readme: simplify readme

.github/workflows/release.yaml

@@ -65,36 +65,14 @@ jobs:
             arch: amd64
             preset: 'CUDA 12'
             install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
             cuda-version: '12.8'
             flags: ''
-            runner_dir: 'cuda_v12'
-          - os: windows
-            arch: amd64
-            preset: 'CUDA 13'
-            install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
-              - '"crt"'
-              - '"nvvm"'
-              - '"nvptxcompiler"'
-            cuda-version: '13.0'
-            flags: ''
-            runner_dir: 'cuda_v13'
           - os: windows
             arch: amd64
             preset: 'ROCm 6'
             install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
             rocm-version: '6.2'
             flags: '-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
-            runner_dir: ''
     runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
     environment: release
     env:
@@ -118,7 +96,7 @@ jobs:
           $ErrorActionPreference = "Stop"
           if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
             Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
+            $subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
             Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
           }
 
@@ -160,7 +138,7 @@ jobs:
         run: |
           Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
           Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
-          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }} -DOLLAMA_RUNNER_DIR="${{ matrix.runner_dir }}"
+          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }}
           cmake --build --parallel --preset "${{ matrix.preset }}"
           cmake --install build --component "${{ startsWith(matrix.preset, 'CUDA ') && 'CUDA' || startsWith(matrix.preset, 'ROCm ') && 'HIP' || 'CPU' }}" --strip --parallel 8
         env:
@@ -254,7 +232,7 @@ jobs:
             case "$COMPONENT" 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/cuda_sbsa)      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 ;;

.github/workflows/test.yaml

@@ -46,7 +46,7 @@ jobs:
         include:
           - preset: CPU
           - preset: CUDA
-            container: nvidia/cuda:13.0.0-devel-ubuntu22.04
+            container: nvidia/cuda:12.8.1-devel-ubuntu22.04
             flags: '-DCMAKE_CUDA_ARCHITECTURES=87'
           - preset: ROCm
             container: rocm/dev-ubuntu-22.04:6.1.2
@@ -78,17 +78,8 @@ jobs:
         include:
           - preset: CPU
           - preset: CUDA
-            install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
+            install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
             flags: '-DCMAKE_CUDA_ARCHITECTURES=80'
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
-              - '"crt"'
-              - '"nvvm"'
-              - '"nvptxcompiler"'
-            cuda-version: '13.0'
           - preset: ROCm
             install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
             flags: '-DAMDGPU_TARGETS=gfx1010 -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
@@ -111,8 +102,7 @@ jobs:
           $ErrorActionPreference = "Stop"
           if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
             Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
-            Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
+            Start-Process -FilePath .\install.exe -ArgumentList (@("-s", "cudart_12.8", "nvcc_12.8", "cublas_12.8", "cublas_dev_12.8")) -NoNewWindow -Wait
           }
 
           $cudaPath = (Resolve-Path "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*").path

CMakeLists.txt

@@ -38,7 +38,7 @@ if (CMAKE_OSX_ARCHITECTURES MATCHES "x86_64")
 endif()
 
 set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
-set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama/${OLLAMA_RUNNER_DIR})
+set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama)
 
 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY         ${OLLAMA_BUILD_DIR})
 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_DEBUG   ${OLLAMA_BUILD_DIR})
@@ -81,7 +81,7 @@ if(CMAKE_CUDA_COMPILER)
     add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cuda)
     install(TARGETS ggml-cuda
         RUNTIME_DEPENDENCIES
-            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
+            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_LIBRARY_DIR}
             PRE_INCLUDE_REGEXES cublas cublasLt cudart
             PRE_EXCLUDE_REGEXES ".*"
         RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA

CMakePresets.json

@@ -18,14 +18,6 @@
       "name": "CUDA",
       "inherits": [ "Default" ]
     },
-    {
-      "name": "CUDA 11",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50-virtual;60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual",
-        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
-      }
-    },
     {
       "name": "CUDA 12",
       "inherits": [ "CUDA" ],
@@ -34,14 +26,6 @@
         "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
       }
     },
-    {
-      "name": "CUDA 13",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;110-virtual;120-virtual;121-virtual",
-        "CMAKE_CUDA_FLAGS": "-t 2"
-      }
-    },
     {
       "name": "JetPack 5",
       "inherits": [ "CUDA" ],
@@ -88,21 +72,11 @@
       "configurePreset": "CUDA",
       "targets": [ "ggml-cuda" ]
     },
-    {
-      "name": "CUDA 11",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "CUDA 11"
-    },
     {
       "name": "CUDA 12",
       "inherits": [ "CUDA" ],
       "configurePreset": "CUDA 12"
     },
-    {
-      "name": "CUDA 13",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "CUDA 13"
-    },
     {
       "name": "JetPack 5",
       "inherits": [ "CUDA" ],

Dockerfile

@@ -1,7 +1,6 @@
 # vim: filetype=dockerfile
 
 ARG FLAVOR=${TARGETARCH}
-ARG PARALLEL=8
 
 ARG ROCMVERSION=6.3.3
 ARG JETPACK5VERSION=r35.4.1
@@ -35,51 +34,26 @@ ENV LDFLAGS=-s
 FROM base AS cpu
 RUN dnf install -y gcc-toolset-11-gcc gcc-toolset-11-gcc-c++
 ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
     cmake --preset 'CPU' \
-        && cmake --build --parallel ${PARALLEL} --preset 'CPU' \
-        && cmake --install build --component CPU --strip --parallel ${PARALLEL}
-
-FROM base AS cuda-11
-ARG CUDA11VERSION=11.8
-RUN dnf install -y cuda-toolkit-${CUDA11VERSION//./-}
-ENV PATH=/usr/local/cuda-11/bin:$PATH
-ARG PARALLEL
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 11' -DOLLAMA_RUNNER_DIR="cuda_v11" \
-        && cmake --build --parallel ${PARALLEL} --preset 'CUDA 11' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'CPU' \
+        && cmake --install build --component CPU --strip --parallel 8
 
 FROM base AS cuda-12
 ARG CUDA12VERSION=12.8
 RUN dnf install -y cuda-toolkit-${CUDA12VERSION//./-}
 ENV PATH=/usr/local/cuda-12/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 12' -DOLLAMA_RUNNER_DIR="cuda_v12"\
-        && cmake --build --parallel ${PARALLEL} --preset 'CUDA 12' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
-
-
-FROM base AS cuda-13
-ARG CUDA13VERSION=13.0
-RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-}
-ENV PATH=/usr/local/cuda-13/bin:$PATH
-ARG PARALLEL
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 13' -DOLLAMA_RUNNER_DIR="cuda_v13" \
-        && cmake --build --parallel ${PARALLEL} --preset 'CUDA 13' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
-
+    cmake --preset 'CUDA 12' \
+        && cmake --build --parallel --preset 'CUDA 12' \
+        && cmake --install build --component CUDA --strip --parallel 8
 
 FROM base AS rocm-6
 ENV PATH=/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:/opt/rocm/hcc/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
     cmake --preset 'ROCm 6' \
-        && cmake --build --parallel ${PARALLEL} --preset 'ROCm 6' \
-        && cmake --install build --component HIP --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'ROCm 6' \
+        && cmake --install build --component HIP --strip --parallel 8
 
 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
 ARG CMAKEVERSION
@@ -87,11 +61,10 @@ RUN apt-get update && apt-get install -y curl ccache \
     && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
 COPY CMakeLists.txt CMakePresets.json .
 COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
     cmake --preset 'JetPack 5' \
-        && cmake --build --parallel ${PARALLEL} --preset 'JetPack 5' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'JetPack 5' \
+        && cmake --install build --component CUDA --strip --parallel 8
 
 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
 ARG CMAKEVERSION
@@ -99,11 +72,10 @@ RUN apt-get update && apt-get install -y curl ccache \
     && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
 COPY CMakeLists.txt CMakePresets.json .
 COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
     cmake --preset 'JetPack 6' \
-        && cmake --build --parallel ${PARALLEL} --preset 'JetPack 6' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'JetPack 6' \
+        && cmake --install build --component CUDA --strip --parallel 8
 
 FROM base AS build
 WORKDIR /go/src/github.com/ollama/ollama
@@ -120,14 +92,10 @@ RUN --mount=type=cache,target=/root/.cache/go-build \
     go build -trimpath -buildmode=pie -o /bin/ollama .
 
 FROM --platform=linux/amd64 scratch AS amd64
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
+COPY --from=cuda-12 dist/lib/ollama /lib/ollama
 
 FROM --platform=linux/arm64 scratch AS arm64
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
+COPY --from=cuda-12 dist/lib/ollama /lib/ollama/cuda_sbsa
 COPY --from=jetpack-5 dist/lib/ollama /lib/ollama/cuda_jetpack5
 COPY --from=jetpack-6 dist/lib/ollama /lib/ollama/cuda_jetpack6
 

README.md

@@ -1,6 +1,6 @@
 <div align="center">
   <a href="https://ollama.com">
-    <img alt="ollama" width="240" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
+    <img width="240" alt="ollama" src="https://github.com/user-attachments/assets/4f2058e5-7da4-43b3-916f-1905abc99d04" />
   </a>
 </div>
 
@@ -46,107 +46,31 @@ To run and chat with [Gemma 3](https://ollama.com/library/gemma3):
 ollama run gemma3
 ```
 
-## Model library
+## Models
 
-Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
+| Model       | Parameters | Size  | Download                 |
+| ----------- | ---------- | ----- | ------------------------ |
+| Gemma 3     | 1B         | 815MB | `ollama run gemma3:1b`   |
+| Gemma 3     | 4B         | 3.3GB | `ollama run gemma3`      |
+| DeepSeek-R1 | 7B         | 4.7GB | `ollama run deepseek-r1` |
+| gpt-oss     | 20B        | 14GB  | `ollama run gpt-oss`     |
 
-Here are some example models that can be downloaded:
-
-| Model              | Parameters | Size  | Download                         |
-| ------------------ | ---------- | ----- | -------------------------------- |
-| Gemma 3            | 1B         | 815MB | `ollama run gemma3:1b`           |
-| Gemma 3            | 4B         | 3.3GB | `ollama run gemma3`              |
-| Gemma 3            | 12B        | 8.1GB | `ollama run gemma3:12b`          |
-| Gemma 3            | 27B        | 17GB  | `ollama run gemma3:27b`          |
-| QwQ                | 32B        | 20GB  | `ollama run qwq`                 |
-| DeepSeek-R1        | 7B         | 4.7GB | `ollama run deepseek-r1`         |
-| DeepSeek-R1        | 671B       | 404GB | `ollama run deepseek-r1:671b`    |
-| Llama 4            | 109B       | 67GB  | `ollama run llama4:scout`        |
-| Llama 4            | 400B       | 245GB | `ollama run llama4:maverick`     |
-| Llama 3.3          | 70B        | 43GB  | `ollama run llama3.3`            |
-| Llama 3.2          | 3B         | 2.0GB | `ollama run llama3.2`            |
-| Llama 3.2          | 1B         | 1.3GB | `ollama run llama3.2:1b`         |
-| Llama 3.2 Vision   | 11B        | 7.9GB | `ollama run llama3.2-vision`     |
-| Llama 3.2 Vision   | 90B        | 55GB  | `ollama run llama3.2-vision:90b` |
-| Llama 3.1          | 8B         | 4.7GB | `ollama run llama3.1`            |
-| Llama 3.1          | 405B       | 231GB | `ollama run llama3.1:405b`       |
-| Phi 4              | 14B        | 9.1GB | `ollama run phi4`                |
-| Phi 4 Mini         | 3.8B       | 2.5GB | `ollama run phi4-mini`           |
-| Mistral            | 7B         | 4.1GB | `ollama run mistral`             |
-| Moondream 2        | 1.4B       | 829MB | `ollama run moondream`           |
-| Neural Chat        | 7B         | 4.1GB | `ollama run neural-chat`         |
-| Starling           | 7B         | 4.1GB | `ollama run starling-lm`         |
-| 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`          |
-
-> [!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.
-
-## Customize a model
-
-### Import from GGUF
-
-Ollama supports importing GGUF models in the Modelfile:
-
-1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import.
-
-   ```
-   FROM ./vicuna-33b.Q4_0.gguf
-   ```
-
-2. Create the model in Ollama
-
-   ```shell
-   ollama create example -f Modelfile
-   ```
-
-3. Run the model
-
-   ```shell
-   ollama run example
-   ```
-
-### Import from Safetensors
-
-See the [guide](docs/import.md) on importing models for more information.
-
-### Customize a prompt
-
-Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3.2` model:
-
-```shell
-ollama pull llama3.2
-```
-
-Create a `Modelfile`:
-
-```
-FROM llama3.2
-
-# set the temperature to 1 [higher is more creative, lower is more coherent]
-PARAMETER temperature 1
-
-# set the system message
-SYSTEM """
-You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
-"""
-```
-
-Next, create and run the model:
-
-```
-ollama create mario -f ./Modelfile
-ollama run mario
->>> hi
-Hello! It's your friend Mario.
-```
-
-For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
+See a full list of models on [ollama.com](https://ollama.com/models)
 
 ## CLI Reference
 
+### Download a model
+
+```shell
+ollama pull gemma3
+```
+
+### Remove a model
+
+```shell
+ollama rm gemma3
+```
+
 ### Create a model
 
 `ollama create` is used to create a model from a Modelfile.
@@ -155,24 +79,22 @@ For more information on working with a Modelfile, see the [Modelfile](docs/model
 ollama create mymodel -f ./Modelfile
 ```
 
-### Pull a model
+### Show model information
 
 ```shell
-ollama pull llama3.2
-```
-
-> This command can also be used to update a local model. Only the diff will be pulled.
-
-### Remove a model
-
-```shell
-ollama rm llama3.2
+ollama show gemma3
 ```
 
 ### Copy a model
 
 ```shell
-ollama cp llama3.2 my-model
+ollama cp gemma3 my-model
+```
+
+### List models on your computer
+
+```shell
+ollama list
 ```
 
 ### Multiline input
@@ -189,29 +111,13 @@ I'm a basic program that prints the famous "Hello, world!" message to the consol
 ### Multimodal models
 
 ```
-ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png"
+ollama run gemma3 "What's in this image? /Users/jmorgan/Desktop/smile.png"
 ```
 
-> **Output**: The image features a yellow smiley face, which is likely the central focus of the picture.
-
 ### Pass the prompt as an argument
 
 ```shell
-ollama run llama3.2 "Summarize this file: $(cat README.md)"
-```
-
-> **Output**: Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
-
-### Show model information
-
-```shell
-ollama show llama3.2
-```
-
-### List models on your computer
-
-```shell
-ollama list
+ollama run gemma3 "Summarize this file: $(cat README.md)"
 ```
 
 ### List which models are currently loaded
@@ -223,30 +129,20 @@ ollama ps
 ### Stop a model which is currently running
 
 ```shell
-ollama stop llama3.2
+ollama stop gemma3
 ```
 
 ### Start Ollama
 
-`ollama serve` is used when you want to start ollama without running the desktop application.
+To run Ollama's server, use:
+
+```shell
+ollama serve
+```
 
 ## Building
 
-See the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
-
-### Running local builds
-
-Next, start the server:
-
-```shell
-./ollama serve
-```
-
-Finally, in a separate shell, run a model:
-
-```shell
-./ollama run llama3.2
-```
+See the [development guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
 
 ## REST API
 
@@ -256,23 +152,12 @@ Ollama has a REST API for running and managing models.
 
 ```shell
 curl http://localhost:11434/api/generate -d '{
-  "model": "llama3.2",
+  "model": "gemma3",
   "prompt":"Why is the sky blue?"
 }'
 ```
 
-### Chat with a model
-
-```shell
-curl http://localhost:11434/api/chat -d '{
-  "model": "llama3.2",
-  "messages": [
-    { "role": "user", "content": "why is the sky blue?" }
-  ]
-}'
-```
-
-See the [API documentation](./docs/api.md) for all endpoints.
+See the [API documentation](./docs/api.md) for more information.
 
 ## Community Integrations
 
@@ -406,7 +291,7 @@ 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.)
@@ -414,7 +299,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Serene Pub](https://github.com/doolijb/serene-pub) (Beginner friendly, open source AI Roleplaying App for Windows, Mac OS and Linux. Search, download and use models with Ollama all inside the app.)
 - [Andes](https://github.com/aqerd/andes) (A Visual Studio Code extension that provides a local UI interface for Ollama models)
 - [Clueless](https://github.com/KashyapTan/clueless) (Open Source & Local Cluely: A desktop application LLM assistant to help you talk to anything on your screen using locally served Ollama models. Also undetectable to screenshare)
-- [ollama-co2](https://github.com/carbonatedWaterOrg/ollama-co2) (FastAPI web interface for monitoring and managing local and remote Ollama servers with real-time model monitoring and concurrent downloads)
 
 ### Cloud
 
@@ -470,7 +354,7 @@ 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)
@@ -611,6 +495,7 @@ 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 intergration 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.

api/client.go

@@ -222,17 +222,7 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 			return fmt.Errorf("unmarshal: %w", err)
 		}
 
-		if response.StatusCode == http.StatusUnauthorized {
-			pubKey, pkErr := auth.GetPublicKey()
-			if pkErr != nil {
-				return pkErr
-			}
-			return AuthorizationError{
-				StatusCode: response.StatusCode,
-				Status:     response.Status,
-				PublicKey:  pubKey,
-			}
-		} else if response.StatusCode >= http.StatusBadRequest {
+		if response.StatusCode >= http.StatusBadRequest {
 			return StatusError{
 				StatusCode:   response.StatusCode,
 				Status:       response.Status,
@@ -438,16 +428,3 @@ func (c *Client) Version(ctx context.Context) (string, error) {
 
 	return version.Version, nil
 }
-
-// Signout will disconnect an ollama instance from ollama.com
-func (c *Client) Signout(ctx context.Context, encodedKey string) error {
-	return c.do(ctx, http.MethodDelete, fmt.Sprintf("/api/user/keys/%s", encodedKey), nil, nil)
-}
-
-func (c *Client) Whoami(ctx context.Context) (*UserResponse, error) {
-	var resp UserResponse
-	if err := c.do(ctx, http.MethodPost, "/api/me", nil, &resp); err != nil {
-		return nil, err
-	}
-	return &resp, nil
-}

api/types.go

@@ -11,8 +11,6 @@ import (
 	"strings"
 	"time"
 
-	"github.com/google/uuid"
-
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/types/model"
 )
@@ -38,19 +36,6 @@ func (e StatusError) Error() string {
 	}
 }
 
-type AuthorizationError struct {
-	StatusCode int
-	Status     string
-	PublicKey  string `json:"public_key"`
-}
-
-func (e AuthorizationError) Error() string {
-	if e.Status != "" {
-		return e.Status
-	}
-	return "something went wrong, please see the ollama server logs for details"
-}
-
 // ImageData represents the raw binary data of an image file.
 type ImageData []byte
 
@@ -328,29 +313,13 @@ func (t *ToolFunction) String() string {
 // ChatResponse is the response returned by [Client.Chat]. Its fields are
 // similar to [GenerateResponse].
 type ChatResponse struct {
-	// Model is the model name that generated the response.
-	Model string `json:"model"`
+	Model      string    `json:"model"`
+	CreatedAt  time.Time `json:"created_at"`
+	Message    Message   `json:"message"`
+	DoneReason string    `json:"done_reason,omitempty"`
 
-	// RemoteModel is the name of the upstream model that generated the response.
-	RemoteModel string `json:"remote_model,omitempty"`
-
-	// RemoteHost is the URL of the upstream Ollama host that generated the response.
-	RemoteHost string `json:"remote_host,omitempty"`
-
-	// CreatedAt is the timestamp of the response.
-	CreatedAt time.Time `json:"created_at"`
-
-	// Message contains the message or part of a message from the model.
-	Message Message `json:"message"`
-
-	// Done specifies if the response is complete.
 	Done bool `json:"done"`
 
-	// DoneReason is the reason the model stopped generating text.
-	DoneReason string `json:"done_reason,omitempty"`
-
-	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
-
 	Metrics
 }
 
@@ -360,6 +329,13 @@ type DebugInfo struct {
 	ImageCount       int    `json:"image_count,omitempty"`
 }
 
+// DebugTemplateResponse is returned when _debug_render_only is set to true
+type DebugTemplateResponse struct {
+	Model     string    `json:"model"`
+	CreatedAt time.Time `json:"created_at"`
+	DebugInfo DebugInfo `json:"_debug_info"`
+}
+
 type Metrics struct {
 	TotalDuration      time.Duration `json:"total_duration,omitempty"`
 	LoadDuration       time.Duration `json:"load_duration,omitempty"`
@@ -412,12 +388,8 @@ type EmbedRequest struct {
 	// this request.
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
-	// Truncate truncates the input to fit the model's max sequence length.
 	Truncate *bool `json:"truncate,omitempty"`
 
-	// Dimensions truncates the output embedding to the specified dimension.
-	Dimensions int `json:"dimensions,omitempty"`
-
 	// Options lists model-specific options.
 	Options map[string]any `json:"options"`
 }
@@ -455,47 +427,18 @@ type EmbeddingResponse struct {
 
 // CreateRequest is the request passed to [Client.Create].
 type CreateRequest struct {
-	// Model is the model name to create.
-	Model string `json:"model"`
-
-	// Stream specifies whether the response is streaming; it is true by default.
-	Stream *bool `json:"stream,omitempty"`
-
-	// Quantize is the quantization format for the model; leave blank to not change the quantization level.
+	Model    string `json:"model"`
+	Stream   *bool  `json:"stream,omitempty"`
 	Quantize string `json:"quantize,omitempty"`
 
-	// From is the name of the model or file to use as the source.
-	From string `json:"from,omitempty"`
-
-	// RemoteHost is the URL of the upstream ollama API for the model (if any).
-	RemoteHost string `json:"remote_host,omitempty"`
-
-	// Files is a map of files include when creating the model.
-	Files map[string]string `json:"files,omitempty"`
-
-	// Adapters is a map of LoRA adapters to include when creating the model.
-	Adapters map[string]string `json:"adapters,omitempty"`
-
-	// Template is the template used when constructing a request to the model.
-	Template string `json:"template,omitempty"`
-
-	// License is a string or list of strings for licenses.
-	License any `json:"license,omitempty"`
-
-	// System is the system prompt for the model.
-	System string `json:"system,omitempty"`
-
-	// Parameters is a map of hyper-parameters which are applied to the model.
-	Parameters map[string]any `json:"parameters,omitempty"`
-
-	// Messages is a list of messages added to the model before chat and generation requests.
-	Messages []Message `json:"messages,omitempty"`
-
-	Renderer string `json:"renderer,omitempty"`
-	Parser   string `json:"parser,omitempty"`
-
-	// Info is a map of additional information for the model
-	Info map[string]any `json:"info,omitempty"`
+	From       string            `json:"from,omitempty"`
+	Files      map[string]string `json:"files,omitempty"`
+	Adapters   map[string]string `json:"adapters,omitempty"`
+	Template   string            `json:"template,omitempty"`
+	License    any               `json:"license,omitempty"`
+	System     string            `json:"system,omitempty"`
+	Parameters map[string]any    `json:"parameters,omitempty"`
+	Messages   []Message         `json:"messages,omitempty"`
 
 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
@@ -533,12 +476,8 @@ type ShowResponse struct {
 	Parameters    string             `json:"parameters,omitempty"`
 	Template      string             `json:"template,omitempty"`
 	System        string             `json:"system,omitempty"`
-	Renderer      string             `json:"renderer,omitempty"`
-	Parser        string             `json:"parser,omitempty"`
 	Details       ModelDetails       `json:"details,omitempty"`
 	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"`
 	ProjectorInfo map[string]any     `json:"projector_info,omitempty"`
 	Tensors       []Tensor           `json:"tensors,omitempty"`
@@ -597,14 +536,12 @@ type ProcessResponse struct {
 
 // ListModelResponse is a single model description in [ListResponse].
 type ListModelResponse struct {
-	Name        string       `json:"name"`
-	Model       string       `json:"model"`
-	RemoteModel string       `json:"remote_model,omitempty"`
-	RemoteHost  string       `json:"remote_host,omitempty"`
-	ModifiedAt  time.Time    `json:"modified_at"`
-	Size        int64        `json:"size"`
-	Digest      string       `json:"digest"`
-	Details     ModelDetails `json:"details,omitempty"`
+	Name       string       `json:"name"`
+	Model      string       `json:"model"`
+	ModifiedAt time.Time    `json:"modified_at"`
+	Size       int64        `json:"size"`
+	Digest     string       `json:"digest"`
+	Details    ModelDetails `json:"details,omitempty"`
 }
 
 // ProcessModelResponse is a single model description in [ProcessResponse].
@@ -628,12 +565,6 @@ type GenerateResponse struct {
 	// Model is the model name that generated the response.
 	Model string `json:"model"`
 
-	// RemoteModel is the name of the upstream model that generated the response.
-	RemoteModel string `json:"remote_model,omitempty"`
-
-	// RemoteHost is the URL of the upstream Ollama host that generated the response.
-	RemoteHost string `json:"remote_host,omitempty"`
-
 	// CreatedAt is the timestamp of the response.
 	CreatedAt time.Time `json:"created_at"`
 
@@ -657,8 +588,6 @@ type GenerateResponse struct {
 	Metrics
 
 	ToolCalls []ToolCall `json:"tool_calls,omitempty"`
-
-	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
 }
 
 // ModelDetails provides details about a model.
@@ -671,18 +600,6 @@ type ModelDetails struct {
 	QuantizationLevel string   `json:"quantization_level"`
 }
 
-// UserResponse provides information about a user.
-type UserResponse struct {
-	ID        uuid.UUID `json:"id"`
-	Email     string    `json:"email"`
-	Name      string    `json:"name"`
-	Bio       string    `json:"bio,omitempty"`
-	AvatarURL string    `json:"avatarurl,omitempty"`
-	FirstName string    `json:"firstname,omitempty"`
-	LastName  string    `json:"lastname,omitempty"`
-	Plan      string    `json:"plan,omitempty"`
-}
-
 // Tensor describes the metadata for a given tensor.
 type Tensor struct {
 	Name  string   `json:"name"`

auth/auth.go

@@ -19,31 +19,6 @@ import (
 const defaultPrivateKey = "id_ed25519"
 
 func keyPath() (string, error) {
-	fileIsReadable := func(fp string) bool {
-		info, err := os.Stat(fp)
-		if err != nil {
-			return false
-		}
-
-		// Check that it's a regular file, not a directory or other file type
-		if !info.Mode().IsRegular() {
-			return false
-		}
-
-		// Try to open it to check readability
-		file, err := os.Open(fp)
-		if err != nil {
-			return false
-		}
-		file.Close()
-		return true
-	}
-
-	systemPath := filepath.Join("/usr/share/ollama/.ollama", defaultPrivateKey)
-	if fileIsReadable(systemPath) {
-		return systemPath, nil
-	}
-
 	home, err := os.UserHomeDir()
 	if err != nil {
 		return "", err

cmd/cmd.go

@@ -5,7 +5,6 @@ import (
 	"context"
 	"crypto/ed25519"
 	"crypto/rand"
-	"encoding/base64"
 	"encoding/json"
 	"encoding/pem"
 	"errors"
@@ -15,7 +14,6 @@ import (
 	"math"
 	"net"
 	"net/http"
-	"net/url"
 	"os"
 	"os/signal"
 	"path/filepath"
@@ -37,7 +35,6 @@ import (
 	"golang.org/x/term"
 
 	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/auth"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/parser"
@@ -50,8 +47,6 @@ import (
 	"github.com/ollama/ollama/version"
 )
 
-const ConnectInstructions = "To sign in, navigate to:\n    https://ollama.com/connect?name=%s&key=%s\n\n"
-
 // ensureThinkingSupport emits a warning if the model does not advertise thinking support
 func ensureThinkingSupport(ctx context.Context, client *api.Client, name string) {
 	if name == "" {
@@ -61,8 +56,10 @@ func ensureThinkingSupport(ctx context.Context, client *api.Client, name string)
 	if err != nil {
 		return
 	}
-	if slices.Contains(resp.Capabilities, model.CapabilityThinking) {
-		return
+	for _, cap := range resp.Capabilities {
+		if cap == model.CapabilityThinking {
+			return
+		}
 	}
 	fmt.Fprintf(os.Stderr, "warning: model %q does not support thinking output\n", name)
 }
@@ -291,17 +288,7 @@ func loadOrUnloadModel(cmd *cobra.Command, opts *runOptions) error {
 		Think: opts.Think,
 	}
 
-	return client.Generate(cmd.Context(), req, func(r api.GenerateResponse) error {
-		if r.RemoteModel != "" && opts.ShowConnect {
-			p.StopAndClear()
-			if strings.HasPrefix(r.RemoteHost, "https://ollama.com") {
-				fmt.Fprintf(os.Stderr, "Connecting to '%s' on 'ollama.com' ⚡\n", r.RemoteModel)
-			} else {
-				fmt.Fprintf(os.Stderr, "Connecting to '%s' on '%s'\n", r.RemoteModel, r.RemoteHost)
-			}
-		}
-		return nil
-	})
+	return client.Generate(cmd.Context(), req, func(api.GenerateResponse) error { return nil })
 }
 
 func StopHandler(cmd *cobra.Command, args []string) error {
@@ -322,10 +309,9 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	interactive := true
 
 	opts := runOptions{
-		Model:       args[0],
-		WordWrap:    os.Getenv("TERM") == "xterm-256color",
-		Options:     map[string]any{},
-		ShowConnect: true,
+		Model:    args[0],
+		WordWrap: os.Getenv("TERM") == "xterm-256color",
+		Options:  map[string]any{},
 	}
 
 	format, err := cmd.Flags().GetString("format")
@@ -383,7 +369,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		}
 
 		prompts = append([]string{string(in)}, prompts...)
-		opts.ShowConnect = false
 		opts.WordWrap = false
 		interactive = false
 	}
@@ -450,21 +435,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 
 	if interactive {
 		if err := loadOrUnloadModel(cmd, &opts); err != nil {
-			var sErr api.AuthorizationError
-			if errors.As(err, &sErr) && sErr.StatusCode == http.StatusUnauthorized {
-				pubKey, pkErr := auth.GetPublicKey()
-				if pkErr != nil {
-					return pkErr
-				}
-				// the server and the client both have the same public key
-				if pubKey == sErr.PublicKey {
-					h, _ := os.Hostname()
-					encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
-					fmt.Printf("You need to be signed in to Ollama to run Cloud models.\n\n")
-					fmt.Printf(ConnectInstructions, url.PathEscape(h), encKey)
-				}
-				return nil
-			}
 			return err
 		}
 
@@ -485,56 +455,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	return generate(cmd, opts)
 }
 
-func SigninHandler(cmd *cobra.Command, args []string) error {
-	client, err := api.ClientFromEnvironment()
-	if err != nil {
-		return err
-	}
-
-	user, err := client.Whoami(cmd.Context())
-	if err != nil {
-		return err
-	}
-
-	if user != nil && user.Name != "" {
-		fmt.Printf("You are already signed in as user '%s'\n", user.Name)
-		fmt.Println()
-		return nil
-	}
-
-	pubKey, pkErr := auth.GetPublicKey()
-	if pkErr != nil {
-		return pkErr
-	}
-	encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
-
-	h, _ := os.Hostname()
-	fmt.Printf(ConnectInstructions, url.PathEscape(h), encKey)
-
-	return nil
-}
-
-func SignoutHandler(cmd *cobra.Command, args []string) error {
-	pubKey, pkErr := auth.GetPublicKey()
-	if pkErr != nil {
-		return pkErr
-	}
-	encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
-
-	client, err := api.ClientFromEnvironment()
-	if err != nil {
-		return err
-	}
-
-	err = client.Signout(cmd.Context(), encKey)
-	if err != nil {
-		return err
-	}
-	fmt.Println("You have signed out of ollama.com")
-	fmt.Println()
-	return nil
-}
-
 func PushHandler(cmd *cobra.Command, args []string) error {
 	client, err := api.ClientFromEnvironment()
 	if err != nil {
@@ -587,8 +507,7 @@ func PushHandler(cmd *cobra.Command, args []string) error {
 		if spinner != nil {
 			spinner.Stop()
 		}
-		errStr := strings.ToLower(err.Error())
-		if strings.Contains(errStr, "access denied") || strings.Contains(errStr, "unauthorized") {
+		if strings.Contains(err.Error(), "access denied") {
 			return errors.New("you are not authorized to push to this namespace, create the model under a namespace you own")
 		}
 		return err
@@ -622,14 +541,7 @@ func ListHandler(cmd *cobra.Command, args []string) error {
 
 	for _, m := range models.Models {
 		if len(args) == 0 || strings.HasPrefix(strings.ToLower(m.Name), strings.ToLower(args[0])) {
-			var size string
-			if m.RemoteModel != "" {
-				size = "-"
-			} else {
-				size = format.HumanBytes(m.Size)
-			}
-
-			data = append(data, []string{m.Name, m.Digest[:12], size, format.HumanTime(m.ModifiedAt, "Never")})
+			data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), format.HumanTime(m.ModifiedAt, "Never")})
 		}
 	}
 
@@ -714,8 +626,8 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
 		KeepAlive: &api.Duration{Duration: 0},
 	}
 	if err := loadOrUnloadModel(cmd, opts); err != nil {
-		if !strings.Contains(strings.ToLower(err.Error()), "not found") {
-			fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", args[0])
+		if !strings.Contains(err.Error(), "not found") {
+			return fmt.Errorf("unable to stop existing running model \"%s\": %s", args[0], err)
 		}
 	}
 
@@ -826,36 +738,12 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 	}
 
 	tableRender("Model", func() (rows [][]string) {
-		if resp.RemoteHost != "" {
-			rows = append(rows, []string{"", "Remote model", resp.RemoteModel})
-			rows = append(rows, []string{"", "Remote URL", resp.RemoteHost})
-		}
-
 		if resp.ModelInfo != nil {
 			arch := resp.ModelInfo["general.architecture"].(string)
 			rows = append(rows, []string{"", "architecture", arch})
-
-			var paramStr string
-			if resp.Details.ParameterSize != "" {
-				paramStr = resp.Details.ParameterSize
-			} else if v, ok := resp.ModelInfo["general.parameter_count"]; ok {
-				if f, ok := v.(float64); ok {
-					paramStr = format.HumanNumber(uint64(f))
-				}
-			}
-			rows = append(rows, []string{"", "parameters", paramStr})
-
-			if v, ok := resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)]; ok {
-				if f, ok := v.(float64); ok {
-					rows = append(rows, []string{"", "context length", strconv.FormatFloat(f, 'f', -1, 64)})
-				}
-			}
-
-			if v, ok := resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)]; ok {
-				if f, ok := v.(float64); ok {
-					rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(f, 'f', -1, 64)})
-				}
-			}
+			rows = append(rows, []string{"", "parameters", format.HumanNumber(uint64(resp.ModelInfo["general.parameter_count"].(float64)))})
+			rows = append(rows, []string{"", "context length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64), 'f', -1, 64)})
+			rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64), 'f', -1, 64)})
 		} else {
 			rows = append(rows, []string{"", "architecture", resp.Details.Family})
 			rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
@@ -1103,7 +991,6 @@ type runOptions struct {
 	KeepAlive    *api.Duration
 	Think        *api.ThinkValue
 	HideThinking bool
-	ShowConnect  bool
 }
 
 type displayResponseState struct {
@@ -1659,22 +1546,6 @@ func NewCLI() *cobra.Command {
 
 	pushCmd.Flags().Bool("insecure", false, "Use an insecure registry")
 
