[test] upstream validation

https://github.com/ggml-org/llama.cpp/issues/15936

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

.devcontainer-scripts/poststart.sh

@@ -2,9 +2,6 @@
 
 cd /workspace
 
-# Grab the pre-stashed backend assets to avoid build issues
-cp -r /build/backend-assets /workspace/backend-assets
-
 # Ensures generated source files are present upon load
 make prepare
 

.devcontainer/docker-compose-devcontainer.yml

@@ -4,10 +4,6 @@ services:
       context: ..
       dockerfile: Dockerfile
       target: devcontainer
-      args:
-      - FFMPEG=true
-      - IMAGE_TYPE=extras
-      - GO_TAGS=p2p tts
     env_file:
       - ../.env
     ports:

.dockerignore

@@ -3,7 +3,13 @@
 .vscode
 .devcontainer
 models
+backends
 examples/chatbot-ui/models
+backend/go/image/stablediffusion-ggml/build/
+backend/go/*/build
+backend/go/*/.cache
+backend/go/*/sources
+backend/go/*/package
 examples/rwkv/models
 examples/**/models
 Dockerfile*

.env

@@ -41,13 +41,6 @@
 ## Uncomment and set to true to enable rebuilding from source
 # REBUILD=true
 
-## Enable go tags, available: p2p, tts
-## p2p: enable distributed inferencing
-## tts: enables text-to-speech with go-piper 
-## (requires REBUILD=true)
-#
-# GO_TAGS=p2p
-
 ## Path where to store generated images
 # LOCALAI_IMAGE_PATH=/tmp/generated/images
 

.github/bump_deps.sh

@@ -3,15 +3,20 @@ set -xe
 REPO=$1
 BRANCH=$2
 VAR=$3
+FILE=$4
+
+if [ -z "$FILE" ]; then
+    FILE="Makefile"
+fi
 
 LAST_COMMIT=$(curl -s -H "Accept: application/vnd.github.VERSION.sha" "https://api.github.com/repos/$REPO/commits/$BRANCH")
 
 # Read $VAR from Makefile (only first match)
 set +e
-CURRENT_COMMIT="$(grep -m1 "^$VAR?=" Makefile | cut -d'=' -f2)"
+CURRENT_COMMIT="$(grep -m1 "^$VAR?=" $FILE | cut -d'=' -f2)"
 set -e
 
-sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
+sed -i $FILE -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
 
 if [ -z "$CURRENT_COMMIT" ]; then
     echo "Could not find $VAR in Makefile."

.github/dependabot.yml

@@ -61,10 +61,6 @@ updates:
     directory: "/backend/python/openvoice"
     schedule:
       interval: "weekly"
-  - package-ecosystem: "pip"
-    directory: "/backend/python/parler-tts"
-    schedule:
-      interval: "weekly"
   - package-ecosystem: "pip"
     directory: "/backend/python/rerankers"
     schedule:

.github/workflows/backend_build.yml

@@ -0,0 +1,243 @@
+---
+name: 'build python backend container images (reusable)'
+
+on:
+  workflow_call:
+    inputs:
+      base-image:
+        description: 'Base image'
+        required: true
+        type: string
+      build-type:
+        description: 'Build type'
+        default: ''
+        type: string
+      cuda-major-version:
+        description: 'CUDA major version'
+        default: "12"
+        type: string
+      cuda-minor-version:
+        description: 'CUDA minor version'
+        default: "1"
+        type: string
+      platforms:
+        description: 'Platforms'
+        default: ''
+        type: string
+      tag-latest:
+        description: 'Tag latest'
+        default: ''
+        type: string
+      tag-suffix:
+        description: 'Tag suffix'
+        default: ''
+        type: string
+      runs-on:
+        description: 'Runs on'
+        required: true
+        default: ''
+        type: string
+      backend:
+        description: 'Backend to build'
+        required: true
+        type: string
+      context:
+        description: 'Build context'
+        required: true
+        type: string
+      dockerfile:
+        description: 'Build Dockerfile'
+        required: true
+        type: string
+      skip-drivers:
+        description: 'Skip drivers'
+        default: 'false'
+        type: string
+    secrets:
+      dockerUsername:
+        required: false
+      dockerPassword:
+        required: false
+      quayUsername:
+        required: true
+      quayPassword:
+        required: true
+
+jobs:
+  backend-build:
+    runs-on: ${{ inputs.runs-on }}
+    env:
+        quay_username: ${{ secrets.quayUsername }}
+    steps:
+
+
+      - name: Free Disk Space (Ubuntu)
+        if: inputs.runs-on == 'ubuntu-latest'
+        uses: jlumbroso/free-disk-space@main
+        with:
+          # this might remove tools that are actually needed,
+          # if set to "true" but frees about 6 GB
+          tool-cache: true
+          # all of these default to true, but feel free to set to
+          # "false" if necessary for your workflow
+          android: true
+          dotnet: true
+          haskell: true
+          large-packages: true
+          docker-images: true
+          swap-storage: true
+
+      - name: Force Install GIT latest
+        run: |
+          sudo apt-get update \
+          && sudo apt-get install -y software-properties-common \
+          && sudo apt-get update \
+          && sudo add-apt-repository -y ppa:git-core/ppa \
+          && sudo apt-get update \
+          && sudo apt-get install -y git
+
+      - name: Checkout
+        uses: actions/checkout@v5
+
+      - name: Release space from worker
+        if: inputs.runs-on == 'ubuntu-latest'
+        run: |
+          echo "Listing top largest packages"
+          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+          head -n 30 <<< "${pkgs}"
+          echo
+          df -h
+          echo
+          sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
+          sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
+          sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
+          sudo rm -rf /usr/local/lib/android
+          sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
+          sudo rm -rf /usr/share/dotnet
+          sudo apt-get remove -y '^mono-.*' || true
+          sudo apt-get remove -y '^ghc-.*' || true
+          sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
+          sudo apt-get remove -y 'php.*' || true
+          sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
+          sudo apt-get remove -y '^google-.*' || true
+          sudo apt-get remove -y azure-cli || true
+          sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
+          sudo apt-get remove -y '^gfortran-.*' || true
+          sudo apt-get remove -y microsoft-edge-stable || true
+          sudo apt-get remove -y firefox || true
+          sudo apt-get remove -y powershell || true
+          sudo apt-get remove -y r-base-core || true
+          sudo apt-get autoremove -y
+          sudo apt-get clean
+          echo
+          echo "Listing top largest packages"
+          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+          head -n 30 <<< "${pkgs}"
+          echo
+          sudo rm -rfv build || true
+          sudo rm -rf /usr/share/dotnet || true
+          sudo rm -rf /opt/ghc || true
+          sudo rm -rf "/usr/local/share/boost" || true
+          sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
+          df -h
+
+      - name: Docker meta
+        id: meta
+        if: github.event_name != 'pull_request'
+        uses: docker/metadata-action@v5
+        with:
+          images: |
+            quay.io/go-skynet/local-ai-backends
+            localai/localai-backends
+          tags: |
+            type=ref,event=branch
+            type=semver,pattern={{raw}}
+            type=sha
+          flavor: |
+            latest=${{ inputs.tag-latest }}
+            suffix=${{ inputs.tag-suffix }},onlatest=true
+
+      - name: Docker meta for PR
+        id: meta_pull_request
+        if: github.event_name == 'pull_request'
+        uses: docker/metadata-action@v5
+        with:
+          images: |
+            quay.io/go-skynet/ci-tests
+          tags: |
+            type=ref,event=branch,suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
+            type=semver,pattern={{raw}},suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
+            type=sha,suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
+          flavor: |
+            latest=${{ inputs.tag-latest }}
+            suffix=${{ inputs.tag-suffix }},onlatest=true
+## End testing image
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@master
+        with:
+          platforms: all
+
+      - name: Set up Docker Buildx
+        id: buildx
+        uses: docker/setup-buildx-action@master
+
+      - name: Login to DockerHub
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.dockerUsername }}
+          password: ${{ secrets.dockerPassword }}
+
+      - name: Login to Quay.io
+        if: ${{ env.quay_username != '' }}
+        uses: docker/login-action@v3
+        with:
+          registry: quay.io
+          username: ${{ secrets.quayUsername }}
+          password: ${{ secrets.quayPassword }}
+
+      - name: Build and push
+        uses: docker/build-push-action@v6
+        if: github.event_name != 'pull_request'
+        with:
+          builder: ${{ steps.buildx.outputs.name }}
+          build-args: |
+            BUILD_TYPE=${{ inputs.build-type }}
+            SKIP_DRIVERS=${{ inputs.skip-drivers }}
+            CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
+            CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
+            BASE_IMAGE=${{ inputs.base-image }}
+            BACKEND=${{ inputs.backend }}
+          context: ${{ inputs.context }}
+          file: ${{ inputs.dockerfile }}
+          cache-from: type=gha
+          platforms: ${{ inputs.platforms }}
+          push: ${{ github.event_name != 'pull_request' }}
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+
+      - name: Build and push (PR)
+        uses: docker/build-push-action@v6
+        if: github.event_name == 'pull_request'
+        with:
+          builder: ${{ steps.buildx.outputs.name }}
+          build-args: |
+            BUILD_TYPE=${{ inputs.build-type }}
+            SKIP_DRIVERS=${{ inputs.skip-drivers }}
+            CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
+            CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
+            BASE_IMAGE=${{ inputs.base-image }}
+            BACKEND=${{ inputs.backend }}
+          context: ${{ inputs.context }}
+          file: ${{ inputs.dockerfile }}
+          cache-from: type=gha
+          platforms: ${{ inputs.platforms }}
+          push: ${{ env.quay_username != '' }}
+          tags: ${{ steps.meta_pull_request.outputs.tags }}
+          labels: ${{ steps.meta_pull_request.outputs.labels }}
+
+
+
+      - name: job summary
+        run: |
+          echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

.github/workflows/backend_build_darwin.yml

@@ -0,0 +1,144 @@
+---
+name: 'build darwin python backend container images (reusable)'
+
+on:
+  workflow_call:
+    inputs:
+      backend:
+        description: 'Backend to build'
+        required: true
+        type: string
+      build-type:
+        description: 'Build type (e.g., mps)'
+        default: ''
+        type: string
+      use-pip:
+        description: 'Use pip to install dependencies'
+        default: false
+        type: boolean
+      lang:
+        description: 'Programming language (e.g. go)'
+        default: 'python'
+        type: string
+      go-version:
+        description: 'Go version to use'
+        default: '1.24.x'
+        type: string
+      tag-suffix:
+        description: 'Tag suffix for the built image'
+        required: true
+        type: string
+      runs-on:
+        description: 'Runner to use'
+        default: 'macOS-14'
+        type: string
+    secrets:
+      dockerUsername:
+        required: false
+      dockerPassword:
+        required: false
+      quayUsername:
+        required: true
+      quayPassword:
+        required: true
+
+jobs:
+  darwin-backend-build:
+    runs-on: ${{ inputs.runs-on }}
+    strategy:
+      matrix:
+        go-version: ['${{ inputs.go-version }}']
+    steps:
+      - name: Clone
+        uses: actions/checkout@v5
+        with:
+          submodules: true
+
+      - name: Setup Go ${{ matrix.go-version }}
+        uses: actions/setup-go@v5
+        with:
+          go-version: ${{ matrix.go-version }}
+          cache: false
+
+      # You can test your matrix by printing the current Go version
+      - name: Display Go version
+        run: go version
+
+      - name: Dependencies
+        run: |
+          brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
+
+      - name: Build ${{ inputs.backend }}-darwin
+        run: |
+          make protogen-go
+          BACKEND=${{ inputs.backend }} BUILD_TYPE=${{ inputs.build-type }} USE_PIP=${{ inputs.use-pip }} make build-darwin-${{ inputs.lang }}-backend
+
+      - name: Upload ${{ inputs.backend }}.tar
+        uses: actions/upload-artifact@v4
+        with:
+          name: ${{ inputs.backend }}-tar
+          path: backend-images/${{ inputs.backend }}.tar
+
+  darwin-backend-publish:
+    needs: darwin-backend-build
+    if: github.event_name != 'pull_request'
+    runs-on: ubuntu-latest
+    steps:
+      - name: Download ${{ inputs.backend }}.tar
+        uses: actions/download-artifact@v5
+        with:
+          name: ${{ inputs.backend }}-tar
+          path: .
+
+      - name: Install crane
+        run: |
+          curl -L https://github.com/google/go-containerregistry/releases/latest/download/go-containerregistry_Linux_x86_64.tar.gz | tar -xz
+          sudo mv crane /usr/local/bin/
+
+      - name: Log in to DockerHub
+        run: |
+          echo "${{ secrets.dockerPassword }}" | crane auth login docker.io -u "${{ secrets.dockerUsername }}" --password-stdin
+
+      - name: Log in to quay.io
+        run: |
+          echo "${{ secrets.quayPassword }}" | crane auth login quay.io -u "${{ secrets.quayUsername }}" --password-stdin
+
+      - name: Docker meta
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: |
+            localai/localai-backends
+          tags: |
+            type=ref,event=branch
+            type=semver,pattern={{raw}}
+            type=sha
+          flavor: |
+            latest=auto
+            suffix=${{ inputs.tag-suffix }},onlatest=true
+
+      - name: Docker meta
+        id: quaymeta
+        uses: docker/metadata-action@v5
+        with:
+          images: |
+            quay.io/go-skynet/local-ai-backends
+          tags: |
+            type=ref,event=branch
+            type=semver,pattern={{raw}}
+            type=sha
+          flavor: |
+            latest=auto
+            suffix=${{ inputs.tag-suffix }},onlatest=true
+
+      - name: Push Docker image (DockerHub)
+        run: |
+          for tag in $(echo "${{ steps.meta.outputs.tags }}" | tr ',' '\n'); do
+            crane push ${{ inputs.backend }}.tar $tag
+          done
+
+      - name: Push Docker image (Quay)
+        run: |
+          for tag in $(echo "${{ steps.quaymeta.outputs.tags }}" | tr ',' '\n'); do
+            crane push ${{ inputs.backend }}.tar $tag
+          done

.github/workflows/backend_pr.yml

@@ -0,0 +1,78 @@
+name: 'build backend container images (PR-filtered)'
+
+on:
+  pull_request:
+
+concurrency:
+  group: ci-backends-pr-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
+jobs:
+  generate-matrix:
+    runs-on: ubuntu-latest
+    outputs:
+      matrix: ${{ steps.set-matrix.outputs.matrix }}
+      matrix-darwin: ${{ steps.set-matrix.outputs.matrix-darwin }}
+      has-backends: ${{ steps.set-matrix.outputs.has-backends }}
+      has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v5
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@v2
+
+      - name: Install dependencies
+        run: |
+          bun add js-yaml
+          bun add @octokit/core
+
+      # filters the matrix in backend.yml
+      - name: Filter matrix for changed backends
+        id: set-matrix
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          GITHUB_EVENT_PATH: ${{ github.event_path }}
+        run: bun run scripts/changed-backends.js
+
+  backend-jobs:
+    needs: generate-matrix
+    uses: ./.github/workflows/backend_build.yml
+    if: needs.generate-matrix.outputs.has-backends == 'true'
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
+      backend: ${{ matrix.backend }}
+      dockerfile: ${{ matrix.dockerfile }}
+      skip-drivers: ${{ matrix.skip-drivers }}
+      context: ${{ matrix.context }}
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: true
+      matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
+  backend-jobs-darwin:
+    needs: generate-matrix
+    uses: ./.github/workflows/backend_build_darwin.yml
+    if: needs.generate-matrix.outputs.has-backends-darwin == 'true'
+    with:
+      backend: ${{ matrix.backend }}
+      build-type: ${{ matrix.build-type }}
+      go-version: "1.24.x"
+      tag-suffix: ${{ matrix.tag-suffix }}
+      lang: ${{ matrix.lang || 'python' }}
+      use-pip: ${{ matrix.backend == 'diffusers' }}
+      runs-on: "macOS-14"
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: true
+      matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix-darwin) }}

.github/workflows/build-test.yaml

@@ -0,0 +1,67 @@
+name: Build test
+
+on:
+  push:
+    branches:
+      - master
+  pull_request:
+
+jobs:
+  build-test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.23
+      - name: Run GoReleaser
+        run: |
+          make dev-dist
+  launcher-build-darwin:
+    runs-on: macos-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.23
+      - name: Build launcher for macOS ARM64
+        run: |
+          make build-launcher-darwin
+          ls -liah dist
+      - name: Upload macOS launcher artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: launcher-macos
+          path: dist/
+          retention-days: 30
+      
+  launcher-build-linux:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.23
+      - name: Build launcher for Linux
+        run: |
+          sudo apt-get update
+          sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
+          make build-launcher-linux
+      - name: Upload Linux launcher artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: launcher-linux
+          path: local-ai-launcher-linux.tar.xz
+          retention-days: 30

.github/workflows/bump_deps.yaml

@@ -10,30 +10,32 @@ jobs:
       matrix:
         include:
           - repository: "ggml-org/llama.cpp"
-            variable: "CPPLLAMA_VERSION"
+            variable: "LLAMA_VERSION"
             branch: "master"
+            file: "backend/cpp/llama-cpp/Makefile"
           - repository: "ggml-org/whisper.cpp"
             variable: "WHISPER_CPP_VERSION"
             branch: "master"
+            file: "backend/go/whisper/Makefile"
           - repository: "PABannier/bark.cpp"
             variable: "BARKCPP_VERSION"
             branch: "main"
+            file: "Makefile"
           - repository: "leejet/stable-diffusion.cpp"
             variable: "STABLEDIFFUSION_GGML_VERSION"
             branch: "master"
-          - repository: "mudler/go-stable-diffusion"
+            file: "backend/go/stablediffusion-ggml/Makefile"
-            variable: "STABLEDIFFUSION_VERSION"
-            branch: "master"
           - repository: "mudler/go-piper"
             variable: "PIPER_VERSION"
             branch: "master"
+            file: "backend/go/piper/Makefile"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Bump dependencies 🔧
         id: bump
         run: |
-          bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
+          bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }} ${{ matrix.file }}
           {
             echo 'message<<EOF'
             cat "${{ matrix.variable }}_message.txt"

.github/workflows/bump_docs.yaml

@@ -12,7 +12,7 @@ jobs:
           - repository: "mudler/LocalAI"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Bump dependencies 🔧
         run: |
           bash .github/bump_docs.sh ${{ matrix.repository }}

.github/workflows/checksum_checker.yaml

@@ -5,7 +5,7 @@ on:
   workflow_dispatch:
 jobs:
   checksum_check:
-    runs-on: arc-runner-set
+    runs-on: ubuntu-latest
     steps:
       - name: Force Install GIT latest
         run: |
@@ -15,12 +15,11 @@ jobs:
           && sudo add-apt-repository -y ppa:git-core/ppa \
           && sudo apt-get update \
           && sudo apt-get install -y git
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Install dependencies
         run: |
           sudo apt-get update
           sudo apt-get install -y pip wget
-          sudo pip install --upgrade pip
           pip install huggingface_hub
       - name: 'Setup yq'
         uses: dcarbone/install-yq-action@v1.3.1

.github/workflows/dependabot_auto.yml

@@ -20,7 +20,7 @@ jobs:
           skip-commit-verification: true
 
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Approve a PR if not already approved
         run: |

.github/workflows/deploy-explorer.yaml

@@ -15,7 +15,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - uses: actions/setup-go@v5
@@ -31,7 +31,7 @@ jobs:
           make protogen-go
       - name: Build api
         run: |
-          CGO_ENABLED=0 make build-api
+          CGO_ENABLED=0 make build
       - name: rm
         uses: appleboy/ssh-action@v1.2.2
         with:

.github/workflows/generate_grpc_cache.yaml

@@ -17,7 +17,7 @@ jobs:
       matrix:
         include:
           - grpc-base-image: ubuntu:22.04
-            runs-on: 'arc-runner-set'
+            runs-on: 'ubuntu-latest'
             platforms: 'linux/amd64,linux/arm64'
     runs-on: ${{matrix.runs-on}}
     steps:
@@ -73,7 +73,7 @@ jobs:
         uses: docker/setup-buildx-action@master
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Cache GRPC
         uses: docker/build-push-action@v6

.github/workflows/generate_intel_image.yaml

@@ -15,7 +15,7 @@ jobs:
     strategy:
       matrix:
         include:
-          - base-image: intel/oneapi-basekit:2025.1.0-0-devel-ubuntu22.04
+          - base-image: intel/oneapi-basekit:2025.2.0-0-devel-ubuntu22.04
             runs-on: 'ubuntu-latest'
             platforms: 'linux/amd64'
     runs-on: ${{matrix.runs-on}}
@@ -43,7 +43,7 @@ jobs:
         uses: docker/setup-buildx-action@master
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Cache Intel images
         uses: docker/build-push-action@v6

