAlive: &api.Duration{Duration: 0},
}); err != nil {
if !strings.Contains(strings.ToLower(err.Error()), "not found") {
fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", args[0])
fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", arg)
}
}
@@ -837,11 +917,6 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
}
func ShowHandler(cmd *cobra.Command, args []string) error {
// Check if this is an image generation model
if imagegen.HasTensorLayers(args[0]) {
return imagegen.Show(args[0], os.Stdout)
}
client, err := api.ClientFromEnvironment()
if err != nil {
return err
@@ -944,8 +1019,10 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
}
if resp.ModelInfo != nil {
arch := resp.ModelInfo["general.architecture"].(string)
rows = append(rows, []string{"", "architecture", arch})
arch, _ := resp.ModelInfo["general.architecture"].(string)
if arch != "" {
rows = append(rows, []string{"", "architecture", arch})
}
var paramStr string
if resp.Details.ParameterSize != "" {
@@ -955,7 +1032,9 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
paramStr = format.HumanNumber(uint64(f))
}
}
rows = append(rows, []string{"", "parameters", paramStr})
if paramStr != "" {
rows = append(rows, []string{"", "parameters", paramStr})
}
if v, ok := resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)]; ok {
if f, ok := v.(float64); ok {
@@ -1741,15 +1820,22 @@ func NewCLI() *cobra.Command {
rootCmd.Flags().BoolP("version", "v", false, "Show version information")
createCmd := &cobra.Command{
Use: "create MODEL",
Short: "Create a model",
Args: cobra.ExactArgs(1),
PreRunE: checkServerHeartbeat,
RunE: CreateHandler,
Use: "create MODEL",
Short: "Create a model",
Args: cobra.ExactArgs(1),
PreRunE: func(cmd *cobra.Command, args []string) error {
// Skip server check for experimental mode (writes directly to disk)
if experimental, _ := cmd.Flags().GetBool("experimental"); experimental {
return nil
}
return checkServerHeartbeat(cmd, args)
},
RunE: CreateHandler,
}
createCmd.Flags().StringP("file", "f", "", "Name of the Modelfile (default \"Modelfile\")")
createCmd.Flags().StringP("quantize", "q", "", "Quantize model to this level (e.g. q4_K_M)")
createCmd.Flags().Bool("experimental", false, "Enable experimental safetensors model creation")
showCmd := &cobra.Command{
Use: "show MODEL",
@@ -1786,6 +1872,7 @@ func NewCLI() *cobra.Command {
runCmd.Flags().Int("dimensions", 0, "Truncate output embeddings to specified dimension (embedding models only)")
runCmd.Flags().Bool("experimental", false, "Enable experimental agent loop with tools")
runCmd.Flags().Bool("experimental-yolo", false, "Skip all tool approval prompts (use with caution)")
runCmd.Flags().Bool("experimental-websearch", false, "Enable web search tool in experimental mode")
// Image generation flags (width, height, steps, seed, etc.)
imagegen.RegisterFlags(runCmd)
@@ -1903,6 +1990,7 @@ func NewCLI() *cobra.Command {
} {
switch cmd {
case runCmd:
imagegen.AppendFlagsDocs(cmd)
appendEnvDocs(cmd, []envconfig.EnvVar{envVars["OLLAMA_HOST"], envVars["OLLAMA_NOHISTORY"]})
case serveCmd:
appendEnvDocs(cmd, []envconfig.EnvVar{
@@ -1943,6 +2031,7 @@ func NewCLI() *cobra.Command {
copyCmd,
deleteCmd,
runnerCmd,
config.LaunchCmd(checkServerHeartbeat),
)
return rootCmd

View File

@@ -1547,6 +1547,79 @@ func TestRunOptions_Copy_ThinkValueVariants(t *testing.T) {
}
}
func TestShowInfoImageGen(t *testing.T) {
var b bytes.Buffer
err := showInfo(&api.ShowResponse{
Details: api.ModelDetails{
Family: "ZImagePipeline",
ParameterSize: "10.3B",
QuantizationLevel: "FP8",
},
Capabilities: []model.Capability{model.CapabilityImage},
Requires: "0.14.0",
}, false, &b)
if err != nil {
t.Fatal(err)
}
expect := " Model\n" +
" architecture ZImagePipeline \n" +
" parameters 10.3B \n" +
" quantization FP8 \n" +
" requires 0.14.0 \n" +
"\n" +
" Capabilities\n" +
" image \n" +
"\n"
if diff := cmp.Diff(expect, b.String()); diff != "" {
t.Errorf("unexpected output (-want +got):\n%s", diff)
}
}
func TestPushProgressMessage(t *testing.T) {
tests := []struct {
name string
status string
digest string
wantMsg string
}{
{
name: "uses status when provided",
status: "uploading model",
digest: "sha256:abc123456789def",
wantMsg: "uploading model",
},
{
name: "falls back to digest when status empty",
status: "",
digest: "sha256:abc123456789def",
wantMsg: "pushing abc123456789...",
},
{
name: "handles short digest gracefully",
status: "",
digest: "sha256:abc",
wantMsg: "pushing sha256:abc...",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
msg := tt.status
if msg == "" {
if len(tt.digest) >= 19 {
msg = fmt.Sprintf("pushing %s...", tt.digest[7:19])
} else {
msg = fmt.Sprintf("pushing %s...", tt.digest)
}
}
if msg != tt.wantMsg {
t.Errorf("got %q, want %q", msg, tt.wantMsg)
}
})
}
}
func TestRunOptions_Copy_Independence(t *testing.T) {
// Test that modifications to original don't affect copy
originalThink := &api.ThinkValue{Value: "original"}

36
cmd/config/claude.go Normal file
View File

@@ -0,0 +1,36 @@
package config
import (
"fmt"
"os"
"os/exec"
)
// Claude implements Runner for Claude Code integration
type Claude struct{}
func (c *Claude) String() string { return "Claude Code" }
func (c *Claude) args(model string) []string {
if model != "" {
return []string{"--model", model}
}
return nil
}
func (c *Claude) Run(model string) error {
if _, err := exec.LookPath("claude"); err != nil {
return fmt.Errorf("claude is not installed, install from https://code.claude.com/docs/en/quickstart")
}
cmd := exec.Command("claude", c.args(model)...)
cmd.Stdin = os.Stdin
cmd.Stdout = os.Stdout
cmd.Stderr = os.Stderr
cmd.Env = append(os.Environ(),
"ANTHROPIC_BASE_URL=http://localhost:11434",
"ANTHROPIC_API_KEY=",
"ANTHROPIC_AUTH_TOKEN=ollama",
)
return cmd.Run()
}

42
cmd/config/claude_test.go Normal file
View File

@@ -0,0 +1,42 @@
package config
import (
"slices"
"testing"
)
func TestClaudeIntegration(t *testing.T) {
c := &Claude{}
t.Run("String", func(t *testing.T) {
if got := c.String(); got != "Claude Code" {
t.Errorf("String() = %q, want %q", got, "Claude Code")
}
})
t.Run("implements Runner", func(t *testing.T) {
var _ Runner = c
})
}
func TestClaudeArgs(t *testing.T) {
c := &Claude{}
tests := []struct {
name string
model string
want []string
}{
{"with model", "llama3.2", []string{"--model", "llama3.2"}},
{"empty model", "", nil},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := c.args(tt.model)
if !slices.Equal(got, tt.want) {
t.Errorf("args(%q) = %v, want %v", tt.model, got, tt.want)
}
})
}
}

61
cmd/config/codex.go Normal file
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package config
import (
"fmt"
"os"
"os/exec"
"strings"
"golang.org/x/mod/semver"
)
// Codex implements Runner for Codex integration
type Codex struct{}
func (c *Codex) String() string { return "Codex" }
func (c *Codex) args(model string) []string {
args := []string{"--oss"}
if model != "" {
args = append(args, "-m", model)
}
return args
}
func (c *Codex) Run(model string) error {
if err := checkCodexVersion(); err != nil {
return err
}
cmd := exec.Command("codex", c.args(model)...)
cmd.Stdin = os.Stdin
cmd.Stdout = os.Stdout
cmd.Stderr = os.Stderr
return cmd.Run()
}
func checkCodexVersion() error {
if _, err := exec.LookPath("codex"); err != nil {
return fmt.Errorf("codex is not installed, install with: npm install -g @openai/codex")
}
out, err := exec.Command("codex", "--version").Output()
if err != nil {
return fmt.Errorf("failed to get codex version: %w", err)
}
// Parse output like "codex-cli 0.87.0"
fields := strings.Fields(strings.TrimSpace(string(out)))
if len(fields) < 2 {
return fmt.Errorf("unexpected codex version output: %s", string(out))
}
version := "v" + fields[len(fields)-1]
minVersion := "v0.81.0"
if semver.Compare(version, minVersion) < 0 {
return fmt.Errorf("codex version %s is too old, minimum required is %s, update with: npm update -g @openai/codex", fields[len(fields)-1], "0.81.0")
}
return nil
}

28
cmd/config/codex_test.go Normal file
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package config
import (
"slices"
"testing"
)
func TestCodexArgs(t *testing.T) {
c := &Codex{}
tests := []struct {
name string
model string
want []string
}{
{"with model", "llama3.2", []string{"--oss", "-m", "llama3.2"}},
{"empty model", "", []string{"--oss"}},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := c.args(tt.model)
if !slices.Equal(got, tt.want) {
t.Errorf("args(%q) = %v, want %v", tt.model, got, tt.want)
}
})
}
}

115
cmd/config/config.go Normal file
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// Package config provides integration configuration for external coding tools
// (Claude Code, Codex, Droid, OpenCode) to use Ollama models.
package config
import (
"encoding/json"
"errors"
"fmt"
"os"
"path/filepath"
"strings"
)
type integration struct {
Models []string `json:"models"`
}
type config struct {
Integrations map[string]*integration `json:"integrations"`
}
func configPath() (string, error) {
home, err := os.UserHomeDir()
if err != nil {
return "", err
}
return filepath.Join(home, ".ollama", "config", "config.json"), nil
}
func load() (*config, error) {
path, err := configPath()
if err != nil {
return nil, err
}
data, err := os.ReadFile(path)
if err != nil {
if os.IsNotExist(err) {
return &config{Integrations: make(map[string]*integration)}, nil
}
return nil, err
}
var cfg config
if err := json.Unmarshal(data, &cfg); err != nil {
return nil, fmt.Errorf("failed to parse config: %w, at: %s", err, path)
}
if cfg.Integrations == nil {
cfg.Integrations = make(map[string]*integration)
}
return &cfg, nil
}
func save(cfg *config) error {
path, err := configPath()
if err != nil {
return err
}
if err := os.MkdirAll(filepath.Dir(path), 0o755); err != nil {
return err
}
data, err := json.MarshalIndent(cfg, "", " ")
if err != nil {
return err
}
return writeWithBackup(path, data)
}
func saveIntegration(appName string, models []string) error {
if appName == "" {
return errors.New("app name cannot be empty")
}
cfg, err := load()
if err != nil {
return err
}
cfg.Integrations[strings.ToLower(appName)] = &integration{
Models: models,
}
return save(cfg)
}
func loadIntegration(appName string) (*integration, error) {
cfg, err := load()
if err != nil {
return nil, err
}
ic, ok := cfg.Integrations[strings.ToLower(appName)]
if !ok {
return nil, os.ErrNotExist
}
return ic, nil
}
func listIntegrations() ([]integration, error) {
cfg, err := load()
if err != nil {
return nil, err
}
result := make([]integration, 0, len(cfg.Integrations))
for _, ic := range cfg.Integrations {
result = append(result, *ic)
}
return result, nil
}

373
cmd/config/config_test.go Normal file
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package config
import (
"os"
"path/filepath"
"strings"
"testing"
)
// setTestHome sets both HOME (Unix) and USERPROFILE (Windows) for cross-platform tests
func setTestHome(t *testing.T, dir string) {
t.Setenv("HOME", dir)
t.Setenv("USERPROFILE", dir)
}
// editorPaths is a test helper that safely calls Paths if the runner implements Editor
func editorPaths(r Runner) []string {
if editor, ok := r.(Editor); ok {
return editor.Paths()
}
return nil
}
func TestIntegrationConfig(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
t.Run("save and load round-trip", func(t *testing.T) {
models := []string{"llama3.2", "mistral", "qwen2.5"}
if err := saveIntegration("claude", models); err != nil {
t.Fatal(err)
}
config, err := loadIntegration("claude")
if err != nil {
t.Fatal(err)
}
if len(config.Models) != len(models) {
t.Errorf("expected %d models, got %d", len(models), len(config.Models))
}
for i, m := range models {
if config.Models[i] != m {
t.Errorf("model %d: expected %s, got %s", i, m, config.Models[i])
}
}
})
t.Run("defaultModel returns first model", func(t *testing.T) {
saveIntegration("codex", []string{"model-a", "model-b"})
config, _ := loadIntegration("codex")
defaultModel := ""
if len(config.Models) > 0 {
defaultModel = config.Models[0]
}
if defaultModel != "model-a" {
t.Errorf("expected model-a, got %s", defaultModel)
}
})
t.Run("defaultModel returns empty for no models", func(t *testing.T) {
config := &integration{Models: []string{}}
defaultModel := ""
if len(config.Models) > 0 {
defaultModel = config.Models[0]
}
if defaultModel != "" {
t.Errorf("expected empty string, got %s", defaultModel)
}
})
t.Run("app name is case-insensitive", func(t *testing.T) {
saveIntegration("Claude", []string{"model-x"})
config, err := loadIntegration("claude")
if err != nil {
t.Fatal(err)
}
defaultModel := ""
if len(config.Models) > 0 {
defaultModel = config.Models[0]
}
if defaultModel != "model-x" {
t.Errorf("expected model-x, got %s", defaultModel)
}
})
t.Run("multiple integrations in single file", func(t *testing.T) {
saveIntegration("app1", []string{"model-1"})
saveIntegration("app2", []string{"model-2"})
config1, _ := loadIntegration("app1")
config2, _ := loadIntegration("app2")
defaultModel1 := ""
if len(config1.Models) > 0 {
defaultModel1 = config1.Models[0]
}
defaultModel2 := ""
if len(config2.Models) > 0 {
defaultModel2 = config2.Models[0]
}
if defaultModel1 != "model-1" {
t.Errorf("expected model-1, got %s", defaultModel1)
}
if defaultModel2 != "model-2" {
t.Errorf("expected model-2, got %s", defaultModel2)
}
})
}
func TestListIntegrations(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
t.Run("returns empty when no integrations", func(t *testing.T) {
configs, err := listIntegrations()
if err != nil {
t.Fatal(err)
}
if len(configs) != 0 {
t.Errorf("expected 0 integrations, got %d", len(configs))
}
})
t.Run("returns all saved integrations", func(t *testing.T) {
saveIntegration("claude", []string{"model-1"})
saveIntegration("droid", []string{"model-2"})
configs, err := listIntegrations()
if err != nil {
t.Fatal(err)
}
if len(configs) != 2 {
t.Errorf("expected 2 integrations, got %d", len(configs))
}
})
}
func TestEditorPaths(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
t.Run("returns empty for claude (no Editor)", func(t *testing.T) {
r := integrations["claude"]
paths := editorPaths(r)
if len(paths) != 0 {
t.Errorf("expected no paths for claude, got %v", paths)
}
})
t.Run("returns empty for codex (no Editor)", func(t *testing.T) {
r := integrations["codex"]
paths := editorPaths(r)
if len(paths) != 0 {
t.Errorf("expected no paths for codex, got %v", paths)
}
})
t.Run("returns empty for droid when no config exists", func(t *testing.T) {
r := integrations["droid"]
paths := editorPaths(r)
if len(paths) != 0 {
t.Errorf("expected no paths, got %v", paths)
}
})
t.Run("returns path for droid when config exists", func(t *testing.T) {
settingsDir, _ := os.UserHomeDir()
settingsDir = filepath.Join(settingsDir, ".factory")
os.MkdirAll(settingsDir, 0o755)
os.WriteFile(filepath.Join(settingsDir, "settings.json"), []byte(`{}`), 0o644)
r := integrations["droid"]
paths := editorPaths(r)
if len(paths) != 1 {
t.Errorf("expected 1 path, got %d", len(paths))
}
})
t.Run("returns paths for opencode when configs exist", func(t *testing.T) {
home, _ := os.UserHomeDir()
configDir := filepath.Join(home, ".config", "opencode")
stateDir := filepath.Join(home, ".local", "state", "opencode")
os.MkdirAll(configDir, 0o755)
os.MkdirAll(stateDir, 0o755)
os.WriteFile(filepath.Join(configDir, "opencode.json"), []byte(`{}`), 0o644)
os.WriteFile(filepath.Join(stateDir, "model.json"), []byte(`{}`), 0o644)
r := integrations["opencode"]
paths := editorPaths(r)
if len(paths) != 2 {
t.Errorf("expected 2 paths, got %d: %v", len(paths), paths)
}
})
}
func TestLoadIntegration_CorruptedJSON(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Create corrupted config.json file
dir := filepath.Join(tmpDir, ".ollama", "config")
os.MkdirAll(dir, 0o755)
os.WriteFile(filepath.Join(dir, "config.json"), []byte(`{corrupted json`), 0o644)
// Corrupted file is treated as empty, so loadIntegration returns not found
_, err := loadIntegration("test")
if err == nil {
t.Error("expected error for nonexistent integration in corrupted file")
}
}
func TestSaveIntegration_NilModels(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
if err := saveIntegration("test", nil); err != nil {
t.Fatalf("saveIntegration with nil models failed: %v", err)
}
config, err := loadIntegration("test")
if err != nil {
t.Fatalf("loadIntegration failed: %v", err)
}
if config.Models == nil {
// nil is acceptable
} else if len(config.Models) != 0 {
t.Errorf("expected empty or nil models, got %v", config.Models)
}
}
func TestSaveIntegration_EmptyAppName(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
err := saveIntegration("", []string{"model"})
if err == nil {
t.Error("expected error for empty app name, got nil")
}
if err != nil && !strings.Contains(err.Error(), "app name cannot be empty") {
t.Errorf("expected 'app name cannot be empty' error, got: %v", err)
}
}
func TestLoadIntegration_NonexistentIntegration(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
_, err := loadIntegration("nonexistent")
if err == nil {
t.Error("expected error for nonexistent integration, got nil")
}
if !os.IsNotExist(err) {
t.Logf("error type is os.ErrNotExist as expected: %v", err)
}
}
func TestConfigPath(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
path, err := configPath()
if err != nil {
t.Fatal(err)
}
expected := filepath.Join(tmpDir, ".ollama", "config", "config.json")
if path != expected {
t.Errorf("expected %s, got %s", expected, path)
}
}
func TestLoad(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
t.Run("returns empty config when file does not exist", func(t *testing.T) {
cfg, err := load()
if err != nil {
t.Fatal(err)
}
if cfg == nil {
t.Fatal("expected non-nil config")
}
if cfg.Integrations == nil {
t.Error("expected non-nil Integrations map")
}
if len(cfg.Integrations) != 0 {
t.Errorf("expected empty Integrations, got %d", len(cfg.Integrations))
}
})
t.Run("loads existing config", func(t *testing.T) {
path, _ := configPath()
os.MkdirAll(filepath.Dir(path), 0o755)
os.WriteFile(path, []byte(`{"integrations":{"test":{"models":["model-a"]}}}`), 0o644)
cfg, err := load()
if err != nil {
t.Fatal(err)
}
if cfg.Integrations["test"] == nil {
t.Fatal("expected test integration")
}
if len(cfg.Integrations["test"].Models) != 1 {
t.Errorf("expected 1 model, got %d", len(cfg.Integrations["test"].Models))
}
})
t.Run("returns error for corrupted JSON", func(t *testing.T) {
path, _ := configPath()
os.MkdirAll(filepath.Dir(path), 0o755)
os.WriteFile(path, []byte(`{corrupted`), 0o644)
_, err := load()
if err == nil {
t.Error("expected error for corrupted JSON")
}
})
}
func TestSave(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
t.Run("creates config file", func(t *testing.T) {
cfg := &config{
Integrations: map[string]*integration{
"test": {Models: []string{"model-a", "model-b"}},
},
}
if err := save(cfg); err != nil {
t.Fatal(err)
}
path, _ := configPath()
if _, err := os.Stat(path); os.IsNotExist(err) {
t.Error("config file was not created")
}
})
t.Run("round-trip preserves data", func(t *testing.T) {
cfg := &config{
Integrations: map[string]*integration{
"claude": {Models: []string{"llama3.2", "mistral"}},
"codex": {Models: []string{"qwen2.5"}},
},
}
if err := save(cfg); err != nil {
t.Fatal(err)
}
loaded, err := load()
if err != nil {
t.Fatal(err)
}
if len(loaded.Integrations) != 2 {
t.Errorf("expected 2 integrations, got %d", len(loaded.Integrations))
}
if loaded.Integrations["claude"] == nil {
t.Error("missing claude integration")
}
if len(loaded.Integrations["claude"].Models) != 2 {
t.Errorf("expected 2 models for claude, got %d", len(loaded.Integrations["claude"].Models))
}
})
}

184
cmd/config/droid.go Normal file
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package config
import (
"encoding/json"
"fmt"
"os"
"os/exec"
"path/filepath"
"slices"
)
// Droid implements Runner and Editor for Droid integration
type Droid struct{}
// droidSettings represents the Droid settings.json file (only fields we use)
type droidSettings struct {
CustomModels []modelEntry `json:"customModels"`
SessionDefaultSettings sessionSettings `json:"sessionDefaultSettings"`
}
type sessionSettings struct {
Model string `json:"model"`
ReasoningEffort string `json:"reasoningEffort"`
}
type modelEntry struct {
Model string `json:"model"`
DisplayName string `json:"displayName"`
BaseURL string `json:"baseUrl"`
APIKey string `json:"apiKey"`
Provider string `json:"provider"`
MaxOutputTokens int `json:"maxOutputTokens"`
SupportsImages bool `json:"supportsImages"`
ID string `json:"id"`
Index int `json:"index"`
}
func (d *Droid) String() string { return "Droid" }
func (d *Droid) Run(model string) error {
if _, err := exec.LookPath("droid"); err != nil {
return fmt.Errorf("droid is not installed, install from https://docs.factory.ai/cli/getting-started/quickstart")
}
// Call Edit() to ensure config is up-to-date before launch
models := []string{model}
if config, err := loadIntegration("droid"); err == nil && len(config.Models) > 0 {
models = config.Models
}
if err := d.Edit(models); err != nil {
return fmt.Errorf("setup failed: %w", err)
}
cmd := exec.Command("droid")
cmd.Stdin = os.Stdin
cmd.Stdout = os.Stdout
cmd.Stderr = os.Stderr
return cmd.Run()
}
func (d *Droid) Paths() []string {
home, err := os.UserHomeDir()
if err != nil {
return nil
}
p := filepath.Join(home, ".factory", "settings.json")
if _, err := os.Stat(p); err == nil {
return []string{p}
}
return nil
}
func (d *Droid) Edit(models []string) error {
if len(models) == 0 {
return nil
}
home, err := os.UserHomeDir()
if err != nil {
return err
}
settingsPath := filepath.Join(home, ".factory", "settings.json")
if err := os.MkdirAll(filepath.Dir(settingsPath), 0o755); err != nil {
return err
}
// Read file once, unmarshal twice:
// map preserves unknown fields for writing back (including extra fields in model entries)
settingsMap := make(map[string]any)
var settings droidSettings
if data, err := os.ReadFile(settingsPath); err == nil {
if err := json.Unmarshal(data, &settingsMap); err != nil {
return fmt.Errorf("failed to parse settings file: %w, at: %s", err, settingsPath)
}
json.Unmarshal(data, &settings) // ignore error, zero values are fine
}
// Keep only non-Ollama models from the raw map (preserves extra fields)
// Rebuild Ollama models
var nonOllamaModels []any
if rawModels, ok := settingsMap["customModels"].([]any); ok {
for _, raw := range rawModels {
if m, ok := raw.(map[string]any); ok {
if m["apiKey"] != "ollama" {
nonOllamaModels = append(nonOllamaModels, raw)
}
}
}
}
// Build new Ollama model entries with sequential indices (0, 1, 2, ...)
var newModels []any
var defaultModelID string
for i, model := range models {
modelID := fmt.Sprintf("custom:%s-%d", model, i)
newModels = append(newModels, modelEntry{
Model: model,
DisplayName: model,
BaseURL: "http://localhost:11434/v1",
APIKey: "ollama",
Provider: "generic-chat-completion-api",
MaxOutputTokens: 64000,
SupportsImages: false,
ID: modelID,
Index: i,
})
if i == 0 {
defaultModelID = modelID
}
}
settingsMap["customModels"] = append(newModels, nonOllamaModels...)
// Update session default settings (preserve unknown fields in the nested object)
sessionSettings, ok := settingsMap["sessionDefaultSettings"].(map[string]any)
if !ok {
sessionSettings = make(map[string]any)
}
sessionSettings["model"] = defaultModelID
if !isValidReasoningEffort(settings.SessionDefaultSettings.ReasoningEffort) {
sessionSettings["reasoningEffort"] = "none"
}
settingsMap["sessionDefaultSettings"] = sessionSettings
data, err := json.MarshalIndent(settingsMap, "", " ")
if err != nil {
return err
}
return writeWithBackup(settingsPath, data)
}
func (d *Droid) Models() []string {
home, err := os.UserHomeDir()
if err != nil {
return nil
}
data, err := os.ReadFile(filepath.Join(home, ".factory", "settings.json"))
if err != nil {
return nil
}
var settings droidSettings
if err := json.Unmarshal(data, &settings); err != nil {
return nil
}
var result []string
for _, m := range settings.CustomModels {
if m.APIKey == "ollama" {
result = append(result, m.Model)
}
}
return result
}
var validReasoningEfforts = []string{"high", "medium", "low", "none"}
func isValidReasoningEffort(effort string) bool {
return slices.Contains(validReasoningEfforts, effort)
}

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cmd/config/droid_test.go Normal file
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99
cmd/config/files.go Normal file
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package config
import (
"bytes"
"encoding/json"
"fmt"
"os"
"path/filepath"
"time"
)
func readJSONFile(path string) (map[string]any, error) {
data, err := os.ReadFile(path)
if err != nil {
return nil, err
}
var result map[string]any
if err := json.Unmarshal(data, &result); err != nil {
return nil, err
}
return result, nil
}
func copyFile(src, dst string) error {
info, err := os.Stat(src)
if err != nil {
return err
}
data, err := os.ReadFile(src)
if err != nil {
return err
}
return os.WriteFile(dst, data, info.Mode().Perm())
}
func backupDir() string {
return filepath.Join(os.TempDir(), "ollama-backups")
}
func backupToTmp(srcPath string) (string, error) {
dir := backupDir()
if err := os.MkdirAll(dir, 0o755); err != nil {
return "", err
}
backupPath := filepath.Join(dir, fmt.Sprintf("%s.%d", filepath.Base(srcPath), time.Now().Unix()))
if err := copyFile(srcPath, backupPath); err != nil {
return "", err
}
return backupPath, nil
}
// writeWithBackup writes data to path via temp file + rename, backing up any existing file first
func writeWithBackup(path string, data []byte) error {
var backupPath string
// backup must be created before any writes to the target file
if existingContent, err := os.ReadFile(path); err == nil {
if !bytes.Equal(existingContent, data) {
backupPath, err = backupToTmp(path)
if err != nil {
return fmt.Errorf("backup failed: %w", err)
}
}
} else if !os.IsNotExist(err) {
return fmt.Errorf("read existing file: %w", err)
}
dir := filepath.Dir(path)
tmp, err := os.CreateTemp(dir, ".tmp-*")
if err != nil {
return fmt.Errorf("create temp failed: %w", err)
}
tmpPath := tmp.Name()
if _, err := tmp.Write(data); err != nil {
_ = tmp.Close()
_ = os.Remove(tmpPath)
return fmt.Errorf("write failed: %w", err)
}
if err := tmp.Sync(); err != nil {
_ = tmp.Close()
_ = os.Remove(tmpPath)
return fmt.Errorf("sync failed: %w", err)
}
if err := tmp.Close(); err != nil {
_ = os.Remove(tmpPath)
return fmt.Errorf("close failed: %w", err)
}
if err := os.Rename(tmpPath, path); err != nil {
_ = os.Remove(tmpPath)
if backupPath != "" {
_ = copyFile(backupPath, path)
}
return fmt.Errorf("rename failed: %w", err)
}
return nil
}

502
cmd/config/files_test.go Normal file
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package config
import (
"encoding/json"
"fmt"
"os"
"path/filepath"
"runtime"
"testing"
)
func mustMarshal(t *testing.T, v any) []byte {
t.Helper()
data, err := json.MarshalIndent(v, "", " ")
if err != nil {
t.Fatal(err)
}
return data
}
func TestWriteWithBackup(t *testing.T) {
tmpDir := t.TempDir()
t.Run("creates file", func(t *testing.T) {
path := filepath.Join(tmpDir, "new.json")
data := mustMarshal(t, map[string]string{"key": "value"})
if err := writeWithBackup(path, data); err != nil {
t.Fatal(err)
}
content, err := os.ReadFile(path)
if err != nil {
t.Fatal(err)
}
var result map[string]string
if err := json.Unmarshal(content, &result); err != nil {
t.Fatal(err)
}
if result["key"] != "value" {
t.Errorf("expected value, got %s", result["key"])
}
})
t.Run("creates backup in /tmp/ollama-backups", func(t *testing.T) {
path := filepath.Join(tmpDir, "backup.json")
os.WriteFile(path, []byte(`{"original": true}`), 0o644)
data := mustMarshal(t, map[string]bool{"updated": true})
if err := writeWithBackup(path, data); err != nil {
t.Fatal(err)
}
entries, err := os.ReadDir(backupDir())
if err != nil {
t.Fatal("backup directory not created")
}
var foundBackup bool
for _, entry := range entries {
if filepath.Ext(entry.Name()) != ".json" {
name := entry.Name()
if len(name) > len("backup.json.") && name[:len("backup.json.")] == "backup.json." {
backupPath := filepath.Join(backupDir(), name)
backup, err := os.ReadFile(backupPath)
if err == nil {
var backupData map[string]bool
json.Unmarshal(backup, &backupData)
if backupData["original"] {
foundBackup = true
os.Remove(backupPath)
break
}
}
}
}
}
if !foundBackup {
t.Error("backup file not created in /tmp/ollama-backups")
}
current, _ := os.ReadFile(path)
var currentData map[string]bool
json.Unmarshal(current, &currentData)
if !currentData["updated"] {
t.Error("file doesn't contain updated data")
}
})
t.Run("no backup for new file", func(t *testing.T) {
path := filepath.Join(tmpDir, "nobak.json")
data := mustMarshal(t, map[string]string{"new": "file"})
if err := writeWithBackup(path, data); err != nil {
t.Fatal(err)
}
entries, _ := os.ReadDir(backupDir())
for _, entry := range entries {
if len(entry.Name()) > len("nobak.json.") && entry.Name()[:len("nobak.json.")] == "nobak.json." {
t.Error("backup should not exist for new file")
}
}
})
t.Run("no backup when content unchanged", func(t *testing.T) {
path := filepath.Join(tmpDir, "unchanged.json")
data := mustMarshal(t, map[string]string{"key": "value"})
if err := writeWithBackup(path, data); err != nil {
t.Fatal(err)
}
entries1, _ := os.ReadDir(backupDir())
countBefore := 0
for _, e := range entries1 {
if len(e.Name()) > len("unchanged.json.") && e.Name()[:len("unchanged.json.")] == "unchanged.json." {
countBefore++
}
}
if err := writeWithBackup(path, data); err != nil {
t.Fatal(err)
}
entries2, _ := os.ReadDir(backupDir())
countAfter := 0
for _, e := range entries2 {
if len(e.Name()) > len("unchanged.json.") && e.Name()[:len("unchanged.json.")] == "unchanged.json." {
countAfter++
}
}
if countAfter != countBefore {
t.Errorf("backup was created when content unchanged (before=%d, after=%d)", countBefore, countAfter)
}
})
t.Run("backup filename contains unix timestamp", func(t *testing.T) {
path := filepath.Join(tmpDir, "timestamped.json")
os.WriteFile(path, []byte(`{"v": 1}`), 0o644)
data := mustMarshal(t, map[string]int{"v": 2})
if err := writeWithBackup(path, data); err != nil {
t.Fatal(err)
}
entries, _ := os.ReadDir(backupDir())
var found bool
for _, entry := range entries {
name := entry.Name()
if len(name) > len("timestamped.json.") && name[:len("timestamped.json.")] == "timestamped.json." {
timestamp := name[len("timestamped.json."):]
for _, c := range timestamp {
if c < '0' || c > '9' {
t.Errorf("backup filename timestamp contains non-numeric character: %s", name)
}
}
found = true
os.Remove(filepath.Join(backupDir(), name))
break
}
}
if !found {
t.Error("backup file with timestamp not found")
}
})
}
// Edge case tests for files.go
// TestWriteWithBackup_FailsIfBackupFails documents critical behavior: if backup fails, we must not proceed.
// User could lose their config with no way to recover.
func TestWriteWithBackup_FailsIfBackupFails(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("permission tests unreliable on Windows")
}
tmpDir := t.TempDir()
path := filepath.Join(tmpDir, "config.json")
// Create original file
originalContent := []byte(`{"original": true}`)
os.WriteFile(path, originalContent, 0o644)
// Make backup directory read-only to force backup failure
backupDir := backupDir()
os.MkdirAll(backupDir, 0o755)
os.Chmod(backupDir, 0o444) // Read-only
defer os.Chmod(backupDir, 0o755)
newContent := []byte(`{"updated": true}`)
err := writeWithBackup(path, newContent)
// Should fail because backup couldn't be created
if err == nil {
t.Error("expected error when backup fails, got nil")
}
// Original file should be preserved
current, _ := os.ReadFile(path)
if string(current) != string(originalContent) {
t.Errorf("original file was modified despite backup failure: got %s", string(current))
}
}
// TestWriteWithBackup_PermissionDenied verifies clear error when target file has wrong permissions.
// Common issue when config owned by root or wrong perms.
func TestWriteWithBackup_PermissionDenied(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("permission tests unreliable on Windows")
}
tmpDir := t.TempDir()
// Create a read-only directory
readOnlyDir := filepath.Join(tmpDir, "readonly")
os.MkdirAll(readOnlyDir, 0o755)
os.Chmod(readOnlyDir, 0o444)
defer os.Chmod(readOnlyDir, 0o755)
path := filepath.Join(readOnlyDir, "config.json")
err := writeWithBackup(path, []byte(`{"test": true}`))
if err == nil {
t.Error("expected permission error, got nil")
}
}
// TestWriteWithBackup_DirectoryDoesNotExist verifies behavior when target directory doesn't exist.
// writeWithBackup doesn't create directories - caller is responsible.
func TestWriteWithBackup_DirectoryDoesNotExist(t *testing.T) {
tmpDir := t.TempDir()
path := filepath.Join(tmpDir, "nonexistent", "subdir", "config.json")
err := writeWithBackup(path, []byte(`{"test": true}`))
// Should fail because directory doesn't exist
if err == nil {
t.Error("expected error for nonexistent directory, got nil")
}
}
// TestWriteWithBackup_SymlinkTarget documents behavior when target is a symlink.
// Documents what happens if user symlinks their config file.
func TestWriteWithBackup_SymlinkTarget(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("symlink tests may require admin on Windows")
}
tmpDir := t.TempDir()
realFile := filepath.Join(tmpDir, "real.json")
symlink := filepath.Join(tmpDir, "link.json")
// Create real file and symlink
os.WriteFile(realFile, []byte(`{"v": 1}`), 0o644)
os.Symlink(realFile, symlink)
// Write through symlink
err := writeWithBackup(symlink, []byte(`{"v": 2}`))
if err != nil {
t.Fatalf("writeWithBackup through symlink failed: %v", err)
}
// The real file should be updated (symlink followed for temp file creation)
content, _ := os.ReadFile(symlink)
if string(content) != `{"v": 2}` {
t.Errorf("symlink target not updated correctly: got %s", string(content))
}
}
// TestBackupToTmp_SpecialCharsInFilename verifies backup works with special characters.
// User may have config files with unusual names.
func TestBackupToTmp_SpecialCharsInFilename(t *testing.T) {
tmpDir := t.TempDir()
// File with spaces and special chars
path := filepath.Join(tmpDir, "my config (backup).json")
os.WriteFile(path, []byte(`{"test": true}`), 0o644)
backupPath, err := backupToTmp(path)
if err != nil {
t.Fatalf("backupToTmp with special chars failed: %v", err)
}
// Verify backup exists and has correct content
content, err := os.ReadFile(backupPath)
if err != nil {
t.Fatalf("could not read backup: %v", err)
}
if string(content) != `{"test": true}` {
t.Errorf("backup content mismatch: got %s", string(content))
}
os.Remove(backupPath)
}
// TestCopyFile_PreservesPermissions verifies that copyFile preserves file permissions.
func TestCopyFile_PreservesPermissions(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("permission preservation tests unreliable on Windows")
}
tmpDir := t.TempDir()
src := filepath.Join(tmpDir, "src.json")
dst := filepath.Join(tmpDir, "dst.json")
// Create source with specific permissions
os.WriteFile(src, []byte(`{"test": true}`), 0o600)
err := copyFile(src, dst)
if err != nil {
t.Fatalf("copyFile failed: %v", err)
}
srcInfo, _ := os.Stat(src)
dstInfo, _ := os.Stat(dst)
if srcInfo.Mode().Perm() != dstInfo.Mode().Perm() {
t.Errorf("permissions not preserved: src=%v, dst=%v", srcInfo.Mode().Perm(), dstInfo.Mode().Perm())
}
}
// TestCopyFile_SourceNotFound verifies clear error when source doesn't exist.
func TestCopyFile_SourceNotFound(t *testing.T) {
tmpDir := t.TempDir()
src := filepath.Join(tmpDir, "nonexistent.json")
dst := filepath.Join(tmpDir, "dst.json")
err := copyFile(src, dst)
if err == nil {
t.Error("expected error for nonexistent source, got nil")
}
}
// TestWriteWithBackup_TargetIsDirectory verifies error when path points to a directory.
func TestWriteWithBackup_TargetIsDirectory(t *testing.T) {
tmpDir := t.TempDir()
dirPath := filepath.Join(tmpDir, "actualdir")
os.MkdirAll(dirPath, 0o755)
err := writeWithBackup(dirPath, []byte(`{"test": true}`))
if err == nil {
t.Error("expected error when target is a directory, got nil")
}
}
// TestWriteWithBackup_EmptyData verifies writing zero bytes works correctly.
func TestWriteWithBackup_EmptyData(t *testing.T) {
tmpDir := t.TempDir()
path := filepath.Join(tmpDir, "empty.json")
err := writeWithBackup(path, []byte{})
if err != nil {
t.Fatalf("writeWithBackup with empty data failed: %v", err)
}
content, err := os.ReadFile(path)
if err != nil {
t.Fatalf("could not read file: %v", err)
}
if len(content) != 0 {
t.Errorf("expected empty file, got %d bytes", len(content))
}
}
// TestWriteWithBackup_FileUnreadableButDirWritable verifies behavior when existing file
// cannot be read (for backup comparison) but directory is writable.
func TestWriteWithBackup_FileUnreadableButDirWritable(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("permission tests unreliable on Windows")
}
tmpDir := t.TempDir()
path := filepath.Join(tmpDir, "unreadable.json")
// Create file and make it unreadable
os.WriteFile(path, []byte(`{"original": true}`), 0o644)
os.Chmod(path, 0o000)
defer os.Chmod(path, 0o644)
// Should fail because we can't read the file to compare/backup
err := writeWithBackup(path, []byte(`{"updated": true}`))
if err == nil {
t.Error("expected error when file is unreadable, got nil")
}
}
// TestWriteWithBackup_RapidSuccessiveWrites verifies backup works with multiple writes
// within the same second (timestamp collision scenario).
func TestWriteWithBackup_RapidSuccessiveWrites(t *testing.T) {
tmpDir := t.TempDir()
path := filepath.Join(tmpDir, "rapid.json")
// Create initial file
os.WriteFile(path, []byte(`{"v": 0}`), 0o644)
// Rapid successive writes
for i := 1; i <= 3; i++ {
data := []byte(fmt.Sprintf(`{"v": %d}`, i))
if err := writeWithBackup(path, data); err != nil {
t.Fatalf("write %d failed: %v", i, err)
}
}
// Verify final content
content, _ := os.ReadFile(path)
if string(content) != `{"v": 3}` {
t.Errorf("expected final content {\"v\": 3}, got %s", string(content))
}
// Verify at least one backup exists
entries, _ := os.ReadDir(backupDir())
var backupCount int
for _, e := range entries {
if len(e.Name()) > len("rapid.json.") && e.Name()[:len("rapid.json.")] == "rapid.json." {
backupCount++
}
}
if backupCount == 0 {
t.Error("expected at least one backup file from rapid writes")
}
}
// TestWriteWithBackup_BackupDirIsFile verifies error when backup directory path is a file.
func TestWriteWithBackup_BackupDirIsFile(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("test modifies system temp directory")
}
// Create a file at the backup directory path
backupPath := backupDir()
// Clean up any existing directory first
os.RemoveAll(backupPath)
// Create a file instead of directory
os.WriteFile(backupPath, []byte("not a directory"), 0o644)
defer func() {
os.Remove(backupPath)
os.MkdirAll(backupPath, 0o755)
}()
tmpDir := t.TempDir()
path := filepath.Join(tmpDir, "test.json")
os.WriteFile(path, []byte(`{"original": true}`), 0o644)
err := writeWithBackup(path, []byte(`{"updated": true}`))
if err == nil {
t.Error("expected error when backup dir is a file, got nil")
}
}
// TestWriteWithBackup_NoOrphanTempFiles verifies temp files are cleaned up on failure.
func TestWriteWithBackup_NoOrphanTempFiles(t *testing.T) {
if runtime.GOOS == "windows" {
t.Skip("permission tests unreliable on Windows")
}
tmpDir := t.TempDir()
// Count existing temp files
countTempFiles := func() int {
entries, _ := os.ReadDir(tmpDir)
count := 0
for _, e := range entries {
if len(e.Name()) > 4 && e.Name()[:4] == ".tmp" {
count++
}
}
return count
}
before := countTempFiles()
// Create a file, then make directory read-only to cause rename failure
path := filepath.Join(tmpDir, "orphan.json")
os.WriteFile(path, []byte(`{"v": 1}`), 0o644)
// Make a subdirectory and try to write there after making parent read-only
subDir := filepath.Join(tmpDir, "subdir")
os.MkdirAll(subDir, 0o755)
subPath := filepath.Join(subDir, "config.json")
os.WriteFile(subPath, []byte(`{"v": 1}`), 0o644)
// Make subdir read-only after creating temp file would succeed but rename would fail
// This is tricky to test - the temp file is created in the same dir, so if we can't
// rename, we also couldn't create. Let's just verify normal failure cleanup works.
// Force a failure by making the target a directory
badPath := filepath.Join(tmpDir, "isdir")
os.MkdirAll(badPath, 0o755)
_ = writeWithBackup(badPath, []byte(`{"test": true}`))
after := countTempFiles()
if after > before {
t.Errorf("orphan temp files left behind: before=%d, after=%d", before, after)
}
}