-	signinCmd := &cobra.Command{
-		Use:     "signin",
-		Short:   "Sign in to ollama.com",
-		Args:    cobra.ExactArgs(0),
-		PreRunE: checkServerHeartbeat,
-		RunE:    SigninHandler,
-	}
-
-	signoutCmd := &cobra.Command{
-		Use:     "signout",
-		Short:   "Sign out from ollama.com",
-		Args:    cobra.ExactArgs(0),
-		PreRunE: checkServerHeartbeat,
-		RunE:    SignoutHandler,
-	}
-
 	listCmd := &cobra.Command{
 		Use:     "list",
 		Aliases: []string{"ls"},
@@ -1769,8 +1640,6 @@ func NewCLI() *cobra.Command {
 		stopCmd,
 		pullCmd,
 		pushCmd,
-		signinCmd,
-		signoutCmd,
 		listCmd,
 		psCmd,
 		copyCmd,

cmd/cmd_test.go

@@ -3,7 +3,6 @@ package cmd
 import (
 	"bytes"
 	"encoding/json"
-	"fmt"
 	"io"
 	"net/http"
 	"net/http/httptest"
@@ -305,8 +304,6 @@ func TestDeleteHandler(t *testing.T) {
 				w.WriteHeader(http.StatusOK)
 			} else {
 				w.WriteHeader(http.StatusNotFound)
-				errPayload := `{"error":"model '%s' not found"}`
-				w.Write([]byte(fmt.Sprintf(errPayload, req.Name)))
 			}
 			return
 		}
@@ -349,7 +346,7 @@ func TestDeleteHandler(t *testing.T) {
 	}
 
 	err := DeleteHandler(cmd, []string{"test-model-not-found"})
-	if err == nil || !strings.Contains(err.Error(), "model 'test-model-not-found' not found") {
+	if err == nil || !strings.Contains(err.Error(), "unable to stop existing running model \"test-model-not-found\"") {
 		t.Fatalf("DeleteHandler failed: expected error about stopping non-existent model, got %v", err)
 	}
 }
@@ -502,7 +499,7 @@ func TestPushHandler(t *testing.T) {
 					w.Header().Set("Content-Type", "application/json")
 					w.WriteHeader(http.StatusUnauthorized)
 					err := json.NewEncoder(w).Encode(map[string]string{
-						"error": "403: {\"errors\":[{\"code\":\"ACCESS DENIED\", \"message\":\"access denied\"}]}",
+						"error": "access denied",
 					})
 					if err != nil {
 						t.Fatal(err)
@@ -525,7 +522,6 @@ func TestPushHandler(t *testing.T) {
 			defer mockServer.Close()
 
 			t.Setenv("OLLAMA_HOST", mockServer.URL)
-			initializeKeypair()
 
 			cmd := &cobra.Command{}
 			cmd.Flags().Bool("insecure", false, "")

convert/convert_bert.go

@@ -28,7 +28,6 @@ type bertModel struct {
 	LayerNormEPS          float32 `json:"layer_norm_eps"`
 	LayerNormEpsilon      float32 `json:"layer_norm_epsilon"`
 	NormEpsilon           float32 `json:"norm_epsilon"`
-	normalizeEmbeddings   bool
 
 	PoolingType uint32
 }
@@ -55,11 +54,9 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
 
 	var pooling string
 	for _, m := range modules {
-		switch m.Type {
-		case "sentence_transformers.models.Pooling":
+		if m.Type == "sentence_transformers.models.Pooling" {
 			pooling = m.Path
-		case "sentence_transformers.models.Normalize":
-			p.normalizeEmbeddings = true
+			break
 		}
 	}
 
@@ -93,7 +90,6 @@ func (p *bertModel) KV(t *Tokenizer) ggml.KV {
 	kv["general.architecture"] = "bert"
 	kv["bert.attention.causal"] = false
 	kv["bert.pooling_type"] = p.PoolingType
-	kv["bert.normalize_embeddings"] = p.normalizeEmbeddings
 
 	kv["bert.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)
 

convert/reader_safetensors.go

@@ -96,7 +96,7 @@ type safetensor struct {
 
 func (st safetensor) Kind() uint32 {
 	kind := st.tensorBase.Kind()
-	if !strings.HasPrefix(st.name, "v.") && st.dtype == "BF16" && kind != tensorKindFP32 {
+	if st.dtype == "BF16" && kind != tensorKindFP32 {
 		kind = tensorKindBF16
 	}
 

convert/reader_test.go

@@ -230,65 +230,3 @@ func TestSafetensors(t *testing.T) {
 		})
 	}
 }
-
-func TestSafetensorKind(t *testing.T) {
-	tests := []struct {
-		name     string
-		st       safetensor
-		expected uint32
-	}{
-		{
-			name: "BF16 dtype with non-v. prefix and non-FP32 base kind should return BF16",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "weight.matrix",
-					shape: []uint64{10, 10}, // will default to FP16
-				},
-				dtype: "BF16",
-			},
-			expected: tensorKindBF16,
-		},
-		{
-			name: "BF16 dtype with v. prefix should return base kind",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "v.weight.matrix",
-					shape: []uint64{10, 10}, // will default to FP16
-				},
-				dtype: "BF16",
-			},
-			expected: tensorKindFP16,
-		},
-		{
-			name: "BF16 dtype with FP32 base kind should return FP32",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "weight.matrix",
-					shape: []uint64{10}, // will default to FP32
-				},
-				dtype: "BF16",
-			},
-			expected: tensorKindFP32,
-		},
-		{
-			name: "Non-BF16 dtype should return base kind",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "weight.matrix",
-					shape: []uint64{10, 10}, // will default to FP16
-				},
-				dtype: "FP16",
-			},
-			expected: tensorKindFP16,
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			result := tt.st.Kind()
-			if result != tt.expected {
-				t.Errorf("Kind() = %d, expected %d", result, tt.expected)
-			}
-		})
-	}
-}

discover/cuda_common.go

@@ -16,7 +16,7 @@ import (
 // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
 var CudaTegra string = os.Getenv("JETSON_JETPACK")
 
-func cudaVariant(gpuInfos []CudaGPUInfo) string {
+func cudaVariant(gpuInfo CudaGPUInfo) string {
 	if runtime.GOARCH == "arm64" && runtime.GOOS == "linux" {
 		if CudaTegra != "" {
 			ver := strings.Split(CudaTegra, ".")
@@ -43,22 +43,14 @@ func cudaVariant(gpuInfos []CudaGPUInfo) string {
 				}
 			}
 		}
+		return "sbsa"
 	}
 
-	// Check GPU compute capability FIRST, lowest common denominator if multi-gpu
-	for _, gpuInfo := range gpuInfos {
-		if gpuInfo.computeMajor < 7 || (gpuInfo.computeMajor == 7 && gpuInfo.computeMinor < 5) {
-			// GPU is Pascal or older (CC <= 7.4) - use CUDA v12 (supports CC 6.1)
-			return "v12"
-		}
+	// driver 12.0 has problems with the cuda v12 library, so run v11 on those older drivers
+	if gpuInfo.DriverMajor < 12 || (gpuInfo.DriverMajor == 12 && gpuInfo.DriverMinor == 0) {
+		// The detected driver is older than Feb 2023
+		slog.Warn("old CUDA driver detected - please upgrade to a newer driver", "version", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor))
+		return "v11"
 	}
-
-	// GPU is Turing or newer (CC >= 7.5) - can use newer CUDA
-	if len(gpuInfos) > 0 && gpuInfos[0].DriverMajor < 13 {
-		// The detected driver is older than 580 (Aug 2025)
-		// Warn if their CC is compatible with v13 and they should upgrade their driver to get better performance
-		slog.Warn("old CUDA driver detected - please upgrade to a newer driver for best performance", "version", fmt.Sprintf("%d.%d", gpuInfos[0].DriverMajor, gpuInfos[0].DriverMinor))
-		return "v12"
-	}
-	return "v13"
+	return "v12"
 }

discover/gpu.go

@@ -284,8 +284,18 @@ func GetGPUInfo() GpuInfoList {
 				gpuInfo.MinimumMemory = cudaMinimumMemory
 				gpuInfo.DriverMajor = driverMajor
 				gpuInfo.DriverMinor = driverMinor
+				variant := cudaVariant(gpuInfo)
 
+				// Start with our bundled libraries
+				if variant != "" {
+					variantPath := filepath.Join(LibOllamaPath, "cuda_"+variant)
+					if _, err := os.Stat(variantPath); err == nil {
+						// Put the variant directory first in the search path to avoid runtime linking to the wrong library
+						gpuInfo.DependencyPath = append([]string{variantPath}, gpuInfo.DependencyPath...)
+					}
+				}
 				gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
+				gpuInfo.Variant = variant
 
 				if int(memInfo.major) < cudaComputeMajorMin || (int(memInfo.major) == cudaComputeMajorMin && int(memInfo.minor) < cudaComputeMinorMin) {
 					unsupportedGPUs = append(unsupportedGPUs,
@@ -323,24 +333,6 @@ func GetGPUInfo() GpuInfoList {
 				// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
 				cudaGPUs = append(cudaGPUs, gpuInfo)
 			}
-			// Second pass on NVIDIA GPUs to set lowest common denominator variant and DependencyPaths
-			variant := cudaVariant(cudaGPUs)
-			var variantPath string
-			// Start with our bundled libraries
-			if variant != "" {
-				variantPath = filepath.Join(LibOllamaPath, "cuda_"+variant)
-				if _, err := os.Stat(variantPath); err != nil {
-					variantPath = ""
-				}
-			}
-
-			for i := range cudaGPUs {
-				cudaGPUs[i].Variant = variant
-				if variantPath != "" {
-					// Put the variant directory first in the search path to avoid runtime linking to the wrong library
-					cudaGPUs[i].DependencyPath = append([]string{variantPath}, cudaGPUs[i].DependencyPath...)
-				}
-			}
 		}
 
 		// Intel

docs/api.md

@@ -1708,7 +1708,6 @@ Advanced parameters:
 - `truncate`: truncates the end of each input to fit within context length. Returns error if `false` and context length is exceeded. Defaults to `true`
 - `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
-- `dimensions`: number of dimensions for the embedding
 
 ### Examples
 

docs/development.md

@@ -11,10 +11,6 @@ Then build and run Ollama from the root directory of the repository:
 go run . serve
 ```
 
-> [!NOTE]
-> Ollama includes native code compiled with CGO.  From time to time these data structures can change and CGO can get out of sync resulting in unexpected crashes.  You can force a full build of the native code by running `go clean -cache` first. 
-
-
 ## macOS (Apple Silicon)
 
 macOS Apple Silicon supports Metal which is built-in to the Ollama binary. No additional steps are required.

docs/linux.md

@@ -11,13 +11,12 @@ curl -fsSL https://ollama.com/install.sh | sh
 ## Manual install
 
 > [!NOTE]
-> If you are upgrading from a prior version, you **MUST** 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.
 
 Download and extract the package:
 