.github/workflows/image-pr.yml

@@ -9,13 +9,11 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  extras-image-build:
+  image-build:
     uses: ./.github/workflows/image_build.yml
     with:
       tag-latest: ${{ matrix.tag-latest }}
       tag-suffix: ${{ matrix.tag-suffix }}
-      ffmpeg: ${{ matrix.ffmpeg }}
-      image-type: ${{ matrix.image-type }}
       build-type: ${{ matrix.build-type }}
       cuda-major-version: ${{ matrix.cuda-major-version }}
       cuda-minor-version: ${{ matrix.cuda-minor-version }}
@@ -36,115 +34,35 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          # This is basically covered by the AIO test
-          # - build-type: ''
-          #   platforms: 'linux/amd64'
-          #   tag-latest: 'false'
-          #   tag-suffix: '-ffmpeg'
-          #   ffmpeg: 'true'
-          #   image-type: 'extras'
-          #   runs-on: 'arc-runner-set'
-          #   base-image: "ubuntu:22.04"
-          #   makeflags: "--jobs=3 --output-sync=target"
           - build-type: 'cublas'
             cuda-major-version: "12"
-            cuda-minor-version: "0"
+            cuda-minor-version: "8"
             platforms: 'linux/amd64'
             tag-latest: 'false'
-            tag-suffix: '-cublas-cuda12-ffmpeg'
+            tag-suffix: '-gpu-nvidia-cuda-12'
-            ffmpeg: 'true'
+            runs-on: 'ubuntu-latest'
-            image-type: 'extras'
-            runs-on: 'arc-runner-set'
             base-image: "ubuntu:22.04"
             makeflags: "--jobs=3 --output-sync=target"
           - build-type: 'hipblas'
             platforms: 'linux/amd64'
             tag-latest: 'false'
             tag-suffix: '-hipblas'
-            ffmpeg: 'false'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
-            image-type: 'extras'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
             grpc-base-image: "ubuntu:22.04"
-            runs-on: 'arc-runner-set'
+            runs-on: 'ubuntu-latest'
             makeflags: "--jobs=3 --output-sync=target"
-          - build-type: 'sycl_f16'
+          - build-type: 'sycl'
             platforms: 'linux/amd64'
             tag-latest: 'false'
             base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
             grpc-base-image: "ubuntu:22.04"
-            tag-suffix: 'sycl-f16-ffmpeg'
+            tag-suffix: 'sycl'
-            ffmpeg: 'true'
+            runs-on: 'ubuntu-latest'
-            image-type: 'extras'
-            runs-on: 'arc-runner-set'
             makeflags: "--jobs=3 --output-sync=target"
           - build-type: 'vulkan'
             platforms: 'linux/amd64'
             tag-latest: 'false'
-            tag-suffix: '-vulkan-ffmpeg-core'
+            tag-suffix: '-vulkan-core'
-            ffmpeg: 'true'
-            image-type: 'core'
             runs-on: 'ubuntu-latest'
             base-image: "ubuntu:22.04"
             makeflags: "--jobs=4 --output-sync=target"
-  # core-image-build:
-  #   uses: ./.github/workflows/image_build.yml
-  #   with:
-  #     tag-latest: ${{ matrix.tag-latest }}
-  #     tag-suffix: ${{ matrix.tag-suffix }}
-  #     ffmpeg: ${{ matrix.ffmpeg }}
-  #     image-type: ${{ matrix.image-type }}
-  #     build-type: ${{ matrix.build-type }}
-  #     cuda-major-version: ${{ matrix.cuda-major-version }}
-  #     cuda-minor-version: ${{ matrix.cuda-minor-version }}
-  #     platforms: ${{ matrix.platforms }}
-  #     runs-on: ${{ matrix.runs-on }}
-  #     base-image: ${{ matrix.base-image }}
-  #     grpc-base-image: ${{ matrix.grpc-base-image }}
-  #     makeflags: ${{ matrix.makeflags }}
-  #   secrets:
-  #     dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
-  #     dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
-  #     quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-  #     quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
-  #   strategy:
-  #     matrix:
-  #       include:
-          # - build-type: ''
-          #   platforms: 'linux/amd64'
-          #   tag-latest: 'false'
-          #   tag-suffix: '-ffmpeg-core'
-          #   ffmpeg: 'true'
-          #   image-type: 'core'
-          #   runs-on: 'ubuntu-latest'
-          #   base-image: "ubuntu:22.04"
-          #   makeflags: "--jobs=4 --output-sync=target"
-          # - build-type: 'sycl_f16'
-          #   platforms: 'linux/amd64'
-          #   tag-latest: 'false'
-          #   base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
-          #   grpc-base-image: "ubuntu:22.04"
-          #   tag-suffix: 'sycl-f16-ffmpeg-core'
-          #   ffmpeg: 'true'
-          #   image-type: 'core'
-          #   runs-on: 'arc-runner-set'
-          #   makeflags: "--jobs=3 --output-sync=target"
-          # - build-type: 'cublas'
-          #   cuda-major-version: "12"
-          #   cuda-minor-version: "0"
-          #   platforms: 'linux/amd64'
-          #   tag-latest: 'false'
-          #   tag-suffix: '-cublas-cuda12-ffmpeg-core'
-          #   ffmpeg: 'true'
-          #   image-type: 'core'
-          #   runs-on: 'ubuntu-latest'
-          #   base-image: "ubuntu:22.04"
-          #   makeflags: "--jobs=4 --output-sync=target"
-          # - build-type: 'vulkan'
-          #   platforms: 'linux/amd64'
-          #   tag-latest: 'false'
-          #   tag-suffix: '-vulkan-ffmpeg-core'
-          #   ffmpeg: 'true'
-          #   image-type: 'core'
-          #   runs-on: 'ubuntu-latest'
-          #   base-image: "ubuntu:22.04"
-          #   makeflags: "--jobs=4 --output-sync=target"

.github/workflows/image.yml

@@ -18,8 +18,6 @@ jobs:
     with:
       tag-latest: ${{ matrix.tag-latest }}
       tag-suffix: ${{ matrix.tag-suffix }}
-      ffmpeg: ${{ matrix.ffmpeg }}
-      image-type: ${{ matrix.image-type }}
       build-type: ${{ matrix.build-type }}
       cuda-major-version: ${{ matrix.cuda-major-version }}
       cuda-minor-version: ${{ matrix.cuda-minor-version }}
@@ -29,157 +27,29 @@ jobs:
       grpc-base-image: ${{ matrix.grpc-base-image }}
       aio: ${{ matrix.aio }}
       makeflags: ${{ matrix.makeflags }}
-      latest-image: ${{ matrix.latest-image }}
-      latest-image-aio: ${{ matrix.latest-image-aio }}
     secrets:
       dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
       dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
       quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
       quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
     strategy:
-      # Pushing with all jobs in parallel
-      # eats the bandwidth of all the nodes
-      max-parallel: 2
       matrix:
         include:
           - build-type: 'hipblas'
             platforms: 'linux/amd64'
             tag-latest: 'auto'
-            tag-suffix: '-hipblas-extras'
+            tag-suffix: '-gpu-hipblas'
-            ffmpeg: 'true'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
-            image-type: 'extras'
+            grpc-base-image: "ubuntu:22.04"
+            runs-on: 'ubuntu-latest'
+            makeflags: "--jobs=3 --output-sync=target"
             aio: "-aio-gpu-hipblas"
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
-            grpc-base-image: "ubuntu:22.04"
-            latest-image: 'latest-gpu-hipblas-extras'
-            latest-image-aio: 'latest-aio-gpu-hipblas'
-            runs-on: 'arc-runner-set'
-            makeflags: "--jobs=3 --output-sync=target"
-          - build-type: 'hipblas'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            tag-suffix: '-hipblas'
-            ffmpeg: 'true'
-            image-type: 'core'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
-            grpc-base-image: "ubuntu:22.04"
-            runs-on: 'arc-runner-set'
-            makeflags: "--jobs=3 --output-sync=target"
-            latest-image: 'latest-gpu-hipblas'
-  self-hosted-jobs:
-    uses: ./.github/workflows/image_build.yml
-    with:
-      tag-latest: ${{ matrix.tag-latest }}
-      tag-suffix: ${{ matrix.tag-suffix }}
-      ffmpeg: ${{ matrix.ffmpeg }}
-      image-type: ${{ matrix.image-type }}
-      build-type: ${{ matrix.build-type }}
-      cuda-major-version: ${{ matrix.cuda-major-version }}
-      cuda-minor-version: ${{ matrix.cuda-minor-version }}
-      platforms: ${{ matrix.platforms }}
-      runs-on: ${{ matrix.runs-on }}
-      base-image: ${{ matrix.base-image }}
-      grpc-base-image: ${{ matrix.grpc-base-image }}
-      aio: ${{ matrix.aio }}
-      makeflags: ${{ matrix.makeflags }}
-      latest-image: ${{ matrix.latest-image }}
-      latest-image-aio: ${{ matrix.latest-image-aio }}
-    secrets:
-      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
-      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
-      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
-    strategy:
-      # Pushing with all jobs in parallel
-      # eats the bandwidth of all the nodes
-      max-parallel: ${{ github.event_name != 'pull_request' && 5 || 8 }}
-      matrix:
-        include:
-          - build-type: 'cublas'
-            cuda-major-version: "11"
-            cuda-minor-version: "7"
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            tag-suffix: '-cublas-cuda11-extras'
-            ffmpeg: 'true'
-            image-type: 'extras'
-            runs-on: 'arc-runner-set'
-            base-image: "ubuntu:22.04"
-            aio: "-aio-gpu-nvidia-cuda-11"
-            latest-image: 'latest-gpu-nvidia-cuda-11-extras'
-            latest-image-aio: 'latest-aio-gpu-nvidia-cuda-11'
-            makeflags: "--jobs=3 --output-sync=target"
-          - build-type: 'cublas'
-            cuda-major-version: "12"
-            cuda-minor-version: "0"
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            tag-suffix: '-cublas-cuda12-extras'
-            ffmpeg: 'true'
-            image-type: 'extras'
-            runs-on: 'arc-runner-set'
-            base-image: "ubuntu:22.04"
-            aio: "-aio-gpu-nvidia-cuda-12"
-            latest-image: 'latest-gpu-nvidia-cuda-12-extras'
-            latest-image-aio: 'latest-aio-gpu-nvidia-cuda-12'
-            makeflags: "--jobs=3 --output-sync=target"
-          - build-type: 'sycl_f16'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
-            grpc-base-image: "ubuntu:22.04"
-            tag-suffix: '-sycl-f16-extras'
-            ffmpeg: 'true'
-            image-type: 'extras'
-            runs-on: 'arc-runner-set'
-            aio: "-aio-gpu-intel-f16"
-            latest-image: 'latest-gpu-intel-f16-extras'
-            latest-image-aio: 'latest-aio-gpu-intel-f16'
-            makeflags: "--jobs=3 --output-sync=target"
-          - build-type: 'sycl_f32'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
-            grpc-base-image: "ubuntu:22.04"
-            tag-suffix: '-sycl-f32-extras'
-            ffmpeg: 'true'
-            image-type: 'extras'
-            runs-on: 'arc-runner-set'
-            aio: "-aio-gpu-intel-f32"
-            latest-image: 'latest-gpu-intel-f32-extras'
-            latest-image-aio: 'latest-aio-gpu-intel-f32'
-            makeflags: "--jobs=3 --output-sync=target"
-          # Core images
-          - build-type: 'sycl_f16'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
-            grpc-base-image: "ubuntu:22.04"
-            tag-suffix: '-sycl-f16'
-            ffmpeg: 'true'
-            image-type: 'core'
-            runs-on: 'arc-runner-set'
-            makeflags: "--jobs=3 --output-sync=target"
-            latest-image: 'latest-gpu-intel-f16'
-          - build-type: 'sycl_f32'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
-            grpc-base-image: "ubuntu:22.04"
-            tag-suffix: '-sycl-f32'
-            ffmpeg: 'true'
-            image-type: 'core'
-            runs-on: 'arc-runner-set'
-            makeflags: "--jobs=3 --output-sync=target"
-            latest-image: 'latest-gpu-intel-f32'
 
   core-image-build:
     uses: ./.github/workflows/image_build.yml
     with:
       tag-latest: ${{ matrix.tag-latest }}
       tag-suffix: ${{ matrix.tag-suffix }}
-      ffmpeg: ${{ matrix.ffmpeg }}
-      image-type: ${{ matrix.image-type }}
       build-type: ${{ matrix.build-type }}
       cuda-major-version: ${{ matrix.cuda-major-version }}
       cuda-minor-version: ${{ matrix.cuda-minor-version }}
@@ -189,8 +59,6 @@ jobs:
       base-image: ${{ matrix.base-image }}
       grpc-base-image: ${{ matrix.grpc-base-image }}
       makeflags: ${{ matrix.makeflags }}
-      latest-image: ${{ matrix.latest-image }}
-      latest-image-aio: ${{ matrix.latest-image-aio }}
       skip-drivers: ${{ matrix.skip-drivers }}
     secrets:
       dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
@@ -198,66 +66,64 @@ jobs:
       quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
       quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
     strategy:
-      max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
+      #max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
       matrix:
         include:
           - build-type: ''
             platforms: 'linux/amd64,linux/arm64'
             tag-latest: 'auto'
             tag-suffix: ''
-            ffmpeg: 'true'
-            image-type: 'core'
             base-image: "ubuntu:22.04"
-            runs-on: 'arc-runner-set'
+            runs-on: 'ubuntu-latest'
             aio: "-aio-cpu"
-            latest-image: 'latest-cpu'
-            latest-image-aio: 'latest-aio-cpu'
             makeflags: "--jobs=4 --output-sync=target"
             skip-drivers: 'false'
           - build-type: 'cublas'
             cuda-major-version: "11"
             cuda-minor-version: "7"
             platforms: 'linux/amd64'
-            tag-latest: 'false'
+            tag-latest: 'auto'
-            tag-suffix: '-cublas-cuda11'
+            tag-suffix: '-gpu-nvidia-cuda-11'
-            ffmpeg: 'true'
+            runs-on: 'ubuntu-latest'
-            image-type: 'core'
-            runs-on: 'arc-runner-set'
             base-image: "ubuntu:22.04"
             makeflags: "--jobs=4 --output-sync=target"
             skip-drivers: 'false'
-            latest-image: 'latest-gpu-nvidia-cuda-12'
+            aio: "-aio-gpu-nvidia-cuda-11"
           - build-type: 'cublas'
             cuda-major-version: "12"
-            cuda-minor-version: "0"
+            cuda-minor-version: "8"
             platforms: 'linux/amd64'
-            tag-latest: 'false'
+            tag-latest: 'auto'
-            tag-suffix: '-cublas-cuda12'
+            tag-suffix: '-gpu-nvidia-cuda-12'
-            ffmpeg: 'true'
+            runs-on: 'ubuntu-latest'
-            image-type: 'core'
-            runs-on: 'arc-runner-set'
             base-image: "ubuntu:22.04"
             skip-drivers: 'false'
             makeflags: "--jobs=4 --output-sync=target"
-            latest-image: 'latest-gpu-nvidia-cuda-12'
+            aio: "-aio-gpu-nvidia-cuda-12"
           - build-type: 'vulkan'
             platforms: 'linux/amd64'
-            tag-latest: 'false'
+            tag-latest: 'auto'
-            tag-suffix: '-vulkan'
+            tag-suffix: '-gpu-vulkan'
-            ffmpeg: 'true'
+            runs-on: 'ubuntu-latest'
-            image-type: 'core'
-            runs-on: 'arc-runner-set'
             base-image: "ubuntu:22.04"
             skip-drivers: 'false'
             makeflags: "--jobs=4 --output-sync=target"
-            latest-image: 'latest-gpu-vulkan'
+            aio: "-aio-gpu-vulkan"
+          - build-type: 'intel'
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
+            grpc-base-image: "ubuntu:22.04"
+            tag-suffix: '-gpu-intel'
+            runs-on: 'ubuntu-latest'
+            makeflags: "--jobs=3 --output-sync=target"
+            aio: "-aio-gpu-intel"
+
   gh-runner:
     uses: ./.github/workflows/image_build.yml
     with:
       tag-latest: ${{ matrix.tag-latest }}
       tag-suffix: ${{ matrix.tag-suffix }}
-      ffmpeg: ${{ matrix.ffmpeg }}
-      image-type: ${{ matrix.image-type }}
       build-type: ${{ matrix.build-type }}
       cuda-major-version: ${{ matrix.cuda-major-version }}
       cuda-minor-version: ${{ matrix.cuda-minor-version }}
@@ -267,8 +133,6 @@ jobs:
       base-image: ${{ matrix.base-image }}
       grpc-base-image: ${{ matrix.grpc-base-image }}
       makeflags: ${{ matrix.makeflags }}
-      latest-image: ${{ matrix.latest-image }}
-      latest-image-aio: ${{ matrix.latest-image-aio }}
       skip-drivers: ${{ matrix.skip-drivers }}
     secrets:
       dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
@@ -280,13 +144,10 @@ jobs:
         include:
           - build-type: 'cublas'
             cuda-major-version: "12"
-            cuda-minor-version: "0"
+            cuda-minor-version: "8"
             platforms: 'linux/arm64'
-            tag-latest: 'false'
+            tag-latest: 'auto'
             tag-suffix: '-nvidia-l4t-arm64'
-            latest-image: 'latest-nvidia-l4t-arm64'
-            ffmpeg: 'true'
-            image-type: 'core'
             base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
             runs-on: 'ubuntu-24.04-arm'
             makeflags: "--jobs=4 --output-sync=target"

.github/workflows/image_build.yml

@@ -33,30 +33,14 @@ on:
         description: 'Tag latest'
         default: ''
         type: string
-      latest-image:
-          description: 'Tag latest'
-          default: ''
-          type: string
-      latest-image-aio:
-          description: 'Tag latest'
-          default: ''
-          type: string
       tag-suffix:
         description: 'Tag suffix'
         default: ''
         type: string
-      ffmpeg:
-        description: 'FFMPEG'
-        default: ''
-        type: string
       skip-drivers:
         description: 'Skip drivers by default'
         default: 'false'
         type: string
-      image-type:
-        description: 'Image type'
-        default: ''
-        type: string
       runs-on:
         description: 'Runs on'
         required: true
@@ -85,6 +69,22 @@ jobs:
   reusable_image-build:
     runs-on: ${{ inputs.runs-on }}
     steps:
+
+      - name: Free Disk Space (Ubuntu)
+        if: inputs.runs-on == 'ubuntu-latest'
+        uses: jlumbroso/free-disk-space@main
+        with:
+          # this might remove tools that are actually needed,
+          # if set to "true" but frees about 6 GB
+          tool-cache: true
+          # all of these default to true, but feel free to set to
+          # "false" if necessary for your workflow
+          android: true
+          dotnet: true
+          haskell: true
+          large-packages: true
+          docker-images: true
+          swap-storage: true
       - name: Force Install GIT latest
         run: |
           sudo apt-get update \
@@ -94,7 +94,7 @@ jobs:
           && sudo apt-get update \
           && sudo apt-get install -y git
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Release space from worker
         if: inputs.runs-on == 'ubuntu-latest'
@@ -106,8 +106,8 @@ jobs:
           df -h
           echo
           sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
-          sudo apt-get remove --auto-remove android-sdk-platform-tools || true
+          sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
-          sudo apt-get purge --auto-remove android-sdk-platform-tools || true
+          sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
           sudo rm -rf /usr/local/lib/android
           sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
           sudo rm -rf /usr/share/dotnet
@@ -152,18 +152,18 @@ jobs:
             type=sha
           flavor: |
             latest=${{ inputs.tag-latest }}
-            suffix=${{ inputs.tag-suffix }}
+            suffix=${{ inputs.tag-suffix }},onlatest=true
       - name: Docker meta for PR
         id: meta_pull_request
         if: github.event_name == 'pull_request'
         uses: docker/metadata-action@v5
         with:
           images: |
-            ttl.sh/localai-ci-pr-${{ github.event.number }}
+            quay.io/go-skynet/ci-tests
           tags: |
-            type=ref,event=branch
+            type=ref,event=branch,suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
-            type=semver,pattern={{raw}}
+            type=semver,pattern={{raw}},suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
-            type=sha
+            type=sha,suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
           flavor: |
             latest=${{ inputs.tag-latest }}
             suffix=${{ inputs.tag-suffix }}
@@ -179,7 +179,7 @@ jobs:
             type=semver,pattern={{raw}}
           flavor: |
             latest=${{ inputs.tag-latest }}
-            suffix=${{ inputs.aio }}
+            suffix=${{ inputs.aio }},onlatest=true
 
       - name: Docker meta AIO (dockerhub)
         if: inputs.aio != ''
@@ -192,7 +192,8 @@ jobs:
             type=ref,event=branch
             type=semver,pattern={{raw}}
           flavor: |
-            suffix=${{ inputs.aio }}
+            latest=${{ inputs.tag-latest }}
+            suffix=${{ inputs.aio }},onlatest=true
 
       - name: Set up QEMU
         uses: docker/setup-qemu-action@master
@@ -231,8 +232,6 @@ jobs:
             BUILD_TYPE=${{ inputs.build-type }}
             CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
             CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
-            FFMPEG=${{ inputs.ffmpeg }}
-            IMAGE_TYPE=${{ inputs.image-type }}
             BASE_IMAGE=${{ inputs.base-image }}
             GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
             GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
@@ -260,8 +259,6 @@ jobs:
             BUILD_TYPE=${{ inputs.build-type }}
             CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
             CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
-            FFMPEG=${{ inputs.ffmpeg }}
-            IMAGE_TYPE=${{ inputs.image-type }}
             BASE_IMAGE=${{ inputs.base-image }}
             GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
             GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
@@ -272,13 +269,9 @@ jobs:
           file: ./Dockerfile
           cache-from: type=gha
           platforms: ${{ inputs.platforms }}
-          push: true
+          #push: true
           tags: ${{ steps.meta_pull_request.outputs.tags }}
           labels: ${{ steps.meta_pull_request.outputs.labels }}
-      - name: Testing image
-        if: github.event_name == 'pull_request'
-        run: |
-          echo "Image is available at ttl.sh/localai-ci-pr-${{ github.event.number }}:${{ steps.meta_pull_request.outputs.version }}" >> $GITHUB_STEP_SUMMARY
 ## End testing image
       - name: Build and push AIO image
         if: inputs.aio != ''
@@ -310,32 +303,6 @@ jobs:
           tags: ${{ steps.meta_aio_dockerhub.outputs.tags }}
           labels: ${{ steps.meta_aio_dockerhub.outputs.labels }}
 
-      - name: Cleanup
-        run: |
-          docker builder prune -f
-          docker system prune --force --volumes --all
-
-      - name: Latest tag
-        # run this on branches, when it is a tag and there is a latest-image defined
-        if: github.event_name != 'pull_request' && inputs.latest-image != ''  && github.ref_type == 'tag'
-        run: |
-          docker pull localai/localai:${{ steps.meta.outputs.version }}
-          docker tag localai/localai:${{ steps.meta.outputs.version }} localai/localai:${{ inputs.latest-image }}
-          docker push localai/localai:${{ inputs.latest-image }}
-          docker pull quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
-          docker tag quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
-          docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
-      - name: Latest AIO tag
-        # run this on branches, when it is a tag and there is a latest-image defined
-        if: github.event_name != 'pull_request' && inputs.latest-image-aio != ''  && github.ref_type == 'tag'
-        run: |
-          docker pull localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }}
-          docker tag localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }} localai/localai:${{ inputs.latest-image-aio }}
-          docker push localai/localai:${{ inputs.latest-image-aio }}
-          docker pull quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }}
-          docker tag quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
-          docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
-
       - name: job summary
         run: |
           echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

.github/workflows/labeler.yml

@@ -9,4 +9,4 @@ jobs:
       pull-requests: write
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/labeler@v5
+    - uses: actions/labeler@v6

.github/workflows/localaibot_automerge.yml

@@ -13,7 +13,7 @@ jobs:
     if: ${{ github.actor == 'localai-bot' }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Approve a PR if not already approved
         run: |

.github/workflows/notify-models.yaml

@@ -11,14 +11,14 @@ jobs:
         MODEL_NAME: gemma-3-12b-it
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         fetch-depth: 0 # needed to checkout all branches for this Action to work
     - uses: mudler/localai-github-action@v1
       with:
         model: 'gemma-3-12b-it' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
         # Check the PR diff using the current branch and the base branch of the PR
-    - uses: GrantBirki/git-diff-action@v2.8.0
+    - uses: GrantBirki/git-diff-action@v2.8.1
       id: git-diff-action
       with:
             json_diff_file_output: diff.json
@@ -90,16 +90,16 @@ jobs:
         MODEL_NAME: gemma-3-12b-it
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         fetch-depth: 0 # needed to checkout all branches for this Action to work
     - name: Start LocalAI
       run: |
         echo "Starting LocalAI..."
-        docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master-ffmpeg-core run --debug $MODEL_NAME
+        docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master run --debug $MODEL_NAME
         until [ "`docker inspect -f {{.State.Health.Status}} local-ai`" == "healthy" ]; do echo "Waiting for container to be ready";  docker logs --tail 10 local-ai; sleep 2; done
       # Check the PR diff using the current branch and the base branch of the PR
-    - uses: GrantBirki/git-diff-action@v2.8.0
+    - uses: GrantBirki/git-diff-action@v2.8.1
       id: git-diff-action
       with:
             json_diff_file_output: diff.json

