cmd: add eval command for lightweight model evals

.gitattributes

@@ -19,8 +19,6 @@ ml/backend/**/*.comp linguist-vendored
 ml/backend/**/*.glsl linguist-vendored
 ml/backend/**/CMakeLists.txt linguist-vendored
 
-app/webview linguist-vendored
-
 llama/build-info.cpp linguist-generated
 ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.s linguist-generated
 

.github/ISSUE_TEMPLATE/10_bug_report.yml

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

.github/workflows/release.yaml

@@ -16,15 +16,13 @@ jobs:
     outputs:
       GOFLAGS: ${{ steps.goflags.outputs.GOFLAGS }}
       VERSION: ${{ steps.goflags.outputs.VERSION }}
-      vendorsha: ${{ steps.changes.outputs.vendorsha }}
     steps:
       - uses: actions/checkout@v4
       - name: Set environment
         id: goflags
         run: |
-          echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${GITHUB_REF_NAME#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" | tee -a $GITHUB_OUTPUT
-          echo VERSION="${GITHUB_REF_NAME#v}" | tee -a $GITHUB_OUTPUT
-          echo vendorsha=$(make -f Makefile.sync print-base) | tee -a $GITHUB_OUTPUT
+          echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${GITHUB_REF_NAME#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_OUTPUT
+          echo VERSION="${GITHUB_REF_NAME#v}" >>$GITHUB_OUTPUT
 
   darwin-build:
     runs-on: macos-14-xlarge
@@ -55,9 +53,6 @@ jobs:
       - uses: actions/setup-go@v5
         with:
           go-version-file: go.mod
-          cache-dependency-path: |
-            go.sum
-            Makefile.sync
       - run: |
           ./scripts/build_darwin.sh
       - name: Log build results
@@ -68,7 +63,6 @@ jobs:
           name: bundles-darwin
           path: |
             dist/*.tgz
-            dist/*.tar.zst
             dist/*.zip
             dist/*.dmg
 
@@ -191,7 +185,7 @@ jobs:
       - uses: actions/cache@v4
         with:
           path: ${{ github.workspace }}\.ccache
-          key: ccache-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}-${{ needs.setup-environment.outputs.vendorsha }}
+          key: ccache-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}
       - name: Build target "${{ matrix.preset }}"
         run: |
           Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
@@ -255,9 +249,6 @@ jobs:
       - uses: actions/setup-go@v5
         with:
           go-version-file: go.mod
-          cache-dependency-path: |
-            go.sum
-            Makefile.sync
       - name: Verify gcc is actually clang
         run: |
           $ErrorActionPreference='Continue'
@@ -311,9 +302,6 @@ jobs:
       - uses: actions/setup-go@v5
         with:
           go-version-file: go.mod
-          cache-dependency-path: |
-            go.sum
-            Makefile.sync
       - uses: actions/download-artifact@v4
         with:
           pattern: depends-windows*
@@ -372,17 +360,13 @@ jobs:
           outputs: type=local,dest=dist/${{ matrix.os }}-${{ matrix.arch }}
           cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
           cache-to: type=inline
-      - name: Deduplicate CUDA libraries
-        run: |
-          ./scripts/deduplicate_cuda_libs.sh dist/${{ matrix.os }}-${{ matrix.arch }}
       - run: |
           for COMPONENT in bin/* lib/ollama/*; do
             case "$COMPONENT" in
-              bin/ollama*)               echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
+              bin/ollama)                echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
               lib/ollama/*.so*)          echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
               lib/ollama/cuda_v*)        echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
               lib/ollama/vulkan*)        echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/mlx*)           echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
               lib/ollama/cuda_jetpack5)  echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
               lib/ollama/cuda_jetpack6)  echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
               lib/ollama/rocm)           echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;
@@ -397,13 +381,13 @@ jobs:
           done
       - run: |
           for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in; do
-            tar c -C dist/${{ matrix.os }}-${{ matrix.arch }} -T $ARCHIVE --owner 0 --group 0 | zstd --ultra -22 -T0 >$(basename ${ARCHIVE//.*/}.tar.zst);
+            tar c -C dist/${{ matrix.os }}-${{ matrix.arch }} -T $ARCHIVE --owner 0 --group 0 | pigz -9vc >$(basename ${ARCHIVE//.*/}.tgz);
           done
       - uses: actions/upload-artifact@v4
         with:
           name: bundles-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.target }}
           path: |
-            *.tar.zst
+            *.tgz
 
   # Build each Docker variant (OS, arch, and flavor) separately. Using QEMU is unreliable and slower.
   docker-build-push:
@@ -536,7 +520,7 @@ jobs:
       - name: Upload release artifacts
         run: |
           pids=()
-          for payload in dist/*.txt dist/*.zip dist/*.tgz dist/*.tar.zst dist/*.exe dist/*.dmg ; do
+          for payload in dist/*.txt dist/*.zip dist/*.tgz dist/*.exe dist/*.dmg ; do
             echo "Uploading $payload"
             gh release upload ${GITHUB_REF_NAME} $payload --clobber &
             pids[$!]=$!

.github/workflows/test.yaml

@@ -22,7 +22,6 @@ jobs:
     runs-on: ubuntu-latest
     outputs:
       changed: ${{ steps.changes.outputs.changed }}
-      vendorsha: ${{ steps.changes.outputs.vendorsha }}
     steps:
       - uses: actions/checkout@v4
         with:
@@ -38,7 +37,6 @@ jobs:
           }
 
           echo changed=$(changed 'llama/llama.cpp/**/*' 'ml/backend/ggml/ggml/**/*') | tee -a $GITHUB_OUTPUT
-          echo vendorsha=$(make -f Makefile.sync print-base) | tee -a $GITHUB_OUTPUT
 
   linux:
     needs: [changes]
@@ -85,7 +83,7 @@ jobs:
       - uses: actions/cache@v4
         with:
           path: /github/home/.cache/ccache
-          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}-${{ needs.changes.outputs.vendorsha }}
+          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}
       - run: |
           cmake --preset ${{ matrix.preset }} ${{ matrix.flags }}
           cmake --build --preset ${{ matrix.preset }} --parallel
@@ -180,7 +178,7 @@ jobs:
       - uses: actions/cache@v4
         with:
           path: ${{ github.workspace }}\.ccache
-          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}-${{ needs.changes.outputs.vendorsha }}
+          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}
       - 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'
@@ -208,9 +206,6 @@ jobs:
       - uses: actions/setup-go@v5
         with:
           go-version-file: 'go.mod'
-          cache-dependency-path: |
-            go.sum
-            Makefile.sync
       - uses: actions/setup-node@v4
         with:
           node-version: '20'

.golangci.yaml

@@ -1,51 +1,77 @@
 version: "2"
 linters:
+  default: none
   enable:
     - asasalint
     - bidichk
     - bodyclose
     - containedctx
+    - copyloopvar
+    - errcheck
+    - errorlint
+    - exptostd
     - gocheckcompilerdirectives
+    - gocritic
+    - govet
+    - ineffassign
     - intrange
     - makezero
     - misspell
+    - modernize
     - nilerr
+    - nilnil
     - nolintlint
     - nosprintfhostport
+    - perfsprint
+    - prealloc
+    - sloglint
+    - staticcheck
     - unconvert
+    - unused
+    - usestdlibvars
     - usetesting
     - wastedassign
     - whitespace
-  disable:
-    - errcheck
-    - usestdlibvars
   settings:
-    govet:
-      disable:
-        - unusedresult
+    errcheck:
+      exclude-functions:
+        - fmt.Fprintf
+    perfsprint:
+      strconcat: false
+      concat-loop: false
     staticcheck:
       checks:
         - all
-        - -QF* # disable quick fix suggestions
+        # Using a deprecated function, variable, constant or field.
+        # https://staticcheck.dev/docs/checks/#SA1019
         - -SA1019
-        - -ST1000 # package comment format
-        - -ST1003 # underscores in package names
-        - -ST1005 # error strings should not be capitalized
-        - -ST1012 # error var naming (ErrFoo)
-        - -ST1016 # receiver name consistency
-        - -ST1020 # comment on exported function format
-        - -ST1021 # comment on exported type format
-        - -ST1022 # comment on exported var format
-        - -ST1023 # omit type from declaration
-severity:
-  default: error
-  rules:
-    - linters:
-        - gofmt
-        - goimports
-        - intrange
-      severity: info
+        # Incorrect or missing package comment.
+        # https://staticcheck.dev/docs/checks/#ST1000
+        - -ST1000
+        # Poorly chosen identifier.
+        # https://staticcheck.dev/docs/checks/#ST1003
+        - -ST1003
+        # The documentation of an exported function should start with the function's name.
+        # https://staticcheck.dev/docs/checks/#ST1020
+        - -ST1020
+        # The documentation of an exported type should start with type's name.
+        # https://staticcheck.dev/docs/checks/#ST1021
+        - -ST1021
+        # The documentation of an exported variable or constant should start with variable's name.
+        # https://staticcheck.dev/docs/checks/#ST1022
+        - -ST1022
+    usestdlibvars:
+      http-method: false
+      http-status-code: false
+
 formatters:
   enable:
+    - gci
     - gofmt
     - gofumpt
+  settings:
+    gci:
+      sections:
+        - standard
+        - default
+        - localmodule

CMakeLists.txt

@@ -2,22 +2,6 @@ cmake_minimum_required(VERSION 3.21)
 
 project(Ollama C CXX)
 
-# Handle cross-compilation on macOS: when CMAKE_OSX_ARCHITECTURES is set to a
-# single architecture different from the host, override CMAKE_SYSTEM_PROCESSOR
-# to match. This is necessary because CMAKE_SYSTEM_PROCESSOR defaults to the
-# host architecture, but downstream projects (like MLX) use it to detect the
-# target architecture.
-if(CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_OSX_ARCHITECTURES MATCHES ";")
-    # Single architecture specified
-    if(CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" AND NOT CMAKE_SYSTEM_PROCESSOR STREQUAL "x86_64")
-        message(STATUS "Cross-compiling for x86_64: overriding CMAKE_SYSTEM_PROCESSOR from ${CMAKE_SYSTEM_PROCESSOR} to x86_64")
-        set(CMAKE_SYSTEM_PROCESSOR "x86_64")
-    elseif(CMAKE_OSX_ARCHITECTURES STREQUAL "arm64" AND NOT CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
-        message(STATUS "Cross-compiling for arm64: overriding CMAKE_SYSTEM_PROCESSOR from ${CMAKE_SYSTEM_PROCESSOR} to arm64")
-        set(CMAKE_SYSTEM_PROCESSOR "arm64")
-    endif()
-endif()
-
 include(CheckLanguage)
 include(GNUInstallDirs)
 
@@ -28,7 +12,7 @@ set(BUILD_SHARED_LIBS ON)
 
 set(CMAKE_CXX_STANDARD 17)
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
-set(CMAKE_CXX_EXTENSIONS ON) # Recent versions of MLX Requires gnu++17 extensions to compile properly
+set(CMAKE_CXX_EXTENSIONS OFF)
 
 set(GGML_BUILD ON)
 set(GGML_SHARED ON)
@@ -48,10 +32,9 @@ if((CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_OSX_ARCHITECTURES MATCHES "arm64")
     set(GGML_CPU_ALL_VARIANTS ON)
 endif()
 
-if(APPLE)
+if (CMAKE_OSX_ARCHITECTURES MATCHES "x86_64")
     set(CMAKE_BUILD_RPATH "@loader_path")
     set(CMAKE_INSTALL_RPATH "@loader_path")
-    set(CMAKE_BUILD_WITH_INSTALL_RPATH ON)
 endif()
 
 set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
@@ -71,13 +54,6 @@ include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cp
 
 add_compile_definitions(NDEBUG GGML_VERSION=0x0 GGML_COMMIT=0x0)
 
-# Define GGML version variables for shared library SOVERSION
-# These are required by ggml/src/CMakeLists.txt for proper library versioning
-set(GGML_VERSION_MAJOR 0)
-set(GGML_VERSION_MINOR 0)
-set(GGML_VERSION_PATCH 0)
-set(GGML_VERSION "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}")
-
 set(GGML_CPU ON)
 add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
 set_property(TARGET ggml PROPERTY EXCLUDE_FROM_ALL TRUE)
@@ -164,56 +140,14 @@ if(CMAKE_HIP_COMPILER)
     endif()
 endif()
 
-if(NOT APPLE)
-    find_package(Vulkan)
-    if(Vulkan_FOUND)
-        add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-vulkan)
-        install(TARGETS ggml-vulkan
-            RUNTIME_DEPENDENCIES
-                PRE_INCLUDE_REGEXES vulkan
-                PRE_EXCLUDE_REGEXES ".*"
-            RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT Vulkan
-            LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT Vulkan
-        )
-    endif()
-endif()
-
-option(MLX_ENGINE "Enable MLX backend" OFF)
-
-if(MLX_ENGINE)
-    message(STATUS "Setting up MLX (this takes a while...)")
-    add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/x/ml/backend/mlx)
-
-    # Find CUDA toolkit if MLX is built with CUDA support
-    find_package(CUDAToolkit)
-
-    install(TARGETS mlx mlxc
+find_package(Vulkan)
+if(Vulkan_FOUND)
+    add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-vulkan)
+    install(TARGETS ggml-vulkan
         RUNTIME_DEPENDENCIES
-            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
-            PRE_INCLUDE_REGEXES cublas cublasLt cudart nvrtc nvrtc-builtins cudnn nccl openblas gfortran
+            PRE_INCLUDE_REGEXES vulkan
             PRE_EXCLUDE_REGEXES ".*"
-        RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
-        LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
-        FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
+        RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT Vulkan
+        LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT Vulkan
     )
-
-    # Install the Metal library for macOS arm64 (must be colocated with the binary)
-    # Metal backend is only built for arm64, not x86_64
-    if(APPLE AND CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
-        install(FILES ${CMAKE_BINARY_DIR}/_deps/mlx-build/mlx/backend/metal/kernels/mlx.metallib
-            DESTINATION ${OLLAMA_INSTALL_DIR}
-            COMPONENT MLX)
-    endif()
-
-    # Manually install cudart and cublas since they might not be picked up as direct dependencies
-    if(CUDAToolkit_FOUND)
-        file(GLOB CUDART_LIBS
-            "${CUDAToolkit_LIBRARY_DIR}/libcudart.so*"
-            "${CUDAToolkit_LIBRARY_DIR}/libcublas.so*")
-        if(CUDART_LIBS)
-            install(FILES ${CUDART_LIBS}
-                DESTINATION ${OLLAMA_INSTALL_DIR}
-                COMPONENT MLX)
-        endif()
-    endif()
-endif()
+endif()

CMakePresets.json

@@ -41,7 +41,7 @@
       "inherits": [ "CUDA" ],
       "cacheVariables": {
         "CMAKE_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;103-virtual;110-virtual;120-virtual;121-virtual",
-        "CMAKE_CUDA_FLAGS": "-t 4",
+        "CMAKE_CUDA_FLAGS": "-t 2",
         "OLLAMA_RUNNER_DIR": "cuda_v13"
       }
     },
@@ -83,28 +83,6 @@
       "cacheVariables": {
         "OLLAMA_RUNNER_DIR": "vulkan"
       }
-    },
-    {
-      "name": "MLX",
-      "inherits": [ "Default" ],
-      "cacheVariables": {
-        "MLX_ENGINE": "ON",
-        "OLLAMA_RUNNER_DIR": "mlx"
-      }
-    },
-    {
-      "name": "MLX CUDA 12",
-      "inherits": [ "MLX", "CUDA 12" ],
-      "cacheVariables": {
-        "OLLAMA_RUNNER_DIR": "mlx_cuda_v12"
-      }
-    },
-    {
-      "name": "MLX CUDA 13",
-      "inherits": [ "MLX", "CUDA 13" ],
-      "cacheVariables": {
-        "OLLAMA_RUNNER_DIR": "mlx_cuda_v13"
-      }
     }
   ],
   "buildPresets": [
@@ -162,21 +140,6 @@
       "name": "Vulkan",
       "targets": [ "ggml-vulkan" ],
       "configurePreset": "Vulkan"
-    },
-    {
-      "name": "MLX",
-      "targets": [ "mlx", "mlxc" ],
-      "configurePreset": "MLX"
-    },
-    {
-      "name": "MLX CUDA 12",
-      "targets": [ "mlx", "mlxc" ],
-      "configurePreset": "MLX CUDA 12"
-    },
-    {
-      "name": "MLX CUDA 13",
-      "targets": [ "mlx", "mlxc" ],
-      "configurePreset": "MLX CUDA 13"
     }
   ]
 }

Dockerfile

@@ -131,39 +131,8 @@ COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
 RUN --mount=type=cache,target=/root/.ccache \
     cmake --preset 'Vulkan' \
         && cmake --build --parallel --preset 'Vulkan' \
-        && cmake --install build --component Vulkan --strip --parallel 8
+        && cmake --install build --component Vulkan --strip --parallel 8 
 
-FROM base AS mlx
-ARG CUDA13VERSION=13.0
-RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-} \
-    && dnf install -y openblas-devel lapack-devel \
-    && dnf install -y libcudnn9-cuda-13 libcudnn9-devel-cuda-13 \
-    && dnf install -y libnccl libnccl-devel
-ENV PATH=/usr/local/cuda-13/bin:$PATH
-ENV BLAS_INCLUDE_DIRS=/usr/include/openblas
-ENV LAPACK_INCLUDE_DIRS=/usr/include/openblas
-ENV CGO_LDFLAGS="-L/usr/local/cuda-13/lib64 -L/usr/local/cuda-13/targets/x86_64-linux/lib/stubs"
-ARG PARALLEL
-WORKDIR /go/src/github.com/ollama/ollama
-COPY CMakeLists.txt CMakePresets.json .
-COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-COPY x/ml/backend/mlx x/ml/backend/mlx
-COPY go.mod go.sum .
-RUN curl -fsSL https://golang.org/dl/go$(awk '/^go/ { print $2 }' go.mod).linux-$(case $(uname -m) in x86_64) echo amd64 ;; aarch64) echo arm64 ;; esac).tar.gz | tar xz -C /usr/local
-ENV PATH=/usr/local/go/bin:$PATH
-RUN go mod download
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'MLX CUDA 13' -DBLAS_INCLUDE_DIRS=/usr/include/openblas -DLAPACK_INCLUDE_DIRS=/usr/include/openblas \
-        && cmake --build --parallel ${PARALLEL} --preset 'MLX CUDA 13' \
-        && cmake --install build --component MLX --strip --parallel ${PARALLEL}
-COPY . .
-ARG GOFLAGS="'-ldflags=-w -s'"
-ENV CGO_ENABLED=1
-ARG CGO_CFLAGS
-ARG CGO_CXXFLAGS
-RUN mkdir -p dist/bin
-RUN --mount=type=cache,target=/root/.cache/go-build \
-    go build -tags mlx -trimpath -buildmode=pie -o dist/bin/ollama-mlx .
 
 FROM base AS build
 WORKDIR /go/src/github.com/ollama/ollama
@@ -184,8 +153,6 @@ FROM --platform=linux/amd64 scratch AS amd64
 COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
 COPY --from=cuda-13 dist/lib/ollama /lib/ollama/
 COPY --from=vulkan  dist/lib/ollama  /lib/ollama/
-COPY --from=mlx     /go/src/github.com/ollama/ollama/dist/lib/ollama /lib/ollama/
-COPY --from=mlx     /go/src/github.com/ollama/ollama/dist/bin/ /bin/
 
 FROM --platform=linux/arm64 scratch AS arm64
 # COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
@@ -204,7 +171,7 @@ COPY --from=build /bin/ollama /bin/ollama
 
 FROM ubuntu:24.04
 RUN apt-get update \
-    && apt-get install -y ca-certificates libvulkan1 libopenblas0 \
+    && apt-get install -y ca-certificates libvulkan1 \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 COPY --from=archive /bin /usr/bin

Makefile.sync

@@ -1,6 +1,6 @@
 UPSTREAM=https://github.com/ggml-org/llama.cpp.git
 WORKDIR=llama/vendor
-FETCH_HEAD=ec98e2002
+FETCH_HEAD=3cfa9c3f125763305b4226bc032f1954f08990dc
 
 .PHONY: help
 help:
@@ -57,7 +57,7 @@ checkout: $(WORKDIR)
 $(WORKDIR):
 	git clone $(UPSTREAM) $(WORKDIR)
 
-.PHONY: format-patches
+.PHONE: format-patches
 format-patches: llama/patches
 	git -C $(WORKDIR) format-patch \
 		--no-signature \
@@ -66,11 +66,7 @@ format-patches: llama/patches
 		-o $(realpath $<) \
 		$(FETCH_HEAD)
 
-.PHONY: clean
+.PHONE: clean
 clean: checkout
 	@git -C $(WORKDIR) am --abort || true
 	$(RM) llama/patches/.*.patched
-
-.PHONY: print-base
-print-base:
-	@echo $(FETCH_HEAD)

README.md

@@ -290,7 +290,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 
 ### Web & Desktop
 
-- [Onyx](https://github.com/onyx-dot-app/onyx)
 - [Open WebUI](https://github.com/open-webui/open-webui)
 - [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat)
 - [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
@@ -556,7 +555,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Parakeet](https://github.com/parakeet-nest/parakeet) is a GoLang library, made to simplify the development of small generative AI applications with Ollama.
 - [Haverscript](https://github.com/andygill/haverscript) with [examples](https://github.com/andygill/haverscript/tree/main/examples)
 - [Ollama for Swift](https://github.com/mattt/ollama-swift)
-- [Swollama for Swift](https://github.com/guitaripod/Swollama) with [DocC](https://guitaripod.github.io/Swollama/documentation/swollama)
+- [Swollama for Swift](https://github.com/marcusziade/Swollama) with [DocC](https://marcusziade.github.io/Swollama/documentation/swollama/)
 - [GoLamify](https://github.com/prasad89/golamify)
 - [Ollama for Haskell](https://github.com/tusharad/ollama-haskell)
 - [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in a unified API)