 ```shell
 curl -LO https://ollama.com/download/ollama-linux-amd64.tgz
-sudo rm -rf /usr/lib/ollama
 sudo tar -C /usr -xzf ollama-linux-amd64.tgz
 ```
 

envconfig/config.go

@@ -134,17 +134,6 @@ func LoadTimeout() (loadTimeout time.Duration) {
 	return loadTimeout
 }
 
-func Remotes() []string {
-	var r []string
-	raw := strings.TrimSpace(Var("OLLAMA_REMOTES"))
-	if raw == "" {
-		r = []string{"ollama.com"}
-	} else {
-		r = strings.Split(raw, ",")
-	}
-	return r
-}
-
 func Bool(k string) func() bool {
 	return func() bool {
 		if s := Var(k); s != "" {
@@ -196,6 +185,8 @@ var (
 	ContextLength = Uint("OLLAMA_CONTEXT_LENGTH", 4096)
 	// Auth enables authentication between the Ollama client and server
 	UseAuth = Bool("OLLAMA_AUTH")
+	// Enable the new memory estimation logic
+	NewMemoryEstimates = Bool("OLLAMA_NEW_ESTIMATES")
 )
 
 func String(s string) func() string {
@@ -281,7 +272,7 @@ func AsMap() map[string]EnvVar {
 		"OLLAMA_MULTIUSER_CACHE":   {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
 		"OLLAMA_CONTEXT_LENGTH":    {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4096)"},
 		"OLLAMA_NEW_ENGINE":        {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
-		"OLLAMA_REMOTES":           {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
+		"OLLAMA_NEW_ESTIMATES":     {"OLLAMA_NEW_ESTIMATES", NewMemoryEstimates(), "Enable the new memory estimation logic"},
 
 		// Informational
 		"HTTP_PROXY":  {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},

fs/ggml/ggml.go

@@ -243,7 +243,6 @@ func (kv KV) OllamaEngineRequired() bool {
 		"gemma3",
 		"gemma3n",
 		"mistral3",
-		"qwen3",
 		"llama4",
 		"mllama",
 		"qwen25vl",
@@ -865,16 +864,12 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 
 // SupportsKVCacheType checks if the requested cache type is supported
 func (f GGML) SupportsKVCacheType(cacheType string) bool {
-	if cacheType == "" || cacheType == "f16" {
-		return true
-	}
-
 	if arch := f.KV().Architecture(); slices.Contains([]string{"gptoss", "gpt-oss"}, arch) {
 		// gpt-oss uses attention with sinks which does not support quantized cache types
-		slog.Warn("model only supports non-quantized cache types", "model", arch)
-		return false
+		slog.Warn("model only supports non-quantized cache types ", "mode", arch)
+		return cacheType == "f16"
 	}
-	return slices.Contains([]string{"q8_0", "q4_0"}, cacheType)
+	return slices.Contains([]string{"f16", "q8_0", "q4_0"}, cacheType)
 }
 
 // SupportsFlashAttention checks if the model supports flash attention
@@ -884,10 +879,6 @@ func (f GGML) SupportsFlashAttention() bool {
 		return false
 	}
 
-	if arch := f.KV().Architecture(); slices.Contains([]string{"gemma2"}, arch) {
-		return false
-	}
-
 	// Check head counts match and are non-zero
 	headCountK := f.KV().EmbeddingHeadCountK()
 	headCountV := f.KV().EmbeddingHeadCountV()

harmony/harmonyparser.go

@@ -3,15 +3,29 @@ package harmony
 import (
 	"fmt"
 	"log/slog"
+	"slices"
 	"strings"
 	"unicode"
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/logutil"
+	"github.com/ollama/ollama/template"
 )
 
 type harmonyParserState int
 
+func ShouldUseHarmony(modelFamily string, template *template.Template) bool {
+	if slices.Contains([]string{"gptoss", "gpt-oss"}, modelFamily) {
+		// heuristic to check whether the template expects to be parsed via harmony:
+		// search for harmony tags that are nearly always used
+		if template.Contains("<|start|>") && template.Contains("<|end|>") {
+			return true
+		}
+	}
+
+	return false
+}
+
 const (
 	harmonyParserState_LookingForMessageStart harmonyParserState = iota
 	harmonyParserState_ParsingHeader
@@ -75,18 +89,28 @@ func (s *HarmonyParser) AddImplicitStart() {
 	s.acc.WriteString("<|start|>assistant")
 }
 
-func (s *HarmonyParser) AddImplicitStartOrPrefill(lastMessage *api.Message) {
-	if lastMessage != nil && lastMessage.Role == "assistant" {
-		// handle prefilling conditions
-		if lastMessage.Content != "" {
-			s.acc.WriteString("<|start|>assistant<|channel|>final<|message|>")
-			return
-		} else if lastMessage.Thinking != "" {
-			s.acc.WriteString("<|start|>assistant<|channel|>analysis<|message|>")
-			return
-		}
+func Prefill(lastMessage api.Message) string {
+	if lastMessage.Role != "assistant" {
+		return ""
+	}
+
+	switch {
+	case strings.TrimSpace(lastMessage.Content) != "":
+		return "<|start|>assistant<|channel|>final<|message|>"
+	case strings.TrimSpace(lastMessage.Thinking) != "":
+		return "<|start|>assistant<|channel|>analysis<|message|>"
+	default:
+		return ""
+	}
+}
+
+// AddImplicitStartOrPrefill adds an implicit start tag or prefill string if provided
+func (s *HarmonyParser) AddImplicitStartOrPrefill(prefillString string) {
+	if strings.TrimSpace(prefillString) != "" {
+		s.acc.WriteString(prefillString)
+	} else {
+		s.AddImplicitStart()
 	}
-	s.AddImplicitStart()
 }
 
 func (s *HarmonyParser) AddContent(content string) []HarmonyEvent {

harmony/harmonyparser_test.go

@@ -3,6 +3,7 @@ package harmony
 import (
 	"fmt"
 	"reflect"
+	"strings"
 	"testing"
 )
 
@@ -535,3 +536,202 @@ func TestFunctionConvertAndAdd(t *testing.T) {
 		})
 	}
 }
+
+func TestHarmonyMessageHandlerStreamingScenarios(t *testing.T) {
+	t.Run("thinking_then_content_streams", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		type step struct {
+			in           string
+			wantContent  string
+			wantThinking string
+		}
+		steps := []step{
+			{in: "<|channel|>analysis<|message|>Thinking...", wantThinking: "Thinking..."},
+			{in: "<|end|>", wantThinking: ""},
+			{in: "<|start|>assistant<|message|>Answer", wantContent: "Answer"},
+			{in: "<|end|>", wantContent: ""},
+		}
+		for i, s := range steps {
+			content, thinking, tool := handler.AddContent(s.in, tp)
+			if tool != "" {
+				tp.Add(tool)
+			}
+			if content != s.wantContent || thinking != s.wantThinking {
+				t.Fatalf("step %d: got (content=%q thinking=%q), want (content=%q thinking=%q)", i, content, thinking, s.wantContent, s.wantThinking)
+			}
+		}
+	})
+
+	t.Run("content_streams_as_it_arrives", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		inputs := []string{
+			"<|start|>assistant<|message|>Hello",
+			", world",
+			"!<|end|>",
+		}
+		var got []string
+		for _, in := range inputs {
+			content, thinking, tool := handler.AddContent(in, tp)
+			if tool != "" {
+				tp.Add(tool)
+			}
+			if thinking != "" {
+				t.Fatalf("unexpected thinking %q", thinking)
+			}
+			if content != "" {
+				got = append(got, content)
+			}
+		}
+		want := []string{"Hello", ", world", "!"}
+		if !reflect.DeepEqual(got, want) {
+			t.Fatalf("content pieces mismatch: got %v want %v", got, want)
+		}
+	})
+
+	t.Run("thinking_streams_separately_from_content", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		inputs := []string{
+			"<|channel|>analysis<|message|>Thinking...",
+			"<|end|>",
+			"<|start|>assistant<|message|>Answer",
+			"<|end|>",
+		}
+		var got []string
+		for _, in := range inputs {
+			content, thinking, tool := handler.AddContent(in, tp)
+			if tool != "" {
+				tp.Add(tool)
+			}
+			if thinking != "" {
+				got = append(got, thinking)
+			}
+			if content != "" {
+				got = append(got, content)
+			}
+		}
+		want := []string{"Thinking...", "Answer"}
+		if !reflect.DeepEqual(got, want) {
+			t.Fatalf("content pieces mismatch: got %v want %v", got, want)
+		}
+	})
+
+	t.Run("partial_tags_buffer_until_complete", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		inputs := []string{
+			"<|chan",
+			"nel|>analysis<|mess",
+			"age|>Deep ",
+			"thought",
+			"<|end|>",
+			"<|start|>assistant<|message|>Done",
+			"<|end|>",
+		}
+		var thinkingPieces []string
+		var contentPieces []string
+		for _, in := range inputs {
+			content, thinking, tool := handler.AddContent(in, tp)
+			if tool != "" {
+				tp.Add(tool)
+			}
+			if thinking != "" {
+				thinkingPieces = append(thinkingPieces, thinking)
+			}
+			if content != "" {
+				contentPieces = append(contentPieces, content)
+			}
+		}
+		if want := []string{"Deep ", "thought"}; !reflect.DeepEqual(thinkingPieces, want) {
+			t.Fatalf("thinking pieces mismatch: got %v want %v", thinkingPieces, want)
+		}
+		if want := []string{"Done"}; !reflect.DeepEqual(contentPieces, want) {
+			t.Fatalf("content pieces mismatch: got %v want %v", contentPieces, want)
+		}
+	})
+
+	t.Run("simple_assistant_after_analysis", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		inputs := []string{
+			"<|channel|>analysis<|message|>Think",
+			"<|end|>",
+			"<|start|>assistant<|message|>Answer",
+			"<|end|>",
+		}
+		var contentSb, thinkingSb strings.Builder
+		for _, in := range inputs {
+			content, thinking, tool := handler.AddContent(in, tp)
+			if tool != "" {
+				tp.Add(tool)
+			}
+			contentSb.WriteString(content)
+			thinkingSb.WriteString(thinking)
+		}
+		if contentSb.String() != "Answer" {
+			t.Fatalf("content mismatch: got %q want %q", contentSb.String(), "Answer")
+		}
+		if thinkingSb.String() != "Think" {
+			t.Fatalf("thinking mismatch: got %q want %q", thinkingSb.String(), "Think")
+		}
+	})
+
+	t.Run("tool_call_parsed_and_returned_correctly", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		inputs := []string{
+			"<|channel|>commentary to=functions.calculate<|message|>{\"expression\":\"2+2\"}<|end|>",
+		}
+		for _, in := range inputs {
+			content, thinking, tool := handler.AddContent(in, tp)
+			if content != "" || thinking != "" {
+				continue
+			}
+			if tool != "" {
+				tp.Add(tool)
+			}
+		}
+		name, args := tp.Drain()
+		if name == nil || *name != "functions.calculate" {
+			t.Fatalf("unexpected tool name: %v", name)
+		}
+		if got, want := args, "{\"expression\":\"2+2\"}"; got != want {
+			t.Fatalf("unexpected tool args: got %s want %s", got, want)
+		}
+	})
+
+	t.Run("tool_call_across_chunks", func(t *testing.T) {
+		handler := NewHarmonyMessageHandler()
+		handler.HarmonyParser.AddImplicitStart()
+		tp := handler.CreateToolParser()
+		inputs := []string{
+			"<|channel|>commentary to=functions.calculate<|message|>{\"expression\":\"2+",
+			"2\"}",
+			"<|end|>",
+		}
+		for _, in := range inputs {
+			content, thinking, tool := handler.AddContent(in, tp)
+			if content != "" || thinking != "" {
+				continue
+			}
+			if tool != "" {
+				tp.Add(tool)
+			}
+		}
+		name, args := tp.Drain()
+		if name == nil || *name != "functions.calculate" {
+			t.Fatalf("unexpected tool name: %v", name)
+		}
+		if got, want := args, "{\"expression\":\"2+2\"}"; got != want {
+			t.Fatalf("unexpected tool args: got %s want %s", got, want)
+		}
+	})
+}

integration/api_test.go

@@ -410,99 +410,3 @@ func TestAPIEmbeddings(t *testing.T) {
 		t.Errorf("zero length embedding response")
 	}
 }
-
-func TestAPIToolCalling(t *testing.T) {
-	initialTimeout := 60 * time.Second
-	streamTimeout := 30 * time.Second
-	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
-	defer cancel()
-
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	modelName := "qwen3:0.6b"
-	if err := PullIfMissing(ctx, client, modelName); err != nil {
-		t.Fatalf("pull failed %s", err)
-	}
-
-	tools := []api.Tool{
-		{
-			Type: "function",
-			Function: api.ToolFunction{
-				Name:        "get_weather",
-				Description: "Get the current weather in a given location",
-				Parameters: api.ToolFunctionParameters{
-					Type:     "object",
-					Required: []string{"location"},
-					Properties: map[string]api.ToolProperty{
-						"location": {
-							Type:        api.PropertyType{"string"},
-							Description: "The city and state, e.g. San Francisco, CA",
-						},
-					},
-				},
-			},
-		},
-	}
-
-	req := api.ChatRequest{
-		Model: modelName,
-		Messages: []api.Message{
-			{
-				Role:    "user",
-				Content: "Call get_weather with location set to San Francisco.",
-			},
-		},
-		Tools: tools,
-		Options: map[string]any{
-			"temperature": 0,
-		},
-	}
-
-	stallTimer := time.NewTimer(initialTimeout)
-	var gotToolCall bool
-	var lastToolCall api.ToolCall
-
-	fn := func(response api.ChatResponse) error {
-		if len(response.Message.ToolCalls) > 0 {
-			gotToolCall = true
-			lastToolCall = response.Message.ToolCalls[len(response.Message.ToolCalls)-1]
-		}
-		if !stallTimer.Reset(streamTimeout) {
-			return fmt.Errorf("stall was detected while streaming response, aborting")
-		}
-		return nil
-	}
-
-	stream := true
-	req.Stream = &stream
-	done := make(chan int)
-	var genErr error
-	go func() {
-		genErr = client.Chat(ctx, &req, fn)
-		done <- 0
-	}()
-
-	select {
-	case <-stallTimer.C:
-		t.Errorf("tool-calling chat never started. Timed out after: %s", initialTimeout.String())
-	case <-done:
-		if genErr != nil {
-			t.Fatalf("chat failed: %v", genErr)
-		}
-
-		if !gotToolCall {
-			t.Fatalf("expected at least one tool call, got none")
-		}
-
-		if lastToolCall.Function.Name != "get_weather" {
-			t.Errorf("unexpected tool called: got %q want %q", lastToolCall.Function.Name, "get_weather")
-		}
-
-		if _, ok := lastToolCall.Function.Arguments["location"]; !ok {
-			t.Errorf("expected tool arguments to include 'location', got: %s", lastToolCall.Function.Arguments.String())
-		}
-	case <-ctx.Done():
-		t.Error("outer test context done while waiting for tool-calling chat")
-	}
-}

integration/concurrency_test.go

@@ -121,7 +121,6 @@ func TestMultiModelStress(t *testing.T) {
 	// The intent is to go 1 over what can fit so we force the scheduler to thrash
 	targetLoadCount := 0
 	slog.Info("Loading models to find how many can fit in VRAM before overflowing")
-chooseModels:
 	for i, model := range chosenModels {
 		req := &api.GenerateRequest{Model: model}
 		slog.Info("loading", "model", model)
@@ -143,13 +142,6 @@ chooseModels:
 				slog.Info("found model load capacity", "target", targetLoadCount, "current", loaded, "chosen", chosenModels[:targetLoadCount])
 				break
 			}
-			// Effectively limit model count to 2 on CPU only systems to avoid thrashing and timeouts
-			for _, m := range models.Models {
-				if m.SizeVRAM == 0 {
-					slog.Info("model running on CPU", "name", m.Name, "target", targetLoadCount, "chosen", chosenModels[:targetLoadCount])
-					break chooseModels
-				}
-			}
 		}
 	}
 	if targetLoadCount == len(chosenModels) {

integration/context_test.go

@@ -50,7 +50,7 @@ func TestContextExhaustion(t *testing.T) {
 	// Set up the test data
 	req := api.GenerateRequest{
 		Model:  smol,
-		Prompt: "Write me a story in english with a lot of emojis",
+		Prompt: "Write me a story with a ton of emojis?",
 		Stream: &stream,
 		Options: map[string]any{
 			"temperature": 0,

integration/embed_test.go

@@ -8,7 +8,6 @@ import (
 	"testing"
 	"time"
 
-	"github.com/google/go-cmp/cmp"
 	"github.com/ollama/ollama/api"
 )
 
@@ -39,14 +38,14 @@ func TestAllMiniLMEmbeddings(t *testing.T) {
 	defer cleanup()
 
 	req := api.EmbeddingRequest{
-		Model:     "all-minilm",
-		Prompt:    "why is the sky blue?",
-		KeepAlive: &api.Duration{Duration: 10 * time.Second},
+		Model:  "all-minilm",
+		Prompt: "why is the sky blue?",
 	}
 
 	res, err := embeddingTestHelper(ctx, client, t, req)
+
 	if err != nil {
-		t.Fatal(err)
+		t.Fatalf("error: %v", err)
 	}
 
 	if len(res.Embedding) != 384 {
@@ -74,8 +73,9 @@ func TestAllMiniLMEmbed(t *testing.T) {
 	}
 
 	res, err := embedTestHelper(ctx, client, t, req)
+
 	if err != nil {
-		t.Fatal(err)
+		t.Fatalf("error: %v", err)
 	}
 
 	if len(res.Embeddings) != 1 {
@@ -111,8 +111,9 @@ func TestAllMiniLMBatchEmbed(t *testing.T) {
 	}
 
 	res, err := embedTestHelper(ctx, client, t, req)
+
 	if err != nil {
-		t.Fatal(err)
+		t.Fatalf("error: %v", err)
 	}
 
 	if len(res.Embeddings) != 2 {
@@ -154,135 +155,93 @@ func TestAllMiniLMEmbedTruncate(t *testing.T) {
 
 	truncTrue, truncFalse := true, false
 
-	want, err := embedTestHelper(ctx, client, t, api.EmbedRequest{
-		Model: "all-minilm",
-		Input: "why",
-	})
-	if err != nil {
-		t.Fatal(err)
+	type testReq struct {
+		Name    string
+		Request api.EmbedRequest
 	}
 
-	cases := []struct {
-		name    string
-		request api.EmbedRequest
-		check   func(*api.EmbedResponse, error)
-	}{
+	reqs := []testReq{
 		{
-			name: "target truncation",
-			request: api.EmbedRequest{
+			Name: "Target Truncation",
+			Request: api.EmbedRequest{
 				Model: "all-minilm",
 				Input: "why",
 			},
-			check: func(got *api.EmbedResponse, err error) {
-				if err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
-					t.Errorf("embedding mismatch (-want +got):\n%s", diff)
-				}
-			},
 		},
 		{
-			name: "default truncate",
-			request: api.EmbedRequest{
+			Name: "Default Truncate",
+			Request: api.EmbedRequest{
 				Model:   "all-minilm",
 				Input:   "why is the sky blue?",
-				Options: map[string]any{"num_ctx": 3},
-			},
-			check: func(got *api.EmbedResponse, err error) {
-				if err != nil {
-					t.Fatal(err)
-				}
-				if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
-					t.Errorf("embedding mismatch (-want +got):\n%s", diff)
-				}
+				Options: map[string]any{"num_ctx": 1},
 			},
 		},
 		{
-			name: "explicit truncate",
-			request: api.EmbedRequest{
-				Model:    "all-minilm",
-				Input:    "why is the sky blue?",
-				Truncate: &truncTrue,
-				Options:  map[string]any{"num_ctx": 3},
-			},
-			check: func(got *api.EmbedResponse, err error) {
-				if err != nil {
-					t.Fatal(err)
-				}
-				if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
-					t.Errorf("embedding mismatch (-want +got):\n%s", diff)
-				}
-			},
-		},
-		{
-			name: "truncate error",
-			request: api.EmbedRequest{
-				Model:    "all-minilm",
-				Input:    "why is the sky blue?",
-				Truncate: &truncFalse,
-				Options:  map[string]any{"num_ctx": 3},
-			},
-			check: func(res *api.EmbedResponse, err error) {
-				if err.Error() != "input exceeds maximum context length" {
-					t.Fatalf("expected truncation error, got: %v", err)
-				}
-			},
-		},
-		{
-			name: "input after truncate error",
-			request: api.EmbedRequest{
+			Name: "Explicit Truncate",
+			Request: api.EmbedRequest{
 				Model:    "all-minilm",
 				Input:    "why is the sky blue?",
 				Truncate: &truncTrue,
 				Options:  map[string]any{"num_ctx": 1},
 			},
-			check: func(res *api.EmbedResponse, err error) {
-				if err.Error() != "input after truncation exceeds maximum context length" {
-					t.Fatalf("expected truncation error, got: %v", err)
-				}
-			},
-		},
-		{
-			name: "input after truncate error",
-			request: api.EmbedRequest{
-				Model:    "all-minilm",
-				Input:    "why is the sky blue?",
-				Truncate: &truncTrue,
-				Options:  map[string]any{"num_ctx": 0},
-			},
-			check: func(res *api.EmbedResponse, err error) {
-				if err.Error() != "input after truncation exceeds maximum context length" {
-					t.Fatalf("expected truncation error, got: %v", err)
-				}
-			},
 		},
 	}
 
-	for _, req := range cases {
-		t.Run(req.name, func(t *testing.T) {
-			req.check(embedTestHelper(ctx, client, t, req.request))
-		})
+	res := make(map[string]*api.EmbedResponse)
+
+	for _, req := range reqs {
+		response, err := embedTestHelper(ctx, client, t, req.Request)
+		if err != nil {
+			t.Fatalf("error: %v", err)
+		}
+		res[req.Name] = response
+	}
+
+	if res["Target Truncation"].Embeddings[0][0] != res["Default Truncate"].Embeddings[0][0] {
+		t.Fatal("expected default request to truncate correctly")
+	}
+
+	if res["Default Truncate"].Embeddings[0][0] != res["Explicit Truncate"].Embeddings[0][0] {
+		t.Fatal("expected default request and truncate true request to be the same")
+	}
+
+	// check that truncate set to false returns an error if context length is exceeded
+	_, err := embedTestHelper(ctx, client, t, api.EmbedRequest{
+		Model:    "all-minilm",
+		Input:    "why is the sky blue?",
+		Truncate: &truncFalse,
+		Options:  map[string]any{"num_ctx": 1},
+	})
+
+	if err == nil {
+		t.Fatal("expected error, got nil")
 	}
 }
 
 func embeddingTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbeddingRequest) (*api.EmbeddingResponse, error) {
-	t.Helper()
-
 	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatal(err)
+		t.Fatalf("failed to pull model %s: %v", req.Model, err)
 	}
 
-	return client.Embeddings(ctx, &req)
+	response, err := client.Embeddings(ctx, &req)
+
+	if err != nil {
+		return nil, err
+	}
+
+	return response, nil
 }
 
 func embedTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) {
-	t.Helper()
-
 	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatal(err)
+		t.Fatalf("failed to pull model %s: %v", req.Model, err)
 	}
 
-	return client.Embed(ctx, &req)
+	response, err := client.Embed(ctx, &req)
+
+	if err != nil {
+		return nil, err
+	}
+
+	return response, nil
 }

integration/utils_test.go

@@ -502,22 +502,6 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
 		done <- 0
 	}()
 
-	var response string
-	verify := func() {
-		// Verify the response contains the expected data
-		response = buf.String()
-		atLeastOne := false
-		for _, resp := range anyResp {
-			if strings.Contains(strings.ToLower(response), resp) {
-				atLeastOne = true
-				break
-			}
-		}
-		if !atLeastOne {
-			t.Fatalf("%s: none of %v found in %s", genReq.Model, anyResp, response)
-		}
-	}
-
 	select {
 	case <-stallTimer.C:
 		if buf.Len() == 0 {
@@ -533,14 +517,21 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
 		if genErr != nil {
 			t.Fatalf("%s failed with %s request prompt %s", genErr, genReq.Model, genReq.Prompt)
 		}
-		verify()
+		// Verify the response contains the expected data
+		response := buf.String()
+		atLeastOne := false
+		for _, resp := range anyResp {
+			if strings.Contains(strings.ToLower(response), resp) {
+				atLeastOne = true
+				break
+			}
+		}
+		if !atLeastOne {
+			t.Fatalf("%s: none of %v found in %s", genReq.Model, anyResp, response)
+		}
 		slog.Info("test pass", "model", genReq.Model, "prompt", genReq.Prompt, "contains", anyResp, "response", response)
 	case <-ctx.Done():
-		// On slow systems, we might timeout before some models finish rambling, so check what we have so far to see
-		// if it's considered a pass - the stallTimer will detect hangs, but we want to consider slow systems a pass
-		// if they are still generating valid responses
-		slog.Warn("outer test context done while waiting for generate")
-		verify()
+		t.Error("outer test context done while waiting for generate")
 	}
 	return context
 }
@@ -561,7 +552,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
 			}, {
 				Model:     smol,
-				Prompt:    "how do rainbows form? Be brief but factual in your reply",
+				Prompt:    "what is the origin of the US thanksgiving holiday? Be brief but factual in your reply",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
 			}, {
@@ -579,9 +570,9 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 		[][]string{
 			{"sunlight", "scattering", "interact", "color", "surface", "depth", "red", "orange", "yellow", "absorbs", "wavelength"},
 			{"soil", "organic", "earth", "black", "tan", "chemical", "processes", "pigments", "particles", "iron oxide", "rust", "air", "water", "mixture", "mixing"},
-			{"water", "droplet", "refracted", "reflect", "color", "spectrum"},
+			{"england", "english", "massachusetts", "pilgrims", "colonists", "independence", "british", "feast", "family", "gatherings", "traditions", "turkey", "colonial", "period", "harvest", "agricultural", "european settlers", "american revolution", "civil war", "16th century", "17th century", "native american", "united states", "cultural", "hardship", "autumn", "festival"},
 			{"fourth", "july", "declaration", "independence"},
-			{"nitrogen", "oxygen", "carbon", "dioxide", "water", "vapor"},
+			{"nitrogen", "oxygen", "carbon", "dioxide"},
 		}
 }
 
@@ -608,22 +599,6 @@ func DoChat(ctx context.Context, t *testing.T, client *api.Client, req api.ChatR
 		done <- 0
 	}()
 
-	var response string
-	verify := func() {
-		// Verify the response contains the expected data
-		response = buf.String()
-		atLeastOne := false
-		for _, resp := range anyResp {
-			if strings.Contains(strings.ToLower(response), resp) {
-				atLeastOne = true
-				break
-			}
-		}
-		if !atLeastOne {
-			t.Fatalf("%s: none of %v found in \"%s\" -- request was:%v", req.Model, anyResp, response, req.Messages)
-		}
-	}
-
 	select {
 	case <-stallTimer.C:
 		if buf.Len() == 0 {
@@ -639,14 +614,23 @@ func DoChat(ctx context.Context, t *testing.T, client *api.Client, req api.ChatR
 		if genErr != nil {
 			t.Fatalf("%s failed with %s request prompt %v", genErr, req.Model, req.Messages)
 		}
-		verify()
+
+		// Verify the response contains the expected data
+		response := buf.String()
+		atLeastOne := false
+		for _, resp := range anyResp {
+			if strings.Contains(strings.ToLower(response), resp) {
+				atLeastOne = true
+				break
+			}
+		}
+		if !atLeastOne {
+			t.Fatalf("%s: none of %v found in \"%s\" -- request was:%v", req.Model, anyResp, response, req.Messages)
+		}
+
 		slog.Info("test pass", "model", req.Model, "messages", req.Messages, "contains", anyResp, "response", response)
 	case <-ctx.Done():
-		// On slow systems, we might timeout before some models finish rambling, so check what we have so far to see
-		// if it's considered a pass - the stallTimer will detect hangs, but we want to consider slow systems a pass
-		// if they are still generating valid responses
-		slog.Warn("outer test context done while waiting for chat")
-		verify()
+		t.Error("outer test context done while waiting for generate")
 	}
 	return &api.Message{Role: role, Content: buf.String()}
 }

llama/llama.go

@@ -515,34 +515,33 @@ func (c *MtmdContext) NewEmbed(llamaContext *Context, data []byte) ([][]float32,
 	}
 	nChunks := C.mtmd_input_chunks_size(ic)
 	numEmbed := llamaContext.Model().NEmbd()
-	embed := make([][]float32, 0)
+	lastChunkSize := 0
 	for i := range int(nChunks) {
 		chunk := C.mtmd_input_chunks_get(ic, C.size_t(i))
 		numTokens := int(C.mtmd_input_chunk_get_n_tokens(chunk))
-		slog.Debug("chunk tokens", "index", i, "numTokens", numTokens)
+		lastChunkSize = numTokens
 
 		// Encode the chunk
 		if C.int32_t(0) != C.mtmd_encode_chunk(c.c, chunk) {
 			return nil, errors.New("unable to encode mtmd image chunk")
 		}
-
-		// Get the embeddings for this chunk
-		chunkEmbed := make([][]float32, numTokens)
-		chunkEmbd := C.mtmd_get_output_embd(c.c)
-		if nil == chunkEmbd {
-			continue
-		}
-
-		// Extend the embedding array for each token
-		s := unsafe.Slice((*float32)(chunkEmbd), numTokens*numEmbed)
-		rows := make([]float32, len(s))
-		copy(rows, s)
-		for i := range numTokens {
-			chunkEmbed[i] = rows[i*numEmbed : (i+1)*numEmbed]
-		}
-		embed = append(embed, chunkEmbed...)
 	}
-	slog.Debug("image embeddings", "totalEmbeddings", len(embed))
+
+	// Get the embeddings
+	embed := make([][]float32, lastChunkSize)
+	embd := C.mtmd_get_output_embd(c.c)
+	if nil == embd {
+		return nil, errors.New("failed to get image embedding")
+	}
+
+	// Extend the embedding array for each token
+	s := unsafe.Slice((*float32)(embd), numEmbed*lastChunkSize)
+	rows := make([]float32, len(s))
+	copy(rows, s)
+	for i := range lastChunkSize {
+		embed[i] = rows[i*numEmbed : (i+1)*numEmbed]
+	}
+
 	return embed, nil
 }
 

llm/memory.go

@@ -202,7 +202,7 @@ func estimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 	var kvct string
 	if useFlashAttention {
 		requested := strings.ToLower(envconfig.KvCacheType())
-		if f.SupportsKVCacheType(requested) {
+		if requested != "" && f.SupportsKVCacheType(requested) {
 			kvct = requested
 		}
 	}

llm/server.go

@@ -148,11 +148,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 	var textProcessor model.TextProcessor
 	var err error
 	if envconfig.NewEngine() || f.KV().OllamaEngineRequired() {
-		if len(projectors) == 0 {
-			textProcessor, err = model.NewTextProcessor(modelPath)
-		} else {
-			err = errors.New("split vision models aren't supported")
-		}
+		textProcessor, err = model.NewTextProcessor(modelPath)
 		if err != nil {
 			// To prepare for opt-out mode, instead of treating this as an error, we fallback to the old runner
 			slog.Debug("model not yet supported by Ollama engine, switching to compatibility mode", "model", modelPath, "error", err)
@@ -165,6 +161,11 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 		}
 	}
 
+	newEstimates := textProcessor != nil && envconfig.NewMemoryEstimates()
+	if newEstimates {
+		slog.Info("enabling new memory estimates")
+	}
+
 	// Verify the requested context size is <= the model training size
 	trainCtx := f.KV().ContextLength()
 	if opts.NumCtx > int(trainCtx) && trainCtx > 0 {
@@ -219,7 +220,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 
 		// Flash Attention also supports kv cache quantization
 		// Enable if the requested and kv cache type is supported by the model
-		if f.SupportsKVCacheType(kvct) {
+		if kvct != "" && f.SupportsKVCacheType(kvct) {
 			loadRequest.KvCacheType = kvct
 		} else {
 			slog.Warn("kv cache type not supported by model", "type", kvct)
@@ -432,7 +433,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 			}
 		}()
 
-		if textProcessor != nil {
+		if newEstimates {
 			return &ollamaServer{llmServer: s}, nil
 		} else {
 			return &llamaServer{llmServer: s, ggml: f}, nil
@@ -1348,7 +1349,9 @@ type CompletionRequest struct {
 	Images  []ImageData
 	Options *api.Options
 
-	Grammar string // set before sending the request to the subprocess
+	Grammar       string // set before sending the request to the subprocess
+	UseHarmony    bool
+	PrefillString string
 }
 
 // DoneReason represents the reason why a completion response is done
@@ -1361,6 +1364,8 @@ const (
 	DoneReasonLength
 	// DoneReasonConnectionClosed indicates the completion stopped due to the connection being closed
 	DoneReasonConnectionClosed
+	// DoneReasonTokenRepeatLimit indicates the completion stopped due to a token repeat limit
+	DoneReasonTokenRepeatLimit
 )
 
 func (d DoneReason) String() string {
@@ -1369,19 +1374,23 @@ func (d DoneReason) String() string {
 		return "length"
 	case DoneReasonStop:
 		return "stop"
+	case DoneReasonTokenRepeatLimit:
+		return "token_repeat_limit"
 	default:
 		return "" // closed
 	}
 }
 
 type CompletionResponse struct {
-	Content            string        `json:"content"`
-	DoneReason         DoneReason    `json:"done_reason"`
-	Done               bool          `json:"done"`
-	PromptEvalCount    int           `json:"prompt_eval_count"`
-	PromptEvalDuration time.Duration `json:"prompt_eval_duration"`
-	EvalCount          int           `json:"eval_count"`
-	EvalDuration       time.Duration `json:"eval_duration"`
+	Content            string         `json:"content"`
+	Thinking           string         `json:"thinking"`
+	ToolCalls          []api.ToolCall `json:"tool_calls"`
+	DoneReason         DoneReason     `json:"done_reason"`
+	Done               bool           `json:"done"`
+	PromptEvalCount    int            `json:"prompt_eval_count"`
+	PromptEvalDuration time.Duration  `json:"prompt_eval_duration"`
+	EvalCount          int            `json:"eval_count"`
+	EvalDuration       time.Duration  `json:"eval_duration"`
 }
 
 func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {
@@ -1499,7 +1508,8 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				return fmt.Errorf("error unmarshalling llm prediction response: %v", err)
 			}
 			switch {
-			case strings.TrimSpace(c.Content) == lastToken:
+			// TODO(parthsareen): token repeat limit is now handled in the runner, this currently support legacy model and can be removed in the future
+			case strings.TrimSpace(c.Content) == lastToken && c.Content != "":
 				tokenRepeat++
 			default:
 				lastToken = strings.TrimSpace(c.Content)
@@ -1512,16 +1522,14 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				return ctx.Err()
 			}
 
-			if c.Content != "" {
-				fn(CompletionResponse{
-					Content: c.Content,
-				})
-			}
-
 			if c.Done {
 				fn(c)
 				return nil
 			}
+
+			if c.Content != "" || c.Thinking != "" || len(c.ToolCalls) > 0 {
+				fn(c)
+			}
 		}
 	}
 

logutil/logutil.go

@@ -5,8 +5,6 @@ import (
 	"io"
 	"log/slog"
 	"path/filepath"
-	"runtime"
-	"time"
 )
 
 const LevelTrace slog.Level = -8
@@ -31,18 +29,10 @@ func NewLogger(w io.Writer, level slog.Level) *slog.Logger {
 	}))
 }
 
-type key string
-
 func Trace(msg string, args ...any) {
-	TraceContext(context.WithValue(context.TODO(), key("skip"), 1), msg, args...)
+	slog.Log(context.TODO(), LevelTrace, msg, args...)
 }
 
 func TraceContext(ctx context.Context, msg string, args ...any) {
-	if logger := slog.Default(); logger.Enabled(ctx, LevelTrace) {
-		skip, _ := ctx.Value(key("skip")).(int)
-		pc, _, _, _ := runtime.Caller(1 + skip)
-		record := slog.NewRecord(time.Now(), LevelTrace, msg, pc)
-		record.Add(args...)
-		logger.Handler().Handle(ctx, record)
-	}
+	slog.Log(ctx, LevelTrace, msg, args...)
 }

ml/backend.go

@@ -416,7 +416,6 @@ type Tensor interface {
 	AddID(ctx Context, t2, ids Tensor) Tensor
 
 	Softmax(ctx Context) Tensor
-	L2Norm(ctx Context, eps float32) Tensor
 	LayerNorm(ctx Context, weight, bias Tensor, eps float32) Tensor
 	RMSNorm(ctx Context, weight Tensor, eps float32) Tensor
 	Scale(ctx Context, s float64) Tensor
@@ -430,13 +429,12 @@ type Tensor interface {
 	Sin(ctx Context) Tensor
 	Cos(ctx Context) Tensor
 	Tanh(ctx Context) Tensor
-	GELU(ctx Context, up ...Tensor) Tensor
-	SILU(ctx Context, up ...Tensor) Tensor
-	RELU(ctx Context, up ...Tensor) Tensor
+	GELU(ctx Context) Tensor
+	QuickGELU(ctx Context) Tensor
+	SILU(ctx Context) Tensor
+	RELU(ctx Context) Tensor
 	Sigmoid(ctx Context) Tensor
-
-	// AlphaLimitSILU is a variant of SILU that clamps the input to the range [-limit, limit]
-	SILUAlphaLimit(ctx Context, up Tensor, alpha, limit float32) Tensor
+	SwiGLU(ctx Context, up Tensor, alpha, limit float32) Tensor
 
 	Reshape(ctx Context, shape ...int) Tensor
 	View(ctx Context, offset int, shape ...int) Tensor

ml/backend/ggml/ggml.go

@@ -1205,13 +1205,6 @@ func (t *Tensor) AddID(ctx ml.Context, t2, ids ml.Tensor) ml.Tensor {
 	}
 }
 
-func (t *Tensor) L2Norm(ctx ml.Context, eps float32) ml.Tensor {
-	return &Tensor{
-		b: t.b,
-		t: C.ggml_l2_norm(ctx.(*Context).ctx, t.t, C.float(eps)),
-	}
-}
-
 func (t *Tensor) LayerNorm(ctx ml.Context, w, b ml.Tensor, eps float32) ml.Tensor {
 	tt := C.ggml_norm(ctx.(*Context).ctx, t.t, C.float(eps))
 	if w != nil {
@@ -1431,46 +1424,35 @@ func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int
 	}
 }
 
-func (t *Tensor) GELU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
-	if len(t2) > 0 {
-		return &Tensor{
-			b: t.b,
-			t: C.ggml_geglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
-		}
-	}
+func (t *Tensor) GELU(ctx ml.Context) ml.Tensor {
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_gelu_inplace(ctx.(*Context).ctx, t.t),
 	}
 }
 
-func (t *Tensor) SILU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
-	if len(t2) > 0 {
-		return &Tensor{
-			b: t.b,
-			t: C.ggml_swiglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
-		}
+func (t *Tensor) QuickGELU(ctx ml.Context) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_gelu_quick_inplace(ctx.(*Context).ctx, t.t),
 	}
+}
+
+func (t *Tensor) SILU(ctx ml.Context) ml.Tensor {
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_silu_inplace(ctx.(*Context).ctx, t.t),
 	}
 }
 
-func (t *Tensor) RELU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
-	if len(t2) > 0 {
-		return &Tensor{
-			b: t.b,
-			t: C.ggml_reglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
-		}
-	}
+func (t *Tensor) RELU(ctx ml.Context) ml.Tensor {
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_relu_inplace(ctx.(*Context).ctx, t.t),
 	}
 }
 
-func (t *Tensor) SILUAlphaLimit(ctx ml.Context, up ml.Tensor, alpha, limit float32) ml.Tensor {
+func (t *Tensor) SwiGLU(ctx ml.Context, up ml.Tensor, alpha, limit float32) ml.Tensor {
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_swiglu_oai(ctx.(*Context).ctx, t.t, up.(*Tensor).t, C.float(alpha), C.float(limit)),