.github/workflows/release.yaml

@@ -1,324 +1,64 @@
-name: Build and Release
+name: goreleaser
 
 on:
   push:
-    branches:
-      - master
     tags:
       - 'v*'
-  pull_request:
-
-env:
-  GRPC_VERSION: v1.65.0
-
-permissions:
-  contents: write
-
-concurrency:
-  group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
 
 jobs:
-
+  goreleaser:
-  build-linux-arm:
     runs-on: ubuntu-latest
     steps:
-      - name: Clone
+      - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
-          submodules: true
+          fetch-depth: 0
-      - uses: actions/setup-go@v5
+      - name: Set up Go
+        uses: actions/setup-go@v5
         with:
-          go-version: '1.21.x'
+          go-version: 1.23
-          cache: false
+      - name: Run GoReleaser
-      - name: Dependencies
+        uses: goreleaser/goreleaser-action@v6
-        run: |
+        with:
-          sudo apt-get update
+          version: v2.11.0
-          sudo apt-get install build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk
+          args: release --clean
-          sudo apt-get install -qy binutils-aarch64-linux-gnu gcc-aarch64-linux-gnu g++-aarch64-linux-gnu libgmock-dev
-          make install-go-tools
-      - name: Install CUDA Dependencies
-        run: |
-          curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/cross-linux-aarch64/cuda-keyring_1.1-1_all.deb
-          sudo dpkg -i cuda-keyring_1.1-1_all.deb
-          sudo apt-get update
-          sudo apt-get install -y cuda-cross-aarch64 cuda-nvcc-cross-aarch64-${CUDA_VERSION} libcublas-cross-aarch64-${CUDA_VERSION}
         env:
-          CUDA_VERSION: 12-4
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      - name: Cache grpc
+  launcher-build-darwin:
-        id: cache-grpc
+    runs-on: macos-latest
-        uses: actions/cache@v4
-        with:
-          path: grpc
-          key: ${{ runner.os }}-arm-grpc-${{ env.GRPC_VERSION }}
-      - name: Build grpc
-        if: steps.cache-grpc.outputs.cache-hit != 'true'
-        run: |
-
-          git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-          cd grpc && sed -i "216i\  TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
-          cd cmake/build && cmake -DgRPC_INSTALL=ON \
-            -DgRPC_BUILD_TESTS=OFF \
-            ../.. && sudo make --jobs 5 --output-sync=target
-      - name: Install gRPC
-        run: |
-          GNU_HOST=aarch64-linux-gnu
-          C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
-          CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
-
-          CROSS_TOOLCHAIN=/usr/$GNU_HOST
-          CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
-          CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
-
-          # https://cmake.org/cmake/help/v3.13/manual/cmake-toolchains.7.html#cross-compiling-for-linux
-          echo "set(CMAKE_SYSTEM_NAME Linux)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_SYSTEM_PROCESSOR arm)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_STAGING_PREFIX $CROSS_STAGING_PREFIX)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_SYSROOT ${CROSS_TOOLCHAIN}/sysroot)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_C_COMPILER /usr/bin/$C_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_CXX_COMPILER /usr/bin/$CXX_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
-            echo "set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN
-          GRPC_DIR=$PWD/grpc
-          cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install && \
-          GRPC_CROSS_BUILD_DIR=$GRPC_DIR/cmake/cross_build && \
-          mkdir -p $GRPC_CROSS_BUILD_DIR && \
-          cd $GRPC_CROSS_BUILD_DIR && \
-          cmake -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN \
-            -DCMAKE_BUILD_TYPE=Release \
-            -DCMAKE_INSTALL_PREFIX=$CROSS_TOOLCHAIN/grpc_install \
-            ../.. && \
-          sudo make -j`nproc` install
-      - name: Build
-        id: build
-        run: |
-          GNU_HOST=aarch64-linux-gnu
-          C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
-          CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
-
-          CROSS_TOOLCHAIN=/usr/$GNU_HOST
-          CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
-          CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
-          go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
-          go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
-          export PATH=$PATH:$GOPATH/bin
-          export PATH=/usr/local/cuda/bin:$PATH
-          sudo rm -rf /usr/aarch64-linux-gnu/lib/libstdc++.so.6
-          sudo cp -rf /usr/aarch64-linux-gnu/lib/libstdc++.so* /usr/aarch64-linux-gnu/lib/libstdc++.so.6
-          sudo cp /usr/aarch64-linux-gnu/lib/ld-linux-aarch64.so.1 ld.so
-          BACKEND_LIBS="./grpc/cmake/cross_build/third_party/re2/libre2.a ./grpc/cmake/cross_build/libgrpc.a ./grpc/cmake/cross_build/libgrpc++.a ./grpc/cmake/cross_build/third_party/protobuf/libprotobuf.a /usr/aarch64-linux-gnu/lib/libc.so.6 /usr/aarch64-linux-gnu/lib/libstdc++.so.6 /usr/aarch64-linux-gnu/lib/libgomp.so.1 /usr/aarch64-linux-gnu/lib/libm.so.6 /usr/aarch64-linux-gnu/lib/libgcc_s.so.1 /usr/aarch64-linux-gnu/lib/libdl.so.2 /usr/aarch64-linux-gnu/lib/libpthread.so.0 ./ld.so" \
-          GOOS=linux \
-          GOARCH=arm64 \
-          CMAKE_ARGS="-DProtobuf_INCLUDE_DIRS=$CROSS_STAGING_PREFIX/include -DProtobuf_DIR=$CROSS_STAGING_PREFIX/lib/cmake/protobuf -DgRPC_DIR=$CROSS_STAGING_PREFIX/lib/cmake/grpc -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN -DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc -DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++" make dist-cross-linux-arm64
-      - uses: actions/upload-artifact@v4
-        with:
-          name: LocalAI-linux-arm64
-          path: release/
-      - name: Release
-        uses: softprops/action-gh-release@v2
-        if: startsWith(github.ref, 'refs/tags/')
-        with:
-          files: |
-            release/*
-      - name: Setup tmate session if tests fail
-        if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.22
-        with:
-          detached: true
-          connect-timeout-seconds: 180
-          limit-access-to-actor: true
-  build-linux:
-    runs-on: arc-runner-set
     steps:
-      - name: Force Install GIT latest
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.23
+      - name: Build launcher for macOS ARM64
         run: |
-          sudo apt-get update \
+          make build-launcher-darwin
-          && sudo apt-get install -y software-properties-common \
+      - name: Upload DMG to Release
-          && sudo apt-get update \
+        uses: softprops/action-gh-release@v2
-          && sudo add-apt-repository -y ppa:git-core/ppa \
-          && sudo apt-get update \
-          && sudo apt-get install -y git
-      - name: Clone
-        uses: actions/checkout@v4
         with:
-          submodules: true
+          files: ./dist/LocalAI.dmg
-      - uses: actions/setup-go@v5
+  launcher-build-linux:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
         with:
-          go-version: '1.21.x'
+          fetch-depth: 0
-          cache: false
+      - name: Set up Go
-      - name: Dependencies
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.23
+      - name: Build launcher for Linux
         run: |
           sudo apt-get update
-          sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
+          sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
-          make install-go-tools
+          make build-launcher-linux
-      - name: Intel Dependencies
+      - name: Upload Linux launcher artifacts
-        run: |
-          wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
-          echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
-          sudo apt update
-          sudo apt install -y intel-basekit
-      - name: Install CUDA Dependencies
-        run: |
-          curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
-          sudo dpkg -i cuda-keyring_1.1-1_all.deb
-          sudo apt-get update
-          sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
-        env:
-          CUDA_VERSION: 12-5
-      - name: "Install Hipblas"
-        env:
-          ROCM_VERSION: "6.1"
-          AMDGPU_VERSION: "6.1"
-        run: |
-            set -ex
-
-            sudo apt-get update
-            sudo DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends ca-certificates curl libnuma-dev gnupg
-
-            curl -sL https://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
-
-            printf "deb [arch=amd64] https://repo.radeon.com/rocm/apt/$ROCM_VERSION/ jammy main" | sudo tee /etc/apt/sources.list.d/rocm.list
-
-            printf "deb [arch=amd64] https://repo.radeon.com/amdgpu/$AMDGPU_VERSION/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-            printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-            sudo apt-get update
-
-            sudo DEBIAN_FRONTEND=noninteractive apt-get install -y \
-                hipblas-dev rocm-dev \
-                rocblas-dev
-
-            sudo apt-get clean
-            sudo rm -rf /var/lib/apt/lists/*
-            sudo ldconfig
-      - name: Cache grpc
-        id: cache-grpc
-        uses: actions/cache@v4
-        with:
-          path: grpc
-          key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
-      - name: Build grpc
-        if: steps.cache-grpc.outputs.cache-hit != 'true'
-        run: |
-          git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-          cd grpc && sed -i "216i\  TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
-          cd cmake/build && cmake -DgRPC_INSTALL=ON \
-            -DgRPC_BUILD_TESTS=OFF \
-            ../.. && sudo make --jobs 5 --output-sync=target
-      - name: Install gRPC
-        run: |
-          cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
-      # BACKEND_LIBS needed for gpu-workload: /opt/intel/oneapi/*/lib/libiomp5.so /opt/intel/oneapi/*/lib/libmkl_core.so /opt/intel/oneapi/*/lib/libmkl_core.so.2 /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so.2 /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so.4 /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so.2 /opt/intel/oneapi/*/lib/libsycl.so /opt/intel/oneapi/*/lib/libsycl.so.7 /opt/intel/oneapi/*/lib/libsycl.so.7.1.0 /opt/rocm-*/lib/libamdhip64.so /opt/rocm-*/lib/libamdhip64.so.5 /opt/rocm-*/lib/libamdhip64.so.6 /opt/rocm-*/lib/libamdhip64.so.6.1.60100 /opt/rocm-*/lib/libhipblas.so /opt/rocm-*/lib/libhipblas.so.2 /opt/rocm-*/lib/libhipblas.so.2.1.60100 /opt/rocm-*/lib/librocblas.so /opt/rocm-*/lib/librocblas.so.4 /opt/rocm-*/lib/librocblas.so.4.1.60100 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1.0.0 /usr/lib/x86_64-linux-gnu/libm.so.6 /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 /usr/lib/x86_64-linux-gnu/libc.so.6 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/local/cuda-*/targets/x86_64-linux/lib/libcublas.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcublasLt.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcudart.so /usr/local/cuda-*/targets/x86_64-linux/lib/stubs/libcuda.so
-      - name: Build
-        id: build
-        run: |
-          go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
-          go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
-          export PATH=$PATH:$GOPATH/bin
-          export PATH=/usr/local/cuda/bin:$PATH
-          export PATH=/opt/rocm/bin:$PATH
-          source /opt/intel/oneapi/setvars.sh
-          sudo cp /lib64/ld-linux-x86-64.so.2 ld.so
-          BACKEND_LIBS="./ld.so ./sources/go-piper/piper/build/fi/lib/libfmt.a ./sources/go-piper/piper-phonemize/pi/lib/libonnxruntime.so.1.14.1 ./sources/go-piper/piper-phonemize/pi/src/libespeak-ng/libespeak-ng.so /usr/lib/x86_64-linux-gnu/libdl.so.2 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/lib/x86_64-linux-gnu/libpthread.so.0 ./sources/go-piper/piper-phonemize/pi/lib/libpiper_phonemize.so.1 ./sources/go-piper/piper/build/si/lib/libspdlog.a ./sources/go-piper/espeak/ei/lib/libucd.so" \
-          make -j4 dist
-      - uses: actions/upload-artifact@v4
-        with:
-          name: LocalAI-linux
-          path: release/
-      - name: Release
         uses: softprops/action-gh-release@v2
-        if: startsWith(github.ref, 'refs/tags/')
         with:
-          files: |
+          files: ./local-ai-launcher-linux.tar.xz
-            release/*
-      - name: Setup tmate session if tests fail
-        if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.22
-        with:
-          detached: true
-          connect-timeout-seconds: 180
-          limit-access-to-actor: true
-
-
-  build-macOS-x86_64:
-    runs-on: macos-13
-    steps:
-      - name: Clone
-        uses: actions/checkout@v4
-        with:
-          submodules: true
-      - uses: actions/setup-go@v5
-        with:
-          go-version: '1.21.x'
-          cache: false
-      - name: Dependencies
-        run: |
-          brew install protobuf grpc
-          make install-go-tools
-      - name: Build
-        id: build
-        run: |
-          export C_INCLUDE_PATH=/usr/local/include
-          export CPLUS_INCLUDE_PATH=/usr/local/include
-          export PATH=$PATH:$GOPATH/bin
-          export SKIP_GRPC_BACKEND=backend-assets/grpc/whisper
-          make dist
-      - uses: actions/upload-artifact@v4
-        with:
-          name: LocalAI-MacOS-x86_64
-          path: release/
-      - name: Release
-        uses: softprops/action-gh-release@v2
-        if: startsWith(github.ref, 'refs/tags/')
-        with:
-          files: |
-            release/*
-      - name: Setup tmate session if tests fail
-        if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.22
-        with:
-          detached: true
-          connect-timeout-seconds: 180
-          limit-access-to-actor: true
-
-  build-macOS-arm64:
-    runs-on: macos-14
-    steps:
-      - name: Clone
-        uses: actions/checkout@v4
-        with:
-          submodules: true
-      - uses: actions/setup-go@v5
-        with:
-          go-version: '1.21.x'
-          cache: false
-      - name: Dependencies
-        run: |
-          brew install protobuf grpc libomp llvm
-          make install-go-tools
-      - name: Build
-        id: build
-        run: |
-          export C_INCLUDE_PATH=/usr/local/include
-          export CPLUS_INCLUDE_PATH=/usr/local/include
-          export PATH=$PATH:$GOPATH/bin
-          export CC=/opt/homebrew/opt/llvm/bin/clang
-          make dist
-      - uses: actions/upload-artifact@v4
-        with:
-          name: LocalAI-MacOS-arm64
-          path: release/
-      - name: Release
-        uses: softprops/action-gh-release@v2
-        if: startsWith(github.ref, 'refs/tags/')
-        with:
-          files: |
-            release/*
-      - name: Setup tmate session if tests fail
-        if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.22
-        with:
-          detached: true
-          connect-timeout-seconds: 180
-          limit-access-to-actor: true

.github/workflows/secscan.yaml

@@ -14,11 +14,11 @@ jobs:
       GO111MODULE: on
     steps:
       - name: Checkout Source
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         if: ${{ github.actor != 'dependabot[bot]' }}
       - name: Run Gosec Security Scanner
         if: ${{ github.actor != 'dependabot[bot]' }}
-        uses: securego/gosec@v2.22.4
+        uses: securego/gosec@v2.22.8
         with:
           # we let the report trigger content trigger a failure using the GitHub Security features.
           args: '-no-fail -fmt sarif -out results.sarif ./...'

.github/workflows/stalebot.yml

@@ -0,0 +1,24 @@
+name: 'Close stale issues and PRs'
+permissions:
+  issues: write
+  pull-requests: write
+on:
+  schedule:
+    - cron: '30 1 * * *'
+
+jobs:
+  stale:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/stale@3a9db7e6a41a89f618792c92c0e97cc736e1b13f # v9
+        with:
+          stale-issue-message: 'This issue is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 5 days.'
+          stale-pr-message: 'This PR is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 10 days.'
+          close-issue-message: 'This issue was closed because it has been stalled for 5 days with no activity.'
+          close-pr-message: 'This PR was closed because it has been stalled for 10 days with no activity.'
+          days-before-issue-stale: 90
+          days-before-pr-stale: 90
+          days-before-issue-close: 5
+          days-before-pr-close: 10
+          exempt-issue-labels: 'roadmap'
+          exempt-pr-labels: 'roadmap'

.github/workflows/test-extra.yml

@@ -14,11 +14,33 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
+  # Requires CUDA
+  # tests-chatterbox-tts:
+  #   runs-on: ubuntu-latest
+  #   steps:
+  #     - name: Clone
+  #       uses: actions/checkout@v5
+  #       with:
+  #         submodules: true
+  #     - name: Dependencies
+  #       run: |
+  #         sudo apt-get update
+  #         sudo apt-get install build-essential ffmpeg
+  #         # Install UV
+  #         curl -LsSf https://astral.sh/uv/install.sh | sh
+  #         sudo apt-get install -y ca-certificates cmake curl patch python3-pip
+  #         sudo apt-get install -y libopencv-dev
+  #         pip install --user --no-cache-dir grpcio-tools==1.64.1
+
+  #     - name: Test chatterbox-tts
+  #       run: |
+  #          make --jobs=5 --output-sync=target -C backend/python/chatterbox
+  #          make --jobs=5 --output-sync=target -C backend/python/chatterbox test
   tests-transformers:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -39,7 +61,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -61,7 +83,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -82,7 +104,7 @@ jobs:
   #  runs-on: ubuntu-latest
   #  steps:
   #    - name: Clone
-  #      uses: actions/checkout@v4
+  #      uses: actions/checkout@v5
   #      with:
   #        submodules: true
   #    - name: Dependencies
@@ -102,7 +124,7 @@ jobs:
   #   runs-on: ubuntu-latest
   #   steps:
   #     - name: Clone
-  #       uses: actions/checkout@v4
+  #       uses: actions/checkout@v5
   #       with:
   #         submodules: true
   #     - name: Dependencies
@@ -164,7 +186,7 @@ jobs:
   #           sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
   #           df -h
   #     - name: Clone
-  #       uses: actions/checkout@v4
+  #       uses: actions/checkout@v5
   #       with:
   #         submodules: true
   #     - name: Dependencies
@@ -189,7 +211,7 @@ jobs:
   #   runs-on: ubuntu-latest
   #   steps:
   #     - name: Clone
-  #       uses: actions/checkout@v4
+  #       uses: actions/checkout@v5
   #       with:
   #         submodules: true
   #     - name: Dependencies
@@ -210,7 +232,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies

.github/workflows/test.yml

@@ -23,6 +23,20 @@ jobs:
       matrix:
         go-version: ['1.21.x']
     steps:
+      - name: Free Disk Space (Ubuntu)
+        uses: jlumbroso/free-disk-space@main
+        with:
+          # this might remove tools that are actually needed,
+          # if set to "true" but frees about 6 GB
+          tool-cache: true
+          # all of these default to true, but feel free to set to
+          # "false" if necessary for your workflow
+          android: true
+          dotnet: true
+          haskell: true
+          large-packages: true
+          docker-images: true
+          swap-storage: true
       - name: Release space from worker
         run: |
           echo "Listing top largest packages"
@@ -56,7 +70,7 @@ jobs:
           sudo rm -rfv build || true
           df -h
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -67,18 +81,20 @@ jobs:
       # You can test your matrix by printing the current Go version
       - name: Display Go version
         run: go version
+      - name: Proto Dependencies
+        run: |
+          # Install protoc
+          curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
+          unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
+          rm protoc.zip
+          go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
+          go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
+          PATH="$PATH:$HOME/go/bin" make protogen-go
       - name: Dependencies
         run: |
           sudo apt-get update
           sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
           sudo apt-get install -y libgmock-dev clang
-          curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
-             sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
-             gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
-             sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
-             sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
-             sudo apt-get update && \
-             sudo apt-get install -y conda
           # Install UV
           curl -LsSf https://astral.sh/uv/install.sh | sh
           sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
@@ -94,38 +110,15 @@ jobs:
           sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
           export CUDACXX=/usr/local/cuda/bin/nvcc
 
-          go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
-          go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
-          go install github.com/GeertJohan/go.rice/rice@latest
 
           # The python3-grpc-tools package in 22.04 is too old
-          pip install --user grpcio-tools
+          pip install --user grpcio-tools==1.71.0 grpcio==1.71.0
 
           make -C backend/python/transformers
 
-          # Pre-build piper before we start tests in order to have shared libraries in place
+          make backends/huggingface backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
-          make sources/go-piper && \
-          GO_TAGS="tts" make -C sources/go-piper piper.o && \
-          sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/
         env:
           CUDA_VERSION: 12-4
-      - name: Cache grpc
-        id: cache-grpc
-        uses: actions/cache@v4
-        with:
-          path: grpc
-          key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
-      - name: Build grpc
-        if: steps.cache-grpc.outputs.cache-hit != 'true'
-        run: |
-          git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
-          cd grpc && sed -i "216i\  TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
-          cmake -DgRPC_INSTALL=ON \
-            -DgRPC_BUILD_TESTS=OFF \
-            ../.. && sudo make --jobs 5
-      - name: Install gRPC
-        run: |
-          cd grpc && cd cmake/build && sudo make --jobs 5 install
       - name: Test
         run: |
           PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
@@ -173,7 +166,7 @@ jobs:
           sudo rm -rfv build || true
           df -h
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -184,16 +177,10 @@ jobs:
           rm protoc.zip
           go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
           go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
-          go install github.com/GeertJohan/go.rice/rice@latest
           PATH="$PATH:$HOME/go/bin" make protogen-go
-      - name: Build images
-        run: |
-          docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
-          BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
       - name: Test
         run: |
-            PATH="$PATH:$HOME/go/bin" LOCALAI_MODELS_DIR=$PWD/models LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio \
+            PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-aio e2e-aio
-            make run-e2e-aio
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
         uses: mxschmitt/action-tmate@v3.22
@@ -209,7 +196,7 @@ jobs:
         go-version: ['1.21.x']
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -223,8 +210,11 @@ jobs:
       - name: Dependencies
         run: |
           brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
-          pip install --user --no-cache-dir grpcio-tools
+          pip install --user --no-cache-dir grpcio-tools==1.71.0 grpcio==1.71.0
-          go install github.com/GeertJohan/go.rice/rice@latest
+      - name: Build llama-cpp-darwin
+        run: |
+          make protogen-go
+          make backends/llama-cpp-darwin
       - name: Test
         run: |
           export C_INCLUDE_PATH=/usr/local/include
@@ -232,7 +222,8 @@ jobs:
           export CC=/opt/homebrew/opt/llvm/bin/clang
           # Used to run the newer GNUMake version from brew that supports --output-sync
           export PATH="/opt/homebrew/opt/make/libexec/gnubin:$PATH"
-          BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF" make --jobs 4 --output-sync=target test
+          PATH="$PATH:$HOME/go/bin" make protogen-go
+          PATH="$PATH:$HOME/go/bin" BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF" make --jobs 4 --output-sync=target test
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
         uses: mxschmitt/action-tmate@v3.22

.github/workflows/update_swagger.yaml

@@ -9,7 +9,7 @@ jobs:
       fail-fast: false
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - uses: actions/setup-go@v5
         with:
           go-version: 'stable'

.github/workflows/yaml-check.yml

@@ -8,7 +8,7 @@ jobs:
     steps:
       - name: 'Checkout'
         uses: actions/checkout@master
-      - name: 'Yamllint'
+      - name: 'Yamllint model gallery'
         uses: karancode/yamllint-github-action@master
         with:
           yamllint_file_or_dir: 'gallery'
@@ -16,3 +16,11 @@ jobs:
           yamllint_comment: true
         env:
           GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+      - name: 'Yamllint Backend gallery'
+        uses: karancode/yamllint-github-action@master
+        with:
+          yamllint_file_or_dir: 'backend'
+          yamllint_strict: false
+          yamllint_comment: true
+        env:
+          GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.gitignore

@@ -5,9 +5,14 @@ __pycache__/
 *.o
 get-sources
 prepare-sources
-/backend/cpp/llama/grpc-server
+/backend/cpp/llama-cpp/grpc-server
-/backend/cpp/llama/llama.cpp
+/backend/cpp/llama-cpp/llama.cpp
 /backend/cpp/llama-*
+!backend/cpp/llama-cpp
+/backends
+/backend-images
+/result.yaml
+protoc
 