anthropic/anthropic.go

@@ -1,778 +0,0 @@
-package anthropic
-
-import (
-	"crypto/rand"
-	"encoding/base64"
-	"encoding/json"
-	"errors"
-	"fmt"
-	"log/slog"
-	"net/http"
-	"strings"
-	"time"
-
-	"github.com/ollama/ollama/api"
-)
-
-// Error types matching Anthropic API
-type Error struct {
-	Type    string `json:"type"`
-	Message string `json:"message"`
-}
-
-type ErrorResponse struct {
-	Type      string `json:"type"` // always "error"
-	Error     Error  `json:"error"`
-	RequestID string `json:"request_id,omitempty"`
-}
-
-// NewError creates a new ErrorResponse with the appropriate error type based on HTTP status code
-func NewError(code int, message string) ErrorResponse {
-	var etype string
-	switch code {
-	case http.StatusBadRequest:
-		etype = "invalid_request_error"
-	case http.StatusUnauthorized:
-		etype = "authentication_error"
-	case http.StatusForbidden:
-		etype = "permission_error"
-	case http.StatusNotFound:
-		etype = "not_found_error"
-	case http.StatusTooManyRequests:
-		etype = "rate_limit_error"
-	case http.StatusServiceUnavailable, 529:
-		etype = "overloaded_error"
-	default:
-		etype = "api_error"
-	}
-
-	return ErrorResponse{
-		Type:      "error",
-		Error:     Error{Type: etype, Message: message},
-		RequestID: generateID("req"),
-	}
-}
-
-// Request types
-
-// MessagesRequest represents an Anthropic Messages API request
-type MessagesRequest struct {
-	Model         string          `json:"model"`
-	MaxTokens     int             `json:"max_tokens"`
-	Messages      []MessageParam  `json:"messages"`
-	System        any             `json:"system,omitempty"` // string or []ContentBlock
-	Stream        bool            `json:"stream,omitempty"`
-	Temperature   *float64        `json:"temperature,omitempty"`
-	TopP          *float64        `json:"top_p,omitempty"`
-	TopK          *int            `json:"top_k,omitempty"`
-	StopSequences []string        `json:"stop_sequences,omitempty"`
-	Tools         []Tool          `json:"tools,omitempty"`
-	ToolChoice    *ToolChoice     `json:"tool_choice,omitempty"`
-	Thinking      *ThinkingConfig `json:"thinking,omitempty"`
-	Metadata      *Metadata       `json:"metadata,omitempty"`
-}
-
-// MessageParam represents a message in the request
-type MessageParam struct {
-	Role    string `json:"role"`    // "user" or "assistant"
-	Content any    `json:"content"` // string or []ContentBlock
-}
-
-// ContentBlock represents a content block in a message.
-// Text and Thinking use pointers so they serialize as the field being present (even if empty)
-// only when set, which is required for SDK streaming accumulation.
-type ContentBlock struct {
-	Type string `json:"type"` // text, image, tool_use, tool_result, thinking
-
-	// For text blocks - pointer so field only appears when set (SDK requires it for accumulation)
-	Text *string `json:"text,omitempty"`
-
-	// For image blocks
-	Source *ImageSource `json:"source,omitempty"`
-
-	// For tool_use blocks
-	ID    string `json:"id,omitempty"`
-	Name  string `json:"name,omitempty"`
-	Input any    `json:"input,omitempty"`
-
-	// For tool_result blocks
-	ToolUseID string `json:"tool_use_id,omitempty"`
-	Content   any    `json:"content,omitempty"` // string or []ContentBlock
-	IsError   bool   `json:"is_error,omitempty"`
-
-	// For thinking blocks - pointer so field only appears when set (SDK requires it for accumulation)
-	Thinking  *string `json:"thinking,omitempty"`
-	Signature string  `json:"signature,omitempty"`
-}
-
-// ImageSource represents the source of an image
-type ImageSource struct {
-	Type      string `json:"type"` // "base64" or "url"
-	MediaType string `json:"media_type,omitempty"`
-	Data      string `json:"data,omitempty"`
-	URL       string `json:"url,omitempty"`
-}
-
-// Tool represents a tool definition
-type Tool struct {
-	Type        string          `json:"type,omitempty"` // "custom" for user-defined tools
-	Name        string          `json:"name"`
-	Description string          `json:"description,omitempty"`
-	InputSchema json.RawMessage `json:"input_schema,omitempty"`
-}
-
-// ToolChoice controls how the model uses tools
-type ToolChoice struct {
-	Type                   string `json:"type"` // "auto", "any", "tool", "none"
-	Name                   string `json:"name,omitempty"`
-	DisableParallelToolUse bool   `json:"disable_parallel_tool_use,omitempty"`
-}
-
-// ThinkingConfig controls extended thinking
-type ThinkingConfig struct {
-	Type         string `json:"type"` // "enabled" or "disabled"
-	BudgetTokens int    `json:"budget_tokens,omitempty"`
-}
-
-// Metadata for the request
-type Metadata struct {
-	UserID string `json:"user_id,omitempty"`
-}
-
-// Response types
-
-// MessagesResponse represents an Anthropic Messages API response
-type MessagesResponse struct {
-	ID           string         `json:"id"`
-	Type         string         `json:"type"` // "message"
-	Role         string         `json:"role"` // "assistant"
-	Model        string         `json:"model"`
-	Content      []ContentBlock `json:"content"`
-	StopReason   string         `json:"stop_reason,omitempty"`
-	StopSequence string         `json:"stop_sequence,omitempty"`
-	Usage        Usage          `json:"usage"`
-}
-
-// Usage contains token usage information
-type Usage struct {
-	InputTokens  int `json:"input_tokens"`
-	OutputTokens int `json:"output_tokens"`
-}
-
-// Streaming event types
-
-// MessageStartEvent is sent at the start of streaming
-type MessageStartEvent struct {
-	Type    string           `json:"type"` // "message_start"
-	Message MessagesResponse `json:"message"`
-}
-
-// ContentBlockStartEvent signals the start of a content block
-type ContentBlockStartEvent struct {
-	Type         string       `json:"type"` // "content_block_start"
-	Index        int          `json:"index"`
-	ContentBlock ContentBlock `json:"content_block"`
-}
-
-// ContentBlockDeltaEvent contains incremental content updates
-type ContentBlockDeltaEvent struct {
-	Type  string `json:"type"` // "content_block_delta"
-	Index int    `json:"index"`
-	Delta Delta  `json:"delta"`
-}
-
-// Delta represents an incremental update
-type Delta struct {
-	Type        string `json:"type"` // "text_delta", "input_json_delta", "thinking_delta", "signature_delta"
-	Text        string `json:"text,omitempty"`
-	PartialJSON string `json:"partial_json,omitempty"`
-	Thinking    string `json:"thinking,omitempty"`
-	Signature   string `json:"signature,omitempty"`
-}
-
-// ContentBlockStopEvent signals the end of a content block
-type ContentBlockStopEvent struct {
-	Type  string `json:"type"` // "content_block_stop"
-	Index int    `json:"index"`
-}
-
-// MessageDeltaEvent contains updates to the message
-type MessageDeltaEvent struct {
-	Type  string       `json:"type"` // "message_delta"
-	Delta MessageDelta `json:"delta"`
-	Usage DeltaUsage   `json:"usage"`
-}
-
-// MessageDelta contains stop information
-type MessageDelta struct {
-	StopReason   string `json:"stop_reason,omitempty"`
-	StopSequence string `json:"stop_sequence,omitempty"`
-}
-
-// DeltaUsage contains cumulative token usage
-type DeltaUsage struct {
-	OutputTokens int `json:"output_tokens"`
-}
-
-// MessageStopEvent signals the end of the message
-type MessageStopEvent struct {
-	Type string `json:"type"` // "message_stop"
-}
-
-// PingEvent is a keepalive event
-type PingEvent struct {
-	Type string `json:"type"` // "ping"
-}
-
-// StreamErrorEvent is an error during streaming
-type StreamErrorEvent struct {
-	Type  string `json:"type"` // "error"
-	Error Error  `json:"error"`
-}
-
-// FromMessagesRequest converts an Anthropic MessagesRequest to an Ollama api.ChatRequest
-func FromMessagesRequest(r MessagesRequest) (*api.ChatRequest, error) {
-	var messages []api.Message
-
-	if r.System != nil {
-		switch sys := r.System.(type) {
-		case string:
-			if sys != "" {
-				messages = append(messages, api.Message{Role: "system", Content: sys})
-			}
-		case []any:
-			// System can be an array of content blocks
-			var content strings.Builder
-			for _, block := range sys {
-				if blockMap, ok := block.(map[string]any); ok {
-					if blockMap["type"] == "text" {
-						if text, ok := blockMap["text"].(string); ok {
-							content.WriteString(text)
-						}
-					}
-				}
-			}
-			if content.Len() > 0 {
-				messages = append(messages, api.Message{Role: "system", Content: content.String()})
-			}
-		}
-	}
-
-	for _, msg := range r.Messages {
-		converted, err := convertMessage(msg)
-		if err != nil {
-			return nil, err
-		}
-		messages = append(messages, converted...)
-	}
-
-	options := make(map[string]any)
-
-	options["num_predict"] = r.MaxTokens
-
-	if r.Temperature != nil {
-		options["temperature"] = *r.Temperature
-	}
-
-	if r.TopP != nil {
-		options["top_p"] = *r.TopP
-	}
-
-	if r.TopK != nil {
-		options["top_k"] = *r.TopK
-	}
-
-	if len(r.StopSequences) > 0 {
-		options["stop"] = r.StopSequences
-	}
-
-	var tools api.Tools
-	for _, t := range r.Tools {
-		tool, err := convertTool(t)
-		if err != nil {
-			return nil, err
-		}
-		tools = append(tools, tool)
-	}
-
-	var think *api.ThinkValue
-	if r.Thinking != nil && r.Thinking.Type == "enabled" {
-		think = &api.ThinkValue{Value: true}
-	}
-
-	stream := r.Stream
-
-	return &api.ChatRequest{
-		Model:    r.Model,
-		Messages: messages,
-		Options:  options,
-		Stream:   &stream,
-		Tools:    tools,
-		Think:    think,
-	}, nil
-}
-
-// convertMessage converts an Anthropic MessageParam to Ollama api.Message(s)
-func convertMessage(msg MessageParam) ([]api.Message, error) {
-	var messages []api.Message
-	role := strings.ToLower(msg.Role)
-
-	switch content := msg.Content.(type) {
-	case string:
-		messages = append(messages, api.Message{Role: role, Content: content})
-
-	case []any:
-		var textContent strings.Builder
-		var images []api.ImageData
-		var toolCalls []api.ToolCall
-		var thinking string
-		var toolResults []api.Message
-
-		for _, block := range content {
-			blockMap, ok := block.(map[string]any)
-			if !ok {
-				return nil, errors.New("invalid content block format")
-			}
-
-			blockType, _ := blockMap["type"].(string)
-
-			switch blockType {
-			case "text":
-				if text, ok := blockMap["text"].(string); ok {
-					textContent.WriteString(text)
-				}
-
-			case "image":
-				source, ok := blockMap["source"].(map[string]any)
-				if !ok {
-					return nil, errors.New("invalid image source")
-				}
-
-				sourceType, _ := source["type"].(string)
-				if sourceType == "base64" {
-					data, _ := source["data"].(string)
-					decoded, err := base64.StdEncoding.DecodeString(data)
-					if err != nil {
-						return nil, fmt.Errorf("invalid base64 image data: %w", err)
-					}
-					images = append(images, decoded)
-				} else {
-					return nil, fmt.Errorf("invalid image source type: %s. Only base64 images are supported.", sourceType)
-				}
-				// URL images would need to be fetched - skip for now
-
-			case "tool_use":
-				id, ok := blockMap["id"].(string)
-				if !ok {
-					return nil, errors.New("tool_use block missing required 'id' field")
-				}
-				name, ok := blockMap["name"].(string)
-				if !ok {
-					return nil, errors.New("tool_use block missing required 'name' field")
-				}
-				tc := api.ToolCall{
-					ID: id,
-					Function: api.ToolCallFunction{
-						Name: name,
-					},
-				}
-				if input, ok := blockMap["input"].(map[string]any); ok {
-					tc.Function.Arguments = mapToArgs(input)
-				}
-				toolCalls = append(toolCalls, tc)
-
-			case "tool_result":
-				toolUseID, _ := blockMap["tool_use_id"].(string)
-				var resultContent string
-
-				switch c := blockMap["content"].(type) {
-				case string:
-					resultContent = c
-				case []any:
-					for _, cb := range c {
-						if cbMap, ok := cb.(map[string]any); ok {
-							if cbMap["type"] == "text" {
-								if text, ok := cbMap["text"].(string); ok {
-									resultContent += text
-								}
-							}
-						}
-					}
-				}
-
-				toolResults = append(toolResults, api.Message{
-					Role:       "tool",
-					Content:    resultContent,
-					ToolCallID: toolUseID,
-				})
-
-			case "thinking":
-				if t, ok := blockMap["thinking"].(string); ok {
-					thinking = t
-				}
-			}
-		}
-
-		if textContent.Len() > 0 || len(images) > 0 || len(toolCalls) > 0 || thinking != "" {
-			m := api.Message{
-				Role:      role,
-				Content:   textContent.String(),
-				Images:    images,
-				ToolCalls: toolCalls,
-				Thinking:  thinking,
-			}
-			messages = append(messages, m)
-		}
-
-		// Add tool results as separate messages
-		messages = append(messages, toolResults...)
-
-	default:
-		return nil, fmt.Errorf("invalid message content type: %T", content)
-	}
-
-	return messages, nil
-}
-
-// convertTool converts an Anthropic Tool to an Ollama api.Tool
-func convertTool(t Tool) (api.Tool, error) {
-	var params api.ToolFunctionParameters
-	if len(t.InputSchema) > 0 {
-		if err := json.Unmarshal(t.InputSchema, &params); err != nil {
-			return api.Tool{}, fmt.Errorf("invalid input_schema for tool %q: %w", t.Name, err)
-		}
-	}
-
-	return api.Tool{
-		Type: "function",
-		Function: api.ToolFunction{
-			Name:        t.Name,
-			Description: t.Description,
-			Parameters:  params,
-		},
-	}, nil
-}
-
-// ToMessagesResponse converts an Ollama api.ChatResponse to an Anthropic MessagesResponse
-func ToMessagesResponse(id string, r api.ChatResponse) MessagesResponse {
-	var content []ContentBlock
-
-	if r.Message.Thinking != "" {
-		content = append(content, ContentBlock{
-			Type:     "thinking",
-			Thinking: ptr(r.Message.Thinking),
-		})
-	}
-
-	if r.Message.Content != "" {
-		content = append(content, ContentBlock{
-			Type: "text",
-			Text: ptr(r.Message.Content),
-		})
-	}
-
-	for _, tc := range r.Message.ToolCalls {
-		content = append(content, ContentBlock{
-			Type:  "tool_use",
-			ID:    tc.ID,
-			Name:  tc.Function.Name,
-			Input: tc.Function.Arguments,
-		})
-	}
-
-	stopReason := mapStopReason(r.DoneReason, len(r.Message.ToolCalls) > 0)
-
-	return MessagesResponse{
-		ID:         id,
-		Type:       "message",
-		Role:       "assistant",
-		Model:      r.Model,
-		Content:    content,
-		StopReason: stopReason,
-		Usage: Usage{
-			InputTokens:  r.Metrics.PromptEvalCount,
-			OutputTokens: r.Metrics.EvalCount,
-		},
-	}
-}
-
-// mapStopReason converts Ollama done_reason to Anthropic stop_reason
-func mapStopReason(reason string, hasToolCalls bool) string {
-	if hasToolCalls {
-		return "tool_use"
-	}
-
-	switch reason {
-	case "stop":
-		return "end_turn"
-	case "length":
-		return "max_tokens"
-	default:
-		if reason != "" {
-			return "stop_sequence"
-		}
-		return ""
-	}
-}
-
-// StreamConverter manages state for converting Ollama streaming responses to Anthropic format
-type StreamConverter struct {
-	ID              string
-	Model           string
-	firstWrite      bool
-	contentIndex    int
-	inputTokens     int
-	outputTokens    int
-	thinkingStarted bool
-	thinkingDone    bool
-	textStarted     bool
-	toolCallsSent   map[string]bool
-}
-
-func NewStreamConverter(id, model string) *StreamConverter {
-	return &StreamConverter{
-		ID:            id,
-		Model:         model,
-		firstWrite:    true,
-		toolCallsSent: make(map[string]bool),
-	}
-}
-
-// StreamEvent represents a streaming event to be sent to the client
-type StreamEvent struct {
-	Event string
-	Data  any
-}
-
-// Process converts an Ollama ChatResponse to Anthropic streaming events
-func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
-	var events []StreamEvent
-
-	if c.firstWrite {
-		c.firstWrite = false
-		c.inputTokens = r.Metrics.PromptEvalCount
-
-		events = append(events, StreamEvent{
-			Event: "message_start",
-			Data: MessageStartEvent{
-				Type: "message_start",
-				Message: MessagesResponse{
-					ID:      c.ID,
-					Type:    "message",
-					Role:    "assistant",
-					Model:   c.Model,
-					Content: []ContentBlock{},
-					Usage: Usage{
-						InputTokens:  c.inputTokens,
-						OutputTokens: 0,
-					},
-				},
-			},
-		})
-	}
-
-	if r.Message.Thinking != "" && !c.thinkingDone {
-		if !c.thinkingStarted {
-			c.thinkingStarted = true
-			events = append(events, StreamEvent{
-				Event: "content_block_start",
-				Data: ContentBlockStartEvent{
-					Type:  "content_block_start",
-					Index: c.contentIndex,
-					ContentBlock: ContentBlock{
-						Type:     "thinking",
-						Thinking: ptr(""),
-					},
-				},
-			})
-		}
-
-		events = append(events, StreamEvent{
-			Event: "content_block_delta",
-			Data: ContentBlockDeltaEvent{
-				Type:  "content_block_delta",
-				Index: c.contentIndex,
-				Delta: Delta{
-					Type:     "thinking_delta",
-					Thinking: r.Message.Thinking,
-				},
-			},
-		})
-	}
-
-	if r.Message.Content != "" {
-		if c.thinkingStarted && !c.thinkingDone {
-			c.thinkingDone = true
-			events = append(events, StreamEvent{
-				Event: "content_block_stop",
-				Data: ContentBlockStopEvent{
-					Type:  "content_block_stop",
-					Index: c.contentIndex,
-				},
-			})
-			c.contentIndex++
-		}
-
-		if !c.textStarted {
-			c.textStarted = true
-			events = append(events, StreamEvent{
-				Event: "content_block_start",
-				Data: ContentBlockStartEvent{
-					Type:  "content_block_start",
-					Index: c.contentIndex,
-					ContentBlock: ContentBlock{
-						Type: "text",
-						Text: ptr(""),
-					},
-				},
-			})
-		}
-
-		events = append(events, StreamEvent{
-			Event: "content_block_delta",
-			Data: ContentBlockDeltaEvent{
-				Type:  "content_block_delta",
-				Index: c.contentIndex,
-				Delta: Delta{
-					Type: "text_delta",
-					Text: r.Message.Content,
-				},
-			},
-		})
-	}
-
-	for _, tc := range r.Message.ToolCalls {
-		if c.toolCallsSent[tc.ID] {
-			continue
-		}
-
-		if c.textStarted {
-			events = append(events, StreamEvent{
-				Event: "content_block_stop",
-				Data: ContentBlockStopEvent{
-					Type:  "content_block_stop",
-					Index: c.contentIndex,
-				},
-			})
-			c.contentIndex++
-			c.textStarted = false
-		}
-
-		argsJSON, err := json.Marshal(tc.Function.Arguments)
-		if err != nil {
-			slog.Error("failed to marshal tool arguments", "error", err, "tool_id", tc.ID)
-			continue
-		}
-
-		events = append(events, StreamEvent{
-			Event: "content_block_start",
-			Data: ContentBlockStartEvent{
-				Type:  "content_block_start",
-				Index: c.contentIndex,
-				ContentBlock: ContentBlock{
-					Type:  "tool_use",
-					ID:    tc.ID,
-					Name:  tc.Function.Name,
-					Input: map[string]any{},
-				},
-			},
-		})
-
-		events = append(events, StreamEvent{
-			Event: "content_block_delta",
-			Data: ContentBlockDeltaEvent{
-				Type:  "content_block_delta",
-				Index: c.contentIndex,
-				Delta: Delta{
-					Type:        "input_json_delta",
-					PartialJSON: string(argsJSON),
-				},
-			},
-		})
-
-		events = append(events, StreamEvent{
-			Event: "content_block_stop",
-			Data: ContentBlockStopEvent{
-				Type:  "content_block_stop",
-				Index: c.contentIndex,
-			},
-		})
-
-		c.toolCallsSent[tc.ID] = true
-		c.contentIndex++
-	}
-
-	if r.Done {
-		if c.textStarted {
-			events = append(events, StreamEvent{
-				Event: "content_block_stop",
-				Data: ContentBlockStopEvent{
-					Type:  "content_block_stop",
-					Index: c.contentIndex,
-				},
-			})
-		} else if c.thinkingStarted && !c.thinkingDone {
-			events = append(events, StreamEvent{
-				Event: "content_block_stop",
-				Data: ContentBlockStopEvent{
-					Type:  "content_block_stop",
-					Index: c.contentIndex,
-				},
-			})
-		}
-
-		c.outputTokens = r.Metrics.EvalCount
-		stopReason := mapStopReason(r.DoneReason, len(c.toolCallsSent) > 0)
-
-		events = append(events, StreamEvent{
-			Event: "message_delta",
-			Data: MessageDeltaEvent{
-				Type: "message_delta",
-				Delta: MessageDelta{
-					StopReason: stopReason,
-				},
-				Usage: DeltaUsage{
-					OutputTokens: c.outputTokens,
-				},
-			},
-		})
-
-		events = append(events, StreamEvent{
-			Event: "message_stop",
-			Data: MessageStopEvent{
-				Type: "message_stop",
-			},
-		})
-	}
-
-	return events
-}
-
-// generateID generates a unique ID with the given prefix using crypto/rand
-func generateID(prefix string) string {
-	b := make([]byte, 12)
-	if _, err := rand.Read(b); err != nil {
-		// Fallback to time-based ID if crypto/rand fails
-		return fmt.Sprintf("%s_%d", prefix, time.Now().UnixNano())
-	}
-	return fmt.Sprintf("%s_%x", prefix, b)
-}
-
-// GenerateMessageID generates a unique message ID
-func GenerateMessageID() string {
-	return generateID("msg")
-}
-
-// ptr returns a pointer to the given string value
-func ptr(s string) *string {
-	return &s
-}
-
-// mapToArgs converts a map to ToolCallFunctionArguments
-func mapToArgs(m map[string]any) api.ToolCallFunctionArguments {
-	args := api.NewToolCallFunctionArguments()
-	for k, v := range m {
-		args.Set(k, v)
-	}
-	return args
-}

anthropic/anthropic_test.go

@@ -1,953 +0,0 @@
-package anthropic
-
-import (
-	"encoding/base64"
-	"encoding/json"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-
-	"github.com/ollama/ollama/api"
-)
-
-const (
-	testImage = `iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=`
-)
-
-// testArgs creates ToolCallFunctionArguments from a map (convenience function for tests)
-func testArgs(m map[string]any) api.ToolCallFunctionArguments {
-	args := api.NewToolCallFunctionArguments()
-	for k, v := range m {
-		args.Set(k, v)
-	}
-	return args
-}
-
-func TestFromMessagesRequest_Basic(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{Role: "user", Content: "Hello"},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if result.Model != "test-model" {
-		t.Errorf("expected model 'test-model', got %q", result.Model)
-	}
-
-	if len(result.Messages) != 1 {
-		t.Fatalf("expected 1 message, got %d", len(result.Messages))
-	}
-
-	if result.Messages[0].Role != "user" || result.Messages[0].Content != "Hello" {
-		t.Errorf("unexpected message: %+v", result.Messages[0])
-	}
-
-	if numPredict, ok := result.Options["num_predict"].(int); !ok || numPredict != 1024 {
-		t.Errorf("expected num_predict 1024, got %v", result.Options["num_predict"])
-	}
-}
-
-func TestFromMessagesRequest_WithSystemPrompt(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		System:    "You are a helpful assistant.",
-		Messages: []MessageParam{
-			{Role: "user", Content: "Hello"},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Messages) != 2 {
-		t.Fatalf("expected 2 messages, got %d", len(result.Messages))
-	}
-
-	if result.Messages[0].Role != "system" || result.Messages[0].Content != "You are a helpful assistant." {
-		t.Errorf("unexpected system message: %+v", result.Messages[0])
-	}
-}
-
-func TestFromMessagesRequest_WithSystemPromptArray(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		System: []any{
-			map[string]any{"type": "text", "text": "You are helpful."},
-			map[string]any{"type": "text", "text": " Be concise."},
-		},
-		Messages: []MessageParam{
-			{Role: "user", Content: "Hello"},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Messages) != 2 {
-		t.Fatalf("expected 2 messages, got %d", len(result.Messages))
-	}
-
-	if result.Messages[0].Content != "You are helpful. Be concise." {
-		t.Errorf("unexpected system message content: %q", result.Messages[0].Content)
-	}
-}
-
-func TestFromMessagesRequest_WithOptions(t *testing.T) {
-	temp := 0.7
-	topP := 0.9
-	topK := 40
-	req := MessagesRequest{
-		Model:         "test-model",
-		MaxTokens:     2048,
-		Messages:      []MessageParam{{Role: "user", Content: "Hello"}},
-		Temperature:   &temp,
-		TopP:          &topP,
-		TopK:          &topK,
-		StopSequences: []string{"\n", "END"},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if result.Options["temperature"] != 0.7 {
-		t.Errorf("expected temperature 0.7, got %v", result.Options["temperature"])
-	}
-	if result.Options["top_p"] != 0.9 {
-		t.Errorf("expected top_p 0.9, got %v", result.Options["top_p"])
-	}
-	if result.Options["top_k"] != 40 {
-		t.Errorf("expected top_k 40, got %v", result.Options["top_k"])
-	}
-	if diff := cmp.Diff([]string{"\n", "END"}, result.Options["stop"]); diff != "" {
-		t.Errorf("stop sequences mismatch: %s", diff)
-	}
-}
-
-func TestFromMessagesRequest_WithImage(t *testing.T) {
-	imgData, _ := base64.StdEncoding.DecodeString(testImage)
-
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{
-				Role: "user",
-				Content: []any{
-					map[string]any{"type": "text", "text": "What's in this image?"},
-					map[string]any{
-						"type": "image",
-						"source": map[string]any{
-							"type":       "base64",
-							"media_type": "image/png",
-							"data":       testImage,
-						},
-					},
-				},
-			},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Messages) != 1 {
-		t.Fatalf("expected 1 message, got %d", len(result.Messages))
-	}
-
-	if result.Messages[0].Content != "What's in this image?" {
-		t.Errorf("expected content 'What's in this image?', got %q", result.Messages[0].Content)
-	}
-
-	if len(result.Messages[0].Images) != 1 {
-		t.Fatalf("expected 1 image, got %d", len(result.Messages[0].Images))
-	}
-
-	if string(result.Messages[0].Images[0]) != string(imgData) {
-		t.Error("image data mismatch")
-	}
-}
-
-func TestFromMessagesRequest_WithToolUse(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{Role: "user", Content: "What's the weather in Paris?"},
-			{
-				Role: "assistant",
-				Content: []any{
-					map[string]any{
-						"type":  "tool_use",
-						"id":    "call_123",
-						"name":  "get_weather",
-						"input": map[string]any{"location": "Paris"},
-					},
-				},
-			},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Messages) != 2 {
-		t.Fatalf("expected 2 messages, got %d", len(result.Messages))
-	}
-
-	if len(result.Messages[1].ToolCalls) != 1 {
-		t.Fatalf("expected 1 tool call, got %d", len(result.Messages[1].ToolCalls))
-	}
-
-	tc := result.Messages[1].ToolCalls[0]
-	if tc.ID != "call_123" {
-		t.Errorf("expected tool call ID 'call_123', got %q", tc.ID)
-	}
-	if tc.Function.Name != "get_weather" {
-		t.Errorf("expected tool name 'get_weather', got %q", tc.Function.Name)
-	}
-}
-
-func TestFromMessagesRequest_WithToolResult(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{
-				Role: "user",
-				Content: []any{
-					map[string]any{
-						"type":        "tool_result",
-						"tool_use_id": "call_123",
-						"content":     "The weather in Paris is sunny, 22°C",
-					},
-				},
-			},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Messages) != 1 {
-		t.Fatalf("expected 1 message, got %d", len(result.Messages))
-	}
-
-	msg := result.Messages[0]
-	if msg.Role != "tool" {
-		t.Errorf("expected role 'tool', got %q", msg.Role)
-	}
-	if msg.ToolCallID != "call_123" {
-		t.Errorf("expected tool_call_id 'call_123', got %q", msg.ToolCallID)
-	}
-	if msg.Content != "The weather in Paris is sunny, 22°C" {
-		t.Errorf("unexpected content: %q", msg.Content)
-	}
-}
-
-func TestFromMessagesRequest_WithTools(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages:  []MessageParam{{Role: "user", Content: "Hello"}},
-		Tools: []Tool{
-			{
-				Name:        "get_weather",
-				Description: "Get current weather",
-				InputSchema: json.RawMessage(`{"type":"object","properties":{"location":{"type":"string"}},"required":["location"]}`),
-			},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Tools) != 1 {
-		t.Fatalf("expected 1 tool, got %d", len(result.Tools))
-	}
-
-	tool := result.Tools[0]
-	if tool.Type != "function" {
-		t.Errorf("expected type 'function', got %q", tool.Type)
-	}
-	if tool.Function.Name != "get_weather" {
-		t.Errorf("expected name 'get_weather', got %q", tool.Function.Name)
-	}
-	if tool.Function.Description != "Get current weather" {
-		t.Errorf("expected description 'Get current weather', got %q", tool.Function.Description)
-	}
-}
-
-func TestFromMessagesRequest_WithThinking(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages:  []MessageParam{{Role: "user", Content: "Hello"}},
-		Thinking:  &ThinkingConfig{Type: "enabled", BudgetTokens: 1000},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if result.Think == nil {
-		t.Fatal("expected Think to be set")
-	}
-	if v, ok := result.Think.Value.(bool); !ok || !v {
-		t.Errorf("expected Think.Value to be true, got %v", result.Think.Value)
-	}
-}
-
-// TestFromMessagesRequest_ThinkingOnlyBlock verifies that messages containing only
-// a thinking block (no text, images, or tool calls) are preserved and not dropped.
-func TestFromMessagesRequest_ThinkingOnlyBlock(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{Role: "user", Content: "Hello"},
-			{
-				Role: "assistant",
-				Content: []any{
-					map[string]any{
-						"type":     "thinking",
-						"thinking": "Let me think about this...",
-					},
-				},
-			},
-		},
-	}
-
-	result, err := FromMessagesRequest(req)
-	if err != nil {
-		t.Fatalf("unexpected error: %v", err)
-	}
-
-	if len(result.Messages) != 2 {
-		t.Fatalf("expected 2 messages, got %d", len(result.Messages))
-	}
-
-	assistantMsg := result.Messages[1]
-	if assistantMsg.Thinking != "Let me think about this..." {
-		t.Errorf("expected thinking content, got %q", assistantMsg.Thinking)
-	}
-}
-
-func TestFromMessagesRequest_ToolUseMissingID(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{
-				Role: "assistant",
-				Content: []any{
-					map[string]any{
-						"type": "tool_use",
-						"name": "get_weather",
-					},
-				},
-			},
-		},
-	}
-
-	_, err := FromMessagesRequest(req)
-	if err == nil {
-		t.Fatal("expected error for missing tool_use id")
-	}
-	if err.Error() != "tool_use block missing required 'id' field" {
-		t.Errorf("unexpected error message: %v", err)
-	}
-}
-
-func TestFromMessagesRequest_ToolUseMissingName(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages: []MessageParam{
-			{
-				Role: "assistant",
-				Content: []any{
-					map[string]any{
-						"type": "tool_use",
-						"id":   "call_123",
-					},
-				},
-			},
-		},
-	}
-
-	_, err := FromMessagesRequest(req)
-	if err == nil {
-		t.Fatal("expected error for missing tool_use name")
-	}
-	if err.Error() != "tool_use block missing required 'name' field" {
-		t.Errorf("unexpected error message: %v", err)
-	}
-}
-
-func TestFromMessagesRequest_InvalidToolSchema(t *testing.T) {
-	req := MessagesRequest{
-		Model:     "test-model",
-		MaxTokens: 1024,
-		Messages:  []MessageParam{{Role: "user", Content: "Hello"}},
-		Tools: []Tool{
-			{
-				Name:        "bad_tool",
-				InputSchema: json.RawMessage(`{invalid json`),
-			},
-		},
-	}
-
-	_, err := FromMessagesRequest(req)
-	if err == nil {
-		t.Fatal("expected error for invalid tool schema")
-	}
-}
-
-func TestToMessagesResponse_Basic(t *testing.T) {
-	resp := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role:    "assistant",
-			Content: "Hello there!",
-		},
-		Done:       true,
-		DoneReason: "stop",
-		Metrics: api.Metrics{
-			PromptEvalCount: 10,
-			EvalCount:       5,
-		},
-	}
-
-	result := ToMessagesResponse("msg_123", resp)
-
-	if result.ID != "msg_123" {
-		t.Errorf("expected ID 'msg_123', got %q", result.ID)
-	}
-	if result.Type != "message" {
-		t.Errorf("expected type 'message', got %q", result.Type)
-	}
-	if result.Role != "assistant" {
-		t.Errorf("expected role 'assistant', got %q", result.Role)
-	}
-	if len(result.Content) != 1 {
-		t.Fatalf("expected 1 content block, got %d", len(result.Content))
-	}
-	if result.Content[0].Type != "text" || result.Content[0].Text == nil || *result.Content[0].Text != "Hello there!" {
-		t.Errorf("unexpected content: %+v", result.Content[0])
-	}
-	if result.StopReason != "end_turn" {
-		t.Errorf("expected stop_reason 'end_turn', got %q", result.StopReason)
-	}
-	if result.Usage.InputTokens != 10 || result.Usage.OutputTokens != 5 {
-		t.Errorf("unexpected usage: %+v", result.Usage)
-	}
-}
-
-func TestToMessagesResponse_WithToolCalls(t *testing.T) {
-	resp := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role: "assistant",
-			ToolCalls: []api.ToolCall{
-				{
-					ID: "call_123",
-					Function: api.ToolCallFunction{
-						Name:      "get_weather",
-						Arguments: testArgs(map[string]any{"location": "Paris"}),
-					},
-				},
-			},
-		},
-		Done:       true,
-		DoneReason: "stop",
-	}
-
-	result := ToMessagesResponse("msg_123", resp)
-
-	if len(result.Content) != 1 {
-		t.Fatalf("expected 1 content block, got %d", len(result.Content))
-	}
-	if result.Content[0].Type != "tool_use" {
-		t.Errorf("expected type 'tool_use', got %q", result.Content[0].Type)
-	}
-	if result.Content[0].ID != "call_123" {
-		t.Errorf("expected ID 'call_123', got %q", result.Content[0].ID)
-	}
-	if result.Content[0].Name != "get_weather" {
-		t.Errorf("expected name 'get_weather', got %q", result.Content[0].Name)
-	}
-	if result.StopReason != "tool_use" {
-		t.Errorf("expected stop_reason 'tool_use', got %q", result.StopReason)
-	}
-}
-
-func TestToMessagesResponse_WithThinking(t *testing.T) {
-	resp := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role:     "assistant",
-			Content:  "The answer is 42.",
-			Thinking: "Let me think about this...",
-		},
-		Done:       true,
-		DoneReason: "stop",
-	}
-
-	result := ToMessagesResponse("msg_123", resp)
-
-	if len(result.Content) != 2 {
-		t.Fatalf("expected 2 content blocks, got %d", len(result.Content))
-	}
-	if result.Content[0].Type != "thinking" {
-		t.Errorf("expected first block type 'thinking', got %q", result.Content[0].Type)
-	}
-	if result.Content[0].Thinking == nil || *result.Content[0].Thinking != "Let me think about this..." {
-		t.Errorf("unexpected thinking content: %v", result.Content[0].Thinking)
-	}
-	if result.Content[1].Type != "text" {
-		t.Errorf("expected second block type 'text', got %q", result.Content[1].Type)
-	}
-}
-
-func TestMapStopReason(t *testing.T) {
-	tests := []struct {
-		reason       string
-		hasToolCalls bool
-		want         string
-	}{
-		{"stop", false, "end_turn"},
-		{"length", false, "max_tokens"},
-		{"stop", true, "tool_use"},
-		{"other", false, "stop_sequence"},
-		{"", false, ""},
-	}
-
-	for _, tt := range tests {
-		got := mapStopReason(tt.reason, tt.hasToolCalls)
-		if got != tt.want {
-			t.Errorf("mapStopReason(%q, %v) = %q, want %q", tt.reason, tt.hasToolCalls, got, tt.want)
-		}
-	}
-}
-
-func TestNewError(t *testing.T) {
-	tests := []struct {
-		code int
-		want string
-	}{
-		{400, "invalid_request_error"},
-		{401, "authentication_error"},
-		{403, "permission_error"},
-		{404, "not_found_error"},
-		{429, "rate_limit_error"},
-		{500, "api_error"},
-		{503, "overloaded_error"},
-		{529, "overloaded_error"},
-	}
-
-	for _, tt := range tests {
-		result := NewError(tt.code, "test message")
-		if result.Type != "error" {
-			t.Errorf("NewError(%d) type = %q, want 'error'", tt.code, result.Type)
-		}
-		if result.Error.Type != tt.want {
-			t.Errorf("NewError(%d) error.type = %q, want %q", tt.code, result.Error.Type, tt.want)
-		}
-		if result.Error.Message != "test message" {
-			t.Errorf("NewError(%d) message = %q, want 'test message'", tt.code, result.Error.Message)
-		}
-		if result.RequestID == "" {
-			t.Errorf("NewError(%d) request_id should not be empty", tt.code)
-		}
-	}
-}
-
-func TestGenerateMessageID(t *testing.T) {
-	id1 := GenerateMessageID()
-	id2 := GenerateMessageID()
-
-	if id1 == "" {
-		t.Error("GenerateMessageID returned empty string")
-	}
-	if id1 == id2 {
-		t.Error("GenerateMessageID returned duplicate IDs")
-	}
-	if len(id1) < 10 {
-		t.Errorf("GenerateMessageID returned short ID: %q", id1)
-	}
-	if id1[:4] != "msg_" {
-		t.Errorf("GenerateMessageID should start with 'msg_', got %q", id1[:4])
-	}
-}
-
-func TestStreamConverter_Basic(t *testing.T) {
-	conv := NewStreamConverter("msg_123", "test-model")
-
-	// First chunk
-	resp1 := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role:    "assistant",
-			Content: "Hello",
-		},
-		Metrics: api.Metrics{PromptEvalCount: 10},
-	}
-
-	events1 := conv.Process(resp1)
-	if len(events1) < 3 {
-		t.Fatalf("expected at least 3 events for first chunk, got %d", len(events1))
-	}
-
-	// Should have message_start, content_block_start, content_block_delta
-	if events1[0].Event != "message_start" {
-		t.Errorf("expected first event 'message_start', got %q", events1[0].Event)
-	}
-	if events1[1].Event != "content_block_start" {
-		t.Errorf("expected second event 'content_block_start', got %q", events1[1].Event)
-	}
-	if events1[2].Event != "content_block_delta" {
-		t.Errorf("expected third event 'content_block_delta', got %q", events1[2].Event)
-	}
-
-	// Final chunk
-	resp2 := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role:    "assistant",
-			Content: " world!",
-		},
-		Done:       true,
-		DoneReason: "stop",
-		Metrics:    api.Metrics{EvalCount: 5},
-	}
-
-	events2 := conv.Process(resp2)
-
-	// Should have content_block_delta, content_block_stop, message_delta, message_stop
-	hasStop := false
-	for _, e := range events2 {
-		if e.Event == "message_stop" {
-			hasStop = true
-		}
-	}
-	if !hasStop {
-		t.Error("expected message_stop event in final chunk")
-	}
-}
-
-func TestStreamConverter_WithToolCalls(t *testing.T) {
-	conv := NewStreamConverter("msg_123", "test-model")
-
-	resp := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role: "assistant",
-			ToolCalls: []api.ToolCall{
-				{
-					ID: "call_123",
-					Function: api.ToolCallFunction{
-						Name:      "get_weather",
-						Arguments: testArgs(map[string]any{"location": "Paris"}),
-					},
-				},
-			},
-		},
-		Done:       true,
-		DoneReason: "stop",
-		Metrics:    api.Metrics{PromptEvalCount: 10, EvalCount: 5},
-	}
-
-	events := conv.Process(resp)
-
-	hasToolStart := false
-	hasToolDelta := false
-	for _, e := range events {
-		if e.Event == "content_block_start" {
-			if start, ok := e.Data.(ContentBlockStartEvent); ok {
-				if start.ContentBlock.Type == "tool_use" {
-					hasToolStart = true
-				}
-			}
-		}
-		if e.Event == "content_block_delta" {
-			if delta, ok := e.Data.(ContentBlockDeltaEvent); ok {
-				if delta.Delta.Type == "input_json_delta" {
-					hasToolDelta = true
-				}
-			}
-		}
-	}
-
-	if !hasToolStart {
-		t.Error("expected tool_use content_block_start event")
-	}
-	if !hasToolDelta {
-		t.Error("expected input_json_delta event")
-	}
-}
-
-func TestStreamConverter_ToolCallWithUnmarshalableArgs(t *testing.T) {
-	// Test that unmarshalable arguments (like channels) are handled gracefully
-	// and don't cause a panic or corrupt stream
-	conv := NewStreamConverter("msg_123", "test-model")
-
-	// Create a channel which cannot be JSON marshaled
-	unmarshalable := make(chan int)
-	badArgs := api.NewToolCallFunctionArguments()
-	badArgs.Set("channel", unmarshalable)
-
-	resp := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role: "assistant",
-			ToolCalls: []api.ToolCall{
-				{
-					ID: "call_bad",
-					Function: api.ToolCallFunction{
-						Name:      "bad_function",
-						Arguments: badArgs,
-					},
-				},
-			},
-		},
-		Done:       true,
-		DoneReason: "stop",
-	}
-
-	// Should not panic and should skip the unmarshalable tool call
-	events := conv.Process(resp)
-
-	// Verify no tool_use block was started (since marshal failed before block start)
-	hasToolStart := false
-	for _, e := range events {
-		if e.Event == "content_block_start" {
-			if start, ok := e.Data.(ContentBlockStartEvent); ok {
-				if start.ContentBlock.Type == "tool_use" {
-					hasToolStart = true
-				}
-			}
-		}
-	}
-
-	if hasToolStart {
-		t.Error("expected no tool_use block when arguments cannot be marshaled")
-	}
-}
-
-func TestStreamConverter_MultipleToolCallsWithMixedValidity(t *testing.T) {
-	// Test that valid tool calls still work when mixed with invalid ones
-	conv := NewStreamConverter("msg_123", "test-model")
-
-	unmarshalable := make(chan int)
-	badArgs := api.NewToolCallFunctionArguments()
-	badArgs.Set("channel", unmarshalable)
-
-	resp := api.ChatResponse{
-		Model: "test-model",
-		Message: api.Message{
-			Role: "assistant",
-			ToolCalls: []api.ToolCall{
-				{
-					ID: "call_good",
-					Function: api.ToolCallFunction{
-						Name:      "good_function",
-						Arguments: testArgs(map[string]any{"location": "Paris"}),
-					},
-				},
-				{
-					ID: "call_bad",
-					Function: api.ToolCallFunction{
-						Name:      "bad_function",
-						Arguments: badArgs,
-					},
-				},
-			},
-		},
-		Done:       true,
-		DoneReason: "stop",
-	}
-
-	events := conv.Process(resp)
-
-	// Count tool_use blocks - should only have 1 (the valid one)
-	toolStartCount := 0
-	toolDeltaCount := 0
-	for _, e := range events {
-		if e.Event == "content_block_start" {
-			if start, ok := e.Data.(ContentBlockStartEvent); ok {
-				if start.ContentBlock.Type == "tool_use" {
-					toolStartCount++
-					if start.ContentBlock.Name != "good_function" {
-						t.Errorf("expected tool name 'good_function', got %q", start.ContentBlock.Name)
-					}
-				}
-			}
-		}
-		if e.Event == "content_block_delta" {
-			if delta, ok := e.Data.(ContentBlockDeltaEvent); ok {
-				if delta.Delta.Type == "input_json_delta" {
-					toolDeltaCount++
-				}
-			}
-		}
-	}
-
-	if toolStartCount != 1 {
-		t.Errorf("expected 1 tool_use block, got %d", toolStartCount)
-	}
-	if toolDeltaCount != 1 {
-		t.Errorf("expected 1 input_json_delta, got %d", toolDeltaCount)
-	}
-}
-
-// TestContentBlockJSON_EmptyFieldsPresent verifies that empty text and thinking fields
-// are serialized in JSON output. The Anthropic SDK requires these fields to be present
-// (even when empty) in content_block_start events to properly accumulate streaming deltas.
-// Without these fields, the SDK throws: "TypeError: unsupported operand type(s) for +=: 'NoneType' and 'str'"
-func TestContentBlockJSON_EmptyFieldsPresent(t *testing.T) {
-	tests := []struct {
-		name     string
-		block    ContentBlock
-		wantKeys []string
-	}{
-		{
-			name: "text block includes empty text field",
-			block: ContentBlock{
-				Type: "text",
-				Text: ptr(""),
-			},
-			wantKeys: []string{"type", "text"},
-		},
-		{
-			name: "thinking block includes empty thinking field",
-			block: ContentBlock{
-				Type:     "thinking",
-				Thinking: ptr(""),
-			},
-			wantKeys: []string{"type", "thinking"},
-		},
-		{
-			name: "text block with content",
-			block: ContentBlock{
-				Type: "text",
-				Text: ptr("hello"),
-			},
-			wantKeys: []string{"type", "text"},
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			data, err := json.Marshal(tt.block)
-			if err != nil {
-				t.Fatalf("failed to marshal: %v", err)
-			}
-
-			var result map[string]any
-			if err := json.Unmarshal(data, &result); err != nil {
-				t.Fatalf("failed to unmarshal: %v", err)
-			}
-
-			for _, key := range tt.wantKeys {
-				if _, ok := result[key]; !ok {
-					t.Errorf("expected key %q to be present in JSON output, got: %s", key, string(data))
-				}
-			}
-		})
-	}
-}
-
-// TestStreamConverter_ContentBlockStartIncludesEmptyFields verifies that content_block_start
-// events include the required empty fields for SDK compatibility.
-func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
-	t.Run("text block start includes empty text", func(t *testing.T) {
-		conv := NewStreamConverter("msg_123", "test-model")
-
-		resp := api.ChatResponse{
-			Model:   "test-model",
-			Message: api.Message{Role: "assistant", Content: "hello"},
-		}
-
-		events := conv.Process(resp)
-
-		var foundTextStart bool
-		for _, e := range events {
-			if e.Event == "content_block_start" {
-				if start, ok := e.Data.(ContentBlockStartEvent); ok {
-					if start.ContentBlock.Type == "text" {
-						foundTextStart = true
-						// Marshal and verify the text field is present
-						data, _ := json.Marshal(start)
-						var result map[string]any
-						json.Unmarshal(data, &result)
-						cb := result["content_block"].(map[string]any)
-						if _, ok := cb["text"]; !ok {
-							t.Error("content_block_start for text should include 'text' field")
-						}
-					}
-				}
-			}
-		}
-
-		if !foundTextStart {
-			t.Error("expected text content_block_start event")
-		}
-	})
-
-	t.Run("thinking block start includes empty thinking", func(t *testing.T) {
-		conv := NewStreamConverter("msg_123", "test-model")
-
-		resp := api.ChatResponse{
-			Model:   "test-model",
-			Message: api.Message{Role: "assistant", Thinking: "let me think..."},
-		}
-
-		events := conv.Process(resp)
-
-		var foundThinkingStart bool
-		for _, e := range events {
-			if e.Event == "content_block_start" {
-				if start, ok := e.Data.(ContentBlockStartEvent); ok {
-					if start.ContentBlock.Type == "thinking" {
-						foundThinkingStart = true
-						data, _ := json.Marshal(start)
-						var result map[string]any
-						json.Unmarshal(data, &result)
-						cb := result["content_block"].(map[string]any)
-						if _, ok := cb["thinking"]; !ok {
-							t.Error("content_block_start for thinking should include 'thinking' field")
-						}
-					}
-				}
-			}
-		}
-
-		if !foundThinkingStart {
-			t.Error("expected thinking content_block_start event")
-		}
-	})
-}