ml/nn/attention.go

@@ -26,7 +26,6 @@ func Attention(ctx ml.Context, query, key, value ml.Tensor, scale float64, cache
 }
 
 func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scale float64, cache kvcache.Cache) ml.Tensor {
-	ctx.Forward(query)
 	if key != nil && value != nil {
 		if query.Dim(0) != key.Dim(0) {
 			panic(fmt.Errorf("d_k in attention operation does not match between query(%v) and key(%v)", query.Dim(0), key.Dim(0)))
@@ -40,7 +39,6 @@ func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scal
 			panic(fmt.Errorf("seq_len_k in attention operation does not match between key(%v) and value(%v)", key.Dim(2), value.Dim(2)))
 		}
 
-		ctx.Forward(key, value)
 		if cache != nil {
 			cache.Put(ctx, key, value)
 		}

ml/nn/pooling/pooling.go

@@ -1,42 +0,0 @@
-package pooling
-
-import (
-	"github.com/ollama/ollama/ml"
-)
-
-type Type uint32
-
-const (
-	TypeNone Type = iota
-	TypeMean
-	TypeCLS
-	TypeLast
-)
-
-func (t Type) String() string {
-	switch t {
-	case TypeMean:
-		return "Mean"
-	case TypeCLS:
-		return "CLS"
-	case TypeLast:
-		return "Last"
-	default:
-		return "Unknown"
-	}
-}
-
-func (t Type) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
-	switch t {
-	case TypeMean:
-		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
-		return hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
-	case TypeCLS:
-		return hiddenStates.View(ctx, 0, hiddenStates.Dim(0))
-	case TypeLast:
-		hiddenStates = hiddenStates.View(ctx, (hiddenStates.Dim(1)-1)*hiddenStates.Stride(1), hiddenStates.Dim(0))
-		return hiddenStates
-	default:
-		panic("unknown pooling type")
-	}
-}

ml/nn/pooling/pooling_test.go

@@ -1,79 +0,0 @@
-package pooling_test
-
-import (
-	"bytes"
-	"os"
-	"slices"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-	"github.com/ollama/ollama/discover"
-	fsggml "github.com/ollama/ollama/fs/ggml"
-	"github.com/ollama/ollama/ml"
-	"github.com/ollama/ollama/ml/backend/ggml"
-	"github.com/ollama/ollama/ml/nn/pooling"
-)
-
-func setup(tb testing.TB, n int) ml.Backend {
-	tb.Helper()
-
-	f, err := os.CreateTemp(tb.TempDir(), "*.bin")
-	if err != nil {
-		tb.Fatal(err)
-	}
-	defer f.Close()
-
-	if err := fsggml.WriteGGUF(f, fsggml.KV{
-		"general.architecture": "test",
-		"test.block_count":     uint32(1),
-	}, []*fsggml.Tensor{
-		{Name: "blk.0.weight", Shape: []uint64{1}, WriterTo: bytes.NewBuffer(make([]byte, 4))},
-	}); err != nil {
-		tb.Fatal(err)
-	}
-
-	var gpuLayers ml.GPULayersList
-	if gpus := discover.GetGPUInfo(); len(gpus) > 0 {
-		gpuLayers = append(gpuLayers, ml.GPULayers{
-			ID: gpus[0].ID,
-			Layers: slices.Collect(func(yield func(int) bool) {
-				for i := range n {
-					if !yield(i) {
-						return
-					}
-				}
-			}),
-		})
-	}
-	b, err := ggml.New(f.Name(), ml.BackendParams{AllocMemory: true, GPULayers: gpuLayers})
-	if err != nil {
-		tb.Fatal(err)
-	}
-
-	return b
-}
-
-func TestForward(t *testing.T) {
-	cases := map[pooling.Type][]float32{
-		pooling.TypeMean: {4, 5, 6, 7, 8, 9, 10, 11},
-		pooling.TypeCLS:  {0, 1, 2, 3, 4, 5, 6, 7},
-		pooling.TypeLast: {8, 9, 10, 11, 12, 13, 14, 15},
-	}
-	for typ, want := range cases {
-		t.Run(typ.String(), func(t *testing.T) {
-			b := setup(t, 99)
-			defer b.Close()
-
-			ctx := b.NewContext()
-			defer ctx.Close()
-
-			tt := ctx.Input().Arange(0, 16, 1, ml.DTypeF32).Reshape(ctx, 8, 2)
-			tt = typ.Forward(ctx, tt)
-
-			ctx.Forward(tt).Compute(tt)
-			if diff := cmp.Diff(want, tt.Floats()); diff != "" {
-				t.Error(diff)
-			}
-		})
-	}
-}

model/input/input.go

@@ -54,9 +54,10 @@ type Batch struct {
 	// Inputs is the input tokens, including placeholders for multimodal inputs.
 	Inputs ml.Tensor
 
-	// Outputs are the set of indicies into Inputs for which output data should
-	// be returned.
-	Outputs ml.Tensor
+	// Multimodal is a set of multimodal embeddings previously created by
+	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
+	// models or for batches without multimodal elements.
+	Multimodal []MultimodalIndex
 
 	// Positions is the position for each Input, relative to its sequence. Equal
 	// in length to Inputs.
@@ -65,8 +66,7 @@ type Batch struct {
 	// Sequences is the sequence for each Input. Equal in length to Inputs.
 	Sequences []int
 
-	// Multimodal is a set of multimodal embeddings previously created by
-	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
-	// models or for batches without multimodal elements.
-	Multimodal []MultimodalIndex
+	// Outputs are the set of indicies into Inputs for which output data should
+	// be returned.
+	Outputs []int32
 }

model/model.go

@@ -5,6 +5,7 @@ import (
 	"fmt"
 	_ "image/jpeg"
 	_ "image/png"
+	"math"
 	"os"
 	"reflect"
 	"strconv"
@@ -20,15 +21,10 @@ import (
 	"github.com/ollama/ollama/logutil"
 	"github.com/ollama/ollama/ml"
 	_ "github.com/ollama/ollama/ml/backend"
-	"github.com/ollama/ollama/ml/nn/pooling"
 	"github.com/ollama/ollama/model/input"
 )
 
-var (
-	ErrNoVisionModel        = errors.New("this model is missing data required for image input")
-	ErrUnsupportedModel     = errors.New("model not supported")
-	ErrUnsupportedTokenizer = errors.New("tokenizer not supported")
-)
+var ErrNoVisionModel = errors.New("this model is missing data required for image input")
 
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {
@@ -107,12 +103,23 @@ func New(modelPath string, params ml.BackendParams) (Model, error) {
 		return nil, err
 	}
 
-	m, err := modelForArch(b.Config())
+	arch := b.Config().Architecture()
+	if b.Config().Uint("pooling_type", math.MaxUint32) != math.MaxUint32 {
+		arch = arch + "_embed"
+	}
+
+	f, ok := models[arch]
+	if !ok {
+		return nil, fmt.Errorf("unsupported model architecture %q", arch)
+	}
+
+	m, err := f(b.Config())
 	if err != nil {
 		return nil, err
 	}
 
 	base := Base{b: b, config: m.Config()}
+
 	v := reflect.ValueOf(m)
 	v.Elem().Set(populateFields(base, v.Elem()))
 	return m, nil
@@ -124,38 +131,30 @@ func NewTextProcessor(s string) (TextProcessor, error) {
 		return nil, err
 	}
 	defer r.Close()
-
 	meta, err := fsggml.Decode(r, -1)
 	if err != nil {
 		return nil, err
 	}
+	return getTextProcessor(meta.KV())
+}
 
-	m, err := modelForArch(meta.KV())
+func getTextProcessor(kv fsggml.KV) (TextProcessor, error) {
+	arch := kv.Architecture()
+	f, ok := models[arch]
+	if !ok {
+		return nil, fmt.Errorf("unsupported model architecture %q", arch)
+	}
+	m, err := f(kv)
 	if err != nil {
 		return nil, err
 	}
-
 	tp, ok := m.(TextProcessor)
 	if !ok {
-		return nil, ErrUnsupportedTokenizer
+		return nil, fmt.Errorf("%v is not a TextProcessor", m)
 	}
 	return tp, nil
 }
 
-func modelForArch(c fs.Config) (Model, error) {
-	arch := c.Architecture()
-	if pooling.Type(c.Uint("pooling_type")) != pooling.TypeNone {
-		arch = arch + "_embed"
-	}
-
-	f, ok := models[arch]
-	if !ok {
-		return nil, ErrUnsupportedModel
-	}
-
-	return f(c)
-}
-
 func populateFields(base Base, v reflect.Value, tags ...Tag) reflect.Value {
 	t := v.Type()
 
@@ -243,7 +242,7 @@ func setPointer(base Base, v reflect.Value, tags []Tag) {
 		vv = vv.Elem()
 	}
 
-	vv = reflect.Indirect(vv)
+	vv = vv.Elem()
 	if v.IsNil() {
 		vv = reflect.New(v.Type().Elem()).Elem()
 	}

model/model_test.go

@@ -1,9 +1,9 @@
 package model
 
 import (
-	"errors"
 	"reflect"
 	"slices"
+	"strings"
 	"testing"
 
 	"github.com/google/go-cmp/cmp"
@@ -12,6 +12,7 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/backend/ggml"
 	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/model/input"
 )
 
 func TestParseTags(t *testing.T) {
@@ -147,58 +148,39 @@ func TestPopulateFieldsAlternateName(t *testing.T) {
 	}
 }
 
-func TestModelForArch(t *testing.T) {
-	type fakeModel struct {
-		Model
+func TestGetTextProcessor(t *testing.T) {
+	tp, err := getTextProcessor(fsggml.KV{})
+	if err == nil {
+		t.Error("expected error")
+	} else if !strings.Contains(err.Error(), "unsupported model architecture") {
+		t.Errorf("unexpected error: %v", err)
+	} else if tp != nil {
+		t.Error("expected nil tp")
 	}
 
-	type fakeEmbeddingModel struct {
-		Model
+	models["dummy"] = func(fs.Config) (Model, error) {
+		return notTextProcessorModel{}, nil
 	}
-
-	models["model"] = func(c fs.Config) (Model, error) { return fakeModel{}, nil }
-	models["model_embed"] = func(c fs.Config) (Model, error) { return fakeEmbeddingModel{}, nil }
-
-	cases := []struct {
-		name   string
-		config fs.Config
-		want   any
-		err    error
-	}{
-		{
-			name: "model",
-			config: fsggml.KV{
-				"general.architecture": "model",
-			},
-			want: fakeModel{},
-		},
-		{
-			name: "embedding",
-			config: fsggml.KV{
-				"general.architecture": "model",
-				"model.pooling_type":   uint32(1),
-			},
-			want: fakeEmbeddingModel{},
-		},
-		{
-			name: "unsupported",
-			config: fsggml.KV{
-				"general.architecture": "unsupported",
-			},
-			err: ErrUnsupportedModel,
-		},
-	}
-
-	for _, tt := range cases {
-		t.Run(tt.name, func(t *testing.T) {
-			got, err := modelForArch(tt.config)
-			if !errors.Is(err, tt.err) {
-				t.Fatal(err)
-			}
-
-			if diff := cmp.Diff(tt.want, got); diff != "" {
-				t.Errorf("modelForArch() returned unexpected values (-want +got):\n%s", diff)
-			}
-		})
+	tp, err = getTextProcessor(fsggml.KV{"general.architecture": "dummy"})
+	if err == nil {
+		t.Error("expected error")
+	} else if !strings.Contains(err.Error(), "not a TextProcessor") {
+		t.Errorf("unexpected error: %v", err)
+	} else if tp != nil {
+		t.Error("expected nil tp")
 	}
 }
+
+type notTextProcessorModel struct{}
+
+func (notTextProcessorModel) Forward(ml.Context, input.Batch) (ml.Tensor, error) {
+	panic("unimplemented")
+}
+
+func (notTextProcessorModel) Backend() ml.Backend {
+	panic("unimplemented")
+}
+
+func (notTextProcessorModel) Config() config {
+	panic("unimplemented")
+}

model/models/bert/embed.go

@@ -1,181 +0,0 @@
-package bert
-
-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/pooling"
-	"github.com/ollama/ollama/model"
-	"github.com/ollama/ollama/model/input"
-)
-
-type Model struct {
-	model.Base
-	model.TextProcessor
-
-	TokenEmbedding     *nn.Embedding `gguf:"token_embd"`
-	TypeEmbedding      *nn.Embedding `gguf:"token_types"`
-	PositionEmbedding  *nn.Embedding `gguf:"position_embd"`
-	TokenEmbeddingNorm *nn.LayerNorm `gguf:"token_embd_norm"`
-
-	Layers []EncoderLayer `gguf:"blk"`
-
-	Options
-}
-
-// Forward implements model.Model.
-func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
-	hiddenStates = hiddenStates.Add(ctx, m.TypeEmbedding.Weight.View(ctx, 0, m.hiddenSize))
-	hiddenStates = hiddenStates.Add(ctx, m.PositionEmbedding.Forward(ctx, ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))))
-	hiddenStates = m.TokenEmbeddingNorm.Forward(ctx, hiddenStates, m.eps)
-
-	for _, layer := range m.Layers {
-		hiddenStates = layer.Forward(ctx, hiddenStates, &m.Options)
-	}
-
-	hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
-	if m.normalize {
-		hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
-	}
-
-	return hiddenStates, nil
-}
-
-type EncoderLayer struct {
-	*Attention
-	AttentionNorm *nn.LayerNorm `gguf:"attn_output_norm"`
-
-	*MLP
-	MLPNorm *nn.LayerNorm `gguf:"layer_output_norm"`
-}
-
-func (e *EncoderLayer) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
-	// Attention
-	residual := hiddenStates
-	hiddenStates = e.Attention.Forward(ctx, hiddenStates, opts)
-	hiddenStates = hiddenStates.Add(ctx, residual)
-	hiddenStates = e.AttentionNorm.Forward(ctx, hiddenStates, opts.eps)
-
-	// MLP
-	residual = hiddenStates
-	hiddenStates = e.MLP.Forward(ctx, hiddenStates, opts)
-	hiddenStates = hiddenStates.Add(ctx, residual)
-	hiddenStates = e.MLPNorm.Forward(ctx, hiddenStates, opts.eps)
-
-	return hiddenStates
-}
-
-type Attention struct {
-	Query     *nn.Linear    `gguf:"attn_q"`
-	QueryNorm *nn.LayerNorm `gguf:"attn_q_norm"`
-
-	Key     *nn.Linear    `gguf:"attn_k"`
-	KeyNorm *nn.LayerNorm `gguf:"attn_k_norm"`
-
-	Value *nn.Linear `gguf:"attn_v"`
-
-	Output *nn.Linear `gguf:"attn_output"`
-}
-
-func (a *Attention) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
-	batchSize := hiddenStates.Dim(1)
-
-	query := a.Query.Forward(ctx, hiddenStates)
-	if a.QueryNorm != nil {
-		query = a.QueryNorm.Forward(ctx, query, opts.eps)
-	}
-	query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
-
-	key := a.Key.Forward(ctx, hiddenStates)
-	if a.KeyNorm != nil {
-		key = a.KeyNorm.Forward(ctx, key, opts.eps)
-	}
-	key = key.Reshape(ctx, opts.headDim(), cmp.Or(opts.numKVHeads, opts.numHeads), batchSize)
-
-	value := a.Value.Forward(ctx, hiddenStates)
-	value = value.Reshape(ctx, opts.headDim(), cmp.Or(opts.numKVHeads, opts.numHeads), batchSize)
-
-	attention := nn.Attention(ctx, query, key, value, 1/math.Sqrt(float64(opts.headDim())), nil)
-	attention = attention.Reshape(ctx, opts.hiddenSize, batchSize)
-	return a.Output.Forward(ctx, attention)
-}
-
-type MLP struct {
-	Up   *nn.Linear `gguf:"ffn_up"`
-	Down *nn.Linear `gguf:"ffn_down"`
-}
-
-func (m *MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
-	return m.Down.Forward(ctx, m.Up.Forward(ctx, hiddenStates).GELU(ctx))
-}
-
-type Options struct {
-	hiddenSize,
-	numHeads,
-	numKVHeads,
-	keyLength,
-	valueLength int
-	poolingType pooling.Type
-	eps         float32
-	normalize   bool
-}
-
-func (o Options) headDim() int {
-	return cmp.Or(o.keyLength, o.valueLength, o.hiddenSize/o.numHeads)
-}
-
-func New(c fs.Config) (model.Model, error) {
-	var processor model.TextProcessor
-	switch c.String("tokenizer.ggml.model", "bert") {
-	case "bert":
-		processor = model.NewWordPiece(
-			&model.Vocabulary{
-				Values: c.Strings("tokenizer.ggml.tokens"),
-				Scores: c.Floats("tokenizer.ggml.scores"),
-				Types:  c.Ints("tokenizer.ggml.token_type"),
-				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
-				BOS: []int32{
-					int32(cmp.Or(
-						c.Uint("tokenizer.ggml.cls_token_id"),
-						c.Uint("tokenizer.ggml.bos_token_id"),
-					)),
-				},
-				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", true),
-				EOS: []int32{
-					int32(cmp.Or(
-						c.Uint("tokenizer.ggml.separator_token_id"),
-						//nolint:misspell
-						// NOTE: "seperator_token_id" is a typo in model metadata but we need to
-						// support it for compatibility.
-						c.Uint("tokenizer.ggml.seperator_token_id"),
-						c.Uint("tokenizer.ggml.eos_token_id"),
-					)),
-				},
-			},
-		)
-	default:
-		return nil, model.ErrUnsupportedTokenizer
-	}
-
-	return &Model{
-		TextProcessor: processor,
-		Layers:        make([]EncoderLayer, c.Uint("block_count")),
-		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_epsilon"),
-			poolingType: pooling.Type(c.Uint("pooling_type")),
-			normalize:   c.Bool("normalize_embeddings", true),
-		},
-	}, nil
-}
-
-func init() {
-	model.Register("bert", New)
-	model.Register("bert_embed", New)
-}

model/models/gemma2/model.go

@@ -24,7 +24,7 @@ type Options struct {
 
 type Model struct {
 	model.Base
-	model.SentencePiece
+	model.SentencePieceModel
 
 	TokenEmbedding *nn.Embedding `gguf:"token_embd"`
 	Layers         []Layer       `gguf:"blk"`
@@ -40,7 +40,7 @@ const (
 
 func New(c fs.Config) (model.Model, error) {
 	m := Model{
-		SentencePiece: model.NewSentencePiece(
+		SentencePieceModel: model.NewSentencePieceModel(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -63,7 +63,7 @@ func New(c fs.Config) (model.Model, error) {
 			attnValLen:        int(c.Uint("attention.value_length")),
 			eps:               c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:          c.Float("rope.freq_base", 10000.0),
-			ropeScale:         c.Float("rope.scaling.factor", 1.0),
+			ropeScale:         c.Float("rope.freq_scale", 1.0),
 			attnLogitSoftcap:  c.Float("attn_logit_softcapping"),
 			finalLogitSoftcap: c.Float("final_logit_softcapping"),
 		},
@@ -88,7 +88,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
-	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	if opts.largeModelScaling {
 		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
@@ -98,7 +98,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
-	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
@@ -128,7 +128,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 }
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.Options.attnKeyLen, m.Options.ropeBase, 1/m.Options.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.Options.attnKeyLen, m.Options.ropeBase, m.Options.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 type MLP struct {
@@ -138,7 +138,7 @@ type MLP struct {
 }
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -176,6 +176,7 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
+	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
 	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
@@ -192,7 +193,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 		var lastLayerOutputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			lastLayerOutputs = batch.Outputs
+			lastLayerOutputs = outputs
 		}
 
 		hiddenState = layer.Forward(ctx, hiddenState, positions, lastLayerOutputs, m.Cache, m.Options)

model/models/gemma3/embed.go

@@ -1,38 +1,49 @@
 package gemma3
 
 import (
+	"errors"
+
 	"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/ml/nn/pooling"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
 )
 
 type embedModel struct {
 	model.Base
-	model.SentencePiece
+	model.SentencePieceModel
 
 	*TextModel
-	poolingType pooling.Type
+	PoolingType uint32
 
 	Dense [2]*nn.Linear `gguf:"dense"`
 }
 
 func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	batch.Outputs = batch.Positions // return all positions
 	hiddenStates := m.TextModel.Forward(ctx, batch, m.Cache)
-	hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
+
+	switch m.PoolingType {
+	case 0: // None
+	case 1: // Mean
+		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
+		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	default:
+		return nil, errors.New("unsupported pooling type")
+	}
+
 	for _, dense := range m.Dense {
 		hiddenStates = dense.Forward(ctx, hiddenStates)
 	}
-	hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
+
 	return hiddenStates, nil
 }
 
 func newEmbedModel(c fs.Config) (model.Model, error) {
 	m := &embedModel{
-		SentencePiece: model.NewSentencePiece(
+		SentencePieceModel: model.NewSentencePieceModel(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -50,7 +61,7 @@ func newEmbedModel(c fs.Config) (model.Model, error) {
 			},
 		),
 		TextModel:   newTextModel(c),
-		poolingType: pooling.Type(c.Uint("pooling_type", 0)),
+		PoolingType: c.Uint("pooling_type", 0),
 	}
 
 	m.Cache = kvcache.NewWrapperCache(

model/models/gemma3/model.go

@@ -16,7 +16,7 @@ import (
 
 type Model struct {
 	model.Base
-	model.SentencePiece
+	model.SentencePieceModel
 
 	*VisionModel `gguf:"v"`
 	*TextModel
@@ -55,7 +55,7 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
 
 func New(c fs.Config) (model.Model, error) {
 	m := Model{
-		SentencePiece: model.NewSentencePiece(
+		SentencePieceModel: model.NewSentencePieceModel(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),

model/models/gemma3/model_text.go

@@ -53,10 +53,7 @@ func newTextModel(c fs.Config) *TextModel {
 			eps:            c.Float("attention.layer_norm_rms_epsilon", 1e-06),
 			ropeLocalBase:  c.Float("rope.local.freq_base", 10000.0),
 			ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0),
-			ropeScale:      1,
-			// NOTE: the rope.scaling.factor is set incorrectly in the official QAT weights
-			//       (8 instead of 1)
-			// ropeScale:      c.Float("rope.scaling.factor", 1.0),
+			ropeScale:      c.Float("rope.freq_scale", 1.0),
 		},
 	}
 
@@ -87,7 +84,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
 	q = sa.QueryNorm.Forward(ctx, q, opts.eps)
-	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	if opts.largeModelScaling {
 		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
@@ -98,7 +95,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
 	k = sa.KeyNorm.Forward(ctx, k, opts.eps)
-	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
@@ -116,7 +113,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
 		ropeBase = m.TextConfig.ropeGlobalBase
 	}
 
-	return fast.RoPE(ctx, key, shift, m.TextConfig.attnKeyLen, ropeBase, 1/m.TextConfig.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.TextConfig.attnKeyLen, ropeBase, m.TextConfig.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 type TextMLP struct {
@@ -126,7 +123,7 @@ type TextMLP struct {
 }
 
 func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextConfig) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -164,6 +161,7 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 
 func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cache) ml.Tensor {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
+	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
 	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextConfig.hiddenSize)))
@@ -196,7 +194,7 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
 
 		var lastLayerOutputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			lastLayerOutputs = batch.Outputs
+			lastLayerOutputs = outputs
 		}
 
 		hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextConfig)

model/models/gemma3n/model.go

@@ -10,7 +10,7 @@ import (
 
 type Model struct {
 	model.Base
-	model.SentencePiece
+	model.SentencePieceModel
 
 	*TextModel
 }
@@ -23,7 +23,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 func New(c fs.Config) (model.Model, error) {
 	m := Model{
 		TextModel: newTextModel(c),
-		SentencePiece: model.NewSentencePiece(
+		SentencePieceModel: model.NewSentencePieceModel(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),

model/models/gemma3n/model_text.go

@@ -83,7 +83,7 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
 
 	hiddenStates = hiddenStates.Permute(ctx, 1, 2, 0, 3).Contiguous(ctx).Mean(ctx)
 	hiddenStates = hiddenStates.Permute(ctx, 2, 0, 1, 3).Contiguous(ctx)
-	hiddenStates = hiddenStates.Rows(ctx, batch.Outputs)
+	hiddenStates = hiddenStates.Rows(ctx, ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)))
 
 	hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps)
 	return m.Output.Forward(ctx, hiddenStates), nil
@@ -95,7 +95,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
 		ropeBase = m.ropeBaseLocal
 	}
 
-	return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 type TextScaledWordEmbedding struct {
@@ -170,7 +170,8 @@ func (d TextLayer) Forward(ctx ml.Context, hiddenStates, perLayerInput, position
 	}
 
 	active = d.PerLayerInputGate.Forward(ctx, active)
-	active = active.GELU(ctx, perLayerInput)
+	active = active.GELU(ctx)
+	active = active.Mul(ctx, perLayerInput)
 
 	active = d.PerLayerProjection.Forward(ctx, active)
 	active = d.PostPerLayerNorm.Forward(ctx, active, opts.eps)
@@ -256,14 +257,14 @@ func (attn TextAttention) Forward(ctx ml.Context, hiddenStates, positions ml.Ten
 	query := attn.Query.Forward(ctx, hiddenStates)
 	query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
 	query = attn.QueryNorm.Forward(ctx, query, opts.eps)
-	query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	var key, value ml.Tensor
 	if !sharedKV {
 		key = attn.Key.Forward(ctx, hiddenStates)
 		key = key.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
 		key = attn.KeyNorm.Forward(ctx, key, opts.eps)
-		key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+		key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 		value = attn.Value.Forward(ctx, hiddenStates)
 		value = value.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
@@ -291,7 +292,7 @@ func (mlp TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, activationSpa
 		hiddenStates = hiddenStates.Sub(ctx, cutoff).RELU(ctx)
 	}
 
-	hiddenStates = hiddenStates.GELU(ctx, upStates)
+	hiddenStates = hiddenStates.GELU(ctx).Mul(ctx, upStates)
 	hiddenStates = mlp.Down.Forward(ctx, hiddenStates)
 	return hiddenStates
 }
@@ -349,7 +350,7 @@ func newTextModel(c fs.Config) *TextModel {
 			eps:           c.Float("attention.layer_norm_rms_epsilon", 1e-06),
 			ropeBase:      c.Float("rope.freq_base", 1_000_000),
 			ropeBaseLocal: c.Float("rope.freq_base_local", 10_000),
-			ropeScale:     c.Float("rope.scaling.factor", 1.0),
+			ropeScale:     c.Float("rope.freq_scale", 1.0),
 
 			slidingWindowPattern:    c.Bools("attention.sliding_window_pattern"),
 			activationSparsityScale: c.Floats("activation_sparsity_scale"),

model/models/gptoss/model.go

@@ -41,8 +41,8 @@ func (m *Transformer) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, err
 		}
 
 		var outputs ml.Tensor
-		if i == len(m.TransformerBlocks)-1 {
-			outputs = batch.Outputs
+		if len(batch.Outputs) > 0 && i == len(m.TransformerBlocks)-1 {
+			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 		}
 
 		hiddenStates = block.Forward(ctx, hiddenStates, positions, outputs, one, m.Cache, &m.Options)
@@ -210,7 +210,7 @@ func (mlp *MLPBlock) Forward(ctx ml.Context, hiddenStates, one ml.Tensor, opts *
 		up = mlp.Up.Forward(ctx, hiddenStates, selectedExperts)
 	}
 
-	hiddenStates = gate.SILUAlphaLimit(ctx, up, 1.702, 7)
+	hiddenStates = gate.SwiGLU(ctx, up, 1.702, 7)
 
 	experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts)
 	experts = experts.Mul(ctx, routingWeights)

model/models/llama/model.go

@@ -2,6 +2,7 @@ package llama
 
 import (
 	"cmp"
+	"fmt"
 	"math"
 
 	"github.com/ollama/ollama/fs"
@@ -22,60 +23,51 @@ type Options struct {
 
 type Model struct {
 	model.Base
-	model.TextProcessor
+	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
+	*Options
 }
 
 func New(c fs.Config) (model.Model, error) {
-	if c.Uint("expert_count") > 0 {
-		// TODO: support mixtures of experts
-		return nil, model.ErrUnsupportedModel
+	// This model currently only supports the gpt2 tokenizer
+	if c.String("tokenizer.ggml.model") == "llama" {
+		return nil, fmt.Errorf("unsupported tokenizer: llama")
 	}
-
-	var processor model.TextProcessor
-	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")...,
-		),
+	// Best effort detection of library/deepseek-coder model(s) which are incompatible
+	if c.String("general.name") == "deepseek-ai" {
+		return nil, fmt.Errorf("unsupported model: %s", c.String("general.name"))
 	}
-	switch c.String("tokenizer.ggml.model") {
-	case "gpt2":
-		processor = model.NewBytePairEncoding(
-			`(?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+`,
-			&vocabulary,
-		)
-	case "llama":
-		processor = model.NewSentencePiece(&vocabulary)
-	default:
-		return nil, model.ErrUnsupportedTokenizer
-	}
-
 	m := Model{
-		TextProcessor: processor,
-		Layers:        make([]Layer, c.Uint("block_count")),
-		Options: Options{
+		BytePairEncoding: model.NewBytePairEncoding(
+			c.String("tokenizer.ggml.pretokenizer", `(?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+`),
+			&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")...,
+				),
+			},
+		),
+		Layers: make([]Layer, c.Uint("block_count")),
+		Options: &Options{
 			hiddenSize: int(c.Uint("embedding_length")),
 			numHeads:   int(c.Uint("attention.head_count")),
 			numKVHeads: int(c.Uint("attention.head_count_kv")),
 			headDim:    int(c.Uint("attention.key_length")),
 			ropeDim:    int(c.Uint("rope.dimension_count")),
 			eps:        c.Float("attention.layer_norm_rms_epsilon"),
-			ropeBase:   c.Float("rope.freq_base", 1e5),
-			ropeScale:  c.Float("rope.scaling.factor", 1),
+			ropeBase:   c.Float("rope.freq_base"),
+			ropeScale:  c.Float("rope.freq_scale", 1),
 		},
 	}
 
@@ -106,8 +98,8 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.Tenso
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
 
-	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
-	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 
 	attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache)
 	attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize)
@@ -116,7 +108,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.Tenso
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads)
-	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(m.Layers[layer].SelfAttention.RopeFactors)), nil
+	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(m.Layers[layer].SelfAttention.RopeFactors)), nil
 }
 
 type MLP struct {
@@ -126,7 +118,7 @@ type MLP struct {
 }
 
 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))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -168,10 +160,10 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 		var outputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			outputs = batch.Outputs
+			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 		}
 
-		hiddenState = layer.Forward(ctx, hiddenState, positions, outputs, m.Cache, &m.Options)
+		hiddenState = layer.Forward(ctx, hiddenState, positions, outputs, m.Cache, m.Options)
 	}
 
 	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)

model/models/llama4/model.go

@@ -176,7 +176,9 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache), nil
+	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
+
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
 }
 
 func init() {

model/models/llama4/model_text.go

@@ -33,8 +33,8 @@ func (sa *TextAttention) Forward(ctx ml.Context, hiddenStates, positions, attent
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
 
 	if useRope {
-		query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
-		key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+		query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+		key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 	}
 
 	if opts.useQKNorm {
@@ -58,14 +58,14 @@ type TextMLP struct {
 }
 
 func (mlp *TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
 type TextExperts struct {
-	Gate *nn.LinearBatch `gguf:"ffn_gate_exps"`
-	Up   *nn.LinearBatch `gguf:"ffn_up_exps"`
-	Down *nn.LinearBatch `gguf:"ffn_down_exps"`
+	Gate *nn.Linear `gguf:"ffn_gate_exps"`
+	Up   *nn.Linear `gguf:"ffn_up_exps"`
+	Down *nn.Linear `gguf:"ffn_down_exps"`
 }
 
 func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tensor, opts *TextOptions) ml.Tensor {
@@ -76,9 +76,9 @@ func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tens
 	hiddenStates = hiddenStates.Repeat(ctx, 1, opts.numExpertsUsed)
 	hiddenStates = hiddenStates.Mul(ctx, scores)
 
-	upStates := e.Up.Forward(ctx, hiddenStates, experts)
-	gateStates := e.Gate.Forward(ctx, hiddenStates, experts)
-	downStates := e.Down.Forward(ctx, upStates.Mul(ctx, gateStates.SILU(ctx)), experts)
+	upStates := e.Up.Weight.MulmatID(ctx, hiddenStates, experts)
+	gateStates := e.Gate.Weight.MulmatID(ctx, hiddenStates, experts)
+	downStates := e.Down.Weight.MulmatID(ctx, upStates.Mul(ctx, gateStates.SILU(ctx)), experts)
 
 	nextStates := downStates.View(ctx, 0, hiddenStates.Dim(0), downStates.Stride(2), hiddenStates.Dim(2))
 	for i := 1; i < opts.numExpertsUsed; i++ {
@@ -96,7 +96,7 @@ type TextSharedExpert struct {
 }
 
 func (mlp *TextSharedExpert) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
@@ -196,7 +196,7 @@ func newTextModel(c fs.Config) *TextModel {
 			numExpertsUsed:             int(c.Uint("expert_used_count")),
 			ropeDim:                    int(c.Uint("rope.dimension_count")),
 			ropeBase:                   c.Float("rope.freq_base"),
-			ropeScale:                  c.Float("rope.scaling.factor", 1),
+			ropeScale:                  c.Float("rope.freq_scale", 1),
 			eps:                        c.Float("attention.layer_norm_rms_epsilon"),
 			interleaveLayerStep:        int(c.Uint("interleave_moe_layer_step", 1)),
 			noRopeInterval:             int(c.Uint("no_rope_interval", 4)),
@@ -248,5 +248,5 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(m.Layers[layer].Attention.RopeFactors)), nil
+	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(m.Layers[layer].Attention.RopeFactors)), nil
 }

model/models/mistral3/model.go

@@ -159,8 +159,9 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
+	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
 }
 
 func init() {

model/models/mistral3/model_text.go

@@ -40,11 +40,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale)
+	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale)
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale)
+	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale)
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -55,7 +55,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale), nil
+	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale), nil
 }
 
 type MLP struct {
@@ -65,7 +65,7 @@ type MLP struct {
 }
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -132,7 +132,7 @@ func newTextModel(c fs.Config) *TextModel {
 			ropeDim:    int(c.Uint("rope.dimension_count")),
 			eps:        c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:   c.Float("rope.freq_base"),
-			ropeScale:  c.Float("rope.scaling.factor", 1),
+			ropeScale:  c.Float("rope.freq_scale", 1),
 		},
 	}
 }

model/models/mistral3/model_vision.go

@@ -51,7 +51,7 @@ type VisionMLP struct {
 }
 
 func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 

model/models/mllama/model.go

@@ -107,9 +107,10 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	}
 
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
+	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
 	// TODO: attention mask, cross attention mask
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
 }
 
 func init() {

model/models/mllama/model_text.go

@@ -26,11 +26,11 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.T
 
 	query := sa.Query.Forward(ctx, hiddenState)
 	query = query.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 
 	key := sa.Key.Forward(ctx, hiddenState)
 	key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -45,7 +45,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.T
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	// This will only get called for layers in the cache, which are just the self attention layers
 	if sa, ok := m.Transformer.Layers[layer].(*TextSelfAttentionDecoderLayer); ok {
-		return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(sa.SelfAttention.RopeFactors)), nil
+		return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(sa.SelfAttention.RopeFactors)), nil
 	}
 
 	return key, nil
@@ -58,7 +58,7 @@ type TextMLP struct {
 }
 
 func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextModelOptions) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -244,7 +244,7 @@ func newTextModel(c fs.Config) *TextModel {
 			ropeDim:              int(c.Uint("rope.dimension_count")),
 			eps:                  c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:             c.Float("rope.freq_base"),
-			ropeScale:            c.Float("rope.scaling.factor", 1),
+			ropeScale:            c.Float("rope.freq_scale", 1),
 			crossAttentionLayers: c.Ints("attention.cross_attention_layers"),
 		},
 	}

model/models/models.go

@@ -1,7 +1,6 @@
 package models
 
 import (
-	_ "github.com/ollama/ollama/model/models/bert"
 	_ "github.com/ollama/ollama/model/models/gemma2"
 	_ "github.com/ollama/ollama/model/models/gemma3"
 	_ "github.com/ollama/ollama/model/models/gemma3n"

model/models/qwen2/model.go

@@ -43,8 +43,8 @@ func (attn Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor,
 	value := attn.Value.Forward(ctx, hiddenStates)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
 
-	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
-	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache)
 	attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize)
@@ -59,7 +59,7 @@ type MLP struct {
 }
 
 func (mlp MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
@@ -111,7 +111,7 @@ func (m Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 		var outputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			outputs = batch.Outputs
+			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 		}
 