353
cmd/config/integrations.go Normal file
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package config
import (
"context"
"errors"
"fmt"
"maps"
"os"
"os/exec"
"runtime"
"slices"
"strings"
"time"
"github.com/ollama/ollama/api"
"github.com/spf13/cobra"
)
// Runners execute the launching of a model with the integration - claude, codex
// Editors can edit config files (supports multi-model selection) - opencode, droid
// They are composable interfaces where in some cases an editor is also a runner - opencode, droid
// Runner can run an integration with a model.
type Runner interface {
Run(model string) error
// String returns the human-readable name of the integration
String() string
}
// Editor can edit config files (supports multi-model selection)
type Editor interface {
// Paths returns the paths to the config files for the integration
Paths() []string
// Edit updates the config files for the integration with the given models
Edit(models []string) error
// Models returns the models currently configured for the integration
// TODO(parthsareen): add error return to Models()
Models() []string
}
// integrations is the registry of available integrations.
var integrations = map[string]Runner{
"claude": &Claude{},
"codex": &Codex{},
"droid": &Droid{},
"opencode": &OpenCode{},
}
func selectIntegration() (string, error) {
if len(integrations) == 0 {
return "", fmt.Errorf("no integrations available")
}
names := slices.Sorted(maps.Keys(integrations))
var items []selectItem
for _, name := range names {
r := integrations[name]
description := r.String()
if conn, err := loadIntegration(name); err == nil && len(conn.Models) > 0 {
description = fmt.Sprintf("%s (%s)", r.String(), conn.Models[0])
}
items = append(items, selectItem{Name: name, Description: description})
}
return selectPrompt("Select integration:", items)
}
// selectModels lets the user select models for an integration
func selectModels(ctx context.Context, name, current string) ([]string, error) {
r, ok := integrations[name]
if !ok {
return nil, fmt.Errorf("unknown integration: %s", name)
}
client, err := api.ClientFromEnvironment()
if err != nil {
return nil, err
}
models, err := client.List(ctx)
if err != nil {
return nil, err
}
if len(models.Models) == 0 {
return nil, fmt.Errorf("no models available, run 'ollama pull <model>' first")
}
var items []selectItem
cloudModels := make(map[string]bool)
for _, m := range models.Models {
if m.RemoteModel != "" {
cloudModels[m.Name] = true
}
items = append(items, selectItem{Name: m.Name})
}
if len(items) == 0 {
return nil, fmt.Errorf("no local models available, run 'ollama pull <model>' first")
}
// Get previously configured models (saved config takes precedence)
var preChecked []string
if saved, err := loadIntegration(name); err == nil {
preChecked = saved.Models
} else if editor, ok := r.(Editor); ok {
preChecked = editor.Models()
}
checked := make(map[string]bool, len(preChecked))
for _, n := range preChecked {
checked[n] = true
}
// Resolve current to full name (e.g., "llama3.2" -> "llama3.2:latest")
for _, item := range items {
if item.Name == current || strings.HasPrefix(item.Name, current+":") {
current = item.Name
break
}
}
// If current model is configured, move to front of preChecked
if checked[current] {
preChecked = append([]string{current}, slices.DeleteFunc(preChecked, func(m string) bool { return m == current })...)
}
// Sort: checked first, then alphabetical
slices.SortFunc(items, func(a, b selectItem) int {
ac, bc := checked[a.Name], checked[b.Name]
if ac != bc {
if ac {
return -1
}
return 1
}
return strings.Compare(strings.ToLower(a.Name), strings.ToLower(b.Name))
})
var selected []string
// only editors support multi-model selection
if _, ok := r.(Editor); ok {
selected, err = multiSelectPrompt(fmt.Sprintf("Select models for %s:", r), items, preChecked)
if err != nil {
return nil, err
}
} else {
model, err := selectPrompt(fmt.Sprintf("Select model for %s:", r), items)
if err != nil {
return nil, err
}
selected = []string{model}
}
// if any model in selected is a cloud model, ensure signed in
var selectedCloudModels []string
for _, m := range selected {
if cloudModels[m] {
selectedCloudModels = append(selectedCloudModels, m)
}
}
if len(selectedCloudModels) > 0 {
// ensure user is signed in
user, err := client.Whoami(ctx)
if err == nil && user != nil && user.Name != "" {
return selected, nil
}
var aErr api.AuthorizationError
if !errors.As(err, &aErr) || aErr.SigninURL == "" {
return nil, err
}
modelList := strings.Join(selectedCloudModels, ", ")
yes, err := confirmPrompt(fmt.Sprintf("sign in to use %s?", modelList))
if err != nil || !yes {
return nil, fmt.Errorf("%s requires sign in", modelList)
}
fmt.Fprintf(os.Stderr, "\nTo sign in, navigate to:\n %s\n\n", aErr.SigninURL)
// TODO(parthsareen): extract into auth package for cmd
// Auto-open browser (best effort, fail silently)
switch runtime.GOOS {
case "darwin":
_ = exec.Command("open", aErr.SigninURL).Start()
case "linux":
_ = exec.Command("xdg-open", aErr.SigninURL).Start()
case "windows":
_ = exec.Command("rundll32", "url.dll,FileProtocolHandler", aErr.SigninURL).Start()
}
spinnerFrames := []string{"|", "/", "-", "\\"}
frame := 0
fmt.Fprintf(os.Stderr, "\033[90mwaiting for sign in to complete... %s\033[0m", spinnerFrames[0])
ticker := time.NewTicker(200 * time.Millisecond)
defer ticker.Stop()
for {
select {
case <-ctx.Done():
fmt.Fprintf(os.Stderr, "\r\033[K")
return nil, ctx.Err()
case <-ticker.C:
frame++
fmt.Fprintf(os.Stderr, "\r\033[90mwaiting for sign in to complete... %s\033[0m", spinnerFrames[frame%len(spinnerFrames)])
// poll every 10th frame (~2 seconds)
if frame%10 == 0 {
u, err := client.Whoami(ctx)
if err == nil && u != nil && u.Name != "" {
fmt.Fprintf(os.Stderr, "\r\033[K\033[A\r\033[K\033[1msigned in:\033[0m %s\n", u.Name)
return selected, nil
}
}
}
}
}
return selected, nil
}
func runIntegration(name, modelName string) error {
r, ok := integrations[name]
if !ok {
return fmt.Errorf("unknown integration: %s", name)
}
fmt.Fprintf(os.Stderr, "\nLaunching %s with %s...\n", r, modelName)
return r.Run(modelName)
}
// LaunchCmd returns the cobra command for launching integrations.
func LaunchCmd(checkServerHeartbeat func(cmd *cobra.Command, args []string) error) *cobra.Command {
var modelFlag string
var configFlag bool
cmd := &cobra.Command{
Use: "launch [INTEGRATION]",
Short: "Launch an integration with Ollama",
Long: `Launch an integration configured with Ollama models.
Supported integrations:
claude Claude Code
codex Codex
droid Droid
opencode OpenCode
Examples:
ollama launch
ollama launch claude
ollama launch claude --model <model>
ollama launch droid --config (does not auto-launch)`,
Args: cobra.MaximumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: func(cmd *cobra.Command, args []string) error {
var name string
if len(args) > 0 {
name = args[0]
} else {
var err error
name, err = selectIntegration()
if errors.Is(err, errCancelled) {
return nil
}
if err != nil {
return err
}
}
r, ok := integrations[strings.ToLower(name)]
if !ok {
return fmt.Errorf("unknown integration: %s", name)
}
// If launching without --model, use saved config if available
if !configFlag && modelFlag == "" {
if config, err := loadIntegration(name); err == nil && len(config.Models) > 0 {
return runIntegration(name, config.Models[0])
}
}
var models []string
if modelFlag != "" {
// When --model is specified, merge with existing models (new model becomes default)
models = []string{modelFlag}
if existing, err := loadIntegration(name); err == nil && len(existing.Models) > 0 {
for _, m := range existing.Models {
if m != modelFlag {
models = append(models, m)
}
}
}
} else {
var err error
models, err = selectModels(cmd.Context(), name, "")
if errors.Is(err, errCancelled) {
return nil
}
if err != nil {
return err
}
}
if editor, isEditor := r.(Editor); isEditor {
paths := editor.Paths()
if len(paths) > 0 {
fmt.Fprintf(os.Stderr, "This will modify your %s configuration:\n", r)
for _, p := range paths {
fmt.Fprintf(os.Stderr, " %s\n", p)
}
fmt.Fprintf(os.Stderr, "Backups will be saved to %s/\n\n", backupDir())
if ok, _ := confirmPrompt("Proceed?"); !ok {
return nil
}
}
}
if err := saveIntegration(name, models); err != nil {
return fmt.Errorf("failed to save: %w", err)
}
if editor, isEditor := r.(Editor); isEditor {
if err := editor.Edit(models); err != nil {
return fmt.Errorf("setup failed: %w", err)
}
}
if _, isEditor := r.(Editor); isEditor {
if len(models) == 1 {
fmt.Fprintf(os.Stderr, "Added %s to %s\n", models[0], r)
} else {
fmt.Fprintf(os.Stderr, "Added %d models to %s (default: %s)\n", len(models), r, models[0])
}
}
if configFlag {
if launch, _ := confirmPrompt(fmt.Sprintf("\nLaunch %s now?", r)); launch {
return runIntegration(name, models[0])
}
fmt.Fprintf(os.Stderr, "Run 'ollama launch %s' to start with %s\n", strings.ToLower(name), models[0])
return nil
}
return runIntegration(name, models[0])
},
}
cmd.Flags().StringVar(&modelFlag, "model", "", "Model to use")
cmd.Flags().BoolVar(&configFlag, "config", false, "Configure without launching")
return cmd
}

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@@ -0,0 +1,188 @@
package config
import (
"slices"
"strings"
"testing"
"github.com/spf13/cobra"
)
func TestIntegrationLookup(t *testing.T) {
tests := []struct {
name string
input string
wantFound bool
wantName string
}{
{"claude lowercase", "claude", true, "Claude Code"},
{"claude uppercase", "CLAUDE", true, "Claude Code"},
{"claude mixed case", "Claude", true, "Claude Code"},
{"codex", "codex", true, "Codex"},
{"droid", "droid", true, "Droid"},
{"opencode", "opencode", true, "OpenCode"},
{"unknown integration", "unknown", false, ""},
{"empty string", "", false, ""},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
r, found := integrations[strings.ToLower(tt.input)]
if found != tt.wantFound {
t.Errorf("integrations[%q] found = %v, want %v", tt.input, found, tt.wantFound)
}
if found && r.String() != tt.wantName {
t.Errorf("integrations[%q].String() = %q, want %q", tt.input, r.String(), tt.wantName)
}
})
}
}
func TestIntegrationRegistry(t *testing.T) {
expectedIntegrations := []string{"claude", "codex", "droid", "opencode"}
for _, name := range expectedIntegrations {
t.Run(name, func(t *testing.T) {
r, ok := integrations[name]
if !ok {
t.Fatalf("integration %q not found in registry", name)
}
if r.String() == "" {
t.Error("integration.String() should not be empty")
}
})
}
}
func TestHasLocalModel(t *testing.T) {
tests := []struct {
name string
models []string
want bool
}{
{"empty list", []string{}, false},
{"single local model", []string{"llama3.2"}, true},
{"single cloud model", []string{"cloud-model"}, false},
{"mixed models", []string{"cloud-model", "llama3.2"}, true},
{"multiple local models", []string{"llama3.2", "qwen2.5"}, true},
{"multiple cloud models", []string{"cloud-a", "cloud-b"}, false},
{"local model first", []string{"llama3.2", "cloud-model"}, true},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := slices.ContainsFunc(tt.models, func(m string) bool {
return !strings.Contains(m, "cloud")
})
if got != tt.want {
t.Errorf("hasLocalModel(%v) = %v, want %v", tt.models, got, tt.want)
}
})
}
}
func TestLaunchCmd(t *testing.T) {
// Mock checkServerHeartbeat that always succeeds
mockCheck := func(cmd *cobra.Command, args []string) error {
return nil
}
cmd := LaunchCmd(mockCheck)
t.Run("command structure", func(t *testing.T) {
if cmd.Use != "launch [INTEGRATION]" {
t.Errorf("Use = %q, want %q", cmd.Use, "launch [INTEGRATION]")
}
if cmd.Short == "" {
t.Error("Short description should not be empty")
}
if cmd.Long == "" {
t.Error("Long description should not be empty")
}
})
t.Run("flags exist", func(t *testing.T) {
modelFlag := cmd.Flags().Lookup("model")
if modelFlag == nil {
t.Error("--model flag should exist")
}
configFlag := cmd.Flags().Lookup("config")
if configFlag == nil {
t.Error("--config flag should exist")
}
})
t.Run("PreRunE is set", func(t *testing.T) {
if cmd.PreRunE == nil {
t.Error("PreRunE should be set to checkServerHeartbeat")
}
})
}
func TestRunIntegration_UnknownIntegration(t *testing.T) {
err := runIntegration("unknown-integration", "model")
if err == nil {
t.Error("expected error for unknown integration, got nil")
}
if !strings.Contains(err.Error(), "unknown integration") {
t.Errorf("error should mention 'unknown integration', got: %v", err)
}
}
func TestHasLocalModel_DocumentsHeuristic(t *testing.T) {
tests := []struct {
name string
models []string
want bool
reason string
}{
{"empty list", []string{}, false, "empty list has no local models"},
{"contains-cloud-substring", []string{"deepseek-r1:cloud"}, false, "model with 'cloud' substring is considered cloud"},
{"cloud-in-name", []string{"my-cloud-model"}, false, "'cloud' anywhere in name = cloud model"},
{"cloudless", []string{"cloudless-model"}, false, "'cloudless' still contains 'cloud'"},
{"local-model", []string{"llama3.2"}, true, "no 'cloud' = local"},
{"mixed", []string{"cloud-model", "llama3.2"}, true, "one local model = hasLocalModel true"},
{"all-cloud", []string{"cloud-a", "cloud-b"}, false, "all contain 'cloud'"},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := slices.ContainsFunc(tt.models, func(m string) bool {
return !strings.Contains(m, "cloud")
})
if got != tt.want {
t.Errorf("hasLocalModel(%v) = %v, want %v (%s)", tt.models, got, tt.want, tt.reason)
}
})
}
}
func TestLaunchCmd_NilHeartbeat(t *testing.T) {
// This should not panic - cmd creation should work even with nil
cmd := LaunchCmd(nil)
if cmd == nil {
t.Fatal("LaunchCmd returned nil")
}
// PreRunE should be nil when passed nil
if cmd.PreRunE != nil {
t.Log("Note: PreRunE is set even when nil is passed (acceptable)")
}
}
func TestAllIntegrations_HaveRequiredMethods(t *testing.T) {
for name, r := range integrations {
t.Run(name, func(t *testing.T) {
// Test String() doesn't panic and returns non-empty
displayName := r.String()
if displayName == "" {
t.Error("String() should not return empty")
}
// Test Run() exists (we can't call it without actually running the command)
// Just verify the method is available
var _ func(string) error = r.Run
})
}
}

203
cmd/config/opencode.go Normal file
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@@ -0,0 +1,203 @@
package config
import (
"encoding/json"
"fmt"
"maps"
"os"
"os/exec"
"path/filepath"
"slices"
"strings"
)
// OpenCode implements Runner and Editor for OpenCode integration
type OpenCode struct{}
func (o *OpenCode) String() string { return "OpenCode" }
func (o *OpenCode) Run(model string) error {
if _, err := exec.LookPath("opencode"); err != nil {
return fmt.Errorf("opencode is not installed, install from https://opencode.ai")
}
// Call Edit() to ensure config is up-to-date before launch
models := []string{model}
if config, err := loadIntegration("opencode"); err == nil && len(config.Models) > 0 {
models = config.Models
}
if err := o.Edit(models); err != nil {
return fmt.Errorf("setup failed: %w", err)
}
cmd := exec.Command("opencode")
cmd.Stdin = os.Stdin
cmd.Stdout = os.Stdout
cmd.Stderr = os.Stderr
return cmd.Run()
}
func (o *OpenCode) Paths() []string {
home, err := os.UserHomeDir()
if err != nil {
return nil
}
var paths []string
p := filepath.Join(home, ".config", "opencode", "opencode.json")
if _, err := os.Stat(p); err == nil {
paths = append(paths, p)
}
sp := filepath.Join(home, ".local", "state", "opencode", "model.json")
if _, err := os.Stat(sp); err == nil {
paths = append(paths, sp)
}
return paths
}
func (o *OpenCode) Edit(modelList []string) error {
if len(modelList) == 0 {
return nil
}
home, err := os.UserHomeDir()
if err != nil {
return err
}
configPath := filepath.Join(home, ".config", "opencode", "opencode.json")
if err := os.MkdirAll(filepath.Dir(configPath), 0o755); err != nil {
return err
}
config := make(map[string]any)
if data, err := os.ReadFile(configPath); err == nil {
_ = json.Unmarshal(data, &config) // Ignore parse errors; treat missing/corrupt files as empty
}
config["$schema"] = "https://opencode.ai/config.json"
provider, ok := config["provider"].(map[string]any)
if !ok {
provider = make(map[string]any)
}
ollama, ok := provider["ollama"].(map[string]any)
if !ok {
ollama = map[string]any{
"npm": "@ai-sdk/openai-compatible",
"name": "Ollama (local)",
"options": map[string]any{
"baseURL": "http://localhost:11434/v1",
},
}
}
models, ok := ollama["models"].(map[string]any)
if !ok {
models = make(map[string]any)
}
selectedSet := make(map[string]bool)
for _, m := range modelList {
selectedSet[m] = true
}
for name, cfg := range models {
if cfgMap, ok := cfg.(map[string]any); ok {
if displayName, ok := cfgMap["name"].(string); ok {
if strings.HasSuffix(displayName, "[Ollama]") && !selectedSet[name] {
delete(models, name)
}
}
}
}
for _, model := range modelList {
models[model] = map[string]any{
"name": fmt.Sprintf("%s [Ollama]", model),
}
}
ollama["models"] = models
provider["ollama"] = ollama
config["provider"] = provider
configData, err := json.MarshalIndent(config, "", " ")
if err != nil {
return err
}
if err := writeWithBackup(configPath, configData); err != nil {
return err
}
statePath := filepath.Join(home, ".local", "state", "opencode", "model.json")
if err := os.MkdirAll(filepath.Dir(statePath), 0o755); err != nil {
return err
}
state := map[string]any{
"recent": []any{},
"favorite": []any{},
"variant": map[string]any{},
}
if data, err := os.ReadFile(statePath); err == nil {
_ = json.Unmarshal(data, &state) // Ignore parse errors; use defaults
}
recent, _ := state["recent"].([]any)
modelSet := make(map[string]bool)
for _, m := range modelList {
modelSet[m] = true
}
// Filter out existing Ollama models we're about to re-add
newRecent := slices.DeleteFunc(slices.Clone(recent), func(entry any) bool {
e, ok := entry.(map[string]any)
if !ok || e["providerID"] != "ollama" {
return false
}
modelID, _ := e["modelID"].(string)
return modelSet[modelID]
})
// Prepend models in reverse order so first model ends up first
for _, model := range slices.Backward(modelList) {
newRecent = slices.Insert(newRecent, 0, any(map[string]any{
"providerID": "ollama",
"modelID": model,
}))
}
const maxRecentModels = 10
newRecent = newRecent[:min(len(newRecent), maxRecentModels)]
state["recent"] = newRecent
stateData, err := json.MarshalIndent(state, "", " ")
if err != nil {
return err
}
return writeWithBackup(statePath, stateData)
}
func (o *OpenCode) Models() []string {
home, err := os.UserHomeDir()
if err != nil {
return nil
}
config, err := readJSONFile(filepath.Join(home, ".config", "opencode", "opencode.json"))
if err != nil {
return nil
}
provider, _ := config["provider"].(map[string]any)
ollama, _ := provider["ollama"].(map[string]any)
models, _ := ollama["models"].(map[string]any)
if len(models) == 0 {
return nil
}
keys := slices.Collect(maps.Keys(models))
slices.Sort(keys)
return keys
}

437
cmd/config/opencode_test.go Normal file
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@@ -0,0 +1,437 @@
package config
import (
"encoding/json"
"os"
"path/filepath"
"testing"
)
func TestOpenCodeIntegration(t *testing.T) {
o := &OpenCode{}
t.Run("String", func(t *testing.T) {
if got := o.String(); got != "OpenCode" {
t.Errorf("String() = %q, want %q", got, "OpenCode")
}
})
t.Run("implements Runner", func(t *testing.T) {
var _ Runner = o
})
t.Run("implements Editor", func(t *testing.T) {
var _ Editor = o
})
}
func TestOpenCodeEdit(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
stateDir := filepath.Join(tmpDir, ".local", "state", "opencode")
statePath := filepath.Join(stateDir, "model.json")
cleanup := func() {
os.RemoveAll(configDir)
os.RemoveAll(stateDir)
}
t.Run("fresh install", func(t *testing.T) {
cleanup()
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
assertOpenCodeModelExists(t, configPath, "llama3.2")
assertOpenCodeRecentModel(t, statePath, 0, "ollama", "llama3.2")
})
t.Run("preserve other providers", func(t *testing.T) {
cleanup()
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(`{"provider":{"anthropic":{"apiKey":"xxx"}}}`), 0o644)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
data, _ := os.ReadFile(configPath)
var cfg map[string]any
json.Unmarshal(data, &cfg)
provider := cfg["provider"].(map[string]any)
if provider["anthropic"] == nil {
t.Error("anthropic provider was removed")
}
assertOpenCodeModelExists(t, configPath, "llama3.2")
})
t.Run("preserve other models", func(t *testing.T) {
cleanup()
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(`{"provider":{"ollama":{"models":{"mistral":{"name":"Mistral"}}}}}`), 0o644)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
assertOpenCodeModelExists(t, configPath, "mistral")
assertOpenCodeModelExists(t, configPath, "llama3.2")
})
t.Run("update existing model", func(t *testing.T) {
cleanup()
o.Edit([]string{"llama3.2"})
o.Edit([]string{"llama3.2"})
assertOpenCodeModelExists(t, configPath, "llama3.2")
})
t.Run("preserve top-level keys", func(t *testing.T) {
cleanup()
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(`{"theme":"dark","keybindings":{}}`), 0o644)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
data, _ := os.ReadFile(configPath)
var cfg map[string]any
json.Unmarshal(data, &cfg)
if cfg["theme"] != "dark" {
t.Error("theme was removed")
}
if cfg["keybindings"] == nil {
t.Error("keybindings was removed")
}
})
t.Run("model state - insert at index 0", func(t *testing.T) {
cleanup()
os.MkdirAll(stateDir, 0o755)
os.WriteFile(statePath, []byte(`{"recent":[{"providerID":"anthropic","modelID":"claude"}],"favorite":[],"variant":{}}`), 0o644)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
assertOpenCodeRecentModel(t, statePath, 0, "ollama", "llama3.2")
assertOpenCodeRecentModel(t, statePath, 1, "anthropic", "claude")
})
t.Run("model state - preserve favorites and variants", func(t *testing.T) {
cleanup()
os.MkdirAll(stateDir, 0o755)
os.WriteFile(statePath, []byte(`{"recent":[],"favorite":[{"providerID":"x","modelID":"y"}],"variant":{"a":"b"}}`), 0o644)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
data, _ := os.ReadFile(statePath)
var state map[string]any
json.Unmarshal(data, &state)
if len(state["favorite"].([]any)) != 1 {
t.Error("favorite was modified")
}
if state["variant"].(map[string]any)["a"] != "b" {
t.Error("variant was modified")
}
})
t.Run("model state - deduplicate on re-add", func(t *testing.T) {
cleanup()
os.MkdirAll(stateDir, 0o755)
os.WriteFile(statePath, []byte(`{"recent":[{"providerID":"ollama","modelID":"llama3.2"},{"providerID":"anthropic","modelID":"claude"}],"favorite":[],"variant":{}}`), 0o644)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
data, _ := os.ReadFile(statePath)
var state map[string]any
json.Unmarshal(data, &state)
recent := state["recent"].([]any)
if len(recent) != 2 {
t.Errorf("expected 2 recent entries, got %d", len(recent))
}
assertOpenCodeRecentModel(t, statePath, 0, "ollama", "llama3.2")
})
t.Run("remove model", func(t *testing.T) {
cleanup()
// First add two models
o.Edit([]string{"llama3.2", "mistral"})
assertOpenCodeModelExists(t, configPath, "llama3.2")
assertOpenCodeModelExists(t, configPath, "mistral")
// Then remove one by only selecting the other
o.Edit([]string{"llama3.2"})
assertOpenCodeModelExists(t, configPath, "llama3.2")
assertOpenCodeModelNotExists(t, configPath, "mistral")
})
t.Run("remove model preserves non-ollama models", func(t *testing.T) {
cleanup()
os.MkdirAll(configDir, 0o755)
// Add a non-Ollama model manually
os.WriteFile(configPath, []byte(`{"provider":{"ollama":{"models":{"external":{"name":"External Model"}}}}}`), 0o644)
o.Edit([]string{"llama3.2"})
assertOpenCodeModelExists(t, configPath, "llama3.2")
assertOpenCodeModelExists(t, configPath, "external") // Should be preserved
})
}
func assertOpenCodeModelExists(t *testing.T, path, model string) {
t.Helper()
data, err := os.ReadFile(path)
if err != nil {
t.Fatal(err)
}
var cfg map[string]any
if err := json.Unmarshal(data, &cfg); err != nil {
t.Fatal(err)
}
provider, ok := cfg["provider"].(map[string]any)
if !ok {
t.Fatal("provider not found")
}
ollama, ok := provider["ollama"].(map[string]any)
if !ok {
t.Fatal("ollama provider not found")
}
models, ok := ollama["models"].(map[string]any)
if !ok {
t.Fatal("models not found")
}
if models[model] == nil {
t.Errorf("model %s not found", model)
}
}
func assertOpenCodeModelNotExists(t *testing.T, path, model string) {
t.Helper()
data, err := os.ReadFile(path)
if err != nil {
t.Fatal(err)
}
var cfg map[string]any
if err := json.Unmarshal(data, &cfg); err != nil {
t.Fatal(err)
}
provider, ok := cfg["provider"].(map[string]any)
if !ok {
return // No provider means no model
}
ollama, ok := provider["ollama"].(map[string]any)
if !ok {
return // No ollama means no model
}
models, ok := ollama["models"].(map[string]any)
if !ok {
return // No models means no model
}
if models[model] != nil {
t.Errorf("model %s should not exist but was found", model)
}
}
func assertOpenCodeRecentModel(t *testing.T, path string, index int, providerID, modelID string) {
t.Helper()
data, err := os.ReadFile(path)
if err != nil {
t.Fatal(err)
}
var state map[string]any
if err := json.Unmarshal(data, &state); err != nil {
t.Fatal(err)
}
recent, ok := state["recent"].([]any)
if !ok {
t.Fatal("recent not found")
}
if index >= len(recent) {
t.Fatalf("index %d out of range (len=%d)", index, len(recent))
}
entry, ok := recent[index].(map[string]any)
if !ok {
t.Fatal("entry is not a map")
}
if entry["providerID"] != providerID {
t.Errorf("expected providerID %s, got %s", providerID, entry["providerID"])
}
if entry["modelID"] != modelID {
t.Errorf("expected modelID %s, got %s", modelID, entry["modelID"])
}
}
// Edge case tests for opencode.go
func TestOpenCodeEdit_CorruptedConfigJSON(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(`{corrupted json content`), 0o644)
// Should not panic - corrupted JSON should be treated as empty
err := o.Edit([]string{"llama3.2"})
if err != nil {
t.Fatalf("Edit failed with corrupted config: %v", err)
}
// Verify valid JSON was created
data, _ := os.ReadFile(configPath)
var cfg map[string]any
if err := json.Unmarshal(data, &cfg); err != nil {
t.Errorf("resulting config is not valid JSON: %v", err)
}
}
func TestOpenCodeEdit_CorruptedStateJSON(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
stateDir := filepath.Join(tmpDir, ".local", "state", "opencode")
statePath := filepath.Join(stateDir, "model.json")
os.MkdirAll(stateDir, 0o755)
os.WriteFile(statePath, []byte(`{corrupted state`), 0o644)
err := o.Edit([]string{"llama3.2"})
if err != nil {
t.Fatalf("Edit failed with corrupted state: %v", err)
}
// Verify valid state was created
data, _ := os.ReadFile(statePath)
var state map[string]any
if err := json.Unmarshal(data, &state); err != nil {
t.Errorf("resulting state is not valid JSON: %v", err)
}
}
func TestOpenCodeEdit_WrongTypeProvider(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(`{"provider": "not a map"}`), 0o644)
err := o.Edit([]string{"llama3.2"})
if err != nil {
t.Fatalf("Edit with wrong type provider failed: %v", err)
}
// Verify provider is now correct type
data, _ := os.ReadFile(configPath)
var cfg map[string]any
json.Unmarshal(data, &cfg)
provider, ok := cfg["provider"].(map[string]any)
if !ok {
t.Fatalf("provider should be map after setup, got %T", cfg["provider"])
}
if provider["ollama"] == nil {
t.Error("ollama provider should be created")
}
}
func TestOpenCodeEdit_WrongTypeRecent(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
stateDir := filepath.Join(tmpDir, ".local", "state", "opencode")
statePath := filepath.Join(stateDir, "model.json")
os.MkdirAll(stateDir, 0o755)
os.WriteFile(statePath, []byte(`{"recent": "not an array", "favorite": [], "variant": {}}`), 0o644)
err := o.Edit([]string{"llama3.2"})
if err != nil {
t.Fatalf("Edit with wrong type recent failed: %v", err)
}
// The function should handle this gracefully
data, _ := os.ReadFile(statePath)
var state map[string]any
json.Unmarshal(data, &state)
// recent should be properly set after setup
recent, ok := state["recent"].([]any)
if !ok {
t.Logf("Note: recent type after setup is %T (documenting behavior)", state["recent"])
} else if len(recent) == 0 {
t.Logf("Note: recent is empty (documenting behavior)")
}
}
func TestOpenCodeEdit_EmptyModels(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
os.MkdirAll(configDir, 0o755)
originalContent := `{"provider":{"ollama":{"models":{"existing":{}}}}}`
os.WriteFile(configPath, []byte(originalContent), 0o644)
// Empty models should be no-op
err := o.Edit([]string{})
if err != nil {
t.Fatalf("Edit with empty models failed: %v", err)
}
// Original content should be preserved (file not modified)
data, _ := os.ReadFile(configPath)
if string(data) != originalContent {
t.Errorf("empty models should not modify file, but content changed")
}
}
func TestOpenCodeEdit_SpecialCharsInModelName(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Model name with special characters (though unusual)
specialModel := `model-with-"quotes"`
err := o.Edit([]string{specialModel})
if err != nil {
t.Fatalf("Edit with special chars failed: %v", err)
}
// Verify it was stored correctly
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
data, _ := os.ReadFile(configPath)
var cfg map[string]any
if err := json.Unmarshal(data, &cfg); err != nil {
t.Fatalf("resulting config is invalid JSON: %v", err)
}
// Model should be accessible
provider, _ := cfg["provider"].(map[string]any)
ollama, _ := provider["ollama"].(map[string]any)
models, _ := ollama["models"].(map[string]any)
if models[specialModel] == nil {
t.Errorf("model with special chars not found in config")
}
}
func TestOpenCodeModels_NoConfig(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
models := o.Models()
if len(models) > 0 {
t.Errorf("expected nil/empty for missing config, got %v", models)
}
}