api/client.go

@@ -165,7 +165,7 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	return nil
 }
 
-const maxBufferSize = 8 * format.MegaByte
+const maxBufferSize = 512 * format.KiloByte
 
 func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
 	var buf io.Reader
@@ -226,14 +226,7 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 
 		bts := scanner.Bytes()
 		if err := json.Unmarshal(bts, &errorResponse); err != nil {
-			if response.StatusCode >= http.StatusBadRequest {
-				return StatusError{
-					StatusCode:   response.StatusCode,
-					Status:       response.Status,
-					ErrorMessage: string(bts),
-				}
-			}
-			return errors.New(string(bts))
+			return fmt.Errorf("unmarshal: %w", err)
 		}
 
 		if response.StatusCode == http.StatusUnauthorized {
@@ -347,7 +340,7 @@ type CreateProgressFunc func(ProgressResponse) error
 // Create creates a model from a [Modelfile]. fn is a progress function that
 // behaves similarly to other methods (see [Client.Pull]).
 //
-// [Modelfile]: https://github.com/ollama/ollama/blob/main/docs/modelfile.mdx
+// [Modelfile]: https://github.com/ollama/ollama/blob/main/docs/modelfile.md
 func (c *Client) Create(ctx context.Context, req *CreateRequest, fn CreateProgressFunc) error {
 	return c.stream(ctx, http.MethodPost, "/api/create", req, func(bts []byte) error {
 		var resp ProgressResponse

api/client_test.go

@@ -55,7 +55,6 @@ func TestClientFromEnvironment(t *testing.T) {
 type testError struct {
 	message    string
 	statusCode int
-	raw        bool // if true, write message as-is instead of JSON encoding
 }
 
 func (e testError) Error() string {
@@ -112,20 +111,6 @@ func TestClientStream(t *testing.T) {
 				},
 			},
 		},
-		{
-			name: "plain text error response",
-			responses: []any{
-				"internal server error",
-			},
-			wantErr: "internal server error",
-		},
-		{
-			name: "HTML error page",
-			responses: []any{
-				"<html><body>404 Not Found</body></html>",
-			},
-			wantErr: "404 Not Found",
-		},
 	}
 
 	for _, tc := range testCases {
@@ -150,12 +135,6 @@ func TestClientStream(t *testing.T) {
 						return
 					}
 
-					if str, ok := resp.(string); ok {
-						fmt.Fprintln(w, str)
-						flusher.Flush()
-						continue
-					}
-
 					if err := json.NewEncoder(w).Encode(resp); err != nil {
 						t.Fatalf("failed to encode response: %v", err)
 					}
@@ -194,10 +173,9 @@ func TestClientStream(t *testing.T) {
 
 func TestClientDo(t *testing.T) {
 	testCases := []struct {
-		name           string
-		response       any
-		wantErr        string
-		wantStatusCode int
+		name     string
+		response any
+		wantErr  string
 	}{
 		{
 			name: "immediate error response",
@@ -205,8 +183,7 @@ func TestClientDo(t *testing.T) {
 				message:    "test error message",
 				statusCode: http.StatusBadRequest,
 			},
-			wantErr:        "test error message",
-			wantStatusCode: http.StatusBadRequest,
+			wantErr: "test error message",
 		},
 		{
 			name: "server error response",
@@ -214,8 +191,7 @@ func TestClientDo(t *testing.T) {
 				message:    "internal error",
 				statusCode: http.StatusInternalServerError,
 			},
-			wantErr:        "internal error",
-			wantStatusCode: http.StatusInternalServerError,
+			wantErr: "internal error",
 		},
 		{
 			name: "successful response",
@@ -227,26 +203,6 @@ func TestClientDo(t *testing.T) {
 				Success: true,
 			},
 		},
-		{
-			name: "plain text error response",
-			response: testError{
-				message:    "internal server error",
-				statusCode: http.StatusInternalServerError,
-				raw:        true,
-			},
-			wantErr:        "internal server error",
-			wantStatusCode: http.StatusInternalServerError,
-		},
-		{
-			name: "HTML error page",
-			response: testError{
-				message:    "<html><body>404 Not Found</body></html>",
-				statusCode: http.StatusNotFound,
-				raw:        true,
-			},
-			wantErr:        "<html><body>404 Not Found</body></html>",
-			wantStatusCode: http.StatusNotFound,
-		},
 	}
 
 	for _, tc := range testCases {
@@ -254,16 +210,11 @@ func TestClientDo(t *testing.T) {
 			ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
 				if errResp, ok := tc.response.(testError); ok {
 					w.WriteHeader(errResp.statusCode)
-					if !errResp.raw {
-						err := json.NewEncoder(w).Encode(map[string]string{
-							"error": errResp.message,
-						})
-						if err != nil {
-							t.Fatal("failed to encode error response:", err)
-						}
-					} else {
-						// Write raw message (simulates non-JSON error responses)
-						fmt.Fprint(w, errResp.message)
+					err := json.NewEncoder(w).Encode(map[string]string{
+						"error": errResp.message,
+					})
+					if err != nil {
+						t.Fatal("failed to encode error response:", err)
 					}
 					return
 				}
@@ -290,15 +241,6 @@ func TestClientDo(t *testing.T) {
 				if err.Error() != tc.wantErr {
 					t.Errorf("error message mismatch: got %q, want %q", err.Error(), tc.wantErr)
 				}
-				if tc.wantStatusCode != 0 {
-					if statusErr, ok := err.(StatusError); ok {
-						if statusErr.StatusCode != tc.wantStatusCode {
-							t.Errorf("status code mismatch: got %d, want %d", statusErr.StatusCode, tc.wantStatusCode)
-						}
-					} else {
-						t.Errorf("expected StatusError, got %T", err)
-					}
-				}
 				return
 			}
 

api/examples/chat/main.go

@@ -15,19 +15,19 @@ func main() {
 	}
 
 	messages := []api.Message{
-		{
+		api.Message{
 			Role:    "system",
 			Content: "Provide very brief, concise responses",
 		},
-		{
+		api.Message{
 			Role:    "user",
 			Content: "Name some unusual animals",
 		},
-		{
+		api.Message{
 			Role:    "assistant",
 			Content: "Monotreme, platypus, echidna",
 		},
-		{
+		api.Message{
 			Role:    "user",
 			Content: "which of these is the most dangerous?",
 		},

api/types.go

@@ -3,7 +3,6 @@ package api
 import (
 	"encoding/json"
 	"fmt"
-	"iter"
 	"log/slog"
 	"math"
 	"os"
@@ -15,7 +14,6 @@ import (
 	"github.com/google/uuid"
 
 	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/internal/orderedmap"
 	"github.com/ollama/ollama/types/model"
 )
 
@@ -127,10 +125,6 @@ type GenerateRequest struct {
 	// each with an associated log probability. Only applies when Logprobs is true.
 	// Valid values are 0-20. Default is 0 (only return the selected token's logprob).
 	TopLogprobs int `json:"top_logprobs,omitempty"`
-
-	// Size specifies the image dimensions for image generation models.
-	// Format: "WxH" (e.g., "1024x1024"). OpenAI-compatible.
-	Size string `json:"size,omitempty"`
 }
 
 // ChatRequest describes a request sent by [Client.Chat].
@@ -233,79 +227,13 @@ type ToolCallFunction struct {
 	Arguments ToolCallFunctionArguments `json:"arguments"`
 }
 
-// ToolCallFunctionArguments holds tool call arguments in insertion order.
-type ToolCallFunctionArguments struct {
-	om *orderedmap.Map[string, any]
-}
-
-// NewToolCallFunctionArguments creates a new empty ToolCallFunctionArguments.
-func NewToolCallFunctionArguments() ToolCallFunctionArguments {
-	return ToolCallFunctionArguments{om: orderedmap.New[string, any]()}
-}
-
-// Get retrieves a value by key.
-func (t *ToolCallFunctionArguments) Get(key string) (any, bool) {
-	if t == nil || t.om == nil {
-		return nil, false
-	}
-	return t.om.Get(key)
-}
-
-// Set sets a key-value pair, preserving insertion order.
-func (t *ToolCallFunctionArguments) Set(key string, value any) {
-	if t == nil {
-		return
-	}
-	if t.om == nil {
-		t.om = orderedmap.New[string, any]()
-	}
-	t.om.Set(key, value)
-}
-
-// Len returns the number of arguments.
-func (t *ToolCallFunctionArguments) Len() int {
-	if t == nil || t.om == nil {
-		return 0
-	}
-	return t.om.Len()
-}
-
-// All returns an iterator over all key-value pairs in insertion order.
-func (t *ToolCallFunctionArguments) All() iter.Seq2[string, any] {
-	if t == nil || t.om == nil {
-		return func(yield func(string, any) bool) {}
-	}
-	return t.om.All()
-}
-
-// ToMap returns a regular map (order not preserved).
-func (t *ToolCallFunctionArguments) ToMap() map[string]any {
-	if t == nil || t.om == nil {
-		return nil
-	}
-	return t.om.ToMap()
-}
+type ToolCallFunctionArguments map[string]any
 
 func (t *ToolCallFunctionArguments) String() string {
-	if t == nil || t.om == nil {
-		return "{}"
-	}
-	bts, _ := json.Marshal(t.om)
+	bts, _ := json.Marshal(t)
 	return string(bts)
 }
 
-func (t *ToolCallFunctionArguments) UnmarshalJSON(data []byte) error {
-	t.om = orderedmap.New[string, any]()
-	return json.Unmarshal(data, t.om)
-}
-
-func (t ToolCallFunctionArguments) MarshalJSON() ([]byte, error) {
-	if t.om == nil {
-		return []byte("{}"), nil
-	}
-	return json.Marshal(t.om)
-}
-
 type Tool struct {
 	Type     string       `json:"type"`
 	Items    any          `json:"items,omitempty"`
@@ -354,78 +282,12 @@ func (pt PropertyType) String() string {
 	return fmt.Sprintf("%v", []string(pt))
 }
 
-// ToolPropertiesMap holds tool properties in insertion order.
-type ToolPropertiesMap struct {
-	om *orderedmap.Map[string, ToolProperty]
-}
-
-// NewToolPropertiesMap creates a new empty ToolPropertiesMap.
-func NewToolPropertiesMap() *ToolPropertiesMap {
-	return &ToolPropertiesMap{om: orderedmap.New[string, ToolProperty]()}
-}
-
-// Get retrieves a property by name.
-func (t *ToolPropertiesMap) Get(key string) (ToolProperty, bool) {
-	if t == nil || t.om == nil {
-		return ToolProperty{}, false
-	}
-	return t.om.Get(key)
-}
-
-// Set sets a property, preserving insertion order.
-func (t *ToolPropertiesMap) Set(key string, value ToolProperty) {
-	if t == nil {
-		return
-	}
-	if t.om == nil {
-		t.om = orderedmap.New[string, ToolProperty]()
-	}
-	t.om.Set(key, value)
-}
-
-// Len returns the number of properties.
-func (t *ToolPropertiesMap) Len() int {
-	if t == nil || t.om == nil {
-		return 0
-	}
-	return t.om.Len()
-}
-
-// All returns an iterator over all properties in insertion order.
-func (t *ToolPropertiesMap) All() iter.Seq2[string, ToolProperty] {
-	if t == nil || t.om == nil {
-		return func(yield func(string, ToolProperty) bool) {}
-	}
-	return t.om.All()
-}
-
-// ToMap returns a regular map (order not preserved).
-func (t *ToolPropertiesMap) ToMap() map[string]ToolProperty {
-	if t == nil || t.om == nil {
-		return nil
-	}
-	return t.om.ToMap()
-}
-
-func (t ToolPropertiesMap) MarshalJSON() ([]byte, error) {
-	if t.om == nil {
-		return []byte("null"), nil
-	}
-	return json.Marshal(t.om)
-}
-
-func (t *ToolPropertiesMap) UnmarshalJSON(data []byte) error {
-	t.om = orderedmap.New[string, ToolProperty]()
-	return json.Unmarshal(data, t.om)
-}
-
 type ToolProperty struct {
-	AnyOf       []ToolProperty     `json:"anyOf,omitempty"`
-	Type        PropertyType       `json:"type,omitempty"`
-	Items       any                `json:"items,omitempty"`
-	Description string             `json:"description,omitempty"`
-	Enum        []any              `json:"enum,omitempty"`
-	Properties  *ToolPropertiesMap `json:"properties,omitempty"`
+	AnyOf       []ToolProperty `json:"anyOf,omitempty"`
+	Type        PropertyType   `json:"type,omitempty"`
+	Items       any            `json:"items,omitempty"`
+	Description string         `json:"description,omitempty"`
+	Enum        []any          `json:"enum,omitempty"`
 }
 
 // ToTypeScriptType converts a ToolProperty to a TypeScript type string
@@ -474,11 +336,11 @@ func mapToTypeScriptType(jsonType string) string {
 }
 
 type ToolFunctionParameters struct {
-	Type       string             `json:"type"`
-	Defs       any                `json:"$defs,omitempty"`
-	Items      any                `json:"items,omitempty"`
-	Required   []string           `json:"required,omitempty"`
-	Properties *ToolPropertiesMap `json:"properties"`
+	Type       string                  `json:"type"`
+	Defs       any                     `json:"$defs,omitempty"`
+	Items      any                     `json:"items,omitempty"`
+	Required   []string                `json:"required,omitempty"`
+	Properties map[string]ToolProperty `json:"properties"`
 }
 
 func (t *ToolFunctionParameters) String() string {
@@ -691,9 +553,6 @@ type CreateRequest struct {
 	Renderer string `json:"renderer,omitempty"`
 	Parser   string `json:"parser,omitempty"`
 
-	// Requires is the minimum version of Ollama required by the model.
-	Requires string `json:"requires,omitempty"`
-
 	// Info is a map of additional information for the model
 	Info map[string]any `json:"info,omitempty"`
 
@@ -744,7 +603,6 @@ type ShowResponse struct {
 	Tensors       []Tensor           `json:"tensors,omitempty"`
 	Capabilities  []model.Capability `json:"capabilities,omitempty"`
 	ModifiedAt    time.Time          `json:"modified_at,omitempty"`
-	Requires      string             `json:"requires,omitempty"`
 }
 
 // CopyRequest is the request passed to [Client.Copy].

api/types_test.go

@@ -11,24 +11,6 @@ import (
 	"github.com/stretchr/testify/require"
 )
 
-// testPropsMap creates a ToolPropertiesMap from a map (convenience function for tests, order not preserved)
-func testPropsMap(m map[string]ToolProperty) *ToolPropertiesMap {
-	props := NewToolPropertiesMap()
-	for k, v := range m {
-		props.Set(k, v)
-	}
-	return props
-}
-
-// testArgs creates ToolCallFunctionArguments from a map (convenience function for tests, order not preserved)
-func testArgs(m map[string]any) ToolCallFunctionArguments {
-	args := NewToolCallFunctionArguments()
-	for k, v := range m {
-		args.Set(k, v)
-	}
-	return args
-}
-
 func TestKeepAliveParsingFromJSON(t *testing.T) {
 	tests := []struct {
 		name string
@@ -327,9 +309,9 @@ func TestToolFunctionParameters_MarshalJSON(t *testing.T) {
 			input: ToolFunctionParameters{
 				Type:     "object",
 				Required: []string{"name"},
-				Properties: testPropsMap(map[string]ToolProperty{
+				Properties: map[string]ToolProperty{
 					"name": {Type: PropertyType{"string"}},
-				}),
+				},
 			},
 			expected: `{"type":"object","required":["name"],"properties":{"name":{"type":"string"}}}`,
 		},
@@ -337,9 +319,9 @@ func TestToolFunctionParameters_MarshalJSON(t *testing.T) {
 			name: "no required",
 			input: ToolFunctionParameters{
 				Type: "object",
-				Properties: testPropsMap(map[string]ToolProperty{
+				Properties: map[string]ToolProperty{
 					"name": {Type: PropertyType{"string"}},
-				}),
+				},
 			},
 			expected: `{"type":"object","properties":{"name":{"type":"string"}}}`,
 		},
@@ -357,7 +339,7 @@ func TestToolFunctionParameters_MarshalJSON(t *testing.T) {
 func TestToolCallFunction_IndexAlwaysMarshals(t *testing.T) {
 	fn := ToolCallFunction{
 		Name:      "echo",
-		Arguments: testArgs(map[string]any{"message": "hi"}),
+		Arguments: ToolCallFunctionArguments{"message": "hi"},
 	}
 
 	data, err := json.Marshal(fn)
@@ -522,116 +504,6 @@ func TestThinking_UnmarshalJSON(t *testing.T) {
 	}
 }
 
-func TestToolPropertyNestedProperties(t *testing.T) {
-	tests := []struct {
-		name     string
-		input    string
-		expected ToolProperty
-	}{
-		{
-			name: "nested object properties",
-			input: `{
-				"type": "object",
-				"description": "Location details",
-				"properties": {
-					"address": {
-						"type": "string",
-						"description": "Street address"
-					},
-					"city": {
-						"type": "string",
-						"description": "City name"
-					}
-				}
-			}`,
-			expected: ToolProperty{
-				Type:        PropertyType{"object"},
-				Description: "Location details",
-				Properties: testPropsMap(map[string]ToolProperty{
-					"address": {
-						Type:        PropertyType{"string"},
-						Description: "Street address",
-					},
-					"city": {
-						Type:        PropertyType{"string"},
-						Description: "City name",
-					},
-				}),
-			},
-		},
-		{
-			name: "deeply nested properties",
-			input: `{
-				"type": "object",
-				"description": "Event",
-				"properties": {
-					"location": {
-						"type": "object",
-						"description": "Location",
-						"properties": {
-							"coordinates": {
-								"type": "object",
-								"description": "GPS coordinates",
-								"properties": {
-									"lat": {"type": "number", "description": "Latitude"},
-									"lng": {"type": "number", "description": "Longitude"}
-								}
-							}
-						}
-					}
-				}
-			}`,
-			expected: ToolProperty{
-				Type:        PropertyType{"object"},
-				Description: "Event",
-				Properties: testPropsMap(map[string]ToolProperty{
-					"location": {
-						Type:        PropertyType{"object"},
-						Description: "Location",
-						Properties: testPropsMap(map[string]ToolProperty{
-							"coordinates": {
-								Type:        PropertyType{"object"},
-								Description: "GPS coordinates",
-								Properties: testPropsMap(map[string]ToolProperty{
-									"lat": {Type: PropertyType{"number"}, Description: "Latitude"},
-									"lng": {Type: PropertyType{"number"}, Description: "Longitude"},
-								}),
-							},
-						}),
-					},
-				}),
-			},
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			var prop ToolProperty
-			err := json.Unmarshal([]byte(tt.input), &prop)
-			require.NoError(t, err)
-
-			// Compare JSON representations since pointer comparison doesn't work
-			expectedJSON, err := json.Marshal(tt.expected)
-			require.NoError(t, err)
-			actualJSON, err := json.Marshal(prop)
-			require.NoError(t, err)
-			assert.JSONEq(t, string(expectedJSON), string(actualJSON))
-
-			// Round-trip test: marshal and unmarshal again
-			data, err := json.Marshal(prop)
-			require.NoError(t, err)
-
-			var prop2 ToolProperty
-			err = json.Unmarshal(data, &prop2)
-			require.NoError(t, err)
-
-			prop2JSON, err := json.Marshal(prop2)
-			require.NoError(t, err)
-			assert.JSONEq(t, string(expectedJSON), string(prop2JSON))
-		})
-	}
-}
-
 func TestToolFunctionParameters_String(t *testing.T) {
 	tests := []struct {
 		name     string
@@ -643,12 +515,12 @@ func TestToolFunctionParameters_String(t *testing.T) {
 			params: ToolFunctionParameters{
 				Type:     "object",
 				Required: []string{"name"},
-				Properties: testPropsMap(map[string]ToolProperty{
+				Properties: map[string]ToolProperty{
 					"name": {
 						Type:        PropertyType{"string"},
 						Description: "The name of the person",
 					},
-				}),
+				},
 			},
 			expected: `{"type":"object","required":["name"],"properties":{"name":{"type":"string","description":"The name of the person"}}}`,
 		},
@@ -665,7 +537,7 @@ func TestToolFunctionParameters_String(t *testing.T) {
 					s.Self = s
 					return s
 				}(),
-				Properties: testPropsMap(map[string]ToolProperty{}),
+				Properties: map[string]ToolProperty{},
 			},
 			expected: "",
 		},
@@ -678,235 +550,3 @@ func TestToolFunctionParameters_String(t *testing.T) {
 		})
 	}
 }
-
-func TestToolCallFunctionArguments_OrderPreservation(t *testing.T) {
-	t.Run("marshal preserves insertion order", func(t *testing.T) {
-		args := NewToolCallFunctionArguments()
-		args.Set("zebra", "z")
-		args.Set("apple", "a")
-		args.Set("mango", "m")
-
-		data, err := json.Marshal(args)
-		require.NoError(t, err)
-
-		// Should preserve insertion order, not alphabetical
-		assert.Equal(t, `{"zebra":"z","apple":"a","mango":"m"}`, string(data))
-	})
-
-	t.Run("unmarshal preserves JSON order", func(t *testing.T) {
-		jsonData := `{"zebra":"z","apple":"a","mango":"m"}`
-
-		var args ToolCallFunctionArguments
-		err := json.Unmarshal([]byte(jsonData), &args)
-		require.NoError(t, err)
-
-		// Verify iteration order matches JSON order
-		var keys []string
-		for k := range args.All() {
-			keys = append(keys, k)
-		}
-		assert.Equal(t, []string{"zebra", "apple", "mango"}, keys)
-	})
-
-	t.Run("round trip preserves order", func(t *testing.T) {
-		original := `{"z":1,"a":2,"m":3,"b":4}`
-
-		var args ToolCallFunctionArguments
-		err := json.Unmarshal([]byte(original), &args)
-		require.NoError(t, err)
-
-		data, err := json.Marshal(args)
-		require.NoError(t, err)
-
-		assert.Equal(t, original, string(data))
-	})
-
-	t.Run("String method returns ordered JSON", func(t *testing.T) {
-		args := NewToolCallFunctionArguments()
-		args.Set("c", 3)
-		args.Set("a", 1)
-		args.Set("b", 2)
-
-		assert.Equal(t, `{"c":3,"a":1,"b":2}`, args.String())
-	})
-
-	t.Run("Get retrieves correct values", func(t *testing.T) {
-		args := NewToolCallFunctionArguments()
-		args.Set("key1", "value1")
-		args.Set("key2", 42)
-
-		v, ok := args.Get("key1")
-		assert.True(t, ok)
-		assert.Equal(t, "value1", v)
-
-		v, ok = args.Get("key2")
-		assert.True(t, ok)
-		assert.Equal(t, 42, v)
-
-		_, ok = args.Get("nonexistent")
-		assert.False(t, ok)
-	})
-
-	t.Run("Len returns correct count", func(t *testing.T) {
-		args := NewToolCallFunctionArguments()
-		assert.Equal(t, 0, args.Len())
-
-		args.Set("a", 1)
-		assert.Equal(t, 1, args.Len())
-
-		args.Set("b", 2)
-		assert.Equal(t, 2, args.Len())
-	})
-
-	t.Run("empty args marshal to empty object", func(t *testing.T) {
-		args := NewToolCallFunctionArguments()
-		data, err := json.Marshal(args)
-		require.NoError(t, err)
-		assert.Equal(t, `{}`, string(data))
-	})
-
-	t.Run("zero value args marshal to empty object", func(t *testing.T) {
-		var args ToolCallFunctionArguments
-		assert.Equal(t, "{}", args.String())
-	})
-}
-
-func TestToolPropertiesMap_OrderPreservation(t *testing.T) {
-	t.Run("marshal preserves insertion order", func(t *testing.T) {
-		props := NewToolPropertiesMap()
-		props.Set("zebra", ToolProperty{Type: PropertyType{"string"}})
-		props.Set("apple", ToolProperty{Type: PropertyType{"number"}})
-		props.Set("mango", ToolProperty{Type: PropertyType{"boolean"}})
-
-		data, err := json.Marshal(props)
-		require.NoError(t, err)
-
-		// Should preserve insertion order, not alphabetical
-		expected := `{"zebra":{"type":"string"},"apple":{"type":"number"},"mango":{"type":"boolean"}}`
-		assert.Equal(t, expected, string(data))
-	})
-
-	t.Run("unmarshal preserves JSON order", func(t *testing.T) {
-		jsonData := `{"zebra":{"type":"string"},"apple":{"type":"number"},"mango":{"type":"boolean"}}`
-
-		var props ToolPropertiesMap
-		err := json.Unmarshal([]byte(jsonData), &props)
-		require.NoError(t, err)
-
-		// Verify iteration order matches JSON order
-		var keys []string
-		for k := range props.All() {
-			keys = append(keys, k)
-		}
-		assert.Equal(t, []string{"zebra", "apple", "mango"}, keys)
-	})
-
-	t.Run("round trip preserves order", func(t *testing.T) {
-		original := `{"z":{"type":"string"},"a":{"type":"number"},"m":{"type":"boolean"}}`
-
-		var props ToolPropertiesMap
-		err := json.Unmarshal([]byte(original), &props)
-		require.NoError(t, err)
-
-		data, err := json.Marshal(props)
-		require.NoError(t, err)
-
-		assert.Equal(t, original, string(data))
-	})
-
-	t.Run("Get retrieves correct values", func(t *testing.T) {
-		props := NewToolPropertiesMap()
-		props.Set("name", ToolProperty{Type: PropertyType{"string"}, Description: "The name"})
-		props.Set("age", ToolProperty{Type: PropertyType{"integer"}, Description: "The age"})
-
-		v, ok := props.Get("name")
-		assert.True(t, ok)
-		assert.Equal(t, "The name", v.Description)
-
-		v, ok = props.Get("age")
-		assert.True(t, ok)
-		assert.Equal(t, "The age", v.Description)
-
-		_, ok = props.Get("nonexistent")
-		assert.False(t, ok)
-	})
-
-	t.Run("Len returns correct count", func(t *testing.T) {
-		props := NewToolPropertiesMap()
-		assert.Equal(t, 0, props.Len())
-
-		props.Set("a", ToolProperty{})
-		assert.Equal(t, 1, props.Len())
-
-		props.Set("b", ToolProperty{})
-		assert.Equal(t, 2, props.Len())
-	})
-
-	t.Run("nil props marshal to null", func(t *testing.T) {
-		var props *ToolPropertiesMap
-		data, err := json.Marshal(props)
-		require.NoError(t, err)
-		assert.Equal(t, `null`, string(data))
-	})
-
-	t.Run("ToMap returns regular map", func(t *testing.T) {
-		props := NewToolPropertiesMap()
-		props.Set("a", ToolProperty{Type: PropertyType{"string"}})
-		props.Set("b", ToolProperty{Type: PropertyType{"number"}})
-
-		m := props.ToMap()
-		assert.Equal(t, 2, len(m))
-		assert.Equal(t, PropertyType{"string"}, m["a"].Type)
-		assert.Equal(t, PropertyType{"number"}, m["b"].Type)
-	})
-}
-
-func TestToolCallFunctionArguments_ComplexValues(t *testing.T) {
-	t.Run("nested objects preserve order", func(t *testing.T) {
-		jsonData := `{"outer":{"z":1,"a":2},"simple":"value"}`
-
-		var args ToolCallFunctionArguments
-		err := json.Unmarshal([]byte(jsonData), &args)
-		require.NoError(t, err)
-
-		// Outer keys should be in order
-		var keys []string
-		for k := range args.All() {
-			keys = append(keys, k)
-		}
-		assert.Equal(t, []string{"outer", "simple"}, keys)
-	})
-
-	t.Run("arrays as values", func(t *testing.T) {
-		args := NewToolCallFunctionArguments()
-		args.Set("items", []string{"a", "b", "c"})
-		args.Set("numbers", []int{1, 2, 3})
-
-		data, err := json.Marshal(args)
-		require.NoError(t, err)
-
-		assert.Equal(t, `{"items":["a","b","c"],"numbers":[1,2,3]}`, string(data))
-	})
-}
-
-func TestToolPropertiesMap_NestedProperties(t *testing.T) {
-	t.Run("nested properties preserve order", func(t *testing.T) {
-		props := NewToolPropertiesMap()
-
-		nestedProps := NewToolPropertiesMap()
-		nestedProps.Set("z_field", ToolProperty{Type: PropertyType{"string"}})
-		nestedProps.Set("a_field", ToolProperty{Type: PropertyType{"number"}})
-
-		props.Set("outer", ToolProperty{
-			Type:       PropertyType{"object"},
-			Properties: nestedProps,
-		})
-
-		data, err := json.Marshal(props)
-		require.NoError(t, err)
-
-		// Both outer and inner should preserve order
-		expected := `{"outer":{"type":"object","properties":{"z_field":{"type":"string"},"a_field":{"type":"number"}}}}`
-		assert.Equal(t, expected, string(data))
-	})
-}