 		hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, &m.Options)
@@ -124,7 +124,7 @@ func (m Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 func (m Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads)
-	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 func New(c fs.Config) (model.Model, error) {
@@ -160,7 +160,7 @@ func New(c fs.Config) (model.Model, error) {
 			headDim:    int(c.Uint("attention.key_length")),
 			ropeDim:    int(c.Uint("rope.dimension_count")),
 			ropeBase:   c.Float("rope.freq_base"),
-			ropeScale:  c.Float("rope.scaling.factor", 1),
+			ropeScale:  c.Float("rope.freq_scale", 1),
 			eps:        c.Float("attention.layer_norm_rms_epsilon"),
 		},
 	}

model/models/qwen25vl/model.go

@@ -140,8 +140,9 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
+	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache)
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache)
 }
 
 func init() {

model/models/qwen25vl/model_text.go

@@ -38,7 +38,7 @@ func NewTextModel(c fs.Config) *TextModel {
 			originalContextLength: int(c.Uint("context_length", 128000)),
 			eps:                   c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:              c.Float("rope.freq_base"),
-			ropeScale:             c.Float("rope.scaling.factor", 1),
+			ropeScale:             c.Float("rope.freq_scale", 1),
 		},
 	}
 
@@ -60,11 +60,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
+	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
+	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -78,7 +78,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 // Shift applies rotary position embeddings to the key tensor for causal attention caching
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithOriginalContextLength(m.originalContextLength), rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithOriginalContextLength(m.originalContextLength), rope.WithTypeNeoX()), nil
 }
 
 // MLP implements the feed-forward network component with SwiGLU activation
@@ -90,7 +90,7 @@ type MLP struct {
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
 	// Apply SwiGLU activation gating
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	// Project back to hidden dimension
 	return mlp.Down.Forward(ctx, hiddenState)
 }

model/models/qwen25vl/model_vision.go

@@ -100,7 +100,8 @@ type VisionMLP struct {
 func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
 	// Using activation as specified in config (likely GELU or SiLU/Swish)
 	gateOutput := mlp.Gate.Forward(ctx, hiddenStates)
-	hiddenStates = gateOutput.SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	upOutput := mlp.Up.Forward(ctx, hiddenStates)
+	hiddenStates = gateOutput.SILU(ctx).Mul(ctx, upOutput)
 
 	return mlp.Down.Forward(ctx, hiddenStates)
 }

model/models/qwen3/embed.go

@@ -1,73 +0,0 @@
-package qwen3
-
-import (
-	"github.com/ollama/ollama/fs"
-	"github.com/ollama/ollama/kvcache"
-	"github.com/ollama/ollama/ml"
-	"github.com/ollama/ollama/ml/nn/pooling"
-	"github.com/ollama/ollama/model"
-	"github.com/ollama/ollama/model/input"
-)
-
-type embedModel struct {
-	model.Base
-	model.BytePairEncoding
-
-	*Model
-	poolingType pooling.Type
-}
-
-func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	hiddenStates, err := m.forward(ctx, batch)
-	if err != nil {
-		return nil, err
-	}
-
-	hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
-	hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
-	return hiddenStates, nil
-}
-
-func newEmbed(c fs.Config) (model.Model, error) {
-	layers := make([]Layer, c.Uint("block_count"))
-	for i := range layers {
-		layers[i].MLP = &dense{}
-	}
-	m := embedModel{
-		BytePairEncoding: model.NewBytePairEncoding(
-			`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
-			&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")...,
-				),
-			},
-		),
-		Model: &Model{
-			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")),
-				keyLength:      int(c.Uint("attention.key_length")),
-				valueLength:    int(c.Uint("attention.value_length")),
-				eps:            c.Float("attention.layer_norm_rms_epsilon"),
-				ropeBase:       c.Float("rope.freq_base"),
-				ropeScale:      c.Float("rope.freq_scale", 1),
-				numExperts:     int(c.Uint("expert_count")),
-				numExpertsUsed: int(c.Uint("expert_used_count")),
-				normTopKProb:   c.Bool("norm_top_k_prob", true),
-			},
-		},
-		poolingType: pooling.Type(c.Uint("pooling_type")),
-	}
-
-	m.Cache = kvcache.NewCausalCache(m.Shift)
-	return &m, nil
-}

model/models/qwen3/model.go

@@ -30,10 +30,10 @@ func (o Options) headDim() int {
 }
 
 type Attention struct {
-	Query     *nn.Linear  `gguf:"attn_q"`
 	QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
-	Key       *nn.Linear  `gguf:"attn_k"`
+	Query     *nn.Linear  `gguf:"attn_q"`
 	KeyNorm   *nn.RMSNorm `gguf:"attn_k_norm"`
+	Key       *nn.Linear  `gguf:"attn_k"`
 	Value     *nn.Linear  `gguf:"attn_v"`
 	Output    *nn.Linear  `gguf:"attn_output"`
 }
@@ -52,8 +52,8 @@ func (sa *Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor,
 	query = sa.QueryNorm.Forward(ctx, query, opts.eps)
 	key = sa.KeyNorm.Forward(ctx, key, opts.eps)
 
-	query = fast.RoPE(ctx, query, positions, opts.headDim(), opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
-	key = fast.RoPE(ctx, key, positions, opts.headDim(), opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	query = fast.RoPE(ctx, query, positions, opts.headDim(), opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	key = fast.RoPE(ctx, key, positions, opts.headDim(), opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
 	attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim())), cache)
 	attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize)
@@ -65,10 +65,10 @@ type MLP interface {
 }
 
 type sparse struct {
-	Router *nn.Linear      `gguf:"ffn_gate_inp"`
-	Gate   *nn.LinearBatch `gguf:"ffn_gate_exps"`
-	Up     *nn.LinearBatch `gguf:"ffn_up_exps"`
-	Down   *nn.LinearBatch `gguf:"ffn_down_exps"`
+	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"`
 }
 
 func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
@@ -87,9 +87,13 @@ func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options
 
 	hiddenStates = hiddenStates.Reshape(ctx, hiddenStates.Dim(0), 1, hiddenStates.Dim(1))
 
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates, selectedExperts).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates, selectedExperts))
+	upStates := mlp.Up.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
 
-	experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts)
+	hiddenStates = mlp.Gate.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
+	hiddenStates = hiddenStates.SILU(ctx)
+	hiddenStates = hiddenStates.Mul(ctx, upStates)
+
+	experts := mlp.Down.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
 	experts = experts.Mul(ctx, routingWeights)
 
 	nextStates := experts.View(ctx, 0, experts.Dim(0), experts.Stride(2), experts.Dim(2))
@@ -107,8 +111,7 @@ type dense struct {
 }
 
 func (mlp *dense) Forward(ctx ml.Context, hiddenStates ml.Tensor, _ *Options) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).
-		SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
@@ -151,39 +154,29 @@ type Model struct {
 	*Options
 }
 
-func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	hiddenStates, err := m.forward(ctx, batch)
-	if err != nil {
-		return nil, err
-	}
-
-	return m.Output.Forward(ctx, hiddenStates), nil
-}
-
 // Forward implements model.Model.
-func (m *Model) forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 
 	hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 
 	for i, layer := range m.Layers {
-		if m.Cache != nil {
-			m.Cache.SetLayer(i)
-		}
+		m.Cache.SetLayer(i)
 
 		var outputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			outputs = batch.Outputs
+			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 		}
 
 		hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, m.Options)
 	}
 
-	return m.OutputNorm.Forward(ctx, hiddenStates, m.eps), nil
+	hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps)
+	return m.Output.Forward(ctx, hiddenStates), nil
 }
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.headDim(), m.ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.headDim(), m.ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 var _ model.Model = (*Model)(nil)
@@ -223,7 +216,7 @@ func New(c fs.Config) (model.Model, error) {
 			valueLength:    int(c.Uint("attention.value_length")),
 			eps:            c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:       c.Float("rope.freq_base"),
-			ropeScale:      c.Float("rope.scaling.factor", 1),
+			ropeScale:      c.Float("rope.freq_scale", 1),
 			numExperts:     int(c.Uint("expert_count")),
 			numExpertsUsed: int(c.Uint("expert_used_count")),
 			normTopKProb:   c.Bool("norm_top_k_prob", true),
@@ -237,5 +230,4 @@ func New(c fs.Config) (model.Model, error) {
 func init() {
 	model.Register("qwen3", New)
 	model.Register("qwen3moe", New)
-	model.Register("qwen3_embed", newEmbed)
 }

model/parsers/parsers.go

@@ -1,37 +0,0 @@
-package parsers
-
-import (
-	"github.com/ollama/ollama/api"
-)
-
-type Parser interface {
-	Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error)
-	HasToolSupport() bool
-	HasThinkingSupport() bool
-}
-
-func ParserForName(name string) Parser {
-	switch name {
-	case "qwen3-coder":
-		parser := &Qwen3CoderParser{}
-		return parser
-	case "passthrough":
-		return &PassthroughParser{}
-	default:
-		return nil
-	}
-}
-
-type PassthroughParser struct{}
-
-func (p *PassthroughParser) Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error) {
-	return s, "", nil, nil
-}
-
-func (p *PassthroughParser) HasToolSupport() bool {
-	return false
-}
-
-func (p *PassthroughParser) HasThinkingSupport() bool {
-	return false
-}

model/parsers/qwen3coder.go

@@ -1,447 +0,0 @@
-package parsers
-
-import (
-	"context"
-	"encoding/json"
-	"encoding/xml"
-	"fmt"
-	"log/slog"
-	"math"
-	"regexp"
-	"strconv"
-	"strings"
-	"unicode"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/logutil"
-)
-
-type qwenParserState int
-
-const (
-	toolOpenTag  = "<tool_call>"
-	toolCloseTag = "</tool_call>"
-)
-
-const (
-	qwenParserState_LookingForToolStart qwenParserState = iota
-	qwenParserState_CollectingToolContent
-)
-
-type Qwen3CoderParser struct {
-	state qwenParserState
-	acc   strings.Builder
-}
-
-func (p *Qwen3CoderParser) HasToolSupport() bool {
-	return true
-}
-
-func (p *Qwen3CoderParser) HasThinkingSupport() bool {
-	return false
-}
-
-func (p *Qwen3CoderParser) Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error) {
-	p.acc.WriteString(s)
-
-	events := p.parseEvents()
-
-	var toolCalls []api.ToolCall
-	var sb strings.Builder
-	for _, event := range events {
-		switch event := event.(type) {
-		case qwenEventRawToolCall:
-			toolCall, err := parseToolCall(event, tools)
-			if err != nil {
-				slog.Warn("qwen tool call parsing failed", "error", err)
-				return "", "", nil, err
-			}
-			toolCalls = append(toolCalls, toolCall)
-		case qwenEventContent:
-			// TODO(drifkin): if the same turn contains multiple interleaved content
-			// events, we naively append them together here. See the note below about
-			// `qwenEvent`s for more details
-			sb.WriteString(event.content)
-		}
-	}
-
-	return sb.String(), "", toolCalls, nil
-}
-
-func (p *Qwen3CoderParser) parseEvents() []qwenEvent {
-	var all []qwenEvent
-
-	keepLooping := true
-	for keepLooping {
-		var events []qwenEvent
-		events, keepLooping = eat(p)
-		if len(events) > 0 {
-			all = append(all, events...)
-		}
-	}
-
-	if len(all) > 0 {
-		slog.Log(context.TODO(), logutil.LevelTrace, "qwen events parsed", "events", all, "state", p.state, "acc", p.acc.String())
-	}
-
-	return all
-}
-
-// we use some internal event types in order to communicate between `Add` and
-// `eat`. We do this to support interleaving content and parallel tool calls in
-// the parser, even though qwen3-coder isn't supposed to do this. Our API
-// doesn't currently support models outputting multiple messages in a turn, so
-// we wouldn't be able to represent it yet, but there's no reason to prevent the
-// parser from supporting it, especially for future models if they end up using
-// a similar format.
-type qwenEvent interface {
-	isQwenEvent()
-}
-
-type qwenEventRawToolCall struct {
-	raw string
-}
-
-type qwenEventContent struct {
-	content string
-}
-
-func (qwenEventContent) isQwenEvent()     {}
-func (qwenEventRawToolCall) isQwenEvent() {}
-
-// eat consumes the parser's buffer, and returns a list of any unambiguous
-// events from the current parser state. If the parser transitions to another
-// state, it may have additional events to emit on the next call, which is what
-// the second return value indicates
-func eat(p *Qwen3CoderParser) ([]qwenEvent, bool) {
-	var events []qwenEvent
-
-	switch p.state {
-	case qwenParserState_LookingForToolStart:
-		if strings.Contains(p.acc.String(), toolOpenTag) {
-			// we found a full tool open tag, so we can emit the content before the
-			// tag, being sure to trim any trailing whitespace
-			split := strings.SplitN(p.acc.String(), toolOpenTag, 2)
-			before := split[0]
-			before = strings.TrimRightFunc(before, unicode.IsSpace)
-			if len(before) > 0 {
-				events = append(events, qwenEventContent{content: before})
-			}
-			after := split[1]
-			p.acc.Reset()
-			p.acc.WriteString(after)
-			p.state = qwenParserState_CollectingToolContent
-			return events, true
-		} else if overlap := overlap(p.acc.String(), toolOpenTag); overlap > 0 {
-			// we found a partial tool open tag, so we can emit the unambiguous part,
-			// which is the (trailing-whitespace trimmed) content before the partial
-			// tool open tag
-			beforePartialTag := p.acc.String()[:len(p.acc.String())-overlap]
-			trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
-			ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
-			unambiguous := p.acc.String()[:ambiguousStart]
-			ambiguous := p.acc.String()[ambiguousStart:]
-			p.acc.Reset()
-			p.acc.WriteString(ambiguous)
-			events = append(events, qwenEventContent{content: unambiguous})
-			return events, false
-		} else {
-			// we found content that is entirely not a tool call. We should withhold
-			// any trailing whitespace in case this is the end of the content
-			whitespaceLen := trailingWhitespaceLen(p.acc.String())
-			ambiguousStart := len(p.acc.String()) - whitespaceLen
-			unambiguous := p.acc.String()[:ambiguousStart]
-			ambiguous := p.acc.String()[ambiguousStart:]
-			p.acc.Reset()
-			p.acc.WriteString(ambiguous)
-			if len(unambiguous) > 0 {
-				events = append(events, qwenEventContent{content: unambiguous})
-			}
-			return events, false
-		}
-	case qwenParserState_CollectingToolContent:
-		if strings.Contains(p.acc.String(), toolCloseTag) {
-			split := strings.SplitN(p.acc.String(), toolCloseTag, 2)
-			before := split[0]
-			if len(before) == 0 {
-				slog.Warn("qwen tool call closing tag found but no content before it")
-			}
-			// remove any whitespace between the tool call and any content after it
-			after := strings.TrimLeftFunc(split[1], unicode.IsSpace)
-			p.acc.Reset()
-			p.acc.WriteString(after)
-			events = append(events, qwenEventRawToolCall{raw: before})
-			p.state = qwenParserState_LookingForToolStart
-			return events, true
-		} else {
-			// note that we don't need to check the overlap here because we only plan
-			// on parsing the tool call once we see the full closing tag. We don't
-			// stream back the unparsed tool content, so there's no need to be eager
-			// here
-			return events, false
-		}
-	default:
-		panic("unreachable")
-	}
-}
-
-// TODO(drifkin): move this to a shared location
-// longest overlap between suffix of s and prefix of delim
-func overlap(s, delim string) int {
-	max := min(len(delim), len(s))
-	for i := max; i > 0; i-- {
-		if strings.HasSuffix(s, delim[:i]) {
-			return i
-		}
-	}
-	return 0
-}
-
-func trailingWhitespaceLen(s string) int {
-	for i := len(s) - 1; i >= 0; i-- {
-		if !unicode.IsSpace(rune(s[i])) {
-			return len(s) - i - 1
-		}
-	}
-	return len(s)
-}
-
-type XMLFunctionCall struct {
-	XMLName    xml.Name       `xml:"function"`
-	Name       string         `xml:"name,attr"`
-	Parameters []XMLParameter `xml:"parameter"`
-}
-
-type XMLParameter struct {
-	Name  string `xml:"name,attr"`
-	Value string `xml:",chardata"`
-}
-
-// parseToolCall parses a raw tool call string into an api.ToolCall.
-// The raw string follows an xml-like format, here's an example:
-//
-// <function=get_current_temperature>
-// <parameter=location>
-// San Francisco
-// </parameter>
-// <parameter=unit>
-// celsius
-// </parameter>
-// </function>
-func parseToolCall(raw qwenEventRawToolCall, tools []api.Tool) (api.ToolCall, error) {
-	toolCall := api.ToolCall{}
-
-	xmlString := transformToXML(raw.raw)
-
-	var functionCall XMLFunctionCall
-	err := xml.Unmarshal([]byte(xmlString), &functionCall)
-	if err != nil {
-		return api.ToolCall{}, err
-	}
-
-	toolCall.Function = api.ToolCallFunction{
-		Name: functionCall.Name,
-	}
-
-	// Find the matching tool to get parameter types
-	var matchedTool *api.Tool
-	for i := range tools {
-		if tools[i].Function.Name == functionCall.Name {
-			matchedTool = &tools[i]
-			break
-		}
-	}
-
-	toolCall.Function.Arguments = make(api.ToolCallFunctionArguments)
-	for _, parameter := range functionCall.Parameters {
-		// Look up the parameter type if we found the tool
-		var paramType api.PropertyType
-		if matchedTool != nil && matchedTool.Function.Parameters.Properties != nil {
-			if prop, ok := matchedTool.Function.Parameters.Properties[parameter.Name]; ok {
-				paramType = prop.Type
-			}
-		}
-
-		toolCall.Function.Arguments[parameter.Name] = parseValue(parameter.Value, paramType)
-	}
-
-	return toolCall, nil
-}
-
-// parseValue converts a raw string value to the appropriate type based on the parameter type specification.
-//
-// For union types (multiple types in PropertyType, which we support but doesn't
-// seem as though the reference parser does type coercion with those types in
-// mind) we use a type precedence approach:
-// 1. null - checked first regardless of declared types (matches reference implementation)
-// 2. boolean - only "true"/"false" are valid booleans
-// 3. integer - must parse as a whole number
-// 4. number - must parse as numeric (returns int if no decimal part)
-// 5. array - must parse as valid JSON array
-// 6. object - must parse as valid JSON object
-// 7. string - always succeeds (least specific type)
-//
-// This precedence ensures we return the most specific type that successfully parses,
-// following the principle of least surprise. For example, with PropertyType{"string", "number"},
-// "123" becomes 123 (number), while "hello" becomes "hello" (string).
-func parseValue(raw string, paramType api.PropertyType) any {
-	// first remove a single leading newlines, and a single trailing newline (if
-	// they exist). This follows the reference implementation
-	raw = strings.TrimPrefix(raw, "\n")
-	raw = strings.TrimSuffix(raw, "\n")
-
-	// Check for null first (case-insensitive) - this takes precedence over any type
-	if strings.ToLower(raw) == "null" {
-		return nil
-	}
-
-	// If no type is specified, default to string
-	if len(paramType) == 0 {
-		return raw
-	}
-
-	// Check if any of the specified types match, using type precedence
-	// Order: boolean -> integer -> number -> array -> object -> string
-	typeSet := make(map[string]bool)
-	for _, t := range paramType {
-		typeSet[t] = true
-	}
-
-	// Try boolean first (most restrictive)
-	if typeSet["boolean"] {
-		lower := strings.ToLower(raw)
-		switch lower {
-		case "true":
-			return true
-		case "false":
-			return false
-		}
-		// If not a valid boolean but boolean is the only type, return false (matching reference)
-		if len(paramType) == 1 {
-			return false
-		}
-		// Otherwise try other types
-	}
-
-	// Try integer
-	if typeSet["integer"] {
-		if i, err := strconv.ParseInt(raw, 10, 64); err == nil {
-			// Return as int if it fits in int32, otherwise int64
-			if i >= math.MinInt32 && i <= math.MaxInt32 {
-				return int(i)
-			}
-			return i
-		}
-		// If integer is the only type and parsing failed, fall back to string
-		if len(paramType) == 1 {
-			return raw
-		}
-	}
-
-	// Try number (float)
-	if typeSet["number"] {
-		if f, err := strconv.ParseFloat(raw, 64); err == nil {
-			// If the number has no decimal part, return as int (matching reference)
-			if f == math.Trunc(f) {
-				i := int64(f)
-				if i >= math.MinInt32 && i <= math.MaxInt32 {
-					return int(i)
-				}
-				return i
-			}
-			return f
-		}
-		// If number is the only type and parsing failed, fall back to string
-		if len(paramType) == 1 {
-			return raw
-		}
-	}
-
-	// Try array
-	if typeSet["array"] {
-		var arr []interface{}
-		if err := json.Unmarshal([]byte(raw), &arr); err == nil {
-			return arr
-		}
-		// If array is the only type and parsing failed, fall back to string
-		if len(paramType) == 1 {
-			return raw
-		}
-	}
-
-	// Try object
-	if typeSet["object"] {
-		var obj map[string]interface{}
-		if err := json.Unmarshal([]byte(raw), &obj); err == nil {
-			return obj
-		}
-		// If object is the only type and parsing failed, fall back to string
-		if len(paramType) == 1 {
-			return raw
-		}
-	}
-
-	// String always succeeds (or if "string" is in the type set)
-	if typeSet["string"] {
-		return raw
-	}
-
-	// If we get here, none of the types matched and string wasn't an option
-	// We return string as a fallback. The reference implementation will attempt
-	// to parse the value as a python literal, but we purposefully don't support
-	// that
-	return raw
-}
-
-var (
-	qwenTagRegex    = regexp.MustCompile(`<(\w+)=([^>]+)>`)
-	qwenXMLTagRegex = regexp.MustCompile(`</?(?:function|parameter)(?:\s+name="[^"]*")?>`)
-)
-
-// transformToXML transforms a raw qwen tool call with xml-like tags into valid
-// xml so that it can be parsed by any xml parser
-func transformToXML(raw string) string {
-	// take the form `<tag=abc>` and transform it to `<tag name="abc">`, taking
-	// care to properly escape the string that becomes the attribute value
-	transformed := qwenTagRegex.ReplaceAllStringFunc(raw, func(match string) string {
-		groups := qwenTagRegex.FindStringSubmatch(match)
-		tag := groups[1]
-		var escapedValue strings.Builder
-		xml.EscapeText(&escapedValue, []byte(groups[2]))
-		return fmt.Sprintf(`<%s name="%s">`, tag, escapedValue.String())
-	})
-
-	// Walk the resulting string, escaping any character data that sits between the
-	// xml tags we just emitted
-	var out strings.Builder
-	lastIdx := 0
-	for _, loc := range qwenXMLTagRegex.FindAllStringIndex(transformed, -1) {
-		if loc[0] > lastIdx {
-			escapeTextNode(&out, transformed[lastIdx:loc[0]])
-		}
-		out.WriteString(transformed[loc[0]:loc[1]])
-		lastIdx = loc[1]
-	}
-	if lastIdx < len(transformed) {
-		escapeTextNode(&out, transformed[lastIdx:])
-	}
-
-	return out.String()
-}
-
-// escapeTextNode escapes XML character data without altering other characters
-// like newlines or tabs (which is why we don't use xml.EscapeText for this)
-func escapeTextNode(sb *strings.Builder, s string) {
-	for _, r := range s {
-		switch r {
-		case '&':
-			sb.WriteString("&amp;")
-		case '<':
-			sb.WriteString("&lt;")
-		case '>':
-			sb.WriteString("&gt;")
-		default:
-			sb.WriteRune(r)
-		}
-	}
-}

model/parsers/qwen3coder_test.go

@@ -1,878 +0,0 @@
-package parsers
-
-import (
-	"reflect"
-	"testing"
-
-	"github.com/ollama/ollama/api"
-)
-
-// tool creates a test tool with the given name and properties
-func tool(name string, props map[string]api.ToolProperty) api.Tool {
-	t := api.Tool{Type: "function", Function: api.ToolFunction{Name: name}}
-	t.Function.Parameters.Type = "object"
-	t.Function.Parameters.Properties = props
-	return t
-}
-
-func TestQwenParserStreaming(t *testing.T) {
-	type step struct {
-		input      string
-		wantEvents []qwenEvent
-	}
-
-	cases := []struct {
-		desc  string
-		steps []step
-		only  bool
-	}{
-		{
-			desc: "simple message streamed word by word",
-			steps: []step{
-				{
-					input:      "hi",
-					wantEvents: []qwenEvent{qwenEventContent{content: "hi"}},
-				},
-				{
-					input:      " there",
-					wantEvents: []qwenEvent{qwenEventContent{content: " there"}},
-				},
-			},
-		},
-		{
-			desc: "content before tool call",
-			steps: []step{
-				{
-					input:      "hi there<tool_call>",
-					wantEvents: []qwenEvent{qwenEventContent{content: "hi there"}},
-				},
-			},
-		},
-		{
-			desc: "multiple tool calls in one message",
-			steps: []step{
-				{
-					input: "before1<tool_call>in tool call</tool_call>after1<tool_call>in tool call 2</tool_call>after2",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "before1"},
-						qwenEventRawToolCall{raw: "in tool call"},
-						qwenEventContent{content: "after1"},
-						qwenEventRawToolCall{raw: "in tool call 2"},
-						qwenEventContent{content: "after2"},
-					},
-				},
-			},
-		},
-		{
-			desc: "tool calls with split tags",
-			steps: []step{
-				{
-					input: "before<tool",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "before"},
-					},
-				},
-				{
-					input:      "_call>in tool call</tool",
-					wantEvents: []qwenEvent{},
-				},
-				{
-					input: "_call>af",
-					wantEvents: []qwenEvent{
-						qwenEventRawToolCall{raw: "in tool call"},
-						qwenEventContent{content: "af"},
-					},
-				},
-				{
-					input: "ter",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "ter"},
-					},
-				},
-			},
-		},
-		{
-			desc: "trailing whitespace between content and tool call",
-			steps: []step{
-				{
-					input: "abc\n<tool_call>def</tool_call>",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "abc"},
-						qwenEventRawToolCall{raw: "def"},
-					},
-				},
-			},
-		},
-		{
-			desc: "trailing whitespace between tool call and content",
-			steps: []step{
-				{
-					input: "<tool_call>abc</tool_call>\ndef",
-					wantEvents: []qwenEvent{
-						qwenEventRawToolCall{raw: "abc"},
-						qwenEventContent{content: "def"},
-					},
-				},
-			},
-		},
-		{
-			desc: "empty content before tool call",
-			steps: []step{
-				{
-					input: "\n<tool_call>abc</tool_call>",
-					wantEvents: []qwenEvent{
-						qwenEventRawToolCall{raw: "abc"},
-					},
-				},
-			},
-		},
-		{
-			desc: "partial tool open tag fakeout",
-			steps: []step{
-				{
-					input: "abc\n<tool_call",
-					wantEvents: []qwenEvent{
-						// \n should not be emitted yet because `<tool_call` might be a tool
-						// open tag, in which case the whitespace should be trimmed
-						qwenEventContent{content: "abc"},
-					},
-				},
-				{
-					input: " fakeout",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "\n<tool_call fakeout"},
-					},
-				},
-			},
-		},
-		{
-			desc: "token-by-token whitespace handling",
-			steps: []step{
-				{
-					input: "a",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "a"},
-					},
-				},
-				{
-					input:      "\n",
-					wantEvents: []qwenEvent{},
-				},
-				{
-					input: "b",
-					wantEvents: []qwenEvent{
-						qwenEventContent{content: "\nb"},
-					},
-				},
-			},
-		},
-	}
-
-	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 := Qwen3CoderParser{}
-
-			for i, step := range tc.steps {
-				parser.acc.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)
-				}
-			}
-		})
-	}
-}
-
-func TestQwenToolParser(t *testing.T) {
-	type step struct {
-		name         string
-		rawToolCall  string
-		tools        []api.Tool
-		wantToolCall api.ToolCall
-	}
-
-	steps := []step{
-		{
-			name:  "simple tool call",
-			tools: []api.Tool{},
-			rawToolCall: `<function=get_current_temperature>
-<parameter=location>
-San Francisco
-</parameter>
-<parameter=unit>
-celsius
-</parameter>
-</function>`,
-			wantToolCall: api.ToolCall{
-				Function: api.ToolCallFunction{
-					Name: "get_current_temperature",
-					Arguments: map[string]any{
-						"location": "San Francisco",
-						"unit":     "celsius",
-					},
-				},
-			},
-		},
-		{
-			name:  "names with spaces",
-			tools: []api.Tool{},
-			rawToolCall: `<function=get current temperature>
-<parameter=location with spaces>
-San Francisco
-</parameter>
-<parameter=unit with spaces>
-celsius
-</parameter>
-</function>`,
-			wantToolCall: api.ToolCall{
-				Function: api.ToolCallFunction{
-					Name: "get current temperature",
-					Arguments: map[string]any{
-						"location with spaces": "San Francisco",
-						"unit with spaces":     "celsius",
-					},
-				},
-			},
-		},
-		// this mirrors the reference implementation's behavior, but unclear if it
-		// ever happens. If so, then we should probably remove them instead, this
-		// test is to just document the current behavior and test that we don't get
-		// xml errors
-		{
-			name:  "names with quotes",
-			tools: []api.Tool{},
-			rawToolCall: `<function="get current temperature">
-<parameter="location with spaces">
-San Francisco
-</parameter>
-<parameter="unit with spaces">
-"celsius"
-</parameter>
-</function>`,
-			wantToolCall: api.ToolCall{
-				Function: api.ToolCallFunction{
-					Name: "\"get current temperature\"",
-					Arguments: map[string]any{
-						"\"location with spaces\"": "San Francisco",
-						"\"unit with spaces\"":     "\"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: `<function=calculate>
-<parameter=x>
-3.14
-</parameter>
-<parameter=y>
-42
-</parameter>
-<parameter=enabled>
-true
-</parameter>
-<parameter=items>
-["a", "b", "c"]
-</parameter>
-</function>`,
-			wantToolCall: api.ToolCall{
-				Function: api.ToolCallFunction{
-					Name: "calculate",
-					Arguments: map[string]any{
-						"x":       3.14,
-						"y":       42,
-						"enabled": true,
-						"items":   []any{"a", "b", "c"},
-					},
-				},
-			},
-		},
-		// regression test for <https://github.com/ollama/ollama/issues/12357>
-		{
-			name:  "ampersands in parameter values",
-			tools: []api.Tool{},
-			rawToolCall: `<function=exec>
-<parameter=command>
-ls && echo "done"
-</parameter>
-</function>`,
-			wantToolCall: api.ToolCall{
-				Function: api.ToolCallFunction{
-					Name: "exec",
-					Arguments: map[string]any{
-						"command": "ls && echo \"done\"",
-					},
-				},
-			},
-		},
-		{
-			name:  "angle brackets in parameter values",
-			tools: []api.Tool{},
-			rawToolCall: `<function=exec>
-<parameter=command>
-ls && echo "a > b and a < b"
-</parameter>
-</function>`,
-			wantToolCall: api.ToolCall{
-				Function: api.ToolCallFunction{
-					Name: "exec",
-					Arguments: map[string]any{
-						"command": "ls && echo \"a > b and a < b\"",
-					},
-				},
-			},
-		},
-	}
-
-	for i, step := range steps {
-		gotToolCall, err := parseToolCall(qwenEventRawToolCall{raw: step.rawToolCall}, step.tools)
-		if err != nil {
-			t.Errorf("step %d (%s): %v", i, step.name, err)
-		}
-		if !reflect.DeepEqual(gotToolCall, step.wantToolCall) {
-			t.Errorf("step %d (%s): got tool call %#v, want %#v", i, step.name, gotToolCall, step.wantToolCall)
-		}
-	}
-}
-
-func TestQwenToolCallValueParsing(t *testing.T) {
-	cases := []struct {
-		desc      string
-		raw       string
-		paramType api.PropertyType
-		want      any
-	}{
-		{
-			desc:      "default string value (no type specified)",
-			paramType: api.PropertyType{},
-			raw:       "some-string",
-			want:      "some-string",
-		},
-		{
-			desc:      "trim a single leading and trailing newline",
-			paramType: api.PropertyType{},
-			raw:       "\nsome-string\n",
-			want:      "some-string",
-		},
-		{
-			desc:      "trim at most one leading and trailing newline",
-			paramType: api.PropertyType{},
-			raw:       "\n\nsome-string\n\n",
-			want:      "\nsome-string\n",
-		},
-		{
-			desc:      "newline really has to be the first character to be trimmed",
-			paramType: api.PropertyType{},
-			raw:       " \nsome-string\n ",
-			want:      " \nsome-string\n ",
-		},
-		{
-			desc:      "numeric type",
-			paramType: api.PropertyType{"number"},
-			raw:       "123",
-			want:      123,
-		},
-		// Integer parsing tests
-		{
-			desc:      "integer type",
-			paramType: api.PropertyType{"integer"},
-			raw:       "42",
-			want:      42,
-		},
-		{
-			desc:      "negative integer",
-			paramType: api.PropertyType{"integer"},
-			raw:       "-100",
-			want:      -100,
-		},
-		{
-			desc:      "zero integer",
-			paramType: api.PropertyType{"integer"},
-			raw:       "0",
-			want:      0,
-		},
-		{
-			desc:      "integer with leading zeros",
-			paramType: api.PropertyType{"integer"},
-			raw:       "007",
-			want:      7,
-		},
-		{
-			desc:      "large integer",
-			paramType: api.PropertyType{"integer"},
-			raw:       "2147483648", // Just beyond int32 max
-			want:      int64(2147483648),
-		},
-		// Float/number parsing tests
-		{
-			desc:      "float type",
-			paramType: api.PropertyType{"number"},
-			raw:       "3.14",
-			want:      3.14,
-		},
-		{
-			desc:      "negative float",
-			paramType: api.PropertyType{"number"},
-			raw:       "-273.15",
-			want:      -273.15,
-		},
-		{
-			desc:      "float without decimal part",
-			paramType: api.PropertyType{"number"},
-			raw:       "100.0",
-			want:      100,
-		},
-		{
-			desc:      "scientific notation positive",
-			paramType: api.PropertyType{"number"},
-			raw:       "1.23e5",
-			want:      123000, // Will be int since it has no decimal part
-		},
-		{
-			desc:      "scientific notation negative",
-			paramType: api.PropertyType{"number"},
-			raw:       "1.5e-3",
-			want:      0.0015,
-		},
-		{
-			desc:      "very small float",
-			paramType: api.PropertyType{"number"},
-			raw:       "0.00000001",
-			want:      0.00000001,
-		},
-		// String parsing tests
-		{
-			desc:      "explicit string type",
-			paramType: api.PropertyType{"string"},
-			raw:       "hello world",
-			want:      "hello world",
-		},
-		{
-			desc:      "string with special characters",
-			paramType: api.PropertyType{"string"},
-			raw:       "/usr/local/bin/test-file_v2.0.sh",
-			want:      "/usr/local/bin/test-file_v2.0.sh",
-		},
-		{
-			desc:      "string with quotes",
-			paramType: api.PropertyType{"string"},
-			raw:       `He said "hello" to me`,
-			want:      `He said "hello" to me`,
-		},
-		{
-			desc:      "multiline string",
-			paramType: api.PropertyType{"string"},
-			raw:       "line one\nline two\nline three",
-			want:      "line one\nline two\nline three",
-		},
-		{
-			desc:      "empty string",
-			paramType: api.PropertyType{"string"},
-			raw:       "",
-			want:      "",
-		},
-		{
-			desc:      "string that looks like a number",
-			paramType: api.PropertyType{"string"},
-			raw:       "12345",
-			want:      "12345",
-		},
-		// Boolean parsing tests
-		{
-			desc:      "boolean true",
-			paramType: api.PropertyType{"boolean"},
-			raw:       "true",
-			want:      true,
-		},
-		{
-			desc:      "boolean false",
-			paramType: api.PropertyType{"boolean"},
-			raw:       "false",
-			want:      false,
-		},
-		{
-			desc:      "boolean case insensitive true",
-			paramType: api.PropertyType{"boolean"},
-			raw:       "True",
-			want:      true,
-		},
-		{
-			desc:      "boolean case insensitive false",
-			paramType: api.PropertyType{"boolean"},
-			raw:       "FALSE",
-			want:      false,
-		},
-		// Null parsing tests
-		{
-			desc:      "null value lowercase",
-			paramType: api.PropertyType{"string"},
-			raw:       "null",
-			want:      nil,
-		},
-		{
-			desc:      "null value case insensitive",
-			paramType: api.PropertyType{"integer"},
-			raw:       "NULL",
-			want:      nil,
-		},
-		// Array parsing tests
-		{
-			desc:      "array of strings",
-			paramType: api.PropertyType{"array"},
-			raw:       `["foo", "bar", "baz"]`,