 *.log
 
@@ -19,7 +24,7 @@ go-bert
 
 # LocalAI build binary
 LocalAI
-local-ai
+/local-ai
 # prevent above rules from omitting the helm chart
 !charts/*
 # prevent above rules from omitting the api/localai folder

.goreleaser.yaml

@@ -0,0 +1,33 @@
+version: 2
+before:
+  hooks:
+    - make protogen-go
+    - go mod tidy
+dist: release
+source:
+  enabled: true
+  name_template: '{{ .ProjectName }}-{{ .Tag }}-source'
+builds:
+  - main: ./cmd/local-ai
+    env:
+      - CGO_ENABLED=0
+    ldflags:
+      - -s -w
+      - -X "github.com/mudler/LocalAI/internal.Version={{ .Tag }}"
+      - -X "github.com/mudler/LocalAI/internal.Commit={{ .FullCommit }}"
+    goos:
+      - linux
+      - darwin
+      #- windows
+    goarch:
+      - amd64
+      - arm64
+archives:
+  - formats: [ 'binary' ] # this removes the tar of the archives, leaving the binaries alone
+    name_template: local-ai-{{ .Tag }}-{{ .Os }}-{{ .Arch }}{{ if .Arm }}v{{ .Arm }}{{ end }}
+checksum:
+  name_template: '{{ .ProjectName }}-{{ .Tag }}-checksums.txt'
+snapshot:
+  version_template: "{{ .Tag }}-next"
+changelog:
+  use: github-native

.vscode/launch.json

@@ -26,7 +26,7 @@
                 "LOCALAI_P2P": "true",
                 "LOCALAI_FEDERATED": "true"
             },
-            "buildFlags": ["-tags", "p2p tts", "-v"],
+            "buildFlags": ["-tags", "", "-v"],
             "envFile": "${workspaceFolder}/.env",
             "cwd": "${workspaceRoot}"
         }

Dockerfile

@@ -1,121 +1,32 @@
-ARG IMAGE_TYPE=extras
 ARG BASE_IMAGE=ubuntu:22.04
 ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
 ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
 
-# The requirements-core target is common to all images.  It should not be placed in requirements-core unless every single build will use it.
+FROM ${BASE_IMAGE} AS requirements
-FROM ${BASE_IMAGE} AS requirements-core
-
-USER root
-
-ARG GO_VERSION=1.22.6
-ARG CMAKE_VERSION=3.26.4
-ARG CMAKE_FROM_SOURCE=false
-ARG TARGETARCH
-ARG TARGETVARIANT
 
 ENV DEBIAN_FRONTEND=noninteractive
-ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,transformers:/build/backend/python/transformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,faster-whisper:/build/backend/python/faster-whisper/run.sh,kokoro:/build/backend/python/kokoro/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh"
 
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
-        build-essential \
+        ca-certificates curl wget espeak-ng libgomp1 \
-        ccache \
+        ffmpeg libopenblas-base libopenblas-dev && \
-        ca-certificates \
-        curl libssl-dev \
-        git \
-        git-lfs \
-        unzip upx-ucl && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# Install Go
-RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
-ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
-
-# Install grpc compilers and rice
-RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
-    go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af && \
-    go install github.com/GeertJohan/go.rice/rice@latest
-
-COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
-RUN update-ca-certificates
-
-RUN test -n "$TARGETARCH" \
-    || (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
-
-# Use the variables in subsequent instructions
-RUN echo "Target Architecture: $TARGETARCH"
-RUN echo "Target Variant: $TARGETVARIANT"
-
-# Cuda
-ENV PATH=/usr/local/cuda/bin:${PATH}
-
-# HipBLAS requirements
-ENV PATH=/opt/rocm/bin:${PATH}
-
-# OpenBLAS requirements and stable diffusion
-RUN apt-get update && \
-    apt-get install -y --no-install-recommends \
-        libopenblas-dev && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
-
-WORKDIR /build
-
-###################################
-###################################
-
-# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
-FROM requirements-core AS requirements-extras
-
-# Install uv as a system package
-RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
-ENV PATH="/root/.cargo/bin:${PATH}"
-
-RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
-RUN apt-get update && \
-    apt-get install -y --no-install-recommends \
-        espeak-ng \
-        espeak \
-        python3-pip \
-        python-is-python3 \
-        python3-dev llvm \
-        python3-venv && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/* && \
-    pip install --upgrade pip
-
-# Install grpcio-tools (the version in 22.04 is too old)
-RUN pip install --user grpcio-tools
-
-###################################
-###################################
-
 # The requirements-drivers target is for BUILD_TYPE specific items.  If you need to install something specific to CUDA, or specific to ROCM, it goes here.
-# This target will be built on top of requirements-core or requirements-extras as retermined by the IMAGE_TYPE build-arg
+FROM requirements AS requirements-drivers
-FROM requirements-${IMAGE_TYPE} AS requirements-drivers
 
 ARG BUILD_TYPE
 ARG CUDA_MAJOR_VERSION=12
-ARG CUDA_MINOR_VERSION=0
+ARG CUDA_MINOR_VERSION=8
 ARG SKIP_DRIVERS=false
-
+ARG TARGETARCH
+ARG TARGETVARIANT
 ENV BUILD_TYPE=${BUILD_TYPE}
 
+RUN mkdir -p /run/localai
+RUN echo "default" > /run/localai/capability
+
 # Vulkan requirements
 RUN <<EOT bash
     if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
@@ -128,7 +39,8 @@ RUN <<EOT bash
         apt-get install -y \
             vulkan-sdk && \
         apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
+        rm -rf /var/lib/apt/lists/* && \
+        echo "vulkan" > /run/localai/capability
     fi
 EOT
 
@@ -155,7 +67,14 @@ RUN <<EOT bash
             libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
         apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
+        rm -rf /var/lib/apt/lists/* && \
+        echo "nvidia" > /run/localai/capability
+    fi
+EOT
+
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
+        echo "nvidia-l4t" > /run/localai/capability
     fi
 EOT
 
@@ -175,11 +94,94 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
             rocblas-dev && \
         apt-get clean && \
         rm -rf /var/lib/apt/lists/* && \
+        echo "amd" > /run/localai/capability && \
         # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
         # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
         ldconfig \
     ; fi
 
+RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
+    ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
+    ; fi
+
+RUN expr "${BUILD_TYPE}" = intel && echo "intel" > /run/localai/capability || echo "not intel"
+
+# Cuda
+ENV PATH=/usr/local/cuda/bin:${PATH}
+
+# HipBLAS requirements
+ENV PATH=/opt/rocm/bin:${PATH}
+
+###################################
+###################################
+
+# The requirements-core target is common to all images.  It should not be placed in requirements-core unless every single build will use it.
+FROM requirements-drivers AS build-requirements
+
+ARG GO_VERSION=1.22.6
+ARG CMAKE_VERSION=3.26.4
+ARG CMAKE_FROM_SOURCE=false
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        ccache \
+        ca-certificates espeak-ng \
+        curl libssl-dev \
+        git \
+        git-lfs \
+        unzip upx-ucl python3 python-is-python3 && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Install CMake (the version in 22.04 is too old)
+RUN <<EOT bash
+    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
+        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
+    else
+        apt-get update && \
+        apt-get install -y \
+            cmake && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# Install Go
+RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
+ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
+
+# Install grpc compilers
+RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
+    go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
+
+COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
+RUN update-ca-certificates
+
+
+# OpenBLAS requirements and stable diffusion
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        libopenblas-dev && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN test -n "$TARGETARCH" \
+    || (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
+
+# Use the variables in subsequent instructions
+RUN echo "Target Architecture: $TARGETARCH"
+RUN echo "Target Variant: $TARGETVARIANT"
+
+
+
+
+WORKDIR /build
+
+
 ###################################
 ###################################
 
@@ -190,69 +192,25 @@ FROM ${INTEL_BASE_IMAGE} AS intel
 RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
 gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
 RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
-
-###################################
-###################################
-
-# The grpc target does one thing, it builds and installs GRPC.  This is in it's own layer so that it can be effectively cached by CI.
-# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
-FROM ${GRPC_BASE_IMAGE} AS grpc
-
-# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
-ARG GRPC_MAKEFLAGS="-j4 -Otarget"
-ARG GRPC_VERSION=v1.65.0
-ARG CMAKE_FROM_SOURCE=false
-ARG CMAKE_VERSION=3.26.4
-
-ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
-
-WORKDIR /build
-
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
-        ca-certificates \
+        intel-oneapi-runtime-libs && \
-        build-essential curl libssl-dev \
-        git && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
-# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
-# and running make install in the target container
-RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-    mkdir -p /build/grpc/cmake/build && \
-    cd /build/grpc/cmake/build && \
-    sed -i "216i\  TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
-    cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
-    make && \
-    make install && \
-    rm -rf /build
-
 ###################################
 ###################################
 
 # The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
 
-FROM requirements-drivers AS builder-base
+FROM build-requirements AS builder-base
 
-ARG GO_TAGS="tts p2p"
+ARG GO_TAGS=""
 ARG GRPC_BACKENDS
 ARG MAKEFLAGS
 ARG LD_FLAGS="-s -w"
-
+ARG TARGETARCH
+ARG TARGETVARIANT
 ENV GRPC_BACKENDS=${GRPC_BACKENDS}
 ENV GO_TAGS=${GO_TAGS}
 ENV MAKEFLAGS=${MAKEFLAGS}
@@ -266,9 +224,7 @@ RUN echo "GO_TAGS: $GO_TAGS" && echo "TARGETARCH: $TARGETARCH"
 WORKDIR /build
 
 
-# We need protoc installed, and the version in 22.04 is too old.  We will create one as part installing the GRPC build below
+# We need protoc installed, and the version in 22.04 is too old.
-# but that will also being in a newer version of absl which stablediffusion cannot compile with.  This version of protoc is only
-# here so that we can generate the grpc code for the stablediffusion build
 RUN <<EOT bash
     if [ "amd64" = "$TARGETARCH" ]; then
         curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
@@ -285,34 +241,39 @@ EOT
 ###################################
 ###################################
 
+# Compile backends first in a separate stage
+FROM builder-base AS builder-backends
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+WORKDIR /build
+
+COPY ./Makefile .
+COPY ./backend ./backend
+COPY ./go.mod .
+COPY ./go.sum .
+COPY ./.git ./.git
+
+# Some of the Go backends use libs from the main src, we could further optimize the caching by building the CPP backends before here
+COPY ./pkg/grpc ./pkg/grpc
+COPY ./pkg/utils ./pkg/utils
+COPY ./pkg/langchain ./pkg/langchain
+
+RUN ls -l ./
+RUN make protogen-go
+
 # The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
 # Adjustments to the build process should likely be made here.
-FROM builder-base AS builder
+FROM builder-backends AS builder
 
-# Install the pre-built GRPC
-COPY --from=grpc /opt/grpc /usr/local
-
-# Rebuild with defaults backends
 WORKDIR /build
 
 COPY . .
-COPY .git .
-
-RUN make prepare
 
 ## Build the binary
 ## If we're on arm64 AND using cublas/hipblas, skip some of the llama-compat backends to save space
 ## Otherwise just run the normal build
-RUN if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
+RUN make build
-        SKIP_GRPC_BACKEND="backend-assets/grpc/llama-cpp-avx512 backend-assets/grpc/llama-cpp-avx backend-assets/grpc/llama-cpp-avx2" make build; \
-    else \
-        make build; \
-    fi
-
-RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
-        mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
-        touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
-    ; fi
 
 ###################################
 ###################################
@@ -322,24 +283,11 @@ RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
 
 FROM builder-base AS devcontainer
 
-ARG FFMPEG
-
-COPY --from=grpc /opt/grpc /usr/local
-
 COPY .devcontainer-scripts /.devcontainer-scripts
 
-# Add FFmpeg
-RUN if [ "${FFMPEG}" = "true" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            ffmpeg && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* \
-    ; fi
-
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
-        ssh less wget
+        ssh less
 # For the devcontainer, leave apt functional in case additional devtools are needed at runtime.
 
 RUN go install github.com/go-delve/delve/cmd/dlv@latest
@@ -353,98 +301,27 @@ RUN go install github.com/mikefarah/yq/v4@latest
 # If you cannot find a more suitable place for an addition, this layer is a suitable place for it.
 FROM requirements-drivers
 
-ARG FFMPEG
-ARG BUILD_TYPE
-ARG TARGETARCH
-ARG IMAGE_TYPE=extras
-ARG EXTRA_BACKENDS
-ARG MAKEFLAGS
-
-ENV BUILD_TYPE=${BUILD_TYPE}
-ENV REBUILD=false
 ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
-ENV MAKEFLAGS=${MAKEFLAGS}
 
 ARG CUDA_MAJOR_VERSION=12
 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
 ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
 ENV NVIDIA_VISIBLE_DEVICES=all
 
-# Add FFmpeg
+WORKDIR /
-RUN if [ "${FFMPEG}" = "true" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            ffmpeg && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* \
-    ; fi
 
-WORKDIR /build
+COPY ./entrypoint.sh .
-
-# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
-# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
-# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
-# https://github.com/go-skynet/LocalAI/pull/434
-COPY . .
-
-COPY --from=builder /build/sources ./sources/
-COPY --from=grpc /opt/grpc /usr/local
-
-RUN make prepare-sources
 
 # Copy the binary
 COPY --from=builder /build/local-ai ./
 
-# Copy shared libraries for piper
-COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
-
-# Change the shell to bash so we can use [[ tests below
-SHELL ["/bin/bash", "-c"]
-# We try to strike a balance between individual layer size (as that affects total push time) and total image size
-# Splitting the backends into more groups with fewer items results in a larger image, but a smaller size for the largest layer
-# Splitting the backends into fewer groups with more items results in a smaller image, but a larger size for the largest layer
-
-RUN if [[ ( "${IMAGE_TYPE}" == "extras ")]]; then \
-        apt-get -qq -y install espeak-ng \
-    ; fi
-
-RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/coqui \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "faster-whisper" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/faster-whisper \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/diffusers \
-    ; fi
-
-RUN if [[ ( "${EXTRA_BACKENDS}" =~ "kokoro" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/kokoro \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/exllama2 \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "transformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/transformers \
-    ; fi
-
-RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/vllm \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "bark" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/bark \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/rerankers \
-    ; fi
-
 # Make sure the models directory exists
-RUN mkdir -p /build/models
+RUN mkdir -p /models /backends
 
 # Define the health check command
 HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
   CMD curl -f ${HEALTHCHECK_ENDPOINT} || exit 1
 
-VOLUME /build/models
+VOLUME /models /backends
 EXPOSE 8080
-ENTRYPOINT [ "/build/entrypoint.sh" ]
+ENTRYPOINT [ "/entrypoint.sh" ]

Earthfile

@@ -1,5 +0,0 @@
-VERSION 0.7
-
-build:
-    FROM DOCKERFILE -f Dockerfile .
-    SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai

README.md

@@ -1,6 +1,6 @@
 <h1 align="center">
   <br>
-  <img height="300" src="./core/http/static/logo.png"> <br>
+  <img width="300" src="./core/http/static/logo.png"> <br>
 <br>
 </h1>
 
@@ -110,25 +110,72 @@ curl https://localai.io/install.sh | sh
 
 For more installation options, see [Installer Options](https://localai.io/docs/advanced/installer/).
 
+### macOS Download:
+
+<a href="https://github.com/mudler/LocalAI/releases/latest/download/LocalAI.dmg">
+  <img src="https://img.shields.io/badge/Download-macOS-blue?style=for-the-badge&logo=apple&logoColor=white" alt="Download LocalAI for macOS"/>
+</a>
+
 Or run with docker:
 
 ### CPU only image:
-```bash
+
-docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-cpu
-```
-### Nvidia GPU:
-```bash
-docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
-```
-### CPU and GPU image (bigger size):
 ```bash
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
 ```
-### AIO images (it will pre-download a set of models ready for use, see https://localai.io/basics/container/)
+
+### NVIDIA GPU Images:
+
 ```bash
-docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
+# CUDA 12.0
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
+
+# CUDA 11.7
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-11
+
+# NVIDIA Jetson (L4T) ARM64
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64
 ```
 
+### AMD GPU Images (ROCm):
+
+```bash
+docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblas
+```
+
+### Intel GPU Images (oneAPI):
+
+```bash
+docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
+```
+
+### Vulkan GPU Images:
+
+```bash
+docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan
+```
+
+### AIO Images (pre-downloaded models):
+
+```bash
+# CPU version
+docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
+
+# NVIDIA CUDA 12 version
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
+
+# NVIDIA CUDA 11 version
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-11
+
+# Intel GPU version
+docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel
+
+# AMD GPU version
+docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-aio-gpu-hipblas
+```
+
+For more information about the AIO images and pre-downloaded models, see [Container Documentation](https://localai.io/basics/container/).
+
 To load models:
 
 ```bash
@@ -144,10 +191,19 @@ local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
 local-ai run oci://localai/phi-2:latest
 ```
 
+> ⚡ **Automatic Backend Detection**: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/#automatic-backend-detection).
+
 For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html)
 
 ## 📰 Latest project news
 
+- August 2025: MLX, MLX-VLM, Diffusers and llama.cpp are now supported on Mac M1/M2/M3+ chips ( with `development` suffix in the gallery ): https://github.com/mudler/LocalAI/pull/6049 https://github.com/mudler/LocalAI/pull/6119 https://github.com/mudler/LocalAI/pull/6121 https://github.com/mudler/LocalAI/pull/6060
+- July/August 2025: 🔍 [Object Detection](https://localai.io/features/object-detection/) added to the API featuring [rf-detr](https://github.com/roboflow/rf-detr)
+- July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. [Read the release notes](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
+- June 2025: [Backend management](https://github.com/mudler/LocalAI/pull/5607) has been added. Attention: extras images are going to be deprecated from the next release! Read [the backend management PR](https://github.com/mudler/LocalAI/pull/5607).
+- May 2025: [Audio input](https://github.com/mudler/LocalAI/pull/5466) and [Reranking](https://github.com/mudler/LocalAI/pull/5396) in llama.cpp backend, [Realtime API](https://github.com/mudler/LocalAI/pull/5392),  Support to Gemma, SmollVLM, and more multimodal models (available in the gallery).
+- May 2025: Important: image name changes [See release](https://github.com/mudler/LocalAI/releases/tag/v2.29.0)
+- Apr 2025: Rebrand, WebUI enhancements
 - Apr 2025: [LocalAGI](https://github.com/mudler/LocalAGI) and [LocalRecall](https://github.com/mudler/LocalRecall) join the LocalAI family stack.
 - Apr 2025: WebUI overhaul, AIO images updates
 - Feb 2025: Backend cleanup, Breaking changes, new backends (kokoro, OutelTTS, faster-whisper), Nvidia L4T images
@@ -166,6 +222,7 @@ Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3A
 
 ## 🚀 [Features](https://localai.io/features/)
 
+- 🧩 [Backend Gallery](https://localai.io/backends/): Install/remove backends on the fly, powered by OCI images — fully customizable and API-driven.
 - 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `transformers`, `vllm` ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
 - 🗣 [Text to Audio](https://localai.io/features/text-to-audio/)
 - 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
@@ -175,12 +232,67 @@ Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3A
 - ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
 - 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
 - 🥽 [Vision API](https://localai.io/features/gpt-vision/)
+- 🔍 [Object Detection](https://localai.io/features/object-detection/)
 - 📈 [Reranker API](https://localai.io/features/reranker/)
 - 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
 - [Agentic capabilities](https://github.com/mudler/LocalAGI)
 - 🔊 Voice activity detection (Silero-VAD support)
 - 🌍 Integrated WebUI!
 
+## 🧩 Supported Backends & Acceleration
+
+LocalAI supports a comprehensive range of AI backends with multiple acceleration options:
+
+### Text Generation & Language Models
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **llama.cpp** | LLM inference in C/C++ | CUDA 11/12, ROCm, Intel SYCL, Vulkan, Metal, CPU |
+| **vLLM** | Fast LLM inference with PagedAttention | CUDA 12, ROCm, Intel |
+| **transformers** | HuggingFace transformers framework | CUDA 11/12, ROCm, Intel, CPU |
+| **exllama2** | GPTQ inference library | CUDA 12 |
+| **MLX** | Apple Silicon LLM inference | Metal (M1/M2/M3+) |
+| **MLX-VLM** | Apple Silicon Vision-Language Models | Metal (M1/M2/M3+) |
+
+### Audio & Speech Processing
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **whisper.cpp** | OpenAI Whisper in C/C++ | CUDA 12, ROCm, Intel SYCL, Vulkan, CPU |
+| **faster-whisper** | Fast Whisper with CTranslate2 | CUDA 12, ROCm, Intel, CPU |
+| **bark** | Text-to-audio generation | CUDA 12, ROCm, Intel |
+| **bark-cpp** | C++ implementation of Bark | CUDA, Metal, CPU |
+| **coqui** | Advanced TTS with 1100+ languages | CUDA 12, ROCm, Intel, CPU |
+| **kokoro** | Lightweight TTS model | CUDA 12, ROCm, Intel, CPU |
+| **chatterbox** | Production-grade TTS | CUDA 11/12, CPU |
+| **piper** | Fast neural TTS system | CPU |
+| **kitten-tts** | Kitten TTS models | CPU |
+| **silero-vad** | Voice Activity Detection | CPU |
+
+### Image & Video Generation
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **stablediffusion.cpp** | Stable Diffusion in C/C++ | CUDA 12, Intel SYCL, Vulkan, CPU |
+| **diffusers** | HuggingFace diffusion models | CUDA 11/12, ROCm, Intel, Metal, CPU |
+
+### Specialized AI Tasks
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **rfdetr** | Real-time object detection | CUDA 12, Intel, CPU |
+| **rerankers** | Document reranking API | CUDA 11/12, ROCm, Intel, CPU |
+| **local-store** | Vector database | CPU |
+| **huggingface** | HuggingFace API integration | API-based |
+
+### Hardware Acceleration Matrix
+
+| Acceleration Type | Supported Backends | Hardware Support |
+|-------------------|-------------------|------------------|
+| **NVIDIA CUDA 11** | llama.cpp, whisper, stablediffusion, diffusers, rerankers, bark, chatterbox | Nvidia hardware |
+| **NVIDIA CUDA 12** | All CUDA-compatible backends | Nvidia hardware |
+| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark | AMD Graphics |
+| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark | Intel Arc, Intel iGPUs |
+| **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM, bark-cpp | Apple M1/M2/M3+ |
+| **Vulkan** | llama.cpp, whisper, stablediffusion | Cross-platform GPUs |
+| **NVIDIA Jetson** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI |
+| **CPU Optimized** | All backends | AVX/AVX2/AVX512, quantization support |
 
 ### 🔗 Community and integrations
 
@@ -195,6 +307,9 @@ WebUIs:
 Model galleries
 - https://github.com/go-skynet/model-gallery
 