app/cmd/app/app.go

@@ -273,6 +273,10 @@ func main() {
 		Handler: uiServer.Handler(),
 	}
 
+	if _, err := uiServer.UserData(ctx); err != nil {
+		slog.Warn("failed to load user data", "error", err)
+	}
+
 	// Start the UI server
 	slog.Info("starting ui server", "port", port)
 	go func() {
@@ -316,17 +320,6 @@ func main() {
 		slog.Debug("no URL scheme request to handle")
 	}
 
-	go func() {
-		slog.Debug("waiting for ollama server to be ready")
-		if err := ui.WaitForServer(ctx, 10*time.Second); err != nil {
-			slog.Warn("ollama server not ready, continuing anyway", "error", err)
-		}
-
-		if _, err := uiServer.UserData(ctx); err != nil {
-			slog.Warn("failed to load user data", "error", err)
-		}
-	}()
-
 	osRun(cancel, hasCompletedFirstRun, startHidden)
 
 	slog.Info("shutting down desktop server")
@@ -368,7 +361,7 @@ func checkUserLoggedIn(uiServerPort int) bool {
 		return false
 	}
 
-	resp, err := http.Post(fmt.Sprintf("http://127.0.0.1:%d/api/me", uiServerPort), "application/json", nil)
+	resp, err := http.Get(fmt.Sprintf("http://127.0.0.1:%d/api/v1/me", uiServerPort))
 	if err != nil {
 		slog.Debug("failed to call local auth endpoint", "error", err)
 		return false

app/cmd/app/app_darwin.go

@@ -191,6 +191,13 @@ func LaunchNewApp() {
 	C.launchApp(appName)
 }
 
+// Send a request to the main app thread to load a UI page
+func sendUIRequestMessage(path string) {
+	p := C.CString(path)
+	defer C.free(unsafe.Pointer(p))
+	C.uiRequest(p)
+}
+
 func registerLaunchAgent(hasCompletedFirstRun bool) {
 	// Remove any stale Login Item registrations
 	C.unregisterSelfFromLoginItem()

app/cmd/app/app_windows.go

@@ -263,6 +263,11 @@ func createLoginShortcut() error {
 	return nil
 }
 
+// Send a request to the main app thread to load a UI page
+func sendUIRequestMessage(path string) {
+	wintray.SendUIRequestMessage(path)
+}
+
 func LaunchNewApp() {
 }
 

app/dialog/cocoa/dlg.m

@@ -169,47 +169,37 @@ DlgResult fileDlg(FileDlgParams* params) {
 	}
 	
 	NSArray* urls = [panel URLs];
-	if([urls count] == 0) {
-		return DLG_CANCEL;
-	}
-	
-	if(self->params->allowMultiple) {
+	if(self->params->allowMultiple && [urls count] >= 1) {
 		// For multiple files, we need to return all paths separated by null bytes
 		char* bufPtr = self->params->buf;
 		int remainingBuf = self->params->nbuf;
 		
-		// Calculate total required buffer size first
-		int totalSize = 0;
-		for(NSURL* url in urls) {
-			char tempBuf[PATH_MAX];
-			if(![url getFileSystemRepresentation:tempBuf maxLength:PATH_MAX]) {
-				return DLG_URLFAIL;
-			}
-			totalSize += strlen(tempBuf) + 1; // +1 for null terminator
-		}
-		totalSize += 1; // Final null terminator
+  // Calculate total required buffer size first
+  int totalSize = 0;
+  for(NSURL* url in urls) {
+      char tempBuf[PATH_MAX];
+      if(![url getFileSystemRepresentation:tempBuf maxLength:PATH_MAX]) {
+          return DLG_URLFAIL;
+      }
+      totalSize += strlen(tempBuf) + 1; // +1 for null terminator
+  }
+  totalSize += 1; // Final null terminator
 
-		if(totalSize > self->params->nbuf) {
-			// Not enough buffer space
-			return DLG_URLFAIL;
-		}
+  if(totalSize > self->params->nbuf) {
+      // Not enough buffer space
+      return DLG_URLFAIL;
+  }
 
-		// Now actually copy the paths (we know we have space)
-		bufPtr = self->params->buf;
-		for(NSURL* url in urls) {
-			char tempBuf[PATH_MAX];
-			[url getFileSystemRepresentation:tempBuf maxLength:PATH_MAX];
-			int pathLen = strlen(tempBuf);
-			strcpy(bufPtr, tempBuf);
-			bufPtr += pathLen + 1;
-		}
-		*bufPtr = '\0'; // Final null terminator
-	} else {
-		// Single file/directory selection - write path to buffer
-		NSURL* url = [urls firstObject];
-		if(![url getFileSystemRepresentation:self->params->buf maxLength:self->params->nbuf]) {
-			return DLG_URLFAIL;
-		}
+  // Now actually copy the paths (we know we have space)
+  bufPtr = self->params->buf;
+  for(NSURL* url in urls) {
+      char tempBuf[PATH_MAX];
+      [url getFileSystemRepresentation:tempBuf maxLength:PATH_MAX];
+      int pathLen = strlen(tempBuf);
+      strcpy(bufPtr, tempBuf);
+      bufPtr += pathLen + 1;
+  }
+  *bufPtr = '\0'; // Final null terminator
 	}
 	
 	return DLG_OK;

app/dialog/dlgs_windows.go

@@ -15,7 +15,7 @@ const multiFileBufferSize = w32.MAX_PATH * 10
 type WinDlgError int
 
 func (e WinDlgError) Error() string {
-	return fmt.Sprintf("CommDlgExtendedError: %#x", int(e))
+	return fmt.Sprintf("CommDlgExtendedError: %#x", e)
 }
 
 func err() error {

app/server/server.go

@@ -224,7 +224,9 @@ func (s *Server) cmd(ctx context.Context) (*exec.Cmd, error) {
 		if _, err := os.Stat(settings.Models); err == nil {
 			env["OLLAMA_MODELS"] = settings.Models
 		} else {
-			slog.Warn("models path not accessible, using default", "path", settings.Models, "err", err)
+			slog.Warn("models path not accessible, clearing models setting", "path", settings.Models, "err", err)
+			settings.Models = ""
+			s.store.SetSettings(settings)
 		}
 	}
 	if settings.ContextLength > 0 {

app/ui/app/codegen/gotypes.gen.ts

@@ -469,24 +469,26 @@ export class HealthResponse {
 }
 export class User {
     id: string;
-    email: string;
     name: string;
-    bio?: string;
-    avatarurl?: string;
-    firstname?: string;
-    lastname?: string;
-    plan?: string;
+    email: string;
+    avatarURL: string;
+    plan: string;
+    bio: string;
+    firstName: string;
+    lastName: string;
+    overThreshold: boolean;
 
     constructor(source: any = {}) {
         if ('string' === typeof source) source = JSON.parse(source);
         this.id = source["id"];
-        this.email = source["email"];
         this.name = source["name"];
-        this.bio = source["bio"];
-        this.avatarurl = source["avatarurl"];
-        this.firstname = source["firstname"];
-        this.lastname = source["lastname"];
+        this.email = source["email"];
+        this.avatarURL = source["avatarURL"];
         this.plan = source["plan"];
+        this.bio = source["bio"];
+        this.firstName = source["firstName"];
+        this.lastName = source["lastName"];
+        this.overThreshold = source["overThreshold"];
     }
 }
 export class Attachment {

app/ui/app/src/api.ts

@@ -15,7 +15,7 @@ import {
 import { parseJsonlFromResponse } from "./util/jsonl-parsing";
 import { ollamaClient as ollama } from "./lib/ollama-client";
 import type { ModelResponse } from "ollama/browser";
-import { API_BASE, OLLAMA_DOT_COM } from "./lib/config";
+import { API_BASE } from "./lib/config";
 
 // Extend Model class with utility methods
 declare module "@/gotypes" {
@@ -27,6 +27,7 @@ declare module "@/gotypes" {
 Model.prototype.isCloud = function (): boolean {
   return this.model.endsWith("cloud");
 };
+
 // Helper function to convert Uint8Array to base64
 function uint8ArrayToBase64(uint8Array: Uint8Array): string {
   const chunkSize = 0x8000; // 32KB chunks to avoid stack overflow
@@ -41,50 +42,44 @@ function uint8ArrayToBase64(uint8Array: Uint8Array): string {
 }
 
 export async function fetchUser(): Promise<User | null> {
-  const response = await fetch(`${API_BASE}/api/me`, {
-    method: "POST",
-    headers: {
-      "Content-Type": "application/json",
-    },
-  });
+  try {
+    const response = await fetch(`${API_BASE}/api/v1/me`, {
+      method: "GET",
+      headers: {
+        "Content-Type": "application/json",
+      },
+    });
 
-  if (response.ok) {
-    const userData: User = await response.json();
-
-    if (userData.avatarurl && !userData.avatarurl.startsWith("http")) {
-      userData.avatarurl = `${OLLAMA_DOT_COM}${userData.avatarurl}`;
+    if (response.ok) {
+      const userData: User = await response.json();
+      return userData;
     }
 
-    return userData;
-  }
-
-  if (response.status === 401 || response.status === 403) {
+    return null;
+  } catch (error) {
+    console.error("Error fetching user:", error);
     return null;
   }
-
-  throw new Error(`Failed to fetch user: ${response.status}`);
 }
 
 export async function fetchConnectUrl(): Promise<string> {
-  const response = await fetch(`${API_BASE}/api/me`, {
-    method: "POST",
+  const response = await fetch(`${API_BASE}/api/v1/connect`, {
+    method: "GET",
     headers: {
       "Content-Type": "application/json",
     },
   });
 
-  if (response.status === 401) {
-    const data = await response.json();
-    if (data.signin_url) {
-      return data.signin_url;
-    }
+  if (!response.ok) {
+    throw new Error("Failed to fetch connect URL");
   }
 
-  throw new Error("Failed to fetch connect URL");
+  const data = await response.json();
+  return data.connect_url;
 }
 
 export async function disconnectUser(): Promise<void> {
-  const response = await fetch(`${API_BASE}/api/signout`, {
+  const response = await fetch(`${API_BASE}/api/v1/disconnect`, {
     method: "POST",
     headers: {
       "Content-Type": "application/json",
@@ -209,10 +204,12 @@ export async function* sendMessage(
     data: uint8ArrayToBase64(att.data),
   }));
 
-  // Send think parameter when it's explicitly set (true, false, or a non-empty string).
+  // Only send think parameter when actually requesting thinking
+  // Don't send false as it causes issues with some providers
   const shouldSendThink =
     think !== undefined &&
-    (typeof think === "boolean" || (typeof think === "string" && think !== ""));
+    ((typeof think === "boolean" && think) ||
+      (typeof think === "string" && think !== ""));
 
   const response = await fetch(`${API_BASE}/api/v1/chat/${chatId}`, {
     method: "POST",
@@ -394,8 +391,7 @@ export async function getInferenceCompute(): Promise<InferenceCompute[]> {
 
 export async function fetchHealth(): Promise<boolean> {
   try {
-    // Use the /api/version endpoint as a health check
-    const response = await fetch(`${API_BASE}/api/version`, {
+    const response = await fetch(`${API_BASE}/api/v1/health`, {
       method: "GET",
       headers: {
         "Content-Type": "application/json",
@@ -404,8 +400,7 @@ export async function fetchHealth(): Promise<boolean> {
 
     if (response.ok) {
       const data = await response.json();
-      // If we get a version back, the server is healthy
-      return !!data.version;
+      return data.healthy || false;
     }
 
     return false;

app/ui/app/src/components/Settings.tsx

@@ -299,9 +299,9 @@ export default function Settings() {
                         </Button>
                       </div>
                     </div>
-                    {user?.avatarurl && (
+                    {user?.avatarURL && (
                       <img
-                        src={user.avatarurl}
+                        src={user.avatarURL}
                         alt={user?.name}
                         className="h-10 w-10 rounded-full bg-neutral-200 dark:bg-neutral-700 flex-shrink-0"
                         onError={(e) => {

app/ui/app/src/components/Thinking.tsx

@@ -50,33 +50,21 @@ export default function Thinking({
   // Position content to show bottom when collapsed
   useEffect(() => {
     if (isCollapsed && contentRef.current && wrapperRef.current) {
-      requestAnimationFrame(() => {
-        if (!contentRef.current || !wrapperRef.current) return;
-
-        const contentHeight = contentRef.current.scrollHeight;
-        const wrapperHeight = wrapperRef.current.clientHeight;
-        if (contentHeight > wrapperHeight) {
-          const translateY = -(contentHeight - wrapperHeight);
-          contentRef.current.style.transform = `translateY(${translateY}px)`;
-          setHasOverflow(true);
-        } else {
-          contentRef.current.style.transform = "translateY(0)";
-          setHasOverflow(false);
-        }
-      });
+      const contentHeight = contentRef.current.scrollHeight;
+      const wrapperHeight = wrapperRef.current.clientHeight;
+      if (contentHeight > wrapperHeight) {
+        const translateY = -(contentHeight - wrapperHeight);
+        contentRef.current.style.transform = `translateY(${translateY}px)`;
+        setHasOverflow(true);
+      } else {
+        setHasOverflow(false);
+      }
     } else if (contentRef.current) {
       contentRef.current.style.transform = "translateY(0)";
       setHasOverflow(false);
     }
   }, [thinking, isCollapsed]);
 
-  useEffect(() => {
-    if (activelyThinking && wrapperRef.current && !isCollapsed) {
-      // When expanded and actively thinking, scroll to bottom
-      wrapperRef.current.scrollTop = wrapperRef.current.scrollHeight;
-    }
-  }, [thinking, activelyThinking, isCollapsed]);
-
   const handleToggle = () => {
     setIsCollapsed(!isCollapsed);
     setHasUserInteracted(true);

app/ui/app/src/hooks/useChats.ts

@@ -7,7 +7,6 @@ import { createQueryBatcher } from "./useQueryBatcher";
 import { useRefetchModels } from "./useModels";
 import { useStreamingContext } from "@/contexts/StreamingContext";
 import { useSettings } from "./useSettings";
-import { getModelCapabilities } from "@/api";
 
 export const useChats = () => {
   return useQuery({
@@ -607,24 +606,6 @@ export const useSendMessage = (chatId: string) => {
               queryClient.setQueryData(["staleModels"], newStaleMap);
 
               queryClient.invalidateQueries({ queryKey: ["models"] });
-
-              // Fetch fresh capabilities for the downloaded model
-              getModelCapabilities(selectedModel.model)
-                .then((capabilities) => {
-                  queryClient.setQueryData(
-                    ["modelCapabilities", selectedModel.model],
-                    capabilities,
-                  );
-                })
-                .catch((error) => {
-                  console.error(
-                    "Failed to fetch capabilities after download:",
-                    error,
-                  );
-                  queryClient.invalidateQueries({
-                    queryKey: ["modelCapabilities", selectedModel.model],
-                  });
-                });
             }
             break;
           }

app/ui/app/src/hooks/useDownloadModel.ts

@@ -0,0 +1,114 @@
+import { useMutation, useQueryClient } from "@tanstack/react-query";
+import { useState } from "react";
+import { pullModel } from "@/api";
+import { useSelectedModel } from "./useSelectedModel";
+import { useSettings } from "./useSettings";
+
+interface DownloadProgress {
+  status: string;
+  digest?: string;
+  total?: number;
+  completed?: number;
+  done?: boolean;
+}
+
+export function useDownloadModel(chatId?: string) {
+  const queryClient = useQueryClient();
+  const { selectedModel } = useSelectedModel(chatId);
+  const { setSettings } = useSettings();
+  const [downloadProgress, setDownloadProgress] =
+    useState<DownloadProgress | null>(null);
+  const [abortController, setAbortController] =
+    useState<AbortController | null>(null);
+  const [downloadingChatIds, setDownloadingChatIds] = useState<Set<string>>(
+    new Set(),
+  );
+
+  const mutation = useMutation({
+    mutationFn: async (modelName: string) => {
+      const controller = new AbortController();
+      setAbortController(controller);
+      setDownloadProgress({ status: "Starting download..." });
+      if (chatId) {
+        setDownloadingChatIds((prev) => new Set(prev).add(chatId));
+      }
+
+      try {
+        for await (const progress of pullModel(modelName, controller.signal)) {
+          setDownloadProgress(progress);
+
+          if (progress.status === "success") {
+            // Update selected model to indicate it's now available locally
+            if (selectedModel && selectedModel.model === modelName) {
+              setSettings({ SelectedModel: modelName });
+            }
+            // Invalidate models query to refresh the list
+            await queryClient.invalidateQueries({ queryKey: ["models"] });
+            break;
+          }
+        }
+      } finally {
+        setAbortController(null);
+        if (chatId) {
+          setDownloadingChatIds((prev) => {
+            const newSet = new Set(prev);
+            newSet.delete(chatId);
+            return newSet;
+          });
+        }
+      }
+    },
+    onSuccess: () => {
+      setDownloadProgress(null);
+      if (chatId) {
+        setDownloadingChatIds((prev) => {
+          const newSet = new Set(prev);
+          newSet.delete(chatId);
+          return newSet;
+        });
+      }
+    },
+    onError: (error: Error) => {
+      const status =
+        error.name === "AbortError" ? "Download cancelled" : "Download failed";
+      setDownloadProgress({ status, done: true });
+
+      // Clear error message after delay
+      const delay = error.name === "AbortError" ? 1500 : 3000;
+      setTimeout(() => {
+        setDownloadProgress(null);
+        if (chatId) {
+          setDownloadingChatIds((prev) => {
+            const newSet = new Set(prev);
+            newSet.delete(chatId);
+            return newSet;
+          });
+        }
+      }, delay);
+    },
+  });
+
+  const cancelDownload = () => {
+    if (abortController) {
+      abortController.abort();
+      setAbortController(null);
+      if (chatId) {
+        setDownloadingChatIds((prev) => {
+          const newSet = new Set(prev);
+          newSet.delete(chatId);
+          return newSet;
+        });
+      }
+    }
+  };
+
+  return {
+    downloadModel: mutation.mutate,
+    isDownloading:
+      mutation.isPending && chatId ? downloadingChatIds.has(chatId) : false,
+    downloadProgress:
+      chatId && downloadingChatIds.has(chatId) ? downloadProgress : null,
+    error: mutation.error,
+    cancelDownload,
+  };
+}

app/ui/app/src/hooks/useUser.ts

@@ -1,20 +1,29 @@
 import { useQuery, useMutation, useQueryClient } from "@tanstack/react-query";
+import { useEffect, useState } from "react";
 import { fetchUser, fetchConnectUrl, disconnectUser } from "@/api";
 
 export function useUser() {
   const queryClient = useQueryClient();
+  const [initialDataLoaded, setInitialDataLoaded] = useState(false);
+
+  // Wait for initial data to be loaded
+  useEffect(() => {
+    const initialPromise = window.__initialUserDataPromise;
+    if (initialPromise) {
+      initialPromise.finally(() => {
+        setInitialDataLoaded(true);
+      });
+    } else {
+      setInitialDataLoaded(true);
+    }
+  }, []);
 
   const userQuery = useQuery({
     queryKey: ["user"],
-    queryFn: async () => {
-      const result = await fetchUser();
-      return result;
-    },
+    queryFn: () => fetchUser(),
     staleTime: 5 * 60 * 1000, // Consider data stale after 5 minutes
     gcTime: 10 * 60 * 1000, // Keep in cache for 10 minutes
-    retry: 10,
-    retryDelay: (attemptIndex) => Math.min(500 * attemptIndex, 2000),
-    refetchOnMount: true, // Always fetch when component mounts
+    initialData: null, // Start with null to prevent flashing
   });
 
   // Mutation to refresh user data
@@ -40,15 +49,14 @@ export function useUser() {
     },
   });
 
-  const isLoading = userQuery.isLoading || userQuery.isFetching;
-  const isAuthenticated = Boolean(userQuery.data?.name);
-
   return {
     user: userQuery.data,
-    isLoading,
+    isLoading:
+      !initialDataLoaded ||
+      (userQuery.isLoading && userQuery.data === undefined), // Show loading until initial data is loaded
     isError: userQuery.isError,
     error: userQuery.error,
-    isAuthenticated,
+    isAuthenticated: Boolean(userQuery.data?.name),
     refreshUser: refreshUser.mutate,
     isRefreshing: refreshUser.isPending,
     refetchUser: userQuery.refetch,

app/ui/app/src/lib/config.ts

@@ -8,6 +8,3 @@ export const API_BASE = import.meta.env.DEV ? DEV_API_URL : "";
 export const OLLAMA_HOST = import.meta.env.DEV
   ? DEV_API_URL
   : window.location.origin;
-
-export const OLLAMA_DOT_COM =
-  import.meta.env.VITE_OLLAMA_DOT_COM_URL || "https://ollama.com";

app/ui/app/src/lib/highlighter.ts

@@ -147,7 +147,6 @@ export const highlighterPromise = createHighlighter({
     "c",
     "cpp",
     "sql",
-    "swift",
     "yaml",
     "markdown",
   ],

app/ui/app/src/main.tsx

@@ -5,6 +5,13 @@ import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
 import { routeTree } from "./routeTree.gen";
 import { fetchUser } from "./api";
 import { StreamingProvider } from "./contexts/StreamingContext";
+import { User } from "@/gotypes";
+
+declare global {
+  interface Window {
+    __initialUserDataPromise?: Promise<User | null>;
+  }
+}
 
 const queryClient = new QueryClient({
   defaultOptions: {
@@ -17,11 +24,27 @@ const queryClient = new QueryClient({
   },
 });
 
-fetchUser().then((userData) => {
-  if (userData) {
+// Track initial user data fetch
+let initialUserDataPromise: Promise<User | null> | null = null;
+
+// Initialize user data on app startup
+const initializeUserData = async () => {
+  try {
+    const userData = await fetchUser();
     queryClient.setQueryData(["user"], userData);
+    return userData;
+  } catch (error) {
+    console.error("Error initializing user data:", error);
+    queryClient.setQueryData(["user"], null);
+    return null;
   }
-});
+};
+
+// Start initialization immediately and track the promise
+initialUserDataPromise = initializeUserData();
+
+// Export the promise so hooks can await it
+window.__initialUserDataPromise = initialUserDataPromise;
 
 const router = createRouter({
   routeTree,

app/ui/responses/types.go

@@ -101,14 +101,15 @@ type HealthResponse struct {
 }
 
 type User struct {
-	ID        string `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"`
+	ID            string `json:"id"`
+	Name          string `json:"name"`
+	Email         string `json:"email"`
+	AvatarURL     string `json:"avatarURL"`
+	Plan          string `json:"plan"`
+	Bio           string `json:"bio"`
+	FirstName     string `json:"firstName"`
+	LastName      string `json:"lastName"`
+	OverThreshold bool   `json:"overThreshold"`
 }
 
 type Attachment struct {

app/ui/ui.go

@@ -12,17 +12,18 @@ import (
 	"log/slog"
 	"net/http"
 	"net/http/httputil"
+	"net/url"
 	"os"
 	"runtime"
 	"runtime/debug"
 	"slices"
 	"strconv"
 	"strings"
-	"sync"
 	"time"
 
 	"github.com/google/uuid"
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/app/auth"
 	"github.com/ollama/ollama/app/server"
 	"github.com/ollama/ollama/app/store"
 	"github.com/ollama/ollama/app/tools"
@@ -117,66 +118,40 @@ func (s *Server) log() *slog.Logger {
 
 // ollamaProxy creates a reverse proxy handler to the Ollama server
 func (s *Server) ollamaProxy() http.Handler {
-	var (
-		proxy   http.Handler
-		proxyMu sync.Mutex
-	)
+	ollamaHost := os.Getenv("OLLAMA_HOST")
+	if ollamaHost == "" {
+		ollamaHost = "http://127.0.0.1:11434"
+	}
 
-	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-		proxyMu.Lock()
-		p := proxy
-		proxyMu.Unlock()
+	if !strings.HasPrefix(ollamaHost, "http://") && !strings.HasPrefix(ollamaHost, "https://") {
+		ollamaHost = "http://" + ollamaHost
+	}
 
-		if p == nil {
-			proxyMu.Lock()
-			if proxy == nil {
-				var err error
-				for i := range 2 {
-					if i > 0 {
-						s.log().Warn("ollama server not ready, retrying", "attempt", i+1)
-						time.Sleep(1 * time.Second)
-					}
+	target, err := url.Parse(ollamaHost)
+	if err != nil {
+		s.log().Error("failed to parse OLLAMA_HOST", "error", err, "host", ollamaHost)
+		return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+			http.Error(w, "failed to configure proxy", http.StatusInternalServerError)
+		})
+	}
 
-					err = WaitForServer(context.Background(), 10*time.Second)
-					if err == nil {
-						break
-					}
-				}
+	s.log().Info("configuring ollama proxy", "target", target.String())
 
-				if err != nil {
-					proxyMu.Unlock()
-					s.log().Error("ollama server not ready after retries", "error", err)
-					http.Error(w, "Ollama server is not ready", http.StatusServiceUnavailable)
-					return
-				}
+	proxy := httputil.NewSingleHostReverseProxy(target)
 
-				target := envconfig.Host()
-				s.log().Info("configuring ollama proxy", "target", target.String())
+	originalDirector := proxy.Director
+	proxy.Director = func(req *http.Request) {
+		originalDirector(req)
+		req.Host = target.Host
+		s.log().Debug("proxying request", "method", req.Method, "path", req.URL.Path, "target", target.Host)
+	}
 
-				newProxy := httputil.NewSingleHostReverseProxy(target)
+	proxy.ErrorHandler = func(w http.ResponseWriter, r *http.Request, err error) {
+		s.log().Error("proxy error", "error", err, "path", r.URL.Path, "target", target.String())
+		http.Error(w, "proxy error: "+err.Error(), http.StatusBadGateway)
+	}
 
-				originalDirector := newProxy.Director
-				newProxy.Director = func(req *http.Request) {
-					originalDirector(req)
-					req.Host = target.Host
-					s.log().Debug("proxying request", "method", req.Method, "path", req.URL.Path, "target", target.Host)
-				}
-
-				newProxy.ErrorHandler = func(w http.ResponseWriter, r *http.Request, err error) {
-					s.log().Error("proxy error", "error", err, "path", r.URL.Path, "target", target.String())
-					http.Error(w, "proxy error: "+err.Error(), http.StatusBadGateway)
-				}
-
-				proxy = newProxy
-				p = newProxy
-			} else {
-				p = proxy
-			}
-			proxyMu.Unlock()
-		}
-
-		p.ServeHTTP(w, r)
-	})
+	return proxy
 }
 
 type errHandlerFunc func(http.ResponseWriter, *http.Request) error
@@ -289,10 +264,11 @@ func (s *Server) Handler() http.Handler {
 	ollamaProxy := s.ollamaProxy()
 	mux.Handle("GET /api/tags", ollamaProxy)
 	mux.Handle("POST /api/show", ollamaProxy)
-	mux.Handle("GET /api/version", ollamaProxy)
-	mux.Handle("HEAD /api/version", ollamaProxy)
-	mux.Handle("POST /api/me", ollamaProxy)
-	mux.Handle("POST /api/signout", ollamaProxy)
+
+	mux.Handle("GET /api/v1/me", handle(s.me))
+	mux.Handle("POST /api/v1/disconnect", handle(s.disconnect))
+	mux.Handle("GET /api/v1/connect", handle(s.connectURL))
+	mux.Handle("GET /api/v1/health", handle(s.health))
 