-			want:      []any{"foo", "bar", "baz"},
-		},
-		{
-			desc:      "array of numbers",
-			paramType: api.PropertyType{"array"},
-			raw:       `[1, 2.5, 3]`,
-			want:      []any{float64(1), 2.5, float64(3)},
-		},
-		{
-			desc:      "array of mixed types",
-			paramType: api.PropertyType{"array"},
-			raw:       `["string", 123, true, null]`,
-			want:      []any{"string", float64(123), true, nil},
-		},
-		{
-			desc:      "empty array",
-			paramType: api.PropertyType{"array"},
-			raw:       `[]`,
-			want:      []any{},
-		},
-		// Object parsing tests
-		{
-			desc:      "simple object",
-			paramType: api.PropertyType{"object"},
-			raw:       `{"key": "value", "number": 42}`,
-			want:      map[string]any{"key": "value", "number": float64(42)},
-		},
-		{
-			desc:      "nested object",
-			paramType: api.PropertyType{"object"},
-			raw:       `{"outer": {"inner": "value"}}`,
-			want:      map[string]any{"outer": map[string]any{"inner": "value"}},
-		},
-		{
-			desc:      "empty object",
-			paramType: api.PropertyType{"object"},
-			raw:       `{}`,
-			want:      map[string]any{},
-		},
-		// Error cases and fallback behavior
-		{
-			desc:      "invalid integer falls back to string",
-			paramType: api.PropertyType{"integer"},
-			raw:       "not-a-number",
-			want:      "not-a-number",
-		},
-		{
-			desc:      "invalid float falls back to string",
-			paramType: api.PropertyType{"number"},
-			raw:       "3.14.159",
-			want:      "3.14.159",
-		},
-		{
-			desc:      "invalid boolean falls back to false",
-			paramType: api.PropertyType{"boolean"},
-			raw:       "yes",
-			want:      false,
-		},
-		{
-			desc:      "invalid JSON array falls back to string",
-			paramType: api.PropertyType{"array"},
-			raw:       "[1, 2, unclosed",
-			want:      "[1, 2, unclosed",
-		},
-		{
-			desc:      "invalid JSON object falls back to string",
-			paramType: api.PropertyType{"object"},
-			raw:       `{"key": unclosed`,
-			want:      `{"key": unclosed`,
-		},
-		// Edge cases
-		{
-			desc:      "integer overflow should use int64",
-			paramType: api.PropertyType{"integer"},
-			raw:       "2147483648", // Beyond int32 max
-			want:      int64(2147483648),
-		},
-		{
-			desc:      "float with many decimal places",
-			paramType: api.PropertyType{"number"},
-			raw:       "3.141592653589793",
-			want:      3.141592653589793,
-		},
-		{
-			desc:      "string with JSON-like content",
-			paramType: api.PropertyType{"string"},
-			raw:       `{"this": "is", "just": "a string"}`,
-			want:      `{"this": "is", "just": "a string"}`,
-		},
-		{
-			desc:      "whitespace-only string",
-			paramType: api.PropertyType{"string"},
-			raw:       "   ",
-			want:      "   ",
-		},
-		// Unknown parameter (no type specified in tools)
-		{
-			desc:      "parameter not in tool definition defaults to string",
-			paramType: api.PropertyType{},
-			raw:       "some value",
-			want:      "some value",
-		},
-		// Union type tests
-		{
-			desc:      "string or number union - valid number",
-			paramType: api.PropertyType{"string", "number"},
-			raw:       "42.5",
-			want:      42.5,
-		},
-		{
-			desc:      "string or number union - non-numeric string",
-			paramType: api.PropertyType{"string", "number"},
-			raw:       "hello",
-			want:      "hello",
-		},
-		{
-			desc:      "number or string union - valid number (order shouldn't matter)",
-			paramType: api.PropertyType{"number", "string"},
-			raw:       "42.5",
-			want:      42.5,
-		},
-		{
-			desc:      "integer or null union - valid integer",
-			paramType: api.PropertyType{"integer", "null"},
-			raw:       "123",
-			want:      123,
-		},
-		{
-			desc:      "integer or null union - null value",
-			paramType: api.PropertyType{"integer", "null"},
-			raw:       "null",
-			want:      nil,
-		},
-		{
-			desc:      "null or integer union - null value (order shouldn't matter)",
-			paramType: api.PropertyType{"null", "integer"},
-			raw:       "null",
-			want:      nil,
-		},
-		{
-			desc:      "boolean or string union - valid boolean",
-			paramType: api.PropertyType{"boolean", "string"},
-			raw:       "true",
-			want:      true,
-		},
-		{
-			desc:      "boolean or string union - non-boolean becomes string",
-			paramType: api.PropertyType{"boolean", "string"},
-			raw:       "yes",
-			want:      "yes",
-		},
-		{
-			desc:      "string or boolean union - valid boolean (precedence test)",
-			paramType: api.PropertyType{"string", "boolean"},
-			raw:       "false",
-			want:      false, // Should be boolean, not string "false"
-		},
-		{
-			desc:      "integer or number union - integer value",
-			paramType: api.PropertyType{"integer", "number"},
-			raw:       "42",
-			want:      42,
-		},
-		{
-			desc:      "integer or number union - float value",
-			paramType: api.PropertyType{"integer", "number"},
-			raw:       "42.5",
-			want:      42.5,
-		},
-		{
-			desc:      "number or integer union - integer value (precedence test)",
-			paramType: api.PropertyType{"number", "integer"},
-			raw:       "42",
-			want:      42, // Should try integer first due to precedence
-		},
-		{
-			desc:      "array or object union - valid array",
-			paramType: api.PropertyType{"array", "object"},
-			raw:       `[1, 2, 3]`,
-			want:      []any{float64(1), float64(2), float64(3)},
-		},
-		{
-			desc:      "array or object union - valid object",
-			paramType: api.PropertyType{"array", "object"},
-			raw:       `{"key": "value"}`,
-			want:      map[string]any{"key": "value"},
-		},
-		{
-			desc:      "object or array union - valid array (precedence test)",
-			paramType: api.PropertyType{"object", "array"},
-			raw:       `[1, 2, 3]`,
-			want:      []any{float64(1), float64(2), float64(3)},
-		},
-		{
-			desc:      "complex multi-type union - null",
-			paramType: api.PropertyType{"string", "number", "boolean", "null"},
-			raw:       "null",
-			want:      nil,
-		},
-		{
-			desc:      "complex multi-type union - boolean",
-			paramType: api.PropertyType{"string", "number", "boolean", "null"},
-			raw:       "true",
-			want:      true,
-		},
-		{
-			desc:      "complex multi-type union - number",
-			paramType: api.PropertyType{"string", "number", "boolean", "null"},
-			raw:       "3.14",
-			want:      3.14,
-		},
-		{
-			desc:      "complex multi-type union - string",
-			paramType: api.PropertyType{"string", "number", "boolean", "null"},
-			raw:       "hello",
-			want:      "hello",
-		},
-		{
-			desc:      "integer string union - integer string becomes integer",
-			paramType: api.PropertyType{"integer", "string"},
-			raw:       "123",
-			want:      123,
-		},
-		{
-			desc:      "string integer union - integer string becomes integer (precedence)",
-			paramType: api.PropertyType{"string", "integer"},
-			raw:       "123",
-			want:      123, // Integer has higher precedence than string
-		},
-	}
-
-	for _, tc := range cases {
-		t.Run(tc.desc, func(t *testing.T) {
-			got := parseValue(tc.raw, tc.paramType)
-			if !reflect.DeepEqual(got, tc.want) {
-				t.Errorf("got %v (type %T), want %v (type %T)", got, got, tc.want, tc.want)
-			}
-		})
-	}
-}
-
-func TestQwenXMLTransform(t *testing.T) {
-	cases := []struct {
-		desc string
-		raw  string
-		want string
-	}{
-		{
-			desc: "simple example",
-			raw: `<function=get_current_temperature>
-<parameter=location>
-San Francisco
-</parameter>
-<parameter=unit>
-celsius
-</parameter>
-</function>`,
-			want: `<function name="get_current_temperature">
-<parameter name="location">
-San Francisco
-</parameter>
-<parameter name="unit">
-celsius
-</parameter>
-</function>`,
-		},
-		// even though quotes aren't expected in these tags, we have these tests to
-		// make sure they're escaped so they don't blow up the xml parser in case
-		// they happen
-		{
-			desc: "names with quotes",
-			raw: `<function="get current temperature">
-<parameter="location with spaces">
-San Francisco
-</parameter>
-<parameter="unit with spaces">
-celsius
-</parameter>
-</function>`,
-			want: `<function name="&#34;get current temperature&#34;">
-<parameter name="&#34;location with spaces&#34;">
-San Francisco
-</parameter>
-<parameter name="&#34;unit with spaces&#34;">
-celsius
-</parameter>
-</function>`,
-		},
-		{
-			desc: "ampersands in parameter values",
-			raw: `<function=get_current_temperature>
-		<parameter=location>
-		San Francisco & San Jose
-		</parameter>
-		</function>`,
-			want: `<function name="get_current_temperature">
-		<parameter name="location">
-		San Francisco &amp; San Jose
-		</parameter>
-		</function>`,
-		},
-	}
-
-	for _, tc := range cases {
-		got := transformToXML(tc.raw)
-		if got != tc.want {
-			t.Errorf("got %q, want %q", got, tc.want)
-		}
-	}
-}
-
-func TestTrailingWhitespaceLen(t *testing.T) {
-	cases := []struct {
-		desc string
-		s    string
-		want int
-	}{
-		{desc: "no whitespace", s: "abc", want: 0},
-		{desc: "trailing whitespace", s: "abc ", want: 1},
-		{desc: "trailing whitespace with newlines", s: "abc \n", want: 2},
-		{desc: "only whitespace", s: " \n  ", want: 4},
-		{desc: "leading whitespace doesn't count", s: " \n abc", want: 0},
-	}
-
-	for _, tc := range cases {
-		got := trailingWhitespaceLen(tc.s)
-		if got != tc.want {
-			t.Errorf("got %d, want %d", got, tc.want)
-		}
-	}
-}

model/renderers/qwen3coder.go

@@ -1,217 +0,0 @@
-package renderers
-
-import (
-	"encoding/json"
-	"fmt"
-	"reflect"
-	"strings"
-
-	"github.com/ollama/ollama/api"
-)
-
-var (
-	imStartTag = "<|im_start|>"
-	imEndTag   = "<|im_end|>"
-)
-
-// renderAdditionalKeys renders all JSON fields except the ones in handledKeys
-// This follows the same approach from the reference implementation, which gives
-// a particular key ordering
-func renderAdditionalKeys(obj any, handledKeys map[string]bool) string {
-	data, err := json.Marshal(obj)
-	if err != nil {
-		return ""
-	}
-
-	var m map[string]any
-	if err := json.Unmarshal(data, &m); err != nil {
-		return ""
-	}
-
-	var sb strings.Builder
-	for key, value := range m {
-		if handledKeys[key] {
-			continue
-		}
-
-		// Check if value is a map or array (needs JSON serialization)
-		switch v := value.(type) {
-		case map[string]any, []any:
-			jsonBytes, _ := json.Marshal(v)
-			// TODO(drifkin): it would be nice to format the JSON here similarly to
-			// python's default json.dumps behavior (spaces after commas and colons).
-			// This would let us be byte-for-byte compatible with the reference
-			// implementation for most common inputs
-			jsonStr := string(jsonBytes)
-			sb.WriteString("\n<" + key + ">" + jsonStr + "</" + key + ">")
-		case nil:
-			continue
-		default:
-			// Simple types, convert to string
-			sb.WriteString("\n<" + key + ">" + fmt.Sprintf("%v", value) + "</" + key + ">")
-		}
-	}
-
-	return sb.String()
-}
-
-func Qwen3CoderRenderer(messages []api.Message, tools []api.Tool, _ *api.ThinkValue) (string, error) {
-	var sb strings.Builder
-
-	// filter out system messages and choose the first (if any) to win
-	var systemMessage string
-	var filteredMessages []api.Message
-	for _, message := range messages {
-		if message.Role != "system" {
-			filteredMessages = append(filteredMessages, message)
-			continue
-		}
-
-		if systemMessage == "" {
-			systemMessage = message.Content
-		}
-	}
-
-	if systemMessage != "" || len(tools) > 0 {
-		sb.WriteString(imStartTag + "system\n")
-
-		// if we have tools but no system message, match the reference implementation by providing a default system message
-		if systemMessage == "" {
-			systemMessage = "You are Qwen, a helpful AI assistant that can interact with a computer to solve tasks."
-		}
-
-		sb.WriteString(systemMessage)
-
-		if len(tools) > 0 {
-			sb.WriteString("\n\n# Tools\n\nYou have access to the following functions:\n\n")
-			sb.WriteString("<tools>")
-			for _, tool := range tools {
-				sb.WriteString("\n")
-				sb.WriteString("<function>\n")
-				sb.WriteString("<name>" + tool.Function.Name + "</name>")
-				if tool.Function.Description != "" {
-					sb.WriteString("\n<description>" + tool.Function.Description + "</description>")
-				}
-				sb.WriteString("\n<parameters>")
-
-				for name, prop := range tool.Function.Parameters.Properties {
-					sb.WriteString("\n<parameter>")
-					sb.WriteString("\n<name>" + name + "</name>")
-
-					if len(prop.Type) > 0 {
-						// TODO(!!!)(drifkin): we should match the reference implementation for
-						// more complex types here instead of using this format
-						sb.WriteString("\n<type>" + prop.ToTypeScriptType() + "</type>")
-					}
-
-					if prop.Description != "" {
-						sb.WriteString("\n<description>" + prop.Description + "</description>")
-					}
-
-					// Render any additional keys not already handled
-					handledKeys := map[string]bool{
-						"type":        true,
-						"description": true,
-					}
-					sb.WriteString(renderAdditionalKeys(prop, handledKeys))
-
-					sb.WriteString("\n</parameter>")
-				}
-
-				// Render extra keys for parameters (everything except 'type' and 'properties')
-				paramHandledKeys := map[string]bool{
-					"type":       true,
-					"properties": true,
-				}
-				sb.WriteString(renderAdditionalKeys(tool.Function.Parameters, paramHandledKeys))
-
-				sb.WriteString("\n</parameters>")
-				sb.WriteString("\n</function>")
-			}
-			sb.WriteString("\n</tools>")
-			sb.WriteString("\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>")
-		}
-
-		sb.WriteString(imEndTag + "\n")
-	}
-
-	for i, message := range filteredMessages {
-		lastMessage := i == len(filteredMessages)-1
-		prefill := lastMessage && message.Role == "assistant"
-		switch message.Role {
-		case "assistant":
-			if len(message.ToolCalls) > 0 {
-				sb.WriteString(imStartTag + "assistant\n")
-				if message.Content != "" {
-					sb.WriteString(message.Content + "\n")
-				}
-				for _, toolCall := range message.ToolCalls {
-					sb.WriteString("\n<tool_call>\n<function=" + toolCall.Function.Name + ">")
-					for name, value := range toolCall.Function.Arguments {
-						valueStr := formatToolCallArgument(value)
-						sb.WriteString("\n<parameter=" + name + ">\n" + valueStr + "\n</parameter>")
-					}
-					sb.WriteString("\n</function>\n</tool_call>")
-				}
-				sb.WriteString("<|im_end|>\n")
-			} else {
-				sb.WriteString(imStartTag + "assistant\n")
-				sb.WriteString(message.Content)
-				if !prefill {
-					sb.WriteString(imEndTag + "\n")
-				}
-			}
-		case "tool":
-			// consecutive tool responses should share a single `<im_start>user`, but
-			// have their own <tool_response> tags
-
-			// only start a new user block if this is the first tool response
-			if i == 0 || filteredMessages[i-1].Role != "tool" {
-				sb.WriteString(imStartTag + "user\n")
-			}
-
-			sb.WriteString("<tool_response>\n")
-			sb.WriteString(message.Content)
-			sb.WriteString("\n</tool_response>\n")
-
-			// close the user block only if this is the last tool response
-			if i == len(filteredMessages)-1 || filteredMessages[i+1].Role != "tool" {
-				sb.WriteString(imEndTag + "\n")
-			}
-		default:
-			sb.WriteString(imStartTag + message.Role + "\n")
-			sb.WriteString(message.Content)
-			sb.WriteString(imEndTag + "\n")
-		}
-
-		if lastMessage && !prefill {
-			sb.WriteString(imStartTag + "assistant\n")
-		}
-	}
-
-	return sb.String(), nil
-}
-
-func formatToolCallArgument(value any) string {
-	if value == nil {
-		return "null"
-	}
-
-	switch v := value.(type) {
-	case string:
-		return v
-	case []byte:
-		return string(v)
-	}
-
-	if reflect.TypeOf(value) != nil {
-		kind := reflect.TypeOf(value).Kind()
-		if kind == reflect.Map || kind == reflect.Slice || kind == reflect.Array {
-			if marshalled, err := json.Marshal(value); err == nil {
-				return string(marshalled)
-			}
-		}
-	}
-
-	return fmt.Sprintf("%v", value)
-}

model/renderers/qwen3coder_test.go

@@ -1,338 +0,0 @@
-package renderers
-
-import (
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-	"github.com/ollama/ollama/api"
-)
-
-func TestQwen3CoderRenderer(t *testing.T) {
-	tests := []struct {
-		name     string
-		msgs     []api.Message
-		tools    []api.Tool
-		expected string
-	}{
-		{
-			name: "basic",
-			msgs: []api.Message{
-				{Role: "system", Content: "You are a helpful assistant."},
-				{Role: "user", Content: "Hello, how are you?"},
-			},
-			expected: `<|im_start|>system
-You are a helpful assistant.<|im_end|>
-<|im_start|>user
-Hello, how are you?<|im_end|>
-<|im_start|>assistant
-`,
-		},
-		{
-			name: "with tools and response",
-			msgs: []api.Message{
-				{Role: "system", Content: "You are a helpful assistant with access to tools."},
-				{Role: "user", Content: "What is the weather like in San Francisco?"},
-				{
-					Role:    "assistant",
-					Content: "I'll check the weather in San Francisco for you.",
-					ToolCalls: []api.ToolCall{
-						{
-							Function: api.ToolCallFunction{
-								Name: "get_weather",
-								Arguments: map[string]any{
-									"unit": "fahrenheit",
-								},
-							},
-						},
-					},
-				},
-				{Role: "tool", Content: "{\"location\": \"San Francisco, CA\", \"temperature\": 68, \"condition\": \"partly cloudy\", \"humidity\": 65, \"wind_speed\": 12}", ToolName: "get_weather"},
-				{Role: "user", Content: "That sounds nice! What about New York?"},
-			},
-			tools: []api.Tool{
-				{Function: api.ToolFunction{
-					Name:        "get_weather",
-					Description: "Get the current weather in a given location",
-					Parameters: api.ToolFunctionParameters{
-						Required: []string{"unit"},
-						Properties: map[string]api.ToolProperty{
-							"unit": {Type: api.PropertyType{"string"}, Enum: []any{"celsius", "fahrenheit"}, Description: "The unit of temperature"},
-							// TODO(drifkin): add multiple params back once we have predictable
-							// order via some sort of ordered map type (see
-							// <https://github.com/ollama/ollama/issues/12244>)
-							/*
-								"location": {Type: api.PropertyType{"string"}, Description: "The city and state, e.g. San Francisco, CA"},
-							*/
-						},
-					},
-				}},
-			},
-			expected: `<|im_start|>system
-You are a helpful assistant with access to tools.
-
-# Tools
-
-You have access to the following functions:
-
-<tools>
-<function>
-<name>get_weather</name>
-<description>Get the current weather in a given location</description>
-<parameters>
-<parameter>
-<name>unit</name>
-<type>string</type>
-<description>The unit of temperature</description>
-<enum>["celsius","fahrenheit"]</enum>
-</parameter>
-<required>["unit"]</required>
-</parameters>
-</function>
-</tools>
-
-If you choose to call a function ONLY reply in the following format with NO suffix:
-
-<tool_call>
-<function=example_function_name>
-<parameter=example_parameter_1>
-value_1
-</parameter>
-<parameter=example_parameter_2>
-This is the value for the second parameter
-that can span
-multiple lines
-</parameter>
-</function>
-</tool_call>
-
-<IMPORTANT>
-Reminder:
-- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags
-- Required parameters MUST be specified
-- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after
-- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
-</IMPORTANT><|im_end|>
-<|im_start|>user
-What is the weather like in San Francisco?<|im_end|>
-<|im_start|>assistant
-I'll check the weather in San Francisco for you.
-
-<tool_call>
-<function=get_weather>
-<parameter=unit>
-fahrenheit
-</parameter>
-</function>
-</tool_call><|im_end|>
-<|im_start|>user
-<tool_response>
-{"location": "San Francisco, CA", "temperature": 68, "condition": "partly cloudy", "humidity": 65, "wind_speed": 12}
-</tool_response>
-<|im_end|>
-<|im_start|>user
-That sounds nice! What about New York?<|im_end|>
-<|im_start|>assistant
-`,
-		},
-		{
-			name: "parallel tool calls",
-			msgs: []api.Message{
-				{Role: "system", Content: "You are a helpful assistant with access to tools."},
-				{Role: "user", Content: "call double(1) and triple(2)"},
-				{Role: "assistant", Content: "I'll call double(1) and triple(2) for you.", ToolCalls: []api.ToolCall{
-					{Function: api.ToolCallFunction{Name: "double", Arguments: map[string]any{"number": "1"}}},
-					{Function: api.ToolCallFunction{Name: "triple", Arguments: map[string]any{"number": "2"}}},
-				}},
-				{Role: "tool", Content: "{\"number\": 2}", ToolName: "double"},
-				{Role: "tool", Content: "{\"number\": 6}", ToolName: "triple"},
-			},
-			tools: []api.Tool{
-				{Function: api.ToolFunction{Name: "double", Description: "Double a number", Parameters: api.ToolFunctionParameters{Properties: map[string]api.ToolProperty{
-					"number": {Type: api.PropertyType{"string"}, Description: "The number to double"},
-				}}}},
-				{Function: api.ToolFunction{Name: "triple", Description: "Triple a number", Parameters: api.ToolFunctionParameters{Properties: map[string]api.ToolProperty{
-					"number": {Type: api.PropertyType{"string"}, Description: "The number to triple"},
-				}}}},
-			},
-			expected: `<|im_start|>system
-You are a helpful assistant with access to tools.
-
-# Tools
-
-You have access to the following functions:
-
-<tools>
-<function>
-<name>double</name>
-<description>Double a number</description>
-<parameters>
-<parameter>
-<name>number</name>
-<type>string</type>
-<description>The number to double</description>
-</parameter>
-</parameters>
-</function>
-<function>
-<name>triple</name>
-<description>Triple a number</description>
-<parameters>
-<parameter>
-<name>number</name>
-<type>string</type>
-<description>The number to triple</description>
-</parameter>
-</parameters>
-</function>
-</tools>
-
-If you choose to call a function ONLY reply in the following format with NO suffix:
-
-<tool_call>
-<function=example_function_name>
-<parameter=example_parameter_1>
-value_1
-</parameter>
-<parameter=example_parameter_2>
-This is the value for the second parameter
-that can span
-multiple lines
-</parameter>
-</function>
-</tool_call>
-
-<IMPORTANT>
-Reminder:
-- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags
-- Required parameters MUST be specified
-- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after
-- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
-</IMPORTANT><|im_end|>
-<|im_start|>user
-call double(1) and triple(2)<|im_end|>
-<|im_start|>assistant
-I'll call double(1) and triple(2) for you.
-
-<tool_call>
-<function=double>
-<parameter=number>
-1
-</parameter>
-</function>
-</tool_call>
-<tool_call>
-<function=triple>
-<parameter=number>
-2
-</parameter>
-</function>
-</tool_call><|im_end|>
-<|im_start|>user
-<tool_response>
-{"number": 2}
-</tool_response>
-<tool_response>
-{"number": 6}
-</tool_response>
-<|im_end|>
-<|im_start|>assistant
-`,
-		},
-		{
-			name: "prefill",
-			msgs: []api.Message{
-				{Role: "system", Content: "You are a helpful assistant."},
-				{Role: "user", Content: "Tell me something interesting."},
-				{Role: "assistant", Content: "I'll tell you something interesting about cats"},
-			},
-			expected: `<|im_start|>system
-You are a helpful assistant.<|im_end|>
-<|im_start|>user
-Tell me something interesting.<|im_end|>
-<|im_start|>assistant
-I'll tell you something interesting about cats`,
-		},
-		{
-			name: "complex tool call arguments should remain json encoded",
-			msgs: []api.Message{
-				{Role: "user", Content: "call tool"},
-				{Role: "assistant", ToolCalls: []api.ToolCall{
-					{Function: api.ToolCallFunction{
-						Name: "echo",
-						Arguments: map[string]any{
-							"payload": map[string]any{"foo": "bar"},
-						},
-					}},
-				}},
-				{Role: "tool", Content: "{\"payload\": {\"foo\": \"bar\"}}", ToolName: "echo"},
-			},
-			expected: `<|im_start|>user
-call tool<|im_end|>
-<|im_start|>assistant
-
-<tool_call>
-<function=echo>
-<parameter=payload>
-{"foo":"bar"}
-</parameter>
-</function>
-</tool_call><|im_end|>
-<|im_start|>user
-<tool_response>
-{"payload": {"foo": "bar"}}
-</tool_response>
-<|im_end|>
-<|im_start|>assistant
-`,
-		},
-	}
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			rendered, err := Qwen3CoderRenderer(tt.msgs, tt.tools, nil)
-			if err != nil {
-				t.Fatal(err)
-			}
-			if diff := cmp.Diff(rendered, tt.expected); diff != "" {
-				t.Errorf("mismatch (-got +want):\n%s", diff)
-			}
-		})
-	}
-}
-
-func TestFormatToolCallArgument(t *testing.T) {
-	tests := []struct {
-		name     string
-		arg      any
-		expected string
-	}{
-		{
-			name: "string",
-			arg:  "foo",
-			// notice no quotes around the string
-			expected: "foo",
-		},
-		{
-			name:     "map",
-			arg:      map[string]any{"foo": "bar"},
-			expected: "{\"foo\":\"bar\"}",
-		},
-		{
-			name:     "number",
-			arg:      1,
-			expected: "1",
-		},
-		{
-			name:     "boolean",
-			arg:      true,
-			expected: "true",
-		},
-	}
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			got := formatToolCallArgument(tt.arg)
-			if got != tt.expected {
-				t.Errorf("formatToolCallArgument(%v) = %v, want %v", tt.arg, got, tt.expected)
-			}
-		})
-	}
-}

model/renderers/renderer.go

@@ -1,26 +0,0 @@
-package renderers
-
-import (
-	"fmt"
-
-	"github.com/ollama/ollama/api"
-)
-
-type rendererFunc func([]api.Message, []api.Tool, *api.ThinkValue) (string, error)
-
-func RenderWithRenderer(name string, msgs []api.Message, tools []api.Tool, think *api.ThinkValue) (string, error) {
-	renderer := rendererForName(name)
-	if renderer == nil {
-		return "", fmt.Errorf("unknown renderer %q", name)
-	}
-	return renderer(msgs, tools, think)
-}
-
-func rendererForName(name string) rendererFunc {
-	switch name {
-	case "qwen3-coder":
-		return Qwen3CoderRenderer
-	default:
-		return nil
-	}
-}

model/sentencepiece.go

@@ -12,18 +12,18 @@ import (
 
 const spmWhitespaceSep = "▁"
 
-type SentencePiece struct {
+type SentencePieceModel struct {
 	maxTokenLen int
 	vocab       *Vocabulary
 }
 
-var _ TextProcessor = (*SentencePiece)(nil)
+var _ TextProcessor = (*SentencePieceModel)(nil)
 
-func (spm SentencePiece) Vocabulary() *Vocabulary {
+func (spm SentencePieceModel) Vocabulary() *Vocabulary {
 	return spm.vocab
 }
 
-func NewSentencePiece(vocab *Vocabulary) SentencePiece {
+func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel {
 	logutil.Trace("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
 
 	counter := map[int]int{}
@@ -42,17 +42,17 @@ func NewSentencePiece(vocab *Vocabulary) SentencePiece {
 		"user defined", counter[TOKEN_TYPE_USER_DEFINED], "unused", counter[TOKEN_TYPE_UNUSED], "byte", counter[TOKEN_TYPE_BYTE],
 		"max token len", maxTokenLen)
 
-	return SentencePiece{
+	return SentencePieceModel{
 		maxTokenLen: maxTokenLen,
 		vocab:       vocab,
 	}
 }
 
-func (spm SentencePiece) Is(id int32, special Special) bool {
+func (spm SentencePieceModel) Is(id int32, special Special) bool {
 	return spm.vocab.Is(id, special)
 }
 
-func (spm SentencePiece) Encode(s string, addSpecial bool) ([]int32, error) {
+func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error) {
 	fragments := []fragment{{value: s}}
 	for _, special := range spm.vocab.SpecialVocabulary() {
 		id := spm.vocab.Encode(special)
@@ -218,7 +218,7 @@ func (q *queue) Pop() interface{} {
 	return item
 }
 
-func (spm SentencePiece) Decode(ids []int32) (string, error) {
+func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
 	var sb strings.Builder
 	for _, id := range ids {
 		data := spm.vocab.Decode(id)

model/sentencepiece_test.go

@@ -12,7 +12,7 @@ import (
 	"github.com/ollama/ollama/convert/sentencepiece"
 )
 
-func loadSentencePieceVocab(t *testing.T) SentencePiece {
+func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 	t.Helper()
 
 	bts, err := os.ReadFile(filepath.Join("testdata", "gemma2", "tokenizer.model"))
@@ -45,7 +45,7 @@ func loadSentencePieceVocab(t *testing.T) SentencePiece {
 		}
 	}
 
-	return NewSentencePiece(&v)
+	return NewSentencePieceModel(&v)
 }
 
 func TestSentencePieceEncode(t *testing.T) {
@@ -115,7 +115,7 @@ func TestSentencePieceEncode(t *testing.T) {
 	})
 }
 
-func TestSentencePieceDecodeByteTokens(t *testing.T) {
+func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
 	vocab := &Vocabulary{
 		Values: []string{
 			"normal",
@@ -134,7 +134,7 @@ func TestSentencePieceDecodeByteTokens(t *testing.T) {
 		Scores: []float32{0, 0, 0, 0, 0},
 	}
 
-	spm := NewSentencePiece(vocab)
+	spm := NewSentencePieceModel(vocab)
 
 	tests := []struct {
 		name     string

model/wordpiece.go

@@ -1,167 +0,0 @@
-package model
-
-import (
-	"fmt"
-	"iter"
-	"strings"
-	"unicode"
-
-	"github.com/ollama/ollama/logutil"
-)
-
-type WordPiece struct {
-	vocab *Vocabulary
-}
-
-// ggmlPrefix is the prefix used by GGML vocabularies to indicate word boundaries.
-// this differs from original word piece which uses "##" to indicate subwords.
-const ggmlPrefix = "▁"
-
-var wordPieceReplacer = strings.NewReplacer(
-	" .", ".",
-	" ?", "?",
-	" !", "!",
-	" ,", ",",
-	" ' ", "'",
-	" n't", "n't",
-	" 'm", "'m",
-	" do not", " don't",
-	" 's", "'s",
-	" 've", "'ve",
-	" 're", "'re",
-)
-
-// Decode implements TextProcessor.
-func (wpm WordPiece) Decode(ids []int32) (string, error) {
-	var sb strings.Builder
-	for i, id := range ids {
-		if id < 0 || int(id) >= len(wpm.vocab.Values) {
-			return "", fmt.Errorf("invalid token id: %d", id)
-		}
-
-		var separator string
-		piece := wpm.vocab.Values[id]
-		if i > 0 &&
-			(strings.HasPrefix(piece, ggmlPrefix) ||
-				(strings.HasPrefix(piece, "[") && strings.HasSuffix(piece, "]"))) {
-			separator = " "
-		}
-
-		sb.WriteString(wordPieceReplacer.Replace(separator + strings.TrimPrefix(piece, ggmlPrefix)))
-	}
-
-	return sb.String(), nil
-}
-
-// words splits a string into words, treating CJK characters as separate words.
-// TODO: this is specifically for BERT and may need to be adjusted or refactored for other models.
-func (wpm WordPiece) words(s string) iter.Seq[string] {
-	return func(yield func(string) bool) {
-		runes := make([]rune, 0, len(s)*3)
-		for _, r := range s {
-			switch {
-			case r >= 0x4E00 && r <= 0x9FFF,
-				r >= 0x3400 && r <= 0x4DBF,
-				r >= 0x20000 && r <= 0x2A6DF,
-				r >= 0x2A700 && r <= 0x2B73F,
-				r >= 0x2B740 && r <= 0x2B81F,
-				r >= 0x2B820 && r <= 0x2CEAF,
-				r >= 0xF900 && r <= 0xFAFF,
-				r >= 0x2F800 && r <= 0x2FA1F:
-				runes = append(runes, ' ', r, ' ')
-			default:
-				runes = append(runes, r)
-			}
-		}
-
-		for w := range strings.FieldsFuncSeq(string(runes), unicode.IsSpace) {
-			// split on but keep punctuation
-			var start int
-			for start < len(w) {
-				end := strings.IndexFunc(w[start:], unicode.IsPunct)
-				if end < 0 {
-					end = len(w) - start
-				} else if end == 0 {
-					end = 1
-				}
-
-				if !yield(w[start : start+end]) {
-					return
-				}
-
-				start += end
-			}
-		}
-	}
-}
-
-// Encode implements TextProcessor.
-func (wpm WordPiece) Encode(s string, addSpecial bool) ([]int32, error) {
-	var ids []int32
-
-	// TODO: use [UNK] from config
-	unk := wpm.vocab.Encode("[UNK]")
-	for word := range wpm.words(s) {
-		var start int
-		var pieces []int32
-		for start < len(word) {
-			end := len(word)
-
-			var piece int32
-			for start < end {
-				subword := word[start:end]
-				if start == 0 {
-					subword = ggmlPrefix + subword
-				}
-
-				// TODO: some models might not want [ToLower]
-				piece = wpm.vocab.Encode(strings.ToLower(subword))
-				if piece >= 0 {
-					break
-				}
-
-				end--
-			}
-
-			if piece < 0 {
-				// Unknown token
-				pieces = pieces[:0]
-				break
-			}
-
-			pieces = append(pieces, piece)
-			start = end
-		}
-
-		if len(pieces) > 0 {
-			ids = append(ids, pieces...)
-		} else {
-			ids = append(ids, unk)
-		}
-	}
-
-	if addSpecial && len(ids) > 0 {
-		ids = wpm.vocab.addSpecials(ids)
-	}
-
-	logutil.Trace("encoded", "string", s, "ids", ids)
-	return ids, nil
-}
-
-// Is implements TextProcessor.
-func (wpm WordPiece) Is(id int32, special Special) bool {
-	return wpm.vocab.Is(id, special)
-}
-
-// Vocabulary implements TextProcessor.
-func (wpm WordPiece) Vocabulary() *Vocabulary {
-	return wpm.vocab
-}
-
-var _ TextProcessor = (*WordPiece)(nil)
-
-func NewWordPiece(vocab *Vocabulary) WordPiece {
-	return WordPiece{
-		vocab: vocab,
-	}
-}

model/wordpiece_test.go

@@ -1,51 +0,0 @@
-package model
-
-import (
-	"slices"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-)
-
-func TestWordPiece(t *testing.T) {
-	wpm := NewWordPiece(
-		&Vocabulary{
-			Values: []string{"[UNK]", "[CLS]", "[SEP]", "▁hello", "▁world", "s", "▁!", "▁@", "▁#"},
-			AddBOS: true,
-			AddEOS: true,
-			BOS:    []int32{1},
-			EOS:    []int32{2},
-		})
-
-	ids, err := wpm.Encode("Hello world!", true)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	if diff := cmp.Diff([]int32{1, 3, 4, 6, 2}, ids); diff != "" {
-		t.Errorf("unexpected ids (-want +got):\n%s", diff)
-	}
-
-	words, err := wpm.Decode(ids)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	if diff := cmp.Diff("[CLS] hello world! [SEP]", words); diff != "" {
-		t.Errorf("unexpected words (-want +got):\n%s", diff)
-	}
-}
-
-func TestWordPieceWords(t *testing.T) {
-	var wpm WordPiece
-
-	basic := slices.Collect(wpm.words("Hey friend!     How are you?!?"))
-	if diff := cmp.Diff([]string{"Hey", "friend", "!", "How", "are", "you", "?", "!", "?"}, basic); diff != "" {
-		t.Errorf("unexpected words (-want +got):\n%s", diff)
-	}
-
-	chinese := slices.Collect(wpm.words("野口里佳 Noguchi Rika"))
-	if diff := cmp.Diff([]string{"野", "口", "里", "佳", "Noguchi", "Rika"}, chinese); diff != "" {
-		t.Errorf("unexpected words (-want +got):\n%s", diff)
-	}
-}

openai/openai.go

@@ -76,9 +76,8 @@ type JsonSchema struct {
 }
 
 type EmbedRequest struct {
-	Input      any    `json:"input"`
-	Model      string `json:"model"`
-	Dimensions int    `json:"dimensions,omitempty"`
+	Input any    `json:"input"`
+	Model string `json:"model"`
 }
 
 type StreamOptions struct {
@@ -105,18 +104,16 @@ type ChatCompletionRequest struct {
 	Tools            []api.Tool      `json:"tools"`
 	Reasoning        *Reasoning      `json:"reasoning,omitempty"`
 	ReasoningEffort  *string         `json:"reasoning_effort,omitempty"`
-	DebugRenderOnly  bool            `json:"_debug_render_only"`
 }
 
 type ChatCompletion struct {
-	Id                string         `json:"id"`
-	Object            string         `json:"object"`
-	Created           int64          `json:"created"`
-	Model             string         `json:"model"`
-	SystemFingerprint string         `json:"system_fingerprint"`
-	Choices           []Choice       `json:"choices"`
-	Usage             Usage          `json:"usage,omitempty"`
-	DebugInfo         *api.DebugInfo `json:"_debug_info,omitempty"`
+	Id                string   `json:"id"`
+	Object            string   `json:"object"`
+	Created           int64    `json:"created"`
+	Model             string   `json:"model"`
+	SystemFingerprint string   `json:"system_fingerprint"`
+	Choices           []Choice `json:"choices"`
+	Usage             Usage    `json:"usage,omitempty"`
 }
 
 type ChatCompletionChunk struct {
@@ -143,7 +140,6 @@ type CompletionRequest struct {
 	Temperature      *float32       `json:"temperature"`
 	TopP             float32        `json:"top_p"`
 	Suffix           string         `json:"suffix"`
-	DebugRenderOnly  bool           `json:"_debug_render_only"`
 }
 
 type Completion struct {
@@ -276,8 +272,8 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 				}
 				return nil
 			}(r.DoneReason),
-		}}, Usage: toUsage(r),
-		DebugInfo: r.DebugInfo,
+		}},
+		Usage: toUsage(r),
 	}
 }
 
@@ -571,14 +567,13 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
 	}
 
 	return &api.ChatRequest{
-		Model:           r.Model,
-		Messages:        messages,
-		Format:          format,
-		Options:         options,
-		Stream:          &r.Stream,
-		Tools:           r.Tools,
-		Think:           think,
-		DebugRenderOnly: r.DebugRenderOnly,
+		Model:    r.Model,
+		Messages: messages,
+		Format:   format,