+Voice:
+- https://github.com/richiejp/VoxInput
+
 Other:
 - Helm chart https://github.com/go-skynet/helm-charts
 - VSCode extension https://github.com/badgooooor/localai-vscode-plugin

aio/cpu/embeddings.yaml

@@ -1,5 +1,6 @@
 embeddings: true
 name: text-embedding-ada-002
+backend: llama-cpp
 parameters:
   model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
 

aio/cpu/rerank.yaml

@@ -1,7 +1,13 @@
 name: jina-reranker-v1-base-en
-backend: rerankers
+reranking: true
+f16: true
 parameters:
-  model: cross-encoder
+  model: jina-reranker-v1-tiny-en.f16.gguf
+backend: llama-cpp
+download_files:
+  - filename: jina-reranker-v1-tiny-en.f16.gguf
+    sha256: 5f696cf0d0f3d347c4a279eee8270e5918554cdac0ed1f632f2619e4e8341407
+    uri: huggingface://mradermacher/jina-reranker-v1-tiny-en-GGUF/jina-reranker-v1-tiny-en.f16.gguf 
 
 usage: |
     You can test this model with curl like this:

aio/cpu/text-to-speech.yaml

@@ -2,7 +2,7 @@ name: tts-1
 download_files:
   - filename: voice-en-us-amy-low.tar.gz
     uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
-
+backend: piper
 parameters:
   model: en-us-amy-low.onnx
 

aio/cpu/text-to-text.yaml

@@ -1,5 +1,6 @@
 context_size: 8192
 f16: true
+backend: llama-cpp
 function:
   grammar:
     no_mixed_free_string: true

aio/cpu/vision.yaml

@@ -1,5 +1,6 @@
 context_size: 4096
 f16: true
+backend: llama-cpp
 mmap: true
 mmproj: minicpm-v-2_6-mmproj-f16.gguf
 name: gpt-4o

aio/entrypoint.sh

@@ -135,4 +135,4 @@ check_vars
 
 echo "===> Starting LocalAI[$PROFILE] with the following models: $MODELS"
 
-exec /build/entrypoint.sh "$@"
+exec /entrypoint.sh "$@"

aio/gpu-8g/embeddings.yaml

@@ -1,5 +1,6 @@
 embeddings: true
 name: text-embedding-ada-002
+backend: llama-cpp
 parameters:
   model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
 

aio/gpu-8g/rerank.yaml

@@ -1,7 +1,13 @@
 name: jina-reranker-v1-base-en
-backend: rerankers
+reranking: true
+f16: true
 parameters:
-  model: cross-encoder
+  model: jina-reranker-v1-tiny-en.f16.gguf
+backend: llama-cpp
+download_files:
+  - filename: jina-reranker-v1-tiny-en.f16.gguf
+    sha256: 5f696cf0d0f3d347c4a279eee8270e5918554cdac0ed1f632f2619e4e8341407
+    uri: huggingface://mradermacher/jina-reranker-v1-tiny-en-GGUF/jina-reranker-v1-tiny-en.f16.gguf 
 
 usage: |
     You can test this model with curl like this:

aio/gpu-8g/text-to-speech.yaml

@@ -2,7 +2,7 @@ name: tts-1
 download_files:
   - filename: voice-en-us-amy-low.tar.gz
     uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
-
+backend: piper
 parameters:
   model: en-us-amy-low.onnx
 

aio/gpu-8g/text-to-text.yaml

@@ -1,5 +1,6 @@
 context_size: 4096
 f16: true
+backend: llama-cpp
 function:
   capture_llm_results:
   - (?s)<Thought>(.*?)</Thought>

aio/gpu-8g/vision.yaml

@@ -1,4 +1,5 @@
 context_size: 4096
+backend: llama-cpp
 f16: true
 mmap: true
 mmproj: minicpm-v-2_6-mmproj-f16.gguf

aio/intel/embeddings.yaml

@@ -1,5 +1,6 @@
 embeddings: true
 name: text-embedding-ada-002
+backend: llama-cpp
 parameters:
   model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
 

aio/intel/rerank.yaml

@@ -1,7 +1,13 @@
 name: jina-reranker-v1-base-en
-backend: rerankers
+reranking: true
+f16: true
 parameters:
-  model: cross-encoder
+  model: jina-reranker-v1-tiny-en.f16.gguf
+backend: llama-cpp
+download_files:
+  - filename: jina-reranker-v1-tiny-en.f16.gguf
+    sha256: 5f696cf0d0f3d347c4a279eee8270e5918554cdac0ed1f632f2619e4e8341407
+    uri: huggingface://mradermacher/jina-reranker-v1-tiny-en-GGUF/jina-reranker-v1-tiny-en.f16.gguf 
 
 usage: |
     You can test this model with curl like this:

aio/intel/text-to-speech.yaml

@@ -2,7 +2,7 @@ name: tts-1
 download_files:
   - filename: voice-en-us-amy-low.tar.gz
     uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
-
+backend: piper
 parameters:
   model: en-us-amy-low.onnx
 

aio/intel/text-to-text.yaml

@@ -1,5 +1,6 @@
 context_size: 4096
 f16: true
+backend: llama-cpp
 function:
   capture_llm_results:
   - (?s)<Thought>(.*?)</Thought>

aio/intel/vision.yaml

@@ -1,4 +1,5 @@
 context_size: 4096
+backend: llama-cpp
 f16: true
 mmap: true
 mmproj: minicpm-v-2_6-mmproj-f16.gguf

assets.go

@@ -1,15 +0,0 @@
-package main
-
-import (
-	rice "github.com/GeertJohan/go.rice"
-)
-
-var backendAssets *rice.Box
-
-func init() {
-	var err error
-	backendAssets, err = rice.FindBox("backend-assets")
-	if err != nil {
-		panic(err)
-	}
-}

backend/Dockerfile.golang

@@ -0,0 +1,131 @@
+ARG BASE_IMAGE=ubuntu:22.04
+
+FROM ${BASE_IMAGE} AS builder
+ARG BACKEND=rerankers
+ARG BUILD_TYPE
+ENV BUILD_TYPE=${BUILD_TYPE}
+ARG CUDA_MAJOR_VERSION
+ARG CUDA_MINOR_VERSION
+ARG SKIP_DRIVERS=false
+ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
+ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
+ENV DEBIAN_FRONTEND=noninteractive
+ARG TARGETARCH
+ARG TARGETVARIANT
+ARG GO_VERSION=1.22.6
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        git ccache \
+        ca-certificates \
+        make cmake \
+        curl unzip \
+        libssl-dev && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+
+# Cuda
+ENV PATH=/usr/local/cuda/bin:${PATH}
+
+# HipBLAS requirements
+ENV PATH=/opt/rocm/bin:${PATH}
+
+# Vulkan requirements
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
+        apt-get update && \
+        apt-get install -y  --no-install-recommends \
+            software-properties-common pciutils wget gpg-agent && \
+        wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
+        wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
+        apt-get update && \
+        apt-get install -y \
+            vulkan-sdk && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# CuBLAS requirements
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
+        apt-get update && \
+        apt-get install -y  --no-install-recommends \
+            software-properties-common pciutils
+        if [ "amd64" = "$TARGETARCH" ]; then
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
+        fi
+        if [ "arm64" = "$TARGETARCH" ]; then
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
+        fi
+        dpkg -i cuda-keyring_1.1-1_all.deb && \
+        rm -f cuda-keyring_1.1-1_all.deb && \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# If we are building with clblas support, we need the libraries for the builds
+RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            libclblast-dev && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/* \
+    ; fi
+
+RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            hipblas-dev \
+            rocblas-dev && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/* && \
+        # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
+        # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
+        ldconfig \
+    ; fi
+
+# Install Go
+RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
+ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/bin
+
+# Install grpc compilers
+RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
+    go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
+RUN echo "TARGETARCH: $TARGETARCH"
+
+# We need protoc installed, and the version in 22.04 is too old.  We will create one as part installing the GRPC build below
+# but that will also being in a newer version of absl which stablediffusion cannot compile with.  This version of protoc is only
+# here so that we can generate the grpc code for the stablediffusion build
+RUN <<EOT bash
+    if [ "amd64" = "$TARGETARCH" ]; then
+        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
+        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
+        rm protoc.zip
+    fi
+    if [ "arm64" = "$TARGETARCH" ]; then
+        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
+        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
+        rm protoc.zip
+    fi
+EOT
+
+COPY . /LocalAI
+
+RUN cd /LocalAI && make protogen-go && make -C /LocalAI/backend/go/${BACKEND} build
+
+FROM scratch
+ARG BACKEND=rerankers
+
+COPY --from=builder /LocalAI/backend/go/${BACKEND}/package/. ./

backend/Dockerfile.llama-cpp

@@ -0,0 +1,207 @@
+ARG BASE_IMAGE=ubuntu:22.04
+ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
+
+
+# The grpc target does one thing, it builds and installs GRPC.  This is in it's own layer so that it can be effectively cached by CI.
+# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
+FROM ${GRPC_BASE_IMAGE} AS grpc
+
+# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
+ARG GRPC_MAKEFLAGS="-j4 -Otarget"
+ARG GRPC_VERSION=v1.65.0
+ARG CMAKE_FROM_SOURCE=false
+ARG CMAKE_VERSION=3.26.4
+
+ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
+
+WORKDIR /build
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        ca-certificates \
+        build-essential curl libssl-dev \
+        git && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Install CMake (the version in 22.04 is too old)
+RUN <<EOT bash
+    if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
+        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
+    else
+        apt-get update && \
+        apt-get install -y \
+            cmake && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
+# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
+# and running make install in the target container
+RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
+    mkdir -p /build/grpc/cmake/build && \
+    cd /build/grpc/cmake/build && \
+    sed -i "216i\  TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
+    cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
+    make && \
+    make install && \
+    rm -rf /build
+
+FROM ${BASE_IMAGE} AS builder
+ARG BACKEND=rerankers
+ARG BUILD_TYPE
+ENV BUILD_TYPE=${BUILD_TYPE}
+ARG CUDA_MAJOR_VERSION
+ARG CUDA_MINOR_VERSION
+ARG SKIP_DRIVERS=false
+ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
+ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
+ENV DEBIAN_FRONTEND=noninteractive
+ARG TARGETARCH
+ARG TARGETVARIANT
+ARG GO_VERSION=1.22.6
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        ccache git \
+        ca-certificates \
+        make \
+        curl unzip \
+        libssl-dev && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Cuda
+ENV PATH=/usr/local/cuda/bin:${PATH}
+
+# HipBLAS requirements
+ENV PATH=/opt/rocm/bin:${PATH}
+
+# Vulkan requirements
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
+        apt-get update && \
+        apt-get install -y  --no-install-recommends \
+            software-properties-common pciutils wget gpg-agent && \
+        wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
+        wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
+        apt-get update && \
+        apt-get install -y \
+            vulkan-sdk && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# CuBLAS requirements
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
+        apt-get update && \
+        apt-get install -y  --no-install-recommends \
+            software-properties-common pciutils
+        if [ "amd64" = "$TARGETARCH" ]; then
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
+        fi
+        if [ "arm64" = "$TARGETARCH" ]; then
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
+        fi
+        dpkg -i cuda-keyring_1.1-1_all.deb && \
+        rm -f cuda-keyring_1.1-1_all.deb && \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# If we are building with clblas support, we need the libraries for the builds
+RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            libclblast-dev && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/* \
+    ; fi
+
+RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            hipblas-dev \
+            rocblas-dev && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/* && \
+        # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
+        # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
+        ldconfig \
+    ; fi
+
+RUN echo "TARGETARCH: $TARGETARCH"
+
+# We need protoc installed, and the version in 22.04 is too old.  We will create one as part installing the GRPC build below
+# but that will also being in a newer version of absl which stablediffusion cannot compile with.  This version of protoc is only
+# here so that we can generate the grpc code for the stablediffusion build
+RUN <<EOT bash
+    if [ "amd64" = "$TARGETARCH" ]; then
+        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
+        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
+        rm protoc.zip
+    fi
+    if [ "arm64" = "$TARGETARCH" ]; then
+        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
+        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
+        rm protoc.zip
+    fi
+EOT
+
+# Install CMake (the version in 22.04 is too old)
+RUN <<EOT bash
+    if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
+        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
+    else
+        apt-get update && \
+        apt-get install -y \
+            cmake && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+COPY --from=grpc /opt/grpc /usr/local
+
+
+COPY . /LocalAI
+
+## Otherwise just run the normal build
+RUN <<EOT bash
+if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
+        cd /LocalAI/backend/cpp/llama-cpp && make llama-cpp-fallback && \
+        make llama-cpp-grpc && make llama-cpp-rpc-server; \
+    else \
+        cd /LocalAI/backend/cpp/llama-cpp && make llama-cpp-avx && \
+        make llama-cpp-avx2 && \
+        make llama-cpp-avx512 && \
+        make llama-cpp-fallback && \
+        make llama-cpp-grpc && \
+        make llama-cpp-rpc-server; \
+    fi  
+EOT
+
+
+# Copy libraries using a script to handle architecture differences
+RUN make -C /LocalAI/backend/cpp/llama-cpp package
+
+
+FROM scratch
+
+
+# Copy all available binaries (the build process only creates the appropriate ones for the target architecture)
+COPY --from=builder /LocalAI/backend/cpp/llama-cpp/package/. ./

backend/Dockerfile.python

@@ -0,0 +1,123 @@
+ARG BASE_IMAGE=ubuntu:22.04
+
+FROM ${BASE_IMAGE} AS builder
+ARG BACKEND=rerankers
+ARG BUILD_TYPE
+ENV BUILD_TYPE=${BUILD_TYPE}
+ARG CUDA_MAJOR_VERSION
+ARG CUDA_MINOR_VERSION
+ARG SKIP_DRIVERS=false
+ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
+ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
+ENV DEBIAN_FRONTEND=noninteractive
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        ccache \
+        ca-certificates \
+        espeak-ng \
+        curl \
+        libssl-dev \
+        git \
+        git-lfs \
+        unzip clang \
+        upx-ucl \
+        curl python3-pip \
+        python-is-python3 \
+        python3-dev llvm \
+        python3-venv make && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/* && \
+    pip install --upgrade pip
+
+
+# Cuda
+ENV PATH=/usr/local/cuda/bin:${PATH}
+
+# HipBLAS requirements
+ENV PATH=/opt/rocm/bin:${PATH}
+
+# Vulkan requirements
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
+        apt-get update && \
+        apt-get install -y  --no-install-recommends \
+            software-properties-common pciutils wget gpg-agent && \
+        wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
+        wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
+        apt-get update && \
+        apt-get install -y \
+            vulkan-sdk && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# CuBLAS requirements
+RUN <<EOT bash
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
+        apt-get update && \
+        apt-get install -y  --no-install-recommends \
+            software-properties-common pciutils
+        if [ "amd64" = "$TARGETARCH" ]; then
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
+        fi
+        if [ "arm64" = "$TARGETARCH" ]; then
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
+        fi
+        dpkg -i cuda-keyring_1.1-1_all.deb && \
+        rm -f cuda-keyring_1.1-1_all.deb && \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/*
+    fi
+EOT
+
+# If we are building with clblas support, we need the libraries for the builds
+RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            libclblast-dev && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/* \
+    ; fi
+
+RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            hipblas-dev \
+            rocblas-dev && \
+        apt-get clean && \
+        rm -rf /var/lib/apt/lists/* && \
+        # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
+        # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
+        ldconfig \
+    ; fi
+# Install uv as a system package
+RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
+ENV PATH="/root/.cargo/bin:${PATH}"
+
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
+
+# Install grpcio-tools (the version in 22.04 is too old)
+RUN pip install --user grpcio-tools==1.71.0 grpcio==1.71.0
+
+COPY python/${BACKEND} /${BACKEND}
+COPY backend.proto /${BACKEND}/backend.proto
+COPY python/common/ /${BACKEND}/common
+
+RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
+
+FROM scratch
+ARG BACKEND=rerankers
+COPY --from=builder /${BACKEND}/ /

backend/README.md

@@ -0,0 +1,213 @@
+# LocalAI Backend Architecture
+
+This directory contains the core backend infrastructure for LocalAI, including the gRPC protocol definition, multi-language Dockerfiles, and language-specific backend implementations.
+
+## Overview
+
+LocalAI uses a unified gRPC-based architecture that allows different programming languages to implement AI backends while maintaining consistent interfaces and capabilities. The backend system supports multiple hardware acceleration targets and provides a standardized way to integrate various AI models and frameworks.
+
+## Architecture Components
+
+### 1. Protocol Definition (`backend.proto`)
+
+The `backend.proto` file defines the gRPC service interface that all backends must implement. This ensures consistency across different language implementations and provides a contract for communication between LocalAI core and backend services.
+
+#### Core Services
+
+- **Text Generation**: `Predict`, `PredictStream` for LLM inference
+- **Embeddings**: `Embedding` for text vectorization
+- **Image Generation**: `GenerateImage` for stable diffusion and image models
+- **Audio Processing**: `AudioTranscription`, `TTS`, `SoundGeneration`
+- **Video Generation**: `GenerateVideo` for video synthesis
+- **Object Detection**: `Detect` for computer vision tasks
+- **Vector Storage**: `StoresSet`, `StoresGet`, `StoresFind` for RAG operations
+- **Reranking**: `Rerank` for document relevance scoring
+- **Voice Activity Detection**: `VAD` for audio segmentation
+
+#### Key Message Types
+
+- **`PredictOptions`**: Comprehensive configuration for text generation
+- **`ModelOptions`**: Model loading and configuration parameters
+- **`Result`**: Standardized response format
+- **`StatusResponse`**: Backend health and memory usage information
+
+### 2. Multi-Language Dockerfiles
+
+The backend system provides language-specific Dockerfiles that handle the build environment and dependencies for different programming languages:
+
+- `Dockerfile.python`
+- `Dockerfile.golang`
+- `Dockerfile.llama-cpp`
+
+### 3. Language-Specific Implementations
+
+#### Python Backends (`python/`)
+- **transformers**: Hugging Face Transformers framework
+- **vllm**: High-performance LLM inference
+- **mlx**: Apple Silicon optimization
+- **diffusers**: Stable Diffusion models
+- **Audio**: bark, coqui, faster-whisper, kitten-tts
+- **Vision**: mlx-vlm, rfdetr
+- **Specialized**: rerankers, chatterbox, kokoro
+
+#### Go Backends (`go/`)
+- **whisper**: OpenAI Whisper speech recognition in Go with GGML cpp backend (whisper.cpp)
+- **stablediffusion-ggml**: Stable Diffusion in Go with GGML Cpp backend
+- **huggingface**: Hugging Face model integration
+- **piper**: Text-to-speech synthesis Golang with C bindings using rhaspy/piper
+- **bark-cpp**: Bark TTS models Golang with Cpp bindings
+- **local-store**: Vector storage backend
+
+#### C++ Backends (`cpp/`)
+- **llama-cpp**: Llama.cpp integration
+- **grpc**: GRPC utilities and helpers
+
+## Hardware Acceleration Support
+
+### CUDA (NVIDIA)
+- **Versions**: CUDA 11.x, 12.x
+- **Features**: cuBLAS, cuDNN, TensorRT optimization
+- **Targets**: x86_64, ARM64 (Jetson)
+
+### ROCm (AMD)
+- **Features**: HIP, rocBLAS, MIOpen
+- **Targets**: AMD GPUs with ROCm support
+
+### Intel
+- **Features**: oneAPI, Intel Extension for PyTorch
+- **Targets**: Intel GPUs, XPUs, CPUs
+
+### Vulkan
+- **Features**: Cross-platform GPU acceleration
+- **Targets**: Windows, Linux, Android, macOS
+
+### Apple Silicon
+- **Features**: MLX framework, Metal Performance Shaders
+- **Targets**: M1/M2/M3 Macs
+
+## Backend Registry (`index.yaml`)
+
+The `index.yaml` file serves as a central registry for all available backends, providing:
+
+- **Metadata**: Name, description, license, icons
+- **Capabilities**: Hardware targets and optimization profiles
+- **Tags**: Categorization for discovery
+- **URLs**: Source code and documentation links
+
+## Building Backends
+
+### Prerequisites
+- Docker with multi-architecture support
+- Appropriate hardware drivers (CUDA, ROCm, etc.)
+- Build tools (make, cmake, compilers)
+
+### Build Commands
+
+Example of build commands with Docker
+
+```bash
+# Build Python backend
+docker build -f backend/Dockerfile.python \
+  --build-arg BACKEND=transformers \
+  --build-arg BUILD_TYPE=cublas12 \
+  --build-arg CUDA_MAJOR_VERSION=12 \
+  --build-arg CUDA_MINOR_VERSION=8 \
+  -t localai-backend-transformers .
+
+# Build Go backend
+docker build -f backend/Dockerfile.golang \
+  --build-arg BACKEND=whisper \
+  --build-arg BUILD_TYPE=cpu \
+  -t localai-backend-whisper .
+
+# Build C++ backend
+docker build -f backend/Dockerfile.llama-cpp \
+  --build-arg BACKEND=llama-cpp \
+  --build-arg BUILD_TYPE=cublas12 \
+  -t localai-backend-llama-cpp .
+```
+
+For ARM64/Mac builds, docker can't be used, and the makefile in the respective backend has to be used.
+
+### Build Types
+
+- **`cpu`**: CPU-only optimization
+- **`cublas11`**: CUDA 11.x with cuBLAS
+- **`cublas12`**: CUDA 12.x with cuBLAS
+- **`hipblas`**: ROCm with rocBLAS
+- **`intel`**: Intel oneAPI optimization
+- **`vulkan`**: Vulkan-based acceleration
+- **`metal`**: Apple Metal optimization
+
+## Backend Development
+
+### Creating a New Backend
+
+1. **Choose Language**: Select Python, Go, or C++ based on requirements
+2. **Implement Interface**: Implement the gRPC service defined in `backend.proto`
+3. **Add Dependencies**: Create appropriate requirements files
+4. **Configure Build**: Set up Dockerfile and build scripts
+5. **Register Backend**: Add entry to `index.yaml`
+6. **Test Integration**: Verify gRPC communication and functionality
+
+### Backend Structure
+
+```
+backend-name/
+├── backend.py/go/cpp    # Main implementation
+├── requirements.txt      # Dependencies
+├── Dockerfile           # Build configuration
+├── install.sh           # Installation script
+├── run.sh              # Execution script
+├── test.sh             # Test script
+└── README.md           # Backend documentation
+```
+
+### Required gRPC Methods
+
+At minimum, backends must implement:
+- `Health()` - Service health check
+- `LoadModel()` - Model loading and initialization
+- `Predict()` - Main inference endpoint
+- `Status()` - Backend status and metrics
+
+## Integration with LocalAI Core
+
+Backends communicate with LocalAI core through gRPC:
+
+1. **Service Discovery**: Core discovers available backends
+2. **Model Loading**: Core requests model loading via `LoadModel`
+3. **Inference**: Core sends requests via `Predict` or specialized endpoints
+4. **Streaming**: Core handles streaming responses for real-time generation
+5. **Monitoring**: Core tracks backend health and performance
+
+## Performance Optimization
+
+### Memory Management
+- **Model Caching**: Efficient model loading and caching
+- **Batch Processing**: Optimize for multiple concurrent requests
+- **Memory Pinning**: GPU memory optimization for CUDA/ROCm
+
+### Hardware Utilization
+- **Multi-GPU**: Support for tensor parallelism
+- **Mixed Precision**: FP16/BF16 for memory efficiency
+- **Kernel Fusion**: Optimized CUDA/ROCm kernels
+
+## Troubleshooting
+
+### Common Issues
+
+1. **GRPC Connection**: Verify backend service is running and accessible
+2. **Model Loading**: Check model paths and dependencies
+3. **Hardware Detection**: Ensure appropriate drivers and libraries
+4. **Memory Issues**: Monitor GPU memory usage and model sizes
+
+## Contributing
+
+When contributing to the backend system:
+
+1. **Follow Protocol**: Implement the exact gRPC interface
+2. **Add Tests**: Include comprehensive test coverage
+3. **Document**: Provide clear usage examples
+4. **Optimize**: Consider performance and resource usage
+5. **Validate**: Test across different hardware targets

backend/backend.proto

@@ -20,6 +20,7 @@ service Backend {
   rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
   rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
   rpc Status(HealthMessage) returns (StatusResponse) {}
+  rpc Detect(DetectOptions) returns (DetectResponse) {}
 
   rpc StoresSet(StoresSetOptions) returns (Result) {}
   rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
@@ -162,6 +163,7 @@ message Reply {
   int32 prompt_tokens = 3;
   double timing_prompt_processing = 4;
   double timing_token_generation = 5;
+  bytes audio = 6;
 }
 
 message GrammarTrigger {
@@ -184,7 +186,6 @@ message ModelOptions {
   string MainGPU = 13;
   string TensorSplit = 14;
   int32 Threads = 15;
-  string LibrarySearchPath = 16;
   float RopeFreqBase = 17;
   float RopeFreqScale = 18;
   float RMSNormEps = 19;
@@ -241,7 +242,7 @@ message ModelOptions {
 
   string Type = 49;
 