 	// React app - catch all non-API routes and serve the React app
 	mux.Handle("GET /", s.appHandler())
@@ -362,7 +338,7 @@ func (s *Server) doSelfSigned(ctx context.Context, method, path string) (*http.R
 }
 
 // UserData fetches user data from ollama.com API for the current ollama key
-func (s *Server) UserData(ctx context.Context) (*api.UserResponse, error) {
+func (s *Server) UserData(ctx context.Context) (*responses.User, error) {
 	resp, err := s.doSelfSigned(ctx, http.MethodPost, "/api/me")
 	if err != nil {
 		return nil, fmt.Errorf("failed to call ollama.com/api/me: %w", err)
@@ -373,7 +349,7 @@ func (s *Server) UserData(ctx context.Context) (*api.UserResponse, error) {
 		return nil, fmt.Errorf("unexpected status code: %d", resp.StatusCode)
 	}
 
-	var user api.UserResponse
+	var user responses.User
 	if err := json.NewDecoder(resp.Body).Decode(&user); err != nil {
 		return nil, fmt.Errorf("failed to parse user response: %w", err)
 	}
@@ -392,27 +368,29 @@ func (s *Server) UserData(ctx context.Context) (*api.UserResponse, error) {
 	return &user, nil
 }
 
-// WaitForServer waits for the Ollama server to be ready
-func WaitForServer(ctx context.Context, timeout time.Duration) error {
-	deadline := time.Now().Add(timeout)
-	for time.Now().Before(deadline) {
+func waitForServer(ctx context.Context) error {
+	timeout := time.Now().Add(10 * time.Second)
+	// TODO: this avoids an error on first load of the app
+	// however we should either show a loading state or
+	// wait for the Ollama server to be ready before redirecting
+	for {
 		c, err := api.ClientFromEnvironment()
 		if err != nil {
 			return err
 		}
 		if _, err := c.Version(ctx); err == nil {
-			slog.Debug("ollama server is ready")
-			return nil
+			break
+		}
+		if time.Now().After(timeout) {
+			return fmt.Errorf("timeout waiting for Ollama server to be ready")
 		}
 		time.Sleep(10 * time.Millisecond)
 	}
-	return errors.New("timeout waiting for Ollama server to be ready")
+	return nil
 }
 
 func (s *Server) createChat(w http.ResponseWriter, r *http.Request) error {
-	if err := WaitForServer(r.Context(), 10*time.Second); err != nil {
-		return err
-	}
+	waitForServer(r.Context())
 
 	id, err := uuid.NewV7()
 	if err != nil {
@@ -997,7 +975,7 @@ func (s *Server) chat(w http.ResponseWriter, r *http.Request) error {
 				for _, toolCall := range res.Message.ToolCalls {
 					// continues loop as tools were executed
 					toolsExecuted = true
-					result, content, err := registry.Execute(ctx, toolCall.Function.Name, toolCall.Function.Arguments.ToMap())
+					result, content, err := registry.Execute(ctx, toolCall.Function.Name, toolCall.Function.Arguments)
 					if err != nil {
 						errContent := fmt.Sprintf("Error: %v", err)
 						toolErrMsg := store.NewMessage("tool", errContent, nil)
@@ -1460,6 +1438,129 @@ func (s *Server) settings(w http.ResponseWriter, r *http.Request) error {
 	})
 }
 
+func (s *Server) me(w http.ResponseWriter, r *http.Request) error {
+	if r.Method != http.MethodGet {
+		http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
+		return nil
+	}
+
+	user, err := s.UserData(r.Context())
+	if err != nil {
+		// If fetching from API fails, try to return cached user data if available
+		if cachedUser, cacheErr := s.Store.User(); cacheErr == nil && cachedUser != nil {
+			s.log().Info("API request failed, returning cached user data", "error", err)
+			responseUser := &responses.User{
+				Name:  cachedUser.Name,
+				Email: cachedUser.Email,
+				Plan:  cachedUser.Plan,
+			}
+			w.Header().Set("Content-Type", "application/json")
+			w.WriteHeader(http.StatusOK)
+			return json.NewEncoder(w).Encode(responseUser)
+		}
+
+		s.log().Error("failed to get user data", "error", err)
+		w.WriteHeader(http.StatusInternalServerError)
+		return json.NewEncoder(w).Encode(responses.Error{
+			Error: "failed to get user data",
+		})
+	}
+
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(http.StatusOK)
+	return json.NewEncoder(w).Encode(user)
+}
+
+func (s *Server) disconnect(w http.ResponseWriter, r *http.Request) error {
+	if r.Method != http.MethodPost {
+		http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
+		return nil
+	}
+
+	if err := s.Store.ClearUser(); err != nil {
+		s.log().Warn("failed to clear cached user data", "error", err)
+	}
+
+	// Get the SSH public key to encode for the delete request
+	pubKey, err := ollamaAuth.GetPublicKey()
+	if err != nil {
+		s.log().Error("failed to get public key", "error", err)
+		w.WriteHeader(http.StatusInternalServerError)
+		return json.NewEncoder(w).Encode(responses.Error{
+			Error: "failed to get public key",
+		})
+	}
+
+	// Encode the key using base64 URL encoding
+	encodedKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
+
+	// Call the /api/user/keys/{encodedKey} endpoint with DELETE
+	resp, err := s.doSelfSigned(r.Context(), http.MethodDelete, fmt.Sprintf("/api/user/keys/%s", encodedKey))
+	if err != nil {
+		s.log().Error("failed to call ollama.com/api/user/keys", "error", err)
+		w.WriteHeader(http.StatusInternalServerError)
+		return json.NewEncoder(w).Encode(responses.Error{
+			Error: "failed to disconnect from ollama.com",
+		})
+	}
+	defer resp.Body.Close()
+
+	if resp.StatusCode != http.StatusOK {
+		s.log().Error("disconnect request failed", "status", resp.StatusCode)
+		w.WriteHeader(http.StatusInternalServerError)
+		return json.NewEncoder(w).Encode(responses.Error{
+			Error: "failed to disconnect from ollama.com",
+		})
+	}
+
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(http.StatusOK)
+	return json.NewEncoder(w).Encode(map[string]string{"status": "disconnected"})
+}
+
+func (s *Server) connectURL(w http.ResponseWriter, r *http.Request) error {
+	if r.Method != http.MethodGet {
+		http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
+		return nil
+	}
+
+	connectURL, err := auth.BuildConnectURL(OllamaDotCom)
+	if err != nil {
+		s.log().Error("failed to build connect URL", "error", err)
+		w.WriteHeader(http.StatusInternalServerError)
+		return json.NewEncoder(w).Encode(responses.Error{
+			Error: "failed to build connect URL",
+		})
+	}
+
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(http.StatusOK)
+	return json.NewEncoder(w).Encode(map[string]string{
+		"connect_url": connectURL,
+	})
+}
+
+func (s *Server) health(w http.ResponseWriter, r *http.Request) error {
+	if r.Method != http.MethodGet {
+		http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
+		return nil
+	}
+
+	healthy := false
+	c, err := api.ClientFromEnvironment()
+	if err == nil {
+		if _, err := c.Version(r.Context()); err == nil {
+			healthy = true
+		}
+	}
+
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(http.StatusOK)
+	return json.NewEncoder(w).Encode(responses.HealthResponse{
+		Healthy: healthy,
+	})
+}
+
 func (s *Server) getInferenceCompute(w http.ResponseWriter, r *http.Request) error {
 	ctx, cancel := context.WithTimeout(r.Context(), 500*time.Millisecond)
 	defer cancel()
@@ -1558,13 +1659,13 @@ func convertToOllamaTool(toolSchema map[string]any) api.Tool {
 
 	tool.Function.Parameters.Type = "object"
 	tool.Function.Parameters.Required = []string{}
-	tool.Function.Parameters.Properties = api.NewToolPropertiesMap()
+	tool.Function.Parameters.Properties = make(map[string]api.ToolProperty)
 
 	if schemaProps, ok := toolSchema["schema"].(map[string]any); ok {
 		tool.Function.Parameters.Type = getStringFromMap(schemaProps, "type", "object")
 
 		if props, ok := schemaProps["properties"].(map[string]any); ok {
-			tool.Function.Parameters.Properties = api.NewToolPropertiesMap()
+			tool.Function.Parameters.Properties = make(map[string]api.ToolProperty)
 
 			for propName, propDef := range props {
 				if propMap, ok := propDef.(map[string]any); ok {
@@ -1572,7 +1673,7 @@ func convertToOllamaTool(toolSchema map[string]any) api.Tool {
 						Type:        api.PropertyType{getStringFromMap(propMap, "type", "string")},
 						Description: getStringFromMap(propMap, "description", ""),
 					}
-					tool.Function.Parameters.Properties.Set(propName, prop)
+					tool.Function.Parameters.Properties[propName] = prop
 				}
 			}
 		}

app/wintray/eventloop.go

@@ -158,16 +158,16 @@ func (t *winTray) wndProc(hWnd windows.Handle, message uint32, wParam, lParam ui
 	case uint32(UI_REQUEST_MSG_ID):
 		// Requests for the UI must always come from the main event thread
 		l := int(wParam)
-		path := unsafe.String((*byte)(unsafe.Pointer(lParam)), l) //nolint:govet,gosec
+		path := unsafe.String((*byte)(unsafe.Pointer(lParam)), l)
 		t.app.UIRun(path)
 	case WM_COPYDATA:
 		// Handle URL scheme requests from other instances
 		if lParam != 0 {
-			cds := (*COPYDATASTRUCT)(unsafe.Pointer(lParam)) //nolint:govet,gosec
-			if cds.DwData == 1 {                             // Our identifier for URL scheme messages
+			cds := (*COPYDATASTRUCT)(unsafe.Pointer(lParam))
+			if cds.DwData == 1 { // Our identifier for URL scheme messages
 				// Convert the data back to string
 				data := make([]byte, cds.CbData)
-				copy(data, (*[1 << 30]byte)(unsafe.Pointer(cds.LpData))[:cds.CbData:cds.CbData]) //nolint:govet,gosec
+				copy(data, (*[1 << 30]byte)(unsafe.Pointer(cds.LpData))[:cds.CbData:cds.CbData])
 				urlScheme := string(data)
 				handleURLSchemeRequest(urlScheme)
 				lResult = 1 // Return non-zero to indicate success

cmd/bench/README.md

@@ -15,7 +15,7 @@ A Go-based command-line tool for benchmarking Ollama models with configurable pa
 
 ```
 go build -o ollama-bench bench.go
-./ollama-bench -model gpt-oss:20b -epochs 6 -format csv
+./bench -model gpt-oss:20b -epochs 6 -format csv
 ```
 
 Using Go Run (without building)
@@ -29,32 +29,31 @@ go run bench.go -model gpt-oss:20b -epochs 3
 ### Basic Example
 
 ```
-./ollama-bench -model gemma3 -epochs 6
+./bench -model gemma3 -epochs 6
 ```
 
 ### Benchmark Multiple Models
 
 ```
-./ollama-bench -model gemma3,gemma3n -epochs 6 -max-tokens 100 -p "Write me a short story" | tee gemma.bench
+./bench -model gemma3,gemma3n -epochs 6 -max-tokens 100 -p "Write me a short story" | tee gemma.bench
 benchstat -col /name gemma.bench
 ```
 
 ### With Image Prompt
 
 ```
-./ollama-bench -model qwen3-vl -image photo.jpg -epochs 6 -max-tokens 100 -p "Describe this image"
+./bench -model qwen3-vl -image photo.jpg -epochs 6 -max-tokens 100 -p "Describe this image"
 ```
 
 ### Advanced Example
 
 ```
-./ollama-bench -model llama3 -epochs 10 -temperature 0.7 -max-tokens 500 -seed 42 -format csv -output results.csv
+./bench -model llama3 -epochs 10 -temperature 0.7 -max-tokens 500 -seed 42 -format csv -output results.csv
 ```
 
 ## Command Line Options
 
 | Option  	| Description | Default |
-|----------|-------------|---------|
 | -model	| Comma-separated list of models to benchmark	| (required)		|
 | -epochs	| Number of iterations per model		| 1			|
 | -max-tokens	| Maximum tokens for model response		| 0 (unlimited)		|

cmd/bench/bench.go

@@ -48,8 +48,8 @@ func OutputMetrics(w io.Writer, format string, metrics []Metrics, verbose bool)
 	case "benchstat":
 		if verbose {
 			printHeader := func() {
-				fmt.Fprintf(w, "sysname: %s\n", runtime.GOOS)
-				fmt.Fprintf(w, "machine: %s\n", runtime.GOARCH)
+				fmt.Printf("sysname: %s\n", runtime.GOOS)
+				fmt.Printf("machine: %s\n", runtime.GOARCH)
 			}
 			once.Do(printHeader)
 		}
@@ -147,17 +147,6 @@ func BenchmarkChat(fOpt flagOptions) error {
 		return err
 	}
 
-	var out io.Writer = os.Stdout
-	if fOpt.outputFile != nil && *fOpt.outputFile != "" {
-		f, err := os.OpenFile(*fOpt.outputFile, os.O_CREATE|os.O_WRONLY, 0o644)
-		if err != nil {
-			fmt.Fprintf(os.Stderr, "ERROR: cannot open output file %s: %v\n", *fOpt.outputFile, err)
-			return err
-		}
-		defer f.Close()
-		out = f
-	}
-
 	for _, model := range models {
 		for range *fOpt.epochs {
 			options := make(map[string]interface{})
@@ -252,14 +241,13 @@ func BenchmarkChat(fOpt flagOptions) error {
 				},
 			}
 
-			OutputMetrics(out, *fOpt.format, metrics, *fOpt.verbose)
+			OutputMetrics(os.Stdout, *fOpt.format, metrics, *fOpt.verbose)
 
 			if *fOpt.keepAlive > 0 {
 				time.Sleep(time.Duration(*fOpt.keepAlive*float64(time.Second)) + 200*time.Millisecond)
 			}
 		}
 	}
-
 	return nil
 }
 

cmd/cmd.go

@@ -45,9 +45,6 @@ import (
 	"github.com/ollama/ollama/types/model"
 	"github.com/ollama/ollama/types/syncmap"
 	"github.com/ollama/ollama/version"
-	xcmd "github.com/ollama/ollama/x/cmd"
-	"github.com/ollama/ollama/x/imagegen"
-	imagegenclient "github.com/ollama/ollama/x/imagegen/client"
 )
 
 const ConnectInstructions = "To sign in, navigate to:\n    %s\n\n"
@@ -98,11 +95,6 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 	filename, err := getModelfileName(cmd)
 	if os.IsNotExist(err) {
 		if filename == "" {
-			// No Modelfile found - check if current directory is an image gen model
-			if imagegen.IsTensorModelDir(".") {
-				quantize, _ := cmd.Flags().GetString("quantize")
-				return imagegenclient.CreateModel(args[0], ".", quantize, p)
-			}
 			reader = strings.NewReader("FROM .\n")
 		} else {
 			return errModelfileNotFound
@@ -464,7 +456,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	}
 
 	name := args[0]
-
 	info, err := func() (*api.ShowResponse, error) {
 		showReq := &api.ShowRequest{Name: name}
 		info, err := client.Show(cmd.Context(), showReq)
@@ -526,19 +517,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		return generateEmbedding(cmd, name, opts.Prompt, opts.KeepAlive, truncate, dimensions)
 	}
 
-	// Check if this is an image generation model
-	if slices.Contains(info.Capabilities, model.CapabilityImageGeneration) {
-		if opts.Prompt == "" && !interactive {
-			return errors.New("image generation models require a prompt. Usage: ollama run " + name + " \"your prompt here\"")
-		}
-		return imagegen.RunCLI(cmd, name, opts.Prompt, interactive, opts.KeepAlive)
-	}
-
-	// Check for experimental flag
-	isExperimental, _ := cmd.Flags().GetBool("experimental")
-	yoloMode, _ := cmd.Flags().GetBool("experimental-yolo")
-	enableWebsearch, _ := cmd.Flags().GetBool("experimental-websearch")
-
 	if interactive {
 		if err := loadOrUnloadModel(cmd, &opts); err != nil {
 			var sErr api.AuthorizationError
@@ -565,11 +543,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 			}
 		}
 
-		// Use experimental agent loop with tools
-		if isExperimental {
-			return xcmd.GenerateInteractive(cmd, opts.Model, opts.WordWrap, opts.Options, opts.Think, opts.HideThinking, opts.KeepAlive, yoloMode, enableWebsearch)
-		}
-
 		return generateInteractive(cmd, opts)
 	}
 	return generate(cmd, opts)
@@ -673,11 +646,7 @@ func PushHandler(cmd *cobra.Command, args []string) error {
 
 			bar, ok := bars[resp.Digest]
 			if !ok {
-				msg := resp.Status
-				if msg == "" {
-					msg = fmt.Sprintf("pushing %s...", resp.Digest[7:19])
-				}
-				bar = progress.NewBar(msg, resp.Total, resp.Completed)
+				bar = progress.NewBar(fmt.Sprintf("pushing %s...", resp.Digest[7:19]), resp.Total, resp.Completed)
 				bars[resp.Digest] = bar
 				p.Add(resp.Digest, bar)
 			}
@@ -974,9 +943,6 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 			rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
 		}
 		rows = append(rows, []string{"", "quantization", resp.Details.QuantizationLevel})
-		if resp.Requires != "" {
-			rows = append(rows, []string{"", "requires", resp.Requires})
-		}
 		return
 	})
 
@@ -1464,7 +1430,7 @@ func chat(cmd *cobra.Command, opts runOptions) (*api.Message, error) {
 		latest.Summary()
 	}
 
-	return &api.Message{Role: role, Thinking: thinkingContent.String(), Content: fullResponse.String()}, nil
+	return &api.Message{Role: role, Content: fullResponse.String()}, nil
 }
 
 func generate(cmd *cobra.Command, opts runOptions) error {
@@ -1785,12 +1751,6 @@ func NewCLI() *cobra.Command {
 	runCmd.Flags().Bool("hidethinking", false, "Hide thinking output (if provided)")
 	runCmd.Flags().Bool("truncate", false, "For embedding models: truncate inputs exceeding context length (default: true). Set --truncate=false to error instead")
 	runCmd.Flags().Int("dimensions", 0, "Truncate output embeddings to specified dimension (embedding models only)")
-	runCmd.Flags().Bool("experimental", false, "Enable experimental agent loop with tools")
-	runCmd.Flags().Bool("experimental-yolo", false, "Skip all tool approval prompts (use with caution)")
-	runCmd.Flags().Bool("experimental-websearch", false, "Enable web search tool in experimental mode")
-
-	// Image generation flags (width, height, steps, seed, etc.)
-	imagegen.RegisterFlags(runCmd)
 
 	stopCmd := &cobra.Command{
 		Use:     "stop MODEL",

cmd/cmd_test.go

@@ -291,31 +291,6 @@ Weigh anchor!
 			t.Errorf("unexpected output (-want +got):\n%s", diff)
 		}
 	})
-
-	t.Run("min version", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-			Requires: "0.14.0",
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture    test      
-    parameters      7B        
-    quantization    FP16      
-    requires        0.14.0    
-
-`
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
 }
 
 func TestDeleteHandler(t *testing.T) {
@@ -1547,79 +1522,6 @@ func TestRunOptions_Copy_ThinkValueVariants(t *testing.T) {
 	}
 }
 
-func TestShowInfoImageGen(t *testing.T) {
-	var b bytes.Buffer
-	err := showInfo(&api.ShowResponse{
-		Details: api.ModelDetails{
-			Family:            "ZImagePipeline",
-			ParameterSize:     "10.3B",
-			QuantizationLevel: "FP8",
-		},
-		Capabilities: []model.Capability{model.CapabilityImageGeneration},
-		Requires:     "0.14.0",
-	}, false, &b)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	expect := "  Model\n" +
-		"    architecture    ZImagePipeline    \n" +
-		"    parameters      10.3B             \n" +
-		"    quantization    FP8               \n" +
-		"    requires        0.14.0            \n" +
-		"\n" +
-		"  Capabilities\n" +
-		"    image    \n" +
-		"\n"
-	if diff := cmp.Diff(expect, b.String()); diff != "" {
-		t.Errorf("unexpected output (-want +got):\n%s", diff)
-	}
-}
-
-func TestPushProgressMessage(t *testing.T) {
-	tests := []struct {
-		name    string
-		status  string
-		digest  string
-		wantMsg string
-	}{
-		{
-			name:    "uses status when provided",
-			status:  "uploading model",
-			digest:  "sha256:abc123456789def",
-			wantMsg: "uploading model",
-		},
-		{
-			name:    "falls back to digest when status empty",
-			status:  "",
-			digest:  "sha256:abc123456789def",
-			wantMsg: "pushing abc123456789...",
-		},
-		{
-			name:    "handles short digest gracefully",
-			status:  "",
-			digest:  "sha256:abc",
-			wantMsg: "pushing sha256:abc...",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			msg := tt.status
-			if msg == "" {
-				if len(tt.digest) >= 19 {
-					msg = fmt.Sprintf("pushing %s...", tt.digest[7:19])
-				} else {
-					msg = fmt.Sprintf("pushing %s...", tt.digest)
-				}
-			}
-			if msg != tt.wantMsg {
-				t.Errorf("got %q, want %q", msg, tt.wantMsg)
-			}
-		})
-	}
-}
-
 func TestRunOptions_Copy_Independence(t *testing.T) {
 	// Test that modifications to original don't affect copy
 	originalThink := &api.ThinkValue{Value: "original"}

cmd/eval/README.md

@@ -0,0 +1,50 @@
+# eval
+
+Evaluation tool for testing Ollama models.
+
+## Usage
+
+Run all tests:
+
+```bash
+go run . -model llama3.2:latest
+```
+
+Run specific suite:
+
+```bash
+go run . -model llama3.2:latest -suite tool-calling-basic -v
+```
+
+List available suites:
+
+```bash
+go run . -list
+```
+
+## Adding Tests
+
+Edit `suites.go` to add new test suites. Each test needs:
+
+- `Name`: test identifier
+- `Prompt`: what to send to the model
+- `Check`: function to validate the response
+
+Example:
+
+```go
+{
+    Name:   "my-test",
+    Prompt: "What is 2+2?",
+    Check:  Contains("4"),
+}
+```
+
+Available check functions:
+
+- `HasResponse()` - response is non-empty
+- `Contains(s)` - response contains substring
+- `CallsTool(name)` - model called specific tool
+- `NoTools()` - model called no tools
+- `MinTools(n)` - model called at least n tools
+- `All(checks...)` - all checks pass

cmd/eval/eval.go

@@ -0,0 +1,151 @@
+package main
+
+import (
+	"context"
+	"strings"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+// Test is a single evaluation test
+type Test struct {
+	Name    string
+	Prompt  string
+	System  string
+	Tools   []api.Tool
+	Think   bool
+	Options map[string]any
+	Check   func(response string, tools []api.ToolCall) bool
+}
+
+// Suite is a collection of tests
+type Suite struct {
+	Name  string
+	Tests []Test
+}
+
+// Result holds test execution results
+type Result struct {
+	Name      string
+	Passed    bool
+	Error     error
+	Duration  time.Duration
+	Response  string
+	Tools     []string
+	ToolCalls []api.ToolCall
+	Thinking  bool
+}
+
+// Run executes a test against a model
+func Run(ctx context.Context, client *api.Client, model string, test Test) Result {
+	result := Result{Name: test.Name}
+
+	req := &api.ChatRequest{
+		Model: model,
+		Messages: []api.Message{
+			{Role: "user", Content: test.Prompt},
+		},
+		Options: test.Options,
+	}
+
+	if test.System != "" {
+		req.Messages = append([]api.Message{
+			{Role: "system", Content: test.System},
+		}, req.Messages...)
+	}
+
+	if len(test.Tools) > 0 {
+		req.Tools = test.Tools
+	}
+
+	if test.Think {
+		req.Think = &api.ThinkValue{Value: true}
+	}
+
+	var resp strings.Builder
+	var toolCalls []api.ToolCall
+
+	start := time.Now()
+	err := client.Chat(ctx, req, func(r api.ChatResponse) error {
+		resp.WriteString(r.Message.Content)
+		if r.Message.Thinking != "" {
+			result.Thinking = true
+		}
+		toolCalls = append(toolCalls, r.Message.ToolCalls...)
+		return nil
+	})
+	result.Duration = time.Since(start)
+
+	if err != nil {
+		result.Error = err
+		return result
+	}
+
+	result.Response = resp.String()
+	result.Tools = uniqueToolNames(toolCalls)
+	result.ToolCalls = toolCalls
+	result.Passed = test.Check(result.Response, toolCalls)
+
+	return result
+}
+
+func uniqueToolNames(calls []api.ToolCall) []string {
+	seen := make(map[string]bool)
+	var names []string
+	for _, c := range calls {
+		if !seen[c.Function.Name] {
+			seen[c.Function.Name] = true
+			names = append(names, c.Function.Name)
+		}
+	}
+	return names
+}
+
+// Check functions for common test patterns
+
+func HasResponse() func(string, []api.ToolCall) bool {
+	return func(resp string, _ []api.ToolCall) bool {
+		return strings.TrimSpace(resp) != ""
+	}
+}
+
+func Contains(s string) func(string, []api.ToolCall) bool {
+	return func(resp string, _ []api.ToolCall) bool {
+		return strings.Contains(strings.ToLower(resp), strings.ToLower(s))
+	}
+}
+
+func CallsTool(name string) func(string, []api.ToolCall) bool {
+	return func(_ string, tools []api.ToolCall) bool {
+		for _, t := range tools {
+			if t.Function.Name == name {
+				return true
+			}
+		}
+		return false
+	}
+}
+
+func NoTools() func(string, []api.ToolCall) bool {
+	return func(_ string, tools []api.ToolCall) bool {
+		return len(tools) == 0
+	}
+}
+
+func MinTools(n int) func(string, []api.ToolCall) bool {
+	return func(_ string, tools []api.ToolCall) bool {
+		return len(tools) >= n
+	}
+}
+
+func All(checks ...func(string, []api.ToolCall) bool) func(string, []api.ToolCall) bool {
+	return func(resp string, tools []api.ToolCall) bool {
+		for _, check := range checks {
+			if !check(resp, tools) {
+				return false
+			}
+		}
+		return true
+	}
+}

cmd/eval/main.go

@@ -0,0 +1,217 @@
+package main
+
+import (
+	"context"
+	"encoding/json"
+	"flag"
+	"fmt"
+	"os"
+	"strings"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+func main() {
+	model := flag.String("model", "", "model to evaluate")
+	suite := flag.String("suite", "", "comma-separated list of suites to run (empty runs all)")
+	list := flag.Bool("list", false, "list available suites")
+	verbose := flag.Bool("v", false, "verbose output")
+	timeout := flag.Int("timeout", 60, "timeout per test in seconds")
+	export := flag.String("export", "eval-results.json", "export results to file")
+	flag.Parse()
+
+	if *list {
+		for _, s := range suites {
+			fmt.Printf("%s (%d tests)\n", s.Name, len(s.Tests))
+		}
+		return
+	}
+
+	if *model == "" {
+		fmt.Fprintf(os.Stderr, "error: -model parameter is required\n")
+		os.Exit(1)
+	}
+
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "error: %v\n", err)
+		os.Exit(1)
+	}
+
+	ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
+	if err := client.Heartbeat(ctx); err != nil {
+		cancel()
+		fmt.Fprintf(os.Stderr, "error: cannot connect to ollama\n")
+		os.Exit(1)
+	}
+	cancel()
+
+	selected := suites
+	if *suite != "" {
+		suiteNames := strings.Split(*suite, ",")
+		selected = []Suite{}
+		var notFound []string
+
+		for _, name := range suiteNames {
+			name = strings.TrimSpace(name)
+			if name == "" {
+				continue
+			}
+
+			found := false
+			for _, s := range suites {
+				if s.Name == name {
+					selected = append(selected, s)
+					found = true
+					break
+				}
+			}
+			if !found {
+				notFound = append(notFound, name)
+			}
+		}
+
+		if len(notFound) > 0 {
+			fmt.Fprintf(os.Stderr, "error: suite(s) not found: %s\n", strings.Join(notFound, ", "))
+			os.Exit(1)
+		}
+	}
+
+	var results []Result
+	for _, s := range selected {
+		if *verbose {
+			fmt.Printf("\n%s (%d tests)\n", s.Name, len(s.Tests))
+		}
+		for i, test := range s.Tests {
+			if test.Options == nil {
+				test.Options = map[string]any{"temperature": 0.1}
+			}
+			if test.Check == nil {
+				test.Check = HasResponse()
+			}
+
+			if *verbose {
+				fmt.Printf("  [%d/%d] %s... ", i+1, len(s.Tests), test.Name)
+			}
+
+			ctx, cancel := context.WithTimeout(context.Background(), time.Duration(*timeout)*time.Second)
+			result := Run(ctx, client, *model, test)
+			cancel()
+
+			results = append(results, result)
+
+			if *verbose {
+				if result.Error != nil {
+					fmt.Printf("ERROR: %v\n", result.Error)
+				} else if result.Passed {
+					fmt.Printf("PASS (%.2fs)", result.Duration.Seconds())
+					if len(result.Tools) > 0 || result.Thinking {
+						fmt.Printf(" [")
+						if len(result.Tools) > 0 {
+							fmt.Printf("tools: %s", strings.Join(result.Tools, ","))
+						}
+						if result.Thinking {
+							if len(result.Tools) > 0 {
+								fmt.Printf(", ")
+							}
+							fmt.Printf("thinking")
+						}
+						fmt.Printf("]")
+					}
+					fmt.Println()
+
+					// Print tool calls with details
+					if len(result.ToolCalls) > 0 {
+						fmt.Printf("    Tool Calls:\n")
+						for _, tc := range result.ToolCalls {
+							argsJSON, _ := json.Marshal(tc.Function.Arguments)
+							fmt.Printf("      - %s: %s\n", tc.Function.Name, string(argsJSON))
+						}
+					}
+
+					// Print response if there is one
+					if result.Response != "" {
+						fmt.Printf("    Response: %s\n", result.Response)
+					}
+				} else {
+					fmt.Printf("FAIL (%.2fs)\n", result.Duration.Seconds())
+
+					// Print tool calls with details even on failure
+					if len(result.ToolCalls) > 0 {
+						fmt.Printf("    Tool Calls:\n")
+						for _, tc := range result.ToolCalls {
+							argsJSON, _ := json.Marshal(tc.Function.Arguments)
+							fmt.Printf("      - %s: %s\n", tc.Function.Name, string(argsJSON))
+						}
+					}
+
+					// Print response even on failure
+					if result.Response != "" {
+						fmt.Printf("    Response: %s\n", result.Response)
+					}
+				}
+			}
+		}
+	}
+
+	printSummary(results)
+
+	if *export != "" {
+		if err := writeJSON(*export, results); err != nil {
+			fmt.Fprintf(os.Stderr, "warning: export failed: %v\n", err)
+		} else if *verbose {
+			fmt.Printf("\nResults: %s\n", *export)
+		}
+	}
+
+	if anyFailed(results) {
+		os.Exit(1)
+	}
+}
+
+func printSummary(results []Result) {
+	var passed, failed, errors int
+	for _, r := range results {
+		if r.Error != nil {
+			errors++
+		} else if r.Passed {
+			passed++
+		} else {
+			failed++
+		}
+	}
+
+	total := len(results)
+	rate := 0.0
+	if total > 0 {
+		rate = float64(passed) / float64(total) * 100
+	}
+
+	fmt.Printf("\n%d/%d passed (%.1f%%)", passed, total, rate)
+	if errors > 0 {
+		fmt.Printf(", %d errors", errors)
+	}
+	fmt.Println()
+}
+
+func anyFailed(results []Result) bool {
+	for _, r := range results {
+		if !r.Passed || r.Error != nil {
+			return true
+		}
+	}
+	return false
+}
+
+func writeJSON(path string, results []Result) error {
+	f, err := os.Create(path)
+	if err != nil {
+		return err
+	}
+	defer f.Close()
+
+	enc := json.NewEncoder(f)
+	enc.SetIndent("", "  ")
+	return enc.Encode(results)
+}