499
cmd/config/selector.go Normal file
View File

@@ -0,0 +1,499 @@
package config
import (
"errors"
"fmt"
"io"
"os"
"strings"
"golang.org/x/term"
)
// ANSI escape sequences for terminal formatting.
const (
ansiHideCursor = "\033[?25l"
ansiShowCursor = "\033[?25h"
ansiBold = "\033[1m"
ansiReset = "\033[0m"
ansiGray = "\033[37m"
ansiClearDown = "\033[J"
)
const maxDisplayedItems = 10
var errCancelled = errors.New("cancelled")
type selectItem struct {
Name string
Description string
}
type inputEvent int
const (
eventNone inputEvent = iota
eventEnter
eventEscape
eventUp
eventDown
eventTab
eventBackspace
eventChar
)
type selectState struct {
items []selectItem
filter string
selected int
scrollOffset int
}
func newSelectState(items []selectItem) *selectState {
return &selectState{items: items}
}
func (s *selectState) filtered() []selectItem {
return filterItems(s.items, s.filter)
}
func (s *selectState) handleInput(event inputEvent, char byte) (done bool, result string, err error) {
filtered := s.filtered()
switch event {
case eventEnter:
if len(filtered) > 0 && s.selected < len(filtered) {
return true, filtered[s.selected].Name, nil
}
case eventEscape:
return true, "", errCancelled
case eventBackspace:
if len(s.filter) > 0 {
s.filter = s.filter[:len(s.filter)-1]
s.selected = 0
s.scrollOffset = 0
}
case eventUp:
if s.selected > 0 {
s.selected--
if s.selected < s.scrollOffset {
s.scrollOffset = s.selected
}
}
case eventDown:
if s.selected < len(filtered)-1 {
s.selected++
if s.selected >= s.scrollOffset+maxDisplayedItems {
s.scrollOffset = s.selected - maxDisplayedItems + 1
}
}
case eventChar:
s.filter += string(char)
s.selected = 0
s.scrollOffset = 0
}
return false, "", nil
}
type multiSelectState struct {
items []selectItem
itemIndex map[string]int
filter string
highlighted int
scrollOffset int
checked map[int]bool
checkOrder []int
focusOnButton bool
}
func newMultiSelectState(items []selectItem, preChecked []string) *multiSelectState {
s := &multiSelectState{
items: items,
itemIndex: make(map[string]int, len(items)),
checked: make(map[int]bool),
}
for i, item := range items {
s.itemIndex[item.Name] = i
}
for _, name := range preChecked {
if idx, ok := s.itemIndex[name]; ok {
s.checked[idx] = true
s.checkOrder = append(s.checkOrder, idx)
}
}
return s
}
func (s *multiSelectState) filtered() []selectItem {
return filterItems(s.items, s.filter)
}
func (s *multiSelectState) toggleItem() {
filtered := s.filtered()
if len(filtered) == 0 || s.highlighted >= len(filtered) {
return
}
item := filtered[s.highlighted]
origIdx := s.itemIndex[item.Name]
if s.checked[origIdx] {
delete(s.checked, origIdx)
for i, idx := range s.checkOrder {
if idx == origIdx {
s.checkOrder = append(s.checkOrder[:i], s.checkOrder[i+1:]...)
break
}
}
} else {
s.checked[origIdx] = true
s.checkOrder = append(s.checkOrder, origIdx)
}
}
func (s *multiSelectState) handleInput(event inputEvent, char byte) (done bool, result []string, err error) {
filtered := s.filtered()
switch event {
case eventEnter:
if s.focusOnButton && len(s.checkOrder) > 0 {
var res []string
for _, idx := range s.checkOrder {
res = append(res, s.items[idx].Name)
}
return true, res, nil
} else if !s.focusOnButton {
s.toggleItem()
}
case eventTab:
if len(s.checkOrder) > 0 {
s.focusOnButton = !s.focusOnButton
}
case eventEscape:
return true, nil, errCancelled
case eventBackspace:
if len(s.filter) > 0 {
s.filter = s.filter[:len(s.filter)-1]
s.highlighted = 0
s.scrollOffset = 0
s.focusOnButton = false
}
case eventUp:
if s.focusOnButton {
s.focusOnButton = false
} else if s.highlighted > 0 {
s.highlighted--
if s.highlighted < s.scrollOffset {
s.scrollOffset = s.highlighted
}
}
case eventDown:
if s.focusOnButton {
s.focusOnButton = false
} else if s.highlighted < len(filtered)-1 {
s.highlighted++
if s.highlighted >= s.scrollOffset+maxDisplayedItems {
s.scrollOffset = s.highlighted - maxDisplayedItems + 1
}
}
case eventChar:
s.filter += string(char)
s.highlighted = 0
s.scrollOffset = 0
s.focusOnButton = false
}
return false, nil, nil
}
func (s *multiSelectState) selectedCount() int {
return len(s.checkOrder)
}
// Terminal I/O handling
type terminalState struct {
fd int
oldState *term.State
}
func enterRawMode() (*terminalState, error) {
fd := int(os.Stdin.Fd())
oldState, err := term.MakeRaw(fd)
if err != nil {
return nil, err
}
fmt.Fprint(os.Stderr, ansiHideCursor)
return &terminalState{fd: fd, oldState: oldState}, nil
}
func (t *terminalState) restore() {
fmt.Fprint(os.Stderr, ansiShowCursor)
term.Restore(t.fd, t.oldState)
}
func clearLines(n int) {
if n > 0 {
fmt.Fprintf(os.Stderr, "\033[%dA", n)
fmt.Fprint(os.Stderr, ansiClearDown)
}
}
func parseInput(r io.Reader) (inputEvent, byte, error) {
buf := make([]byte, 3)
n, err := r.Read(buf)
if err != nil {
return 0, 0, err
}
switch {
case n == 1 && buf[0] == 13:
return eventEnter, 0, nil
case n == 1 && (buf[0] == 3 || buf[0] == 27):
return eventEscape, 0, nil
case n == 1 && buf[0] == 9:
return eventTab, 0, nil
case n == 1 && buf[0] == 127:
return eventBackspace, 0, nil
case n == 3 && buf[0] == 27 && buf[1] == 91 && buf[2] == 65:
return eventUp, 0, nil
case n == 3 && buf[0] == 27 && buf[1] == 91 && buf[2] == 66:
return eventDown, 0, nil
case n == 1 && buf[0] >= 32 && buf[0] < 127:
return eventChar, buf[0], nil
}
return eventNone, 0, nil
}
// Rendering
func renderSelect(w io.Writer, prompt string, s *selectState) int {
filtered := s.filtered()
fmt.Fprintf(w, "%s %s\r\n", prompt, s.filter)
lineCount := 1
if len(filtered) == 0 {
fmt.Fprintf(w, " %s(no matches)%s\r\n", ansiGray, ansiReset)
lineCount++
} else {
displayCount := min(len(filtered), maxDisplayedItems)
for i := range displayCount {
idx := s.scrollOffset + i
if idx >= len(filtered) {
break
}
item := filtered[idx]
prefix := " "
if idx == s.selected {
prefix = " " + ansiBold + "> "
}
if item.Description != "" {
fmt.Fprintf(w, "%s%s%s %s- %s%s\r\n", prefix, item.Name, ansiReset, ansiGray, item.Description, ansiReset)
} else {
fmt.Fprintf(w, "%s%s%s\r\n", prefix, item.Name, ansiReset)
}
lineCount++
}
if remaining := len(filtered) - s.scrollOffset - displayCount; remaining > 0 {
fmt.Fprintf(w, " %s... and %d more%s\r\n", ansiGray, remaining, ansiReset)
lineCount++
}
}
return lineCount
}
func renderMultiSelect(w io.Writer, prompt string, s *multiSelectState) int {
filtered := s.filtered()
fmt.Fprintf(w, "%s %s\r\n", prompt, s.filter)
lineCount := 1
if len(filtered) == 0 {
fmt.Fprintf(w, " %s(no matches)%s\r\n", ansiGray, ansiReset)
lineCount++
} else {
displayCount := min(len(filtered), maxDisplayedItems)
for i := range displayCount {
idx := s.scrollOffset + i
if idx >= len(filtered) {
break
}
item := filtered[idx]
origIdx := s.itemIndex[item.Name]
checkbox := "[ ]"
if s.checked[origIdx] {
checkbox = "[x]"
}
prefix := " "
suffix := ""
if idx == s.highlighted && !s.focusOnButton {
prefix = "> "
}
if len(s.checkOrder) > 0 && s.checkOrder[0] == origIdx {
suffix = " " + ansiGray + "(default)" + ansiReset
}
if idx == s.highlighted && !s.focusOnButton {
fmt.Fprintf(w, " %s%s %s %s%s%s\r\n", ansiBold, prefix, checkbox, item.Name, ansiReset, suffix)
} else {
fmt.Fprintf(w, " %s %s %s%s\r\n", prefix, checkbox, item.Name, suffix)
}
lineCount++
}
if remaining := len(filtered) - s.scrollOffset - displayCount; remaining > 0 {
fmt.Fprintf(w, " %s... and %d more%s\r\n", ansiGray, remaining, ansiReset)
lineCount++
}
}
fmt.Fprintf(w, "\r\n")
lineCount++
count := s.selectedCount()
switch {
case count == 0:
fmt.Fprintf(w, " %sSelect at least one model.%s\r\n", ansiGray, ansiReset)
case s.focusOnButton:
fmt.Fprintf(w, " %s> [ Continue ]%s %s(%d selected)%s\r\n", ansiBold, ansiReset, ansiGray, count, ansiReset)
default:
fmt.Fprintf(w, " %s[ Continue ] (%d selected) - press Tab%s\r\n", ansiGray, count, ansiReset)
}
lineCount++
return lineCount
}
// selectPrompt prompts the user to select a single item from a list.
func selectPrompt(prompt string, items []selectItem) (string, error) {
if len(items) == 0 {
return "", fmt.Errorf("no items to select from")
}
ts, err := enterRawMode()
if err != nil {
return "", err
}
defer ts.restore()
state := newSelectState(items)
var lastLineCount int
render := func() {
clearLines(lastLineCount)
lastLineCount = renderSelect(os.Stderr, prompt, state)
}
render()
for {
event, char, err := parseInput(os.Stdin)
if err != nil {
return "", err
}
done, result, err := state.handleInput(event, char)
if done {
clearLines(lastLineCount)
if err != nil {
return "", err
}
return result, nil
}
render()
}
}
// multiSelectPrompt prompts the user to select multiple items from a list.
func multiSelectPrompt(prompt string, items []selectItem, preChecked []string) ([]string, error) {
if len(items) == 0 {
return nil, fmt.Errorf("no items to select from")
}
ts, err := enterRawMode()
if err != nil {
return nil, err
}
defer ts.restore()
state := newMultiSelectState(items, preChecked)
var lastLineCount int
render := func() {
clearLines(lastLineCount)
lastLineCount = renderMultiSelect(os.Stderr, prompt, state)
}
render()
for {
event, char, err := parseInput(os.Stdin)
if err != nil {
return nil, err
}
done, result, err := state.handleInput(event, char)
if done {
clearLines(lastLineCount)
if err != nil {
return nil, err
}
return result, nil
}
render()
}
}
func confirmPrompt(prompt string) (bool, error) {
fd := int(os.Stdin.Fd())
oldState, err := term.MakeRaw(fd)
if err != nil {
return false, err
}
defer term.Restore(fd, oldState)
fmt.Fprintf(os.Stderr, "%s (\033[1my\033[0m/n) ", prompt)
buf := make([]byte, 1)
for {
if _, err := os.Stdin.Read(buf); err != nil {
return false, err
}
switch buf[0] {
case 'Y', 'y', 13:
fmt.Fprintf(os.Stderr, "yes\r\n")
return true, nil
case 'N', 'n', 27, 3:
fmt.Fprintf(os.Stderr, "no\r\n")
return false, nil
}
}
}
func filterItems(items []selectItem, filter string) []selectItem {
if filter == "" {
return items
}
var result []selectItem
filterLower := strings.ToLower(filter)
for _, item := range items {
if strings.Contains(strings.ToLower(item.Name), filterLower) {
result = append(result, item)
}
}
return result
}

913
cmd/config/selector_test.go Normal file
View File

@@ -0,0 +1,913 @@
package config
import (
"bytes"
"strings"
"testing"
)
func TestFilterItems(t *testing.T) {
items := []selectItem{
{Name: "llama3.2:latest"},
{Name: "qwen2.5:7b"},
{Name: "deepseek-v3:cloud"},
{Name: "GPT-OSS:20b"},
}
t.Run("EmptyFilter_ReturnsAllItems", func(t *testing.T) {
result := filterItems(items, "")
if len(result) != len(items) {
t.Errorf("expected %d items, got %d", len(items), len(result))
}
})
t.Run("CaseInsensitive_UppercaseFilterMatchesLowercase", func(t *testing.T) {
result := filterItems(items, "LLAMA")
if len(result) != 1 || result[0].Name != "llama3.2:latest" {
t.Errorf("expected llama3.2:latest, got %v", result)
}
})
t.Run("CaseInsensitive_LowercaseFilterMatchesUppercase", func(t *testing.T) {
result := filterItems(items, "gpt")
if len(result) != 1 || result[0].Name != "GPT-OSS:20b" {
t.Errorf("expected GPT-OSS:20b, got %v", result)
}
})
t.Run("PartialMatch", func(t *testing.T) {
result := filterItems(items, "deep")
if len(result) != 1 || result[0].Name != "deepseek-v3:cloud" {
t.Errorf("expected deepseek-v3:cloud, got %v", result)
}
})
t.Run("NoMatch_ReturnsEmpty", func(t *testing.T) {
result := filterItems(items, "nonexistent")
if len(result) != 0 {
t.Errorf("expected 0 items, got %d", len(result))
}
})
}
func TestSelectState(t *testing.T) {
items := []selectItem{
{Name: "item1"},
{Name: "item2"},
{Name: "item3"},
}
t.Run("InitialState", func(t *testing.T) {
s := newSelectState(items)
if s.selected != 0 {
t.Errorf("expected selected=0, got %d", s.selected)
}
if s.filter != "" {
t.Errorf("expected empty filter, got %q", s.filter)
}
if s.scrollOffset != 0 {
t.Errorf("expected scrollOffset=0, got %d", s.scrollOffset)
}
})
t.Run("Enter_SelectsCurrentItem", func(t *testing.T) {
s := newSelectState(items)
done, result, err := s.handleInput(eventEnter, 0)
if !done || result != "item1" || err != nil {
t.Errorf("expected (true, item1, nil), got (%v, %v, %v)", done, result, err)
}
})
t.Run("Enter_WithFilter_SelectsFilteredItem", func(t *testing.T) {
s := newSelectState(items)
s.filter = "item3"
done, result, err := s.handleInput(eventEnter, 0)
if !done || result != "item3" || err != nil {
t.Errorf("expected (true, item3, nil), got (%v, %v, %v)", done, result, err)
}
})
t.Run("Enter_EmptyFilteredList_DoesNothing", func(t *testing.T) {
s := newSelectState(items)
s.filter = "nonexistent"
done, result, err := s.handleInput(eventEnter, 0)
if done || result != "" || err != nil {
t.Errorf("expected (false, '', nil), got (%v, %v, %v)", done, result, err)
}
})
t.Run("Escape_ReturnsCancelledError", func(t *testing.T) {
s := newSelectState(items)
done, result, err := s.handleInput(eventEscape, 0)
if !done || result != "" || err != errCancelled {
t.Errorf("expected (true, '', errCancelled), got (%v, %v, %v)", done, result, err)
}
})
t.Run("Down_MovesSelection", func(t *testing.T) {
s := newSelectState(items)
s.handleInput(eventDown, 0)
if s.selected != 1 {
t.Errorf("expected selected=1, got %d", s.selected)
}
})
t.Run("Down_AtBottom_StaysAtBottom", func(t *testing.T) {
s := newSelectState(items)
s.selected = 2
s.handleInput(eventDown, 0)
if s.selected != 2 {
t.Errorf("expected selected=2 (stayed at bottom), got %d", s.selected)
}
})
t.Run("Up_MovesSelection", func(t *testing.T) {
s := newSelectState(items)
s.selected = 2
s.handleInput(eventUp, 0)
if s.selected != 1 {
t.Errorf("expected selected=1, got %d", s.selected)
}
})
t.Run("Up_AtTop_StaysAtTop", func(t *testing.T) {
s := newSelectState(items)
s.handleInput(eventUp, 0)
if s.selected != 0 {
t.Errorf("expected selected=0 (stayed at top), got %d", s.selected)
}
})
t.Run("Char_AppendsToFilter", func(t *testing.T) {
s := newSelectState(items)
s.handleInput(eventChar, 'i')
s.handleInput(eventChar, 't')
s.handleInput(eventChar, 'e')
s.handleInput(eventChar, 'm')
s.handleInput(eventChar, '2')
if s.filter != "item2" {
t.Errorf("expected filter='item2', got %q", s.filter)
}
filtered := s.filtered()
if len(filtered) != 1 || filtered[0].Name != "item2" {
t.Errorf("expected [item2], got %v", filtered)
}
})
t.Run("Char_ResetsSelectionToZero", func(t *testing.T) {
s := newSelectState(items)
s.selected = 2
s.handleInput(eventChar, 'x')
if s.selected != 0 {
t.Errorf("expected selected=0 after typing, got %d", s.selected)
}
})
t.Run("Backspace_RemovesLastFilterChar", func(t *testing.T) {
s := newSelectState(items)
s.filter = "test"
s.handleInput(eventBackspace, 0)
if s.filter != "tes" {
t.Errorf("expected filter='tes', got %q", s.filter)
}
})
t.Run("Backspace_EmptyFilter_DoesNothing", func(t *testing.T) {
s := newSelectState(items)
s.handleInput(eventBackspace, 0)
if s.filter != "" {
t.Errorf("expected filter='', got %q", s.filter)
}
})
t.Run("Backspace_ResetsSelectionToZero", func(t *testing.T) {
s := newSelectState(items)
s.filter = "test"
s.selected = 2
s.handleInput(eventBackspace, 0)
if s.selected != 0 {
t.Errorf("expected selected=0 after backspace, got %d", s.selected)
}
})
t.Run("Scroll_DownPastVisibleItems_ScrollsViewport", func(t *testing.T) {
// maxDisplayedItems is 10, so with 15 items we need to scroll
manyItems := make([]selectItem, 15)
for i := range manyItems {
manyItems[i] = selectItem{Name: string(rune('a' + i))}
}
s := newSelectState(manyItems)
// move down 12 times (past the 10-item viewport)
for range 12 {
s.handleInput(eventDown, 0)
}
if s.selected != 12 {
t.Errorf("expected selected=12, got %d", s.selected)
}
if s.scrollOffset != 3 {
t.Errorf("expected scrollOffset=3 (12-10+1), got %d", s.scrollOffset)
}
})
t.Run("Scroll_UpPastScrollOffset_ScrollsViewport", func(t *testing.T) {
manyItems := make([]selectItem, 15)
for i := range manyItems {
manyItems[i] = selectItem{Name: string(rune('a' + i))}
}
s := newSelectState(manyItems)
s.selected = 5
s.scrollOffset = 5
s.handleInput(eventUp, 0)
if s.selected != 4 {
t.Errorf("expected selected=4, got %d", s.selected)
}
if s.scrollOffset != 4 {
t.Errorf("expected scrollOffset=4, got %d", s.scrollOffset)
}
})
}
func TestMultiSelectState(t *testing.T) {
items := []selectItem{
{Name: "item1"},
{Name: "item2"},
{Name: "item3"},
}
t.Run("InitialState_NoPrechecked", func(t *testing.T) {
s := newMultiSelectState(items, nil)
if s.highlighted != 0 {
t.Errorf("expected highlighted=0, got %d", s.highlighted)
}
if s.selectedCount() != 0 {
t.Errorf("expected 0 selected, got %d", s.selectedCount())
}
if s.focusOnButton {
t.Error("expected focusOnButton=false initially")
}
})
t.Run("InitialState_WithPrechecked", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item2", "item3"})
if s.selectedCount() != 2 {
t.Errorf("expected 2 selected, got %d", s.selectedCount())
}
if !s.checked[1] || !s.checked[2] {
t.Error("expected item2 and item3 to be checked")
}
})
t.Run("Prechecked_PreservesSelectionOrder", func(t *testing.T) {
// order matters: first checked = default model
s := newMultiSelectState(items, []string{"item3", "item1"})
if len(s.checkOrder) != 2 {
t.Fatalf("expected 2 in checkOrder, got %d", len(s.checkOrder))
}
if s.checkOrder[0] != 2 || s.checkOrder[1] != 0 {
t.Errorf("expected checkOrder=[2,0] (item3 first), got %v", s.checkOrder)
}
})
t.Run("Prechecked_IgnoresInvalidNames", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1", "nonexistent"})
if s.selectedCount() != 1 {
t.Errorf("expected 1 selected (nonexistent ignored), got %d", s.selectedCount())
}
})
t.Run("Toggle_ChecksUncheckedItem", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.toggleItem()
if !s.checked[0] {
t.Error("expected item1 to be checked after toggle")
}
})
t.Run("Toggle_UnchecksCheckedItem", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
s.toggleItem()
if s.checked[0] {
t.Error("expected item1 to be unchecked after toggle")
}
})
t.Run("Toggle_RemovesFromCheckOrder", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1", "item2", "item3"})
s.highlighted = 1 // toggle item2
s.toggleItem()
if len(s.checkOrder) != 2 {
t.Fatalf("expected 2 in checkOrder, got %d", len(s.checkOrder))
}
// should be [0, 2] (item1, item3) with item2 removed
if s.checkOrder[0] != 0 || s.checkOrder[1] != 2 {
t.Errorf("expected checkOrder=[0,2], got %v", s.checkOrder)
}
})
t.Run("Enter_TogglesWhenNotOnButton", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.handleInput(eventEnter, 0)
if !s.checked[0] {
t.Error("expected item1 to be checked after enter")
}
})
t.Run("Enter_OnButton_ReturnsSelection", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item2", "item1"})
s.focusOnButton = true
done, result, err := s.handleInput(eventEnter, 0)
if !done || err != nil {
t.Errorf("expected done=true, err=nil, got done=%v, err=%v", done, err)
}
// result should preserve selection order
if len(result) != 2 || result[0] != "item2" || result[1] != "item1" {
t.Errorf("expected [item2, item1], got %v", result)
}
})
t.Run("Enter_OnButton_EmptySelection_DoesNothing", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.focusOnButton = true
done, result, err := s.handleInput(eventEnter, 0)
if done || result != nil || err != nil {
t.Errorf("expected (false, nil, nil), got (%v, %v, %v)", done, result, err)
}
})
t.Run("Tab_SwitchesToButton_WhenHasSelection", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
s.handleInput(eventTab, 0)
if !s.focusOnButton {
t.Error("expected focus on button after tab")
}
})
t.Run("Tab_DoesNothing_WhenNoSelection", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.handleInput(eventTab, 0)
if s.focusOnButton {
t.Error("tab should not focus button when nothing selected")
}
})
t.Run("Tab_TogglesButtonFocus", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
s.handleInput(eventTab, 0)
if !s.focusOnButton {
t.Error("expected focus on button after first tab")
}
s.handleInput(eventTab, 0)
if s.focusOnButton {
t.Error("expected focus back on list after second tab")
}
})
t.Run("Escape_ReturnsCancelledError", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
done, result, err := s.handleInput(eventEscape, 0)
if !done || result != nil || err != errCancelled {
t.Errorf("expected (true, nil, errCancelled), got (%v, %v, %v)", done, result, err)
}
})
t.Run("IsDefault_TrueForFirstChecked", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item2", "item1"})
if !(len(s.checkOrder) > 0 && s.checkOrder[0] == 1) {
t.Error("expected item2 (idx 1) to be default (first checked)")
}
if len(s.checkOrder) > 0 && s.checkOrder[0] == 0 {
t.Error("expected item1 (idx 0) to NOT be default")
}
})
t.Run("IsDefault_FalseWhenNothingChecked", func(t *testing.T) {
s := newMultiSelectState(items, nil)
if len(s.checkOrder) > 0 && s.checkOrder[0] == 0 {
t.Error("expected isDefault=false when nothing checked")
}
})
t.Run("Down_MovesHighlight", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.handleInput(eventDown, 0)
if s.highlighted != 1 {
t.Errorf("expected highlighted=1, got %d", s.highlighted)
}
})
t.Run("Up_MovesHighlight", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.highlighted = 1
s.handleInput(eventUp, 0)
if s.highlighted != 0 {
t.Errorf("expected highlighted=0, got %d", s.highlighted)
}
})
t.Run("Arrow_ReturnsFocusFromButton", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
s.focusOnButton = true
s.handleInput(eventDown, 0)
if s.focusOnButton {
t.Error("expected focus to return to list on arrow key")
}
})
t.Run("Char_AppendsToFilter", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.handleInput(eventChar, 'x')
if s.filter != "x" {
t.Errorf("expected filter='x', got %q", s.filter)
}
})
t.Run("Char_ResetsHighlightAndScroll", func(t *testing.T) {
manyItems := make([]selectItem, 15)
for i := range manyItems {
manyItems[i] = selectItem{Name: string(rune('a' + i))}
}
s := newMultiSelectState(manyItems, nil)
s.highlighted = 10
s.scrollOffset = 5
s.handleInput(eventChar, 'x')
if s.highlighted != 0 {
t.Errorf("expected highlighted=0, got %d", s.highlighted)
}
if s.scrollOffset != 0 {
t.Errorf("expected scrollOffset=0, got %d", s.scrollOffset)
}
})
t.Run("Backspace_RemovesLastFilterChar", func(t *testing.T) {
s := newMultiSelectState(items, nil)
s.filter = "test"
s.handleInput(eventBackspace, 0)
if s.filter != "tes" {
t.Errorf("expected filter='tes', got %q", s.filter)
}
})
t.Run("Backspace_RemovesFocusFromButton", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
s.filter = "x"
s.focusOnButton = true
s.handleInput(eventBackspace, 0)
if s.focusOnButton {
t.Error("expected focusOnButton=false after backspace")
}
})
}
func TestParseInput(t *testing.T) {
t.Run("Enter", func(t *testing.T) {
event, char, err := parseInput(bytes.NewReader([]byte{13}))
if err != nil || event != eventEnter || char != 0 {
t.Errorf("expected (eventEnter, 0, nil), got (%v, %v, %v)", event, char, err)
}
})
t.Run("Escape", func(t *testing.T) {
event, _, err := parseInput(bytes.NewReader([]byte{27}))
if err != nil || event != eventEscape {
t.Errorf("expected eventEscape, got %v", event)
}
})
t.Run("CtrlC_TreatedAsEscape", func(t *testing.T) {
event, _, err := parseInput(bytes.NewReader([]byte{3}))
if err != nil || event != eventEscape {
t.Errorf("expected eventEscape for Ctrl+C, got %v", event)
}
})
t.Run("Tab", func(t *testing.T) {
event, _, err := parseInput(bytes.NewReader([]byte{9}))
if err != nil || event != eventTab {
t.Errorf("expected eventTab, got %v", event)
}
})
t.Run("Backspace", func(t *testing.T) {
event, _, err := parseInput(bytes.NewReader([]byte{127}))
if err != nil || event != eventBackspace {
t.Errorf("expected eventBackspace, got %v", event)
}
})
t.Run("UpArrow", func(t *testing.T) {
event, _, err := parseInput(bytes.NewReader([]byte{27, 91, 65}))
if err != nil || event != eventUp {
t.Errorf("expected eventUp, got %v", event)
}
})
t.Run("DownArrow", func(t *testing.T) {
event, _, err := parseInput(bytes.NewReader([]byte{27, 91, 66}))
if err != nil || event != eventDown {
t.Errorf("expected eventDown, got %v", event)
}
})
t.Run("PrintableChars", func(t *testing.T) {
tests := []struct {
name string
char byte
}{
{"lowercase", 'a'},
{"uppercase", 'Z'},
{"digit", '5'},
{"space", ' '},
{"tilde", '~'},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
event, char, err := parseInput(bytes.NewReader([]byte{tt.char}))
if err != nil || event != eventChar || char != tt.char {
t.Errorf("expected (eventChar, %q), got (%v, %q)", tt.char, event, char)
}
})
}
})
}
func TestRenderSelect(t *testing.T) {
items := []selectItem{
{Name: "item1", Description: "first item"},
{Name: "item2"},
}
t.Run("ShowsPromptAndItems", func(t *testing.T) {
s := newSelectState(items)
var buf bytes.Buffer
lineCount := renderSelect(&buf, "Select:", s)
output := buf.String()
if !strings.Contains(output, "Select:") {
t.Error("expected prompt in output")
}
if !strings.Contains(output, "item1") {
t.Error("expected item1 in output")
}
if !strings.Contains(output, "first item") {
t.Error("expected description in output")
}
if !strings.Contains(output, "item2") {
t.Error("expected item2 in output")
}
if lineCount != 3 { // 1 prompt + 2 items
t.Errorf("expected 3 lines, got %d", lineCount)
}
})
t.Run("EmptyFilteredList_ShowsNoMatches", func(t *testing.T) {
s := newSelectState(items)
s.filter = "xyz"
var buf bytes.Buffer
renderSelect(&buf, "Select:", s)
if !strings.Contains(buf.String(), "no matches") {
t.Error("expected 'no matches' message")
}
})
t.Run("LongList_ShowsRemainingCount", func(t *testing.T) {
manyItems := make([]selectItem, 15)
for i := range manyItems {
manyItems[i] = selectItem{Name: string(rune('a' + i))}
}
s := newSelectState(manyItems)
var buf bytes.Buffer
renderSelect(&buf, "Select:", s)
// 15 items - 10 displayed = 5 more
if !strings.Contains(buf.String(), "5 more") {
t.Error("expected '5 more' indicator")
}
})
}
func TestRenderMultiSelect(t *testing.T) {
items := []selectItem{
{Name: "item1"},
{Name: "item2"},
}
t.Run("ShowsCheckboxes", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
var buf bytes.Buffer
renderMultiSelect(&buf, "Select:", s)
output := buf.String()
if !strings.Contains(output, "[x]") {
t.Error("expected checked checkbox [x]")
}
if !strings.Contains(output, "[ ]") {
t.Error("expected unchecked checkbox [ ]")
}
})
t.Run("ShowsDefaultMarker", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1"})
var buf bytes.Buffer
renderMultiSelect(&buf, "Select:", s)
if !strings.Contains(buf.String(), "(default)") {
t.Error("expected (default) marker for first checked item")
}
})
t.Run("ShowsSelectedCount", func(t *testing.T) {
s := newMultiSelectState(items, []string{"item1", "item2"})
var buf bytes.Buffer
renderMultiSelect(&buf, "Select:", s)
if !strings.Contains(buf.String(), "2 selected") {
t.Error("expected '2 selected' in output")
}
})
t.Run("NoSelection_ShowsHelperText", func(t *testing.T) {
s := newMultiSelectState(items, nil)
var buf bytes.Buffer
renderMultiSelect(&buf, "Select:", s)
if !strings.Contains(buf.String(), "Select at least one") {
t.Error("expected 'Select at least one' helper text")
}
})
}
func TestErrCancelled(t *testing.T) {
t.Run("NotNil", func(t *testing.T) {
if errCancelled == nil {
t.Error("errCancelled should not be nil")
}
})
t.Run("Message", func(t *testing.T) {
if errCancelled.Error() != "cancelled" {
t.Errorf("expected 'cancelled', got %q", errCancelled.Error())
}
})
}
// Edge case tests for selector.go
// TestSelectState_SingleItem verifies that single item list works without crash.
// List with only one item should still work.
func TestSelectState_SingleItem(t *testing.T) {
items := []selectItem{{Name: "only-one"}}
s := newSelectState(items)
// Down should do nothing (already at bottom)
s.handleInput(eventDown, 0)
if s.selected != 0 {
t.Errorf("down on single item: expected selected=0, got %d", s.selected)
}
// Up should do nothing (already at top)
s.handleInput(eventUp, 0)
if s.selected != 0 {
t.Errorf("up on single item: expected selected=0, got %d", s.selected)
}
// Enter should select the only item
done, result, err := s.handleInput(eventEnter, 0)
if !done || result != "only-one" || err != nil {
t.Errorf("enter on single item: expected (true, 'only-one', nil), got (%v, %q, %v)", done, result, err)
}
}
// TestSelectState_ExactlyMaxItems verifies boundary condition at maxDisplayedItems.
// List with exactly maxDisplayedItems items should not scroll.
func TestSelectState_ExactlyMaxItems(t *testing.T) {
items := make([]selectItem, maxDisplayedItems)
for i := range items {
items[i] = selectItem{Name: string(rune('a' + i))}
}
s := newSelectState(items)
// Move to last item
for range maxDisplayedItems - 1 {
s.handleInput(eventDown, 0)
}
if s.selected != maxDisplayedItems-1 {
t.Errorf("expected selected=%d, got %d", maxDisplayedItems-1, s.selected)
}
// Should not scroll when exactly at max
if s.scrollOffset != 0 {
t.Errorf("expected scrollOffset=0 for exactly maxDisplayedItems, got %d", s.scrollOffset)
}
// One more down should do nothing
s.handleInput(eventDown, 0)
if s.selected != maxDisplayedItems-1 {
t.Errorf("down at max: expected selected=%d, got %d", maxDisplayedItems-1, s.selected)
}
}
// TestFilterItems_RegexSpecialChars verifies that filter is literal, not regex.
// User typing "model.v1" shouldn't match "modelsv1".
func TestFilterItems_RegexSpecialChars(t *testing.T) {
items := []selectItem{
{Name: "model.v1"},
{Name: "modelsv1"},
{Name: "model-v1"},
}
// Filter with dot should only match literal dot
result := filterItems(items, "model.v1")
if len(result) != 1 {
t.Errorf("expected 1 exact match, got %d", len(result))
}
if len(result) > 0 && result[0].Name != "model.v1" {
t.Errorf("expected 'model.v1', got %s", result[0].Name)
}
// Other regex special chars should be literal too
items2 := []selectItem{
{Name: "test[0]"},
{Name: "test0"},
{Name: "test(1)"},
}
result2 := filterItems(items2, "test[0]")
if len(result2) != 1 || result2[0].Name != "test[0]" {
t.Errorf("expected only 'test[0]', got %v", result2)
}
}
// TestMultiSelectState_DuplicateNames documents handling of duplicate item names.
// itemIndex uses name as key - duplicates cause collision. This documents
// the current behavior: the last index for a duplicate name is stored
func TestMultiSelectState_DuplicateNames(t *testing.T) {
// Duplicate names - this is an edge case that shouldn't happen in practice
items := []selectItem{
{Name: "duplicate"},
{Name: "duplicate"},
{Name: "unique"},
}
s := newMultiSelectState(items, nil)
// DOCUMENTED BEHAVIOR: itemIndex maps name to LAST index
// When there are duplicates, only the last occurrence's index is stored
if s.itemIndex["duplicate"] != 1 {
t.Errorf("itemIndex should map 'duplicate' to last index (1), got %d", s.itemIndex["duplicate"])
}
// Toggle item at highlighted=0 (first "duplicate")
// Due to name collision, toggleItem uses itemIndex["duplicate"] = 1
// So it actually toggles the SECOND duplicate item, not the first
s.toggleItem()
// This documents the potentially surprising behavior:
// We toggled at highlighted=0, but itemIndex lookup returned 1
if !s.checked[1] {
t.Error("toggle should check index 1 (due to name collision in itemIndex)")
}
if s.checked[0] {
t.Log("Note: index 0 is NOT checked, even though highlighted=0 (name collision behavior)")
}
}
// TestSelectState_FilterReducesBelowSelection verifies selection resets when filter reduces list.
// Prevents index-out-of-bounds on next keystroke
func TestSelectState_FilterReducesBelowSelection(t *testing.T) {
items := []selectItem{
{Name: "apple"},
{Name: "banana"},
{Name: "cherry"},
}
s := newSelectState(items)
s.selected = 2 // Select "cherry"
// Type a filter that removes cherry from results
s.handleInput(eventChar, 'a') // Filter to "a" - matches "apple" and "banana"
// Selection should reset to 0
if s.selected != 0 {
t.Errorf("expected selected=0 after filter, got %d", s.selected)
}
filtered := s.filtered()
if len(filtered) != 2 {
t.Errorf("expected 2 filtered items, got %d", len(filtered))
}
}
// TestFilterItems_UnicodeCharacters verifies filtering works with UTF-8.
// Model names might contain unicode characters
func TestFilterItems_UnicodeCharacters(t *testing.T) {
items := []selectItem{
{Name: "llama-日本語"},
{Name: "模型-chinese"},
{Name: "émoji-🦙"},
{Name: "regular-model"},
}
t.Run("filter japanese", func(t *testing.T) {
result := filterItems(items, "日本")
if len(result) != 1 || result[0].Name != "llama-日本語" {
t.Errorf("expected llama-日本語, got %v", result)
}
})
t.Run("filter chinese", func(t *testing.T) {
result := filterItems(items, "模型")
if len(result) != 1 || result[0].Name != "模型-chinese" {
t.Errorf("expected 模型-chinese, got %v", result)
}
})
t.Run("filter emoji", func(t *testing.T) {
result := filterItems(items, "🦙")
if len(result) != 1 || result[0].Name != "émoji-🦙" {
t.Errorf("expected émoji-🦙, got %v", result)
}
})
t.Run("filter accented char", func(t *testing.T) {
result := filterItems(items, "émoji")
if len(result) != 1 || result[0].Name != "émoji-🦙" {
t.Errorf("expected émoji-🦙, got %v", result)
}
})
}
// TestMultiSelectState_FilterReducesBelowHighlight verifies highlight resets when filter reduces list.
func TestMultiSelectState_FilterReducesBelowHighlight(t *testing.T) {
items := []selectItem{
{Name: "apple"},
{Name: "banana"},
{Name: "cherry"},
}
s := newMultiSelectState(items, nil)
s.highlighted = 2 // Highlight "cherry"
// Type a filter that removes cherry
s.handleInput(eventChar, 'a')
if s.highlighted != 0 {
t.Errorf("expected highlighted=0 after filter, got %d", s.highlighted)
}
}
// TestMultiSelectState_EmptyItems verifies handling of empty item list.
// Empty list should be handled gracefully.
func TestMultiSelectState_EmptyItems(t *testing.T) {
s := newMultiSelectState([]selectItem{}, nil)
// Toggle should not panic on empty list
s.toggleItem()
if s.selectedCount() != 0 {
t.Errorf("expected 0 selected for empty list, got %d", s.selectedCount())
}
// Render should handle empty list
var buf bytes.Buffer
lineCount := renderMultiSelect(&buf, "Select:", s)
if lineCount == 0 {
t.Error("renderMultiSelect should produce output even for empty list")
}
if !strings.Contains(buf.String(), "no matches") {
t.Error("expected 'no matches' for empty list")
}
}
// TestSelectState_RenderWithDescriptions verifies rendering items with descriptions.
func TestSelectState_RenderWithDescriptions(t *testing.T) {
items := []selectItem{
{Name: "item1", Description: "First item description"},
{Name: "item2", Description: ""},
{Name: "item3", Description: "Third item"},
}
s := newSelectState(items)
var buf bytes.Buffer
renderSelect(&buf, "Select:", s)
output := buf.String()
if !strings.Contains(output, "First item description") {
t.Error("expected description to be rendered")
}
if !strings.Contains(output, "item2") {
t.Error("expected item without description to be rendered")
}
}