-  bool FlashAttention = 56;
+  string FlashAttention = 56;
   bool NoKVOffload = 57;
 
   string ModelPath = 59;
@@ -255,6 +256,10 @@ message ModelOptions {
   string CacheTypeValue = 64;
 
   repeated GrammarTrigger GrammarTriggers = 65;
+
+  bool Reranking = 71;
+
+  repeated string Overrides = 72;
 }
 
 message Result {
@@ -271,6 +276,7 @@ message TranscriptRequest {
   string language = 3;
   uint32 threads = 4;
   bool translate = 5;
+  bool diarize = 6;
 }
 
 message TranscriptResult {
@@ -300,19 +306,24 @@ message GenerateImageRequest {
   // Diffusers
   string EnableParameters = 10;
   int32 CLIPSkip = 11;
+
+  // Reference images for models that support them (e.g., Flux Kontext)
+  repeated string ref_images = 12;
 }
 
 message GenerateVideoRequest {
   string prompt = 1;
-  string start_image = 2;  // Path or base64 encoded image for the start frame
+  string negative_prompt = 2;  // Negative prompt for video generation
-  string end_image = 3;    // Path or base64 encoded image for the end frame
+  string start_image = 3;  // Path or base64 encoded image for the start frame
-  int32 width = 4;
+  string end_image = 4;    // Path or base64 encoded image for the end frame
-  int32 height = 5;
+  int32 width = 5;
-  int32 num_frames = 6;    // Number of frames to generate
+  int32 height = 6;
-  int32 fps = 7;          // Frames per second
+  int32 num_frames = 7;    // Number of frames to generate
-  int32 seed = 8;
+  int32 fps = 8;          // Frames per second
-  float cfg_scale = 9;    // Classifier-free guidance scale
+  int32 seed = 9;
-  string dst = 10;        // Output path for the generated video
+  float cfg_scale = 10;    // Classifier-free guidance scale
+  int32 step = 11;         // Number of inference steps
+  string dst = 12;        // Output path for the generated video
 }
 
 message TTSRequest {
@@ -372,3 +383,20 @@ message Message {
   string role = 1;
   string content = 2;
 }
+
+message DetectOptions {
+  string src = 1;
+}
+
+message Detection {
+  float x = 1;
+  float y = 2;
+  float width = 3;
+  float height = 4;
+  float confidence = 5;
+  string class_name = 6;
+}
+
+message DetectResponse {
+  repeated Detection Detections = 1;
+}

backend/cpp/llama-cpp/CMakeLists.txt

@@ -1,20 +1,3 @@
-
-## XXX: In some versions of CMake clip wasn't being built before llama.
-## This is an hack for now, but it should be fixed in the future.
-# set(TARGET myclip)
-# add_library(${TARGET} clip.cpp clip.h clip-impl.h llava.cpp llava.h)
-# install(TARGETS ${TARGET} LIBRARY)
-# target_include_directories(myclip PUBLIC .)
-# target_include_directories(myclip PUBLIC ../..)
-# target_include_directories(myclip PUBLIC ../../common)
-# target_link_libraries(${TARGET} PRIVATE common ggml llama ${CMAKE_THREAD_LIBS_INIT})
-# target_compile_features(${TARGET} PRIVATE cxx_std_11)
-# if (NOT MSVC)
-#     target_compile_options(${TARGET} PRIVATE -Wno-cast-qual) # stb_image.h
-# endif()
-# END CLIP hack
-
-
 set(TARGET grpc-server)
 set(CMAKE_CXX_STANDARD 17)
 cmake_minimum_required(VERSION 3.15)
@@ -74,7 +57,7 @@ add_library(hw_grpc_proto
   ${hw_proto_srcs}
   ${hw_proto_hdrs} )
 
-add_executable(${TARGET} grpc-server.cpp utils.hpp json.hpp)
+add_executable(${TARGET} grpc-server.cpp utils.hpp json.hpp httplib.h)
 
 target_include_directories(${TARGET} PRIVATE ../llava)
 target_include_directories(${TARGET} PRIVATE ${CMAKE_SOURCE_DIR})

backend/cpp/llama-cpp/Makefile

@@ -0,0 +1,166 @@
+
+LLAMA_VERSION?=fe4eb4f8ec25a1239b0923f1c7f87adf5730c3e5
+LLAMA_REPO?=https://github.com/JohannesGaessler/llama.cpp
+
+CMAKE_ARGS?=
+BUILD_TYPE?=
+NATIVE?=false
+ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
+TARGET?=--target grpc-server
+JOBS?=$(shell nproc)
+
+# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
+CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF -DLLAMA_CURL=OFF
+
+CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
+ifeq ($(NATIVE),false)
+	CMAKE_ARGS+=-DGGML_NATIVE=OFF
+endif
+# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
+ifeq ($(BUILD_TYPE),cublas)
+	CMAKE_ARGS+=-DGGML_CUDA=ON
+# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
+# to CMAKE_ARGS automatically
+else ifeq ($(BUILD_TYPE),openblas)
+	CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
+# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
+else ifeq ($(BUILD_TYPE),clblas)
+	CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
+# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
+else ifeq ($(BUILD_TYPE),hipblas)
+	ROCM_HOME ?= /opt/rocm
+	ROCM_PATH ?= /opt/rocm
+	export CXX=$(ROCM_HOME)/llvm/bin/clang++
+	export CC=$(ROCM_HOME)/llvm/bin/clang
+	AMDGPU_TARGETS?=gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201
+	CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
+else ifeq ($(BUILD_TYPE),vulkan)
+	CMAKE_ARGS+=-DGGML_VULKAN=1
+else ifeq ($(OS),Darwin)
+	ifeq ($(BUILD_TYPE),)
+		BUILD_TYPE=metal
+	endif
+	ifneq ($(BUILD_TYPE),metal)
+		CMAKE_ARGS+=-DGGML_METAL=OFF
+	else
+		CMAKE_ARGS+=-DGGML_METAL=ON
+		CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
+		CMAKE_ARGS+=-DGGML_METAL_USE_BF16=ON
+		CMAKE_ARGS+=-DGGML_OPENMP=OFF
+	endif
+	TARGET+=--target ggml-metal
+endif
+
+ifeq ($(BUILD_TYPE),sycl_f16)
+	CMAKE_ARGS+=-DGGML_SYCL=ON \
+		-DCMAKE_C_COMPILER=icx \
+		-DCMAKE_CXX_COMPILER=icpx \
+		-DCMAKE_CXX_FLAGS="-fsycl" \
+		-DGGML_SYCL_F16=ON
+endif
+
+ifeq ($(BUILD_TYPE),sycl_f32)
+	CMAKE_ARGS+=-DGGML_SYCL=ON \
+		-DCMAKE_C_COMPILER=icx \
+		-DCMAKE_CXX_COMPILER=icpx \
+		-DCMAKE_CXX_FLAGS="-fsycl"
+endif
+
+INSTALLED_PACKAGES=$(CURDIR)/../grpc/installed_packages
+INSTALLED_LIB_CMAKE=$(INSTALLED_PACKAGES)/lib/cmake
+ADDED_CMAKE_ARGS=-Dabsl_DIR=${INSTALLED_LIB_CMAKE}/absl \
+				 -DProtobuf_DIR=${INSTALLED_LIB_CMAKE}/protobuf \
+				 -Dutf8_range_DIR=${INSTALLED_LIB_CMAKE}/utf8_range \
+				 -DgRPC_DIR=${INSTALLED_LIB_CMAKE}/grpc \
+				 -DCMAKE_CXX_STANDARD_INCLUDE_DIRECTORIES=${INSTALLED_PACKAGES}/include
+build-llama-cpp-grpc-server:
+# Conditionally build grpc for the llama backend to use if needed
+ifdef BUILD_GRPC_FOR_BACKEND_LLAMA
+	$(MAKE) -C ../../grpc build
+	_PROTOBUF_PROTOC=${INSTALLED_PACKAGES}/bin/proto \
+	_GRPC_CPP_PLUGIN_EXECUTABLE=${INSTALLED_PACKAGES}/bin/grpc_cpp_plugin \
+	PATH="${INSTALLED_PACKAGES}/bin:${PATH}" \
+	CMAKE_ARGS="${CMAKE_ARGS} ${ADDED_CMAKE_ARGS}" \
+	LLAMA_VERSION=$(LLAMA_VERSION) \
+	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../$(VARIANT) grpc-server
+else
+	echo "BUILD_GRPC_FOR_BACKEND_LLAMA is not defined."
+	LLAMA_VERSION=$(LLAMA_VERSION) $(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../$(VARIANT) grpc-server
+endif
+
+llama-cpp-avx2: llama.cpp
+	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build
+	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build purge
+	$(info ${GREEN}I llama-cpp build info:avx2${RESET})
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-cpp-avx2-build" build-llama-cpp-grpc-server
+	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build/grpc-server llama-cpp-avx2
+
+llama-cpp-avx512: llama.cpp
+	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build
+	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build purge
+	$(info ${GREEN}I llama-cpp build info:avx512${RESET})
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=on -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-cpp-avx512-build" build-llama-cpp-grpc-server
+	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build/grpc-server llama-cpp-avx512
+
+llama-cpp-avx: llama.cpp
+	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build
+	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build purge
+	$(info ${GREEN}I llama-cpp build info:avx${RESET})
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-cpp-avx-build" build-llama-cpp-grpc-server
+	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build/grpc-server llama-cpp-avx
+
+llama-cpp-fallback: llama.cpp
+	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build
+	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build purge
+	$(info ${GREEN}I llama-cpp build info:fallback${RESET})
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-cpp-fallback-build" build-llama-cpp-grpc-server
+	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build/grpc-server llama-cpp-fallback
+
+llama-cpp-grpc: llama.cpp
+	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build
+	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build purge
+	$(info ${GREEN}I llama-cpp build info:grpc${RESET})
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" TARGET="--target grpc-server --target rpc-server" $(MAKE) VARIANT="llama-cpp-grpc-build" build-llama-cpp-grpc-server
+	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/grpc-server llama-cpp-grpc
+
+llama-cpp-rpc-server: llama-cpp-grpc
+	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/llama.cpp/build/bin/rpc-server llama-cpp-rpc-server
+
+llama.cpp:
+	mkdir -p llama.cpp
+	cd llama.cpp && \
+	git init && \
+	git remote add origin $(LLAMA_REPO)  && \
+	git fetch origin && \
+	git checkout -b build $(LLAMA_VERSION) && \
+	git submodule update --init --recursive --depth 1 --single-branch
+
+llama.cpp/tools/grpc-server: llama.cpp
+	mkdir -p llama.cpp/tools/grpc-server
+	bash prepare.sh
+
+rebuild:
+	bash prepare.sh
+	rm -rf grpc-server
+	$(MAKE) grpc-server
+
+package:
+	bash package.sh
+
+purge:
+	rm -rf llama.cpp/build
+	rm -rf llama.cpp/tools/grpc-server
+	rm -rf grpc-server
+
+clean: purge
+	rm -rf llama.cpp
+
+grpc-server: llama.cpp llama.cpp/tools/grpc-server
+	@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
+ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+	+bash -c "source $(ONEAPI_VARS); \
+	cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)"
+else
+	+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)
+endif
+	cp llama.cpp/build/bin/grpc-server .