+		Options:  options,
+		Stream:   &r.Stream,
+		Tools:    r.Tools,
+		Think:    think,
 	}, nil
 }
 
@@ -652,12 +647,11 @@ func fromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
 	}
 
 	return api.GenerateRequest{
-		Model:           r.Model,
-		Prompt:          r.Prompt,
-		Options:         options,
-		Stream:          &r.Stream,
-		Suffix:          r.Suffix,
-		DebugRenderOnly: r.DebugRenderOnly,
+		Model:   r.Model,
+		Prompt:  r.Prompt,
+		Options: options,
+		Stream:  &r.Stream,
+		Suffix:  r.Suffix,
 	}, nil
 }
 
@@ -1011,7 +1005,7 @@ func EmbeddingsMiddleware() gin.HandlerFunc {
 		}
 
 		var b bytes.Buffer
-		if err := json.NewEncoder(&b).Encode(api.EmbedRequest{Model: req.Model, Input: req.Input, Dimensions: req.Dimensions}); err != nil {
+		if err := json.NewEncoder(&b).Encode(api.EmbedRequest{Model: req.Model, Input: req.Input}); err != nil {
 			c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
 			return
 		}

parser/parser.go

@@ -100,10 +100,6 @@ func (f Modelfile) CreateRequest(relativeDir string) (*api.CreateRequest, error)
 			req.System = c.Args
 		case "license":
 			licenses = append(licenses, c.Args)
-		case "renderer":
-			req.Renderer = c.Args
-		case "parser":
-			req.Parser = c.Args
 		case "message":
 			role, msg, _ := strings.Cut(c.Args, ": ")
 			messages = append(messages, api.Message{Role: role, Content: msg})
@@ -324,7 +320,7 @@ func (c Command) String() string {
 	switch c.Name {
 	case "model":
 		fmt.Fprintf(&sb, "FROM %s", c.Args)
-	case "license", "template", "system", "adapter", "renderer", "parser":
+	case "license", "template", "system", "adapter":
 		fmt.Fprintf(&sb, "%s %s", strings.ToUpper(c.Name), quote(c.Args))
 	case "message":
 		role, message, _ := strings.Cut(c.Args, ": ")
@@ -350,7 +346,7 @@ const (
 var (
 	errMissingFrom        = errors.New("no FROM line")
 	errInvalidMessageRole = errors.New("message role must be one of \"system\", \"user\", or \"assistant\"")
-	errInvalidCommand     = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"renderer\", \"parser\", \"parameter\", or \"message\"")
+	errInvalidCommand     = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
 )
 
 type ParserError struct {
@@ -610,7 +606,7 @@ func isValidMessageRole(role string) bool {
 
 func isValidCommand(cmd string) bool {
 	switch strings.ToLower(cmd) {
-	case "from", "license", "template", "system", "adapter", "renderer", "parser", "parameter", "message":
+	case "from", "license", "template", "system", "adapter", "parameter", "message":
 		return true
 	default:
 		return false

parser/parser_test.go

@@ -198,34 +198,6 @@ BADCOMMAND param1 value1
 	}
 }
 
-func TestParseFileRenderer(t *testing.T) {
-	input := `
-FROM foo
-RENDERER renderer1
-`
-
-	reader := strings.NewReader(input)
-
-	modelfile, err := ParseFile(reader)
-	require.NoError(t, err)
-
-	assert.Equal(t, []Command{{Name: "model", Args: "foo"}, {Name: "renderer", Args: "renderer1"}}, modelfile.Commands)
-}
-
-func TestParseFileParser(t *testing.T) {
-	input := `
-FROM foo
-PARSER parser1
-`
-
-	reader := strings.NewReader(input)
-
-	modelfile, err := ParseFile(reader)
-	require.NoError(t, err)
-
-	assert.Equal(t, []Command{{Name: "model", Args: "foo"}, {Name: "parser", Args: "parser1"}}, modelfile.Commands)
-}
-
 func TestParseFileMessages(t *testing.T) {
 	cases := []struct {
 		input    string

runner/llamarunner/cache.go

@@ -204,8 +204,13 @@ func (c *InputCache) ShiftDiscard(inputLen int, numKeep int) int {
 	targetFree = max(targetFree, 1)
 
 	currentFree := c.numCtx - inputLen
+	discard := targetFree - currentFree
 
-	return max(targetFree-currentFree, 0)
+	if discard < 0 {
+		discard = 0
+	}
+
+	return discard
 }
 
 type ErrReprocessInputs struct {

runner/ollamarunner/cache.go

@@ -242,8 +242,13 @@ func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
 	targetFree = max(targetFree, 1)
 
 	currentFree := c.numCtx - inputLen
+	discard := targetFree - currentFree
 
-	return max(targetFree-currentFree, 0)
+	if discard < 0 {
+		discard = 0
+	}
+
+	return discard
 }
 
 type ErrReprocessInputs struct {

runner/ollamarunner/runner.go

@@ -11,12 +11,14 @@ import (
 	"image"
 	"log"
 	"log/slog"
+	"math"
 	"net"
 	"net/http"
 	"os"
 	"reflect"
 	"regexp"
 	"runtime"
+	"runtime/debug"
 	"strconv"
 	"strings"
 	"sync"
@@ -28,10 +30,10 @@ import (
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
+	"github.com/ollama/ollama/harmony"
 	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/logutil"
 	"github.com/ollama/ollama/ml"
-	"github.com/ollama/ollama/ml/nn/pooling"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
 	"github.com/ollama/ollama/runner/common"
@@ -405,7 +407,7 @@ func (s *Server) removeSequence(seqIndex int, reason llm.DoneReason) {
 func (s *Server) run(ctx context.Context) {
 	s.ready.Wait()
 
-	supportsAsync := pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone
+	supportsAsync := s.model.Backend().Config().Uint("pooling_type", math.MaxUint32) == math.MaxUint32
 
 	var activeBatch batchState
 	for {
@@ -467,7 +469,6 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 
 	// Prepare the seqs and batch, but defer the input token values as we may not be ready yet
 	var batchInputs []*input.Input
-	var batchOutputs []int32
 	var batch input.Batch
 
 	resumeSeq := -1
@@ -550,9 +551,9 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 			batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
 			batch.Sequences = append(batch.Sequences, seq.cache.Id)
 
-			seq.iBatch = len(batchOutputs)
-			if i+1 == len(seq.inputs) || seq.embeddingOnly {
-				batchOutputs = append(batchOutputs, int32(len(batchInputs)-1))
+			seq.iBatch = len(batch.Outputs)
+			if i+1 == len(seq.inputs) {
+				batch.Outputs = append(batch.Outputs, int32(len(batchInputs)-1))
 			}
 			logutil.Trace("forwardBatch iBatch", "batchID", s.batchID, "seqIdx", seqIdx, "seq.iBatch", seq.iBatch, "i+1", i+1, "len(seq.inputs)", len(seq.inputs))
 			seq.pendingInputs = append(seq.pendingInputs, inp)
@@ -577,7 +578,6 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 
 	// Actual batchInputs values will be injected into the batch.Inputs tensor before calling Compute
 	batch.Inputs = nextBatch.ctx.Input().Empty(ml.DTypeI32, len(batchInputs))
-	batch.Outputs = nextBatch.ctx.Input().FromIntSlice(batchOutputs, len(batchOutputs))
 	nextBatch.modelOutput, err = model.Forward(nextBatch.ctx, s.model, batch)
 	if err != nil {
 		err = fmt.Errorf("failed to build graph: %w", err)
@@ -705,8 +705,8 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		}
 
 		// sample a token
-		vocabSize := len(outputs) / activeBatch.batch.Outputs.Dim(0)
-		logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", activeBatch.batch.Outputs.Dim(0), "vocabSize", vocabSize, "iBatches", iBatches)
+		vocabSize := len(outputs) / len(activeBatch.batch.Outputs)
+		logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", len(activeBatch.batch.Outputs), "vocabSize", vocabSize, "iBatches", iBatches)
 		token, err := seq.sampler.Sample(outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize])
 		if err != nil {
 			s.hardErrCh <- fmt.Errorf("failed to sample token: %w", err)
@@ -782,6 +782,14 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
+	var harmonyMessageHandler *harmony.HarmonyMessageHandler
+	var harmonyToolParser *harmony.HarmonyToolCallAccumulator
+	if req.UseHarmony {
+		harmonyMessageHandler = harmony.NewHarmonyMessageHandler()
+		harmonyMessageHandler.HarmonyParser.AddImplicitStartOrPrefill(req.PrefillString)
+		harmonyToolParser = harmonyMessageHandler.CreateToolParser()
+	}
+
 	if req.Options == nil {
 		opts := api.DefaultOptions()
 		req.Options = &opts
@@ -864,6 +872,9 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}
+	var lastToken string
+	tokenRepeat := 0
+	const tokenRepeatLimit = 30
 
 	for {
 		select {
@@ -872,8 +883,27 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			return
 		case content, ok := <-seq.responses:
 			if ok {
+				if strings.TrimSpace(content) == lastToken {
+					tokenRepeat++
+				}
+				if tokenRepeat == tokenRepeatLimit {
+					http.Error(w, "token repeat limit reached", http.StatusInternalServerError)
+					seq.doneReason = llm.DoneReasonTokenRepeatLimit
+					close(seq.quit)
+					return
+				}
+				lastToken = strings.TrimSpace(content)
+
+				var thinking string
+				if harmonyMessageHandler != nil {
+					var toolContent string
+					content, thinking, toolContent = harmonyMessageHandler.AddContent(content, harmonyToolParser)
+					harmonyToolParser.Add(toolContent)
+				}
+
 				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
-					Content: content,
+					Content:  content,
+					Thinking: thinking,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
 					close(seq.quit)
@@ -882,7 +912,29 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 
 				flusher.Flush()
 			} else {
+				var toolCalls []api.ToolCall
+				if harmonyMessageHandler != nil {
+					// these tools still need to be transformed to the original function name
+					toolName, toolContent := harmonyToolParser.Drain()
+					if toolName != nil {
+						*toolName = strings.TrimPrefix(*toolName, "functions.")
+						var args api.ToolCallFunctionArguments
+						if err := json.Unmarshal([]byte(toolContent), &args); err != nil {
+							http.Error(w, fmt.Sprintf("failed to unmarshal tool call function arguments: %v", err), http.StatusInternalServerError)
+							close(seq.quit)
+							return
+						}
+						toolCalls = append(toolCalls, api.ToolCall{
+							Function: api.ToolCallFunction{
+								Name:      *toolName,
+								Arguments: args,
+							},
+						})
+					}
+				}
+
 				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
+					ToolCalls:          toolCalls,
 					Done:               true,
 					DoneReason:         seq.doneReason,
 					PromptEvalCount:    seq.numPromptInputs,
@@ -900,7 +952,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 }
 
 func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
-	if pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone {
+	if s.model.Backend().Config().Uint("pooling_type", math.MaxUint32) == math.MaxUint32 {
 		http.Error(w, "this model does not support embeddings", http.StatusNotImplemented)
 		return
 	}
@@ -1048,8 +1100,12 @@ func (s *Server) reserveWorstCaseGraph() error {
 		batch.Positions[i] = int32(i)
 	}
 
+	batch.Outputs = make([]int32, s.parallel)
+	for i := range batch.Outputs {
+		batch.Outputs[i] = int32(i)
+	}
+
 	batch.Inputs = ctx.Input().FromIntSlice(batchInputs, len(batchInputs))
-	batch.Outputs = ctx.Input().Empty(ml.DTypeI32, s.parallel)
 
 	cache := s.model.Config().Cache
 	if cache != nil {
@@ -1083,13 +1139,9 @@ func (s *Server) allocModel(
 	// Convert memory allocation panics to errors
 	defer func() {
 		if r := recover(); r != nil {
+			debug.PrintStack()
 			if err, ok := r.(error); ok {
-				var noMem ml.ErrNoMem
-				if errors.As(err, &noMem) {
-					panicErr = noMem
-				} else {
-					panic(r)
-				}
+				panicErr = err
 			} else {
 				panic(r)
 			}

scripts/build_windows.ps1

@@ -78,7 +78,7 @@ function checkEnv() {
 }
 
 
-function buildCPU() {
+function buildOllama() {
     mkdir -Force -path "${script:DIST_DIR}\"
     if ($script:ARCH -ne "arm64") {
         Remove-Item -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}"
@@ -90,72 +90,20 @@ function buildCPU() {
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         & cmake --install build --component CPU --strip
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-    }
-}
 
-function buildCUDA11() {
-    # CUDA v11 claims to be compatible with MSVC 2022, but the latest updates are no longer compatible
-    # 19.40 is the last compiler version that works, but recent udpates are 19.43
-    # So this pins to MSVC 2019 for best compatibility
-    mkdir -Force -path "${script:DIST_DIR}\"
-    if ($script:ARCH -ne "arm64") {
         $hashEnv = @{}
         Get-ChildItem env: | foreach { $hashEnv[$_.Name] = $_.Value }
-        if ("$script:CUDA_DIRS".Contains("v11")) {
-            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V11")) { $x=$hashEnv[$_]; if (test-path -literalpath "$x\bin\nvcc.exe" ) { $cuda=$x}  }}
-            write-host "Building CUDA v11 backend libraries $cuda"
-            $env:CUDAToolkit_ROOT=$cuda
-            & cmake --fresh --preset "CUDA 11" -T cuda="$cuda" -DCMAKE_CUDA_COMPILER="$cuda\bin\nvcc.exe" -G "Visual Studio 16 2019" --install-prefix $script:DIST_DIR -DOLLAMA_RUNNER_DIR="cuda_v11"
-            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-            & cmake --build --preset "CUDA 11"  --config Release --parallel $script:JOBS
-            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-            & cmake --install build --component "CUDA" --strip
-            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-        }
-    }
-}
-
-function buildCUDA12() {
-    mkdir -Force -path "${script:DIST_DIR}\"
-    if ($script:ARCH -ne "arm64") {
-        $hashEnv = @{}
-        Get-ChildItem env: | foreach { $hashEnv[$_.Name] = $_.Value }
-        if ("$script:CUDA_DIRS".Contains("v12.8")) {
-            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V12_8")) { $x=$hashEnv[$_]; if (test-path -literalpath "$x\bin\nvcc.exe" ) { $cuda=$x}  }}
-            write-host "Building CUDA v12 backend libraries $cuda"
-            $env:CUDAToolkit_ROOT=$cuda
-            & cmake --fresh --preset "CUDA 12" -T cuda="$cuda" --install-prefix $script:DIST_DIR -DOLLAMA_RUNNER_DIR="cuda_v12"
+        if ("$script:CUDA_DIRS".Contains("v12")) {
+            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V12")) { $v12="$_" }}
+            $env:CUDAToolkit_ROOT=$hashEnv[$v12]
+            write-host "Building CUDA v12 backend libraries"
+            & cmake --fresh --preset "CUDA 12" --install-prefix $script:DIST_DIR
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --build --preset "CUDA 12"  --config Release --parallel $script:JOBS
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --install build --component "CUDA" --strip
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         }
-    }
-}
-
-function buildCUDA13() {
-    mkdir -Force -path "${script:DIST_DIR}\"
-    if ($script:ARCH -ne "arm64") {
-        $hashEnv = @{}
-        Get-ChildItem env: | foreach { $hashEnv[$_.Name] = $_.Value }
-        if ("$script:CUDA_DIRS".Contains("v13")) {
-            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V13")) { $x=$hashEnv[$_]; if (test-path -literalpath "$x\bin\nvcc.exe" ) { $cuda=$x}  }}
-            $env:CUDAToolkit_ROOT=$cuda
-            write-host "Building CUDA v13 backend libraries $cuda"
-            & cmake --fresh --preset "CUDA 13" -T cuda="$cuda" --install-prefix $script:DIST_DIR -DOLLAMA_RUNNER_DIR="cuda_v13"
-            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-            & cmake --build --preset "CUDA 13"  --config Release --parallel $script:JOBS
-            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-            & cmake --install build --component "CUDA" --strip
-            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-        }
-    }
-}
-
-function buildROCm() {
-    mkdir -Force -path "${script:DIST_DIR}\"
-    if ($script:ARCH -ne "arm64") {
         if ($env:HIP_PATH) {
             write-host "Building ROCm backend libraries"
             if (-Not (get-command -ErrorAction silent ninja)) {
@@ -181,10 +129,6 @@ function buildROCm() {
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         }
     }
-}
-
-function buildOllama() {
-    mkdir -Force -path "${script:DIST_DIR}\"
     write-host "Building ollama CLI"
     & go build -trimpath -ldflags "-s -w -X=github.com/ollama/ollama/version.Version=$script:VERSION -X=github.com/ollama/ollama/server.mode=release" .
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
@@ -292,10 +236,6 @@ function distZip() {
 checkEnv
 try {
     if ($($args.count) -eq 0) {
-        buildCPU
-        buildCUDA12
-        buildCUDA13
-        buildROCm
         buildOllama
         buildApp
         gatherDependencies

scripts/env.sh

@@ -16,7 +16,6 @@ OLLAMA_COMMON_BUILD_ARGS="--build-arg=VERSION \
     --build-arg=OLLAMA_FAST_BUILD \
     --build-arg=CUSTOM_CPU_FLAGS \
     --build-arg=GPU_RUNNER_CPU_FLAGS \
-    --build-arg=PARALLEL \
     --build-arg=AMDGPU_TARGETS"
 
 echo "Building Ollama"

server/create.go

@@ -10,11 +10,8 @@ import (
 	"io"
 	"io/fs"
 	"log/slog"
-	"net"
 	"net/http"
-	"net/url"
 	"os"
-	"path"
 	"path/filepath"
 	"slices"
 	"strings"
@@ -42,14 +39,6 @@ var (
 )
 
 func (s *Server) CreateHandler(c *gin.Context) {
-	config := &ConfigV2{
-		OS:           "linux",
-		Architecture: "amd64",
-		RootFS: RootFS{
-			Type: "layers",
-		},
-	}
-
 	var r api.CreateRequest
 	if err := c.ShouldBindJSON(&r); errors.Is(err, io.EOF) {
 		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
@@ -59,9 +48,6 @@ func (s *Server) CreateHandler(c *gin.Context) {
 		return
 	}
 
-	config.Renderer = r.Renderer
-	config.Parser = r.Parser
-
 	for v := range r.Files {
 		if !fs.ValidPath(v) {
 			c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": errFilePath.Error()})
@@ -91,34 +77,20 @@ func (s *Server) CreateHandler(c *gin.Context) {
 		oldManifest, _ := ParseNamedManifest(name)
 
 		var baseLayers []*layerGGML
-		var err error
-		var remote bool
-
 		if r.From != "" {
-			slog.Debug("create model from model name", "from", r.From)
+			slog.Debug("create model from model name")
 			fromName := model.ParseName(r.From)
 			if !fromName.IsValid() {
 				ch <- gin.H{"error": errtypes.InvalidModelNameErrMsg, "status": http.StatusBadRequest}
 				return
 			}
-			if r.RemoteHost != "" {
-				ru, err := remoteURL(r.RemoteHost)
-				if err != nil {
-					ch <- gin.H{"error": "bad remote", "status": http.StatusBadRequest}
-					return
-				}
 
-				config.RemoteModel = r.From
-				config.RemoteHost = ru
-				remote = true
-			} else {
-				ctx, cancel := context.WithCancel(c.Request.Context())
-				defer cancel()
+			ctx, cancel := context.WithCancel(c.Request.Context())
+			defer cancel()
 
-				baseLayers, err = parseFromModel(ctx, fromName, fn)
-				if err != nil {
-					ch <- gin.H{"error": err.Error()}
-				}
+			baseLayers, err = parseFromModel(ctx, fromName, fn)
+			if err != nil {
+				ch <- gin.H{"error": err.Error()}
 			}
 		} else if r.Files != nil {
 			baseLayers, err = convertModelFromFiles(r.Files, baseLayers, false, fn)
@@ -138,7 +110,7 @@ func (s *Server) CreateHandler(c *gin.Context) {
 		}
 
 		var adapterLayers []*layerGGML
-		if !remote && r.Adapters != nil {
+		if r.Adapters != nil {
 			adapterLayers, err = convertModelFromFiles(r.Adapters, baseLayers, true, fn)
 			if err != nil {
 				for _, badReq := range []error{errNoFilesProvided, errOnlyOneAdapterSupported, errOnlyGGUFSupported, errUnknownType, errFilePath} {
@@ -156,56 +128,7 @@ func (s *Server) CreateHandler(c *gin.Context) {
 			baseLayers = append(baseLayers, adapterLayers...)
 		}
 
-		// Info is not currently exposed by Modelfiles, but allows overriding various
-		// config values
-		if r.Info != nil {
-			caps, ok := r.Info["capabilities"]
-			if ok {
-				switch tcaps := caps.(type) {
-				case []any:
-					caps := make([]string, len(tcaps))
-					for i, c := range tcaps {
-						str, ok := c.(string)
-						if !ok {
-							continue
-						}
-						caps[i] = str
-					}
-					config.Capabilities = append(config.Capabilities, caps...)
-				}
-			}
-
-			strFromInfo := func(k string) string {
-				v, ok := r.Info[k]
-				if ok {
-					val := v.(string)
-					return val
-				}
-				return ""
-			}
-
-			vFromInfo := func(k string) float64 {
-				v, ok := r.Info[k]
-				if ok {
-					val := v.(float64)
-					return val
-				}
-				return 0
-			}
-
-			config.ModelFamily = strFromInfo("model_family")
-			if config.ModelFamily != "" {
-				config.ModelFamilies = []string{config.ModelFamily}
-			}
-
-			config.BaseName = strFromInfo("base_name")
-			config.FileType = strFromInfo("quantization_level")
-			config.ModelType = strFromInfo("parameter_size")
-			config.ContextLen = int(vFromInfo("context_length"))
-			config.EmbedLen = int(vFromInfo("embedding_length"))
-		}
-
-		if err := createModel(r, name, baseLayers, config, fn); err != nil {
+		if err := createModel(r, name, baseLayers, fn); err != nil {
 			if errors.Is(err, errBadTemplate) {
 				ch <- gin.H{"error": err.Error(), "status": http.StatusBadRequest}
 				return
@@ -231,51 +154,6 @@ func (s *Server) CreateHandler(c *gin.Context) {
 	streamResponse(c, ch)
 }
 
-func remoteURL(raw string) (string, error) {
-	// Special‑case: user supplied only a path ("/foo/bar").
-	if strings.HasPrefix(raw, "/") {
-		return (&url.URL{
-			Scheme: "http",
-			Host:   net.JoinHostPort("localhost", "11434"),
-			Path:   path.Clean(raw),
-		}).String(), nil
-	}
-
-	if !strings.Contains(raw, "://") {
-		raw = "http://" + raw
-	}
-
-	if raw == "ollama.com" || raw == "http://ollama.com" {
-		raw = "https://ollama.com:443"
-	}
-
-	u, err := url.Parse(raw)
-	if err != nil {
-		return "", fmt.Errorf("parse error: %w", err)
-	}
-
-	if u.Host == "" {
-		u.Host = "localhost"
-	}
-
-	hostPart, portPart, err := net.SplitHostPort(u.Host)
-	if err == nil {
-		u.Host = net.JoinHostPort(hostPart, portPart)
-	} else {
-		u.Host = net.JoinHostPort(u.Host, "11434")
-	}
-
-	if u.Path != "" {
-		u.Path = path.Clean(u.Path)
-	}
-
-	if u.Path == "/" {
-		u.Path = ""
-	}
-
-	return u.String(), nil
-}
-
 func convertModelFromFiles(files map[string]string, baseLayers []*layerGGML, isAdapter bool, fn func(resp api.ProgressResponse)) ([]*layerGGML, error) {
 	switch detectModelTypeFromFiles(files) {
 	case "safetensors":
@@ -438,7 +316,15 @@ func kvFromLayers(baseLayers []*layerGGML) (ggml.KV, error) {
 	return ggml.KV{}, fmt.Errorf("no base model was found")
 }
 
-func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML, config *ConfigV2, fn func(resp api.ProgressResponse)) (err error) {
+func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML, fn func(resp api.ProgressResponse)) (err error) {
+	config := ConfigV2{
+		OS:           "linux",
+		Architecture: "amd64",
+		RootFS: RootFS{
+			Type: "layers",
+		},
+	}
+
 	var layers []Layer
 	for _, layer := range baseLayers {
 		if layer.GGML != nil {
@@ -518,7 +404,7 @@ func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML,
 		return err
 	}
 
-	configLayer, err := createConfigLayer(layers, *config)
+	configLayer, err := createConfigLayer(layers, config)
 	if err != nil {
 		return err
 	}

server/create_test.go

@@ -104,154 +104,3 @@ func TestConvertFromSafetensors(t *testing.T) {
 		})
 	}
 }
-
-func TestRemoteURL(t *testing.T) {
-	tests := []struct {
-		name     string
-		input    string
-		expected string
-		hasError bool
-	}{
-		{
-			name:     "absolute path",
-			input:    "/foo/bar",
-			expected: "http://localhost:11434/foo/bar",
-			hasError: false,
-		},
-		{
-			name:     "absolute path with cleanup",
-			input:    "/foo/../bar",
-			expected: "http://localhost:11434/bar",
-			hasError: false,
-		},
-		{
-			name:     "root path",
-			input:    "/",
-			expected: "http://localhost:11434/",
-			hasError: false,
-		},
-		{
-			name:     "host without scheme",
-			input:    "example.com",
-			expected: "http://example.com:11434",
-			hasError: false,
-		},
-		{
-			name:     "host with port",
-			input:    "example.com:8080",
-			expected: "http://example.com:8080",
-			hasError: false,
-		},
-		{
-			name:     "full URL",
-			input:    "https://example.com:8080/path",
-			expected: "https://example.com:8080/path",
-			hasError: false,
-		},
-		{
-			name:     "full URL with path cleanup",
-			input:    "https://example.com:8080/path/../other",
-			expected: "https://example.com:8080/other",
-			hasError: false,
-		},
-		{
-			name:     "ollama.com special case",
-			input:    "ollama.com",
-			expected: "https://ollama.com:443",
-			hasError: false,
-		},
-		{
-			name:     "http ollama.com special case",
-			input:    "http://ollama.com",
-			expected: "https://ollama.com:443",
-			hasError: false,
-		},
-		{
-			name:     "URL with only host",
-			input:    "http://example.com",
-			expected: "http://example.com:11434",
-			hasError: false,
-		},
-		{
-			name:     "URL with root path cleaned",
-			input:    "http://example.com/",
-			expected: "http://example.com:11434",
-			hasError: false,
-		},
-		{
-			name:     "invalid URL",
-			input:    "http://[::1]:namedport", // invalid port
-			expected: "",
-			hasError: true,
-		},
-		{
-			name:     "empty string",
-			input:    "",
-			expected: "http://localhost:11434",
-			hasError: false,
-		},
-		{
-			name:     "host with scheme but no port",
-			input:    "http://localhost",
-			expected: "http://localhost:11434",
-			hasError: false,
-		},
-		{
-			name:     "complex path cleanup",
-			input:    "/a/b/../../c/./d",
-			expected: "http://localhost:11434/c/d",
-			hasError: false,
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			result, err := remoteURL(tt.input)
-
-			if tt.hasError {
-				if err == nil {
-					t.Errorf("expected error but got none")
-				}
-				return
-			}
-
-			if err != nil {
-				t.Errorf("unexpected error: %v", err)
-				return
-			}
-
-			if result != tt.expected {
-				t.Errorf("expected %q, got %q", tt.expected, result)
-			}
-		})
-	}
-}
-
-func TestRemoteURL_Idempotent(t *testing.T) {
-	// Test that applying remoteURL twice gives the same result as applying it once
-	testInputs := []string{
-		"/foo/bar",
-		"example.com",
-		"https://example.com:8080/path",
-		"ollama.com",
-		"http://localhost:11434",
-	}
-
-	for _, input := range testInputs {
-		t.Run(input, func(t *testing.T) {
-			firstResult, err := remoteURL(input)
-			if err != nil {
-				t.Fatalf("first call failed: %v", err)
-			}
-
-			secondResult, err := remoteURL(firstResult)
-			if err != nil {
-				t.Fatalf("second call failed: %v", err)
-			}
-
-			if firstResult != secondResult {
-				t.Errorf("function is not idempotent: first=%q, second=%q", firstResult, secondResult)
-			}
-		})
-	}
-}

server/images.go

@@ -24,7 +24,6 @@ import (
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/fs/gguf"
-	"github.com/ollama/ollama/model/parsers"
 	"github.com/ollama/ollama/parser"
 	"github.com/ollama/ollama/template"
 	"github.com/ollama/ollama/thinking"
@@ -74,38 +73,29 @@ func (m *Model) Capabilities() []model.Capability {
 	capabilities := []model.Capability{}
 
 	// Check for completion capability
-	if m.ModelPath != "" {
-		f, err := gguf.Open(m.ModelPath)
-		if err == nil {
-			defer f.Close()
+	f, err := gguf.Open(m.ModelPath)
+	if err == nil {
+		defer f.Close()
 
-			if f.KeyValue("pooling_type").Valid() {
-				capabilities = append(capabilities, model.CapabilityEmbedding)
-			} else {
-				// If no embedding is specified, we assume the model supports completion
-				capabilities = append(capabilities, model.CapabilityCompletion)
-			}
-			if f.KeyValue("vision.block_count").Valid() {
-				capabilities = append(capabilities, model.CapabilityVision)
-			}
+		if f.KeyValue("pooling_type").Valid() {
+			capabilities = append(capabilities, model.CapabilityEmbedding)
 		} else {
-			slog.Error("couldn't open model file", "error", err)
+			// If no embedding is specified, we assume the model supports completion
+			capabilities = append(capabilities, model.CapabilityCompletion)
 		}
-	} else if len(m.Config.Capabilities) > 0 {
-		for _, c := range m.Config.Capabilities {
-			capabilities = append(capabilities, model.Capability(c))
+		if f.KeyValue("vision.block_count").Valid() {
+			capabilities = append(capabilities, model.CapabilityVision)
 		}
 	} else {
-		slog.Warn("unknown capabilities for model", "model", m.Name)
+		slog.Error("couldn't open model file", "error", err)
 	}
 
 	if m.Template == nil {
 		return capabilities
 	}
 
-	builtinParser := parsers.ParserForName(m.Config.Parser)
 	// Check for tools capability
-	if slices.Contains(m.Template.Vars(), "tools") || (builtinParser != nil && builtinParser.HasToolSupport()) {
+	if slices.Contains(m.Template.Vars(), "tools") {
 		capabilities = append(capabilities, model.CapabilityTools)
 	}
 
@@ -119,16 +109,10 @@ func (m *Model) Capabilities() []model.Capability {
 		capabilities = append(capabilities, model.CapabilityVision)
 	}
 
-	// Skip the thinking check if it's already set
-	if slices.Contains(capabilities, "thinking") {
-		return capabilities
-	}
-
 	// Check for thinking capability
 	openingTag, closingTag := thinking.InferTags(m.Template.Template)
 	hasTags := openingTag != "" && closingTag != ""
-	isGptoss := slices.Contains([]string{"gptoss", "gpt-oss"}, m.Config.ModelFamily)
-	if hasTags || isGptoss || (builtinParser != nil && builtinParser.HasThinkingSupport()) {
+	if hasTags || slices.Contains([]string{"gptoss", "gpt-oss"}, m.Config.ModelFamily) {
 		capabilities = append(capabilities, model.CapabilityThinking)
 	}
 
@@ -214,20 +198,6 @@ func (m *Model) String() string {
 		})
 	}
 
-	if m.Config.Renderer != "" {
-		modelfile.Commands = append(modelfile.Commands, parser.Command{
-			Name: "renderer",
-			Args: m.Config.Renderer,
-		})
-	}
-
-	if m.Config.Parser != "" {
-		modelfile.Commands = append(modelfile.Commands, parser.Command{
-			Name: "parser",
-			Args: m.Config.Parser,
-		})
-	}
-
 	for k, v := range m.Options {
 		switch v := v.(type) {
 		case []any:
@@ -266,19 +236,8 @@ type ConfigV2 struct {
 	ModelFormat   string   `json:"model_format"`
 	ModelFamily   string   `json:"model_family"`
 	ModelFamilies []string `json:"model_families"`
-	ModelType     string   `json:"model_type"` // shown as Parameter Size
-	FileType      string   `json:"file_type"`  // shown as Quantization Level
-	Renderer      string   `json:"renderer,omitempty"`
-	Parser        string   `json:"parser,omitempty"`
-
-	RemoteHost  string `json:"remote_host,omitempty"`
-	RemoteModel string `json:"remote_model,omitempty"`
-
-	// used for remotes
-	Capabilities []string `json:"capabilities,omitempty"`
-	ContextLen   int      `json:"context_length,omitempty"`
-	EmbedLen     int      `json:"embedding_length,omitempty"`
-	BaseName     string   `json:"base_name,omitempty"`
+	ModelType     string   `json:"model_type"`
+	FileType      string   `json:"file_type"`
 
 	// required by spec
 	Architecture string `json:"architecture"`

server/internal/internal/backoff/backoff.go

@@ -25,7 +25,10 @@ func Loop(ctx context.Context, maxBackoff time.Duration) iter.Seq2[int, error] {
 
 			// n^2 backoff timer is a little smoother than the
 			// common choice of 2^n.
-			d := min(time.Duration(n*n)*10*time.Millisecond, maxBackoff)
+			d := time.Duration(n*n) * 10 * time.Millisecond
+			if d > maxBackoff {
+				d = maxBackoff
+			}
 			// Randomize the delay between 0.5-1.5 x msec, in order
 			// to prevent accidental "thundering herd" problems.
 			d = time.Duration(float64(d) * (rand.Float64() + 0.5))

server/prompt.go

@@ -11,7 +11,6 @@ import (
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/llm"
-	"github.com/ollama/ollama/model/renderers"
 	"github.com/ollama/ollama/template"
 )
 
@@ -42,12 +41,18 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 			}
 		}
 
-		p, err := renderPrompt(m, append(system, msgs[i:]...), tools, think)
-		if err != nil {
+		thinkVal := false
+		thinkLevel := ""
+		if think != nil {
+			thinkVal = think.Bool()
+			thinkLevel = think.String()
+		}
+		var b bytes.Buffer
+		if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[i:]...), Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
 			return "", nil, err
 		}
 
-		s, err := tokenize(ctx, p)
+		s, err := tokenize(ctx, b.String())
 		if err != nil {
 			return "", nil, err
 		}
@@ -96,23 +101,6 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	}
 
 	// truncate any messages that do not fit into the context window
-	p, err := renderPrompt(m, append(system, msgs[currMsgIdx:]...), tools, think)
-	if err != nil {
-		return "", nil, err
-	}
-
-	return p, images, nil
-}
-
-func renderPrompt(m *Model, msgs []api.Message, tools []api.Tool, think *api.ThinkValue) (string, error) {
-	if m.Config.Renderer != "" {
-		rendered, err := renderers.RenderWithRenderer(m.Config.Renderer, msgs, tools, think)
-		if err != nil {
-			return "", err
-		}
-		return rendered, nil
-	}
-
 	var b bytes.Buffer
 	thinkVal := false
 	thinkLevel := ""
@@ -120,8 +108,9 @@ func renderPrompt(m *Model, msgs []api.Message, tools []api.Tool, think *api.Thi
 		thinkVal = think.Bool()
 		thinkLevel = think.String()
 	}
-	if err := m.Template.Execute(&b, template.Values{Messages: msgs, Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
-		return "", err
+	if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[currMsgIdx:]...), Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
+		return "", nil, err
 	}
-	return b.String(), nil
+
+	return b.String(), images, nil
 }

server/routes.go

@@ -15,7 +15,6 @@ import (
 	"net"
 	"net/http"
 	"net/netip"
-	"net/url"
 	"os"
 	"os/signal"
 	"slices"
@@ -36,7 +35,6 @@ import (
 	"github.com/ollama/ollama/harmony"
 	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/logutil"
-	"github.com/ollama/ollama/model/parsers"
 	"github.com/ollama/ollama/openai"
 	"github.com/ollama/ollama/server/internal/client/ollama"
 	"github.com/ollama/ollama/server/internal/registry"
@@ -48,18 +46,6 @@ import (
 	"github.com/ollama/ollama/version"
 )
 
-func shouldUseHarmony(model *Model) bool {
-	if slices.Contains([]string{"gptoss", "gpt-oss"}, model.Config.ModelFamily) {
-		// heuristic to check whether the template expects to be parsed via harmony:
-		// search for harmony tags that are nearly always used
-		if model.Template.Contains("<|start|>") && model.Template.Contains("<|end|>") {
-			return true
-		}
-	}
-
-	return false
-}
-
 func experimentEnabled(name string) bool {
 	return slices.Contains(strings.Split(os.Getenv("OLLAMA_EXPERIMENT"), ","), name)
 }
@@ -190,83 +176,6 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
-		origModel := req.Model
-
-		remoteURL, err := url.Parse(m.Config.RemoteHost)
-		if err != nil {
-			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			return
-		}
-
-		if !slices.Contains(envconfig.Remotes(), remoteURL.Hostname()) {
-			slog.Info("remote model", "remotes", envconfig.Remotes(), "remoteURL", m.Config.RemoteHost, "hostname", remoteURL.Hostname())
-			c.JSON(http.StatusBadRequest, gin.H{"error": "this server cannot run this remote model"})
-			return
-		}
-
-		req.Model = m.Config.RemoteModel
-
-		if req.Template == "" && m.Template.String() != "" {
-			req.Template = m.Template.String()
-		}
-
-		if req.Options == nil {
-			req.Options = map[string]any{}
-		}
-
-		for k, v := range m.Options {
-			if _, ok := req.Options[k]; !ok {
-				req.Options[k] = v
-			}
-		}
-
-		// update the system prompt from the model if one isn't already specified
-		if req.System == "" && m.System != "" {
-			req.System = m.System
-		}
-
-		if len(m.Messages) > 0 {
-			slog.Warn("embedded messages in the model not supported with '/api/generate'; try '/api/chat' instead")
-		}
-
-		fn := func(resp api.GenerateResponse) error {
-			resp.Model = origModel
-			resp.RemoteModel = m.Config.RemoteModel
-			resp.RemoteHost = m.Config.RemoteHost
-
-			data, err := json.Marshal(resp)
-			if err != nil {
-				return err
-			}
-
-			if _, err = c.Writer.Write(append(data, '\n')); err != nil {
-				return err
-			}
-			c.Writer.Flush()
-			return nil
-		}
-
-		client := api.NewClient(remoteURL, http.DefaultClient)
-		err = client.Generate(c, &req, fn)
-		if err != nil {
-			var authError api.AuthorizationError
-			if errors.As(err, &authError) {
-				c.JSON(authError.StatusCode, gin.H{"error": "unauthorized", "public_key": authError.PublicKey})
-				return
-			}
-			var apiError api.StatusError
-			if errors.As(err, &apiError) {