cmd/eval/suites.go

@@ -0,0 +1,178 @@
+package main
+
+import "github.com/ollama/ollama/api"
+
+var suites = []Suite{
+	{
+		Name: "basic-qa",
+		Tests: []Test{
+			{
+				Name:   "simple-math",
+				Prompt: "What is 2+2? Reply with just the number.",
+				Check:  Contains("4"),
+			},
+			{
+				Name:   "capital-city",
+				Prompt: "What is the capital of France? Reply with just the city name.",
+				Check:  Contains("Paris"),
+			},
+			{
+				Name:   "greeting",
+				Prompt: "Say hello",
+				Check:  HasResponse(),
+			},
+		},
+	},
+	{
+		Name: "reasoning",
+		Tests: []Test{
+			{
+				Name:   "logic-puzzle",
+				Prompt: "If all roses are flowers and some flowers fade quickly, can we conclude that some roses fade quickly? Answer yes or no.",
+				Check:  Contains("no"),
+			},
+			{
+				Name:   "counting",
+				Prompt: "How many letters are in the word 'HELLO'?",
+				Check:  Contains("5"),
+			},
+		},
+	},
+	{
+		Name: "instruction-following",
+		Tests: []Test{
+			{
+				Name:   "json-output",
+				Prompt: "Reply with a JSON object containing a 'status' field set to 'ok'.",
+				Check:  All(Contains("status"), Contains("ok")),
+			},
+			{
+				Name:   "system-prompt",
+				Prompt: "What is your name?",
+				System: "You are a helpful assistant named TestBot. When asked your name, always respond with 'TestBot'.",
+				Check:  Contains("TestBot"),
+			},
+		},
+	},
+	{
+		Name: "tool-calling-basic",
+		Tests: []Test{
+			{
+				Name:   "single-tool",
+				Prompt: "What's the weather like in San Francisco?",
+				Tools:  []api.Tool{weatherTool},
+				Check:  CallsTool("get_weather"),
+			},
+			{
+				Name:   "tool-selection",
+				Prompt: "What time is it in Tokyo?",
+				Tools:  []api.Tool{weatherTool, timeTool},
+				Check:  CallsTool("get_time"),
+			},
+			{
+				Name:   "no-tool-needed",
+				Prompt: "What is 2+2?",
+				Tools:  []api.Tool{weatherTool, timeTool},
+				Check:  NoTools(),
+			},
+		},
+	},
+	{
+		Name: "tool-calling-advanced",
+		Tests: []Test{
+			{
+				Name:   "parallel-calls",
+				Prompt: "Get the weather in both New York and Los Angeles.",
+				Tools:  []api.Tool{weatherTool},
+				Check:  All(CallsTool("get_weather"), MinTools(2)),
+			},
+			{
+				Name:   "multi-param",
+				Prompt: "Search for Italian restaurants with prices between $20 and $40.",
+				Tools:  []api.Tool{restaurantTool},
+				Check:  CallsTool("search_restaurants"),
+			},
+		},
+	},
+	{
+		Name: "tool-calling-thinking",
+		Tests: []Test{
+			{
+				Name:   "thinking-before-tool",
+				Prompt: "I need to know the weather in Paris before I decide what to pack.",
+				Tools:  []api.Tool{weatherTool},
+				Think:  true,
+				Check:  CallsTool("get_weather"),
+			},
+			{
+				Name:   "thinking-multi-tool",
+				Prompt: "I'm planning a trip to London. I need to know what time it is there and what the weather is like.",
+				Tools:  []api.Tool{weatherTool, timeTool},
+				Think:  true,
+				Check:  MinTools(1),
+			},
+		},
+	},
+}
+
+var weatherTool = 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",
+				},
+			},
+		},
+	},
+}
+
+var timeTool = api.Tool{
+	Type: "function",
+	Function: api.ToolFunction{
+		Name:        "get_time",
+		Description: "Get the current time in a timezone",
+		Parameters: api.ToolFunctionParameters{
+			Type:     "object",
+			Required: []string{"timezone"},
+			Properties: map[string]api.ToolProperty{
+				"timezone": {
+					Type:        api.PropertyType{"string"},
+					Description: "The timezone name",
+				},
+			},
+		},
+	},
+}
+
+var restaurantTool = api.Tool{
+	Type: "function",
+	Function: api.ToolFunction{
+		Name:        "search_restaurants",
+		Description: "Search for restaurants",
+		Parameters: api.ToolFunctionParameters{
+			Type:     "object",
+			Required: []string{"cuisine"},
+			Properties: map[string]api.ToolProperty{
+				"cuisine": {
+					Type:        api.PropertyType{"string"},
+					Description: "Type of cuisine",
+				},
+				"min_price": {
+					Type:        api.PropertyType{"number"},
+					Description: "Minimum price",
+				},
+				"max_price": {
+					Type:        api.PropertyType{"number"},
+					Description: "Maximum price",
+				},
+			},
+		},
+	},
+}

cmd/interactive.go

@@ -40,7 +40,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "  /bye            Exit")
 		fmt.Fprintln(os.Stderr, "  /?, /help       Help for a command")
 		fmt.Fprintln(os.Stderr, "  /? shortcuts    Help for keyboard shortcuts")
-
 		fmt.Fprintln(os.Stderr, "")
 		fmt.Fprintln(os.Stderr, "Use \"\"\" to begin a multi-line message.")
 

convert/convert.go

@@ -6,14 +6,11 @@ import (
 	"errors"
 	"fmt"
 	"io/fs"
-	"iter"
 	"log/slog"
-	"maps"
 	"os"
 	"slices"
 	"strings"
 
-	ofs "github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/fs/ggml"
 )
 
@@ -21,13 +18,8 @@ type ModelParameters struct {
 	Architectures []string `json:"architectures"`
 	VocabSize     uint32   `json:"vocab_size"`
 
-	// TODO is this needed?
-	ModelType string `json:"model_type"`
-
 	TextModel struct {
-		VocabSize  uint32 `json:"vocab_size"`
-		HiddenSize uint32 `json:"hidden_size"`
-		ModelType  string `json:"model_type"`
+		VocabSize uint32 `json:"vocab_size"`
 	} `json:"text_config"`
 }
 
@@ -41,94 +33,8 @@ type AdapterParameters struct {
 	} `json:"lora_parameters"`
 }
 
-type KV map[string]any
-
-func (kv KV) Architecture() string {
-	return kv.String("general.architecture", "unknown")
-}
-
-type valueTypes interface {
-	uint8 | int8 | uint16 | int16 |
-		uint32 | int32 | uint64 | int64 |
-		string | float32 | float64 | bool
-}
-
-type arrayValueTypes interface {
-	[]uint8 | []int8 | []uint16 | []int16 |
-		[]uint32 | []int32 | []uint64 | []int64 |
-		[]string | []float32 | []float64 | []bool
-}
-
-func keyValue[T valueTypes | arrayValueTypes](kv KV, key string, defaultValue ...T) (T, bool) {
-	if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
-		key = kv.Architecture() + "." + key
-	}
-
-	if val, ok := kv[key].(T); ok {
-		return val, true
-	}
-	return defaultValue[0], false
-}
-
-func (kv KV) String(key string, defaultValue ...string) string {
-	val, _ := keyValue(kv, key, append(defaultValue, "")...)
-	return val
-}
-
-func (kv KV) Uint(key string, defaultValue ...uint32) uint32 {
-	val, _ := keyValue(kv, key, append(defaultValue, 0)...)
-	return val
-}
-
-func (kv KV) Float(key string, defaultValue ...float32) float32 {
-	val, _ := keyValue(kv, key, append(defaultValue, 0)...)
-	return val
-}
-
-func (kv KV) Bool(key string, defaultValue ...bool) bool {
-	val, _ := keyValue(kv, key, append(defaultValue, false)...)
-	return val
-}
-
-func (kv KV) Strings(key string, defaultValue ...[]string) []string {
-	val, _ := keyValue(kv, key, append(defaultValue, []string{""})...)
-	return val
-}
-
-func (kv KV) Ints(key string, defaultValue ...[]int32) []int32 {
-	val, _ := keyValue(kv, key, append(defaultValue, []int32{0})...)
-	return val
-}
-
-func (kv KV) Uints(key string, defaultValue ...[]uint32) []uint32 {
-	val, _ := keyValue(kv, key, append(defaultValue, []uint32{0})...)
-	return val
-}
-
-func (kv KV) Floats(key string, defaultValue ...[]float32) []float32 {
-	val, _ := keyValue(kv, key, append(defaultValue, []float32{0})...)
-	return val
-}
-
-func (kv KV) Bools(key string, defaultValue ...[]bool) []bool {
-	val, _ := keyValue(kv, key, append(defaultValue, []bool{false})...)
-	return val
-}
-
-func (kv KV) Len() int {
-	return len(kv)
-}
-
-func (kv KV) Keys() iter.Seq[string] {
-	return maps.Keys(kv)
-}
-
-func (kv KV) Value(key string) any {
-	return kv[key]
-}
-
-func (ModelParameters) KV(t *Tokenizer) KV {
-	kv := KV{
+func (ModelParameters) KV(t *Tokenizer) ggml.KV {
+	kv := ggml.KV{
 		"general.file_type":            uint32(1),
 		"general.quantization_version": uint32(2),
 		"tokenizer.ggml.pre":           t.Pre,
@@ -157,7 +63,7 @@ func (ModelParameters) KV(t *Tokenizer) KV {
 	return kv
 }
 
-func (p AdapterParameters) KV() KV {
+func (p AdapterParameters) KV() ggml.KV {
 	var alpha float32
 	if p.LoraParameters.Alpha == 0 {
 		alpha = float32(p.Alpha)
@@ -165,7 +71,7 @@ func (p AdapterParameters) KV() KV {
 		alpha = p.LoraParameters.Alpha
 	}
 
-	kv := KV{
+	kv := ggml.KV{
 		"adapter.lora.alpha": alpha,
 		"adapter.type":       "lora",
 		"general.file_type":  uint32(1),
@@ -182,14 +88,9 @@ func (ModelParameters) specialTokenTypes() []string {
 	}
 }
 
-type ModelKV interface {
-	// KV maps parameters to LLM key-values
-	KV(*Tokenizer) KV
-}
-
 type ModelConverter interface {
-	ModelKV
-
+	// KV maps parameters to LLM key-values
+	KV(*Tokenizer) ggml.KV
 	// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
 	Tensors([]Tensor) []*ggml.Tensor
 	// Replacements returns a list of string pairs to replace in tensor names.
@@ -206,7 +107,7 @@ type moreParser interface {
 
 type AdapterConverter interface {
 	// KV maps parameters to LLM key-values
-	KV(ofs.Config) KV
+	KV(ggml.KV) ggml.KV
 	// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
 	Tensors([]Tensor) []*ggml.Tensor
 	// Replacements returns a list of string pairs to replace in tensor names.
@@ -214,7 +115,7 @@ type AdapterConverter interface {
 	Replacements() []string
 }
 
-func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ofs.Config) error {
+func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ggml.KV) error {
 	bts, err := fs.ReadFile(fsys, "adapter_config.json")
 	if err != nil {
 		return err
@@ -225,8 +126,8 @@ func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ofs.Config) error {
 		return err
 	}
 
-	arch := baseKV.Architecture()
-	if arch == "" {
+	arch, ok := baseKV["general.architecture"]
+	if !ok {
 		return errors.New("architecture not set for the base model")
 	}
 
@@ -252,19 +153,23 @@ func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ofs.Config) error {
 	return writeFile(f, conv.KV(baseKV), conv.Tensors(ts))
 }
 
-func LoadModelMetadata(fsys fs.FS) (ModelKV, *Tokenizer, error) {
+// Convert writes an Ollama compatible model to the provided io.WriteSeeker based on configurations
+// and files it finds in the input path.
+// Supported input model formats include safetensors.
+// Supported input tokenizers files include tokenizer.json (preferred) and tokenizer.model.
+func ConvertModel(fsys fs.FS, f *os.File) error {
 	bts, err := fs.ReadFile(fsys, "config.json")
 	if err != nil {
-		return nil, nil, err
+		return err
 	}
 
 	var p ModelParameters
 	if err := json.Unmarshal(bts, &p); err != nil {
-		return nil, nil, err
+		return err
 	}
 
 	if len(p.Architectures) < 1 {
-		return nil, nil, errors.New("unknown architecture")
+		return errors.New("unknown architecture")
 	}
 
 	var conv ModelConverter
@@ -277,8 +182,6 @@ func LoadModelMetadata(fsys fs.FS) (ModelKV, *Tokenizer, error) {
 		conv = &llama4Model{}
 	case "Mistral3ForConditionalGeneration":
 		conv = &mistral3Model{}
-	case "Ministral3ForCausalLM":
-		conv = &mistral3CausalModel{}
 	case "MixtralForCausalLM":
 		conv = &mixtralModel{}
 	case "GemmaForCausalLM":
@@ -297,37 +200,31 @@ func LoadModelMetadata(fsys fs.FS) (ModelKV, *Tokenizer, error) {
 		conv = &qwen25VLModel{}
 	case "Qwen3VLForConditionalGeneration", "Qwen3VLMoeForConditionalGeneration":
 		conv = &qwen3VLModel{}
-	case "Olmo3ForCausalLM":
-		conv = &olmoModel{}
 	case "BertModel":
 		conv = &bertModel{}
-	case "NomicBertModel", "NomicBertMoEModel":
-		conv = &nomicbertModel{}
 	case "CohereForCausalLM":
 		conv = &commandrModel{}
 	case "GptOssForCausalLM":
 		conv = &gptossModel{}
 	case "DeepseekOCRForCausalLM":
 		conv = &deepseekocr{}
-	case "DeepseekV3ForCausalLM":
-		conv = &deepseek2Model{}
 	default:
-		return nil, nil, fmt.Errorf("unsupported architecture %q", p.Architectures[0])
+		return fmt.Errorf("unsupported architecture %q", p.Architectures[0])
 	}
 
 	if err := json.Unmarshal(bts, conv); err != nil {
-		return nil, nil, err
+		return err
 	}
 
 	if t, ok := conv.(moreParser); ok {
 		if err := t.parseMore(fsys); err != nil {
-			return nil, nil, err
+			return err
 		}
 	}
 
 	t, err := parseTokenizer(fsys, conv.specialTokenTypes())
 	if err != nil {
-		return nil, nil, err
+		return err
 	}
 
 	vocabSize := int(cmp.Or(p.VocabSize, p.TextModel.VocabSize))
@@ -349,19 +246,6 @@ func LoadModelMetadata(fsys fs.FS) (ModelKV, *Tokenizer, error) {
 	default:
 		slog.Debug("vocabulary", "size", len(t.Vocabulary.Tokens))
 	}
-	return conv, t, nil
-}
-
-// Convert writes an Ollama compatible model to the provided io.WriteSeeker based on configurations
-// and files it finds in the input path.
-// Supported input model formats include safetensors.
-// Supported input tokenizers files include tokenizer.json (preferred) and tokenizer.model.
-func ConvertModel(fsys fs.FS, f *os.File) error {
-	kv, t, err := LoadModelMetadata(fsys)
-	if err != nil {
-		return err
-	}
-	conv := kv.(ModelConverter)
 
 	ts, err := parseTensors(fsys, strings.NewReplacer(conv.Replacements()...))
 	if err != nil {
@@ -371,7 +255,7 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 	return writeFile(f, conv.KV(t), conv.Tensors(ts))
 }
 
-func writeFile(f *os.File, kv KV, ts []*ggml.Tensor) error {
+func writeFile(f *os.File, kv ggml.KV, ts []*ggml.Tensor) error {
 	for i := range ts {
 		ts[i].Shape = slices.Clone(ts[i].Shape)
 		slices.Reverse(ts[i].Shape)

convert/convert_bert.go

@@ -88,7 +88,7 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
 	return nil
 }
 
-func (p *bertModel) KV(t *Tokenizer) KV {
+func (p *bertModel) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "bert"
 	kv["bert.attention.causal"] = false

convert/convert_commandr.go

@@ -24,7 +24,7 @@ type commandrModel struct {
 
 var _ ModelConverter = (*commandrModel)(nil)
 
-func (p *commandrModel) KV(t *Tokenizer) KV {
+func (p *commandrModel) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "command-r"
 	kv["general.name"] = "command-r"

convert/convert_deepseek2.go

@@ -1,173 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"fmt"
-	"log/slog"
-	"regexp"
-	"strconv"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type deepseek2Model struct {
-	ModelParameters               // architectures, vocab_size
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	HiddenLayers          uint32  `json:"num_hidden_layers"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	RMSNormEPS            float32 `json:"rms_norm_eps"`
-
-	RopeTheta     float32 `json:"rope_theta"`
-	QKNopeHeadDim uint32  `json:"qk_nope_head_dim"`
-	QKRopeHeadDim uint32  `json:"qk_rope_head_dim"`
-	KVLoraRank    uint32  `json:"kv_lora_rank"`
-	QLoraRank     uint32  `json:"q_lora_rank"`
-	VHeadDim      uint32  `json:"v_head_dim"`
-
-	ExpertCount            uint32  `json:"n_routed_experts"`
-	ExpertSharedCount      uint32  `json:"n_shared_experts"`
-	ExpertIntermediateSize uint32  `json:"moe_intermediate_size"`
-	ExpertUsedCount        uint32  `json:"num_experts_per_tok"`
-	ExpertWeightsNorm      bool    `json:"norm_topk_prob"`
-	ExpertWeightsScale     float32 `json:"routed_scaling_factor"`
-
-	ScoringFunc            string `json:"scoring_func"`
-	LeadingDenseBlockCount uint32 `json:"first_k_dense_replace"`
-
-	RopeScaling struct {
-		Factor                        float32 `json:"factor"`
-		OriginalMaxPositionEmbeddings uint32  `json:"original_max_position_embeddings"`
-		Type                          string  `json:"type"`
-		MScaleAllDim                  float32 `json:"mscale_all_dim"`
-	} `json:"rope_scaling"`
-
-	Architecture string
-}
-
-func (p *deepseek2Model) KV(t *Tokenizer) KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "deepseek2"
-	kv["general.type"] = "model"
-	kv["deepseek2.block_count"] = p.HiddenLayers
-
-	numHeads := p.NumAttentionHeads
-	numKVHeads := p.NumKeyValueHeads
-
-	kv["deepseek2.attention.head_count"] = numHeads
-	kv["deepseek2.attention.head_count_kv"] = numKVHeads
-	kv["deepseek2.attention.key_length"] = p.QKNopeHeadDim + p.QKRopeHeadDim
-	kv["deepseek2.attention.kv_lora_rank"] = p.KVLoraRank
-	kv["deepseek2.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
-	kv["deepseek2.attention.q_lora_rank"] = p.QLoraRank
-	kv["deepseek2.attention.value_length"] = p.VHeadDim
-	kv["deepseek2.context_length"] = p.MaxPositionEmbeddings
-	kv["deepseek2.embedding_length"] = p.HiddenSize
-	kv["deepseek2.expert_count"] = p.ExpertCount
-	kv["deepseek2.expert_feed_forward_length"] = p.ExpertIntermediateSize
-	kv["deepseek2.expert_shared_count"] = p.ExpertSharedCount
-
-	var scoringFunc uint32
-	switch p.ScoringFunc {
-	case "softmax":
-		// not currently supported in the model, but needed for Deepseek-OCR
-		scoringFunc = 1
-	case "sigmoid":
-		scoringFunc = 2
-	}
-	kv["deepseek2.expert_gating_func"] = scoringFunc
-	kv["deepseek2.expert_used_count"] = p.ExpertUsedCount
-	kv["deepseek2.expert_weights_norm"] = p.ExpertWeightsNorm
-	kv["deepseek2.expert_weights_scale"] = p.ExpertWeightsScale
-	kv["deepseek2.feed_forward_length"] = p.IntermediateSize
-	kv["deepseek2.leading_dense_block_count"] = p.LeadingDenseBlockCount
-
-	kv["deepseek2.rope.dimension_count"] = p.QKRopeHeadDim
-	kv["deepseek2.rope.freq_base"] = cmp.Or(p.RopeTheta, 10000.0)
-	kv["deepseek2.rope.scaling.factor"] = p.RopeScaling.Factor
-	kv["deepseek2.rope.scaling.original_context_length"] = p.RopeScaling.OriginalMaxPositionEmbeddings
-	kv["deepseek2.rope.scaling.type"] = p.RopeScaling.Type
-	kv["deepseek2.rope.scaling.yarn_log_multiplier"] = 0.1 * p.RopeScaling.MScaleAllDim
-
-	kv["tokenizer.ggml.pre"] = "deepseek-v3"
-
-	return kv
-}
-
-func (p *deepseek2Model) Replacements() []string {
-	return []string{
-		"lm_head", "output",
-		"model.embed_tokens", "token_embd",
-		"model.norm", "output_norm",
-		"language_model.", "",
-		"model.layers", "blk",
-		"input_layernorm", "attn_norm",
-		"self_attn.kv_a_proj_with_mqa", "attn_kv_a_mqa",
-		"self_attn.kv_a_layernorm", "attn_kv_a_norm",
-		"self_attn.kv_b_proj", "attn_kv_b",
-		"self_attn.q_a_proj", "attn_q_a",
-		"self_attn.q_a_layernorm", "attn_q_a_norm",
-		"self_attn.q_b_proj", "attn_q_b",
-		"self_attn.o_proj", "attn_output",
-		"post_attention_layernorm", "ffn_norm",
-		"mlp.shared_experts.down_proj", "ffn_down_shexp",
-		"mlp.shared_experts.gate_proj", "ffn_gate_shexp",
-		"mlp.shared_experts.up_proj", "ffn_up_shexp",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.down_proj", "ffn_down",
-		"mlp.up_proj", "ffn_up",
-		"mlp.gate.e_score_correction_bias", "exp_probs_b.bias",
-		"mlp.gate", "ffn_gate_inp",
-	}
-}
-
-func (p *deepseek2Model) Tensors(s []Tensor) (out []*ggml.Tensor) {
-	merges := make([]merge, p.HiddenLayers*3)
-	for i := range p.HiddenLayers {
-		merges[i*3+0] = merge{
-			fmt.Sprintf("blk.%d.mlp.experts.*.gate_proj.weight", i),
-			fmt.Sprintf("blk.%d.ffn_gate_exps.weight", i),
-		}
-		merges[i*3+1] = merge{
-			fmt.Sprintf("blk.%d.mlp.experts.*.up_proj.weight", i),
-			fmt.Sprintf("blk.%d.ffn_up_exps.weight", i),
-		}
-		merges[i*3+2] = merge{
-			fmt.Sprintf("blk.%d.mlp.experts.*.down_proj.weight", i),
-			fmt.Sprintf("blk.%d.ffn_down_exps.weight", i),
-		}
-	}
-
-	skipLayer := func(n string, minValue uint32) bool {
-		re := regexp.MustCompile(`^blk\.(\d+)`)
-		matches := re.FindStringSubmatch(n)
-		if matches == nil {
-			return false
-		}
-
-		blkNum, err := strconv.Atoi(matches[1])
-		if err != nil {
-			return false
-		}
-
-		return uint32(blkNum) >= minValue
-	}
-
-	out, s = mergeTensors(s, merges...)
-	for _, t := range s {
-		// skip any additional layers (such as the Multi-Token Prediction layer)
-		if skipLayer(t.Name(), p.HiddenLayers) {
-			slog.Debug("skipping layer", "name", t.Name())
-			continue
-		}
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-	return out
-}

convert/convert_deepseekocr.go

@@ -41,7 +41,7 @@ type deepseekocr struct {
 	} `json:"vision_config"`
 }
 
-func (m *deepseekocr) KV(t *Tokenizer) KV {
+func (m *deepseekocr) KV(t *Tokenizer) ggml.KV {
 	kv := m.ModelParameters.KV(t)
 	kv["general.architecture"] = "deepseekocr"
 	kv["block_count"] = m.LanguageConfig.HiddenLayers

convert/convert_gemma.go

@@ -23,7 +23,7 @@ type gemmaModel struct {
 
 var _ ModelConverter = (*gemmaModel)(nil)
 
-func (p *gemmaModel) KV(t *Tokenizer) KV {
+func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma"
 	kv["gemma.context_length"] = p.MaxPositionEmbeddings

convert/convert_gemma2.go

@@ -1,5 +1,7 @@
 package convert
 
+import "github.com/ollama/ollama/fs/ggml"
+
 type gemma2Model struct {
 	gemmaModel
 	SlidingWindow         uint32  `json:"sliding_window"`
@@ -7,7 +9,7 @@ type gemma2Model struct {
 	FinalLogitSoftcap     float32 `json:"final_logit_softcapping"`
 }
 
-func (p *gemma2Model) KV(t *Tokenizer) KV {
+func (p *gemma2Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma2"
 	kv["gemma2.context_length"] = p.MaxPositionEmbeddings

convert/convert_gemma2_adapter.go

@@ -6,7 +6,6 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/fs/ggml"
 )
 
@@ -16,7 +15,7 @@ type gemma2Adapter struct {
 
 var _ AdapterConverter = (*gemma2Adapter)(nil)
 
-func (p *gemma2Adapter) KV(baseKV fs.Config) KV {
+func (p *gemma2Adapter) KV(baseKV ggml.KV) ggml.KV {
 	kv := p.AdapterParameters.KV()
 	kv["general.architecture"] = "gemma2"
 	return kv

convert/convert_gemma3.go

@@ -2,7 +2,8 @@ package convert
 
 import (
 	"cmp"
-	"slices"
+
+	"github.com/ollama/ollama/fs/ggml"
 )
 
 type gemma3Model struct {
@@ -25,26 +26,16 @@ type gemma3Model struct {
 		NumChannels       uint32  `json:"num_channels"`        // num_channels 3
 		PatchSize         uint32  `json:"patch_size"`          // patch_size 14
 	} `json:"vision_config"`
-	MaxPositionEmbeddings    uint32   `json:"max_position_embeddings"`
-	NumAttentionHeads        uint32   `json:"num_attention_heads"`
-	NumKeyValueHeads         uint32   `json:"num_key_value_heads"`
-	RMSNormEPS               float32  `json:"rms_norm_eps"`
-	HeadDim                  uint32   `json:"head_dim"`
-	FinalLogitSoftcap        float32  `json:"final_logit_softcapping"`
-	RopeLocalTheta           float32  `json:"rope_local_base_freq"`
-	RopeTheta                float32  `json:"rope_theta"`
-	SlidingWindow            uint32   `json:"sliding_window"`
-	SlidingWindowPattern     *uint32  `json:"sliding_window_pattern"`
-	LayerTypes               []string `json:"layer_types"`
-	MultiModalTokensPerImage uint32   `json:"mm_tokens_per_image"`
-	RopeScaling              *struct {
-		Type                          string  `json:"rope_type"`
-		Factor                        float32 `json:"factor"`
-		OriginalMaxPositionEmbeddings uint32  `json:"original_max_position_embeddings"`
-		ExtrapolationFactor           float32 `json:"extrapolation_factor"`
-		BetaFast                      float32 `json:"beta_fast"`
-		BetaSlow                      float32 `json:"beta_slow"`
-	} `json:"rope_scaling"`
+	MaxPositionEmbeddings    uint32  `json:"max_position_embeddings"`
+	NumAttentionHeads        uint32  `json:"num_attention_heads"`
+	NumKeyValueHeads         uint32  `json:"num_key_value_heads"`
+	RMSNormEPS               float32 `json:"rms_norm_eps"`
+	HeadDim                  uint32  `json:"head_dim"`
+	FinalLogitSoftcap        float32 `json:"final_logit_softcapping"`
+	RopeLocalTheta           float32 `json:"rope_local_base_freq"`
+	RopeGlobalTheta          float32 `json:"rope_global_base_freq"`
+	SlidingWindow            uint32  `json:"sliding_window"`
+	MultiModalTokensPerImage uint32  `json:"mm_tokens_per_image"`
 }
 
 const (
@@ -53,7 +44,7 @@ const (
 	gemma27BLayerCount = 62
 )
 
-func (p *gemma3Model) KV(t *Tokenizer) KV {
+func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma3"
 
@@ -90,38 +81,9 @@ func (p *gemma3Model) KV(t *Tokenizer) KV {
 		kv["gemma3.attention.key_length"] = p.HeadDim
 		kv["gemma3.attention.value_length"] = p.HeadDim
 		kv["gemma3.attention.sliding_window"] = p.SlidingWindow
-
-		// The sliding window pattern is either provided as the sliding_window_pattern
-		// key (an int) or as the layer_types key (a list of strings).
-		if p.SlidingWindowPattern != nil || len(p.LayerTypes) > 0 {
-			kv["gemma3.attention.sliding_window_pattern"] = slices.Collect(func(yield func(bool) bool) {
-				for i := range numBlocks {
-					var isLocal bool
-					if len(p.LayerTypes) > 0 && int(i) < len(p.LayerTypes) {
-						isLocal = p.LayerTypes[i] == "sliding_attention"
-					} else if p.SlidingWindowPattern != nil && *p.SlidingWindowPattern > 0 {
-						isLocal = (i+1)%*p.SlidingWindowPattern != 0
-					}
-					if !yield(isLocal) {
-						break
-					}
-				}
-			})
-		}
-		if p.FinalLogitSoftcap > 0 {
-			kv["gemma3.final_logit_softcapping"] = p.FinalLogitSoftcap
-		}
+		kv["gemma3.final_logit_softcapping"] = cmp.Or(p.FinalLogitSoftcap, 30)
 		kv["gemma3.rope.local.freq_base"] = cmp.Or(p.RopeLocalTheta, 10000.0)
-		kv["gemma3.rope.freq_base"] = cmp.Or(p.RopeTheta, 1000000.0)
-		if p.RopeScaling != nil && p.RopeScaling.Type == "yarn" && p.RopeScaling.Factor > 0 {
-			kv["gemma3.rope.scaling.type"] = "yarn"
-			kv["gemma3.rope.scaling.factor"] = p.RopeScaling.Factor
-			kv["gemma3.rope.scaling.original_context_length"] = p.RopeScaling.OriginalMaxPositionEmbeddings
-			kv["gemma3.rope.scaling.extrapolation_factor"] = cmp.Or(p.RopeScaling.ExtrapolationFactor, float32(1.0))
-			kv["gemma3.rope.scaling.beta_fast"] = cmp.Or(p.RopeScaling.BetaFast, float32(64.0))
-			kv["gemma3.rope.scaling.beta_slow"] = cmp.Or(p.RopeScaling.BetaSlow, float32(1.0))
-		}
-
+		kv["gemma3.rope.global.freq_base"] = cmp.Or(p.RopeGlobalTheta, 1000000.0)
 		kv["gemma3.embedding_length"] = p.HiddenSize
 		kv["gemma3.feed_forward_length"] = p.IntermediateSize
 	default:

convert/convert_gemma3n.go

@@ -38,7 +38,7 @@ type gemma3nModel struct {
 	VisionModel struct{} `json:"vision_config"`
 }
 