backend/cpp/llama-cpp/grpc-server.cpp

@@ -0,0 +1,978 @@
+// llama.cpp gRPC C++ backend server
+//
+// Ettore Di Giacinto <mudler@localai.io> and llama.cpp authors
+//
+// This is a gRPC server for llama.cpp compatible with the LocalAI proto
+// Note: this is a re-adaptation of the original llama.cpp example/server.cpp for HTTP (https://github.com/ggerganov/llama.cpp/tree/master/examples/server), 
+// but modified to work with gRPC
+//
+
+#include "server.cpp"
+// LocalAI
+
+#include "backend.pb.h"
+#include "backend.grpc.pb.h"
+#include "common.h"
+#include <getopt.h>
+#include <grpcpp/ext/proto_server_reflection_plugin.h>
+#include <grpcpp/grpcpp.h>
+#include <grpcpp/health_check_service_interface.h>
+#include <regex>
+
+
+using grpc::Server;
+using grpc::ServerBuilder;
+using grpc::ServerContext;
+using grpc::Status;
+// END LocalAI
+
+
+
+
+/////////////////////////////////
+////////////////////////////////
+//////// LOCALAI code starts below here
+/////////////////////////////////
+////////////////////////////////
+
+bool loaded_model; // TODO: add a mutex for this, but happens only once loading the model
+
+static void start_llama_server(server_context& ctx_server) {
+
+    LOG_INF("%s: starting llama server\n", __func__);
+
+    LOG_INF("%s: waiting for model to be loaded\n", __func__);
+    // Wait for model to be loaded first
+    while (!loaded_model) {
+        std::this_thread::sleep_for(std::chrono::milliseconds(100));
+    }
+
+    ctx_server.init();
+    //state.store(SERVER_STATE_READY);
+
+    LOG_INF("%s: model loaded\n", __func__);
+
+    // print sample chat example to make it clear which template is used
+    // LOG_INF("%s: chat template, chat_template: %s, example_format: '%s'\n", __func__,
+    //     common_chat_templates_source(ctx_server.chat_templates.get()),
+    //     common_chat_format_example(ctx_server.chat_templates.get(), ctx_server.params_base.use_jinja).c_str(), ctx_server.params_base.default_template_kwargs);
+
+    // Reset the chat templates
+    // TODO: We should make this configurable by respecting the option that is already present in LocalAI for vLLM
+    ctx_server.chat_templates.reset();
+
+    ctx_server.queue_tasks.on_new_task([&ctx_server](server_task && task) {
+        ctx_server.process_single_task(std::move(task));
+    });
+
+    ctx_server.queue_tasks.on_update_slots([&ctx_server]() {
+        ctx_server.update_slots();
+    });
+
+    shutdown_handler = [&](int) {
+        // this will unblock start_loop()
+        ctx_server.queue_tasks.terminate();
+    };
+
+#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
+    struct sigaction sigint_action;
+    sigint_action.sa_handler = signal_handler;
+    sigemptyset (&sigint_action.sa_mask);
+    sigint_action.sa_flags = 0;
+    sigaction(SIGINT, &sigint_action, NULL);
+    sigaction(SIGTERM, &sigint_action, NULL);
+#elif defined (_WIN32)
+    auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
+        return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
+    };
+    SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
+#endif
+
+    // this call blocks the main thread until queue_tasks.terminate() is called
+    ctx_server.queue_tasks.start_loop();
+}
+
+json parse_options(bool streaming, const backend::PredictOptions* predict)
+{
+    
+    // Create now a json data from the prediction options instead
+    //
+    json data;
+    data["stream"] = streaming;
+    data["cache_prompt"] = predict->promptcacheall();
+    data["n_predict"] = predict->tokens() == 0 ? -1 : predict->tokens();
+    data["top_k"] = predict->topk();
+    data["top_p"] = predict->topp();
+    data["typical_p"] = predict->typicalp();
+    data["temperature"] = predict->temperature();
+    data["repeat_last_n"] = predict->repeat();
+    data["repeat_penalty"] = predict->penalty();
+    data["frequency_penalty"] = predict->frequencypenalty();
+    data["presence_penalty"] = predict->presencepenalty();
+    data["mirostat"] = predict->mirostat();
+    data["mirostat_tau"] = predict->mirostattau();
+    data["mirostat_eta"] = predict->mirostateta();
+    data["n_keep"] = predict->nkeep();
+    data["seed"] = predict->seed();
+    data["grammar"] = predict->grammar();
+    data["prompt"] = predict->prompt();
+    data["ignore_eos"] = predict->ignoreeos();
+    data["embeddings"] = predict->embeddings();
+    // TODO: add back json_schema and let this be controlled by the user
+    // data["json_schema"] = predict->jsonschema();
+
+    // Add the correlationid to json data
+    data["correlation_id"] = predict->correlationid();
+
+    // for each image in the request, add the image data
+    //
+    for (int i = 0; i < predict->images_size(); i++) {
+        data["image_data"].push_back(json
+            {
+                {"id", i},
+                {"data",    predict->images(i)},
+            });
+    }
+
+    // for each audio in the request, add the audio data
+    for (int i = 0; i < predict->audios_size(); i++) {
+        data["audio_data"].push_back(json
+            {
+                {"id", i},
+                {"data",    predict->audios(i)},
+            });
+    }
+
+    data["stop"] = predict->stopprompts();
+    // data["n_probs"] = predict->nprobs();
+    //TODO: images,
+
+    return data;
+}
+
+
+const std::vector<ggml_type> kv_cache_types = {
+    GGML_TYPE_F32,
+    GGML_TYPE_F16,
+    GGML_TYPE_BF16,
+    GGML_TYPE_Q8_0,
+    GGML_TYPE_Q4_0,
+    GGML_TYPE_Q4_1,
+    GGML_TYPE_IQ4_NL,
+    GGML_TYPE_Q5_0,
+    GGML_TYPE_Q5_1,
+};
+
+static ggml_type kv_cache_type_from_str(const std::string & s) {
+    for (const auto & type : kv_cache_types) {
+        if (ggml_type_name(type) == s) {
+            return type;
+        }
+    }
+    throw std::runtime_error("Unsupported cache type: " + s);
+}
+
+static std::string get_all_kv_cache_types() {
+    std::ostringstream msg;
+    for (const auto & type : kv_cache_types) {
+        msg << ggml_type_name(type) << (&type == &kv_cache_types.back() ? "" : ", ");
+    }
+    return msg.str();
+}
+
+
+// Adds an RPC server
+// https://github.com/ggerganov/llama.cpp/compare/4dbc8b9cb71876e005724f4e8f73a3544646bcf5..3edfa7d3753c29e44b964c0ff424d2ea8d5fdee6
+static void add_rpc_devices(std::string servers) {
+    auto rpc_servers = string_split<std::string>(servers, ',');
+    if (rpc_servers.empty()) {
+        throw std::invalid_argument("no RPC servers specified");
+    }
+    ggml_backend_reg_t rpc_reg = ggml_backend_reg_by_name("RPC");
+    if (!rpc_reg) {
+        throw std::invalid_argument("failed to find RPC backend");
+    }
+    typedef ggml_backend_dev_t (*ggml_backend_rpc_add_device_t)(const char * endpoint);
+    ggml_backend_rpc_add_device_t ggml_backend_rpc_add_device_fn = (ggml_backend_rpc_add_device_t) ggml_backend_reg_get_proc_address(rpc_reg, "ggml_backend_rpc_add_device");
+    if (!ggml_backend_rpc_add_device_fn) {
+        throw std::invalid_argument("failed to find RPC device add function");
+    }
+    for (const auto & server : rpc_servers) {
+        ggml_backend_dev_t dev = ggml_backend_rpc_add_device_fn(server.c_str());
+        if (dev) {
+            ggml_backend_device_register(dev);
+        } else {
+            throw std::invalid_argument("failed to register RPC device");
+        }
+    }
+}
+
+static void params_parse(const backend::ModelOptions* request,
+                                common_params & params) {
+   
+    // this is comparable to: https://github.com/ggerganov/llama.cpp/blob/d9b33fe95bd257b36c84ee5769cc048230067d6f/examples/server/server.cpp#L1809
+
+    params.model.path = request->modelfile();
+    if (!request->mmproj().empty()) {
+    // get the directory of modelfile
+      std::string model_dir = params.model.path.substr(0, params.model.path.find_last_of("/\\"));
+      params.mmproj.path = model_dir + "/"+ request->mmproj();
+    }
+    //  params.model_alias ??
+    params.model_alias =  request->modelfile();
+    if (!request->cachetypekey().empty()) {
+        params.cache_type_k = kv_cache_type_from_str(request->cachetypekey());
+    }
+    if (!request->cachetypevalue().empty()) {
+        params.cache_type_v = kv_cache_type_from_str(request->cachetypevalue());
+    }
+    params.n_ctx = request->contextsize();
+    //params.memory_f16 = request->f16memory();
+    params.cpuparams.n_threads = request->threads();
+    params.n_gpu_layers = request->ngpulayers();
+    params.n_batch = request->nbatch();
+    // Set params.n_parallel by environment variable (LLAMA_PARALLEL), defaults to 1
+    //params.n_parallel = 1;
+    const char *env_parallel = std::getenv("LLAMACPP_PARALLEL");
+    if (env_parallel != NULL) {
+        params.n_parallel = std::stoi(env_parallel);
+        params.cont_batching = true;
+    } else {
+        params.n_parallel = 1;
+    }
+
+
+    const char *llama_grpc_servers = std::getenv("LLAMACPP_GRPC_SERVERS");
+    if (llama_grpc_servers != NULL) {
+        add_rpc_devices(std::string(llama_grpc_servers));
+    }
+    
+     // decode options. Options are in form optname:optvale, or if booleans only optname.
+    for (int i = 0; i < request->options_size(); i++) {
+        std::string opt = request->options(i);
+        char *optname = strtok(&opt[0], ":");
+        char *optval = strtok(NULL, ":");
+        if (optval == NULL) {
+            optval = "true";
+        }
+
+        if (!strcmp(optname, "gpu")) {
+          //  llama.has_gpu = true;
+        }
+    }
+
+    // Add kv_overrides
+    if (request->overrides_size() > 0) {
+        for (int i = 0; i < request->overrides_size(); i++) {
+            string_parse_kv_override(request->overrides(i).c_str(), params.kv_overrides);
+        }
+    }
+
+    // TODO: Add yarn
+
+    if (!request->tensorsplit().empty()) {
+        std::string arg_next = request->tensorsplit();
+
+        // split string by , and /
+        const std::regex regex{ R"([,/]+)" };
+        std::sregex_token_iterator it{ arg_next.begin(), arg_next.end(), regex, -1 };
+        std::vector<std::string> split_arg{ it, {} };
+
+        GGML_ASSERT(split_arg.size() <= llama_max_devices());
+
+        for (size_t i_device = 0; i_device < llama_max_devices(); ++i_device) {
+            if (i_device < split_arg.size()) {
+                params.tensor_split[i_device] = std::stof(split_arg[i_device]);
+            }
+            else {
+                params.tensor_split[i_device] = 0.0f;
+            }
+        }
+    }
+
+    if (!request->maingpu().empty()) {
+        params.main_gpu = std::stoi(request->maingpu());
+    }
+    if (!request->loraadapter().empty() && !request->lorabase().empty()) {
+     float scale_factor = 1.0f;
+     if (request->lorascale() != 0.0f) {
+        scale_factor = request->lorascale();
+     }
+     // get the directory of modelfile
+     std::string model_dir = params.model.path.substr(0, params.model.path.find_last_of("/\\"));
+     params.lora_adapters.push_back({ model_dir + "/"+request->loraadapter(), scale_factor });
+    }
+    params.use_mlock = request->mlock();
+    params.use_mmap = request->mmap();
+
+    if (request->flashattention() == "on" || request->flashattention() == "enabled") {
+        params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_ENABLED;
+    } else if (request->flashattention() == "off" || request->flashattention() == "disabled") {
+        params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_DISABLED;
+    } else if (request->flashattention() == "auto") {
+        params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_AUTO;
+    }
+
+    params.no_kv_offload = request->nokvoffload();
+    params.ctx_shift = false; // We control context-shifting in any case (and we disable it as it could just lead to infinite loops)
+
+    params.embedding = request->embeddings() || request->reranking();
+    if (request->reranking()) {
+        params.pooling_type = LLAMA_POOLING_TYPE_RANK;
+    }
+
+    
+    if (request->ropescaling() == "none")   { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_NONE; }
+    else if (request->ropescaling() == "yarn")   { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_YARN; }
+    else if (request->ropescaling() == "linear")   {  params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_LINEAR; }
+
+    if ( request->yarnextfactor() != 0.0f ) {
+        params.yarn_ext_factor = request->yarnextfactor();
+    }
+    if ( request->yarnattnfactor() != 0.0f ) {
+        params.yarn_attn_factor = request->yarnattnfactor();
+    }
+    if ( request->yarnbetafast() != 0.0f ) {
+        params.yarn_beta_fast = request->yarnbetafast();
+    }
+    if ( request->yarnbetaslow() != 0.0f ) {
+        params.yarn_beta_slow = request->yarnbetaslow();
+    }
+    if ( request->ropefreqbase() != 0.0f ) {
+        params.rope_freq_base = request->ropefreqbase();
+    }
+    if ( request->ropefreqscale() != 0.0f ) {
+        params.rope_freq_scale = request->ropefreqscale();
+    }
+
+    if (request->grammartriggers_size() > 0) {
+        params.sampling.grammar_lazy = true;
+        for (int i = 0; i < request->grammartriggers_size(); i++) {
+            common_grammar_trigger trigger;
+	    trigger.type = COMMON_GRAMMAR_TRIGGER_TYPE_WORD;
+            trigger.value = request->grammartriggers(i).word();
+	    // trigger.at_start = request->grammartriggers(i).at_start();
+            params.sampling.grammar_triggers.push_back(trigger);
+           
+        }
+    }
+}
+
+
+// GRPC Server start
+class BackendServiceImpl final : public backend::Backend::Service {
+private:
+    server_context& ctx_server;
+
+public:
+    BackendServiceImpl(server_context& ctx) : ctx_server(ctx) {}
+
+    grpc::Status Health(ServerContext* context, const backend::HealthMessage* request, backend::Reply* reply) {
+        // Implement Health RPC
+        reply->set_message("OK");
+        return Status::OK;
+    }
+
+    grpc::Status LoadModel(ServerContext* context, const backend::ModelOptions* request, backend::Result* result) {
+        // Implement LoadModel RPC
+        common_params params;
+        params_parse(request, params);
+
+        common_init();
+
+        llama_backend_init();
+        llama_numa_init(params.numa);
+
+
+        LOG_INF("system info: n_threads = %d, n_threads_batch = %d, total_threads = %d\n", params.cpuparams.n_threads, params.cpuparams_batch.n_threads, std::thread::hardware_concurrency());
+        LOG_INF("\n");
+        LOG_INF("%s\n", common_params_get_system_info(params).c_str());
+        LOG_INF("\n");
+        // load the model
+        if (!ctx_server.load_model(params)) {
+            result->set_message("Failed loading model");
+            result->set_success(false);
+            return Status::CANCELLED;
+        }
+
+        //ctx_server.init();
+        result->set_message("Loading succeeded");
+        result->set_success(true);
+        loaded_model = true;
+        ctx_server.slot_prompt_similarity = params.slot_prompt_similarity;
+
+        return Status::OK;
+    }
+
+    grpc::Status PredictStream(grpc::ServerContext* context, const backend::PredictOptions* request, grpc::ServerWriter<backend::Reply>* writer) override {
+        json data = parse_options(true, request);
+
+
+        //Raise error if embeddings is set to true
+        if (ctx_server.params_base.embedding) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "Embedding is not supported in streaming mode");
+        }
+
+
+        auto completion_id = gen_chatcmplid();
+        std::unordered_set<int> task_ids;
+        try {
+            std::vector<server_task> tasks;
+
+            const auto & prompt = data.at("prompt");
+            const auto type = SERVER_TASK_TYPE_COMPLETION;
+            // TODO: this log can become very long, put it behind a flag or think about a more compact format
+            //SRV_DBG("Prompt: %s\n", prompt.is_string() ? prompt.get<std::string>().c_str() : prompt.dump(2).c_str());
+
+            std::vector<raw_buffer> files;
+            const auto &images_data = data.find("image_data");
+            if (images_data != data.end() && images_data->is_array())
+            {
+                for (const auto &img : *images_data)
+                {
+                    auto decoded_data = base64_decode(img["data"].get<std::string>());
+                    files.push_back(decoded_data);
+                }
+            }
+
+            const auto &audio_data = data.find("audio_data");
+            if (audio_data != data.end() && audio_data->is_array())
+            {
+                for (const auto &audio : *audio_data)
+                {
+                    auto decoded_data = base64_decode(audio["data"].get<std::string>());
+                    files.push_back(decoded_data);
+                }
+            }
+
+            const bool has_mtmd = ctx_server.mctx != nullptr;
+
+            // process prompt
+            std::vector<server_tokens> inputs;
+            if (!prompt.is_string()) {
+                throw std::runtime_error("prompt must be a string");
+            }
+
+            if (has_mtmd) {
+                // multimodal
+                inputs.push_back(process_mtmd_prompt(ctx_server.mctx, prompt.get<std::string>(), files));
+            } else {
+                 // Everything else, including multimodal completions.
+                inputs = tokenize_input_prompts(ctx_server.vocab, ctx_server.mctx, prompt, true, true);
+            }
+
+            tasks.reserve(inputs.size());
+            for (size_t i = 0; i < inputs.size(); i++) {
+                server_task task = server_task(type);
+
+                task.id    = ctx_server.queue_tasks.get_new_id();
+                task.index = i;
+
+                task.prompt_tokens    = std::move(inputs[i]);
+                task.params           = server_task::params_from_json_cmpl(
+                        ctx_server.ctx,
+                        ctx_server.params_base,
+                        data);
+                task.id_selected_slot = json_value(data, "id_slot", -1);
+
+                // OAI-compat
+                task.params.oaicompat                 = OAICOMPAT_TYPE_NONE;
+                task.params.oaicompat_cmpl_id         = completion_id;
+                // oaicompat_model is already populated by params_from_json_cmpl
+
+                tasks.push_back(std::move(task));
+            }
+
+            task_ids = server_task::get_list_id(tasks);
+            ctx_server.queue_results.add_waiting_tasks(tasks);
+            ctx_server.queue_tasks.post(std::move(tasks));
+        } catch (const std::exception & e) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, e.what());
+        }
+
+        ctx_server.receive_cmpl_results_stream(task_ids, [&](server_task_result_ptr & result) -> bool {
+            json res_json = result->to_json();
+            if (res_json.is_array()) {
+                for (const auto & res : res_json) {
+                    std::string completion_text = res.value("content", "");
+
+                    backend::Reply reply;
+                    reply.set_message(completion_text);
+                    int32_t tokens_predicted = res.value("tokens_predicted", 0);
+                    reply.set_tokens(tokens_predicted);
+                    int32_t tokens_evaluated = res.value("tokens_evaluated", 0);
+                    reply.set_prompt_tokens(tokens_evaluated);
+
+                    if (res.contains("timings")) {
+                        double timing_prompt_processing = res.at("timings").value("prompt_ms", 0.0);
+                        reply.set_timing_prompt_processing(timing_prompt_processing);
+                        double timing_token_generation = res.at("timings").value("predicted_ms", 0.0);
+                        reply.set_timing_token_generation(timing_token_generation);
+                    }
+
+                    // Log Request Correlation Id
+                
+                    // Send the reply
+                    writer->Write(reply);
+                }
+            } else {
+                std::string completion_text = res_json.value("content", "");
+
+                backend::Reply reply;
+                reply.set_message(completion_text);
+                int32_t tokens_predicted = res_json.value("tokens_predicted", 0);
+                reply.set_tokens(tokens_predicted);
+                int32_t tokens_evaluated = res_json.value("tokens_evaluated", 0);
+                reply.set_prompt_tokens(tokens_evaluated);
+
+                if (res_json.contains("timings")) {
+                    double timing_prompt_processing = res_json.at("timings").value("prompt_ms", 0.0);
+                    reply.set_timing_prompt_processing(timing_prompt_processing);
+                    double timing_token_generation = res_json.at("timings").value("predicted_ms", 0.0);
+                    reply.set_timing_token_generation(timing_token_generation);
+                }
+
+                
+
+                // Send the reply
+                    writer->Write(reply);
+           
+            }
+                 return true;
+        }, [&](const json & error_data) {
+            backend::Reply reply;
+            reply.set_message(error_data.value("content", ""));
+            writer->Write(reply);
+            return true;
+        }, [&]() {
+            // NOTE: we should try to check when the writer is closed here
+            return false;
+        });
+
+        ctx_server.queue_results.remove_waiting_task_ids(task_ids);
+
+        return grpc::Status::OK;
+    }
+
+    grpc::Status Predict(ServerContext* context, const backend::PredictOptions* request, backend::Reply* reply) {
+         json data = parse_options(true, request);
+
+        data["stream"] = false;
+        //Raise error if embeddings is set to true
+        if (ctx_server.params_base.embedding) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "Embedding is not supported in Predict mode");
+        }
+        std::cout << "[PREDICT] Received result: " << data.dump(2) << std::endl;
+        auto completion_id = gen_chatcmplid();
+        std::unordered_set<int> task_ids;
+        try {
+            std::vector<server_task> tasks;
+
+            const auto & prompt = data.at("prompt");
+            const auto type = SERVER_TASK_TYPE_COMPLETION;
+            // TODO: this log can become very long, put it behind a flag or think about a more compact format
+            //SRV_DBG("Prompt: %s\n", prompt.is_string() ? prompt.get<std::string>().c_str() : prompt.dump(2).c_str());
+
+            std::vector<raw_buffer> files;
+            const auto &images_data = data.find("image_data");
+           // std::cout << "[PREDICT] Images data: " << images_data->dump(2) << std::endl;
+           
+            if (images_data != data.end() && images_data->is_array())
+            {
+                std::cout << "[PREDICT] Processing " << images_data->size() << " images" << std::endl;
+                for (const auto &img : *images_data)
+                {
+                    std::cout << "[PREDICT] Processing image" << std::endl;
+                    auto decoded_data = base64_decode(img["data"].get<std::string>());
+                    files.push_back(decoded_data);
+                }
+            }
+
+            const auto &audio_data = data.find("audio_data");
+            if (audio_data != data.end() && audio_data->is_array())
+            {
+                for (const auto &audio : *audio_data)
+                {
+                    auto decoded_data = base64_decode(audio["data"].get<std::string>());
+                    files.push_back(decoded_data);
+                }
+            }
+
+            // process files
+            const bool has_mtmd = ctx_server.mctx != nullptr;
+
+            // process prompt
+            std::vector<server_tokens> inputs;
+            if (!prompt.is_string()) {
+                std::cout << "[PREDICT] Prompt must be a string" << std::endl;
+                throw std::runtime_error("prompt must be a string");
+            }
+
+            if (has_mtmd) {
+                // multimodal
+                inputs.push_back(process_mtmd_prompt(ctx_server.mctx, prompt.get<std::string>(), files));
+            } else {
+                 // Everything else, including multimodal completions.
+                inputs = tokenize_input_prompts(ctx_server.vocab, ctx_server.mctx, prompt, true, true);
+            }
+
+            tasks.reserve(inputs.size());
+            for (size_t i = 0; i < inputs.size(); i++) {
+                server_task task = server_task(type);
+
+                task.id    = ctx_server.queue_tasks.get_new_id();
+                task.index = i;
+
+                task.prompt_tokens    = std::move(inputs[i]);
+                task.params           = server_task::params_from_json_cmpl(
+                        ctx_server.ctx,
+                        ctx_server.params_base,
+                        data);
+                task.id_selected_slot = json_value(data, "id_slot", -1);
+
+                // OAI-compat
+                task.params.oaicompat                 = OAICOMPAT_TYPE_NONE;
+                task.params.oaicompat_cmpl_id         = completion_id;
+                // oaicompat_model is already populated by params_from_json_cmpl
+
+                tasks.push_back(std::move(task));
+            }
+
+            task_ids = server_task::get_list_id(tasks);
+            ctx_server.queue_results.add_waiting_tasks(tasks);
+            ctx_server.queue_tasks.post(std::move(tasks));
+        } catch (const std::exception & e) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, e.what());
+        }
+
+
+        std::cout << "[DEBUG] Waiting for results..." << std::endl;
+        ctx_server.receive_multi_results(task_ids, [&](std::vector<server_task_result_ptr> & results) {
+            std::cout << "[DEBUG] Received " << results.size() << " results" << std::endl;
+            if (results.size() == 1) {
+                // single result
+                reply->set_message(results[0]->to_json().value("content", ""));
+
+                int32_t tokens_predicted = results[0]->to_json().value("tokens_predicted", 0);
+                reply->set_tokens(tokens_predicted);
+                int32_t tokens_evaluated = results[0]->to_json().value("tokens_evaluated", 0);
+                reply->set_prompt_tokens(tokens_evaluated);
+
+                if (results[0]->to_json().contains("timings")) {
+                    double timing_prompt_processing = results[0]->to_json().at("timings").value("prompt_ms", 0.0);
+                    reply->set_timing_prompt_processing(timing_prompt_processing);
+                    double timing_token_generation = results[0]->to_json().at("timings").value("predicted_ms", 0.0);
+                    reply->set_timing_token_generation(timing_token_generation);
+                }
+
+            } else {
+                // multiple results (multitask)
+                json arr = json::array();
+                for (auto & res : results) {
+                    arr.push_back(res->to_json().value("content", ""));
+                }
+                reply->set_message(arr);
+            }
+
+            
+        }, [&](const json & error_data) {
+            std::cout << "[DEBUG] Error in results: " << error_data.value("content", "") << std::endl;
+            reply->set_message(error_data.value("content", ""));
+        }, [&]() {
+            return false;
+        });
+
+        ctx_server.queue_results.remove_waiting_task_ids(task_ids);
+        std::cout << "[DEBUG] Predict request completed successfully" << std::endl;
+
+        return grpc::Status::OK;
+    }
+
+    grpc::Status Embedding(ServerContext* context, const backend::PredictOptions* request, backend::EmbeddingResult* embeddingResult) {
+
+        json body = parse_options(false, request);
+
+        body["stream"] = false;
+
+        /*
+        if (llama_pooling_type(ctx_server.ctx) == LLAMA_POOLING_TYPE_NONE) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "Pooling type 'none' is not OAI compatible. Please use a different pooling type");
+        }
+        */
+
+        // for the shape of input/content, see tokenize_input_prompts()
+        json prompt = body.at("prompt");
+
+
+        auto tokenized_prompts = tokenize_input_prompts(ctx_server.vocab, ctx_server.mctx, prompt, true, true);
+        for (const auto & tokens : tokenized_prompts) {
+            // this check is necessary for models that do not add BOS token to the input
+            if (tokens.empty()) {
+                return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "Input content cannot be empty");
+            }
+        }
+
+        // create and queue the task
+        json responses = json::array();
+        bool error = false;
+        std::unordered_set<int> task_ids;
+        {
+            std::vector<server_task> tasks;
+            for (size_t i = 0; i < tokenized_prompts.size(); i++) {
+                server_task task = server_task(SERVER_TASK_TYPE_EMBEDDING);
+
+                task.id            = ctx_server.queue_tasks.get_new_id();
+                task.index         = i;
+                task.prompt_tokens = std::move(tokenized_prompts[i]);
+
+                // OAI-compat
+                task.params.oaicompat = OAICOMPAT_TYPE_EMBEDDING;
+
+                tasks.push_back(std::move(task));
+            }
+
+            task_ids = server_task::get_list_id(tasks);
+            ctx_server.queue_results.add_waiting_tasks(tasks);
+            ctx_server.queue_tasks.post(std::move(tasks));
+        }
+
+        // get the result
+        ctx_server.receive_multi_results(task_ids, [&](std::vector<server_task_result_ptr> & results) {
+            for (auto & res : results) {
+                GGML_ASSERT(dynamic_cast<server_task_result_embd*>(res.get()) != nullptr);
+                responses.push_back(res->to_json());
+            }
+        }, [&](const json & error_data) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, error_data.value("content", ""));
+        }, [&]() {
+            // NOTE: we should try to check when the writer is closed here
+            return false;
+        });
+
+        ctx_server.queue_results.remove_waiting_task_ids(task_ids);
+
+        if (error) {
+            return grpc::Status(grpc::StatusCode::INTERNAL, "Error in receiving results");
+        }
+
+        std::vector<float> embeddings = responses[0].value("embedding", std::vector<float>());
+        // loop the vector and set the embeddings results
+        for (int i = 0; i < embeddings.size(); i++) {
+            embeddingResult->add_embeddings(embeddings[i]);
+        }
+
+        return grpc::Status::OK;
+    }
+
+    grpc::Status Rerank(ServerContext* context, const backend::RerankRequest* request, backend::RerankResult* rerankResult) {
+        if (!ctx_server.params_base.embedding || ctx_server.params_base.pooling_type != LLAMA_POOLING_TYPE_RANK) {
+            return grpc::Status(grpc::StatusCode::UNIMPLEMENTED, "This server does not support reranking. Start it with `--reranking` and without `--embedding`");
+        }
+
+        // Validate request
+        if (request->query().empty()) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "\"query\" must be provided");
+        }
+
+        if (request->documents_size() == 0) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "\"documents\" must be a non-empty string array");
+        }
+
+        // Tokenize the query
+        auto tokenized_query = tokenize_input_prompts(ctx_server.vocab, ctx_server.mctx, request->query(), /* add_special */ false, true);
+        if (tokenized_query.size() != 1) {
+            return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, "\"query\" must contain only a single prompt");
+        }
+        // Create and queue the task
+        json responses = json::array();
+        bool error = false;
+        std::unordered_set<int> task_ids;
+        {
+            std::vector<server_task> tasks;
+            std::vector<std::string> documents;
+            for (int i = 0; i < request->documents_size(); i++) {
+                documents.push_back(request->documents(i));
+            }
+            
+            auto tokenized_docs = tokenize_input_prompts(ctx_server.vocab, ctx_server.mctx, documents, /* add_special */ false, true);
+            tasks.reserve(tokenized_docs.size());
+            for (size_t i = 0; i < tokenized_docs.size(); i++) {
+                auto tmp = format_rerank(ctx_server.vocab, tokenized_query[0], tokenized_docs[i]);
+                server_task task = server_task(SERVER_TASK_TYPE_RERANK);
+                task.id = ctx_server.queue_tasks.get_new_id();
+                task.index = i;
+                task.prompt_tokens = std::move(tmp);
+                tasks.push_back(std::move(task));
+            }
+
+            task_ids = server_task::get_list_id(tasks);
+            ctx_server.queue_results.add_waiting_tasks(tasks);
+            ctx_server.queue_tasks.post(std::move(tasks));
+        }
+
+        // Get the results
+        ctx_server.receive_multi_results(task_ids, [&](std::vector<server_task_result_ptr> & results) {
+            for (auto & res : results) {
+                GGML_ASSERT(dynamic_cast<server_task_result_rerank*>(res.get()) != nullptr);
+                responses.push_back(res->to_json());
+            }
+        }, [&](const json & error_data) {
+            error = true;
+        }, [&]() {
+            return false;
+        });
+
+        ctx_server.queue_results.remove_waiting_task_ids(task_ids);
+
+        if (error) {
+            return grpc::Status(grpc::StatusCode::INTERNAL, "Error in receiving results");
+        }
+
+        // Set usage information
+        backend::Usage* usage = rerankResult->mutable_usage();
+        int total_tokens = 0;
+        int prompt_tokens = 0;
+
+        // Create document results
+        for (const auto& response : responses) {
+            backend::DocumentResult* doc_result = rerankResult->add_results();
+            doc_result->set_index(response.value("index", 0));
+            doc_result->set_text(request->documents(response.value("index", 0)));
+            doc_result->set_relevance_score(response.value("score", 0.0f));
+            
+            // Add tokens evaluated for this document
+            int tokens_evaluated = response.value("tokens_evaluated", 0);
+            total_tokens += tokens_evaluated;
+            prompt_tokens += tokens_evaluated;
+        }
+
+        // Set the total tokens in usage
+        usage->set_total_tokens(total_tokens);
+        usage->set_prompt_tokens(prompt_tokens);
+
+        return grpc::Status::OK;
+    }
+
+    grpc::Status TokenizeString(ServerContext* context, const backend::PredictOptions* request, backend::TokenizationResponse* response) {
+        json body = parse_options(false, request);
+        body["stream"] = false;
+        
+        json tokens_response = json::array();
+        if (body.count("prompt") != 0) {
+            const bool add_special = json_value(body, "add_special", false);
+            const bool with_pieces = json_value(body, "with_pieces", false);
+
+            llama_tokens tokens = tokenize_mixed(ctx_server.vocab, body.at("content"), add_special, true);
+
+
+            for (const auto& token : tokens) {
+                std::string piece = common_token_to_piece(ctx_server.ctx, token);
+                response->add_tokens(token);
+            }
+        }
+
+        return grpc::Status::OK;
+    }
+
+    grpc::Status GetMetrics(ServerContext* context, const backend::MetricsRequest* request, backend::MetricsResponse* response) {
+
+// request slots data using task queue
+        int task_id = ctx_server.queue_tasks.get_new_id();
+        {
+            server_task task(SERVER_TASK_TYPE_METRICS);
+            task.id = task_id;
+            ctx_server.queue_results.add_waiting_task_id(task_id);
+            ctx_server.queue_tasks.post(std::move(task), true); // high-priority task
+        }
+
+        // get the result
+        server_task_result_ptr result = ctx_server.queue_results.recv(task_id);
+        ctx_server.queue_results.remove_waiting_task_id(task_id);
+
+        if (result->is_error()) {
+            // Handle case when no active slot exists
+            response->set_slot_id(0);
+            response->set_prompt_json_for_slot("");
+            response->set_tokens_per_second(0);
+            response->set_tokens_generated(0);
+            response->set_prompt_tokens_processed(0);
+            return grpc::Status(grpc::StatusCode::INTERNAL, "Error in receiving results");
+        }
+
+        // TODO: get rid of this dynamic_cast
+        auto res_metrics = dynamic_cast<server_task_result_metrics*>(result.get());
+        GGML_ASSERT(res_metrics != nullptr);    
+
+        // Populate the response with metrics
+        response->set_slot_id(0);
+        response->set_prompt_json_for_slot("");
+        response->set_tokens_per_second(res_metrics->n_prompt_tokens_processed ? 1.e3 / res_metrics->t_prompt_processing * res_metrics->n_prompt_tokens_processed : 0.);
+        response->set_tokens_generated(res_metrics->n_tokens_predicted_total);
+        response->set_prompt_tokens_processed(res_metrics->n_prompt_tokens_processed_total);
+        
+
+        return grpc::Status::OK;
+    }
+};
+
+
+int main(int argc, char** argv) {
+  std::string server_address("localhost:50051");
+
+  // Define long and short options
+  struct option long_options[] = {
+      {"addr", required_argument, nullptr, 'a'},
+      {nullptr, 0, nullptr, 0}
+  };
+
+  // Parse command-line arguments
+  int option;
+  int option_index = 0;
+  while ((option = getopt_long(argc, argv, "a:", long_options, &option_index)) != -1) {
+    switch (option) {
+      case 'a':
+        server_address = optarg;
+        break;
+      default:
+        std::cerr << "Usage: " << argv[0] << " [--addr=<address>] or [-a <address>]" << std::endl;
+        return 1;
+    }
+  }
+  
+    server_context ctx_server;
+    BackendServiceImpl service(ctx_server);
+
+    ServerBuilder builder;
+    builder.AddListeningPort(server_address, grpc::InsecureServerCredentials());
+    builder.RegisterService(&service);
+    builder.SetMaxMessageSize(50 * 1024 * 1024); // 50MB
+    builder.SetMaxSendMessageSize(50 * 1024 * 1024); // 50MB
+    builder.SetMaxReceiveMessageSize(50 * 1024 * 1024); // 50MB
+    std::unique_ptr<Server> server(builder.BuildAndStart());
+   // run the HTTP server in a thread - see comment below
+    std::thread t([&]()
+    {
+        std::cout << "Server listening on " << server_address << std::endl;
+        server->Wait();
+        return 0;
+    });
+
+    // clean up function, to be called before exit
+    auto clean_up = [&server, &ctx_server]() {
+        SRV_INF("%s: cleaning up before exit...\n", __func__);
+        server->Shutdown();
+        ctx_server.queue_results.terminate();
+        llama_backend_free();
+    };
+
+
+    //);
+    start_llama_server(ctx_server);
+    std::cout << "stopping" << std::endl;
+
+
+    clean_up();
+    t.join();
+
+    return 0;
+}