-				c.JSON(apiError.StatusCode, apiError)
-				return
-			}
-			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			return
-		}
-
-		return
-	}
-
 	// expire the runner
 	if req.Prompt == "" && req.KeepAlive != nil && req.KeepAlive.Duration == 0 {
 		s.sched.expireRunner(m)
@@ -286,13 +195,11 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	useHarmony := shouldUseHarmony(m) && !req.Raw
-	var harmonyMessageHandler *harmony.HarmonyMessageHandler
-	var harmonyToolParser *harmony.HarmonyToolCallAccumulator
+	useHarmony := harmony.ShouldUseHarmony(m.Config.ModelFamily, m.Template) && !req.Raw
+	var functionNameMap *harmony.FunctionNameMap
+
 	if useHarmony {
-		harmonyMessageHandler = harmony.NewHarmonyMessageHandler()
-		harmonyMessageHandler.HarmonyParser.AddImplicitStart()
-		harmonyToolParser = harmonyMessageHandler.CreateToolParser()
+		functionNameMap = harmony.NewFunctionNameMap()
 	}
 
 	// Validate Think value: string values currently only allowed for gptoss models
@@ -408,10 +315,10 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	// If debug mode is enabled, return the rendered template instead of calling the model
 	if req.DebugRenderOnly {
-		c.JSON(http.StatusOK, api.GenerateResponse{
+		c.JSON(http.StatusOK, api.DebugTemplateResponse{
 			Model:     req.Model,
 			CreatedAt: time.Now().UTC(),
-			DebugInfo: &api.DebugInfo{
+			DebugInfo: api.DebugInfo{
 				RenderedTemplate: prompt,
 				ImageCount:       len(images),
 			},
@@ -427,9 +334,6 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 				OpeningTag: openingTag,
 				ClosingTag: closingTag,
 			}
-			if strings.HasSuffix(strings.TrimSpace(prompt), openingTag) {
-				thinkingState.AddContent(openingTag)
-			}
 		}
 	}
 
@@ -439,16 +343,19 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		var sb strings.Builder
 		defer close(ch)
 		if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
-			Prompt:  prompt,
-			Images:  images,
-			Format:  req.Format,
-			Options: opts,
+			Prompt:     prompt,
+			Images:     images,
+			Format:     req.Format,
+			Options:    opts,
+			UseHarmony: useHarmony,
 		}, func(cr llm.CompletionResponse) {
 			res := api.GenerateResponse{
 				Model:     req.Model,
 				CreatedAt: time.Now().UTC(),
 				Response:  cr.Content,
 				Done:      cr.Done,
+				Thinking:  cr.Thinking,
+				ToolCalls: cr.ToolCalls,
 				Metrics: api.Metrics{
 					PromptEvalCount:    cr.PromptEvalCount,
 					PromptEvalDuration: cr.PromptEvalDuration,
@@ -457,12 +364,22 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 				},
 			}
 
+			if res.Done {
+				res.DoneReason = cr.DoneReason.String()
+				res.TotalDuration = time.Since(checkpointStart)
+				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
+			}
+
 			if useHarmony {
-				content, thinking, toolContent := harmonyMessageHandler.AddContent(cr.Content, harmonyToolParser)
-				res.Response = content
-				res.Thinking = thinking
-				harmonyToolParser.Add(toolContent)
-			} else if thinkingState != nil {
+				for i, tool := range res.ToolCalls {
+					res.ToolCalls[i].Function.Name = functionNameMap.OriginalFromConverted(tool.Function.Name)
+				}
+				if res.Response != "" || res.Thinking != "" || len(res.ToolCalls) > 0 || res.Done {
+					ch <- res
+				}
+				return
+			}
+			if thinkingState != nil {
 				thinking, content := thinkingState.AddContent(cr.Content)
 				res.Thinking = thinking
 				res.Response = content
@@ -473,30 +390,6 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 			}
 
 			if cr.Done {
-				if useHarmony {
-					toolName, toolContent := harmonyToolParser.Drain()
-					if toolName != nil {
-						*toolName = strings.TrimPrefix(*toolName, "functions.")
-						var args api.ToolCallFunctionArguments
-						if err := json.Unmarshal([]byte(toolContent), &args); err != nil {
-							errStr := fmt.Sprintf("error parsing tool call: raw='%s', err=%s", toolContent, err.Error())
-							ch <- gin.H{"error": errStr}
-							return
-						}
-
-						res.ToolCalls = append(res.ToolCalls, api.ToolCall{
-							Function: api.ToolCallFunction{
-								Name:      *toolName,
-								Arguments: args,
-							},
-						})
-					}
-				}
-
-				res.DoneReason = cr.DoneReason.String()
-				res.TotalDuration = time.Since(checkpointStart)
-				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
-
 				if !req.Raw {
 					tokens, err := r.Tokenize(c.Request.Context(), prompt+sb.String())
 					if err != nil {
@@ -570,6 +463,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 	}
 
 	truncate := true
+
 	if req.Truncate != nil && !*req.Truncate {
 		truncate = false
 	}
@@ -632,27 +526,11 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 		ctxLen := min(opts.NumCtx, int(kvData.ContextLength()))
 		if len(tokens) > ctxLen {
 			if !truncate {
-				c.JSON(http.StatusBadRequest, gin.H{"error": "input exceeds maximum context length"})
-				return
-			}
-
-			if bos := kvData.Uint("tokenizer.ggml.bos_token_id"); tokens[0] != int(bos) && kvData.Bool("add_bos_token", true) {
-				ctxLen--
-			}
-
-			if eos := kvData.Uint("tokenizer.ggml.eos_token_id"); tokens[len(tokens)-1] != int(eos) && kvData.Bool("add_eos_token", true) {
-				ctxLen--
-			}
-
-			slog.Info("", "ctxLen", ctxLen, "tokenCount", len(tokens))
-			if ctxLen <= 0 {
-				// return error if the truncated input would be empty or just special tokens
-				c.JSON(http.StatusBadRequest, gin.H{"error": "input after truncation exceeds maximum context length"})
+				c.JSON(http.StatusBadRequest, gin.H{"error": "input length exceeds maximum context length"})
 				return
 			}
 
 			tokens = tokens[:ctxLen]
-
 			s, err = r.Detokenize(c.Request.Context(), tokens)
 			if err != nil {
 				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
@@ -673,12 +551,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 			if err != nil {
 				return err
 			}
-			// TODO: this first normalization should be done by the model
-			embedding = normalize(embedding)
-			if req.Dimensions > 0 && req.Dimensions < len(embedding) {
-				embedding = normalize(embedding[:req.Dimensions])
-			}
-			embeddings[i] = embedding
+			embeddings[i] = normalize(embedding)
 			return nil
 		})
 	}
@@ -704,7 +577,11 @@ func normalize(vec []float32) []float32 {
 		sum += v * v
 	}
 
-	norm := float32(1.0 / max(math.Sqrt(float64(sum)), 1e-12))
+	norm := float32(0.0)
+	if sum > 0 {
+		norm = float32(1.0 / math.Sqrt(float64(sum)))
+	}
+
 	for i := range vec {
 		vec[i] *= norm
 	}
@@ -1019,28 +896,6 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 		ModifiedAt:   manifest.fi.ModTime(),
 	}
 
-	if m.Config.RemoteHost != "" {
-		resp.RemoteHost = m.Config.RemoteHost
-		resp.RemoteModel = m.Config.RemoteModel
-
-		if m.Config.ModelFamily != "" {
-			resp.ModelInfo = make(map[string]any)
-			resp.ModelInfo["general.architecture"] = m.Config.ModelFamily
-
-			if m.Config.BaseName != "" {
-				resp.ModelInfo["general.basename"] = m.Config.BaseName
-			}
-
-			if m.Config.ContextLen > 0 {
-				resp.ModelInfo[fmt.Sprintf("%s.context_length", m.Config.ModelFamily)] = m.Config.ContextLen
-			}
-
-			if m.Config.EmbedLen > 0 {
-				resp.ModelInfo[fmt.Sprintf("%s.embedding_length", m.Config.ModelFamily)] = m.Config.EmbedLen
-			}
-		}
-	}
-
 	var params []string
 	cs := 30
 	for k, v := range m.Options {
@@ -1071,11 +926,6 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	fmt.Fprint(&sb, m.String())
 	resp.Modelfile = sb.String()
 
-	// skip loading tensor information if this is a remote model
-	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
-		return resp, nil
-	}
-
 	kvData, tensors, err := getModelData(m.ModelPath, req.Verbose)
 	if err != nil {
 		return nil, err
@@ -1152,13 +1002,11 @@ func (s *Server) ListHandler(c *gin.Context) {
 
 		// tag should never be masked
 		models = append(models, api.ListModelResponse{
-			Model:       n.DisplayShortest(),
-			Name:        n.DisplayShortest(),
-			RemoteModel: cf.RemoteModel,
-			RemoteHost:  cf.RemoteHost,
-			Size:        m.Size(),
-			Digest:      m.digest,
-			ModifiedAt:  m.fi.ModTime(),
+			Model:      n.DisplayShortest(),
+			Name:       n.DisplayShortest(),
+			Size:       m.Size(),
+			Digest:     m.digest,
+			ModifiedAt: m.fi.ModTime(),
 			Details: api.ModelDetails{
 				Format:            cf.ModelFormat,
 				Family:            cf.ModelFamily,
@@ -1418,9 +1266,6 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
 	r.POST("/api/show", s.ShowHandler)
 	r.DELETE("/api/delete", s.DeleteHandler)
 
-	r.DELETE("/api/user/keys/:encodedKey", s.SignoutHandler)
-	r.POST("/api/me", s.WhoamiHandler)
-
 	// Create
 	r.POST("/api/create", s.CreateHandler)
 	r.POST("/api/blobs/:digest", s.CreateBlobHandler)
@@ -1617,49 +1462,6 @@ func streamResponse(c *gin.Context, ch chan any) {
 	})
 }
 
-func (s *Server) WhoamiHandler(c *gin.Context) {
-	// todo allow other hosts
-	u, err := url.Parse("https://ollama.com")
-	if err != nil {
-		slog.Error(err.Error())
-		c.JSON(http.StatusInternalServerError, gin.H{"error": "URL parse error"})
-		return
-	}
-
-	client := api.NewClient(u, http.DefaultClient)
-	user, err := client.Whoami(c)
-	if err != nil {
-		slog.Error(err.Error())
-	}
-	c.JSON(http.StatusOK, user)
-}
-
-func (s *Server) SignoutHandler(c *gin.Context) {
-	encodedKey := c.Param("encodedKey")
-
-	// todo allow other hosts
-	u, err := url.Parse("https://ollama.com")
-	if err != nil {
-		slog.Error(err.Error())
-		c.JSON(http.StatusInternalServerError, gin.H{"error": "URL parse error"})
-		return
-	}
-
-	client := api.NewClient(u, http.DefaultClient)
-	err = client.Signout(c, encodedKey)
-	if err != nil {
-		slog.Error(err.Error())
-		if strings.Contains(err.Error(), "page not found") || strings.Contains(err.Error(), "invalid credentials") {
-			c.JSON(http.StatusNotFound, gin.H{"error": "you are not currently signed in"})
-			return
-		}
-		c.JSON(http.StatusInternalServerError, gin.H{"error": "there was an error signing out"})
-		return
-	}
-
-	c.JSON(http.StatusOK, nil)
-}
-
 func (s *Server) PsHandler(c *gin.Context) {
 	models := []api.ProcessModelResponse{}
 
@@ -1716,34 +1518,21 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
-	name := model.ParseName(req.Model)
-	if !name.IsValid() {
-		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
-		return
-	}
-
-	name, err := getExistingName(name)
-	if err != nil {
-		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
-		return
-	}
-
-	m, err := GetModel(req.Model)
-	if err != nil {
-		switch {
-		case os.IsNotExist(err):
-			c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Model)})
-		case err.Error() == errtypes.InvalidModelNameErrMsg:
-			c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
-		default:
-			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-		}
-		return
-	}
-
 	// expire the runner
-	if len(req.Messages) == 0 && req.KeepAlive != nil && int(req.KeepAlive.Seconds()) == 0 {
-		s.sched.expireRunner(m)
+	if len(req.Messages) == 0 && req.KeepAlive != nil && req.KeepAlive.Duration == 0 {
+		model, err := GetModel(req.Model)
+		if err != nil {
+			switch {
+			case os.IsNotExist(err):
+				c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Model)})
+			case err.Error() == errtypes.InvalidModelNameErrMsg:
+				c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
+			default:
+				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+			}
+			return
+		}
+		s.sched.expireRunner(model)
 
 		c.JSON(http.StatusOK, api.ChatResponse{
 			Model:      req.Model,
@@ -1755,76 +1544,6 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
-	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
-		origModel := req.Model
-
-		remoteURL, err := url.Parse(m.Config.RemoteHost)
-		if err != nil {
-			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			return
-		}
-
-		if !slices.Contains(envconfig.Remotes(), remoteURL.Hostname()) {
-			slog.Info("remote model", "remotes", envconfig.Remotes(), "remoteURL", m.Config.RemoteHost, "hostname", remoteURL.Hostname())
-			c.JSON(http.StatusBadRequest, gin.H{"error": "this server cannot run this remote model"})
-			return
-		}
-
-		req.Model = m.Config.RemoteModel
-		if req.Options == nil {
-			req.Options = map[string]any{}
-		}
-
-		msgs := append(m.Messages, req.Messages...)
-		if req.Messages[0].Role != "system" && m.System != "" {
-			msgs = append([]api.Message{{Role: "system", Content: m.System}}, msgs...)
-		}
-		msgs = filterThinkTags(msgs, m)
-		req.Messages = msgs
-
-		for k, v := range m.Options {
-			if _, ok := req.Options[k]; !ok {
-				req.Options[k] = v
-			}
-		}
-
-		fn := func(resp api.ChatResponse) error {
-			resp.Model = origModel
-			resp.RemoteModel = m.Config.RemoteModel
-			resp.RemoteHost = m.Config.RemoteHost
-
-			data, err := json.Marshal(resp)
-			if err != nil {
-				return err
-			}
-
-			if _, err = c.Writer.Write(append(data, '\n')); err != nil {
-				return err
-			}
-			c.Writer.Flush()
-			return nil
-		}
-
-		client := api.NewClient(remoteURL, http.DefaultClient)
-		err = client.Chat(c, &req, fn)
-		if err != nil {
-			var authError api.AuthorizationError
-			if errors.As(err, &authError) {
-				c.JSON(authError.StatusCode, gin.H{"error": "unauthorized", "public_key": authError.PublicKey})
-				return
-			}
-			var apiError api.StatusError
-			if errors.As(err, &apiError) {
-				c.JSON(apiError.StatusCode, apiError)
-				return
-			}
-			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			return
-		}
-
-		return
-	}
-
 	caps := []model.Capability{model.CapabilityCompletion}
 	if len(req.Tools) > 0 {
 		caps = append(caps, model.CapabilityTools)
@@ -1833,6 +1552,17 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		caps = append(caps, model.CapabilityThinking)
 	}
 
+	name := model.ParseName(req.Model)
+	if !name.IsValid() {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
+		return
+	}
+	name, err := getExistingName(name)
+	if err != nil {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
+		return
+	}
+
 	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
 	if errors.Is(err, errCapabilityCompletion) {
 		c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support chat", req.Model)})
@@ -1861,32 +1591,21 @@ func (s *Server) ChatHandler(c *gin.Context) {
 	}
 	msgs = filterThinkTags(msgs, m)
 
-	var builtinParser parsers.Parser
-	if m.Config.Parser != "" {
-		builtinParser = parsers.ParserForName(m.Config.Parser)
-	}
-
-	var harmonyMessageHandler *harmony.HarmonyMessageHandler
-	var harmonyToolParser *harmony.HarmonyToolCallAccumulator
-
-	useHarmony := shouldUseHarmony(m) || m.Config.Parser == "harmony"
+	useHarmony := harmony.ShouldUseHarmony(m.Config.ModelFamily, m.Template)
 
 	processedTools := req.Tools
+	var functionNameMap *harmony.FunctionNameMap
+	var prefillString string
+	// TODO(parthsareen): this can be abstracted to not be model specific and potentially moved to the runner
 	if useHarmony {
-		harmonyMessageHandler = harmony.NewHarmonyMessageHandler()
-		var lastMessage *api.Message
-		if len(msgs) > 0 {
-			lastMessage = &msgs[len(msgs)-1]
-		}
-		harmonyMessageHandler.HarmonyParser.AddImplicitStartOrPrefill(lastMessage)
-		harmonyToolParser = harmonyMessageHandler.CreateToolParser()
-
+		prefillString = harmony.Prefill(msgs[len(msgs)-1])
+		functionNameMap = harmony.NewFunctionNameMap()
 		// make a copy of tools to pass to the chat prompt. Function names may be
 		// renamed to be valid Harmony function names.
 		processedTools = make([]api.Tool, len(req.Tools))
 		copy(processedTools, req.Tools)
 		for i, tool := range processedTools {
-			processedTools[i].Function.Name = harmonyMessageHandler.FunctionNameMap.ConvertAndAdd(tool.Function.Name)
+			processedTools[i].Function.Name = functionNameMap.ConvertAndAdd(tool.Function.Name)
 		}
 	}
 
@@ -1899,10 +1618,10 @@ func (s *Server) ChatHandler(c *gin.Context) {
 
 	// If debug mode is enabled, return the rendered template instead of calling the model
 	if req.DebugRenderOnly {
-		c.JSON(http.StatusOK, api.ChatResponse{
+		c.JSON(http.StatusOK, api.DebugTemplateResponse{
 			Model:     req.Model,
 			CreatedAt: time.Now().UTC(),
-			DebugInfo: &api.DebugInfo{
+			DebugInfo: api.DebugInfo{
 				RenderedTemplate: prompt,
 				ImageCount:       len(images),
 			},
@@ -1939,15 +1658,17 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		defer close(ch)
 
 		if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
-			Prompt:  prompt,
-			Images:  images,
-			Format:  req.Format,
-			Options: opts,
+			Prompt:        prompt,
+			Images:        images,
+			Format:        req.Format,
+			Options:       opts,
+			UseHarmony:    useHarmony,
+			PrefillString: prefillString,
 		}, func(r llm.CompletionResponse) {
 			res := api.ChatResponse{
 				Model:     req.Model,
 				CreatedAt: time.Now().UTC(),
-				Message:   api.Message{Role: "assistant", Content: r.Content},
+				Message:   api.Message{Role: "assistant", Content: r.Content, Thinking: r.Thinking, ToolCalls: r.ToolCalls},
 				Done:      r.Done,
 				Metrics: api.Metrics{
 					PromptEvalCount:    r.PromptEvalCount,
@@ -1962,54 +1683,14 @@ func (s *Server) ChatHandler(c *gin.Context) {
 				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
 			}
 
-			// TODO(drifkin): fold this as much as possibleinto the generic m.Config.Parser logic
 			if useHarmony {
-				content, thinking, toolContent := harmonyMessageHandler.AddContent(r.Content, harmonyToolParser)
-				res.Message.Content = content
-				res.Message.Thinking = thinking
-				harmonyToolParser.Add(toolContent)
-
-				if r.Done {
-					toolName, toolContent := harmonyToolParser.Drain()
-					if toolName != nil {
-						*toolName = strings.TrimPrefix(*toolName, "functions.")
-						*toolName = harmonyMessageHandler.FunctionNameMap.OriginalFromConverted(*toolName)
-						var args api.ToolCallFunctionArguments
-						if err := json.Unmarshal([]byte(toolContent), &args); err != nil {
-							errStr := fmt.Sprintf("error parsing tool call: raw='%s', err=%s", toolContent, err.Error())
-							ch <- gin.H{"error": errStr}
-							return
-						}
-						res.Message.ToolCalls = []api.ToolCall{{Function: api.ToolCallFunction{Name: *toolName, Arguments: args}}}
-					}
+				for i, tool := range res.Message.ToolCalls {
+					res.Message.ToolCalls[i].Function.Name = functionNameMap.OriginalFromConverted(tool.Function.Name)
 				}
-
 				// only send messages with meaningful content (empty messages confuse clients)
 				if res.Message.Content != "" || res.Message.Thinking != "" || len(res.Message.ToolCalls) > 0 || res.Done {
 					ch <- res
 				}
-
-				return
-			} else if builtinParser != nil {
-				slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser input", "parser", m.Config.Parser, "content", r.Content)
-
-				content, thinking, toolCalls, err := builtinParser.Add(r.Content, req.Tools)
-				if err != nil {
-					ch <- gin.H{"error": err.Error()}
-					return
-				}
-
-				res.Message.Content = content
-				res.Message.Thinking = thinking
-				res.Message.ToolCalls = toolCalls
-
-				if res.Message.Content != "" || res.Message.Thinking != "" || len(res.Message.ToolCalls) > 0 || r.Done {
-					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser output", "parser", m.Config.Parser, "content", content, "thinking", thinking, "toolCalls", toolCalls, "done", r.Done)
-					ch <- res
-				} else {
-					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser empty output", "parser", m.Config.Parser)
-				}
-
 				return
 			}
 

server/routes_create_test.go

@@ -11,7 +11,6 @@ import (
 	"net/http/httptest"
 	"os"
 	"path/filepath"
-	"reflect"
 	"slices"
 	"strings"
 	"testing"
@@ -21,7 +20,6 @@ import (
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/fs/ggml"
-	"github.com/ollama/ollama/types/model"
 )
 
 var stream bool = false
@@ -617,78 +615,6 @@ func TestCreateTemplateSystem(t *testing.T) {
 	})
 }
 
-func TestCreateAndShowRemoteModel(t *testing.T) {
-	gin.SetMode(gin.TestMode)
-
-	var s Server
-
-	w := createRequest(t, s.CreateHandler, api.CreateRequest{
-		Model:      "test",
-		From:       "bob",
-		RemoteHost: "https://ollama.com",
-		Info: map[string]any{
-			"capabilities":       []string{"completion", "tools", "thinking"},
-			"model_family":       "gptoss",
-			"context_length":     131072,
-			"embedding_length":   2880,
-			"quantization_level": "MXFP4",
-			"parameter_size":     "20.9B",
-		},
-		Stream: &stream,
-	})
-
-	if w.Code != http.StatusOK {
-		t.Fatalf("exected status code 200, actual %d", w.Code)
-	}
-
-	w = createRequest(t, s.ShowHandler, api.ShowRequest{Model: "test"})
-	if w.Code != http.StatusOK {
-		t.Fatalf("exected status code 200, actual %d", w.Code)
-	}
-
-	var resp api.ShowResponse
-	if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
-		t.Fatal(err)
-	}
-
-	expectedDetails := api.ModelDetails{
-		ParentModel:       "",
-		Format:            "",
-		Family:            "gptoss",
-		Families:          []string{"gptoss"},
-		ParameterSize:     "20.9B",
-		QuantizationLevel: "MXFP4",
-	}
-
-	if !reflect.DeepEqual(resp.Details, expectedDetails) {
-		t.Errorf("model details: expected %#v, actual %#v", expectedDetails, resp.Details)
-	}
-
-	expectedCaps := []model.Capability{
-		model.Capability("completion"),
-		model.Capability("tools"),
-		model.Capability("thinking"),
-	}
-
-	if !slices.Equal(resp.Capabilities, expectedCaps) {
-		t.Errorf("capabilities: expected %#v, actual %#v", expectedCaps, resp.Capabilities)
-	}
-
-	v, ok := resp.ModelInfo["gptoss.context_length"]
-	ctxlen := v.(float64)
-	if !ok || int(ctxlen) != 131072 {
-		t.Errorf("context len: expected %d, actual %d", 131072, int(ctxlen))
-	}
-
-	v, ok = resp.ModelInfo["gptoss.embedding_length"]
-	embedlen := v.(float64)
-	if !ok || int(embedlen) != 2880 {
-		t.Errorf("embed len: expected %d, actual %d", 2880, int(embedlen))
-	}
-
-	fmt.Printf("resp = %#v\n", resp)
-}
-
 func TestCreateLicenses(t *testing.T) {
 	gin.SetMode(gin.TestMode)
 

server/routes_debug_test.go

@@ -180,7 +180,7 @@ func TestGenerateDebugRenderOnly(t *testing.T) {
 						t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String())
 					}
 
-					var response api.GenerateResponse
+					var response api.DebugTemplateResponse
 					if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil {
 						t.Fatalf("failed to unmarshal response: %v", err)
 					}
@@ -385,7 +385,7 @@ func TestChatDebugRenderOnly(t *testing.T) {
 						t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String())
 					}
 
-					var response api.ChatResponse
+					var response api.DebugTemplateResponse
 					if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil {
 						t.Fatalf("failed to unmarshal response: %v", err)
 					}

server/routes_harmony_streaming_test.go

@@ -7,7 +7,6 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
-	"net/http"
 	"strings"
 	"testing"
 	"time"
@@ -118,7 +117,7 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 			name: "content streams as it arrives",
 			steps: []step{
 				{
-					input:       llm.CompletionResponse{Content: "<|message|>Hello", Done: false},
+					input:       llm.CompletionResponse{Content: "Hello", Done: false},
 					wantContent: "Hello",
 				},
 				{
@@ -126,7 +125,7 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 					wantContent: ", world",
 				},
 				{
-					input:       llm.CompletionResponse{Content: "!<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
+					input:       llm.CompletionResponse{Content: "!", Done: true, DoneReason: llm.DoneReasonStop},
 					wantContent: "!",
 				},
 			},
@@ -135,20 +134,15 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 			name: "thinking streams separately from content",
 			steps: []step{
 				{
-					input:        llm.CompletionResponse{Content: "<|channel|>analysis<|message|>Thinking...", Done: false},
+					input:        llm.CompletionResponse{Thinking: "Thinking...", Done: false},
 					wantThinking: "Thinking...",
 				},
 				{
-					input: llm.CompletionResponse{Content: "<|end|>", Done: false},
-					// No output expected - just closes the analysis message and resets state to normal
+					input:       llm.CompletionResponse{Content: "Answer", Done: false},
+					wantContent: "Answer",
 				},
 				{
-					input:       llm.CompletionResponse{Content: "<|start|>assistant<|message|>Answer", Done: false},
-					wantContent: "Answer", // After message end, state is reset to normal
-				},
-				{
-					input: llm.CompletionResponse{Content: "<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
-					// No output expected - just closes the assistant message
+					input: llm.CompletionResponse{Done: true, DoneReason: llm.DoneReasonStop},
 				},
 			},
 		},
@@ -156,24 +150,16 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 			name: "partial tags buffer until complete",
 			steps: []step{
 				{
-					input: llm.CompletionResponse{Content: "<|chan", Done: false},
-					// No output - partial tag
-				},
-				{
-					input: llm.CompletionResponse{Content: "nel|>analysis<|mess", Done: false},
-					// No output - still building tags
-				},
-				{
-					input:        llm.CompletionResponse{Content: "age|>Deep ", Done: false},
+					input:        llm.CompletionResponse{Thinking: "Deep ", Done: false},
 					wantThinking: "Deep ",
 				},
 				{
-					input:        llm.CompletionResponse{Content: "thought<|end|>", Done: false},
+					input:        llm.CompletionResponse{Thinking: "thought", Done: false},
 					wantThinking: "thought",
 				},
 				{
-					input:       llm.CompletionResponse{Content: "<|start|>assistant<|message|>Done<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
-					wantContent: "Done", // After message end, state is reset to normal
+					input:       llm.CompletionResponse{Content: "Done", Done: true, DoneReason: llm.DoneReasonStop},
+					wantContent: "Done",
 				},
 			},
 		},
@@ -181,7 +167,7 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 			name: "simple assistant after analysis",
 			steps: []step{
 				{
-					input:        llm.CompletionResponse{Content: "<|channel|>analysis<|message|>Think<|end|><|start|>assistant<|message|>Answer<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
+					input:        llm.CompletionResponse{Thinking: "Think", Content: "Answer", Done: true, DoneReason: llm.DoneReasonStop},
 					wantContent:  "Answer",
 					wantThinking: "Think",
 				},
@@ -191,7 +177,7 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 			name: "tool call parsed and returned correctly",
 			steps: []step{
 				{
-					input:       llm.CompletionResponse{Content: "<|channel|>commentary to=functions.get_weather<|message|>{\"location\":\"San Francisco\"}<|end|><|start|>assistant<|message|>The weather is sunny<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
+					input:       llm.CompletionResponse{Content: "The weather is sunny", ToolCalls: []api.ToolCall{{Function: api.ToolCallFunction{Name: "get_weather", Arguments: api.ToolCallFunctionArguments{"location": "San Francisco"}}}}, Done: true, DoneReason: llm.DoneReasonStop},
 					wantContent: "The weather is sunny",
 					wantToolCalls: []api.ToolCall{
 						{
@@ -210,15 +196,10 @@ func TestChatHarmonyParserStreamingRealtime(t *testing.T) {
 			name: "tool call with streaming JSON across chunks",
 			steps: []step{
 				{
-					input: llm.CompletionResponse{Content: "<|channel|>commentary to=functions.calculate<|message|>{\"expr", Done: false},
-					// No output yet - incomplete JSON
+					input: llm.CompletionResponse{Done: false},
 				},
 				{
-					input: llm.CompletionResponse{Content: "ession\":\"2+", Done: false},
-					// Still no output - incomplete JSON
-				},
-				{
-					input: llm.CompletionResponse{Content: "2\"}", Done: true},
+					input: llm.CompletionResponse{ToolCalls: []api.ToolCall{{Function: api.ToolCallFunction{Name: "calculate", Arguments: api.ToolCallFunctionArguments{"expression": "2+2"}}}}, Done: true},
 					wantToolCalls: []api.ToolCall{
 						{
 							Function: api.ToolCallFunction{
@@ -400,9 +381,9 @@ func TestChatHarmonyParserStreamingSimple(t *testing.T) {
 	gin.SetMode(gin.TestMode)
 
 	mockResponses := []llm.CompletionResponse{
-		{Content: "<|message|>First ", Done: false},
+		{Content: "First ", Done: false},
 		{Content: "chunk ", Done: false},
-		{Content: "here<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
+		{Content: "here", Done: true, DoneReason: llm.DoneReasonStop},
 	}
 
 	mock := mockRunner{
@@ -507,189 +488,3 @@ func TestChatHarmonyParserStreamingSimple(t *testing.T) {
 		t.Errorf("expected at least 2 content chunks for streaming, got %d", contentChunks)
 	}
 }
-
-func TestChatHarmonyParserStreaming(t *testing.T) {
-	gin.SetMode(gin.TestMode)
-
-	type expectedChunk struct {
-		afterResponse int    // Which mock response this chunk should appear after
-		content       string // Expected content in this chunk
-		thinking      string // Expected thinking in this chunk
-	}
-
-	testCases := []struct {
-		name           string
-		mockResponses  []llm.CompletionResponse
-		expectedChunks []expectedChunk
-		wantContent    string
-		wantThinking   string
-	}{
-		{
-			name: "simple message without thinking",
-			mockResponses: []llm.CompletionResponse{
-				{Content: "<|start|>assistant<|message|>Hello, ", Done: false},
-				{Content: "how can I help?", Done: false},
-				{Content: "<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
-			},
-			expectedChunks: []expectedChunk{
-				{afterResponse: 1, content: "Hello, "},
-				{afterResponse: 2, content: "how can I help?"},
-			},
-			wantContent: "Hello, how can I help?",
-		},
-		{
-			name: "message with analysis channel for thinking",
-			mockResponses: []llm.CompletionResponse{
-				{Content: "<|channel|>analysis<|message|>", Done: false},
-				{Content: "Let me think ", Done: false},
-				{Content: "about this problem...", Done: false},
-				{Content: "<|end|>", Done: false},
-				{Content: "<|start|>assistant<|message|>", Done: false},
-				{Content: "The answer ", Done: false},
-				{Content: "is 42", Done: false},
-				{Content: "<|end|>", Done: true, DoneReason: llm.DoneReasonStop},
-			},
-			expectedChunks: []expectedChunk{
-				{afterResponse: 2, thinking: "Let me think "},
-				{afterResponse: 3, thinking: "about this problem..."},
-				{afterResponse: 6, content: "The answer "},
-				{afterResponse: 7, content: "is 42"},
-			},
-			wantContent:  "The answer is 42",
-			wantThinking: "Let me think about this problem...",
-		},
-		{
-			name: "streaming with partial tags across boundaries",
-			mockResponses: []llm.CompletionResponse{
-				{Content: "<|chan", Done: false},
-				{Content: "nel|>analy", Done: false},
-				{Content: "sis<|mess", Done: false},
-				{Content: "age|>Think", Done: false},
-				{Content: "ing deeply...<|end|>", Done: false},
-				{Content: "<|start|>assi", Done: false},
-				{Content: "stant<|message|>Result ", Done: false},
-				{Content: "computed<|e", Done: false},
-				{Content: "nd|>", Done: true, DoneReason: llm.DoneReasonStop},
-			},
-			expectedChunks: []expectedChunk{
-				{afterResponse: 4, thinking: "Think"},
-				{afterResponse: 5, thinking: "ing deeply..."},
-				{afterResponse: 7, content: "Result "},
-				{afterResponse: 8, content: "computed"},
-			},
-			wantContent:  "Result computed",
-			wantThinking: "Thinking deeply...",
-		},
-	}
-
-	for _, tc := range testCases {
-		t.Run(tc.name, func(t *testing.T) {
-			// Channel to synchronize mock responses with chunk verification
-			responsesSent := make(chan int, len(tc.mockResponses))
-
-			mock := mockRunner{
-				CompletionFn: func(ctx context.Context, r llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
-					// Send mock responses one at a time, notifying when each is sent
-					for i, resp := range tc.mockResponses {
-						fn(resp)
-						responsesSent <- i + 1
-					}
-					close(responsesSent)
-					return nil
-				},
-			}
-
-			s := Server{
-				sched: &Scheduler{
-					pendingReqCh:  make(chan *LlmRequest, 1),
-					finishedReqCh: make(chan *LlmRequest, 1),
-					expiredCh:     make(chan *runnerRef, 1),
-					unloadedCh:    make(chan any, 1),
-					loaded:        make(map[string]*runnerRef),
-					newServerFn:   newMockServer(&mock),
-					getGpuFn:      discover.GetGPUInfo,
-					getCpuFn:      discover.GetCPUInfo,
-					reschedDelay:  250 * time.Millisecond,
-					loadFn: func(req *LlmRequest, _ *ggml.GGML, _ discover.GpuInfoList, _ bool) bool {
-						req.successCh <- &runnerRef{
-							llama: &mock,
-						}
-						return false
-					},
-				},
-			}
-
-			go s.sched.Run(t.Context())
-
-			// Create a minimal model
-			_, digest := createHarmonyTestModel(t)
-
-			// Create model with passthrough template
-			stream := false
-			w := createRequest(t, s.CreateHandler, api.CreateRequest{
-				Model:    "harmony-test",
-				Files:    map[string]string{"file.gguf": digest},
-				Template: `<|start|><|end|>{{ with .Tools }}{{ end }}{{ .Prompt }}`,
-				Stream:   &stream,
-			})
-
-			if w.Code != http.StatusOK {
-				t.Fatalf("failed to create model: %d", w.Code)
-			}
-
-			// Test chat endpoint with streaming
-			streamTrue := true
-			w = createRequest(t, s.ChatHandler, api.ChatRequest{
-				Model:    "harmony-test",
-				Messages: []api.Message{{Role: "user", Content: "Hello"}},
-				Stream:   &streamTrue,
-				Tools:    getTestTools(),
-			})
-
-			if w.Code != http.StatusOK {
-				t.Fatalf("chat request failed: %d - %s", w.Code, w.Body.String())
-			}
-
-			// Parse streaming response
-			var chunks []api.ChatResponse
-			var content, thinking strings.Builder
-
-			decoder := json.NewDecoder(w.Body)
-			for decoder.More() {
-				var chunk api.ChatResponse
-				if err := decoder.Decode(&chunk); err != nil {
-					t.Fatalf("failed to decode chunk: %v", err)
-				}
-				chunks = append(chunks, chunk)
-
-				// Accumulate content and thinking from each chunk
-				content.WriteString(chunk.Message.Content)
-				thinking.WriteString(chunk.Message.Thinking)
-
-				// Debug output
-				t.Logf("Chunk %d: content=%q thinking=%q done=%v", len(chunks), chunk.Message.Content, chunk.Message.Thinking, chunk.Done)
-			}
-
-			// Verify we got streaming chunks
-			if len(chunks) == 0 {
-				t.Fatal("expected streaming chunks, got none")
-			}
-
-			gotContent := content.String()
-			gotThinking := thinking.String()
-
-			if gotContent != tc.wantContent {
-				t.Errorf("content mismatch: got %q, want %q", gotContent, tc.wantContent)
-			}
-			if gotThinking != tc.wantThinking {
-				t.Errorf("thinking mismatch: got %q, want %q", gotThinking, tc.wantThinking)
-			}
-
-			// Verify last chunk has done=true
-			lastChunk := chunks[len(chunks)-1]
-			if !lastChunk.Done {
-				t.Error("expected last chunk to have done=true")
-			}
-		})
-	}
-}

server/routes_test.go

@@ -126,15 +126,7 @@ func TestRoutes(t *testing.T) {
 			t.Fatalf("failed to create model: %v", err)
 		}
 
-		config := &ConfigV2{
-			OS:           "linux",
-			Architecture: "amd64",
-			RootFS: RootFS{
-				Type: "layers",
-			},
-		}
-
-		if err := createModel(r, modelName, baseLayers, config, fn); err != nil {
+		if err := createModel(r, modelName, baseLayers, fn); err != nil {
 			t.Fatal(err)
 		}
 	}

server/sched.go

@@ -382,7 +382,10 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
 // load creates a new model based on req and loads it. If requireFull is true then the model must be loaded fully onto GPUs
 // (if any). Returns whether the scheduler needs to evict a model to make this one fit.
 func (s *Scheduler) load(req *LlmRequest, f *ggml.GGML, gpus discover.GpuInfoList, requireFull bool) bool {
-	numParallel := max(int(envconfig.NumParallel()), 1)
+	numParallel := int(envconfig.NumParallel())
+	if numParallel < 1 {
+		numParallel = 1
+	}
 
 	// Embedding models should always be loaded with parallel=1
 	if req.model.CheckCapabilities(model.CapabilityCompletion) != nil {