View File

@@ -116,7 +116,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
Prompt: ">>> ",
AltPrompt: "... ",
Placeholder: "Send a message (/? for help)",
AltPlaceholder: `Use """ to end multi-line input`,
AltPlaceholder: "Press Enter to send",
})
if err != nil {
return err
@@ -159,6 +159,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
sb.WriteString(before)
if !ok {
fmt.Fprintln(&sb)
scanner.Prompt.UseAlt = true
continue
}

View File

@@ -311,6 +311,10 @@ func LoadModelMetadata(fsys fs.FS) (ModelKV, *Tokenizer, error) {
conv = &deepseekocr{}
case "DeepseekV3ForCausalLM":
conv = &deepseek2Model{}
case "Glm4MoeLiteForCausalLM":
conv = &glm4MoeLiteModel{}
case "Lfm2ForCausalLM":
conv = &lfm2Model{}
default:
return nil, nil, fmt.Errorf("unsupported architecture %q", p.Architectures[0])
}

View File

@@ -0,0 +1,264 @@
package convert
import (
"cmp"
"fmt"
"log/slog"
"regexp"
"strconv"
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/fs/ggml"
)
type glm4MoeLiteModel struct {
ModelParameters
MaxPositionEmbeddings uint32 `json:"max_position_embeddings"`
HiddenSize uint32 `json:"hidden_size"`
HiddenLayers uint32 `json:"num_hidden_layers"`
IntermediateSize uint32 `json:"intermediate_size"`
NumAttentionHeads uint32 `json:"num_attention_heads"`
NumKeyValueHeads uint32 `json:"num_key_value_heads"`
RMSNormEPS float32 `json:"rms_norm_eps"`
RopeTheta float32 `json:"rope_theta"`
QKNopeHeadDim uint32 `json:"qk_nope_head_dim"`
QKRopeHeadDim uint32 `json:"qk_rope_head_dim"`
KVLoraRank uint32 `json:"kv_lora_rank"`
QLoraRank uint32 `json:"q_lora_rank"`
VHeadDim uint32 `json:"v_head_dim"`
ExpertCount uint32 `json:"n_routed_experts"`
ExpertSharedCount uint32 `json:"n_shared_experts"`
ExpertIntermediateSize uint32 `json:"moe_intermediate_size"`
ExpertUsedCount uint32 `json:"num_experts_per_tok"`
ExpertWeightsNorm bool `json:"norm_topk_prob"`
ExpertWeightsScale float32 `json:"routed_scaling_factor"`
LeadingDenseBlockCount uint32 `json:"first_k_dense_replace"`
}
func (p *glm4MoeLiteModel) KV(t *Tokenizer) KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "glm4moelite"
kv["general.type"] = "model"
kv["glm4moelite.block_count"] = p.HiddenLayers
numHeads := p.NumAttentionHeads
numKVHeads := p.NumKeyValueHeads
kv["glm4moelite.attention.head_count"] = numHeads
kv["glm4moelite.attention.head_count_kv"] = numKVHeads
kv["glm4moelite.attention.key_length"] = p.QKNopeHeadDim + p.QKRopeHeadDim
kv["glm4moelite.attention.kv_lora_rank"] = p.KVLoraRank
kv["glm4moelite.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
kv["glm4moelite.attention.q_lora_rank"] = p.QLoraRank
kv["glm4moelite.attention.value_length"] = p.VHeadDim
kv["glm4moelite.context_length"] = p.MaxPositionEmbeddings
kv["glm4moelite.embedding_length"] = p.HiddenSize
kv["glm4moelite.expert_count"] = p.ExpertCount
kv["glm4moelite.expert_feed_forward_length"] = p.ExpertIntermediateSize
kv["glm4moelite.expert_shared_count"] = p.ExpertSharedCount
kv["glm4moelite.expert_gating_func"] = uint32(2)
kv["glm4moelite.expert_used_count"] = p.ExpertUsedCount
kv["glm4moelite.expert_weights_norm"] = p.ExpertWeightsNorm
kv["glm4moelite.expert_weights_scale"] = p.ExpertWeightsScale
kv["glm4moelite.feed_forward_length"] = p.IntermediateSize
kv["glm4moelite.leading_dense_block_count"] = p.LeadingDenseBlockCount
kv["glm4moelite.rope.dimension_count"] = p.QKRopeHeadDim
kv["glm4moelite.rope.freq_base"] = cmp.Or(p.RopeTheta, float32(1000000.0))
kv["glm4moelite.attention.key_length_mla"] = p.KVLoraRank + p.QKRopeHeadDim
kv["glm4moelite.attention.value_length_mla"] = p.KVLoraRank
kv["tokenizer.ggml.pre"] = "glm4"
return kv
}
func (p *glm4MoeLiteModel) Replacements() []string {
return []string{
"lm_head", "output",
"model.embed_tokens", "token_embd",
"model.norm", "output_norm",
"model.layers", "blk",
"input_layernorm", "attn_norm",
"self_attn.kv_a_proj_with_mqa", "attn_kv_a_mqa",
"self_attn.kv_a_layernorm", "attn_kv_a_norm",
"self_attn.kv_b_proj", "attn_kv_b",
"self_attn.q_a_proj", "attn_q_a",
"self_attn.q_a_layernorm", "attn_q_a_norm",
"self_attn.q_b_proj", "attn_q_b",
"self_attn.o_proj", "attn_output",
"post_attention_layernorm", "ffn_norm",
"mlp.shared_experts.down_proj", "ffn_down_shexp",
"mlp.shared_experts.gate_proj", "ffn_gate_shexp",
"mlp.shared_experts.up_proj", "ffn_up_shexp",
"mlp.gate_proj", "ffn_gate",
"mlp.down_proj", "ffn_down",
"mlp.up_proj", "ffn_up",
"mlp.gate.e_score_correction_bias", "exp_probs_b.bias",
"mlp.gate", "ffn_gate_inp",
}
}
// repackKVB extracts K or V from the combined KV_B tensor for MLA absorption.
// K output row-major: [n_head, kv_lora_rank, qk_nope] -> GGML ne[]={qk_nope, kv_lora_rank, n_head}
// V output row-major: [n_head, v_head, kv_lora_rank] -> GGML ne[]={kv_lora_rank, v_head, n_head}
func (p *glm4MoeLiteModel) repackKVB(extractK bool, kvFirst bool, numHeads int) Repacker {
qkNope := int(p.QKNopeHeadDim)
vHeadDim := int(p.VHeadDim)
kvLoraRank := int(p.KVLoraRank)
kvPerHead := qkNope + vHeadDim
return func(_ string, data []float32, shape []uint64) ([]float32, error) {
dims := make([]int, len(shape))
for i := range shape {
dims[i] = int(shape[i])
}
var tt tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
var err error
// Normalize to [n_head * (qk_nope + v_head), kv_lora_rank] layout
if kvFirst {
tt, err = tensor.Transpose(tt, 1, 0)
if err != nil {
return nil, err
}
tt = tensor.Materialize(tt)
}
// Reshape to [n_head, qk_nope + v_head, kv_lora_rank]
if err := tt.Reshape(numHeads, kvPerHead, kvLoraRank); err != nil {
return nil, err
}
if extractK {
// Slice K: [n_head, qk_nope, kv_lora_rank]
tt, err = tt.Slice(nil, tensor.S(0, qkNope), nil)
if err != nil {
return nil, err
}
tt = tensor.Materialize(tt)
// Transpose to [n_head, kv_lora_rank, qk_nope]
tt, err = tensor.Transpose(tt, 0, 2, 1)
if err != nil {
return nil, err
}
tt = tensor.Materialize(tt)
} else {
// Slice V: [n_head, v_head, kv_lora_rank] - already correct layout
tt, err = tt.Slice(nil, tensor.S(qkNope, kvPerHead), nil)
if err != nil {
return nil, err
}
tt = tensor.Materialize(tt)
}
if err := tt.Reshape(tt.Shape().TotalSize()); err != nil {
return nil, err
}
return native.VectorF32(tt.(*tensor.Dense))
}
}
func (p *glm4MoeLiteModel) Tensors(s []Tensor) (out []*ggml.Tensor) {
merges := make([]merge, p.HiddenLayers*3)
for i := range p.HiddenLayers {
merges[i*3+0] = merge{
fmt.Sprintf("blk.%d.mlp.experts.*.gate_proj.weight", i),
fmt.Sprintf("blk.%d.ffn_gate_exps.weight", i),
}
merges[i*3+1] = merge{
fmt.Sprintf("blk.%d.mlp.experts.*.up_proj.weight", i),
fmt.Sprintf("blk.%d.ffn_up_exps.weight", i),
}
merges[i*3+2] = merge{
fmt.Sprintf("blk.%d.mlp.experts.*.down_proj.weight", i),
fmt.Sprintf("blk.%d.ffn_down_exps.weight", i),
}
}
skipLayer := func(n string, minValue uint32) bool {
re := regexp.MustCompile(`^blk\.(\d+)`)
matches := re.FindStringSubmatch(n)
if matches == nil {
return false
}
blkNum, err := strconv.Atoi(matches[1])
if err != nil {
return false
}
return uint32(blkNum) >= minValue
}
out, s = mergeTensors(s, merges...)
for _, t := range s {
// skip any additional layers (such as the Multi-Token Prediction layer)
if skipLayer(t.Name(), p.HiddenLayers) {
slog.Debug("skipping layer", "name", t.Name())
continue
}
// Split attn_kv_b into separate attn_k_b and attn_v_b for MLA absorption
if strings.HasSuffix(t.Name(), ".attn_kv_b.weight") {
qkNope := int(p.QKNopeHeadDim)
vHeadDim := int(p.VHeadDim)
kvLoraRank := int(p.KVLoraRank)
kvPerHead := qkNope + vHeadDim
numHeads := int(p.NumAttentionHeads)
kvFirst := true
if len(t.Shape()) == 2 {
switch {
case int(t.Shape()[0]) == kvLoraRank:
if kvPerHead > 0 && int(t.Shape()[1])%kvPerHead == 0 {
numHeads = int(t.Shape()[1]) / kvPerHead
}
kvFirst = true
case int(t.Shape()[1]) == kvLoraRank:
if kvPerHead > 0 && int(t.Shape()[0])%kvPerHead == 0 {
numHeads = int(t.Shape()[0]) / kvPerHead
}
kvFirst = false
default:
slog.Warn("glm4moelite: unexpected attn_kv_b layout", "name", t.Name(), "shape", t.Shape())
}
}
kTensor := t.Clone()
kTensor.SetRepacker(p.repackKVB(true, kvFirst, numHeads))
out = append(out, &ggml.Tensor{
Name: strings.Replace(t.Name(), "attn_kv_b", "attn_k_b", 1),
Kind: t.Kind(),
Shape: []uint64{uint64(numHeads), uint64(kvLoraRank), uint64(qkNope)},
WriterTo: kTensor,
})
vTensor := t.Clone()
vTensor.SetRepacker(p.repackKVB(false, kvFirst, numHeads))
out = append(out, &ggml.Tensor{
Name: strings.Replace(t.Name(), "attn_kv_b", "attn_v_b", 1),
Kind: t.Kind(),
Shape: []uint64{uint64(numHeads), uint64(vHeadDim), uint64(kvLoraRank)},
WriterTo: vTensor,
})
continue
}
out = append(out, &ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),
WriterTo: t,
})
}
return out
}

100
convert/convert_lfm2.go Normal file
View File

@@ -0,0 +1,100 @@
package convert
import (
"slices"
"strings"
"github.com/ollama/ollama/fs/ggml"
)
type lfm2Model struct {
ModelParameters
HiddenSize uint32 `json:"hidden_size"`
NumHiddenLayers uint32 `json:"num_hidden_layers"`
MaxPositionEmbeddings uint32 `json:"max_position_embeddings"`
IntermediateSize uint32 `json:"intermediate_size"`
NumAttentionHeads uint32 `json:"num_attention_heads"`
NumKeyValueHeads uint32 `json:"num_key_value_heads"`
RopeTheta float32 `json:"rope_theta"`
NormEps float32 `json:"norm_eps"`
ConvLCache uint32 `json:"conv_L_cache"`
LayerTypes []string `json:"layer_types"`
TieEmbedding bool `json:"tie_embedding"`
}
var _ ModelConverter = (*lfm2Model)(nil)
func (p *lfm2Model) KV(t *Tokenizer) KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "lfm2"
kv["lfm2.vocab_size"] = p.VocabSize
kv["lfm2.block_count"] = p.NumHiddenLayers
kv["lfm2.embedding_length"] = p.HiddenSize
kv["lfm2.feed_forward_length"] = p.IntermediateSize
kv["lfm2.context_length"] = p.MaxPositionEmbeddings
// Build per-layer KV head count array based on layer_types
// (0 = shortconv layer, non-zero = attention layer with that many KV heads)
kvHeadCounts := make([]uint32, p.NumHiddenLayers)
for i := range p.NumHiddenLayers {
if int(i) < len(p.LayerTypes) && p.LayerTypes[i] == "full_attention" {
kvHeadCounts[i] = p.NumKeyValueHeads
}
}
kv["lfm2.attention.head_count"] = p.NumAttentionHeads
kv["lfm2.attention.head_count_kv"] = kvHeadCounts
kv["lfm2.attention.key_length"] = p.HiddenSize / p.NumAttentionHeads
kv["lfm2.attention.value_length"] = p.HiddenSize / p.NumAttentionHeads
kv["lfm2.attention.layer_norm_rms_epsilon"] = p.NormEps
kv["lfm2.rope.freq_base"] = p.RopeTheta
kv["lfm2.shortconv.l_cache"] = p.ConvLCache
return kv
}
func (p *lfm2Model) Tensors(ts []Tensor) []*ggml.Tensor {
var out []*ggml.Tensor
for _, t := range ts {
shape := t.Shape()
// Squeeze conv weights: [D, 1, K] -> [D, K]
if strings.HasSuffix(t.Name(), "shortconv.conv.weight") {
if len(shape) == 3 && shape[1] == 1 {
shape = []uint64{shape[0], shape[2]}
}
}
out = append(out, &ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: slices.Clone(shape),
WriterTo: t,
})
}
return out
}
func (p *lfm2Model) Replacements() []string {
return []string{
"model.embed_tokens", "token_embd",
"model.embedding_norm", "output_norm",
"model.layers", "blk",
"operator_norm", "attn_norm",
"self_attn.q_proj", "attn_q",
"self_attn.k_proj", "attn_k",
"self_attn.v_proj", "attn_v",
"self_attn.out_proj", "attn_output",
"self_attn.q_layernorm", "attn_q_norm",
"self_attn.k_layernorm", "attn_k_norm",
"conv.conv", "shortconv.conv",
"conv.in_proj", "shortconv.in_proj",
"conv.out_proj", "shortconv.out_proj",
"feed_forward.w1", "ffn_gate",
"feed_forward.w2", "ffn_down",
"feed_forward.w3", "ffn_up",
"ffn_norm", "ffn_norm",
}
}

View File

@@ -40,6 +40,7 @@ const (
func (t tensorBase) Kind() uint32 {
if strings.HasSuffix(t.name, ".ffn_gate_inp.weight") ||
strings.HasSuffix(t.name, ".bias") ||
strings.HasSuffix(t.name, ".shortconv.conv.weight") ||
t.name == "token_types.weight" ||
t.name == "v.positional_embedding_vlm" ||
t.name == "v.tile_position_embd.weight" ||

View File

@@ -16,6 +16,7 @@
- [Generate Embeddings](#generate-embeddings)
- [List Running Models](#list-running-models)
- [Version](#version)
- [Experimental: Image Generation](#image-generation-experimental)
## Conventions
@@ -58,6 +59,15 @@ Advanced parameters (optional):
- `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
- `context` (deprecated): the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
Experimental image generation parameters (for image generation models only):
> [!WARNING]
> These parameters are experimental and may change in future versions.
- `width`: width of the generated image in pixels
- `height`: height of the generated image in pixels
- `steps`: number of diffusion steps
#### Structured outputs
Structured outputs are supported by providing a JSON schema in the `format` parameter. The model will generate a response that matches the schema. See the [structured outputs](#request-structured-outputs) example below.
@@ -1867,3 +1877,55 @@ curl http://localhost:11434/api/version
"version": "0.5.1"
}
```
## Experimental Features
### Image Generation (Experimental)
> [!WARNING]
> Image generation is experimental and may change in future versions.
Image generation is now supported through the standard `/api/generate` endpoint when using image generation models. The API automatically detects when an image generation model is being used.
See the [Generate a completion](#generate-a-completion) section for the full API documentation. The experimental image generation parameters (`width`, `height`, `steps`) are documented there.
#### Example
##### Request
```shell
curl http://localhost:11434/api/generate -d '{
"model": "x/z-image-turbo",
"prompt": "a sunset over mountains",
"width": 1024,
"height": 768
}'
```
##### Response (streaming)
Progress updates during generation:
```json
{
"model": "x/z-image-turbo",
"created_at": "2024-01-15T10:30:00.000000Z",
"completed": 5,
"total": 20,
"done": false
}
```
##### Final Response
```json
{
"model": "x/z-image-turbo",
"created_at": "2024-01-15T10:30:15.000000Z",
"image": "iVBORw0KGgoAAAANSUhEUg...",
"done": true,
"done_reason": "stop",
"total_duration": 15000000000,
"load_duration": 2000000000
}
```

View File

@@ -4,16 +4,6 @@ title: Anthropic compatibility
Ollama provides compatibility with the [Anthropic Messages API](https://docs.anthropic.com/en/api/messages) to help connect existing applications to Ollama, including tools like Claude Code.
## Recommended models
For coding use cases, models like `glm-4.7:cloud`, `minimax-m2.1:cloud`, and `qwen3-coder` are recommended.
Pull a model before use:
```shell
ollama pull qwen3-coder
ollama pull glm-4.7:cloud
```
## Usage
### Environment variables
@@ -21,8 +11,9 @@ ollama pull glm-4.7:cloud
To use Ollama with tools that expect the Anthropic API (like Claude Code), set these environment variables:
```shell
export ANTHROPIC_AUTH_TOKEN=ollama # required but ignored
export ANTHROPIC_API_KEY="" # required but ignored
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama # required but ignored
```
### Simple `/v1/messages` example
@@ -244,29 +235,55 @@ curl -X POST http://localhost:11434/v1/messages \
## Using with Claude Code
[Claude Code](https://code.claude.com/docs/en/overview) can be configured to use Ollama as its backend:
[Claude Code](https://code.claude.com/docs/en/overview) can be configured to use Ollama as its backend.
### Recommended models
For coding use cases, models like `glm-4.7`, `minimax-m2.1`, and `qwen3-coder` are recommended.
Download a model before use:
```shell
ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
ollama pull qwen3-coder
```
> Note: Qwen 3 coder is a 30B parameter model requiring at least 24GB of VRAM to run smoothly. More is required for longer context lengths.
```shell
ollama pull glm-4.7:cloud
```
### Quick setup
```shell
ollama launch claude
```
This will prompt you to select a model, configure Claude Code automatically, and launch it. To configure without launching:
```shell
ollama launch claude --config
```
### Manual setup
Set the environment variables and run Claude Code:
```shell
ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY="" claude --model qwen3-coder
```
Or set the environment variables in your shell profile:
```shell
export ANTHROPIC_AUTH_TOKEN=ollama
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama
export ANTHROPIC_API_KEY=""
```
Then run Claude Code with any Ollama model:
```shell
# Local models
claude --model qwen3-coder
claude --model gpt-oss:20b
# Cloud models
claude --model glm-4.7:cloud
claude --model minimax-m2.1:cloud
```
## Endpoints

View File

@@ -275,6 +275,73 @@ curl -X POST http://localhost:11434/v1/chat/completions \
- [x] `dimensions`
- [ ] `user`
### `/v1/images/generations` (experimental)
> Note: This endpoint is experimental and may change or be removed in future versions.
Generate images using image generation models.
<CodeGroup dropdown>
```python images.py
from openai import OpenAI
client = OpenAI(
base_url='http://localhost:11434/v1/',
api_key='ollama', # required but ignored
)
response = client.images.generate(
model='x/z-image-turbo',
prompt='A cute robot learning to paint',
size='1024x1024',
response_format='b64_json',
)
print(response.data[0].b64_json[:50] + '...')
```
```javascript images.js
import OpenAI from "openai";
const openai = new OpenAI({
baseURL: "http://localhost:11434/v1/",
apiKey: "ollama", // required but ignored
});
const response = await openai.images.generate({
model: "x/z-image-turbo",
prompt: "A cute robot learning to paint",
size: "1024x1024",
response_format: "b64_json",
});
console.log(response.data[0].b64_json.slice(0, 50) + "...");
```
```shell images.sh
curl -X POST http://localhost:11434/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"model": "x/z-image-turbo",
"prompt": "A cute robot learning to paint",
"size": "1024x1024",
"response_format": "b64_json"
}'
```
</CodeGroup>
#### Supported request fields
- [x] `model`
- [x] `prompt`
- [x] `size` (e.g. "1024x1024")
- [x] `response_format` (only `b64_json` supported)
- [ ] `n`
- [ ] `quality`
- [ ] `style`
- [ ] `user`
### `/v1/responses`
> Note: Added in Ollama v0.13.3

View File

@@ -110,7 +110,7 @@ More Ollama [Python example](https://github.com/ollama/ollama-python/blob/main/e
import { Ollama } from "ollama";
const client = new Ollama();
const results = await client.webSearch({ query: "what is ollama?" });
const results = await client.webSearch("what is ollama?");
console.log(JSON.stringify(results, null, 2));
```
@@ -213,7 +213,7 @@ models](https://ollama.com/models)\n\nAvailable for macOS, Windows, and Linux',
import { Ollama } from "ollama";
const client = new Ollama();
const fetchResult = await client.webFetch({ url: "https://ollama.com" });
const fetchResult = await client.webFetch("https://ollama.com");
console.log(JSON.stringify(fetchResult, null, 2));
```

View File

@@ -8,6 +8,47 @@ title: CLI Reference
ollama run gemma3
```
### Launch integrations
```
ollama launch
```
Configure and launch external applications to use Ollama models. This provides an interactive way to set up and start integrations with supported apps.
#### Supported integrations
- **OpenCode** - Open-source coding assistant
- **Claude Code** - Anthropic's agentic coding tool
- **Codex** - OpenAI's coding assistant
- **Droid** - Factory's AI coding agent
#### Examples
Launch an integration interactively:
```
ollama launch
```
Launch a specific integration:
```
ollama launch claude
```
Launch with a specific model:
```
ollama launch claude --model qwen3-coder
```
Configure without launching:
```
ollama launch droid --config
```
#### Multiline input
For multiline input, you can wrap text with `"""`:

View File

@@ -3,8 +3,6 @@ title: Cloud
sidebarTitle: Cloud
---
<Info>Ollama's cloud is currently in preview.</Info>
## Cloud Models
Ollama's cloud models are a new kind of model in Ollama that can run without a powerful GPU. Instead, cloud models are automatically offloaded to Ollama's cloud service while offering the same capabilities as local models, making it possible to keep using your local tools while running larger models that wouldn't fit on a personal computer.

View File

@@ -8,7 +8,7 @@ Context length is the maximum number of tokens that the model has access to in m
The default context length in Ollama is 4096 tokens.
</Note>
Tasks which require large context like web search, agents, and coding tools should be set to at least 32000 tokens.
Tasks which require large context like web search, agents, and coding tools should be set to at least 64000 tokens.
## Setting context length
@@ -24,7 +24,7 @@ Change the slider in the Ollama app under settings to your desired context lengt
### CLI
If editing the context length for Ollama is not possible, the context length can also be updated when serving Ollama.
```
OLLAMA_CONTEXT_LENGTH=32000 ollama serve
OLLAMA_CONTEXT_LENGTH=64000 ollama serve
```
### Check allocated context length and model offloading

View File

@@ -102,16 +102,19 @@
"group": "Integrations",
"pages": [
"/integrations/claude-code",
"/integrations/vscode",
"/integrations/jetbrains",
"/integrations/codex",
"/integrations/cline",
"/integrations/codex",
"/integrations/droid",
"/integrations/goose",
"/integrations/zed",
"/integrations/roo-code",
"/integrations/jetbrains",
"/integrations/marimo",
"/integrations/n8n",
"/integrations/xcode"
"/integrations/onyx",
"/integrations/opencode",
"/integrations/roo-code",
"/integrations/vscode",
"/integrations/xcode",
"/integrations/zed"
]
},
{

View File

@@ -22,7 +22,7 @@ Please refer to the [GPU docs](./gpu).
## How can I specify the context window size?
By default, Ollama uses a context window size of 2048 tokens.
By default, Ollama uses a context window size of 4096 tokens.
This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use:

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@@ -9,7 +9,7 @@ sidebarTitle: Welcome
<CardGroup cols={2}>
<Card title="Quickstart" icon="rocket" href="/quickstart">
Get up and running with your first model
Get up and running with your first model or integrate Ollama with your favorite tools
</Card>
<Card
title="Download Ollama"

View File

@@ -2,6 +2,12 @@
title: Claude Code
---
Claude Code is Anthropic's agentic coding tool that can read, modify, and execute code in your working directory.
Open models can be used with Claude Code through Ollama's Anthropic-compatible API, enabling you to use models such as `glm-4.7`, `qwen3-coder`, `gpt-oss`.
![Claude Code with Ollama](https://files.ollama.com/claude-code.png)
## Install
Install [Claude Code](https://code.claude.com/docs/en/overview):
@@ -20,50 +26,50 @@ irm https://claude.ai/install.ps1 | iex
## Usage with Ollama
### Quick setup
```shell
ollama launch claude
```
To configure without launching:
```shell
ollama launch claude --config
```
### Manual setup
Claude Code connects to Ollama using the Anthropic-compatible API.
1. Set the environment variables:
```shell
export ANTHROPIC_AUTH_TOKEN=ollama
export ANTHROPIC_API_KEY=""
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama
```
2. Run Claude Code with an Ollama model:
```shell
claude --model qwen3-coder
claude --model gpt-oss:20b
```
Or run with environment variables inline:
```shell
ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY="" claude --model qwen3-coder
```
## Connecting to ollama.com
1. Create an [API key](https://ollama.com/settings/keys) on ollama.com
2. Set the environment variables:
```shell
export ANTHROPIC_BASE_URL=https://ollama.com
export ANTHROPIC_API_KEY=<your-api-key>
```
3. Run Claude Code with a cloud model:
```shell
claude --model glm-4.7:cloud
```
**Note:** Claude Code requires a large context window. We recommend at least 64k tokens. See the [context length documentation](/context-length) for how to adjust context length in Ollama.
## Recommended Models
### Cloud models
- `glm-4.7:cloud` - High-performance cloud model
- `minimax-m2.1:cloud` - Fast cloud model
- `qwen3-coder:480b` - Large coding model
- `qwen3-coder`
- `glm-4.7`
- `gpt-oss:20b`
- `gpt-oss:120b`
Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
### Local models
- `qwen3-coder` - Excellent for coding tasks
- `gpt-oss:20b` - Strong general-purpose model

View File

@@ -13,7 +13,21 @@ npm install -g @openai/codex
## Usage with Ollama
<Note>Codex requires a larger context window. It is recommended to use a context window of at least 32K tokens.</Note>
<Note>Codex requires a larger context window. It is recommended to use a context window of at least 64k tokens.</Note>
### Quick setup
```
ollama launch codex
```
To configure without launching:
```shell
ollama launch codex --config
```
### Manual setup
To use `codex` with Ollama, use the `--oss` flag:

View File

@@ -11,10 +11,24 @@ Install the [Droid CLI](https://factory.ai/):
curl -fsSL https://app.factory.ai/cli | sh
```
<Note>Droid requires a larger context window. It is recommended to use a context window of at least 32K tokens. See [Context length](/context-length) for more information.</Note>
<Note>Droid requires a larger context window. It is recommended to use a context window of at least 64k tokens. See [Context length](/context-length) for more information.</Note>
## Usage with Ollama
### Quick setup
```bash
ollama launch droid
```
To configure without launching:
```shell
ollama launch droid --config
```
### Manual setup
Add a local configuration block to `~/.factory/config.json`:
```json
@@ -73,4 +87,4 @@ Add the cloud configuration block to `~/.factory/config.json`:
}
```
Run `droid` in a new terminal to load the new settings.
Run `droid` in a new terminal to load the new settings.

View File

@@ -0,0 +1,73 @@
---
title: marimo
---
## Install
Install [marimo](https://marimo.io). You can use `pip` or `uv` for this. You
can also use `uv` to create a sandboxed environment for marimo by running:
```
uvx marimo edit --sandbox notebook.py
```
## Usage with Ollama
1. In marimo, go to the user settings and go to the AI tab. From here
you can find and configure Ollama as an AI provider. For local use you
would typically point the base url to `http://localhost:11434/v1`.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-settings.png"
alt="Ollama settings in marimo"
width="50%"
/>
</div>
2. Once the AI provider is set up, you can turn on/off specific AI models you'd like to access.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-models.png"
alt="Selecting an Ollama model"
width="50%"
/>
</div>
3. You can also add a model to the list of available models by scrolling to the bottom and using the UI there.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-add-model.png"
alt="Adding a new Ollama model"
width="50%"
/>
</div>
4. Once configured, you can now use Ollama for AI chats in marimo.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-chat.png"
alt="Configure code completion"
width="50%"
/>
</div>
4. Alternatively, you can now use Ollama for **inline code completion** in marimo. This can be configured in the "AI Features" tab.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-code-completion.png"
alt="Configure code completion"
width="50%"
/>
</div>
## Connecting to ollama.com
1. Sign in to ollama cloud via `ollama signin`
2. In the ollama model settings add a model that ollama hosts, like `gpt-oss:120b`.
3. You can now refer to this model in marimo!

View File

@@ -0,0 +1,63 @@
---
title: Onyx
---
## Overview
[Onyx](http://onyx.app/) is a self-hostable Chat UI that integrates with all Ollama models. Features include:
- Creating custom Agents
- Web search
- Deep Research
- RAG over uploaded documents and connected apps
- Connectors to applications like Google Drive, Email, Slack, etc.
- MCP and OpenAPI Actions support
- Image generation
- User/Groups management, RBAC, SSO, etc.
Onyx can be deployed for single users or large organizations.
## Install Onyx
Deploy Onyx with the [quickstart guide](https://docs.onyx.app/deployment/getting_started/quickstart).
<Info>
Resourcing/scaling docs [here](https://docs.onyx.app/deployment/getting_started/resourcing).
</Info>
## Usage with Ollama
1. Login to your Onyx deployment (create an account first).
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-login.png"
alt="Onyx Login Page"
width="75%"
/>
</div>
2. In the set-up process select `Ollama` as the LLM provider.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-ollama-llm.png"
alt="Onyx Set Up Form"
width="75%"
/>
</div>
3. Provide your **Ollama API URL** and select your models.
<Note>If you're running Onyx in Docker, to access your computer's local network use `http://host.docker.internal` instead of `http://127.0.0.1`.</Note>
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-ollama-form.png"
alt="Selecting Ollama Models"
width="75%"
/>
</div>
You can also easily connect up Onyx Cloud with the `Ollama Cloud` tab of the setup.
## Send your first query
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-query.png"
alt="Onyx Query Example"
width="75%"
/>
</div>

View File

@@ -0,0 +1,106 @@
---
title: OpenCode
---
OpenCode is an open-source AI coding assistant that runs in your terminal.
## Install
Install the [OpenCode CLI](https://opencode.ai):
```bash
curl -fsSL https://opencode.ai/install.sh | bash
```
<Note>OpenCode requires a larger context window. It is recommended to use a context window of at least 64k tokens. See [Context length](/context-length) for more information.</Note>
## Usage with Ollama
### Quick setup
```bash
ollama launch opencode
```
To configure without launching:
```shell
ollama launch opencode --config
```
### Manual setup
Add a configuration block to `~/.config/opencode/opencode.json`:
```json
{
"$schema": "https://opencode.ai/config.json",
"provider": {
"ollama": {
"npm": "@ai-sdk/openai-compatible",
"name": "Ollama",
"options": {
"baseURL": "http://localhost:11434/v1"
},
"models": {
"qwen3-coder": {
"name": "qwen3-coder"
}
}
}
}
}
```
## Cloud Models
`glm-4.7:cloud` is the recommended model for use with OpenCode.
Add the cloud configuration to `~/.config/opencode/opencode.json`:
```json
{
"$schema": "https://opencode.ai/config.json",
"provider": {
"ollama": {
"npm": "@ai-sdk/openai-compatible",
"name": "Ollama",
"options": {
"baseURL": "http://localhost:11434/v1"
},
"models": {
"glm-4.7:cloud": {
"name": "glm-4.7:cloud"
}
}
}
}
}
```
## Connecting to ollama.com
1. Create an [API key](https://ollama.com/settings/keys) from ollama.com and export it as `OLLAMA_API_KEY`.
2. Update `~/.config/opencode/opencode.json` to point to ollama.com:
```json
{
"$schema": "https://opencode.ai/config.json",
"provider": {
"ollama": {
"npm": "@ai-sdk/openai-compatible",
"name": "Ollama Cloud",
"options": {
"baseURL": "https://ollama.com/v1"
},
"models": {
"glm-4.7:cloud": {
"name": "glm-4.7:cloud"
}
}
}
}
}
```
Run `opencode` in a new terminal to load the new settings.

View File

@@ -1,5 +1,5 @@
---
title: "Linux"
title: Linux
---
## Install
@@ -13,14 +13,15 @@ curl -fsSL https://ollama.com/install.sh | sh
## Manual install
<Note>
If you are upgrading from a prior version, you should remove the old libraries with `sudo rm -rf /usr/lib/ollama` first.
If you are upgrading from a prior version, you should remove the old libraries
with `sudo rm -rf /usr/lib/ollama` first.
</Note>
Download and extract the package:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
| sudo tar zx -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tar.zst \
| sudo tar x -C /usr
```
Start Ollama:
@@ -40,8 +41,8 @@ ollama -v
If you have an AMD GPU, also download and extract the additional ROCm package:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tgz \
| sudo tar zx -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tar.zst \
| sudo tar x -C /usr
```
### ARM64 install
@@ -49,8 +50,8 @@ curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tgz \
Download and extract the ARM64-specific package:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-arm64.tgz \
| sudo tar zx -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-arm64.tar.zst \
| sudo tar x -C /usr
```
### Adding Ollama as a startup service (recommended)
@@ -112,7 +113,11 @@ sudo systemctl status ollama
```
<Note>
While AMD has contributed the `amdgpu` driver upstream to the official linux kernel source, the version is older and may not support all ROCm features. We recommend you install the latest driver from https://www.amd.com/en/support/linux-drivers for best support of your Radeon GPU.
While AMD has contributed the `amdgpu` driver upstream to the official linux
kernel source, the version is older and may not support all ROCm features. We
recommend you install the latest driver from
https://www.amd.com/en/support/linux-drivers for best support of your Radeon
GPU.
</Note>
## Customizing
@@ -141,8 +146,8 @@ curl -fsSL https://ollama.com/install.sh | sh
Or by re-downloading Ollama:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
| sudo tar zx -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tar.zst \
| sudo tar x -C /usr
```
## Installing specific versions
@@ -191,4 +196,4 @@ Remove the downloaded models and Ollama service user and group:
sudo userdel ollama
sudo groupdel ollama
sudo rm -r /usr/share/ollama
```
```

View File

@@ -18,13 +18,13 @@ This quickstart will walk your through running your first model with Ollama. To
<Tab title="CLI">
Open a terminal and run the command:
```
```sh
ollama run gemma3
```
</Tab>
<Tab title="cURL">
```
```sh
ollama pull gemma3
```
@@ -45,13 +45,13 @@ This quickstart will walk your through running your first model with Ollama. To
<Tab title="Python">
Start by downloading a model:
```
```sh
ollama pull gemma3
```
Then install Ollama's Python library:
```
```sh
pip install ollama
```
@@ -101,3 +101,42 @@ This quickstart will walk your through running your first model with Ollama. To
</Tabs>
See a full list of available models [here](https://ollama.com/models).
## Coding
For coding use cases, we recommend using the `glm-4.7-flash` model.
Note: this model requires 23 GB of VRAM with 64000 tokens context length.
```sh
ollama pull glm-4.7-flash
```
Alternatively, you can use a more powerful cloud model (with full context length):
```sh
ollama pull glm-4.7:cloud
```
Use `ollama launch` to quickly set up a coding tool with Ollama models:
```sh
ollama launch
```
### Supported integrations
- [OpenCode](/integrations/opencode) - Open-source coding assistant
- [Claude Code](/integrations/claude-code) - Anthropic's agentic coding tool
- [Codex](/integrations/codex) - OpenAI's coding assistant
- [Droid](/integrations/droid) - Factory's AI coding agent
### Launch with a specific model
```sh
ollama launch claude --model glm-4.7-flash
```
### Configure without launching
```sh
ollama launch claude --config
```

View File

@@ -1,3 +0,0 @@
# Troubleshooting
For troubleshooting, see [https://docs.ollama.com/troubleshooting](https://docs.ollama.com/troubleshooting)

View File

@@ -269,6 +269,8 @@ func (kv KV) OllamaEngineRequired() bool {
"qwen25vl",
"qwen3", "qwen3moe",
"qwen3vl", "qwen3vlmoe",
"glm4moelite",
"lfm2",
}, kv.Architecture())
}
@@ -856,7 +858,9 @@ func (f GGML) FlashAttention() bool {
return slices.Contains([]string{
"bert",
"gemma3",
"glm4moelite",
"gptoss", "gpt-oss",
"lfm2",
"mistral3",
"olmo3",
"qwen3", "qwen3moe",

18
go.mod
View File

@@ -15,8 +15,8 @@ require (
github.com/spf13/cobra v1.7.0
github.com/stretchr/testify v1.9.0
github.com/x448/float16 v0.8.4
golang.org/x/sync v0.19.0
golang.org/x/sys v0.39.0
golang.org/x/sync v0.17.0
golang.org/x/sys v0.37.0
)
require (
@@ -30,8 +30,8 @@ require (
github.com/tkrajina/typescriptify-golang-structs v0.2.0
github.com/wk8/go-ordered-map/v2 v2.1.8
golang.org/x/image v0.22.0
golang.org/x/mod v0.31.0
golang.org/x/tools v0.40.0
golang.org/x/mod v0.30.0
golang.org/x/tools v0.38.0
gonum.org/v1/gonum v0.15.0
)
@@ -81,11 +81,11 @@ require (
github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
github.com/ugorji/go/codec v1.2.12 // indirect
golang.org/x/arch v0.8.0 // indirect
golang.org/x/crypto v0.46.0
golang.org/x/exp v0.0.0-20251219203646-944ab1f22d93
golang.org/x/net v0.48.0 // indirect
golang.org/x/term v0.38.0
golang.org/x/text v0.32.0
golang.org/x/crypto v0.43.0
golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa // indirect
golang.org/x/net v0.46.0 // indirect
golang.org/x/term v0.36.0
golang.org/x/text v0.30.0
google.golang.org/protobuf v1.34.1
gopkg.in/yaml.v3 v3.0.1 // indirect
)

36
go.sum
View File

@@ -233,16 +233,16 @@ golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACk
golang.org/x/crypto v0.0.0-20190510104115-cbcb75029529/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20191011191535-87dc89f01550/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
golang.org/x/crypto v0.46.0 h1:cKRW/pmt1pKAfetfu+RCEvjvZkA9RimPbh7bhFjGVBU=
golang.org/x/crypto v0.46.0/go.mod h1:Evb/oLKmMraqjZ2iQTwDwvCtJkczlDuTmdJXoZVzqU0=
golang.org/x/crypto v0.43.0 h1:dduJYIi3A3KOfdGOHX8AVZ/jGiyPa3IbBozJ5kNuE04=
golang.org/x/crypto v0.43.0/go.mod h1:BFbav4mRNlXJL4wNeejLpWxB7wMbc79PdRGhWKncxR0=
golang.org/x/exp v0.0.0-20180321215751-8460e604b9de/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20180807140117-3d87b88a115f/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20190121172915-509febef88a4/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20190125153040-c74c464bbbf2/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20190306152737-a1d7652674e8/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20191002040644-a1355ae1e2c3/go.mod h1:NOZ3BPKG0ec/BKJQgnvsSFpcKLM5xXVWnvZS97DWHgE=
golang.org/x/exp v0.0.0-20251219203646-944ab1f22d93 h1:fQsdNF2N+/YewlRZiricy4P1iimyPKZ/xwniHj8Q2a0=
golang.org/x/exp v0.0.0-20251219203646-944ab1f22d93/go.mod h1:EPRbTFwzwjXj9NpYyyrvenVh9Y+GFeEvMNh7Xuz7xgU=
golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa h1:t2QcU6V556bFjYgu4L6C+6VrCPyJZ+eyRsABUPs1mz4=
golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa/go.mod h1:BHOTPb3L19zxehTsLoJXVaTktb06DFgmdW6Wb9s8jqk=
golang.org/x/image v0.0.0-20180708004352-c73c2afc3b81/go.mod h1:ux5Hcp/YLpHSI86hEcLt0YII63i6oz57MZXIpbrjZUs=
golang.org/x/image v0.0.0-20190227222117-0694c2d4d067/go.mod h1:kZ7UVZpmo3dzQBMxlp+ypCbDeSB+sBbTgSJuh5dn5js=
golang.org/x/image v0.0.0-20190802002840-cff245a6509b/go.mod h1:FeLwcggjj3mMvU+oOTbSwawSJRM1uh48EjtB4UJZlP0=
@@ -264,8 +264,8 @@ golang.org/x/mod v0.1.1-0.20191105210325-c90efee705ee/go.mod h1:QqPTAvyqsEbceGzB
golang.org/x/mod v0.2.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.3.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.4.2/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.31.0 h1:HaW9xtz0+kOcWKwli0ZXy79Ix+UW/vOfmWI5QVd2tgI=
golang.org/x/mod v0.31.0/go.mod h1:43JraMp9cGx1Rx3AqioxrbrhNsLl2l/iNAvuBkrezpg=
golang.org/x/mod v0.30.0 h1:fDEXFVZ/fmCKProc/yAXXUijritrDzahmwwefnjoPFk=
golang.org/x/mod v0.30.0/go.mod h1:lAsf5O2EvJeSFMiBxXDki7sCgAxEUcZHXoXMKT4GJKc=
golang.org/x/net v0.0.0-20180724234803-3673e40ba225/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20180826012351-8a410e7b638d/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20190108225652-1e06a53dbb7e/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
@@ -278,8 +278,8 @@ golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81R
golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
golang.org/x/net v0.0.0-20210405180319-a5a99cb37ef4/go.mod h1:p54w0d4576C0XHj96bSt6lcn1PtDYWL6XObtHCRCNQM=
golang.org/x/net v0.0.0-20210614182718-04defd469f4e/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y=
golang.org/x/net v0.48.0 h1:zyQRTTrjc33Lhh0fBgT/H3oZq9WuvRR5gPC70xpDiQU=
golang.org/x/net v0.48.0/go.mod h1:+ndRgGjkh8FGtu1w1FGbEC31if4VrNVMuKTgcAAnQRY=
golang.org/x/net v0.46.0 h1:giFlY12I07fugqwPuWJi68oOnpfqFnJIJzaIIm2JVV4=
golang.org/x/net v0.46.0/go.mod h1:Q9BGdFy1y4nkUwiLvT5qtyhAnEHgnQ/zd8PfU6nc210=
golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
golang.org/x/oauth2 v0.0.0-20200107190931-bf48bf16ab8d/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
@@ -289,8 +289,8 @@ golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJ
golang.org/x/sync v0.0.0-20190911185100-cd5d95a43a6e/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20201020160332-67f06af15bc9/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20210220032951-036812b2e83c/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.19.0 h1:vV+1eWNmZ5geRlYjzm2adRgW2/mcpevXNg50YZtPCE4=
golang.org/x/sync v0.19.0/go.mod h1:9KTHXmSnoGruLpwFjVSX0lNNA75CykiMECbovNTZqGI=
golang.org/x/sync v0.17.0 h1:l60nONMj9l5drqw6jlhIELNv9I0A4OFgRsG9k2oT9Ug=
golang.org/x/sync v0.17.0/go.mod h1:9KTHXmSnoGruLpwFjVSX0lNNA75CykiMECbovNTZqGI=
golang.org/x/sys v0.0.0-20180830151530-49385e6e1522/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190312061237-fead79001313/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
@@ -306,17 +306,17 @@ golang.org/x/sys v0.0.0-20210510120138-977fb7262007/go.mod h1:oPkhp1MJrh7nUepCBc
golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.5.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.39.0 h1:CvCKL8MeisomCi6qNZ+wbb0DN9E5AATixKsvNtMoMFk=
golang.org/x/sys v0.39.0/go.mod h1:OgkHotnGiDImocRcuBABYBEXf8A9a87e/uXjp9XT3ks=
golang.org/x/sys v0.37.0 h1:fdNQudmxPjkdUTPnLn5mdQv7Zwvbvpaxqs831goi9kQ=
golang.org/x/sys v0.37.0/go.mod h1:OgkHotnGiDImocRcuBABYBEXf8A9a87e/uXjp9XT3ks=
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
golang.org/x/term v0.38.0 h1:PQ5pkm/rLO6HnxFR7N2lJHOZX6Kez5Y1gDSJla6jo7Q=
golang.org/x/term v0.38.0/go.mod h1:bSEAKrOT1W+VSu9TSCMtoGEOUcKxOKgl3LE5QEF/xVg=
golang.org/x/term v0.36.0 h1:zMPR+aF8gfksFprF/Nc/rd1wRS1EI6nDBGyWAvDzx2Q=
golang.org/x/term v0.36.0/go.mod h1:Qu394IJq6V6dCBRgwqshf3mPF85AqzYEzofzRdZkWss=
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.5/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.32.0 h1:ZD01bjUt1FQ9WJ0ClOL5vxgxOI/sVCNgX1YtKwcY0mU=
golang.org/x/text v0.32.0/go.mod h1:o/rUWzghvpD5TXrTIBuJU77MTaN0ljMWE47kxGJQ7jY=
golang.org/x/text v0.30.0 h1:yznKA/E9zq54KzlzBEAWn1NXSQ8DIp/NYMy88xJjl4k=
golang.org/x/text v0.30.0/go.mod h1:yDdHFIX9t+tORqspjENWgzaCVXgk0yYnYuSZ8UzzBVM=
golang.org/x/tools v0.0.0-20180525024113-a5b4c53f6e8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20190114222345-bf090417da8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
@@ -330,8 +330,8 @@ golang.org/x/tools v0.0.0-20200130002326-2f3ba24bd6e7/go.mod h1:TB2adYChydJhpapK
golang.org/x/tools v0.0.0-20200619180055-7c47624df98f/go.mod h1:EkVYQZoAsY45+roYkvgYkIh4xh/qjgUK9TdY2XT94GE=
golang.org/x/tools v0.0.0-20210106214847-113979e3529a/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
golang.org/x/tools v0.1.4/go.mod h1:o0xws9oXOQQZyjljx8fwUC0k7L1pTE6eaCbjGeHmOkk=
golang.org/x/tools v0.40.0 h1:yLkxfA+Qnul4cs9QA3KnlFu0lVmd8JJfoq+E41uSutA=
golang.org/x/tools v0.40.0/go.mod h1:Ik/tzLRlbscWpqqMRjyWYDisX8bG13FrdXp3o4Sr9lc=
golang.org/x/tools v0.38.0 h1:Hx2Xv8hISq8Lm16jvBZ2VQf+RLmbd7wVUsALibYI/IQ=
golang.org/x/tools v0.38.0/go.mod h1:yEsQ/d/YK8cjh0L6rZlY8tgtlKiBNTL14pGDJPJpYQs=
golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=

View File

@@ -0,0 +1,148 @@
//go:build integration
package integration
import (
"context"
"encoding/base64"
"fmt"
"strings"
"testing"
"time"
"github.com/ollama/ollama/api"
)
func TestImageGeneration(t *testing.T) {
skipUnderMinVRAM(t, 8)
type testCase struct {
imageGenModel string
visionModel string
prompt string
expectedWords []string
}
testCases := []testCase{
{
imageGenModel: "jmorgan/z-image-turbo",
visionModel: "llama3.2-vision",
prompt: "A cartoon style llama flying like a superhero through the air with clouds in the background",
expectedWords: []string{"llama", "flying", "cartoon", "cloud", "sky", "superhero", "air", "animal", "camelid"},
},
}
for _, tc := range testCases {
t.Run(fmt.Sprintf("%s->%s", tc.imageGenModel, tc.visionModel), func(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
// Pull both models
if err := PullIfMissing(ctx, client, tc.imageGenModel); err != nil {
t.Fatalf("failed to pull image gen model: %v", err)
}
if err := PullIfMissing(ctx, client, tc.visionModel); err != nil {
t.Fatalf("failed to pull vision model: %v", err)
}
// Generate the image
t.Logf("Generating image with prompt: %s", tc.prompt)
imageBase64, err := generateImage(ctx, client, tc.imageGenModel, tc.prompt)
if err != nil {
if strings.Contains(err.Error(), "image generation not available") {
t.Skip("Target system does not support image generation")
} else if strings.Contains(err.Error(), "executable file not found in") { // Windows pattern, not yet supported
t.Skip("Windows does not support image generation yet")
} else if strings.Contains(err.Error(), "CUDA driver version is insufficient") {
t.Skip("Driver is too old")
} else if strings.Contains(err.Error(), "insufficient memory for image generation") {
t.Skip("insufficient memory for image generation")
} else if strings.Contains(err.Error(), "error while loading shared libraries: libcuda.so.1") { // AMD GPU or CPU
t.Skip("CUDA GPU is not available")
} else if strings.Contains(err.Error(), "ollama-mlx: no such file or directory") {
// most likely linux arm - not supported yet
t.Skip("unsupported architecture")
}
t.Fatalf("failed to generate image: %v", err)
}
imageData, err := base64.StdEncoding.DecodeString(imageBase64)
if err != nil {
t.Fatalf("failed to decode image: %v", err)
}
t.Logf("Generated image: %d bytes", len(imageData))
// Preload vision model and check GPU loading
err = client.Generate(ctx, &api.GenerateRequest{Model: tc.visionModel}, func(response api.GenerateResponse) error { return nil })
if err != nil {
t.Fatalf("failed to load vision model: %v", err)
}
// Use vision model to describe the image
chatReq := api.ChatRequest{
Model: tc.visionModel,
Messages: []api.Message{
{
Role: "user",
Content: "Describe this image in detail. What is shown? What style is it? What is the main subject doing?",
Images: []api.ImageData{imageData},
},
},
Stream: &stream,
Options: map[string]any{
"seed": 42,
"temperature": 0.0,
},
}
// Verify the vision model's response contains expected keywords
response := DoChat(ctx, t, client, chatReq, tc.expectedWords, 240*time.Second, 30*time.Second)
if response != nil {
t.Logf("Vision model response: %s", response.Content)
// Additional detailed check for keywords
content := strings.ToLower(response.Content)
foundWords := []string{}
missingWords := []string{}
for _, word := range tc.expectedWords {
if strings.Contains(content, word) {
foundWords = append(foundWords, word)
} else {
missingWords = append(missingWords, word)
}
}
t.Logf("Found keywords: %v", foundWords)
if len(missingWords) > 0 {
t.Logf("Missing keywords (at least one was found so test passed): %v", missingWords)
}
}
})
}
}
// generateImage calls the Ollama API to generate an image and returns the base64 image data
func generateImage(ctx context.Context, client *api.Client, model, prompt string) (string, error) {
var imageBase64 string
err := client.Generate(ctx, &api.GenerateRequest{
Model: model,
Prompt: prompt,
}, func(resp api.GenerateResponse) error {
if resp.Image != "" {
imageBase64 = resp.Image
}
return nil
})
if err != nil {
return "", fmt.Errorf("failed to generate image: %w", err)
}
if imageBase64 == "" {
return "", fmt.Errorf("no image data in response")
}
return imageBase64, nil
}

View File

@@ -131,7 +131,7 @@ func TestAPIToolCalling(t *testing.T) {
t.Errorf("unexpected tool called: got %q want %q", lastToolCall.Function.Name, "get_weather")
}
if _, ok := lastToolCall.Function.Arguments["location"]; !ok {
if _, ok := lastToolCall.Function.Arguments.Get("location"); !ok {
t.Errorf("expected tool arguments to include 'location', got: %s", lastToolCall.Function.Arguments.String())
}
case <-ctx.Done():

View File

@@ -38,6 +38,7 @@ var (
// Note: add newer models at the top of the list to test them first
ollamaEngineChatModels = []string{
"lfm2.5-thinking",
"ministral-3",
"qwen3-coder:30b",
"gpt-oss:20b",
@@ -143,6 +144,7 @@ var (
"granite3.3",
"hermes3",
"internlm2",
"lfm2.5-thinking",
"llama-guard3",
"llama-pro",
"llama2-chinese",
@@ -263,6 +265,7 @@ var (
"snowflake-arctic-embed2",
}
libraryToolsModels = []string{
"lfm2.5-thinking",
"qwen3-vl",
"gpt-oss:20b",
"gpt-oss:120b",

View File

@@ -0,0 +1,309 @@
From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
From: nobody <>
Date: Sat, 24 Jan 2026 02:31:01 +0000
Subject: [PATCH] ggml: enable MLA flash attention for GLM-4.7-flash
Add support for gqa_ratio 4 in MLA flash attention kernels. GLM-4.7-flash
uses head size 576 with gqa_ratio 4, which was previously only supported
for gqa_ratio 16 (DeepSeek).
Metal changes:
- Enable head size 576 for flash attention
- Increase simdgroups to 8 for large heads (>=512)
- Add case 8 kernel dispatch for 8 simdgroups
CUDA changes:
- Add gqa_ratio 4 support for head 576/512
- Add tile configs for (576, 512, 4) and (576, 512, 8)
- Add MMA config cases for ncols 4
- Add template instances for ncols2=4
- Fix nbatch_fa values in nvidia_fp32 config (32->64)
---
ggml/src/ggml-cuda/fattn-mma-f16.cuh | 40 +++++++++++++++----
ggml/src/ggml-cuda/fattn-tile.cuh | 16 ++++++++
ggml/src/ggml-cuda/fattn.cu | 12 ++++--
...ttn-mma-f16-instance-ncols1_16-ncols2_4.cu | 1 +
...attn-mma-f16-instance-ncols1_2-ncols2_4.cu | 1 +
...attn-mma-f16-instance-ncols1_4-ncols2_4.cu | 1 +
...attn-mma-f16-instance-ncols1_8-ncols2_4.cu | 1 +
ggml/src/ggml-metal/ggml-metal-device.m | 8 +---
ggml/src/ggml-metal/ggml-metal-ops.cpp | 2 +-
ggml/src/ggml-metal/ggml-metal.metal | 1 +
10 files changed, 64 insertions(+), 19 deletions(-)
diff --git a/ggml/src/ggml-cuda/fattn-mma-f16.cuh b/ggml/src/ggml-cuda/fattn-mma-f16.cuh
index 7bd1044c1..3dea2205e 100644
--- a/ggml/src/ggml-cuda/fattn-mma-f16.cuh
+++ b/ggml/src/ggml-cuda/fattn-mma-f16.cuh
@@ -66,7 +66,8 @@ static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_co
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 32, 128, 2, 32, 128, 128, 128, 2, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 64, 128, 2, 32, 128, 128, 128, 2, true);
- GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 128, 1, false);
+ GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 4, 64, 4, 32, 288, 256, 128, 1, false);
+ GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 128, 1, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 288, 256, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 128, 1, false);
@@ -80,7 +81,8 @@ static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_co
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 32, 128, 2, 64, 128, 128, 64, 2, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 64, 128, 2, 64, 128, 128, 64, 2, true);
- GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 96, 64, 128, 1, false);
+ GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 4, 64, 4, 32, 96, 64, 128, 1, false);
+ GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 96, 64, 128, 1, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 96, 64, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 128, 1, false);
@@ -89,7 +91,8 @@ static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_co
}
static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_config_volta(const int DKQ, const int DV, const int ncols) {
- GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 64, 1, false);
+ GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 4, 64, 4, 32, 288, 256, 64, 1, false);
+ GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 64, 1, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 288, 256, 64, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 64, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 64, 1, false);
@@ -397,7 +400,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter(
constexpr int ncols = ncols1 * ncols2;
constexpr int cols_per_warp = T_B_KQ::I;
constexpr int cols_per_thread = 2; // This is specifically KQ columns, Volta only has a single VKQ column.
- constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column.
+ constexpr int np = cols_per_warp > ncols ? nwarps : nwarps * cols_per_warp/ncols; // Number of parallel CUDA warps per Q column.
constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa(DKQ, DV, ncols);
constexpr int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2(DKQ, DV, ncols);
constexpr int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2(DKQ, DV, ncols);
@@ -467,7 +470,6 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter(
}
}
} else {
- static_assert(cols_per_warp != 8, "cols_per_warp == 8 not implemented");
#pragma unroll
for (int k_KQ_0 = k0_start; k_KQ_0 < k0_stop; k_KQ_0 += T_A_KQ::J) {
load_ldmatrix(Q_B[0], tile_Q + (threadIdx.y / np)*(T_B_KQ::I*stride_tile_Q) + k_KQ_0, stride_tile_Q);
@@ -479,8 +481,18 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter(
T_A_KQ K_A;
load_ldmatrix(K_A, tile_K + i_KQ_0*stride_tile_K + (k_KQ_0 - k0_start), stride_tile_K);
- // Wide version of KQ_C is column-major => swap A and B.
- mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], Q_B[0], K_A);
+ if constexpr (cols_per_warp == 8) {
+ mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], K_A, Q_B[0]);
+ } else {
+ // Wide version of KQ_C is column-major
+#if defined(AMD_WMMA_AVAILABLE)
+ // RDNA matrix C is column-major.
+ mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], K_A, Q_B[0]);
+#else
+ // swap A and B for CUDA.
+ mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], Q_B[0], K_A);
+#endif // defined(AMD_WMMA_AVAILABLE)
+ }
}
}
}
@@ -841,7 +853,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile(
constexpr int cols_per_warp = T_B_KQ::I;
constexpr int cols_per_thread = 2; // This is specifically KQ columns, Volta only has a single VKQ column.
- constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column.
+ constexpr int np = cols_per_warp > ncols ? nwarps : nwarps * cols_per_warp/ncols; // Number of parallel CUDA warps per Q column.
constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa (DKQ, DV, ncols);
constexpr int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2 (DKQ, DV, ncols);
constexpr int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2 (DKQ, DV, ncols);
@@ -1353,6 +1365,13 @@ static __global__ void flash_attn_ext_f16(
NO_DEVICE_CODE;
return;
}
+#ifdef VOLTA_MMA_AVAILABLE
+ if (ncols1*ncols2 < 32) {
+ NO_DEVICE_CODE;
+ return;
+ }
+#endif // VOLTA_MMA_AVAILABLE
+
#if __CUDA_ARCH__ == GGML_CUDA_CC_TURING
if (ncols1*ncols2 > 32) {
NO_DEVICE_CODE;
@@ -1585,3 +1604,8 @@ DECL_FATTN_MMA_F16_CASE_ALL_NCOLS2(256, 256, 64)
extern DECL_FATTN_MMA_F16_CASE(576, 512, 1, 16);
extern DECL_FATTN_MMA_F16_CASE(576, 512, 2, 16);
extern DECL_FATTN_MMA_F16_CASE(576, 512, 4, 16);
+
+// For GLM 4.7 Flash
+extern DECL_FATTN_MMA_F16_CASE(576, 512, 4, 4);
+extern DECL_FATTN_MMA_F16_CASE(576, 512, 8, 4);
+extern DECL_FATTN_MMA_F16_CASE(576, 512, 16, 4);
diff --git a/ggml/src/ggml-cuda/fattn-tile.cuh b/ggml/src/ggml-cuda/fattn-tile.cuh
index 7c4d6fe67..371be7442 100644
--- a/ggml/src/ggml-cuda/fattn-tile.cuh
+++ b/ggml/src/ggml-cuda/fattn-tile.cuh
@@ -68,6 +68,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_nv
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 2, 64, 64)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 64, 64)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 2, 64, 64)
return 0;
@@ -122,6 +124,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_nv
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 2, 32, 128)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 2, 32, 64)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 32, 64)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 32, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 2, 32, 64)
return 0;
@@ -183,6 +187,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_am
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 2, 32, 128)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 2, 32, 128)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 64, 64)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 32, 512, 1, 128, 64)
@@ -245,6 +251,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_am
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 5, 32, 256)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 3, 64, 128)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 64, 64)
+ GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 4, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 32, 256, 2, 128, 64)
@@ -1187,6 +1195,14 @@ static void launch_fattn_tile_switch_ncols2(ggml_backend_cuda_context & ctx, ggm
launch_fattn_tile_switch_ncols1<DKQ, DV, 16, use_logit_softcap>(ctx, dst);
return;
}
+ if (use_gqa_opt && gqa_ratio % 8 == 0) {
+ launch_fattn_tile_switch_ncols1<DKQ, DV, 8, use_logit_softcap>(ctx, dst);
+ return;
+ }
+ if (use_gqa_opt && gqa_ratio % 4 == 0) {
+ launch_fattn_tile_switch_ncols1<DKQ, DV, 4, use_logit_softcap>(ctx, dst);
+ return;
+ }
}
if constexpr (DV <= 256) {
diff --git a/ggml/src/ggml-cuda/fattn.cu b/ggml/src/ggml-cuda/fattn.cu
index 015540666..1693479cb 100644
--- a/ggml/src/ggml-cuda/fattn.cu
+++ b/ggml/src/ggml-cuda/fattn.cu
@@ -111,7 +111,7 @@ static void ggml_cuda_flash_attn_ext_mma_f16(ggml_backend_cuda_context & ctx, gg
ggml_cuda_flash_attn_ext_mma_f16_switch_ncols2<256, 256>(ctx, dst);
break;
case 576: {
- // For Deepseek, go straight to the ncols1 switch to avoid compiling unnecessary kernels.
+ // For Deepseek/GLM4, go straight to the ncols1 switch to avoid compiling unnecessary kernels.
GGML_ASSERT(V->ne[0] == 512);
float max_bias = 0.0f;
memcpy(&max_bias, (const float *) KQV->op_params + 1, sizeof(float));
@@ -121,8 +121,12 @@ static void ggml_cuda_flash_attn_ext_mma_f16(ggml_backend_cuda_context & ctx, gg
GGML_ASSERT(Q->ne[2] % K->ne[2] == 0);
const int gqa_ratio = Q->ne[2] / K->ne[2];
- GGML_ASSERT(gqa_ratio % 16 == 0);
- ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1<576, 512, 16>(ctx, dst);
+ GGML_ASSERT(gqa_ratio % 4 == 0);
+ if (gqa_ratio % 16 == 0) {
+ ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1<576, 512, 16>(ctx, dst);
+ } else {
+ ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1<576, 512, 4>(ctx, dst);
+ }
} break;
default:
GGML_ABORT("fatal error");
@@ -251,7 +255,7 @@ static best_fattn_kernel ggml_cuda_get_best_fattn_kernel(const int device, const
if (V->ne[0] != 512) {
return BEST_FATTN_KERNEL_NONE;
}
- if (!gqa_opt_applies || gqa_ratio % 16 != 0) {
+ if (!gqa_opt_applies || gqa_ratio % 4 != 0) {
return BEST_FATTN_KERNEL_NONE;
}
break;
diff --git a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_16-ncols2_4.cu b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_16-ncols2_4.cu
index 2074e954a..517993cb0 100644
--- a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_16-ncols2_4.cu
+++ b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_16-ncols2_4.cu
@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 16, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 16, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 16, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 16, 4);
+DECL_FATTN_MMA_F16_CASE(576, 512, 16, 4);
diff --git a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_2-ncols2_4.cu b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_2-ncols2_4.cu
index 24c64cf00..97b19c67a 100644
--- a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_2-ncols2_4.cu
+++ b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_2-ncols2_4.cu
@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 2, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 2, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 2, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 2, 4);
+DECL_FATTN_MMA_F16_CASE(576, 512, 2, 4);
diff --git a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_4-ncols2_4.cu b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_4-ncols2_4.cu
index 1ada657f1..989626dfa 100644
--- a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_4-ncols2_4.cu
+++ b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_4-ncols2_4.cu
@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 4, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 4, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 4, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 4, 4);
+DECL_FATTN_MMA_F16_CASE(576, 512, 4, 4);
diff --git a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_8-ncols2_4.cu b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_8-ncols2_4.cu
index 86d4ffae2..173de7aac 100644
--- a/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_8-ncols2_4.cu
+++ b/ggml/src/ggml-cuda/template-instances/fattn-mma-f16-instance-ncols1_8-ncols2_4.cu
@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 8, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 8, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 8, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 8, 4);
+DECL_FATTN_MMA_F16_CASE(576, 512, 8, 4);
diff --git a/ggml/src/ggml-metal/ggml-metal-device.m b/ggml/src/ggml-metal/ggml-metal-device.m
index f24270bb1..7b5ee968c 100644
--- a/ggml/src/ggml-metal/ggml-metal-device.m
+++ b/ggml/src/ggml-metal/ggml-metal-device.m
@@ -1071,12 +1071,8 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
op->src[0]->ne[0] != 112 &&
op->src[0]->ne[0] != 128 &&
op->src[0]->ne[0] != 192 &&
- op->src[0]->ne[0] != 256) {
- return false;
- }
- if (op->src[0]->ne[0] == 576) {
- // DeepSeek sizes
- // TODO: disabled for now, until optmized
+ op->src[0]->ne[0] != 256 &&
+ op->src[0]->ne[0] != 576) {
return false;
}
if (op->src[1]->type != op->src[2]->type) {
diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp
index e99c1763f..80864f303 100644
--- a/ggml/src/ggml-metal/ggml-metal-ops.cpp
+++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp
@@ -2456,7 +2456,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
// simdgroups per threadgroup (a.k.a. warps)
//nsg = ne01 <= nqptg ? MAX(4, MIN(nsgmax, MIN(ne11/ncpsg, (int64_t) pipeline.maxTotalThreadsPerThreadgroup/32))) : 4;
- int32_t nsg = 4;
+ int32_t nsg = ne00 >= 512 ? 8 : 4;
const size_t smem = FATTN_SMEM(nsg);
diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal
index c98d269d1..d33c16079 100644
--- a/ggml/src/ggml-metal/ggml-metal.metal
+++ b/ggml/src/ggml-metal/ggml-metal.metal
@@ -6166,6 +6166,7 @@ kernel void kernel_flash_attn_ext(
//case 1: kernel_flash_attn_ext_impl<FWD_TMPL, 1>(FWD_ARGS); break;
//case 2: kernel_flash_attn_ext_impl<FWD_TMPL, 2>(FWD_ARGS); break;
case 4: kernel_flash_attn_ext_impl<FWD_TMPL, 4>(FWD_ARGS); break;
+ case 8: kernel_flash_attn_ext_impl<FWD_TMPL, 8>(FWD_ARGS); break;
}
#undef FWD_TMPL
#undef FWD_ARGS