-func (m *gemma3nModel) KV(t *Tokenizer) KV {
+func (m *gemma3nModel) KV(t *Tokenizer) ggml.KV {
 	kv := m.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma3n"
 	kv["gemma3n.activation_sparsity_scale"] = slices.Collect(func(yield func(float32) bool) {

convert/convert_gptoss.go

@@ -37,7 +37,7 @@ type gptossModel struct {
 
 var _ ModelConverter = (*gptossModel)(nil)
 
-func (m *gptossModel) KV(t *Tokenizer) KV {
+func (m *gptossModel) KV(t *Tokenizer) ggml.KV {
 	kv := m.ModelParameters.KV(t)
 	kv["general.architecture"] = "gptoss"
 	kv["general.file_type"] = uint32(4)

convert/convert_llama.go

@@ -48,7 +48,7 @@ type llamaModel struct {
 
 var _ ModelConverter = (*llamaModel)(nil)
 
-func (p *llamaModel) KV(t *Tokenizer) KV {
+func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "llama"
 	kv["llama.vocab_size"] = p.VocabSize

convert/convert_llama4.go

@@ -35,7 +35,7 @@ type llama4Model struct {
 }
 
 // KV implements ModelConverter.
-func (p *llama4Model) KV(t *Tokenizer) KV {
+func (p *llama4Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "llama4"
 

convert/convert_llama_adapter.go

@@ -7,7 +7,6 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/fs/ggml"
 )
 
@@ -19,13 +18,13 @@ type llamaAdapter struct {
 
 var _ AdapterConverter = (*llamaAdapter)(nil)
 
-func (p *llamaAdapter) KV(baseKV fs.Config) KV {
+func (p *llamaAdapter) KV(baseKV ggml.KV) ggml.KV {
 	kv := p.AdapterParameters.KV()
 	kv["general.architecture"] = "llama"
-	kv["llama.attention.head_count"] = baseKV.Value("llama.attention.head_count")
-	kv["llama.attention.head_count_kv"] = baseKV.Value("llama.attention.head_count_kv")
+	kv["llama.attention.head_count"] = baseKV["llama.attention.head_count"]
+	kv["llama.attention.head_count_kv"] = baseKV["llama.attention.head_count_kv"]
 
-	p.NumAttentionHeads = baseKV.Value("llama.attention.head_count").(uint32)
+	p.NumAttentionHeads = baseKV["llama.attention.head_count"].(uint32)
 
 	return kv
 }

convert/convert_mistral.go

@@ -29,17 +29,6 @@ type mistral3Model struct {
 		SlidingWindow         *uint32 `json:"sliding_window"`
 		HiddenAct             string  `json:"hidden_act"`
 		VocabSize             uint32  `json:"vocab_size"`
-		RopeParameters        struct {
-			BetaFast                  float32  `json:"beta_fast"`
-			BetaSlow                  float32  `json:"beta_slow"`
-			Factor                    float32  `json:"factor"`
-			Llama4ScalingBeta         *float32 `json:"llama_4_scaling_beta"`
-			OrigMaxPositionEmbeddings uint32   `json:"original_max_position_embeddings"`
-			RopeType                  string   `json:"rope_type"`
-			RopeTheta                 float32  `json:"rope_theta"`
-			Mscale                    *float32 `json:"mscale"`
-			MscaleAllDim              *float32 `json:"mscale_all_dim"`
-		} `json:"rope_parameters"`
 	} `json:"text_config"`
 	VisionModel struct {
 		NumAttentionHeads uint32  `json:"num_attention_heads"`
@@ -52,15 +41,12 @@ type mistral3Model struct {
 		HeadDim           uint32  `json:"head_dim"`
 		HiddenAct         string  `json:"hidden_act"`
 		RopeTheta         float32 `json:"rope_theta"`
-		RopeParameters    struct {
-			RopeTheta float32 `json:"rope_theta"`
-		} `json:"rope_parameters"`
 	} `json:"vision_config"`
 	MultiModalProjectorBias bool   `json:"multimodal_projector_bias"`
 	ProjectorHiddenAct      string `json:"projector_hidden_act"`
 }
 
-func (p *mistral3Model) KV(t *Tokenizer) KV {
+func (p *mistral3Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "mistral3"
 	kv["mistral3.vocab_size"] = p.TextModel.VocabSize
@@ -75,25 +61,8 @@ func (p *mistral3Model) KV(t *Tokenizer) KV {
 	kv["mistral3.attention.layer_norm_rms_epsilon"] = p.TextModel.RMSNormEPS
 	kv["mistral3.attention.key_length"] = p.TextModel.HeadDim
 	kv["mistral3.attention.value_length"] = p.TextModel.HeadDim
-	kv["mistral3.rope.dimension_count"] = cmp.Or(p.TextModel.HeadDim, p.TextModel.HiddenSize/p.TextModel.NumAttentionHeads)
-	kv["mistral3.rope.freq_base"] = cmp.Or(p.TextModel.RopeTheta, p.TextModel.RopeParameters.RopeTheta)
-	kv["mistral3.rope.scaling.factor"] = p.TextModel.RopeParameters.Factor
-	kv["mistral3.rope.scaling.type"] = p.TextModel.RopeParameters.RopeType
-	kv["mistral3.rope.scaling.beta_fast"] = p.TextModel.RopeParameters.BetaFast
-	kv["mistral3.rope.scaling.beta_slow"] = p.TextModel.RopeParameters.BetaSlow
-
-	if p.TextModel.RopeParameters.Mscale != nil {
-		kv["mistral3.rope.scaling.mscale"] = *p.TextModel.RopeParameters.Mscale
-	}
-	if p.TextModel.RopeParameters.MscaleAllDim != nil {
-		kv["mistral3.rope.scaling.mscale_all_dim"] = *p.TextModel.RopeParameters.MscaleAllDim
-	}
-	if p.TextModel.RopeParameters.OrigMaxPositionEmbeddings > 0 {
-		kv["mistral3.rope.scaling.original_context_length"] = p.TextModel.RopeParameters.OrigMaxPositionEmbeddings
-	}
-	if p.TextModel.RopeParameters.Llama4ScalingBeta != nil {
-		kv["mistral3.rope.scaling_beta"] = *p.TextModel.RopeParameters.Llama4ScalingBeta
-	}
+	kv["mistral3.rope.dimension_count"] = p.TextModel.HiddenSize / p.TextModel.NumHiddenLayers
+	kv["mistral3.rope.freq_base"] = p.TextModel.RopeTheta
 
 	// Vision configuration
 	kv["mistral3.vision.block_count"] = p.VisionModel.NumHiddenLayers
@@ -105,7 +74,7 @@ func (p *mistral3Model) KV(t *Tokenizer) KV {
 	kv["mistral3.vision.patch_size"] = p.VisionModel.PatchSize
 	kv["mistral3.vision.num_channels"] = p.VisionModel.NumChannels
 	// kv["mistral3.vision.attention.layer_norm_epsilon"] = 1e-05 // Default value
-	kv["mistral3.vision.rope.freq_base"] = cmp.Or(p.VisionModel.RopeTheta, p.VisionModel.RopeParameters.RopeTheta)
+	kv["mistral3.vision.rope.freq_base"] = p.VisionModel.RopeTheta
 
 	// Multimodal configuration
 	kv["mistral3.image_token_index"] = p.ImageTokenIndex

convert/convert_mistral_causal.go

@@ -1,181 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"fmt"
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type mistral3CausalModel struct {
-	ModelParameters
-
-	NumHiddenLayers       uint32  `json:"num_hidden_layers"`
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	RopeTheta             float32 `json:"rope_theta"`
-	RMSNormEPS            float32 `json:"rms_norm_eps"`
-	HeadDim               uint32  `json:"head_dim"`
-	SlidingWindow         *uint32 `json:"sliding_window"`
-	HiddenAct             string  `json:"hidden_act"`
-	VocabSize             uint32  `json:"vocab_size"`
-	RopeParameters        struct {
-		BetaFast                  float32  `json:"beta_fast"`
-		BetaSlow                  float32  `json:"beta_slow"`
-		Factor                    float32  `json:"factor"`
-		Llama4ScalingBeta         *float32 `json:"llama_4_scaling_beta"`
-		OrigMaxPositionEmbeddings uint32   `json:"original_max_position_embeddings"`
-		RopeType                  string   `json:"rope_type"`
-		RopeTheta                 float32  `json:"rope_theta"`
-		Mscale                    *float32 `json:"mscale"`
-		MscaleAllDim              *float32 `json:"mscale_all_dim"`
-	} `json:"rope_parameters"`
-}
-
-func (p *mistral3CausalModel) KV(t *Tokenizer) KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "mistral3"
-	kv["mistral3.vocab_size"] = p.VocabSize
-
-	// Text configuration
-	kv["mistral3.block_count"] = p.NumHiddenLayers
-	kv["mistral3.context_length"] = p.MaxPositionEmbeddings
-	kv["mistral3.embedding_length"] = p.HiddenSize
-	kv["mistral3.feed_forward_length"] = p.IntermediateSize
-	kv["mistral3.attention.head_count"] = p.NumAttentionHeads
-	kv["mistral3.attention.head_count_kv"] = p.NumKeyValueHeads
-	kv["mistral3.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
-	kv["mistral3.attention.key_length"] = p.HeadDim
-	kv["mistral3.attention.value_length"] = p.HeadDim
-	kv["mistral3.rope.dimension_count"] = cmp.Or(p.HeadDim, p.HiddenSize/p.NumAttentionHeads)
-	kv["mistral3.rope.freq_base"] = cmp.Or(p.RopeTheta, p.RopeParameters.RopeTheta)
-	kv["mistral3.rope.scaling.factor"] = p.RopeParameters.Factor
-	kv["mistral3.rope.scaling.type"] = p.RopeParameters.RopeType
-	kv["mistral3.rope.scaling.beta_fast"] = p.RopeParameters.BetaFast
-	kv["mistral3.rope.scaling.beta_slow"] = p.RopeParameters.BetaSlow
-
-	if p.RopeParameters.Mscale != nil {
-		kv["mistral3.rope.scaling.mscale"] = *p.RopeParameters.Mscale
-	}
-
-	if p.RopeParameters.MscaleAllDim != nil {
-		kv["mistral3.rope.scaling.mscale_all_dim"] = *p.RopeParameters.MscaleAllDim
-	}
-
-	if p.RopeParameters.OrigMaxPositionEmbeddings > 0 {
-		kv["mistral3.rope.scaling.original_context_length"] = p.RopeParameters.OrigMaxPositionEmbeddings
-		kv["mistral3.rope.scaling_beta"] = *p.RopeParameters.Llama4ScalingBeta
-	}
-
-	if p.RopeParameters.Llama4ScalingBeta != nil {
-		kv["mistral3.rope.scaling_beta"] = *p.RopeParameters.Llama4ScalingBeta
-	}
-
-	return kv
-}
-
-func (p *mistral3CausalModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-
-	for _, t := range ts {
-		if !strings.HasPrefix(t.Name(), "v.") {
-			if strings.HasSuffix(t.Name(), ".attn_q.weight") ||
-				strings.HasSuffix(t.Name(), ".attn_k.weight") {
-				t.SetRepacker(p.repack)
-			}
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *mistral3CausalModel) Replacements() []string {
-	return []string{
-		"model.norm", "output_norm",
-		"model.", "",
-		"layers", "blk",
-		"transformer.layers", "blk",
-		"vision_tower", "v",
-		"ln_pre", "encoder_norm",
-		"input_layernorm", "attn_norm",
-		"post_attention_layernorm", "ffn_norm",
-		"embed_tokens", "token_embd",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.o_proj", "attn_output",
-		"mlp.down_proj", "ffn_down",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.up_proj", "ffn_up",
-		"attention.q_proj", "attn_q",
-		"attention.k_proj", "attn_k",
-		"attention.v_proj", "attn_v",
-		"attention.o_proj", "attn_output",
-		"attention_norm", "attn_norm",
-		"feed_forward.gate_proj", "ffn_gate",
-		"feed_forward.down_proj", "ffn_down",
-		"feed_forward.up_proj", "ffn_up",
-		"multi_modal_projector", "mm",
-		"ffn_norm", "ffn_norm",
-		"lm_head", "output",
-	}
-}
-
-func (p *mistral3CausalModel) repack(name string, data []float32, shape []uint64) ([]float32, error) {
-	var dims []int
-	for _, dim := range shape {
-		dims = append(dims, int(dim))
-	}
-
-	var heads uint32
-	if strings.HasSuffix(name, ".attn_q.weight") {
-		heads = p.NumAttentionHeads
-	} else if strings.HasSuffix(name, ".attn_k.weight") {
-		heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
-	} else {
-		return nil, fmt.Errorf("unknown tensor for repack: %s", name)
-	}
-
-	n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-	if err := n.Reshape(append([]int{int(heads), 2, dims[0] / int(heads) / 2}, dims[1:]...)...); err != nil {
-		return nil, err
-	}
-
-	if err := n.T(0, 2, 1, 3); err != nil {
-		return nil, err
-	}
-
-	if err := n.Reshape(dims...); err != nil {
-		return nil, err
-	}
-
-	if err := n.Transpose(); err != nil {
-		return nil, err
-	}
-
-	ts, err := native.SelectF32(n, 1)
-	if err != nil {
-		return nil, err
-	}
-
-	var f32s []float32
-	for _, t := range ts {
-		f32s = append(f32s, t...)
-	}
-
-	return f32s, nil
-}

convert/convert_mixtral.go

@@ -12,7 +12,7 @@ type mixtralModel struct {
 	NumExpertsPerToken uint32 `json:"num_experts_per_tok"`
 }
 
-func (p *mixtralModel) KV(t *Tokenizer) KV {
+func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
 	kv := p.llamaModel.KV(t)
 
 	if p.NumLocalExperts > 0 {

convert/convert_mllama.go

@@ -34,7 +34,7 @@ type mllamaModel struct {
 	} `json:"vision_config"`
 }
 
-func (m *mllamaModel) KV(t *Tokenizer) KV {
+func (m *mllamaModel) KV(t *Tokenizer) ggml.KV {
 	kv := m.ModelParameters.KV(t)
 	kv["general.architecture"] = "mllama"
 

convert/convert_nomicbert.go

@@ -1,213 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"encoding/json"
-	"io/fs"
-	"path/filepath"
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type nomicbertModel struct {
-	ModelParameters
-	NLayers               uint32  `json:"n_layers"`
-	NumHiddenLayers       uint32  `json:"num_hidden_layers"`
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	LayerNormEPS          float32 `json:"layer_norm_eps"`
-	LayerNormEpsilon      float32 `json:"layer_norm_epsilon"`
-	RopeFreqBase          float32 `json:"rope_theta"`
-	normalizeEmbeddings   bool
-	PoolingType           uint32
-
-	// MoE parameters (only present in v2 models)
-	NumExperts      uint32 `json:"num_local_experts"`
-	NumExpertsUsed  uint32 `json:"num_experts_per_tok"`
-	MoEEveryNLayers uint32 `json:"moe_every_n_layers"`
-}
-
-var (
-	_ ModelConverter = (*nomicbertModel)(nil)
-	_ moreParser     = (*nomicbertModel)(nil)
-)
-
-func (p *nomicbertModel) parseMore(fsys fs.FS) error {
-	bts, err := fs.ReadFile(fsys, "modules.json")
-	if err != nil {
-		return err
-	}
-
-	var modules []struct {
-		Type string `json:"type"`
-		Path string `json:"path"`
-	}
-
-	if err := json.Unmarshal(bts, &modules); err != nil {
-		return err
-	}
-
-	var pooling string
-	for _, m := range modules {
-		switch m.Type {
-		case "sentence_transformers.models.Pooling":
-			pooling = m.Path
-		case "sentence_transformers.models.Normalize":
-			p.normalizeEmbeddings = true
-		}
-	}
-
-	if pooling != "" {
-		bts, err := fs.ReadFile(fsys, filepath.Join(pooling, "config.json"))
-		if err != nil {
-			return err
-		}
-
-		var pc struct {
-			PoolingModeCLSToken   bool `json:"pooling_mode_cls_token"`
-			PoolingModeMeanTokens bool `json:"pooling_mode_mean_tokens"`
-		}
-
-		if err := json.Unmarshal(bts, &pc); err != nil {
-			return err
-		}
-
-		if pc.PoolingModeMeanTokens {
-			p.PoolingType = 1
-		} else if pc.PoolingModeCLSToken {
-			p.PoolingType = 2
-		}
-	}
-
-	return nil
-}
-
-func (p *nomicbertModel) KV(t *Tokenizer) KV {
-	kv := p.ModelParameters.KV(t)
-
-	// Determine architecture based on MoE parameters (following qwen3 pattern)
-	arch := "nomic-bert"
-	if p.MoEEveryNLayers > 0 {
-		arch += "-moe"
-	}
-
-	kv["general.architecture"] = arch
-	kv["attention.causal"] = false
-	kv["pooling_type"] = p.PoolingType
-	kv["normalize_embeddings"] = p.normalizeEmbeddings
-
-	kv["block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers)
-
-	if contextLength := p.MaxPositionEmbeddings; contextLength > 0 {
-		kv["context_length"] = contextLength
-	}
-
-	if embeddingLength := p.HiddenSize; embeddingLength > 0 {
-		kv["embedding_length"] = p.HiddenSize
-	}
-
-	if feedForwardLength := p.IntermediateSize; feedForwardLength > 0 {
-		kv["feed_forward_length"] = p.IntermediateSize
-	}
-
-	if headCount := p.NumAttentionHeads; headCount > 0 {
-		kv["attention.head_count"] = p.NumAttentionHeads
-	}
-
-	if kvHeadCount := p.NumKeyValueHeads; kvHeadCount > 0 {
-		kv["attention.head_count_kv"] = p.NumKeyValueHeads
-	}
-
-	if layerNormEpsilon := cmp.Or(p.LayerNormEPS, p.LayerNormEpsilon); layerNormEpsilon > 0 {
-		kv["attention.layer_norm_epsilon"] = layerNormEpsilon
-	}
-
-	if p.RopeFreqBase > 0 {
-		kv["rope.freq_base"] = p.RopeFreqBase
-	}
-
-	// MoE specific parameters (only if MoE is enabled)
-	if p.NumExperts > 0 {
-		kv["expert_count"] = p.NumExperts
-	}
-
-	if p.NumExpertsUsed > 0 {
-		kv["expert_used_count"] = p.NumExpertsUsed
-	}
-
-	if p.MoEEveryNLayers > 0 {
-		kv["moe_every_n_layers"] = p.MoEEveryNLayers
-	}
-
-	kv["tokenizer.ggml.model"] = "bert"
-	kv["tokenizer.ggml.token_type_count"] = uint32(2)
-
-	// convert to phantom space tokens
-	for i, e := range t.Tokens {
-		switch {
-		case strings.HasPrefix(e, "[") && strings.HasSuffix(e, "]"):
-			// noop - keep special tokens as-is
-		case strings.HasPrefix(e, "##"):
-			t.Tokens[i] = e[2:]
-		default:
-			t.Tokens[i] = "\u2581" + e
-		}
-	}
-
-	kv["tokenizer.ggml.tokens"] = t.Tokens
-
-	return kv
-}
-
-func (p *nomicbertModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	out := make([]*ggml.Tensor, 0, len(ts))
-	for _, t := range ts {
-		if slices.Contains([]string{
-			"embeddings.position_ids",
-			"pooler.dense.weight",
-			"pooler.dense.bias",
-		}, t.Name()) {
-			continue
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (nomicbertModel) Replacements() []string {
-	return []string{
-		"encoder.layer", "blk",
-		"encoder.layers", "blk",
-		"embeddings.word_embeddings", "token_embd",
-		"embeddings.token_type_embeddings", "token_types",
-		"embeddings.LayerNorm", "token_embd_norm",
-
-		"attention.self.qkv", "attn_qkv",
-
-		"attention.output.dense", "attn_output",
-		"attention.output.LayerNorm", "attn_output_norm",
-
-		"mlp.up", "ffn_up",
-		"mlp.down", "ffn_down",
-
-		"mlp.router", "ffn_gate_inp",
-		"mlp.experts.up", "ffn_up_exps",
-		"mlp.experts.down", "ffn_down_exps",
-
-		"intermediate.dense", "ffn_up",
-		"output.dense", "ffn_down",
-		"output.LayerNorm", "layer_output_norm",
-	}
-}

convert/convert_olmo.go

@@ -1,117 +0,0 @@
-package convert
-
-import (
-	"cmp"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type ropeScaling struct {
-	Factor                    float32 `json:"factor"`
-	OriginalMaxPositionEmbeds uint32  `json:"original_max_position_embeddings"`
-	AttentionFactor           float32 `json:"attention_factor"`
-	BetaFast                  float32 `json:"beta_fast"`
-	BetaSlow                  float32 `json:"beta_slow"`
-	RopeType                  string  `json:"rope_type"`
-	ExtrapolationFactor       float32 `json:"extrapolation_factor"`
-}
-
-type olmoModel struct {
-	ModelParameters
-
-	HiddenSize            uint32       `json:"hidden_size"`
-	NumHiddenLayers       uint32       `json:"num_hidden_layers"`
-	IntermediateSize      uint32       `json:"intermediate_size"`
-	NumAttentionHeads     uint32       `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32       `json:"num_key_value_heads"`
-	MaxPositionEmbeddings uint32       `json:"max_position_embeddings"`
-	RMSNormEPS            float32      `json:"rms_norm_eps"`
-	RopeTheta             float32      `json:"rope_theta"`
-	RopeScaling           *ropeScaling `json:"rope_scaling"`
-	SlidingWindow         uint32       `json:"sliding_window"`
-	LayerTypes            []string     `json:"layer_types"`
-}
-
-var _ ModelConverter = (*olmoModel)(nil)
-
-func (p *olmoModel) KV(t *Tokenizer) KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "olmo3"
-	kv["olmo3.block_count"] = p.NumHiddenLayers
-	kv["olmo3.context_length"] = p.MaxPositionEmbeddings
-	kv["olmo3.embedding_length"] = p.HiddenSize
-	kv["olmo3.feed_forward_length"] = p.IntermediateSize
-	kv["olmo3.attention.head_count"] = p.NumAttentionHeads
-	kv["olmo3.attention.head_count_kv"] = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
-
-	if p.RopeTheta > 0 {
-		kv["olmo3.rope.freq_base"] = p.RopeTheta
-	}
-
-	if p.RopeScaling != nil {
-		if p.RopeScaling.Factor > 0 {
-			kv["olmo3.rope.scaling.factor"] = p.RopeScaling.Factor
-		}
-		if p.RopeScaling.OriginalMaxPositionEmbeds > 0 {
-			kv["olmo3.rope.scaling.original_context_length"] = p.RopeScaling.OriginalMaxPositionEmbeds
-		}
-		if p.RopeScaling.AttentionFactor > 0 {
-			kv["olmo3.rope.scaling.attn_factor"] = p.RopeScaling.AttentionFactor
-		}
-		if p.RopeScaling.RopeType != "" {
-			kv["olmo3.rope.scaling.type"] = p.RopeScaling.RopeType
-		}
-	}
-
-	if p.RMSNormEPS > 0 {
-		kv["olmo3.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
-	}
-
-	if p.SlidingWindow > 0 {
-		kv["olmo3.attention.sliding_window"] = p.SlidingWindow
-	}
-
-	if len(p.LayerTypes) > 0 {
-		slidingPattern := make([]bool, len(p.LayerTypes))
-		for i, layerType := range p.LayerTypes {
-			slidingPattern[i] = (layerType == "sliding_attention")
-		}
-		kv["olmo3.attention.sliding_window_pattern"] = slidingPattern
-	}
-
-	return kv
-}
-
-func (p *olmoModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	out := make([]*ggml.Tensor, 0, len(ts))
-	for _, t := range ts {
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *olmoModel) Replacements() []string {
-	return []string{
-		"lm_head", "output",
-		"model.embed_tokens", "token_embd",
-		"model.layers", "blk",
-		"model.norm", "output_norm",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.o_proj", "attn_output",
-		"self_attn.q_norm", "attn_q_norm",
-		"self_attn.k_norm", "attn_k_norm",
-		"post_attention_layernorm", "post_attention_norm",
-		"post_feedforward_layernorm", "post_ffw_norm",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.down_proj", "ffn_down",
-		"mlp.up_proj", "ffn_up",
-	}
-}

convert/convert_phi3.go

@@ -37,7 +37,7 @@ type phi3Model struct {
 
 var _ ModelConverter = (*phi3Model)(nil)
 
-func (p *phi3Model) KV(t *Tokenizer) KV {
+func (p *phi3Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "phi3"
 	kv["phi3.context_length"] = p.MaxPositionEmbeddings

convert/convert_qwen2.go

@@ -22,7 +22,7 @@ type qwen2Model struct {
 
 var _ ModelConverter = (*qwen2Model)(nil)
 
-func (q *qwen2Model) KV(t *Tokenizer) KV {
+func (q *qwen2Model) KV(t *Tokenizer) ggml.KV {
 	kv := q.ModelParameters.KV(t)
 	kv["general.architecture"] = "qwen2"
 	kv["qwen2.block_count"] = q.HiddenLayers

convert/convert_qwen25vl.go

@@ -29,7 +29,7 @@ type qwen25VLModel struct {
 
 var _ ModelConverter = (*qwen25VLModel)(nil)
 
-func (q *qwen25VLModel) KV(t *Tokenizer) KV {
+func (q *qwen25VLModel) KV(t *Tokenizer) ggml.KV {
 	kv := q.ModelParameters.KV(t)
 	kv["general.architecture"] = "qwen25vl"
 

convert/convert_qwen3.go

@@ -32,7 +32,7 @@ type qwen3Model struct {
 }
 
 // KV implements ModelConverter.
-func (q *qwen3Model) KV(t *Tokenizer) KV {
+func (q *qwen3Model) KV(t *Tokenizer) ggml.KV {
 	arch := "qwen3"
 	if q.NumExperts > 0 {
 		arch += "moe"

convert/convert_qwen3vl.go

@@ -45,7 +45,7 @@ func (m *qwen3VLModel) parseMore(fsys fs.FS) error {
 	return json.Unmarshal(bts, &m.VisionModel)
 }
 
-func (m *qwen3VLModel) KV(t *Tokenizer) KV {
+func (m *qwen3VLModel) KV(t *Tokenizer) ggml.KV {
 	kv := m.qwen3Model.KV(t)
 
 	arch := "qwen3vl"

convert/convert_test.go

@@ -19,7 +19,6 @@ import (
 	"testing"
 
 	"github.com/google/go-cmp/cmp"
-	fsc "github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/fs/ggml"
 )
 
@@ -29,7 +28,7 @@ type tensorData struct {
 	Shape   []int  `json:"shape"`
 }
 
-func convertFull(t *testing.T, fsys fs.FS) (*os.File, fsc.Config, ggml.Tensors) {
+func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
 	t.Helper()
 
 	f, err := os.CreateTemp(t.TempDir(), "f16")
@@ -60,10 +59,9 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, fsc.Config, ggml.Tensors)
 	return r, m.KV(), m.Tensors()
 }
 
-func generateResultsJSON(t *testing.T, f *os.File, kv fsc.Config, tensors ggml.Tensors) map[string]string {
+func generateResultsJSON(t *testing.T, f *os.File, kv ggml.KV, tensors ggml.Tensors) map[string]string {
 	actual := make(map[string]string)
-	for k := range kv.Keys() {
-		v := kv.Value(k)
+	for k, v := range kv {
 		if s, ok := v.(json.Marshaler); !ok {
 			actual[k] = fmt.Sprintf("%v", v)
 		} else {
@@ -279,7 +277,7 @@ func generateSafetensorTestData(t *testing.T, tempDir string, tensorData map[str
 func TestConvertAdapter(t *testing.T) {
 	type AdapterCase struct {
 		Name     string
-		BaseKV   KV
+		BaseKV   map[string]any
 		Expected map[string]string
 	}
 

convert/tokenizer_spm.go

@@ -49,8 +49,7 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 			tt := int32(sentencepiece.ModelProto_SentencePiece_NORMAL)
 
 			// temporary fix to handle gemma3 broken configs
-			// TODO(parthsareen): allow reading of tokenizer.json to allow managing special tokens when using spm
-			if slices.Contains([]string{"<end_of_turn>", "<start_of_turn>", "<start_function_declaration>", "<end_function_declaration>", "<start_function_call>", "<end_function_call>", "<start_function_response>", "<end_function_response>", "<escape>"}, piece.GetPiece()) {
+			if slices.Contains([]string{"<end_of_turn>", "<start_of_turn>"}, piece.GetPiece()) {
 				tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
 			}
 

discover/runner.go

@@ -65,7 +65,6 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 		}
 
 		slog.Info("discovering available GPUs...")
-		detectIncompatibleLibraries()
 
 		// Warn if any user-overrides are set which could lead to incorrect GPU discovery
 		overrideWarnings()
@@ -99,9 +98,6 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 					continue
 				} else if jetpack != "" && filepath.Base(dir) != "cuda_"+jetpack {
 					continue
-				} else if jetpack == "" && strings.Contains(filepath.Base(dir), "cuda_jetpack") {
-					slog.Debug("jetpack not detected (set JETSON_JETPACK or OLLAMA_LLM_LIBRARY to override), skipping", "libDir", dir)
-					continue
 				} else if !envconfig.EnableVulkan() && strings.Contains(filepath.Base(dir), "vulkan") {
 					slog.Info("experimental Vulkan support disabled.  To enable, set OLLAMA_VULKAN=1")
 					continue
@@ -147,7 +143,7 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 			wg.Add(1)
 			go func(i int) {
 				defer wg.Done()
-				extraEnvs := ml.GetVisibleDevicesEnv(devices[i:i+1], true)
+				extraEnvs := ml.GetVisibleDevicesEnv(devices[i : i+1])
 				devices[i].AddInitValidation(extraEnvs)
 				if len(bootstrapDevices(ctx2ndPass, devices[i].LibraryPath, extraEnvs)) == 0 {
 					slog.Debug("filtering device which didn't fully initialize",
@@ -333,8 +329,7 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 			defer cancel()
 
 			// Apply any dev filters to avoid re-discovering unsupported devices, and get IDs correct
-			// We avoid CUDA filters here to keep ROCm from failing to discover GPUs in a mixed environment
-			devFilter := ml.GetVisibleDevicesEnv(devices, false)
+			devFilter := ml.GetVisibleDevicesEnv(devices)
 
 			for dir := range libDirs {
 				updatedDevices := bootstrapDevices(ctx, []string{ml.LibOllamaPath, dir}, devFilter)
@@ -489,16 +484,3 @@ func overrideWarnings() {
 		slog.Warn("if GPUs are not correctly discovered, unset and try again")
 	}
 }
-
-func detectIncompatibleLibraries() {
-	if runtime.GOOS != "windows" {
-		return
-	}
-	basePath, err := exec.LookPath("ggml-base.dll")
-	if err != nil || basePath == "" {
-		return
-	}
-	if !strings.HasPrefix(basePath, ml.LibOllamaPath) {
-		slog.Warn("potentially incompatible library detected in PATH", "location", basePath)
-	}
-}

docs/README.md

@@ -14,7 +14,6 @@
 * [API Reference](https://docs.ollama.com/api)
 * [Modelfile Reference](https://docs.ollama.com/modelfile)
 * [OpenAI Compatibility](https://docs.ollama.com/api/openai-compatibility)
-* [Anthropic Compatibility](./api/anthropic-compatibility.mdx)
 