View File

@@ -1464,6 +1464,12 @@ type CompletionRequest struct {
// TopLogprobs specifies the number of most likely alternative tokens to return (0-20)
TopLogprobs int
// Image generation fields
Width int32 `json:"width,omitempty"`
Height int32 `json:"height,omitempty"`
Steps int32 `json:"steps,omitempty"`
Seed int64 `json:"seed,omitempty"`
}
// DoneReason represents the reason why a completion response is done
@@ -1512,6 +1518,15 @@ type CompletionResponse struct {
// Logprobs contains log probability information if requested
Logprobs []Logprob `json:"logprobs,omitempty"`
// Image contains base64-encoded image data for image generation
Image string `json:"image,omitempty"`
// Step is the current step in image generation
Step int `json:"step,omitempty"`
// TotalSteps is the total number of steps for image generation
TotalSteps int `json:"total_steps,omitempty"`
}
func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {

View File

@@ -1,4 +1,4 @@
package server
package manifest
import (
"crypto/sha256"
@@ -14,7 +14,7 @@ type Layer struct {
Size int64 `json:"size"`
From string `json:"from,omitempty"`
Name string `json:"name,omitempty"` // tensor name, e.g., "text_encoder/model.embed_tokens.weight"
status string
Status string `json:"-"`
}
const (
@@ -22,7 +22,7 @@ const (
)
func NewLayer(r io.Reader, mediatype string) (Layer, error) {
blobs, err := GetBlobsPath("")
blobs, err := BlobsPath("")
if err != nil {
return Layer{}, err
}
@@ -45,7 +45,7 @@ func NewLayer(r io.Reader, mediatype string) (Layer, error) {
}
digest := fmt.Sprintf("sha256:%x", sha256sum.Sum(nil))
blob, err := GetBlobsPath(digest)
blob, err := BlobsPath(digest)
if err != nil {
return Layer{}, err
}
@@ -65,7 +65,7 @@ func NewLayer(r io.Reader, mediatype string) (Layer, error) {
MediaType: mediatype,
Digest: digest,
Size: n,
status: fmt.Sprintf("%s %s", status, digest),
Status: fmt.Sprintf("%s %s", status, digest),
}, nil
}
@@ -74,7 +74,7 @@ func NewLayerFromLayer(digest, mediatype, from string) (Layer, error) {
return Layer{}, errors.New("creating new layer from layer with empty digest")
}
blob, err := GetBlobsPath(digest)
blob, err := BlobsPath(digest)
if err != nil {
return Layer{}, err
}
@@ -89,7 +89,7 @@ func NewLayerFromLayer(digest, mediatype, from string) (Layer, error) {
Digest: digest,
Size: fi.Size(),
From: from,
status: fmt.Sprintf("using existing layer %s", digest),
Status: fmt.Sprintf("using existing layer %s", digest),
}, nil
}
@@ -98,7 +98,7 @@ func (l *Layer) Open() (io.ReadSeekCloser, error) {
return nil, errors.New("opening layer with empty digest")
}
blob, err := GetBlobsPath(l.Digest)
blob, err := BlobsPath(l.Digest)
if err != nil {
return nil, err
}
@@ -126,7 +126,7 @@ func (l *Layer) Remove() error {
}
}
blob, err := GetBlobsPath(l.Digest)
blob, err := BlobsPath(l.Digest)
if err != nil {
return err
}

View File

@@ -1,10 +1,9 @@
package server
package manifest
import (
"crypto/sha256"
"encoding/hex"
"encoding/json"
"errors"
"fmt"
"io"
"log/slog"
@@ -33,12 +32,38 @@ func (m *Manifest) Size() (size int64) {
return
}
func (m *Manifest) Digest() string {
return m.digest
}
func (m *Manifest) FileInfo() os.FileInfo {
return m.fi
}
// ReadConfigJSON reads and unmarshals a config layer as JSON.
func (m *Manifest) ReadConfigJSON(configPath string, v any) error {
for _, layer := range m.Layers {
if layer.MediaType == "application/vnd.ollama.image.json" && layer.Name == configPath {
blobPath, err := BlobsPath(layer.Digest)
if err != nil {
return err
}
data, err := os.ReadFile(blobPath)
if err != nil {
return err
}
return json.Unmarshal(data, v)
}
}
return fmt.Errorf("config %q not found in manifest", configPath)
}
func (m *Manifest) Remove() error {
if err := os.Remove(m.filepath); err != nil {
return err
}
manifests, err := GetManifestPath()
manifests, err := Path()
if err != nil {
return err
}
@@ -47,16 +72,40 @@ func (m *Manifest) Remove() error {
}
func (m *Manifest) RemoveLayers() error {
for _, layer := range append(m.Layers, m.Config) {
if layer.Digest != "" {
if err := layer.Remove(); errors.Is(err, os.ErrNotExist) {
slog.Debug("layer does not exist", "digest", layer.Digest)
} else if err != nil {
return err
ms, err := Manifests(true)
if err != nil {
return err
}
// Build set of digests still in use by other manifests
inUse := make(map[string]struct{})
for _, other := range ms {
for _, layer := range append(other.Layers, other.Config) {
if layer.Digest != "" {
inUse[layer.Digest] = struct{}{}
}
}
}
// Remove layers not used by any other manifest
for _, layer := range append(m.Layers, m.Config) {
if layer.Digest == "" {
continue
}
if _, used := inUse[layer.Digest]; used {
continue
}
blob, err := BlobsPath(layer.Digest)
if err != nil {
return err
}
if err := os.Remove(blob); os.IsNotExist(err) {
slog.Debug("layer does not exist", "digest", layer.Digest)
} else if err != nil {
return err
}
}
return nil
}
@@ -65,7 +114,7 @@ func ParseNamedManifest(n model.Name) (*Manifest, error) {
return nil, model.Unqualified(n)
}
manifests, err := GetManifestPath()
manifests, err := Path()
if err != nil {
return nil, err
}
@@ -97,7 +146,7 @@ func ParseNamedManifest(n model.Name) (*Manifest, error) {
}
func WriteManifest(name model.Name, config Layer, layers []Layer) error {
manifests, err := GetManifestPath()
manifests, err := Path()
if err != nil {
return err
}
@@ -124,7 +173,7 @@ func WriteManifest(name model.Name, config Layer, layers []Layer) error {
}
func Manifests(continueOnError bool) (map[model.Name]*Manifest, error) {
manifests, err := GetManifestPath()
manifests, err := Path()
if err != nil {
return nil, err
}

View File

@@ -1,4 +1,4 @@
package server
package manifest
import (
"encoding/json"

95
manifest/paths.go Normal file
View File

@@ -0,0 +1,95 @@
package manifest
import (
"errors"
"fmt"
"os"
"path/filepath"
"regexp"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/types/model"
)
var ErrInvalidDigestFormat = errors.New("invalid digest format")
func Path() (string, error) {
path := filepath.Join(envconfig.Models(), "manifests")
if err := os.MkdirAll(path, 0o755); err != nil {
return "", fmt.Errorf("%w: ensure path elements are traversable", err)
}
return path, nil
}
// PathForName returns the path to the manifest file for a specific model name.
func PathForName(n model.Name) (string, error) {
if !n.IsValid() {
return "", os.ErrNotExist
}
manifests, err := Path()
if err != nil {
return "", err
}
return filepath.Join(manifests, n.Filepath()), nil
}
func BlobsPath(digest string) (string, error) {
// only accept actual sha256 digests
pattern := "^sha256[:-][0-9a-fA-F]{64}$"
re := regexp.MustCompile(pattern)
if digest != "" && !re.MatchString(digest) {
return "", ErrInvalidDigestFormat
}
digest = strings.ReplaceAll(digest, ":", "-")
path := filepath.Join(envconfig.Models(), "blobs", digest)
dirPath := filepath.Dir(path)
if digest == "" {
dirPath = path
}
if err := os.MkdirAll(dirPath, 0o755); err != nil {
return "", fmt.Errorf("%w: ensure path elements are traversable", err)
}
return path, nil
}
// PruneDirectory removes empty directories recursively.
func PruneDirectory(path string) error {
info, err := os.Lstat(path)
if err != nil {
return err
}
if info.IsDir() && info.Mode()&os.ModeSymlink == 0 {
entries, err := os.ReadDir(path)
if err != nil {
return err
}
for _, entry := range entries {
if err := PruneDirectory(filepath.Join(path, entry.Name())); err != nil {
return err
}
}
entries, err = os.ReadDir(path)
if err != nil {
return err
}
if len(entries) > 0 {
return nil
}
return os.Remove(path)
}
return nil
}

View File

@@ -118,6 +118,9 @@ func AnthropicMessagesMiddleware() gin.HandlerFunc {
return
}
// Set think to nil when being used with Anthropic API to connect to tools like claude code
c.Set("relax_thinking", true)
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(chatReq); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, anthropic.NewError(http.StatusInternalServerError, err.Error()))

View File

@@ -582,3 +582,26 @@ func TestAnthropicWriter_ErrorFromRoutes(t *testing.T) {
})
}
}
func TestAnthropicMessagesMiddleware_SetsRelaxThinkingFlag(t *testing.T) {
gin.SetMode(gin.TestMode)
var flagSet bool
router := gin.New()
router.Use(AnthropicMessagesMiddleware())
router.POST("/v1/messages", func(c *gin.Context) {
_, flagSet = c.Get("relax_thinking")
c.Status(http.StatusOK)
})
body := `{"model": "test-model", "max_tokens": 100, "messages": [{"role": "user", "content": "Hi"}]}`
req, _ := http.NewRequest(http.MethodPost, "/v1/messages", strings.NewReader(body))
req.Header.Set("Content-Type", "application/json")
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if !flagSet {
t.Error("expected relax_thinking flag to be set in context")
}
}

View File

@@ -8,6 +8,7 @@ import (
"math/rand"
"net/http"
"strings"
"time"
"github.com/gin-gonic/gin"
@@ -441,6 +442,7 @@ type ResponsesWriter struct {
stream bool
responseID string
itemID string
request openai.ResponsesRequest
}
func (w *ResponsesWriter) writeEvent(eventType string, data any) error {
@@ -478,7 +480,9 @@ func (w *ResponsesWriter) writeResponse(data []byte) (int, error) {
// Non-streaming response
w.ResponseWriter.Header().Set("Content-Type", "application/json")
response := openai.ToResponse(w.model, w.responseID, w.itemID, chatResponse)
response := openai.ToResponse(w.model, w.responseID, w.itemID, chatResponse, w.request)
completedAt := time.Now().Unix()
response.CompletedAt = &completedAt
return len(data), json.NewEncoder(w.ResponseWriter).Encode(response)
}
@@ -523,11 +527,12 @@ func ResponsesMiddleware() gin.HandlerFunc {
w := &ResponsesWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
converter: openai.NewResponsesStreamConverter(responseID, itemID, req.Model),
converter: openai.NewResponsesStreamConverter(responseID, itemID, req.Model, req),
model: req.Model,
stream: streamRequested,
responseID: responseID,
itemID: itemID,
request: req,
}
// Set headers based on streaming mode
@@ -541,3 +546,112 @@ func ResponsesMiddleware() gin.HandlerFunc {
c.Next()
}
}
type ImageWriter struct {
BaseWriter
}
func (w *ImageWriter) writeResponse(data []byte) (int, error) {
var generateResponse api.GenerateResponse
if err := json.Unmarshal(data, &generateResponse); err != nil {
return 0, err
}
// Only write response when done with image
if generateResponse.Done && generateResponse.Image != "" {
w.ResponseWriter.Header().Set("Content-Type", "application/json")
return len(data), json.NewEncoder(w.ResponseWriter).Encode(openai.ToImageGenerationResponse(generateResponse))
}
return len(data), nil
}
func (w *ImageWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(data)
}
return w.writeResponse(data)
}
func ImageGenerationsMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req openai.ImageGenerationRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, err.Error()))
return
}
if req.Prompt == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, "prompt is required"))
return
}
if req.Model == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, "model is required"))
return
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(openai.FromImageGenerationRequest(req)); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, openai.NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &ImageWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
}
c.Writer = w
c.Next()
}
}
func ImageEditsMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req openai.ImageEditRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, err.Error()))
return
}
if req.Prompt == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, "prompt is required"))
return
}
if req.Model == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, "model is required"))
return
}
if req.Image == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, "image is required"))
return
}
genReq, err := openai.FromImageEditRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, err.Error()))
return
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(genReq); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, openai.NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &ImageWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
}
c.Writer = w
c.Next()
}
}

View File

@@ -961,3 +961,280 @@ func TestRetrieveMiddleware(t *testing.T) {
}
}
}
func TestImageGenerationsMiddleware(t *testing.T) {
type testCase struct {
name string
body string
req api.GenerateRequest
err openai.ErrorResponse
}
var capturedRequest *api.GenerateRequest
testCases := []testCase{
{
name: "image generation basic",
body: `{
"model": "test-model",
"prompt": "a beautiful sunset"
}`,
req: api.GenerateRequest{
Model: "test-model",
Prompt: "a beautiful sunset",
},
},
{
name: "image generation with size",
body: `{
"model": "test-model",
"prompt": "a beautiful sunset",
"size": "512x768"
}`,
req: api.GenerateRequest{
Model: "test-model",
Prompt: "a beautiful sunset",
Width: 512,
Height: 768,
},
},
{
name: "image generation missing prompt",
body: `{
"model": "test-model"
}`,
err: openai.ErrorResponse{
Error: openai.Error{
Message: "prompt is required",
Type: "invalid_request_error",
},
},
},
{
name: "image generation missing model",
body: `{
"prompt": "a beautiful sunset"
}`,
err: openai.ErrorResponse{
Error: openai.Error{
Message: "model is required",
Type: "invalid_request_error",
},
},
},
}
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(ImageGenerationsMiddleware(), captureRequestMiddleware(&capturedRequest))
router.Handle(http.MethodPost, "/api/generate", endpoint)
for _, tc := range testCases {
t.Run(tc.name, func(t *testing.T) {
req, _ := http.NewRequest(http.MethodPost, "/api/generate", strings.NewReader(tc.body))
req.Header.Set("Content-Type", "application/json")
defer func() { capturedRequest = nil }()
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if tc.err.Error.Message != "" {
var errResp openai.ErrorResponse
if err := json.Unmarshal(resp.Body.Bytes(), &errResp); err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(tc.err, errResp); diff != "" {
t.Fatalf("errors did not match:\n%s", diff)
}
return
}
if resp.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", resp.Code, resp.Body.String())
}
if diff := cmp.Diff(&tc.req, capturedRequest); diff != "" {
t.Fatalf("requests did not match:\n%s", diff)
}
})
}
}
func TestImageWriterResponse(t *testing.T) {
gin.SetMode(gin.TestMode)
// Test that ImageWriter transforms GenerateResponse to OpenAI format
endpoint := func(c *gin.Context) {
resp := api.GenerateResponse{
Model: "test-model",
CreatedAt: time.Unix(1234567890, 0).UTC(),
Done: true,
Image: "dGVzdC1pbWFnZS1kYXRh", // base64 of "test-image-data"
}
data, _ := json.Marshal(resp)
c.Writer.Write(append(data, '\n'))
}
router := gin.New()
router.Use(ImageGenerationsMiddleware())
router.Handle(http.MethodPost, "/api/generate", endpoint)
body := `{"model": "test-model", "prompt": "test"}`
req, _ := http.NewRequest(http.MethodPost, "/api/generate", strings.NewReader(body))
req.Header.Set("Content-Type", "application/json")
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if resp.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", resp.Code, resp.Body.String())
}
var imageResp openai.ImageGenerationResponse
if err := json.Unmarshal(resp.Body.Bytes(), &imageResp); err != nil {
t.Fatalf("failed to unmarshal response: %v", err)
}
if imageResp.Created != 1234567890 {
t.Errorf("expected created 1234567890, got %d", imageResp.Created)
}
if len(imageResp.Data) != 1 {
t.Fatalf("expected 1 image, got %d", len(imageResp.Data))
}
if imageResp.Data[0].B64JSON != "dGVzdC1pbWFnZS1kYXRh" {
t.Errorf("expected image data 'dGVzdC1pbWFnZS1kYXRh', got %s", imageResp.Data[0].B64JSON)
}
}
func TestImageEditsMiddleware(t *testing.T) {
type testCase struct {
name string
body string
req api.GenerateRequest
err openai.ErrorResponse
}
var capturedRequest *api.GenerateRequest
// Base64-encoded test image (1x1 pixel PNG)
testImage := "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII="
decodedImage, _ := base64.StdEncoding.DecodeString("iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=")
testCases := []testCase{
{
name: "image edit basic",
body: `{
"model": "test-model",
"prompt": "make it blue",
"image": "` + testImage + `"
}`,
req: api.GenerateRequest{
Model: "test-model",
Prompt: "make it blue",
Images: []api.ImageData{decodedImage},
},
},
{
name: "image edit with size",
body: `{
"model": "test-model",
"prompt": "make it blue",
"image": "` + testImage + `",
"size": "512x768"
}`,
req: api.GenerateRequest{
Model: "test-model",
Prompt: "make it blue",
Images: []api.ImageData{decodedImage},
Width: 512,
Height: 768,
},
},
{
name: "image edit missing prompt",
body: `{
"model": "test-model",
"image": "` + testImage + `"
}`,
err: openai.ErrorResponse{
Error: openai.Error{
Message: "prompt is required",
Type: "invalid_request_error",
},
},
},
{
name: "image edit missing model",
body: `{
"prompt": "make it blue",
"image": "` + testImage + `"
}`,
err: openai.ErrorResponse{
Error: openai.Error{
Message: "model is required",
Type: "invalid_request_error",
},
},
},
{
name: "image edit missing image",
body: `{
"model": "test-model",
"prompt": "make it blue"
}`,
err: openai.ErrorResponse{
Error: openai.Error{
Message: "image is required",
Type: "invalid_request_error",
},
},
},
}
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(ImageEditsMiddleware(), captureRequestMiddleware(&capturedRequest))
router.Handle(http.MethodPost, "/api/generate", endpoint)
for _, tc := range testCases {
t.Run(tc.name, func(t *testing.T) {
req, _ := http.NewRequest(http.MethodPost, "/api/generate", strings.NewReader(tc.body))
req.Header.Set("Content-Type", "application/json")
defer func() { capturedRequest = nil }()
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if tc.err.Error.Message != "" {
var errResp openai.ErrorResponse
if err := json.Unmarshal(resp.Body.Bytes(), &errResp); err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(tc.err, errResp); diff != "" {
t.Fatalf("errors did not match:\n%s", diff)
}
return
}
if resp.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", resp.Code, resp.Body.String())
}
if diff := cmp.Diff(&tc.req, capturedRequest); diff != "" {
t.Fatalf("requests did not match:\n%s", diff)
}
})
}
}

View File

@@ -162,6 +162,7 @@ type Tensor interface {
AvgPool2D(ctx Context, k, s int, p float32) Tensor
Conv2D(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
Conv3D(ctx Context, weight Tensor, c, s0, s1, s2, p0, p1, p2, d0, d1, d2 int) Tensor
SSMConv(ctx Context, kernel Tensor) Tensor
IM2Col(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor

View File

@@ -1641,6 +1641,13 @@ func (t *Tensor) Conv3D(ctx ml.Context, t2 ml.Tensor, c, s0, s1, s2, p0, p1, p2,
return tt
}
func (t *Tensor) SSMConv(ctx ml.Context, kernel ml.Tensor) ml.Tensor {
return &Tensor{
b: t.b,
t: C.ggml_ssm_conv(ctx.(*Context).ctx, t.t, kernel.(*Tensor).t),
}
}
func (t *Tensor) AvgPool2D(ctx ml.Context, k, s int, p float32) ml.Tensor {
return &Tensor{
b: t.b,

View File

@@ -66,7 +66,8 @@ static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_co
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 32, 128, 2, 32, 128, 128, 128, 2, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 64, 128, 2, 32, 128, 128, 128, 2, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 4, 64, 4, 32, 288, 256, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 128, 1, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 288, 256, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 128, 1, false);
@@ -80,7 +81,8 @@ static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_co
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 32, 128, 2, 64, 128, 128, 64, 2, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 64, 128, 2, 64, 128, 128, 64, 2, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 96, 64, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 4, 64, 4, 32, 96, 64, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 96, 64, 128, 1, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 96, 64, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 128, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 128, 1, false);
@@ -89,7 +91,8 @@ static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_co
}
static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_config_volta(const int DKQ, const int DV, const int ncols) {
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 64, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 4, 64, 4, 32, 288, 256, 64, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 64, 1, true);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 288, 256, 64, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 64, 1, false);
GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 64, 1, false);
@@ -397,7 +400,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter(
constexpr int ncols = ncols1 * ncols2;
constexpr int cols_per_warp = T_B_KQ::I;
constexpr int cols_per_thread = 2; // This is specifically KQ columns, Volta only has a single VKQ column.
constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column.
constexpr int np = cols_per_warp > ncols ? nwarps : nwarps * cols_per_warp/ncols; // Number of parallel CUDA warps per Q column.
constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa(DKQ, DV, ncols);
constexpr int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2(DKQ, DV, ncols);
constexpr int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2(DKQ, DV, ncols);
@@ -467,7 +470,6 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter(
}
}
} else {
static_assert(cols_per_warp != 8, "cols_per_warp == 8 not implemented");
#pragma unroll
for (int k_KQ_0 = k0_start; k_KQ_0 < k0_stop; k_KQ_0 += T_A_KQ::J) {
load_ldmatrix(Q_B[0], tile_Q + (threadIdx.y / np)*(T_B_KQ::I*stride_tile_Q) + k_KQ_0, stride_tile_Q);
@@ -479,8 +481,18 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter(
T_A_KQ K_A;
load_ldmatrix(K_A, tile_K + i_KQ_0*stride_tile_K + (k_KQ_0 - k0_start), stride_tile_K);
// Wide version of KQ_C is column-major => swap A and B.
mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], Q_B[0], K_A);
if constexpr (cols_per_warp == 8) {
mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], K_A, Q_B[0]);
} else {
// Wide version of KQ_C is column-major
#if defined(AMD_WMMA_AVAILABLE)
// RDNA matrix C is column-major.
mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], K_A, Q_B[0]);
#else
// swap A and B for CUDA.
mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], Q_B[0], K_A);
#endif // defined(AMD_WMMA_AVAILABLE)
}
}
}
}
@@ -841,7 +853,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile(
constexpr int cols_per_warp = T_B_KQ::I;
constexpr int cols_per_thread = 2; // This is specifically KQ columns, Volta only has a single VKQ column.
constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column.
constexpr int np = cols_per_warp > ncols ? nwarps : nwarps * cols_per_warp/ncols; // Number of parallel CUDA warps per Q column.
constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa (DKQ, DV, ncols);
constexpr int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2 (DKQ, DV, ncols);
constexpr int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2 (DKQ, DV, ncols);
@@ -1353,6 +1365,13 @@ static __global__ void flash_attn_ext_f16(
NO_DEVICE_CODE;
return;
}
#ifdef VOLTA_MMA_AVAILABLE
if (ncols1*ncols2 < 32) {
NO_DEVICE_CODE;
return;
}
#endif // VOLTA_MMA_AVAILABLE
#if __CUDA_ARCH__ == GGML_CUDA_CC_TURING
if (ncols1*ncols2 > 32) {
NO_DEVICE_CODE;
@@ -1585,3 +1604,8 @@ DECL_FATTN_MMA_F16_CASE_ALL_NCOLS2(256, 256, 64)
extern DECL_FATTN_MMA_F16_CASE(576, 512, 1, 16);
extern DECL_FATTN_MMA_F16_CASE(576, 512, 2, 16);
extern DECL_FATTN_MMA_F16_CASE(576, 512, 4, 16);
// For GLM 4.7 Flash
extern DECL_FATTN_MMA_F16_CASE(576, 512, 4, 4);
extern DECL_FATTN_MMA_F16_CASE(576, 512, 8, 4);
extern DECL_FATTN_MMA_F16_CASE(576, 512, 16, 4);

View File

@@ -68,6 +68,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_nv
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 2, 64, 64)
return 0;
@@ -122,6 +124,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_nv
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 2, 32, 128)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 2, 32, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 32, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 32, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 2, 32, 64)
return 0;
@@ -183,6 +187,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_am
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 2, 32, 128)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 2, 32, 128)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 32, 512, 1, 128, 64)
@@ -245,6 +251,8 @@ static constexpr __host__ __device__ uint32_t ggml_cuda_fattn_tile_get_config_am
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 16, 256, 5, 32, 256)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(256, 256, 32, 256, 3, 64, 128)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 4, 128, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 8, 256, 2, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 16, 256, 4, 64, 64)
GGML_CUDA_FATTN_TILE_CONFIG_CASE(576, 512, 32, 256, 2, 128, 64)
@@ -1187,6 +1195,14 @@ static void launch_fattn_tile_switch_ncols2(ggml_backend_cuda_context & ctx, ggm
launch_fattn_tile_switch_ncols1<DKQ, DV, 16, use_logit_softcap>(ctx, dst);
return;
}
if (use_gqa_opt && gqa_ratio % 8 == 0) {
launch_fattn_tile_switch_ncols1<DKQ, DV, 8, use_logit_softcap>(ctx, dst);
return;
}
if (use_gqa_opt && gqa_ratio % 4 == 0) {
launch_fattn_tile_switch_ncols1<DKQ, DV, 4, use_logit_softcap>(ctx, dst);
return;
}
}
if constexpr (DV <= 256) {

View File

@@ -111,7 +111,7 @@ static void ggml_cuda_flash_attn_ext_mma_f16(ggml_backend_cuda_context & ctx, gg
ggml_cuda_flash_attn_ext_mma_f16_switch_ncols2<256, 256>(ctx, dst);
break;
case 576: {
// For Deepseek, go straight to the ncols1 switch to avoid compiling unnecessary kernels.
// For Deepseek/GLM4, go straight to the ncols1 switch to avoid compiling unnecessary kernels.
GGML_ASSERT(V->ne[0] == 512);
float max_bias = 0.0f;
memcpy(&max_bias, (const float *) KQV->op_params + 1, sizeof(float));
@@ -121,8 +121,12 @@ static void ggml_cuda_flash_attn_ext_mma_f16(ggml_backend_cuda_context & ctx, gg
GGML_ASSERT(Q->ne[2] % K->ne[2] == 0);
const int gqa_ratio = Q->ne[2] / K->ne[2];
GGML_ASSERT(gqa_ratio % 16 == 0);
ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1<576, 512, 16>(ctx, dst);
GGML_ASSERT(gqa_ratio % 4 == 0);
if (gqa_ratio % 16 == 0) {
ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1<576, 512, 16>(ctx, dst);
} else {
ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1<576, 512, 4>(ctx, dst);
}
} break;
default:
GGML_ABORT("fatal error");
@@ -251,7 +255,7 @@ static best_fattn_kernel ggml_cuda_get_best_fattn_kernel(const int device, const
if (V->ne[0] != 512) {
return BEST_FATTN_KERNEL_NONE;
}
if (!gqa_opt_applies || gqa_ratio % 16 != 0) {
if (!gqa_opt_applies || gqa_ratio % 4 != 0) {
return BEST_FATTN_KERNEL_NONE;
}
break;

View File

@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 16, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 16, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 16, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 16, 4);
DECL_FATTN_MMA_F16_CASE(576, 512, 16, 4);

View File

@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 2, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 2, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 2, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 2, 4);
DECL_FATTN_MMA_F16_CASE(576, 512, 2, 4);

View File

@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 4, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 4, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 4, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 4, 4);
DECL_FATTN_MMA_F16_CASE(576, 512, 4, 4);

View File

@@ -8,3 +8,4 @@ DECL_FATTN_MMA_F16_CASE(96, 96, 8, 4);
DECL_FATTN_MMA_F16_CASE(112, 112, 8, 4);
DECL_FATTN_MMA_F16_CASE(128, 128, 8, 4);
DECL_FATTN_MMA_F16_CASE(256, 256, 8, 4);
DECL_FATTN_MMA_F16_CASE(576, 512, 8, 4);

View File

@@ -1071,12 +1071,8 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
op->src[0]->ne[0] != 112 &&
op->src[0]->ne[0] != 128 &&
op->src[0]->ne[0] != 192 &&
op->src[0]->ne[0] != 256) {
return false;
}
if (op->src[0]->ne[0] == 576) {
// DeepSeek sizes
// TODO: disabled for now, until optmized
op->src[0]->ne[0] != 256 &&
op->src[0]->ne[0] != 576) {
return false;
}
if (op->src[1]->type != op->src[2]->type) {

View File

@@ -8967,6 +8967,7 @@ kernel void kernel_flash_attn_ext(
//case 1: kernel_flash_attn_ext_impl<FWD_TMPL, 1>(FWD_ARGS); break;
//case 2: kernel_flash_attn_ext_impl<FWD_TMPL, 2>(FWD_ARGS); break;
case 4: kernel_flash_attn_ext_impl<FWD_TMPL, 4>(FWD_ARGS); break;
case 8: kernel_flash_attn_ext_impl<FWD_TMPL, 8>(FWD_ARGS); break;
}
#undef FWD_TMPL
#undef FWD_ARGS

View File

@@ -2456,7 +2456,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
// simdgroups per threadgroup (a.k.a. warps)
//nsg = ne01 <= nqptg ? MAX(4, MIN(nsgmax, MIN(ne11/ncpsg, (int64_t) pipeline.maxTotalThreadsPerThreadgroup/32))) : 4;
int32_t nsg = 4;
int32_t nsg = ne00 >= 512 ? 8 : 4;
const size_t smem = FATTN_SMEM(nsg);

View File

@@ -6166,6 +6166,7 @@ kernel void kernel_flash_attn_ext(
//case 1: kernel_flash_attn_ext_impl<FWD_TMPL, 1>(FWD_ARGS); break;
//case 2: kernel_flash_attn_ext_impl<FWD_TMPL, 2>(FWD_ARGS); break;
case 4: kernel_flash_attn_ext_impl<FWD_TMPL, 4>(FWD_ARGS); break;
case 8: kernel_flash_attn_ext_impl<FWD_TMPL, 8>(FWD_ARGS); break;
}
#undef FWD_TMPL
#undef FWD_ARGS

View File

@@ -39,6 +39,13 @@ type Model interface {
Config() config
}
// Validator is an optional interface that models can implement to perform
// validation after tensors have been loaded. If validation fails, model
// loading will fail with the returned error.
type Validator interface {
Validate() error
}
// MultimodalProcessor must be implemented by multimodal models.
type MultimodalProcessor interface {
// EncodeMultimodal processes a single input (such as an image) and
@@ -116,6 +123,13 @@ func New(modelPath string, params ml.BackendParams) (Model, error) {
base := Base{b: b, config: m.Config()}
v := reflect.ValueOf(m)
v.Elem().Set(populateFields(base, v.Elem()))
if validator, ok := m.(Validator); ok {
if err := validator.Validate(); err != nil {
return nil, err
}
}
return m, nil
}

View File

@@ -0,0 +1,323 @@
package glm4moelite
import (
"errors"
"math"
"github.com/ollama/ollama/fs"
"github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
)
var ErrOldModelFormat = errors.New("this model uses a weight format that is no longer supported; please re-download it")
type Options struct {
numExpertsUsed int
numExperts int
normTopKProb bool
routedScalingFactor float32
kvLoraRank,
qkNopeHeadDim,
qkRopeHeadDim,
kqNopeHeadDim,
qkHeadDim int
qLoraRank int
vHeadDim int
hiddenSize,
numHeads,
numKVHeads int
eps,
ropeBase float32
kqScale float64
}
func (o Options) applyRotaryPositionEmbeddings(ctx ml.Context, t, p ml.Tensor) ml.Tensor {
return nn.RoPE(ctx, t, p, o.qkRopeHeadDim, o.ropeBase, 1.0)
}
type Attention struct {
Q *nn.Linear `gguf:"attn_q"`
QA *nn.Linear `gguf:"attn_q_a"`
QANorm *nn.RMSNorm `gguf:"attn_q_a_norm"`
QB *nn.Linear `gguf:"attn_q_b"`
KVA *nn.Linear `gguf:"attn_kv_a_mqa"`
KVANorm *nn.RMSNorm `gguf:"attn_kv_a_norm"`
KB *nn.Linear `gguf:"attn_k_b"`
VB *nn.Linear `gguf:"attn_v_b"`
Output *nn.Linear `gguf:"attn_out,alt:attn_output"`
}
func (attn *Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
seqLength := hiddenStates.Dim(1)
var query ml.Tensor
if opts.qLoraRank == 0 {
query = attn.Q.Forward(ctx, hiddenStates)
} else {
query = attn.QA.Forward(ctx, hiddenStates)
query = attn.QANorm.Forward(ctx, query, opts.eps)
query = attn.QB.Forward(ctx, query)
}
query = query.Reshape(ctx, query.Dim(0)/opts.numHeads, opts.numHeads, seqLength)
queryChunks := query.ChunkSections(ctx, 0, opts.qkNopeHeadDim, opts.qkRopeHeadDim)
compressedKV := attn.KVA.Forward(ctx, hiddenStates)
kPass := compressedKV.Slice(ctx, 0, 0, opts.kvLoraRank, 1)
kRot := compressedKV.View(ctx,
opts.kvLoraRank*compressedKV.Stride(0), opts.qkRopeHeadDim,
compressedKV.Stride(1), 1,
compressedKV.Stride(1), compressedKV.Dim(1),
)
qRot := opts.applyRotaryPositionEmbeddings(ctx, queryChunks[1], positions)
kRot = opts.applyRotaryPositionEmbeddings(ctx, kRot, positions)
kPass = attn.KVANorm.Forward(ctx, kPass, opts.eps)
// MLA absorption: absorb K projection into query
qPass := queryChunks[0].Permute(ctx, 0, 2, 1, 3)
qPassAbsorb := attn.KB.Forward(ctx, qPass).Permute(ctx, 0, 2, 1, 3)
query = qRot.Concat(ctx, qPassAbsorb, 0)
kPass = kPass.Reshape(ctx, opts.kvLoraRank, 1, seqLength)
key := kRot.Concat(ctx, kPass, 0)
attention := nn.AttentionWithVMLA(ctx, query, key, kPass, nil, attn.VB.Weight, opts.kqScale, cache)
attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), seqLength)
return attn.Output.Forward(ctx, attention)
}
type MLP interface {
Forward(ml.Context, ml.Tensor, *Options) ml.Tensor
}
type sparse struct {
Router *nn.Linear `gguf:"ffn_gate_inp"`
Gate *nn.Linear `gguf:"ffn_gate_exps"`
Up *nn.Linear `gguf:"ffn_up_exps"`
Down *nn.Linear `gguf:"ffn_down_exps"`
SharedExpert *dense `gguf:",suf:_shexp"`
ExpProbsBias ml.Tensor `gguf:"exp_probs_b.bias,alt:exp_probs_b"`
}
func (moe *sparse) Moe(ctx ml.Context, hiddenStates, topKIndices, topKWeights ml.Tensor, opts *Options) ml.Tensor {
hiddenStates = hiddenStates.Reshape(ctx, hiddenStates.Dim(0), 1, hiddenStates.Dim(1))
upStates := moe.Up.Weight.MulmatID(ctx, hiddenStates, topKIndices)
hiddenStates = moe.Gate.Weight.MulmatID(ctx, hiddenStates, topKIndices)
hiddenStates = hiddenStates.SILU(ctx, upStates)
experts := moe.Down.Weight.MulmatID(ctx, hiddenStates, topKIndices)
experts = experts.Mul(ctx, topKWeights)
nextStates := experts.View(ctx, 0, experts.Dim(0), experts.Stride(2), experts.Dim(2))
for i := 1; i < opts.numExpertsUsed; i++ {
nextStates = nextStates.Add(ctx, experts.View(ctx, i*experts.Stride(1), experts.Dim(0), experts.Stride(2), experts.Dim(2)))
}
return nextStates
}
func (moe *sparse) topKIndices(ctx ml.Context, scores ml.Tensor, opts *Options) ml.Tensor {
if moe.ExpProbsBias != nil {
scores = scores.Add(ctx, moe.ExpProbsBias)
}
topKIndices := scores.TopK(ctx, opts.numExpertsUsed)
return topKIndices
}
func (moe *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
residuals := hiddenStates
routerLogits := moe.Router.Forward(ctx, hiddenStates)
scores := routerLogits.Sigmoid(ctx)
topKIndices := moe.topKIndices(ctx, scores, opts)
topKWeights := scores.Reshape(ctx, 1, opts.numExperts, hiddenStates.Dim(1)).Rows(ctx, topKIndices)
if opts.normTopKProb {
topKWeights = topKWeights.Reshape(ctx, opts.numExpertsUsed, hiddenStates.Dim(1))
topKWeights = topKWeights.Div(ctx, topKWeights.SumRows(ctx))
topKWeights = topKWeights.Reshape(ctx, 1, opts.numExpertsUsed, hiddenStates.Dim(1))
}
topKWeights = topKWeights.Scale(ctx, float64(opts.routedScalingFactor))
hiddenStates = moe.Moe(ctx, hiddenStates, topKIndices, topKWeights, opts)
sharedExpertResult := moe.SharedExpert.Forward(ctx, residuals, opts)
hiddenStates = hiddenStates.Add(ctx, sharedExpertResult)
return hiddenStates
}
type dense struct {
Gate *nn.Linear `gguf:"ffn_gate"`
Up *nn.Linear `gguf:"ffn_up"`
Down *nn.Linear `gguf:"ffn_down"`
}
func (mlp *dense) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
return mlp.Down.Forward(ctx, hiddenStates)
}
type Layer struct {
AttentionNorm *nn.RMSNorm `gguf:"attn_norm"`
Attention *Attention
MLPNorm *nn.RMSNorm `gguf:"ffn_norm"`
MLP MLP
}
func (t *Layer) Forward(ctx ml.Context, hiddenStates, positions, outputs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
residual := hiddenStates
hiddenStates = t.AttentionNorm.Forward(ctx, hiddenStates, opts.eps)
hiddenStates = t.Attention.Forward(ctx, hiddenStates, positions, cache, opts)
if outputs != nil {
hiddenStates = hiddenStates.Rows(ctx, outputs)
residual = residual.Rows(ctx, outputs)
}
hiddenStates = hiddenStates.Add(ctx, residual)
residual = hiddenStates
hiddenStates = t.MLPNorm.Forward(ctx, hiddenStates, opts.eps)
hiddenStates = t.MLP.Forward(ctx, hiddenStates, opts)
hiddenStates = hiddenStates.Add(ctx, residual)
return hiddenStates
}
type Model struct {
model.Base
model.BytePairEncoding
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
OutputNorm *nn.RMSNorm `gguf:"output_norm"`
Output *nn.Linear `gguf:"output,alt:token_embd"`
*Options
}
func New(c fs.Config) (model.Model, error) {
layers := make([]Layer, c.Uint("block_count"))
firstDenseLayerIndex := int(c.Uint("leading_dense_block_count"))
for i := range layers {
if i < firstDenseLayerIndex {
layers[i].MLP = &dense{}
} else {
layers[i].MLP = &sparse{}
}
}
keyLength := int(c.Uint("attention.key_length"))
valueLength := int(c.Uint("attention.value_length"))
kvLoraRank := int(c.Uint("attention.kv_lora_rank"))
qkRopeHeadDim := int(c.Uint("rope.dimension_count"))
// For MLA absorption, the effective key dimension is kvLoraRank + qkRopeHeadDim
mlaKeyLength := kvLoraRank + qkRopeHeadDim
kqScale := 1.0 / math.Sqrt(float64(mlaKeyLength))
var pre []string
switch c.String("tokenizer.ggml.pre") {
case "glm4":
pre = []string{
`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
}
default:
return nil, model.ErrUnsupportedTokenizer
}
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
BOS: []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
EOS: append(
[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
c.Ints("tokenizer.ggml.eos_token_ids")...,
),
},
pre...,
),
Layers: layers,
Options: &Options{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),
numKVHeads: int(c.Uint("attention.head_count_kv")),
eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"),
numExperts: int(c.Uint("expert_count")),
numExpertsUsed: int(c.Uint("expert_used_count")),
normTopKProb: c.Bool("expert_weights_norm", true),
qLoraRank: int(c.Uint("attention.q_lora_rank")),
kvLoraRank: int(c.Uint("attention.kv_lora_rank")),
qkHeadDim: keyLength,
vHeadDim: valueLength,
qkRopeHeadDim: int(c.Uint("rope.dimension_count")),
qkNopeHeadDim: keyLength - int(c.Uint("rope.dimension_count")),
kqNopeHeadDim: keyLength - int(c.Uint("rope.dimension_count")),
routedScalingFactor: c.Float("expert_weights_scale"),
kqScale: kqScale,
},
}
m.Cache = kvcache.NewCausalCache(m.Shift)
return &m, nil
}
func (m Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return m.applyRotaryPositionEmbeddings(ctx, key, shift), nil
}
func (m *Model) Validate() error {
for _, layer := range m.Layers {
if layer.Attention != nil && (layer.Attention.KB == nil || layer.Attention.VB == nil) {
return ErrOldModelFormat
}
}
return nil
}
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromInts(batch.Positions, len(batch.Positions))
hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
for i, layer := range m.Layers {
m.Cache.SetLayer(i)
var outputs ml.Tensor
if i == len(m.Layers)-1 {
outputs = batch.Outputs
}
hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, m.Options)
}
hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps)
return m.Output.Forward(ctx, hiddenStates), nil
}
func init() {
model.Register("glm4moelite", New)
}

View File

@@ -0,0 +1,73 @@
package glm4moelite
import (
"testing"
"github.com/ollama/ollama/ml/nn"
)
func TestValidate(t *testing.T) {
tests := []struct {
name string
model *Model
wantErr bool
}{
{
name: "valid model with KB and VB",
model: &Model{
Layers: []Layer{
{Attention: &Attention{KB: &nn.Linear{}, VB: &nn.Linear{}}},
},
},
wantErr: false,
},
{
name: "missing KB",
model: &Model{
Layers: []Layer{
{Attention: &Attention{VB: &nn.Linear{}}},
},
},
wantErr: true,
},
{
name: "missing VB",
model: &Model{
Layers: []Layer{
{Attention: &Attention{KB: &nn.Linear{}}},
},
},
wantErr: true,
},
{
name: "missing both KB and VB",
model: &Model{
Layers: []Layer{
{Attention: &Attention{}},
},
},
wantErr: true,
},
{
name: "nil Attention is ok",
model: &Model{
Layers: []Layer{
{Attention: nil},
},
},
wantErr: false,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
err := tt.model.Validate()
if (err != nil) != tt.wantErr {
t.Errorf("Validate() error = %v, wantErr %v", err, tt.wantErr)
}
if tt.wantErr && err != ErrOldModelFormat {
t.Errorf("Validate() error = %v, want %v", err, ErrOldModelFormat)
}
})
}
}

410
model/models/lfm2/cache.go Normal file
View File

@@ -0,0 +1,410 @@
package lfm2
import (
"slices"
"github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model/input"
)
var _ kvcache.Cache = (*HybridCache)(nil)
// HybridCache stores:
// - a standard causal KV cache for attention layers
// - a per-sequence recurrent conv state for shortconv layers
//
// Conv state shape (per layer, per sequence): [dConv, hiddenSize] where dConv = L_cache - 1.
// Stored internally as a tensor of shape [dConv * hiddenSize, maxSlots].
type HybridCache struct {
kv *kvcache.Causal
backend ml.Backend
dtype ml.DType
maxSequences int
hiddenSize int
dConv int
// slot mapping for recurrent state
slotForSeq map[int]int
refCount []int
freeSlots []int
// per-layer conv state buffers (allocated lazily)
convCtxs map[int]ml.Context
convStates map[int]ml.Tensor // [dConv*hiddenSize, maxSlots]
// current forward batch (derived in StartForward)
curSeqs []int
curSlots []int
curSlotsInput ml.Tensor
curSeqTokens int
// track if EnsureWritable has been called for this forward pass
writableEnsured bool
// track any error from EnsureWritable to propagate later
writableError error
}
func NewHybridCache(shift func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error), hiddenSize, dConv int) *HybridCache {
return &HybridCache{
kv: kvcache.NewCausalCache(shift),
hiddenSize: hiddenSize,
dConv: dConv,
slotForSeq: make(map[int]int),
convCtxs: make(map[int]ml.Context),
convStates: make(map[int]ml.Tensor),
}
}
func (c *HybridCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
c.backend = backend
c.dtype = dtype
c.maxSequences = maxSequences
// initialize slot allocator
c.refCount = make([]int, maxSequences)
c.freeSlots = c.freeSlots[:0]
for i := maxSequences - 1; i >= 0; i-- {
c.freeSlots = append(c.freeSlots, i)
}
c.kv.Init(backend, dtype, maxSequences, capacity, maxBatch)
}
func (c *HybridCache) Close() {
for _, ctx := range c.convCtxs {
ctx.Close()
}
c.kv.Close()
}
func (c *HybridCache) SetConfig(config ml.CacheConfig) {
c.kv.SetConfig(config)
}
func (c *HybridCache) SetLayer(layer int) {
c.kv.SetLayer(layer)
}
func (c *HybridCache) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor) {
return c.kv.Get(ctx)
}
func (c *HybridCache) Put(ctx ml.Context, key, value ml.Tensor) {
c.kv.Put(ctx, key, value)
}
func (c *HybridCache) StartForward(ctx ml.Context, batch input.Batch, reserve bool) error {
if err := c.kv.StartForward(ctx, batch, reserve); err != nil {
return err
}
// Derive equal-length sequence layout for shortconv.
// LFM2 shortconv assumes tokens form a [seq_tokens, seqs] grid.
seqCounts := make(map[int]int)
c.curSeqs = c.curSeqs[:0]
for _, s := range batch.Sequences {
if _, ok := seqCounts[s]; !ok {
c.curSeqs = append(c.curSeqs, s)
}
seqCounts[s]++
}
if len(c.curSeqs) == 0 {
return nil
}
nTokens := len(batch.Sequences)
nSeqs := len(c.curSeqs)
want := nTokens / nSeqs
for _, s := range c.curSeqs {
if seqCounts[s] != want {
return kvcache.ErrNotSupported
}
}
c.curSeqTokens = want
// When reserving memory for estimation, use fake slot assignments
// without modifying permanent state (slotForSeq, refCount)
if reserve {
c.curSlots = c.curSlots[:0]
slots := make([]int32, nSeqs)
for i := range nSeqs {
c.curSlots = append(c.curSlots, i)
slots[i] = int32(i)
}
c.curSlotsInput = ctx.Input().FromInts(slots, len(slots))
return nil
}
// Ensure slots exist for sequences in this batch
c.curSlots = c.curSlots[:0]
var newSlots []int // track newly allocated slots that need zeroing
for _, s := range c.curSeqs {
slot, ok := c.slotForSeq[s]
if !ok {
var err error
slot, err = c.allocSlot()
if err != nil {
return err
}
c.slotForSeq[s] = slot
c.refCount[slot] = 1
newSlots = append(newSlots, slot)
}
c.curSlots = append(c.curSlots, slot)
}
// Zero conv state for newly allocated slots to clear stale data from previous sequences
if len(newSlots) > 0 {
c.zeroConvSlots(ctx, newSlots)
}
// Create a tensor for the current slots
slots := make([]int32, len(c.curSlots))
for i, v := range c.curSlots {
slots[i] = int32(v)
}
c.curSlotsInput = ctx.Input().FromInts(slots, len(slots))
// Reset writable state for new forward pass
c.writableEnsured = false
c.writableError = nil
return nil
}
func (c *HybridCache) allocSlot() (int, error) {
if len(c.freeSlots) == 0 {
return 0, kvcache.ErrKvCacheFull
}
slot := c.freeSlots[len(c.freeSlots)-1]
c.freeSlots = c.freeSlots[:len(c.freeSlots)-1]
return slot, nil
}
func (c *HybridCache) freeSlot(slot int) {
// Bounds check before freeing
if slot >= 0 && slot < c.maxSequences {
c.freeSlots = append(c.freeSlots, slot)
}
}
// zeroConvSlots zeros the conv state for the given slots across all layers.
// This must be called when recycling slots to prevent stale state from affecting new sequences.
func (c *HybridCache) zeroConvSlots(ctx ml.Context, slots []int) {
if len(slots) == 0 || len(c.convStates) == 0 {
return
}
// Use input context for creating tensors
inputCtx := ctx.Input()
// Create slot indices tensor
slotIndices := make([]int32, len(slots))
for i, s := range slots {
slotIndices[i] = int32(s)
}
slotsTensor := inputCtx.FromInts(slotIndices, len(slotIndices))
// Create zero tensor for the slots (SetRows requires F32 source)
zeros := inputCtx.Zeros(ml.DTypeF32, c.dConv*c.hiddenSize, len(slots))
// Zero each layer's conv state for these slots
for _, buf := range c.convStates {
ctx.Forward(buf.SetRows(ctx, zeros, slotsTensor))
}
}
// EnsureWritable ensures that sequences in the current batch have private (non-shared) conv slots.
// Returns an error if slot allocation fails.
func (c *HybridCache) EnsureWritable(ctx ml.Context) error {
for i, seq := range c.curSeqs {
slot, ok := c.slotForSeq[seq]
if !ok {
continue
}
// Bounds check
if slot < 0 || slot >= len(c.refCount) {
continue
}
if c.refCount[slot] <= 1 {
continue
}
newSlot, err := c.allocSlot()
if err != nil {
return err
}
c.refCount[slot]--
c.refCount[newSlot] = 1
c.slotForSeq[seq] = newSlot
c.curSlots[i] = newSlot
// Copy existing conv state for all initialized layers
for _, buf := range c.convStates {
// buf: [dConv*hiddenSize, maxSlots]
src := buf.Rows(ctx, ctx.Input().FromInts([]int32{int32(slot)}, 1))
// SetRows requires F32 source
srcF32 := src.Cast(ctx, ml.DTypeF32)
ctx.Forward(buf.SetRows(ctx, srcF32, ctx.Input().FromInts([]int32{int32(newSlot)}, 1)))
}
}
// Rebuild current slots tensor
slots := make([]int32, len(c.curSlots))
for i, v := range c.curSlots {
slots[i] = int32(v)
}
c.curSlotsInput = ctx.Input().FromInts(slots, len(slots))
return nil
}
func (c *HybridCache) CopyPrefix(srcSeq, dstSeq int, prefixLen int32) {
// KV cache shares prefix metadata (no copy) which is correct for prefix reuse.
c.kv.CopyPrefix(srcSeq, dstSeq, prefixLen)
// For shortconv state we implement copy-on-write: dst shares the same slot as src.
// On the first write to dst, EnsureWritable will create a private slot.
if dstSlot, ok := c.slotForSeq[dstSeq]; ok {
// Bounds check before decrementing
if dstSlot >= 0 && dstSlot < len(c.refCount) {
c.refCount[dstSlot]--
if c.refCount[dstSlot] <= 0 {
c.refCount[dstSlot] = 0
c.freeSlot(dstSlot)
}
}
delete(c.slotForSeq, dstSeq)
}
srcSlot, ok := c.slotForSeq[srcSeq]
if !ok {
// src may not have a slot yet; dst will allocate on demand
return
}
// Bounds check before incrementing
if srcSlot >= 0 && srcSlot < len(c.refCount) {
c.slotForSeq[dstSeq] = srcSlot
c.refCount[srcSlot]++
}
}
func (c *HybridCache) CanResume(seq int, pos int32) bool {
return c.kv.CanResume(seq, pos)
}
func (c *HybridCache) Remove(seq int, beginIndex, endIndex int32) error {
if err := c.kv.Remove(seq, beginIndex, endIndex); err != nil {
return err
}
// For recurrent state, any removal invalidates the state because
// the state at position N depends on all previous positions.
// Drop the slot mapping so it resets on next use.
slot, ok := c.slotForSeq[seq]
if !ok {
return nil
}
// Bounds check
if slot < 0 || slot >= len(c.refCount) {
delete(c.slotForSeq, seq)
return nil
}
c.refCount[slot]--
if c.refCount[slot] <= 0 {
c.refCount[slot] = 0
c.freeSlot(slot)
}
delete(c.slotForSeq, seq)
return nil
}
func (c *HybridCache) slotsTensor() ml.Tensor {
return c.curSlotsInput
}
func (c *HybridCache) seqTokens() int {
return c.curSeqTokens
}
func (c *HybridCache) numSeqs() int {
return len(c.curSeqs)
}
func (c *HybridCache) convBuffer(ctx ml.Context, layer int) ml.Tensor {
if buf, ok := c.convStates[layer]; ok {
return buf
}
if _, ok := c.convCtxs[layer]; !ok {
c.convCtxs[layer] = c.backend.NewContextSize(1).Layer(layer)
}
buf := c.convCtxs[layer].Zeros(c.dtype, c.dConv*c.hiddenSize, c.maxSequences)
c.convStates[layer] = buf
return buf
}
// ConvState returns the conv state for current batch sequences as shape [dConv, hiddenSize, nSeqs].
// Returns an error if copy-on-write allocation fails.
func (c *HybridCache) ConvState(ctx ml.Context, layer int) (ml.Tensor, error) {
if !c.writableEnsured {
needsWritable := false
for _, seq := range c.curSeqs {
slot, ok := c.slotForSeq[seq]
if !ok {
continue
}
if slot >= 0 && slot < len(c.refCount) && c.refCount[slot] > 1 {
needsWritable = true
break
}
}
if needsWritable {
if err := c.EnsureWritable(ctx); err != nil {
c.writableError = err
}
}
c.writableEnsured = true
}
if c.writableError != nil {
return nil, c.writableError
}
buf := c.convBuffer(ctx, layer)
cur := buf.Rows(ctx, c.slotsTensor())
return cur.Reshape(ctx, c.dConv, c.hiddenSize, c.numSeqs()), nil
}
// UpdateConvState writes a new conv state for current batch sequences.
// newState must have shape [dConv, hiddenSize, nSeqs].
func (c *HybridCache) UpdateConvState(ctx ml.Context, layer int, newState ml.Tensor) {
buf := c.convBuffer(ctx, layer)
src := newState.Reshape(ctx, c.dConv*c.hiddenSize, c.numSeqs())
// SetRows requires F32 source
srcF32 := src.Cast(ctx, ml.DTypeF32)
ctx.Forward(buf.SetRows(ctx, srcF32, c.slotsTensor()))
}
// IsSupportedForBatch returns true if the current batch layout supports shortconv.
func (c *HybridCache) IsSupportedForBatch() bool {
return c.curSeqTokens > 0 && len(c.curSeqs) > 0
}
// Seqs returns the ordered unique sequences for the current forward pass.
func (c *HybridCache) Seqs() []int {
return slices.Clone(c.curSeqs)
}

View File

@@ -0,0 +1,444 @@
package lfm2
import (
"testing"
"github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml"
)
// TestHybridCache tests verify the slot management logic of HybridCache.
// These tests focus on the recurrent state slot allocation, reference counting,
// and copy-on-write semantics without requiring a full ML backend.
// createSlotOnlyCache creates a HybridCache with only the slot management
// fields initialized. Used to test slot logic in isolation.
func createSlotOnlyCache(maxSequences int) *HybridCache {
return &HybridCache{
hiddenSize: 256,
dConv: 3,
maxSequences: maxSequences,
refCount: make([]int, maxSequences),
freeSlots: initFreeSlots(maxSequences),
slotForSeq: make(map[int]int),
convCtxs: make(map[int]ml.Context),
convStates: make(map[int]ml.Tensor),
}
}
func initFreeSlots(n int) []int {
slots := make([]int, 0, n)
for i := n - 1; i >= 0; i-- {
slots = append(slots, i)
}
return slots
}
func TestHybridCache_SlotAllocation(t *testing.T) {
cache := createSlotOnlyCache(4)
// Verify initial state
if len(cache.freeSlots) != 4 {
t.Errorf("expected 4 free slots, got %d", len(cache.freeSlots))
}
// Allocate all slots
for range 4 {
slot, err := cache.allocSlot()
if err != nil {
t.Fatalf("allocSlot failed: %v", err)
}
cache.refCount[slot] = 1
}
// Should be full now
if len(cache.freeSlots) != 0 {
t.Errorf("expected 0 free slots, got %d", len(cache.freeSlots))
}
// Trying to allocate another should fail
_, err := cache.allocSlot()
if err != kvcache.ErrKvCacheFull {
t.Errorf("expected ErrKvCacheFull, got %v", err)
}
}
func TestHybridCache_SlotReuse(t *testing.T) {
cache := createSlotOnlyCache(4)
// Allocate a slot
slot1, _ := cache.allocSlot()
cache.refCount[slot1] = 1
// Free it
cache.refCount[slot1] = 0
cache.freeSlot(slot1)
// Allocate again - should get the same slot back (LIFO)
slot2, _ := cache.allocSlot()
if slot2 != slot1 {
t.Errorf("expected slot %d to be reused, got %d", slot1, slot2)
}
}
func TestHybridCache_SlotRefCounting_ShareSlot(t *testing.T) {
cache := createSlotOnlyCache(4)
// Allocate slot for seq 1
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
// Simulate sharing slot with seq 2 (copy-on-write style)
cache.slotForSeq[2] = slot1
cache.refCount[slot1]++
// Should share the same slot
if cache.slotForSeq[2] != slot1 {
t.Errorf("expected seq 2 to share slot %d, got %d", slot1, cache.slotForSeq[2])
}
// Ref count should be 2
if cache.refCount[slot1] != 2 {
t.Errorf("expected refCount 2, got %d", cache.refCount[slot1])
}
}
func TestHybridCache_SlotRefCounting_DecRef(t *testing.T) {
cache := createSlotOnlyCache(4)
// Allocate slot for seq 1
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
// Share with seq 2
cache.slotForSeq[2] = slot1
cache.refCount[slot1]++
// Unshare seq 2
cache.refCount[slot1]--
delete(cache.slotForSeq, 2)
// Ref count should be back to 1
if cache.refCount[slot1] != 1 {
t.Errorf("expected refCount 1 after unshare, got %d", cache.refCount[slot1])
}
// Seq 2 should no longer have a slot
if _, ok := cache.slotForSeq[2]; ok {
t.Error("seq 2 should not have a slot after unshare")
}
}
func TestHybridCache_SlotFreeWhenUnused(t *testing.T) {
cache := createSlotOnlyCache(4)
initialFreeSlots := len(cache.freeSlots)
// Allocate slot for seq 1
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
// Free the slot when refCount drops to 0
cache.refCount[slot1]--
if cache.refCount[slot1] <= 0 {
cache.refCount[slot1] = 0
cache.freeSlot(slot1)
}
delete(cache.slotForSeq, 1)
// Slot should be freed
if len(cache.freeSlots) != initialFreeSlots {
t.Errorf("expected %d free slots, got %d", initialFreeSlots, len(cache.freeSlots))
}
// Ref count should be 0
if cache.refCount[slot1] != 0 {
t.Errorf("expected refCount 0, got %d", cache.refCount[slot1])
}
}
func TestHybridCache_SlotOverwrite(t *testing.T) {
cache := createSlotOnlyCache(4)
// Allocate slots for seq 1 and seq 2
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
slot2, _ := cache.allocSlot()
cache.slotForSeq[2] = slot2
cache.refCount[slot2] = 1
initialFreeSlots := len(cache.freeSlots)
// Simulate overwriting seq 2's slot with slot1 (sharing)
// First free the old slot
cache.refCount[slot2]--
if cache.refCount[slot2] <= 0 {
cache.refCount[slot2] = 0
cache.freeSlot(slot2)
}
// Then share slot1
cache.slotForSeq[2] = slot1
cache.refCount[slot1]++
// Seq 2 should now share slot1
if cache.slotForSeq[2] != slot1 {
t.Errorf("expected seq 2 to share slot %d, got %d", slot1, cache.slotForSeq[2])
}
// Old slot2 should be freed
if len(cache.freeSlots) != initialFreeSlots+1 {
t.Errorf("expected %d free slots, got %d", initialFreeSlots+1, len(cache.freeSlots))
}
}
func TestHybridCache_BoundsChecking(t *testing.T) {
cache := createSlotOnlyCache(4)
// Test freeing invalid slot (should not panic)
cache.freeSlot(-1)
cache.freeSlot(100) // out of bounds
// freeSlot does bounds checking, so invalid slots should be ignored
if len(cache.freeSlots) != 4 {
t.Errorf("invalid slots should not affect free list, got %d slots", len(cache.freeSlots))
}
}
func TestHybridCache_MultipleSequences_RefCounting(t *testing.T) {
cache := createSlotOnlyCache(8)
// Allocate slot for seq 1
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
// Fork to seq 2, 3, 4 (all share slot1)
for _, seq := range []int{2, 3, 4} {
cache.slotForSeq[seq] = slot1
cache.refCount[slot1]++
}
// Ref count should be 4
if cache.refCount[slot1] != 4 {
t.Errorf("expected refCount 4, got %d", cache.refCount[slot1])
}
// Remove seq 2, 3
for _, seq := range []int{2, 3} {
delete(cache.slotForSeq, seq)
cache.refCount[slot1]--
}
if cache.refCount[slot1] != 2 {
t.Errorf("expected refCount 2, got %d", cache.refCount[slot1])
}
// Slot should still be allocated (not in free list)
found := false
for _, s := range cache.freeSlots {
if s == slot1 {
found = true
break
}
}
if found {
t.Error("slot1 should not be in free list yet")
}
// Remove remaining sequences
for _, seq := range []int{1, 4} {
delete(cache.slotForSeq, seq)
cache.refCount[slot1]--
}
if cache.refCount[slot1] != 0 {
t.Errorf("expected refCount 0, got %d", cache.refCount[slot1])
}
}
func TestHybridCache_ChainedSharing(t *testing.T) {
cache := createSlotOnlyCache(8)
// Create seq 1
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
// Share 1 -> 2
cache.slotForSeq[2] = slot1
cache.refCount[slot1]++
// Share 2 -> 3 (should still share slot1)
cache.slotForSeq[3] = cache.slotForSeq[2] // which is slot1
cache.refCount[slot1]++
// All should share slot1
if cache.slotForSeq[1] != slot1 || cache.slotForSeq[2] != slot1 || cache.slotForSeq[3] != slot1 {
t.Error("all sequences should share slot1")
}
if cache.refCount[slot1] != 3 {
t.Errorf("expected refCount 3, got %d", cache.refCount[slot1])
}
}
func TestHybridCache_CacheParameters(t *testing.T) {
cache := NewHybridCache(nil, 512, 5) // hiddenSize=512, dConv=5
if cache.hiddenSize != 512 {
t.Errorf("expected hiddenSize 512, got %d", cache.hiddenSize)
}
if cache.dConv != 5 {
t.Errorf("expected dConv 5, got %d", cache.dConv)
}
}
func TestHybridCache_NumSeqs(t *testing.T) {
cache := createSlotOnlyCache(4)
// Initially no sequences
if cache.numSeqs() != 0 {
t.Errorf("expected 0 seqs, got %d", cache.numSeqs())
}
// Manually set up current batch state
cache.curSeqs = []int{1, 2, 3}
if cache.numSeqs() != 3 {
t.Errorf("expected 3 seqs, got %d", cache.numSeqs())
}
}
func TestHybridCache_SeqTokens(t *testing.T) {
cache := createSlotOnlyCache(4)
// Initially 0
if cache.seqTokens() != 0 {
t.Errorf("expected 0 seqTokens, got %d", cache.seqTokens())
}
// Manually set up current batch state
cache.curSeqTokens = 16
if cache.seqTokens() != 16 {
t.Errorf("expected 16 seqTokens, got %d", cache.seqTokens())
}
}
// Test that Seqs returns a clone of curSeqs
func TestHybridCache_Seqs_ReturnsClone(t *testing.T) {
cache := createSlotOnlyCache(4)
cache.curSeqs = []int{1, 2, 3}
seqs := cache.Seqs()
// Modify returned slice
seqs[0] = 999
// Original should be unchanged
if cache.curSeqs[0] != 1 {
t.Error("Seqs should return a clone, not the original slice")
}
}
func TestHybridCache_IsSupportedForBatch(t *testing.T) {
cache := createSlotOnlyCache(4)
// Initially not supported (no batch set up)
if cache.IsSupportedForBatch() {
t.Error("expected IsSupportedForBatch to be false initially")
}
// Set up a valid batch
cache.curSeqTokens = 1
cache.curSeqs = []int{1}
if !cache.IsSupportedForBatch() {
t.Error("expected IsSupportedForBatch to be true with valid batch")
}
}
func TestHybridCache_ZeroConvSlots_EmptyInputs(t *testing.T) {
cache := createSlotOnlyCache(4)
// zeroConvSlots should handle empty slots without panicking
cache.zeroConvSlots(nil, nil)
cache.zeroConvSlots(nil, []int{})
// zeroConvSlots should handle empty convStates without panicking
cache.zeroConvSlots(nil, []int{0, 1, 2})
}
func TestHybridCache_SlotRecycling_TracksNewSlots(t *testing.T) {
cache := createSlotOnlyCache(4)
// Allocate slot for seq 1
slot1, _ := cache.allocSlot()
cache.slotForSeq[1] = slot1
cache.refCount[slot1] = 1
// Free the slot (simulating sequence removal)
cache.refCount[slot1]--
cache.freeSlot(slot1)
delete(cache.slotForSeq, 1)
// Verify slot is in free list
if len(cache.freeSlots) != 4 {
t.Errorf("expected 4 free slots after freeing, got %d", len(cache.freeSlots))
}
// Allocate for new seq 2 - should get recycled slot
slot2, _ := cache.allocSlot()
if slot2 != slot1 {
t.Errorf("expected recycled slot %d, got %d", slot1, slot2)
}
// This recycled slot would need zeroing in the real implementation
// The actual zeroing is tested via integration tests since it requires ML context
}
func TestHybridCache_NewSequence_GetsTrackedForZeroing(t *testing.T) {
cache := createSlotOnlyCache(4)
// Simulate the slot allocation flow from StartForward
// When a sequence doesn't have a slot, it gets allocated and tracked as "new"
newSlots := []int{}
// Seq 1 doesn't have a slot - allocate and track
seq := 1
if _, ok := cache.slotForSeq[seq]; !ok {
slot, err := cache.allocSlot()
if err != nil {
t.Fatalf("allocSlot failed: %v", err)
}
cache.slotForSeq[seq] = slot
cache.refCount[slot] = 1
newSlots = append(newSlots, slot)
}
// Verify newSlots contains the allocated slot
if len(newSlots) != 1 {
t.Errorf("expected 1 new slot, got %d", len(newSlots))
}
// Seq 1 already has a slot - should NOT be tracked as new
newSlots2 := []int{}
if _, ok := cache.slotForSeq[seq]; !ok {
slot, _ := cache.allocSlot()
cache.slotForSeq[seq] = slot
cache.refCount[slot] = 1
newSlots2 = append(newSlots2, slot)
}
// Verify no new slots for existing sequence
if len(newSlots2) != 0 {
t.Errorf("expected 0 new slots for existing sequence, got %d", len(newSlots2))
}
}

253
model/models/lfm2/model.go Normal file
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@@ -0,0 +1,253 @@
package lfm2
import (
"cmp"
"math"
"github.com/ollama/ollama/fs"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
)
type Options struct {
hiddenSize int
headDim, ropeDim int
eps, ropeBase, ropeScale float32
ropeType string
originalContextLength int
// per-layer head counts (LFM2 alternates attention and recurrent layers)
numHeadsByLayer []int
numKVHeadsByLayer []int
}
func (o Options) headDimValue() int {
// Head dim is shared across layers; fall back to first attention layer head count.
for _, h := range o.numHeadsByLayer {
if h > 0 {
return cmp.Or(o.headDim, o.hiddenSize/h)
}
}
return cmp.Or(o.headDim, o.hiddenSize)
}
func (o Options) applyRotaryPositionEmbeddings(ctx ml.Context, states, positions ml.Tensor) ml.Tensor {
opts := []func(*rope.Options){rope.WithTypeNeoX()}
if o.ropeType == "yarn" {
attnFactor := float32(1.0 / (1.0 + 0.1*math.Log(float64(o.ropeScale))))
opts = append(opts,
rope.WithOriginalContextLength(o.originalContextLength),
rope.WithExtrapolationFactor(1.),
rope.WithAttentionFactor(attnFactor),
)
}
headCount := 1
for _, h := range o.numHeadsByLayer {
if h > 0 {
headCount = h
break
}
}
return nn.RoPE(ctx, states, positions, cmp.Or(o.ropeDim, o.headDim, o.hiddenSize/headCount), o.ropeBase, 1./o.ropeScale, opts...)
}
type Model struct {
model.Base
model.TextProcessor
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
OutputNorm *nn.RMSNorm `gguf:"output_norm,alt:token_embd_norm"`
Output *nn.Linear `gguf:"output,alt:token_embd"`
Options
}
func New(c fs.Config) (model.Model, error) {
if c.Uint("expert_count") > 0 {
return nil, model.ErrUnsupportedModel
}
if c.String("tokenizer.ggml.model") != "gpt2" {
return nil, model.ErrUnsupportedTokenizer
}
vocabulary := model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
BOS: []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
EOS: append(
[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
c.Ints("tokenizer.ggml.eos_token_ids")...,
),
}
var pretokenizers []string
switch c.String("tokenizer.ggml.pre") {
case "default":
// use default BPE pretokenizer
default:
// llama-bpe style (default for LFM2)
pretokenizers = []string{
`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
}
}
m := Model{
TextProcessor: model.NewBytePairEncoding(&vocabulary, pretokenizers...),
Layers: make([]Layer, c.Uint("block_count")),
Options: Options{
hiddenSize: int(c.Uint("embedding_length")),
headDim: int(c.Uint("attention.key_length")),
ropeDim: int(c.Uint("rope.dimension_count")),
eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeType: c.String("rope.scaling.type"),
ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.scaling.factor", 1),
originalContextLength: int(c.Uint("rope.scaling.original_context_length")),
},
}
type headCounts interface {
HeadCount() []uint64
HeadCountKV() []uint64
}
hc, ok := c.(headCounts)
if !ok {
return nil, model.ErrUnsupportedModel
}
headCount := hc.HeadCount()
headCountKV := hc.HeadCountKV()
m.numHeadsByLayer = make([]int, len(m.Layers))
m.numKVHeadsByLayer = make([]int, len(m.Layers))
for i := range m.Layers {
m.numHeadsByLayer[i] = int(headCount[i])
m.numKVHeadsByLayer[i] = int(headCountKV[i])
if m.numKVHeadsByLayer[i] == 0 {
m.Layers[i].Operator = &ShortConv{}
} else {
m.Layers[i].Operator = &Attention{}
}
}
lCache := int(c.Uint("shortconv.l_cache"))
dConv := max(0, lCache-1)
m.Cache = NewHybridCache(m.Shift, m.hiddenSize, dConv)
return &m, nil
}
type Operator interface {
Forward(ctx ml.Context, hiddenStates, positions ml.Tensor, cache *HybridCache, layer int, opts *Options) ml.Tensor
}
type Attention struct {
Query *nn.Linear `gguf:"attn_q"`
QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
Key *nn.Linear `gguf:"attn_k"`
KeyNorm *nn.RMSNorm `gguf:"attn_k_norm"`
Value *nn.Linear `gguf:"attn_v"`
Output *nn.Linear `gguf:"attn_output,alt:attn_out"`
}
func (sa *Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor, cache *HybridCache, layer int, opts *Options) ml.Tensor {
batchSize := hiddenStates.Dim(1)
headDim := opts.headDimValue()
numHeads := opts.numHeadsByLayer[layer]
numKVHeads := opts.numKVHeadsByLayer[layer]
query := sa.Query.Forward(ctx, hiddenStates)
key := sa.Key.Forward(ctx, hiddenStates)
value := sa.Value.Forward(ctx, hiddenStates)
query = query.Reshape(ctx, headDim, numHeads, batchSize)
key = key.Reshape(ctx, headDim, numKVHeads, batchSize)
value = value.Reshape(ctx, headDim, numKVHeads, batchSize)
query = sa.QueryNorm.Forward(ctx, query, opts.eps)
key = sa.KeyNorm.Forward(ctx, key, opts.eps)
query = opts.applyRotaryPositionEmbeddings(ctx, query, positions)
key = opts.applyRotaryPositionEmbeddings(ctx, key, positions)
attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(headDim)), cache)
attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize)
return sa.Output.Forward(ctx, attention)
}
type MLP struct {
Up *nn.Linear `gguf:"ffn_up"`
Down *nn.Linear `gguf:"ffn_down"`
Gate *nn.Linear `gguf:"ffn_gate"`
}
func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
return mlp.Down.Forward(ctx, hiddenState)
}
type Layer struct {
AttentionNorm *nn.RMSNorm `gguf:"attn_norm"`
Operator Operator
MLPNorm *nn.RMSNorm `gguf:"ffn_norm"`
MLP *MLP
}
func (l *Layer) Forward(ctx ml.Context, layer int, hiddenState, positions, outputs ml.Tensor, cache *HybridCache, opts *Options) ml.Tensor {
residual := hiddenState
hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
hiddenState = l.Operator.Forward(ctx, hiddenState, positions, cache, layer, opts)
if outputs != nil {
hiddenState = hiddenState.Rows(ctx, outputs)
residual = residual.Rows(ctx, outputs)
}
hiddenState = hiddenState.Add(ctx, residual)
residual = hiddenState
hiddenState = l.MLPNorm.Forward(ctx, hiddenState, opts.eps)
hiddenState = l.MLP.Forward(ctx, hiddenState, opts)
return hiddenState.Add(ctx, residual)
}
func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return m.applyRotaryPositionEmbeddings(ctx, key, shift), nil
}
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromInts(batch.Positions, len(batch.Positions))
hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
for i, layer := range m.Layers {
m.Cache.SetLayer(i)
var outputs ml.Tensor
if i == len(m.Layers)-1 {
outputs = batch.Outputs
}
hiddenState = layer.Forward(ctx, i, hiddenState, positions, outputs, m.Cache.(*HybridCache), &m.Options)
}
hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
return m.Output.Forward(ctx, hiddenState), nil
}
func init() {
model.Register("lfm2", New)
}