 ### Resources
 

docs/api.md

@@ -50,7 +50,7 @@ Generate a response for a given prompt with a provided model. This is a streamin
 Advanced parameters (optional):
 
 - `format`: the format to return a response in. Format can be `json` or a JSON schema
-- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.mdx#valid-parameters-and-values) such as `temperature`
+- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `system`: system message to (overrides what is defined in the `Modelfile`)
 - `template`: the prompt template to use (overrides what is defined in the `Modelfile`)
 - `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
@@ -507,7 +507,7 @@ The `message` object has the following fields:
 Advanced parameters (optional):
 
 - `format`: the format to return a response in. Format can be `json` or a JSON schema.
-- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.mdx#valid-parameters-and-values) such as `temperature`
+- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
 
@@ -895,11 +895,11 @@ curl http://localhost:11434/api/chat -d '{
       "tool_calls": [
         {
           "function": {
-            "name": "get_weather",
+            "name": "get_temperature",
             "arguments": {
               "city": "Toronto"
             }
-          }
+          },
         }
       ]
     },
@@ -907,7 +907,7 @@ curl http://localhost:11434/api/chat -d '{
     {
       "role": "tool",
       "content": "11 degrees celsius",
-      "tool_name": "get_weather"
+      "tool_name": "get_temperature",
     }
   ],
   "stream": false,
@@ -1189,7 +1189,7 @@ If you are creating a model from a safetensors directory or from a GGUF file, yo
 - `template`: (optional) the prompt template for the model
 - `license`: (optional) a string or list of strings containing the license or licenses for the model
 - `system`: (optional) a string containing the system prompt for the model
-- `parameters`: (optional) a dictionary of parameters for the model (see [Modelfile](./modelfile.mdx#valid-parameters-and-values) for a list of parameters)
+- `parameters`: (optional) a dictionary of parameters for the model (see [Modelfile](./modelfile.md#valid-parameters-and-values) for a list of parameters)
 - `messages`: (optional) a list of message objects used to create a conversation
 - `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
 - `quantize` (optional): quantize a non-quantized (e.g. float16) model
@@ -1698,7 +1698,7 @@ Generate embeddings from a model
 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.mdx#valid-parameters-and-values) such as `temperature`
+- `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
 
@@ -1817,7 +1817,7 @@ Generate embeddings from a model
 
 Advanced parameters:
 
-- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.mdx#valid-parameters-and-values) such as `temperature`
+- `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`)
 
 ### Examples

docs/api/anthropic-compatibility.mdx

@@ -1,406 +0,0 @@
----
-title: Anthropic compatibility
----
-
-Ollama provides compatibility with the [Anthropic Messages API](https://docs.anthropic.com/en/api/messages) to help connect existing applications to Ollama, including tools like Claude Code.
-
-## Recommended models
-
-For coding use cases, models like `glm-4.7:cloud`, `minimax-m2.1:cloud`, and `qwen3-coder` are recommended.
-
-Pull a model before use:
-```shell
-ollama pull qwen3-coder
-ollama pull glm-4.7:cloud
-```
-
-## Usage
-
-### Environment variables
-
-To use Ollama with tools that expect the Anthropic API (like Claude Code), set these environment variables:
-
-```shell
-export ANTHROPIC_BASE_URL=http://localhost:11434
-export ANTHROPIC_API_KEY=ollama  # required but ignored
-```
-
-### Simple `/v1/messages` example
-
-<CodeGroup dropdown>
-
-```python basic.py
-import anthropic
-
-client = anthropic.Anthropic(
-    base_url='http://localhost:11434',
-    api_key='ollama',  # required but ignored
-)
-
-message = client.messages.create(
-    model='qwen3-coder',
-    max_tokens=1024,
-    messages=[
-        {'role': 'user', 'content': 'Hello, how are you?'}
-    ]
-)
-print(message.content[0].text)
-```
-
-```javascript basic.js
-import Anthropic from "@anthropic-ai/sdk";
-
-const anthropic = new Anthropic({
-  baseURL: "http://localhost:11434",
-  apiKey: "ollama", // required but ignored
-});
-
-const message = await anthropic.messages.create({
-  model: "qwen3-coder",
-  max_tokens: 1024,
-  messages: [{ role: "user", content: "Hello, how are you?" }],
-});
-
-console.log(message.content[0].text);
-```
-
-```shell basic.sh
-curl -X POST http://localhost:11434/v1/messages \
--H "Content-Type: application/json" \
--H "x-api-key: ollama" \
--H "anthropic-version: 2023-06-01" \
--d '{
-  "model": "qwen3-coder",
-  "max_tokens": 1024,
-  "messages": [{ "role": "user", "content": "Hello, how are you?" }]
-}'
-```
-
-</CodeGroup>
-
-### Streaming example
-
-<CodeGroup dropdown>
-
-```python streaming.py
-import anthropic
-
-client = anthropic.Anthropic(
-    base_url='http://localhost:11434',
-    api_key='ollama',
-)
-
-with client.messages.stream(
-    model='qwen3-coder',
-    max_tokens=1024,
-    messages=[{'role': 'user', 'content': 'Count from 1 to 10'}]
-) as stream:
-    for text in stream.text_stream:
-        print(text, end='', flush=True)
-```
-
-```javascript streaming.js
-import Anthropic from "@anthropic-ai/sdk";
-
-const anthropic = new Anthropic({
-  baseURL: "http://localhost:11434",
-  apiKey: "ollama",
-});
-
-const stream = await anthropic.messages.stream({
-  model: "qwen3-coder",
-  max_tokens: 1024,
-  messages: [{ role: "user", content: "Count from 1 to 10" }],
-});
-
-for await (const event of stream) {
-  if (
-    event.type === "content_block_delta" &&
-    event.delta.type === "text_delta"
-  ) {
-    process.stdout.write(event.delta.text);
-  }
-}
-```
-
-```shell streaming.sh
-curl -X POST http://localhost:11434/v1/messages \
--H "Content-Type: application/json" \
--d '{
-  "model": "qwen3-coder",
-  "max_tokens": 1024,
-  "stream": true,
-  "messages": [{ "role": "user", "content": "Count from 1 to 10" }]
-}'
-```
-
-</CodeGroup>
-
-### Tool calling example
-
-<CodeGroup dropdown>
-
-```python tools.py
-import anthropic
-
-client = anthropic.Anthropic(
-    base_url='http://localhost:11434',
-    api_key='ollama',
-)
-
-message = client.messages.create(
-    model='qwen3-coder',
-    max_tokens=1024,
-    tools=[
-        {
-            'name': 'get_weather',
-            'description': 'Get the current weather in a location',
-            'input_schema': {
-                'type': 'object',
-                'properties': {
-                    'location': {
-                        'type': 'string',
-                        'description': 'The city and state, e.g. San Francisco, CA'
-                    }
-                },
-                'required': ['location']
-            }
-        }
-    ],
-    messages=[{'role': 'user', 'content': "What's the weather in San Francisco?"}]
-)
-
-for block in message.content:
-    if block.type == 'tool_use':
-        print(f'Tool: {block.name}')
-        print(f'Input: {block.input}')
-```
-
-```javascript tools.js
-import Anthropic from "@anthropic-ai/sdk";
-
-const anthropic = new Anthropic({
-  baseURL: "http://localhost:11434",
-  apiKey: "ollama",
-});
-
-const message = await anthropic.messages.create({
-  model: "qwen3-coder",
-  max_tokens: 1024,
-  tools: [
-    {
-      name: "get_weather",
-      description: "Get the current weather in a location",
-      input_schema: {
-        type: "object",
-        properties: {
-          location: {
-            type: "string",
-            description: "The city and state, e.g. San Francisco, CA",
-          },
-        },
-        required: ["location"],
-      },
-    },
-  ],
-  messages: [{ role: "user", content: "What's the weather in San Francisco?" }],
-});
-
-for (const block of message.content) {
-  if (block.type === "tool_use") {
-    console.log("Tool:", block.name);
-    console.log("Input:", block.input);
-  }
-}
-```
-
-```shell tools.sh
-curl -X POST http://localhost:11434/v1/messages \
--H "Content-Type: application/json" \
--d '{
-  "model": "qwen3-coder",
-  "max_tokens": 1024,
-  "tools": [
-    {
-      "name": "get_weather",
-      "description": "Get the current weather in a location",
-      "input_schema": {
-        "type": "object",
-        "properties": {
-          "location": {
-            "type": "string",
-            "description": "The city and state"
-          }
-        },
-        "required": ["location"]
-      }
-    }
-  ],
-  "messages": [{ "role": "user", "content": "What is the weather in San Francisco?" }]
-}'
-```
-
-</CodeGroup>
-
-## Using with Claude Code
-
-[Claude Code](https://code.claude.com/docs/en/overview) can be configured to use Ollama as its backend:
-
-```shell
-ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
-```
-
-Or set the environment variables in your shell profile:
-
-```shell
-export ANTHROPIC_BASE_URL=http://localhost:11434
-export ANTHROPIC_API_KEY=ollama
-```
-
-Then run Claude Code with any Ollama model:
-
-```shell
-# Local models
-claude --model qwen3-coder
-claude --model gpt-oss:20b
-
-# Cloud models
-claude --model glm-4.7:cloud
-claude --model minimax-m2.1:cloud
-```
-
-## Endpoints
-
-### `/v1/messages`
-
-#### Supported features
-
-- [x] Messages
-- [x] Streaming
-- [x] System prompts
-- [x] Multi-turn conversations
-- [x] Vision (images)
-- [x] Tools (function calling)
-- [x] Tool results
-- [x] Thinking/extended thinking
-
-#### Supported request fields
-
-- [x] `model`
-- [x] `max_tokens`
-- [x] `messages`
-  - [x] Text `content`
-  - [x] Image `content` (base64)
-  - [x] Array of content blocks
-  - [x] `tool_use` blocks
-  - [x] `tool_result` blocks
-  - [x] `thinking` blocks
-- [x] `system` (string or array)
-- [x] `stream`
-- [x] `temperature`
-- [x] `top_p`
-- [x] `top_k`
-- [x] `stop_sequences`
-- [x] `tools`
-- [x] `thinking`
-- [ ] `tool_choice`
-- [ ] `metadata`
-
-#### Supported response fields
-
-- [x] `id`
-- [x] `type`
-- [x] `role`
-- [x] `model`
-- [x] `content` (text, tool_use, thinking blocks)
-- [x] `stop_reason` (end_turn, max_tokens, tool_use)
-- [x] `usage` (input_tokens, output_tokens)
-
-#### Streaming events
-
-- [x] `message_start`
-- [x] `content_block_start`
-- [x] `content_block_delta` (text_delta, input_json_delta, thinking_delta)
-- [x] `content_block_stop`
-- [x] `message_delta`
-- [x] `message_stop`
-- [x] `ping`
-- [x] `error`
-
-## Models
-
-Ollama supports both local and cloud models.
-
-### Local models
-
-Pull a local model before use:
-
-```shell
-ollama pull qwen3-coder
-```
-
-Recommended local models:
-- `qwen3-coder` - Excellent for coding tasks
-- `gpt-oss:20b` - Strong general-purpose model
-
-### Cloud models
-
-Cloud models are available immediately without pulling:
-
-- `glm-4.7:cloud` - High-performance cloud model
-- `minimax-m2.1:cloud` - Fast cloud model
-
-### Default model names
-
-For tooling that relies on default Anthropic model names such as `claude-3-5-sonnet`, use `ollama cp` to copy an existing model name:
-
-```shell
-ollama cp qwen3-coder claude-3-5-sonnet
-```
-
-Afterwards, this new model name can be specified in the `model` field:
-
-```shell
-curl http://localhost:11434/v1/messages \
-    -H "Content-Type: application/json" \
-    -d '{
-        "model": "claude-3-5-sonnet",
-        "max_tokens": 1024,
-        "messages": [
-            {
-                "role": "user",
-                "content": "Hello!"
-            }
-        ]
-    }'
-```
-
-## Differences from the Anthropic API
-
-### Behavior differences
-
-- API key is accepted but not validated
-- `anthropic-version` header is accepted but not used
-- Token counts are approximations based on the underlying model's tokenizer
-
-### Not supported
-
-The following Anthropic API features are not currently supported:
-
-| Feature | Description |
-|---------|-------------|
-| `/v1/messages/count_tokens` | Token counting endpoint |
-| `tool_choice` | Forcing specific tool use or disabling tools |
-| `metadata` | Request metadata (user_id) |
-| Prompt caching | `cache_control` blocks for caching prefixes |
-| Batches API | `/v1/messages/batches` for async batch processing |
-| Citations | `citations` content blocks |
-| PDF support | `document` content blocks with PDF files |
-| Server-sent errors | `error` events during streaming (errors return HTTP status) |
-
-### Partial support
-
-| Feature | Status |
-|---------|--------|
-| Image content | Base64 images supported; URL images not supported |
-| Extended thinking | Basic support; `budget_tokens` accepted but not enforced |

docs/capabilities/tool-calling.mdx

@@ -15,7 +15,7 @@ Also known as "single-shot" tool calling.
     ```shell
     curl -s http://localhost:11434/api/chat -H "Content-Type: application/json" -d '{
       "model": "qwen3",
-      "messages": [{"role": "user", "content": "What is the temperature in New York?"}],
+      "messages": [{"role": "user", "content": "What's the temperature in New York?"}],
       "stream": false,
       "tools": [
         {
@@ -41,7 +41,7 @@ Also known as "single-shot" tool calling.
     curl -s http://localhost:11434/api/chat -H "Content-Type: application/json" -d '{
       "model": "qwen3",
       "messages": [
-        {"role": "user", "content": "What is the temperature in New York?"},
+        {"role": "user", "content": "What's the temperature in New York?"},
         {
           "role": "assistant",
           "tool_calls": [
@@ -90,7 +90,7 @@ Also known as "single-shot" tool calling.
       }
       return temperatures.get(city, "Unknown")
 
-    messages = [{"role": "user", "content": "What is the temperature in New York?"}]
+    messages = [{"role": "user", "content": "What's the temperature in New York?"}]
 
     # pass functions directly as tools in the tools list or as a JSON schema
     response = chat(model="qwen3", messages=messages, tools=[get_temperature], think=True)
@@ -146,7 +146,7 @@ Also known as "single-shot" tool calling.
       },
     ]
 
-    const messages = [{ role: 'user', content: "What is the temperature in New York?" }]
+    const messages = [{ role: 'user', content: "What's the temperature in New York?" }]
 
     const response = await ollama.chat({
       model: 'qwen3',
@@ -609,7 +609,7 @@ def get_temperature(city: str) -> str:
   return temperatures.get(city, 'Unknown')
 
 
-messages = [{'role': 'user', 'content': "What is the temperature in New York?"}]
+messages = [{'role': 'user', 'content': "What's the temperature in New York?"}]
 
 while True:
   stream = chat(
@@ -684,7 +684,7 @@ const getTemperatureTool = {
 }
 
 async function agentLoop() {
-  const messages = [{ role: 'user', content: "What is the temperature in New York?" }]
+  const messages = [{ role: 'user', content: "What's the temperature in New York?" }]
 
   while (true) {
     const stream = await ollama.chat({

docs/capabilities/vision.mdx

@@ -36,6 +36,7 @@ Provide an `images` array. SDKs accept file paths, URLs or raw bytes while the R
         }],
         "stream": false
     }'
+    "
     ```
   </Tab>
   <Tab title="Python">

docs/capabilities/web-search.mdx

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

docs/development.md

@@ -49,8 +49,6 @@ Install prerequisites:
     - [Ninja](https://github.com/ninja-build/ninja/releases)
 - (Optional) NVIDIA GPU support
     - [CUDA SDK](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=11&target_type=exe_network)
-- (Optional) VULKAN GPU support
-    - [VULKAN SDK](https://vulkan.lunarg.com/sdk/home) - useful for AMD/Intel GPUs
 
 Then, configure and build the project:
 
@@ -59,17 +57,6 @@ cmake -B build
 cmake --build build --config Release
 ```
 
-> Building for Vulkan requires VULKAN_SDK environment variable:
-> 
-> PowerShell
-> ```powershell
-> $env:VULKAN_SDK="C:\VulkanSDK\<version>"
-> ```
-> CMD
-> ```cmd
-> set VULKAN_SDK=C:\VulkanSDK\<version>
-> ```
-
 > [!IMPORTANT]
 > Building for ROCm requires additional flags:
 > ```
@@ -78,7 +65,6 @@ cmake --build build --config Release
 > ```
 
 
-
 Lastly, run Ollama:
 
 ```shell
@@ -98,9 +84,7 @@ Install prerequisites:
     - [ROCm](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)
 - (Optional) NVIDIA GPU support
     - [CUDA SDK](https://developer.nvidia.com/cuda-downloads)
-- (Optional) VULKAN GPU support
-    - [VULKAN SDK](https://vulkan.lunarg.com/sdk/home) - useful for AMD/Intel GPUs
-    - Or install via package manager: `sudo apt install vulkan-sdk` (Ubuntu/Debian) or `sudo dnf install vulkan-sdk` (Fedora/CentOS)
+
 > [!IMPORTANT]
 > Ensure prerequisites are in `PATH` before running CMake.
 

docs/docs.json

@@ -32,9 +32,7 @@
     "codeblocks": "system"
   },
   "contextual": {
-    "options": [
-      "copy"
-    ]
+    "options": ["copy"]
   },
   "navbar": {
     "links": [
@@ -54,9 +52,7 @@
       "display": "simple"
     },
     "examples": {
-      "languages": [
-        "curl"
-      ]
+      "languages": ["curl"]
     }
   },
   "redirects": [
@@ -101,7 +97,6 @@
           {
             "group": "Integrations",
             "pages": [
-              "/integrations/claude-code",
               "/integrations/vscode",
               "/integrations/jetbrains",
               "/integrations/codex",
@@ -111,9 +106,7 @@
               "/integrations/zed",
               "/integrations/roo-code",
               "/integrations/n8n",
-              "/integrations/xcode",
-              "/integrations/onyx",
-              "/integrations/marimo"
+              "/integrations/xcode"
             ]
           },
           {
@@ -146,8 +139,7 @@
               "/api/streaming",
               "/api/usage",
               "/api/errors",
-              "/api/openai-compatibility",
-              "/api/anthropic-compatibility"
+              "/api/openai-compatibility"
             ]
           },
           {

docs/faq.mdx

@@ -14,15 +14,15 @@ curl -fsSL https://ollama.com/install.sh | sh
 
 ## How can I view the logs?
 
-Review the [Troubleshooting](./troubleshooting) docs for more about using logs.
+Review the [Troubleshooting](./troubleshooting.md) docs for more about using logs.
 
 ## Is my GPU compatible with Ollama?
 
-Please refer to the [GPU docs](./gpu).
+Please refer to the [GPU docs](./gpu.md).
 
 ## How can I specify the context window size?
 
-By default, Ollama uses a context window size of 4096 tokens.
+By default, Ollama uses a context window size of 2048 tokens.
 
 This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use:
 
@@ -57,13 +57,8 @@ ollama ps
 ```
 
 <Info>
-
-**Output**:
-
-```
-NAME        ID            SIZE    PROCESSOR   UNTIL
-llama3:70b  bcfb190ca3a7  42 GB   100% GPU    4 minutes from now
-```
+  **Output**: ``` NAME ID SIZE PROCESSOR UNTIL llama3:70b bcfb190ca3a7 42 GB
+  100% GPU 4 minutes from now ```
 </Info>
 
 The `Processor` column will show which memory the model was loaded in to:
@@ -390,4 +385,4 @@ Ollama for Windows and macOS register as a login item during installation.  You
 - In `Task Manager` go to the `Startup apps` tab, search for `ollama` then click `Disable`
 
 **MacOS**
-- Open `Settings` and search for "Login Items", find the `Ollama` entry under "Allow in the Background`, then click the slider to disable.
+- Open `Settings` and search for "Login Items", find the `Ollama` entry under "Allow in the Background`, then click the slider to disable.

docs/gpu.mdx

@@ -33,7 +33,7 @@ Check your compute compatibility to see if your card is supported:
 | 5.0                | GeForce GTX         | `GTX 750 Ti` `GTX 750` `NVS 810`                                                                                               |
 |                    | Quadro              | `K2200` `K1200` `K620` `M1200` `M520` `M5000M` `M4000M` `M3000M` `M2000M` `M1000M` `K620M` `M600M` `M500M`                     |
 
-For building locally to support older GPUs, see [developer](./development#linux-cuda-nvidia)
+For building locally to support older GPUs, see [developer.md](./development.md#linux-cuda-nvidia)
 
 ### GPU Selection
 
@@ -54,7 +54,7 @@ sudo modprobe nvidia_uvm`
 
 Ollama supports the following AMD GPUs via the ROCm library:
 
-> **NOTE:**
+> [!NOTE]
 > Additional AMD GPU support is provided by the Vulkan Library - see below.
 
 
@@ -132,9 +132,9 @@ Ollama supports GPU acceleration on Apple devices via the Metal API.
 
 ## Vulkan GPU Support
 
-> **NOTE:**
+> [!NOTE]
 > Vulkan is currently an Experimental feature.  To enable, you must set OLLAMA_VULKAN=1 for the Ollama server as
-described in the [FAQ](faq#how-do-i-configure-ollama-server)
+described in the [FAQ](faq.md#how-do-i-configure-ollama-server)
 
 Additional GPU support on Windows and Linux is provided via
 [Vulkan](https://www.vulkan.org/). On Windows most GPU vendors drivers come
@@ -161,6 +161,6 @@ sudo setcap cap_perfmon+ep /usr/local/bin/ollama
 
 To select specific Vulkan GPU(s), you can set the environment variable
 `GGML_VK_VISIBLE_DEVICES` to one or more numeric IDs on the Ollama server as
-described in the [FAQ](faq#how-do-i-configure-ollama-server). If you
+described in the [FAQ](faq.md#how-do-i-configure-ollama-server). If you
 encounter any problems with Vulkan based GPUs, you can disable all Vulkan GPUs
 by setting `GGML_VK_VISIBLE_DEVICES=-1` 

docs/integrations/claude-code.mdx

@@ -1,69 +0,0 @@
----
-title: Claude Code
----
-
-## Install
-
-Install [Claude Code](https://code.claude.com/docs/en/overview):
-
-<CodeGroup>
-
-```shell macOS / Linux
-curl -fsSL https://claude.ai/install.sh | bash
-```
-
-```powershell Windows
-irm https://claude.ai/install.ps1 | iex
-```
-
-</CodeGroup>
-
-## Usage with Ollama
-
-Claude Code connects to Ollama using the Anthropic-compatible API.
-
-1. Set the environment variables:
-
-```shell
-export ANTHROPIC_BASE_URL=http://localhost:11434
-export ANTHROPIC_API_KEY=ollama
-```
-
-2. Run Claude Code with an Ollama model:
-
-```shell
-claude --model qwen3-coder
-```
-
-Or run with environment variables inline:
-
-```shell
-ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
-```
-
-## Connecting to ollama.com
-
-1. Create an [API key](https://ollama.com/settings/keys) on ollama.com
-2. Set the environment variables:
-
-```shell
-export ANTHROPIC_BASE_URL=https://ollama.com
-export ANTHROPIC_API_KEY=<your-api-key>
-```
-
-3. Run Claude Code with a cloud model:
-
-```shell
-claude --model glm-4.7:cloud
-```
-
-## Recommended Models
-
-### Cloud models
-- `glm-4.7:cloud` - High-performance cloud model
-- `minimax-m2.1:cloud` - Fast cloud model
-- `qwen3-coder:480b` - Large coding model
-
-### Local models
-- `qwen3-coder` - Excellent for coding tasks
-- `gpt-oss:20b` - Strong general-purpose model

docs/integrations/marimo.mdx

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

docs/integrations/onyx.mdx

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

docs/linux.mdx

@@ -20,8 +20,8 @@ curl -fsSL https://ollama.com/install.sh | sh
 Download and extract the package:
 
 ```shell
-curl -fsSL https://ollama.com/download/ollama-linux-amd64.tar.zst \
-    | sudo tar x -C /usr
+curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
+    | sudo tar zx -C /usr
 ```
 
 Start Ollama:
@@ -41,8 +41,8 @@ ollama -v
 If you have an AMD GPU, also download and extract the additional ROCm package:
 
 ```shell
-curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tar.zst \
-    | sudo tar x -C /usr
+curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tgz \
+    | sudo tar zx -C /usr
 ```
 
 ### ARM64 install
@@ -50,8 +50,8 @@ curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tar.zst \
 Download and extract the ARM64-specific package:
 
 ```shell
-curl -fsSL https://ollama.com/download/ollama-linux-arm64.tar.zst \
-    | sudo tar x -C /usr
+curl -fsSL https://ollama.com/download/ollama-linux-arm64.tgz \
+    | sudo tar zx -C /usr
 ```
 
 ### Adding Ollama as a startup service (recommended)
@@ -146,8 +146,8 @@ curl -fsSL https://ollama.com/install.sh | sh
 Or by re-downloading Ollama:
 
 ```shell
-curl -fsSL https://ollama.com/download/ollama-linux-amd64.tar.zst \
-    | sudo tar x -C /usr
+curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
+    | sudo tar zx -C /usr
 ```
 
 ## Installing specific versions

docs/modelfile.mdx

@@ -41,7 +41,6 @@ INSTRUCTION arguments
 | [`ADAPTER`](#adapter)               | Defines the (Q)LoRA adapters to apply to the model.            |
 | [`LICENSE`](#license)               | Specifies the legal license.                                   |
 | [`MESSAGE`](#message)               | Specify message history.                                       |
-| [`REQUIRES`](#requires)             | Specify the minimum version of Ollama required by the model.   |
 
 ## Examples
 
@@ -249,16 +248,6 @@ MESSAGE user Is Ontario in Canada?
 MESSAGE assistant yes
 ```
 
-### REQUIRES
-
-The `REQUIRES` instruction allows you to specify the minimum version of Ollama required by the model.
-
-```
-REQUIRES <version>
-```
-
-The version should be a valid Ollama version (e.g. 0.14.0).
-
 ## Notes
 
 - the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.

docs/tools/extract-examples/README.md

@@ -1,46 +0,0 @@
-# extract-examples
-
-Extracts code examples from MDX files to a temp directory so you can run them.
-
-## Usage
-
-```shell
-go run docs/tools/extract-examples/main.go <mdx-file>
-```
-
-## Example
-
-```shell
-go run docs/tools/extract-examples/main.go docs/api/openai-compatibility.mdx
-```
-
-Output:
-
-```
-Extracting code examples to: /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
-
-  - 01_basic.py
-  - 01_basic.js
-  - 01_basic.sh
-  - 02_responses.py
-  - 02_responses.js
-  - 02_responses.sh
-  - 03_vision.py
-  - 03_vision.js
-  - 03_vision.sh
-
-Extracted 9 file(s) to /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
-
-To run examples:
-
-  cd /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
-  npm install   # for JS examples
-
-then run individual files with `node file.js`, `python file.py`, `bash file.sh`
-```
-
-## How it works
-
-- Parses MDX files looking for fenced code blocks with filenames (e.g., ` ```python basic.py `)
-- Groups examples by their `<CodeGroup>` and prefixes filenames with `01_`, `02_`, etc.
-- Writes all extracted files to a temp directory

docs/tools/extract-examples/main.go

@@ -1,137 +0,0 @@
-package main
-
-import (
-	"bufio"
-	"fmt"
-	"os"
-	"path/filepath"
-	"regexp"
-	"strings"
-)
-
-func main() {
-	if len(os.Args) < 2 {
-		fmt.Fprintln(os.Stderr, "Usage: go run extract-examples.go <mdx-file>")
-		os.Exit(1)
-	}
-
-	mdxFile := os.Args[1]
-
-	f, err := os.Open(mdxFile)
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error: %v\n", err)
-		os.Exit(1)
-	}
-	defer f.Close()
-
-	// Create temp directory
-	tempDir, err := os.MkdirTemp("", "mdx-examples-*")
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error creating temp dir: %v\n", err)
-		os.Exit(1)
-	}
-
-	fmt.Printf("Extracting code examples to: %s\n\n", tempDir)
-
-	// Patterns
-	codeBlockStart := regexp.MustCompile("^```([a-zA-Z0-9_-]+)\\s+([^\\s]+)$")
-	codeGroupStart := regexp.MustCompile("^<CodeGroup")
-	codeGroupEnd := regexp.MustCompile("^</CodeGroup>")
-
-	scanner := bufio.NewScanner(f)
-	inCodeBlock := false
-	inCodeGroup := false
-	var currentFile string
-	var content strings.Builder
-	count := 0
-	codeGroupNum := 0
-
-	for scanner.Scan() {
-		line := scanner.Text()
-
-		// Track CodeGroup boundaries
-		if codeGroupStart.MatchString(line) {
-			inCodeGroup = true
-			codeGroupNum++
-			continue
-		}
-		if codeGroupEnd.MatchString(line) {
-			inCodeGroup = false
-			continue
-		}
-
-		if inCodeBlock {
-			if line == "```" {
-				// End of code block - write file
-				if currentFile != "" {
-					outPath := filepath.Join(tempDir, currentFile)
-					if err := os.WriteFile(outPath, []byte(content.String()), 0o644); err != nil {
-						fmt.Fprintf(os.Stderr, "Error writing %s: %v\n", currentFile, err)
-					} else {
-						fmt.Printf("  - %s\n", currentFile)
-						count++
-					}
-				}
-				inCodeBlock = false
-				currentFile = ""
-				content.Reset()
-			} else {
-				content.WriteString(line)
-				content.WriteString("\n")
-			}
-		} else {
-			if matches := codeBlockStart.FindStringSubmatch(line); matches != nil {
-				inCodeBlock = true
-				filename := matches[2]
-				// Prefix with CodeGroup number if inside a CodeGroup
-				if inCodeGroup {
-					currentFile = fmt.Sprintf("%02d_%s", codeGroupNum, filename)
-				} else {
-					currentFile = filename
-				}
-				content.Reset()
-			}
-		}
-	}
-
-	if err := scanner.Err(); err != nil {
-		fmt.Fprintf(os.Stderr, "Error reading file: %v\n", err)
-		os.Exit(1)
-	}
-
-	// Write package.json for JavaScript dependencies
-	packageJSON := `{
-  "name": "mdx-examples",
-  "type": "module",
-  "dependencies": {
-    "openai": "^4",
-    "ollama": "^0.5"
-  }
-}
-`
-	if err := os.WriteFile(filepath.Join(tempDir, "package.json"), []byte(packageJSON), 0o644); err != nil {
-		fmt.Fprintf(os.Stderr, "Error writing package.json: %v\n", err)
-	}
-
-	// Write pyproject.toml for Python dependencies
-	pyprojectTOML := `[project]
-name = "mdx-examples"
-version = "0.0.0"
-dependencies = [
-    "openai",
-    "ollama",
-]
-`
-	if err := os.WriteFile(filepath.Join(tempDir, "pyproject.toml"), []byte(pyprojectTOML), 0o644); err != nil {
-		fmt.Fprintf(os.Stderr, "Error writing pyproject.toml: %v\n", err)
-	}
-
-	fmt.Printf("\n")
-	fmt.Printf("Extracted %d file(s) to %s\n", count, tempDir)
-	fmt.Printf("\n")
-	fmt.Printf("To run examples:\n")
-	fmt.Printf("\n")
-	fmt.Printf("  cd %s\n  npm install   # for JS examples\n", tempDir)
-	fmt.Printf("\n")
-	fmt.Printf("then run individual files with `node file.js`, `python file.py`, `bash file.sh`\n")
-}