View File

@@ -0,0 +1,50 @@
package lfm2
import (
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn"
)
type shortConvKernel struct {
Weight ml.Tensor `gguf:"weight"`
}
// ShortConv implements the LFM2 short-convolution block (GGML_OP_SSM_CONV) with a recurrent
// state stored in the HybridCache.
type ShortConv struct {
Conv *shortConvKernel `gguf:"shortconv.conv"`
InProj *nn.Linear `gguf:"shortconv.in_proj"`
OutProj *nn.Linear `gguf:"shortconv.out_proj"`
}
func (sc *ShortConv) Forward(ctx ml.Context, hiddenStates ml.Tensor, _ ml.Tensor, cache *HybridCache, layer int, opts *Options) ml.Tensor {
nSeqs := cache.numSeqs()
seqTokens := cache.seqTokens()
hiddenSize := hiddenStates.Dim(0)
if nSeqs <= 0 || seqTokens <= 0 || hiddenStates.Dim(1) != nSeqs*seqTokens {
panic("lfm2: unsupported batch layout for shortconv")
}
bcx := sc.InProj.Forward(ctx, hiddenStates).Reshape(ctx, 3*hiddenSize, seqTokens, nSeqs)
elementSize := bcx.Stride(0)
b := bcx.View(ctx, 0*hiddenSize*elementSize, hiddenSize, bcx.Stride(1), seqTokens, bcx.Stride(2), nSeqs)
c := bcx.View(ctx, 1*hiddenSize*elementSize, hiddenSize, bcx.Stride(1), seqTokens, bcx.Stride(2), nSeqs)
x := bcx.View(ctx, 2*hiddenSize*elementSize, hiddenSize, bcx.Stride(1), seqTokens, bcx.Stride(2), nSeqs)
bx := b.Mul(ctx, x).Permute(ctx, 1, 0, 2, 3)
state, err := cache.ConvState(ctx, layer)
if err != nil {
panic("lfm2: failed to get conv state: " + err.Error())
}
sx := state.Concat(ctx, bx, 0)
convOut := sx.SSMConv(ctx, sc.Conv.Weight)
y := c.Mul(ctx, convOut)
dConv := sx.Dim(0) - seqTokens
cache.UpdateConvState(ctx, layer, sx.Slice(ctx, 0, sx.Dim(0)-dConv, sx.Dim(0), 1))
return sc.OutProj.Forward(ctx, y.Reshape(ctx, hiddenSize, seqTokens*nSeqs))
}

View File

@@ -7,7 +7,9 @@ import (
_ "github.com/ollama/ollama/model/models/gemma2"
_ "github.com/ollama/ollama/model/models/gemma3"
_ "github.com/ollama/ollama/model/models/gemma3n"
_ "github.com/ollama/ollama/model/models/glm4moelite"
_ "github.com/ollama/ollama/model/models/gptoss"
_ "github.com/ollama/ollama/model/models/lfm2"
_ "github.com/ollama/ollama/model/models/llama"
_ "github.com/ollama/ollama/model/models/llama4"
_ "github.com/ollama/ollama/model/models/mistral3"

410
model/parsers/glm46.go Normal file
View File

@@ -0,0 +1,410 @@
package parsers
import (
"context"
"encoding/xml"
"fmt"
"log/slog"
"strings"
"unicode"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/logutil"
)
type glm46ParserState int
const (
glm46ParserState_LookingForThinkingOpen glm46ParserState = iota
glm46ParserState_ThinkingStartedEatingWhitespace
glm46ParserState_CollectingThinking
glm46ParserState_ThinkingDoneEatingWhitespace
glm46ParserState_CollectingContent
glm46ParserState_ToolStartedEatingWhitespace
glm46ParserState_CollectingToolContent
)
const (
glm46ThinkingOpenTag = "<think>"
glm46ThinkingCloseTag = "</think>"
glm46ToolOpenTag = "<tool_call>"
glm46ToolCloseTag = "</tool_call>"
)
type GLM46Parser struct {
state glm46ParserState
buffer strings.Builder
tools []api.Tool
}
func (p *GLM46Parser) HasToolSupport() bool {
return true
}
func (p *GLM46Parser) HasThinkingSupport() bool {
return true
}
// func (p *GLM46Parser) Init(tools []api.Tool, lastMessage *api.Message) []api.Tool {
func (p *GLM46Parser) Init(tools []api.Tool, lastMessage *api.Message, thinkValue *api.ThinkValue) []api.Tool {
p.tools = tools
return tools
}
type glm46Event interface {
isGLM46Event()
}
type glm46EventContent struct {
content string
}
func (glm46EventContent) isGLM46Event() {}
type glm46EventRawToolCall struct {
raw string
}
func (glm46EventRawToolCall) isGLM46Event() {}
type glm46EventThinkingContent struct {
content string
}
func (glm46EventThinkingContent) isGLM46Event() {}
func (p *GLM46Parser) Add(s string, done bool) (content string, thinking string, calls []api.ToolCall, err error) {
p.buffer.WriteString(s)
events := p.parseEvents()
var toolCalls []api.ToolCall
var contentSb strings.Builder
var thinkingSb strings.Builder
for _, event := range events {
switch event := event.(type) {
case glm46EventRawToolCall:
toolCall, err := parseGLM46ToolCall(event, p.tools)
if err != nil {
slog.Warn("glm-4.6 tool call parsing failed", "error", err)
return "", "", nil, err
}
toolCalls = append(toolCalls, toolCall)
case glm46EventThinkingContent:
thinkingSb.WriteString(event.content)
case glm46EventContent:
// TODO(drifkin): if the same turn contains multiple interleaved content
// events, we naively append them together here.
contentSb.WriteString(event.content)
}
}
return contentSb.String(), thinkingSb.String(), toolCalls, nil
}
func (p *GLM46Parser) parseEvents() []glm46Event {
var all []glm46Event
keepLooping := true
for keepLooping {
var events []glm46Event
events, keepLooping = p.eat()
if len(events) > 0 {
all = append(all, events...)
}
}
if len(all) > 0 {
slog.Log(context.TODO(), logutil.LevelTrace, "glm-4.6 events parsed", "events", all, "state", p.state, "buffer", p.buffer.String())
}
return all
}
// eatLeadingWhitespaceAndTransitionTo consumes leading whitespace from the buffer
// and transitions to the next state. Returns (nil, false) if only whitespace remains
// in the buffer (needs more input), or (nil, true) if we successfully transitioned.
func (p *GLM46Parser) eatLeadingWhitespaceAndTransitionTo(nextState glm46ParserState) ([]glm46Event, bool) {
trimmed := strings.TrimLeftFunc(p.buffer.String(), unicode.IsSpace)
p.buffer.Reset()
if trimmed == "" {
return nil, false // Still only whitespace, keep waiting for more input
}
p.state = nextState
p.buffer.WriteString(trimmed)
return nil, true // Successfully transitioned
}
// glm46SplitAtTag splits the buffer at the given tag, returns the content before (trimmed of trailing whitespace),
// the content after (optionally trimmed of leading whitespace), and updates the buffer
func glm46SplitAtTag(p *GLM46Parser, tag string, trimAfter bool) (string, string) {
split := strings.SplitN(p.buffer.String(), tag, 2)
before := split[0]
before = strings.TrimRightFunc(before, unicode.IsSpace)
after := split[1]
if trimAfter {
after = strings.TrimLeftFunc(after, unicode.IsSpace)
}
p.buffer.Reset()
p.buffer.WriteString(after)
return before, after
}
func (p *GLM46Parser) eat() ([]glm46Event, bool) {
var events []glm46Event
switch p.state {
case glm46ParserState_LookingForThinkingOpen:
trimmed := strings.TrimLeftFunc(p.buffer.String(), unicode.IsSpace)
if strings.HasPrefix(trimmed, glm46ThinkingOpenTag) {
// Found <think> opening tag
after := strings.TrimPrefix(trimmed, glm46ThinkingOpenTag)
after = strings.TrimLeftFunc(after, unicode.IsSpace)
p.buffer.Reset()
p.buffer.WriteString(after)
if after == "" {
p.state = glm46ParserState_ThinkingStartedEatingWhitespace
} else {
p.state = glm46ParserState_CollectingThinking
}
return events, true
} else if strings.HasPrefix(glm46ThinkingOpenTag, trimmed) {
// Partial opening tag seen, keep accumulating
return events, false
} else if trimmed == "" {
// Only whitespace, keep accumulating
return events, false
} else {
// No thinking tag found, skip to content collection
p.state = glm46ParserState_CollectingContent
// Don't trim - we want to keep the original content
return events, true
}
case glm46ParserState_ThinkingStartedEatingWhitespace:
return p.eatLeadingWhitespaceAndTransitionTo(glm46ParserState_CollectingThinking)
case glm46ParserState_CollectingThinking:
acc := p.buffer.String()
if strings.Contains(acc, glm46ThinkingCloseTag) {
thinking, remaining := glm46SplitAtTag(p, glm46ThinkingCloseTag, true)
if len(thinking) > 0 {
events = append(events, glm46EventThinkingContent{content: thinking})
}
if remaining == "" {
p.state = glm46ParserState_ThinkingDoneEatingWhitespace
} else {
p.state = glm46ParserState_CollectingContent
}
return events, true
} else if overlapLen := overlap(acc, glm46ThinkingCloseTag); overlapLen > 0 {
// Partial closing tag - withhold it along with any trailing whitespace before it
beforePartialTag := acc[:len(acc)-overlapLen]
trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
unambiguous := acc[:ambiguousStart]
ambiguous := acc[ambiguousStart:]
p.buffer.Reset()
p.buffer.WriteString(ambiguous)
if len(unambiguous) > 0 {
events = append(events, glm46EventThinkingContent{content: unambiguous})
}
return events, false
} else {
// Pure thinking content - withhold trailing whitespace (might precede closing tag)
whitespaceLen := trailingWhitespaceLen(acc)
ambiguousStart := len(acc) - whitespaceLen
unambiguous := acc[:ambiguousStart]
ambiguous := acc[ambiguousStart:]
p.buffer.Reset()
p.buffer.WriteString(ambiguous)
if len(unambiguous) > 0 {
events = append(events, glm46EventThinkingContent{content: unambiguous})
}
return events, false
}
case glm46ParserState_ThinkingDoneEatingWhitespace:
return p.eatLeadingWhitespaceAndTransitionTo(glm46ParserState_CollectingContent)
case glm46ParserState_CollectingContent:
if strings.Contains(p.buffer.String(), glm46ToolOpenTag) {
before, after := glm46SplitAtTag(p, glm46ToolOpenTag, true)
if len(before) > 0 {
events = append(events, glm46EventContent{content: before})
}
if after == "" {
p.state = glm46ParserState_ToolStartedEatingWhitespace
} else {
p.state = glm46ParserState_CollectingToolContent
}
return events, true
} else if overlapLen := overlap(p.buffer.String(), glm46ToolOpenTag); overlapLen > 0 {
beforePartialTag := p.buffer.String()[:len(p.buffer.String())-overlapLen]
trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
unambiguous := p.buffer.String()[:ambiguousStart]
ambiguous := p.buffer.String()[ambiguousStart:]
p.buffer.Reset()
p.buffer.WriteString(ambiguous)
if len(unambiguous) > 0 {
events = append(events, glm46EventContent{content: unambiguous})
}
return events, false
} else {
whitespaceLen := trailingWhitespaceLen(p.buffer.String())
ambiguousStart := len(p.buffer.String()) - whitespaceLen
unambiguous := p.buffer.String()[:ambiguousStart]
ambiguous := p.buffer.String()[ambiguousStart:]
p.buffer.Reset()
p.buffer.WriteString(ambiguous)
if len(unambiguous) > 0 {
events = append(events, glm46EventContent{content: unambiguous})
}
return events, false
}
case glm46ParserState_ToolStartedEatingWhitespace:
return p.eatLeadingWhitespaceAndTransitionTo(glm46ParserState_CollectingToolContent)
case glm46ParserState_CollectingToolContent:
acc := p.buffer.String()
if strings.Contains(acc, glm46ToolCloseTag) {
toolContent, _ := glm46SplitAtTag(p, glm46ToolCloseTag, true)
if len(toolContent) == 0 {
slog.Warn("glm46 tool call closing tag found but no content before it")
}
events = append(events, glm46EventRawToolCall{raw: toolContent})
p.state = glm46ParserState_CollectingContent
return events, true
} else {
// Keep accumulating - tool calls are not streamed
// We just wait for the closing tag
return events, false
}
default:
panic("unreachable")
}
}
// GLMToolCallXML represents the structure of a GLM-4.6 tool call for XML parsing
type GLMToolCallXML struct {
XMLName xml.Name `xml:"tool_call"`
Content string `xml:",chardata"` // Function name (text nodes between tags)
Keys []string `xml:"arg_key"` // All arg_key elements in document order
Values []string `xml:"arg_value"` // All arg_value elements in document order
}
// escapeGLM46Content escapes XML entities in text content while preserving arg_key/arg_value tags
func escapeGLM46Content(s string) string {
var result strings.Builder
inTag := false
for i := range len(s) {
ch := s[i]
if ch == '<' {
// Check if this is a known tag
if strings.HasPrefix(s[i:], "<arg_key>") ||
strings.HasPrefix(s[i:], "</arg_key>") ||
strings.HasPrefix(s[i:], "<arg_value>") ||
strings.HasPrefix(s[i:], "</arg_value>") {
inTag = true
}
}
if inTag {
result.WriteByte(ch)
if ch == '>' {
inTag = false
}
} else {
// Escape special characters in text content
switch ch {
case '&':
result.WriteString("&amp;")
case '<':
result.WriteString("&lt;")
case '>':
result.WriteString("&gt;")
default:
result.WriteByte(ch)
}
}
}
return result.String()
}
func parseGLM46ToolCall(raw glm46EventRawToolCall, tools []api.Tool) (api.ToolCall, error) {
// Escape any unescaped entities in text content
// We need to escape text between tags, but not the tags themselves
escaped := escapeGLM46Content(raw.raw)
// Wrap the content in a root element to make it valid XML
xmlString := "<tool_call>" + escaped + "</tool_call>"
// Parse XML into struct
var parsed GLMToolCallXML
if err := xml.Unmarshal([]byte(xmlString), &parsed); err != nil {
return api.ToolCall{}, fmt.Errorf("failed to parse XML: %w", err)
}
// Extract and trim function name
functionName := strings.TrimSpace(parsed.Content)
if functionName == "" {
return api.ToolCall{}, fmt.Errorf("empty function name")
}
// Verify keys and values are paired correctly
if len(parsed.Keys) != len(parsed.Values) {
return api.ToolCall{}, fmt.Errorf("mismatched arg_key and arg_value counts: %d keys, %d values", len(parsed.Keys), len(parsed.Values))
}
// Find the matching tool to get parameter types
var matchedTool *api.Tool
for i := range tools {
if tools[i].Function.Name == functionName {
matchedTool = &tools[i]
break
}
}
// Build arguments map by pairing keys and values
toolCall := api.ToolCall{
Function: api.ToolCallFunction{
Name: functionName,
Arguments: api.NewToolCallFunctionArguments(),
},
}
for i := range parsed.Keys {
key := strings.TrimSpace(parsed.Keys[i])
value := parsed.Values[i] // Don't trim here - parseValue handles it
// Look up parameter type
var paramType api.PropertyType
if matchedTool != nil && matchedTool.Function.Parameters.Properties != nil {
if prop, ok := matchedTool.Function.Parameters.Properties.Get(key); ok {
// Handle anyOf by collecting all types from the union
if len(prop.AnyOf) > 0 {
for _, anyOfProp := range prop.AnyOf {
paramType = append(paramType, anyOfProp.Type...)
}
} else {
paramType = prop.Type
}
}
}
// Parse value with type coercion
toolCall.Function.Arguments.Set(key, parseValue(value, paramType))
}
return toolCall, nil
}

862
model/parsers/glm46_test.go Normal file
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@@ -0,0 +1,862 @@
package parsers
import (
"encoding/xml"
"reflect"
"testing"
"github.com/ollama/ollama/api"
)
func TestGLM46ParserStreaming(t *testing.T) {
type step struct {
input string
wantEvents []glm46Event
}
cases := []struct {
desc string
steps []step
only bool
}{
{
desc: "leading whitespace before think tag",
steps: []step{
{
input: " \n\t ",
wantEvents: []glm46Event{},
},
{
input: "<think>thinking</think>",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "thinking"}},
},
},
},
{
desc: "think tag with whitespace inside",
steps: []step{
{
input: "<think> \n thinking content \n </think>regular content",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking content"},
glm46EventContent{content: "regular content"},
},
},
},
},
{
desc: "tool call with leading whitespace after opening tag",
steps: []step{
{
input: "<think></think><tool_call> \n test \n </tool_call>",
wantEvents: []glm46Event{
glm46EventRawToolCall{raw: "test"},
},
},
},
},
{
desc: "simple thinking then content",
steps: []step{
{
input: "<think>I am thinking</think>Now I respond",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "I am thinking"},
glm46EventContent{content: "Now I respond"},
},
},
},
},
{
desc: "streamed thinking content",
steps: []step{
{
input: "<think>hello",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "hello"}},
},
{
input: " world",
wantEvents: []glm46Event{glm46EventThinkingContent{content: " world"}},
},
{
input: "</think>content",
wantEvents: []glm46Event{
glm46EventContent{content: "content"},
},
},
},
},
{
desc: "content before tool call",
steps: []step{
{
input: "<think>Let me call a tool</think>here is text<tool_call>",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "Let me call a tool"},
glm46EventContent{content: "here is text"},
},
},
{
input: "function_name\n<arg_key>param</arg_key>\n<arg_value>value</arg_value>\n</tool_call>",
wantEvents: []glm46Event{
glm46EventRawToolCall{raw: "function_name\n<arg_key>param</arg_key>\n<arg_value>value</arg_value>"},
},
},
},
},
{
desc: "tool call with content after",
steps: []step{
{
input: "<think>thinking</think><tool_call>test</tool_call>after tool",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking"},
glm46EventRawToolCall{raw: "test"},
glm46EventContent{content: "after tool"},
},
},
},
},
{
desc: "trailing whitespace between content and tool call is trimmed",
steps: []step{
{
input: "<think>thinking</think>content\n \t <tool_call>test</tool_call>",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking"},
glm46EventContent{content: "content"},
glm46EventRawToolCall{raw: "test"},
},
},
},
},
{
desc: "trailing whitespace between tool call and content is trimmed",
steps: []step{
{
input: "<think>think</think><tool_call>test</tool_call>\n\t after",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "think"},
glm46EventRawToolCall{raw: "test"},
glm46EventContent{content: "after"},
},
},
},
},
{
desc: "split thinking close tag",
steps: []step{
{
input: "<think>thinking content</th",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "thinking content"}},
},
{
input: "ink>after",
wantEvents: []glm46Event{
glm46EventContent{content: "after"},
},
},
},
},
{
desc: "split thinking open tag",
steps: []step{
{
input: " <thi",
wantEvents: []glm46Event{},
},
{
input: "nk>content</think>",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "content"}},
},
},
},
{
desc: "split tool open tag",
steps: []step{
{
input: "<think>think</think>content<tool",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "think"}, glm46EventContent{content: "content"}},
},
{
input: "_call>inside",
wantEvents: []glm46Event{},
},
{
input: "</tool_call>",
wantEvents: []glm46Event{
glm46EventRawToolCall{raw: "inside"},
},
},
},
},
{
desc: "partial thinking close tag fakeout",
steps: []step{
{
input: "<think>content</th",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "content"}},
},
{
input: "ought more",
wantEvents: []glm46Event{glm46EventThinkingContent{content: "</thought more"}},
},
},
},
{
desc: "partial thinking open tag fakeout",
steps: []step{
{
input: " <thi",
wantEvents: []glm46Event{},
},
{
input: "nking is fun",
wantEvents: []glm46Event{
glm46EventContent{content: " <thinking is fun"},
},
},
},
},
{
desc: "partial tool open tag fakeout",
steps: []step{
{
input: "<think></think>content\n<tool",
wantEvents: []glm46Event{
glm46EventContent{content: "content"},
},
},
{
input: " fakeout",
wantEvents: []glm46Event{
glm46EventContent{content: "\n<tool fakeout"},
},
},
},
},
{
desc: "partial tool close tag fakeout",
steps: []step{
{
input: "<think></think><tool_call>content</tool",
wantEvents: []glm46Event{},
},
{
input: " fakeout",
wantEvents: []glm46Event{},
},
{
input: "</tool_call>",
wantEvents: []glm46Event{
glm46EventRawToolCall{raw: "content</tool fakeout"},
},
},
},
},
{
desc: "empty thinking tag",
steps: []step{
{
input: "<think></think>content here",
wantEvents: []glm46Event{
glm46EventContent{content: "content here"},
},
},
},
},
{
desc: "multiple tool calls in sequence",
steps: []step{
{
input: "<think>think</think><tool_call>first</tool_call>between<tool_call>second</tool_call>end",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "think"},
glm46EventRawToolCall{raw: "first"},
glm46EventContent{content: "between"},
glm46EventRawToolCall{raw: "second"},
glm46EventContent{content: "end"},
},
},
},
},
{
desc: "no thinking tag - direct to content",
steps: []step{
{
input: "just content here",
wantEvents: []glm46Event{
glm46EventContent{content: "just content here"},
},
},
},
},
{
desc: "no thinking tag - skip to content then tool call",
steps: []step{
{
input: "Here's the answer:<tool_call>test</tool_call>done",
wantEvents: []glm46Event{
glm46EventContent{content: "Here's the answer:"},
glm46EventRawToolCall{raw: "test"},
glm46EventContent{content: "done"},
},
},
},
},
{
desc: "no thinking tag - whitespace preserved when no tags",
steps: []step{
{
input: " \n content with leading whitespace",
wantEvents: []glm46Event{
glm46EventContent{content: " \n content with leading whitespace"},
},
},
},
},
{
desc: "whitespace after think close tag gets eaten",
steps: []step{
{
input: "<think>thinking</think> \n\t content",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking"},
glm46EventContent{content: "content"},
},
},
},
},
{
desc: "whitespace after tool_call close tag gets eaten",
steps: []step{
{
input: "<think></think><tool_call>test</tool_call> \n\t content",
wantEvents: []glm46Event{
glm46EventRawToolCall{raw: "test"},
glm46EventContent{content: "content"},
},
},
},
},
{
desc: "thinking content withholds trailing whitespace (single chunk)",
steps: []step{
{
input: "<think>thinking content ",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking content"},
},
},
{
input: "</think>after",
wantEvents: []glm46Event{
glm46EventContent{content: "after"},
},
},
},
},
{
desc: "thinking content withholds trailing whitespace with newlines",
steps: []step{
{
input: "<think>thinking\n\n ",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking"},
},
},
{
input: "</think>content",
wantEvents: []glm46Event{
glm46EventContent{content: "content"},
},
},
},
},
{
desc: "thinking content trailing whitespace emitted when more content arrives",
steps: []step{
{
input: "<think>thinking ",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking"},
},
},
{
input: "more thinking",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: " more thinking"},
},
},
{
input: "</think>",
wantEvents: []glm46Event{},
},
},
},
{
desc: "thinking content withholds trailing whitespace before partial close tag",
steps: []step{
{
input: "<think>thinking </th",
wantEvents: []glm46Event{
glm46EventThinkingContent{content: "thinking"},
},
},
{
input: "ink>content",
wantEvents: []glm46Event{
glm46EventContent{content: "content"},
},
},
},
},
}
anyOnlies := false
for _, tc := range cases {
if tc.only {
anyOnlies = true
}
}
for _, tc := range cases {
if anyOnlies && !tc.only {
continue
}
t.Run(tc.desc, func(t *testing.T) {
parser := GLM46Parser{}
for i, step := range tc.steps {
parser.buffer.WriteString(step.input)
gotEvents := parser.parseEvents()
if len(gotEvents) == 0 && len(step.wantEvents) == 0 {
// avoid deep equal on empty vs. nil slices
continue
}
if !reflect.DeepEqual(gotEvents, step.wantEvents) {
t.Errorf("step %d: input %q: got events %#v, want %#v", i, step.input, gotEvents, step.wantEvents)
}
}
})
}
}
// TestGLMToolCallXMLOrderPreservation verifies that xml.Unmarshal preserves
// document order when collecting multiple elements with the same tag name into slices.
// This is a critical assumption for the GLM-4.6 parser's struct-based approach.
func TestGLMToolCallXMLOrderPreservation(t *testing.T) {
testCases := []struct {
name string
xml string
wantKeys []string
wantValues []string
}{
{
name: "alternating keys and values",
xml: `<tool_call>
function_name
<arg_key>first</arg_key>
<arg_value>A</arg_value>
<arg_key>second</arg_key>
<arg_value>B</arg_value>
<arg_key>third</arg_key>
<arg_value>C</arg_value>
</tool_call>`,
wantKeys: []string{"first", "second", "third"},
wantValues: []string{"A", "B", "C"},
},
{
name: "all keys then all values",
xml: `<tool_call>
function_name
<arg_key>key1</arg_key>
<arg_key>key2</arg_key>
<arg_key>key3</arg_key>
<arg_value>val1</arg_value>
<arg_value>val2</arg_value>
<arg_value>val3</arg_value>
</tool_call>`,
wantKeys: []string{"key1", "key2", "key3"},
wantValues: []string{"val1", "val2", "val3"},
},
{
name: "mixed grouping",
xml: `<tool_call>
function_name
<arg_key>a</arg_key>
<arg_value>1</arg_value>
<arg_key>b</arg_key>
<arg_key>c</arg_key>
<arg_value>2</arg_value>
<arg_value>3</arg_value>
</tool_call>`,
wantKeys: []string{"a", "b", "c"},
wantValues: []string{"1", "2", "3"},
},
{
name: "reverse order - all values then all keys",
xml: `<tool_call>
function_name
<arg_value>X</arg_value>
<arg_value>Y</arg_value>
<arg_value>Z</arg_value>
<arg_key>x</arg_key>
<arg_key>y</arg_key>
<arg_key>z</arg_key>
</tool_call>`,
wantKeys: []string{"x", "y", "z"},
wantValues: []string{"X", "Y", "Z"},
},
}
for _, tc := range testCases {
t.Run(tc.name, func(t *testing.T) {
var parsed GLMToolCallXML
err := xml.Unmarshal([]byte(tc.xml), &parsed)
if err != nil {
t.Fatalf("failed to unmarshal XML: %v", err)
}
if !reflect.DeepEqual(parsed.Keys, tc.wantKeys) {
t.Errorf("Keys order mismatch:\ngot: %v\nwant: %v", parsed.Keys, tc.wantKeys)
}
if !reflect.DeepEqual(parsed.Values, tc.wantValues) {
t.Errorf("Values order mismatch:\ngot: %v\nwant: %v", parsed.Values, tc.wantValues)
}
})
}
}
func TestGLM46ToolCallParsing(t *testing.T) {
type testCase struct {
name string
rawToolCall string
tools []api.Tool
wantToolCall api.ToolCall
}
cases := []testCase{
{
name: "simple tool call",
tools: []api.Tool{},
rawToolCall: `get-current-weather
<arg_key>location</arg_key>
<arg_value>New York, NY</arg_value>
<arg_key>unit</arg_key>
<arg_value>celsius</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "get-current-weather",
Arguments: args(`{"location": "New York, NY", "unit": "celsius"}`),
},
},
},
{
name: "tool call with typed parameters",
tools: []api.Tool{
tool("calculate", map[string]api.ToolProperty{
"x": {Type: api.PropertyType{"number"}},
"y": {Type: api.PropertyType{"integer"}},
"enabled": {Type: api.PropertyType{"boolean"}},
"items": {Type: api.PropertyType{"array"}},
}),
},
rawToolCall: `calculate
<arg_key>x</arg_key>
<arg_value>3.14</arg_value>
<arg_key>y</arg_key>
<arg_value>42</arg_value>
<arg_key>enabled</arg_key>
<arg_value>true</arg_value>
<arg_key>items</arg_key>
<arg_value>["a", "b", "c"]</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "calculate",
Arguments: args(`{"enabled": true, "items": ["a", "b", "c"], "x": 3.14, "y": 42}`),
},
},
},
{
name: "function name with whitespace",
tools: []api.Tool{},
rawToolCall: ` get-weather
<arg_key>city</arg_key>
<arg_value>Paris</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "get-weather",
Arguments: args(`{"city": "Paris"}`),
},
},
},
{
name: "values with special characters",
tools: []api.Tool{},
rawToolCall: `execute-command
<arg_key>command</arg_key>
<arg_value>ls && echo "done"</arg_value>
<arg_key>message</arg_key>
<arg_value>a < b and c > d</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "execute-command",
Arguments: args(`{"command": "ls && echo \"done\"", "message": "a < b and c > d"}`),
},
},
},
{
name: "unicode in function names and values",
tools: []api.Tool{},
rawToolCall: `获取天气
<arg_key>城市</arg_key>
<arg_value>北京</arg_value>
<arg_key>message</arg_key>
<arg_value>Hello! 你好! 🌟</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "获取天气",
Arguments: args(`{"message": "Hello! 你好! 🌟", "城市": "北京"}`),
},
},
},
{
name: "empty value",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>param1</arg_key>
<arg_value></arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"param1": ""}`),
},
},
},
{
name: "special chars in arg_key names",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>param<1></arg_key>
<arg_value>value1</arg_value>
<arg_key>a&b</arg_key>
<arg_value>value2</arg_value>
<arg_key>x>y</arg_key>
<arg_value>value3</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"a&b": "value2", "param<1>": "value1", "x>y": "value3"}`),
},
},
},
{
name: "multiple consecutive ampersands",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>param</arg_key>
<arg_value>test &&&& more</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"param": "test &&&& more"}`),
},
},
},
{
name: "mixed special chars together",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>param</arg_key>
<arg_value><>&<>&</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"param": "<>&<>&"}`),
},
},
},
{
name: "newlines and tabs in parameter values",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>multiline</arg_key>
<arg_value>line1
indented line2
line3</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"multiline": "line1\n\tindented line2\nline3"}`),
},
},
},
{
name: "single and double quotes in values",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>quotes</arg_key>
<arg_value>She said "Hello's there!"</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"quotes": "She said \"Hello's there!\""}`),
},
},
},
{
name: "CDATA-like content that should be treated as text",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>cdata</arg_key>
<arg_value><![CDATA[not actual cdata]]></arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"cdata": "<![CDATA[not actual cdata]]>"}`),
},
},
},
{
name: "all special XML entities",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>entities</arg_key>
<arg_value>&lt;&gt;&amp;&apos;&quot;</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"entities": "&lt;&gt;&amp;&apos;&quot;"}`),
},
},
},
{
name: "order preservation with multiple parameters",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>first</arg_key>
<arg_value>value1</arg_value>
<arg_key>second</arg_key>
<arg_value>value2</arg_value>
<arg_key>third</arg_key>
<arg_value>value3</arg_value>
<arg_key>fourth</arg_key>
<arg_value>value4</arg_value>
<arg_key>fifth</arg_key>
<arg_value>value5</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
Arguments: args(`{"fifth": "value5", "first": "value1", "fourth": "value4", "second": "value2", "third": "value3"}`),
},
},
},
{
name: "order preservation with identical key names but different positions",
tools: []api.Tool{},
rawToolCall: `test-function
<arg_key>param</arg_key>
<arg_value>first occurrence</arg_value>
<arg_key>other</arg_key>
<arg_value>middle</arg_value>
<arg_key>param</arg_key>
<arg_value>second occurrence</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test-function",
// Later occurrence should overwrite earlier one
Arguments: args(`{"other": "middle", "param": "second occurrence"}`),
},
},
},
{
name: "array with mixed types",
tools: []api.Tool{
tool("process", map[string]api.ToolProperty{
"items": {Type: api.PropertyType{"array"}},
}),
},
rawToolCall: `process
<arg_key>items</arg_key>
<arg_value>[1, "hello", true, null]</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "process",
Arguments: args(`{"items": [1, "hello", true, null]}`),
},
},
},
{
name: "empty array",
tools: []api.Tool{
tool("test", map[string]api.ToolProperty{
"tags": {Type: api.PropertyType{"array"}},
}),
},
rawToolCall: `test
<arg_key>tags</arg_key>
<arg_value>[]</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "test",
Arguments: args(`{"tags": []}`),
},
},
},
{
name: "anyOf array or string - with array of objects",
tools: []api.Tool{
tool("TodoWrite", map[string]api.ToolProperty{
"todos": {AnyOf: []api.ToolProperty{{Type: api.PropertyType{"array"}}, {Type: api.PropertyType{"string"}}}},
}),
},
// <tool_call>TodoWrite
// <arg_key>todos</arg_key>
// <arg_value>[{"content": "Set up HTML file and basic structure", "id": "1", "priority": "high", "status": "pending"}, {"content": "Create 3D scene with Three.js", "id": "2", "priority": "high", "status": "pending"}, {"content": "Implement terrain generation with blocks", "id": "3", "priority": "high", "status": "pending"}, {"content": "Add player controls (movement, camera)", "id": "4", "priority": "high", "status": "pending"}, {"content": "Implement block placement/destruction", "id": "5", "priority": "medium", "status": "pending"}, {"content": "Add lighting and textures", "id": "6", "priority": "medium", "status": "pending"}, {"content": "Test and optimize performance", "id": "7", "priority": "low", "status": "pending"}]</arg_value>
// </tool_call>
rawToolCall: `TodoWrite
<arg_key>todos</arg_key>
<arg_value>[{"content": "task 1", "status": "pending", "priority": "high", "id": "1"}, {"content": "task 2", "status": "completed", "priority": "low", "id": "2"}]</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "TodoWrite",
Arguments: args(`{"todos": [{"content": "task 1", "id": "1", "priority": "high", "status": "pending"}, {"content": "task 2", "id": "2", "priority": "low", "status": "completed"}]}`),
},
},
},
{
name: "anyOf array or string - with plain string",
tools: []api.Tool{
tool("TodoWrite", map[string]api.ToolProperty{
"todos": {Type: api.PropertyType{"array", "string"}},
}),
},
rawToolCall: `TodoWrite
<arg_key>todos</arg_key>
<arg_value>Error: could not load todos</arg_value>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "TodoWrite",
Arguments: args(`{"todos": "Error: could not load todos"}`),
},
},
},
}
for i, tc := range cases {
t.Run(tc.name, func(t *testing.T) {
gotToolCall, err := parseGLM46ToolCall(glm46EventRawToolCall{raw: tc.rawToolCall}, tc.tools)
if err != nil {
t.Errorf("case %d (%s): %v", i, tc.name, err)
}
if !toolCallEqual(gotToolCall, tc.wantToolCall) {
t.Errorf("case %d (%s): got tool call %#v, want %#v", i, tc.name, gotToolCall, tc.wantToolCall)
}
})
}
}

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