backend/cpp/llama-cpp/package.sh

@@ -0,0 +1,42 @@
+#!/bin/bash
+
+# Script to copy the appropriate libraries based on architecture
+# This script is used in the final stage of the Dockerfile
+
+set -e
+
+CURDIR=$(dirname "$(realpath $0)")
+
+# Create lib directory
+mkdir -p $CURDIR/package/lib
+
+cp -avrf $CURDIR/llama-cpp-* $CURDIR/package/
+cp -rfv $CURDIR/run.sh $CURDIR/package/
+
+# Detect architecture and copy appropriate libraries
+if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
+    # x86_64 architecture
+    echo "Detected x86_64 architecture, copying x86_64 libraries..."
+    cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
+    # ARM64 architecture
+    echo "Detected ARM64 architecture, copying ARM64 libraries..."
+    cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+else
+    echo "Error: Could not detect architecture"
+    exit 1
+fi
+
+echo "Packaging completed successfully" 
+ls -liah $CURDIR/package/
+ls -liah $CURDIR/package/lib/

backend/cpp/llama-cpp/prepare.sh

@@ -0,0 +1,52 @@
+#!/bin/bash
+
+## Patches
+## Apply patches from the `patches` directory
+for patch in $(ls patches); do
+    echo "Applying patch $patch"
+    patch -d llama.cpp/ -p1 < patches/$patch
+done 
+
+set -e
+
+cp -r CMakeLists.txt llama.cpp/tools/grpc-server/
+cp -r grpc-server.cpp llama.cpp/tools/grpc-server/
+cp -rfv llama.cpp/vendor/nlohmann/json.hpp llama.cpp/tools/grpc-server/
+cp -rfv llama.cpp/tools/server/utils.hpp llama.cpp/tools/grpc-server/
+cp -rfv llama.cpp/vendor/cpp-httplib/httplib.h llama.cpp/tools/grpc-server/
+
+set +e
+if grep -q "grpc-server" llama.cpp/tools/CMakeLists.txt; then
+    echo "grpc-server already added"
+else
+    echo "add_subdirectory(grpc-server)" >> llama.cpp/tools/CMakeLists.txt
+fi
+set -e
+
+# Now to keep maximum compatibility with the original server.cpp, we need to remove the index.html.gz.hpp and loading.html.hpp includes
+# and remove the main function
+# TODO: upstream this to the original server.cpp by extracting the upstream main function to a separate file
+awk '
+/int[ \t]+main[ \t]*\(/ {          # If the line starts the main function
+    in_main=1;                     # Set a flag
+    open_braces=0;                 # Track number of open braces
+}
+in_main {
+    open_braces += gsub(/\{/, "{"); # Count opening braces
+    open_braces -= gsub(/\}/, "}"); # Count closing braces
+    if (open_braces == 0) {         # If all braces are closed
+        in_main=0;                  # End skipping
+    }
+    next;                           # Skip lines inside main
+}
+!in_main                           # Print lines not inside main
+' "llama.cpp/tools/server/server.cpp" > llama.cpp/tools/grpc-server/server.cpp
+
+# remove index.html.gz.hpp and loading.html.hpp includes
+if [[ "$OSTYPE" == "darwin"* ]]; then
+    # macOS
+    sed -i '' '/#include "index\.html\.gz\.hpp"/d; /#include "loading\.html\.hpp"/d' llama.cpp/tools/grpc-server/server.cpp
+else
+    # Linux and others
+    sed -i '/#include "index\.html\.gz\.hpp"/d; /#include "loading\.html\.hpp"/d' llama.cpp/tools/grpc-server/server.cpp
+fi

backend/cpp/llama-cpp/run.sh

@@ -0,0 +1,62 @@
+#!/bin/bash
+set -ex
+
+# Get the absolute current dir where the script is located
+CURDIR=$(dirname "$(realpath $0)")
+
+cd /
+
+echo "CPU info:"
+grep -e "model\sname" /proc/cpuinfo | head -1
+grep -e "flags" /proc/cpuinfo | head -1
+
+BINARY=llama-cpp-fallback
+
+if grep -q -e "\savx\s" /proc/cpuinfo ; then
+	echo "CPU:    AVX    found OK"
+	if [ -e $CURDIR/llama-cpp-avx ]; then
+		BINARY=llama-cpp-avx
+	fi
+fi
+
+if grep -q -e "\savx2\s" /proc/cpuinfo ; then
+	echo "CPU:    AVX2   found OK"
+	if [ -e $CURDIR/llama-cpp-avx2 ]; then
+		BINARY=llama-cpp-avx2
+	fi
+fi
+
+# Check avx 512
+if grep -q -e "\savx512f\s" /proc/cpuinfo ; then
+	echo "CPU:    AVX512F found OK"
+	if [ -e $CURDIR/llama-cpp-avx512 ]; then
+		BINARY=llama-cpp-avx512
+	fi
+fi
+
+if [ -n "$LLAMACPP_GRPC_SERVERS" ]; then
+	if [ -e $CURDIR/llama-cpp-grpc ]; then
+		BINARY=llama-cpp-grpc
+	fi
+fi
+ 
+# Extend ld library path with the dir where this script is located/lib
+if [ "$(uname)" == "Darwin" ]; then
+	export DYLD_LIBRARY_PATH=$CURDIR/lib:$DYLD_LIBRARY_PATH
+	#export DYLD_FALLBACK_LIBRARY_PATH=$CURDIR/lib:$DYLD_FALLBACK_LIBRARY_PATH
+else
+	export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
+fi
+
+# If there is a lib/ld.so, use it
+if [ -f $CURDIR/lib/ld.so ]; then
+	echo "Using lib/ld.so"
+	echo "Using binary: $BINARY"
+	exec $CURDIR/lib/ld.so $CURDIR/$BINARY "$@"
+fi
+
+echo "Using binary: $BINARY"
+exec $CURDIR/$BINARY "$@"
+
+# We should never reach this point, however just in case we do, run fallback
+exec $CURDIR/llama-cpp-fallback "$@"

backend/cpp/llama/Makefile

@@ -1,87 +0,0 @@
-
-LLAMA_VERSION?=
-LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
-
-CMAKE_ARGS?=
-BUILD_TYPE?=
-ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
-TARGET?=--target grpc-server
-
-# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
-CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF -DLLAMA_CURL=OFF
-
-# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
-ifeq ($(BUILD_TYPE),cublas)
-	CMAKE_ARGS+=-DGGML_CUDA=ON
-# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-# to CMAKE_ARGS automatically
-else ifeq ($(BUILD_TYPE),openblas)
-	CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
-else ifeq ($(BUILD_TYPE),clblas)
-	CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
-# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++ 
-else ifeq ($(BUILD_TYPE),hipblas)
-	CMAKE_ARGS+=-DGGML_HIP=ON
-# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
-# But if it's OSX without metal, disable it here
-else ifeq ($(OS),Darwin)
-	ifneq ($(BUILD_TYPE),metal)
-		CMAKE_ARGS+=-DGGML_METAL=OFF
-	else
-		CMAKE_ARGS+=-DGGML_METAL=ON
-		CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
-		TARGET+=--target ggml-metal
-	endif
-endif
-
-ifeq ($(BUILD_TYPE),sycl_f16)
-	CMAKE_ARGS+=-DGGML_SYCL=ON \
-		-DCMAKE_C_COMPILER=icx \
-		-DCMAKE_CXX_COMPILER=icpx \
-		-DCMAKE_CXX_FLAGS="-fsycl" \
-		-DGGML_SYCL_F16=ON
-endif
-
-ifeq ($(BUILD_TYPE),sycl_f32)
-	CMAKE_ARGS+=-DGGML_SYCL=ON \
-		-DCMAKE_C_COMPILER=icx \
-		-DCMAKE_CXX_COMPILER=icpx \
-		-DCMAKE_CXX_FLAGS="-fsycl"
-endif
-
-llama.cpp:
-	mkdir -p llama.cpp
-	cd llama.cpp && \
-	git init && \
-	git remote add origin $(LLAMA_REPO)  && \
-	git fetch origin && \
-	git checkout -b build $(LLAMA_VERSION) && \
-	git submodule update --init --recursive --depth 1 --single-branch
-
-llama.cpp/tools/grpc-server: llama.cpp
-	mkdir -p llama.cpp/tools/grpc-server
-	bash prepare.sh
-
-rebuild:
-	bash prepare.sh
-	rm -rf grpc-server
-	$(MAKE) grpc-server
-
-purge:
-	rm -rf llama.cpp/build
-	rm -rf llama.cpp/tools/grpc-server
-	rm -rf grpc-server
-
-clean: purge
-	rm -rf llama.cpp
-
-grpc-server: llama.cpp llama.cpp/tools/grpc-server
-	@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-	+bash -c "source $(ONEAPI_VARS); \
-	cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)"
-else
-	+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)
-endif
-	cp llama.cpp/build/bin/grpc-server .

backend/cpp/llama/prepare.sh

@@ -1,28 +0,0 @@
-#!/bin/bash
-
-## Patches
-## Apply patches from the `patches` directory
-for patch in $(ls patches); do
-    echo "Applying patch $patch"
-    patch -d llama.cpp/ -p1 < patches/$patch
-done 
-
-cp -r CMakeLists.txt llama.cpp/tools/grpc-server/
-cp -r grpc-server.cpp llama.cpp/tools/grpc-server/
-cp -rfv json.hpp llama.cpp/tools/grpc-server/
-cp -rfv utils.hpp llama.cpp/tools/grpc-server/
-    
-if grep -q "grpc-server" llama.cpp/tools/CMakeLists.txt; then
-    echo "grpc-server already added"
-else
-    echo "add_subdirectory(grpc-server)" >> llama.cpp/tools/CMakeLists.txt
-fi
-
-## XXX: In some versions of CMake clip wasn't being built before llama.
-## This is an hack for now, but it should be fixed in the future.
-# cp -rfv llama.cpp/tools/mtmd/clip.h llama.cpp/tools/grpc-server/clip.h
-# cp -rfv llama.cpp/tools/mtmd/clip-impl.h llama.cpp/tools/grpc-server/clip-impl.h
-# cp -rfv llama.cpp/tools/mtmd/llava.cpp llama.cpp/tools/grpc-server/llava.cpp
-# echo '#include "llama.h"' > llama.cpp/tools/grpc-server/llava.h
-# cat llama.cpp/tools/mtmd/llava.h >> llama.cpp/tools/grpc-server/llava.h
-# cp -rfv llama.cpp/tools/mtmd/clip.cpp llama.cpp/tools/grpc-server/clip.cpp

backend/cpp/llama/utils.hpp

@@ -1,910 +0,0 @@
-// https://github.com/ggerganov/llama.cpp/blob/master/tools/server/utils.hpp
-
-#pragma once
-
-#include <string>
-#include <vector>
-#include <set>
-#include <mutex>
-#include <condition_variable>
-#include <unordered_map>
-
-#include "json.hpp"
-
-#include "../mtmd/clip.h"
-
-using json = nlohmann::json;
-
-extern bool server_verbose;
-
-#ifndef SERVER_VERBOSE
-#define SERVER_VERBOSE 1
-#endif
-
-#if SERVER_VERBOSE != 1
-#define LOG_VERBOSE(MSG, ...)
-#else
-#define LOG_VERBOSE(MSG, ...)                                            \
-    do                                                                   \
-    {                                                                    \
-        if (server_verbose)                                              \
-        {                                                                \
-            server_log("VERBOSE", __func__, __LINE__, MSG, __VA_ARGS__); \
-        }                                                                \
-    } while (0)
-#endif
-
-#define LOG_ERROR(  MSG, ...) server_log("ERROR",   __func__, __LINE__, MSG, __VA_ARGS__)
-#define LOG_WARNING(MSG, ...) server_log("WARNING", __func__, __LINE__, MSG, __VA_ARGS__)
-#define LOG_INFO(   MSG, ...) server_log("INFO",    __func__, __LINE__, MSG, __VA_ARGS__)
-
-//
-// parallel
-//
-
-enum server_state {
-    SERVER_STATE_LOADING_MODEL,  // Server is starting up, model not fully loaded yet
-    SERVER_STATE_READY,          // Server is ready and model is loaded
-    SERVER_STATE_ERROR           // An error occurred, load_model failed
-};
-
-enum task_type {
-    TASK_TYPE_COMPLETION,
-    TASK_TYPE_CANCEL,
-    TASK_TYPE_NEXT_RESPONSE
-};
-
-struct task_server {
-    int id = -1; // to be filled by llama_server_queue
-    int target_id;
-    task_type type;
-    json data;
-    bool infill_mode = false;
-    bool embedding_mode = false;
-    int multitask_id = -1;
-};
-
-struct task_result {
-    int id;
-    int multitask_id = -1;
-    bool stop;
-    bool error;
-    json result_json;
-};
-
-struct task_multi {
-    int id;
-    std::set<int> subtasks_remaining{};
-    std::vector<task_result> results{};
-};
-
-// TODO: can become bool if we can't find use of more states
-enum slot_state
-{
-    IDLE,
-    PROCESSING,
-};
-
-enum slot_command
-{
-    NONE,
-    LOAD_PROMPT,
-    RELEASE,
-};
-
-struct slot_params
-{
-    bool stream       = true;
-    bool cache_prompt = false; // remember the prompt to avoid reprocessing all prompt
-
-    uint32_t seed      = -1; // RNG seed
-    int32_t  n_keep    =  0; // number of tokens to keep from initial prompt
-    int32_t  n_predict = -1; // new tokens to predict
-
-    std::vector<std::string> antiprompt;
-
-    json input_prefix;
-    json input_suffix;
-};
-
-struct slot_image
-{
-    int32_t id;
-
-    bool request_encode_image = false;
-    float * image_embedding = nullptr;
-    int32_t image_tokens = 0;
-
-    clip_image_u8 * img_data;
-
-    std::string prefix_prompt; // before of this image
-};
-
-// completion token output with probabilities
-struct completion_token_output
-{
-    struct token_prob
-    {
-        llama_token tok;
-        float prob;
-    };
-
-    std::vector<token_prob> probs;
-    llama_token tok;
-    std::string text_to_send;
-};
-
-static inline void server_log(const char *level, const char *function, int line,
-                       const char *message, const nlohmann::ordered_json &extra)
-{
-    nlohmann::ordered_json log
-    {
-        {"timestamp", time(nullptr)},
-        {"level",     level},
-        {"function",  function},
-        {"line",      line},
-        {"message",   message},
-    };
-
-    if (!extra.empty())
-    {
-        log.merge_patch(extra);
-    }
-
-    const std::string str = log.dump(-1, ' ', false, json::error_handler_t::replace);
-    printf("%.*s\n", (int)str.size(), str.data());
-    fflush(stdout);
-}
-
-//
-// server utils
-//
-
-template <typename T>
-static T json_value(const json &body, const std::string &key, const T &default_value)
-{
-    // Fallback null to default value
-    return body.contains(key) && !body.at(key).is_null()
-        ? body.value(key, default_value)
-        : default_value;
-}
-
-inline std::string format_chatml(std::vector<json> messages)
-{
-    std::ostringstream chatml_msgs;
-
-    for (auto it = messages.begin(); it != messages.end(); ++it) {
-        chatml_msgs << "<|im_start|>"
-                    << json_value(*it, "role",    std::string("user")) << '\n';
-        chatml_msgs << json_value(*it, "content", std::string(""))
-                    << "<|im_end|>\n";
-    }
-
-    chatml_msgs << "<|im_start|>assistant" << '\n';
-
-    return chatml_msgs.str();
-}
-
-//
-// work queue utils
-//
-
-struct llama_server_queue {
-    int id = 0;
-    std::mutex mutex_tasks;
-    // queues
-    std::vector<task_server> queue_tasks;
-    std::vector<task_server> queue_tasks_deferred;
-    std::vector<task_multi> queue_multitasks;
-    std::condition_variable condition_tasks;
-    // callback functions
-    std::function<void(task_server&)> callback_new_task;
-    std::function<void(task_multi&)> callback_finish_multitask;
-    std::function<void(void)> callback_all_task_finished;
-
-    // Add a new task to the end of the queue
-    int post(task_server task) {
-        std::unique_lock<std::mutex> lock(mutex_tasks);
-        if (task.id == -1) {
-            task.id = id++;
-        }
-        queue_tasks.push_back(std::move(task));
-        condition_tasks.notify_one();
-        return task.id;
-    }
-
-    // Add a new task, but defer until one slot is available
-    void defer(task_server task) {
-        std::unique_lock<std::mutex> lock(mutex_tasks);
-        queue_tasks_deferred.push_back(std::move(task));
-    }
-
-    // Get the next id for creating anew task
-    int get_new_id() {
-        std::unique_lock<std::mutex> lock(mutex_tasks);
-        return id++;
-    }
-
-    // Register function to process a new task
-    void on_new_task(std::function<void(task_server&)> callback) {
-        callback_new_task = callback;
-    }
-
-    // Register function to process a multitask
-    void on_finish_multitask(std::function<void(task_multi&)> callback) {
-        callback_finish_multitask = callback;
-    }
-
-    // Register the function to be called when the batch of tasks is finished
-    void on_all_tasks_finished(std::function<void(void)> callback) {
-        callback_all_task_finished = callback;
-    }
-
-    // Call when the state of one slot is changed
-    void notify_slot_changed() {
-        // move deferred tasks back to main loop
-        std::unique_lock<std::mutex> lock(mutex_tasks);
-        for (auto & task : queue_tasks_deferred) {
-            queue_tasks.push_back(std::move(task));
-        }
-        queue_tasks_deferred.clear();
-    }
-
-    // Start the main loop. This call is blocking
-    [[noreturn]]
-    void start_loop() {
-        while (true) {
-            // new task arrived
-            LOG_VERBOSE("have new task", {});
-            {
-                while (true)
-                {
-                    std::unique_lock<std::mutex> lock(mutex_tasks);
-                    if (queue_tasks.empty()) {
-                        lock.unlock();
-                        break;
-                    }
-                    task_server task = queue_tasks.front();
-                    queue_tasks.erase(queue_tasks.begin());
-                    lock.unlock();
-                    LOG_VERBOSE("callback_new_task", {});
-                    callback_new_task(task);
-                }
-                LOG_VERBOSE("callback_all_task_finished", {});
-                // process and update all the multitasks
-                auto queue_iterator = queue_multitasks.begin();
-                while (queue_iterator != queue_multitasks.end())
-                {
-                    if (queue_iterator->subtasks_remaining.empty())
-                    {
-                        // all subtasks done == multitask is done
-                        task_multi current_multitask = *queue_iterator;
-                        callback_finish_multitask(current_multitask);
-                        // remove this multitask
-                        queue_iterator = queue_multitasks.erase(queue_iterator);
-                    }
-                    else
-                    {
-                        ++queue_iterator;
-                    }
-                }
-                // all tasks in the current loop is finished
-                callback_all_task_finished();
-            }
-            LOG_VERBOSE("wait for new task", {});
-            // wait for new task
-            {
-                std::unique_lock<std::mutex> lock(mutex_tasks);
-                if (queue_tasks.empty()) {
-                    condition_tasks.wait(lock, [&]{
-                        return !queue_tasks.empty();
-                    });
-                }
-            }
-        }
-    }
-
-    //
-    // functions to manage multitasks
-    //
-
-    // add a multitask by specifying the id of all subtask (subtask is a task_server)
-    void add_multitask(int multitask_id, std::vector<int>& sub_ids)
-    {
-        std::lock_guard<std::mutex> lock(mutex_tasks);
-        task_multi multi;
-        multi.id = multitask_id;
-        std::copy(sub_ids.begin(), sub_ids.end(), std::inserter(multi.subtasks_remaining, multi.subtasks_remaining.end()));
-        queue_multitasks.push_back(multi);
-    }
-
-    // updatethe remaining subtasks, while appending results to multitask
-    void update_multitask(int multitask_id, int subtask_id, task_result& result)
-    {
-        std::lock_guard<std::mutex> lock(mutex_tasks);
-        for (auto& multitask : queue_multitasks)
-        {
-            if (multitask.id == multitask_id)
-            {
-                multitask.subtasks_remaining.erase(subtask_id);
-                multitask.results.push_back(result);
-            }
-        }
-    }
-};
-
-struct llama_server_response {
-    typedef std::function<void(int, int, task_result&)> callback_multitask_t;
-    callback_multitask_t callback_update_multitask;
-    // for keeping track of all tasks waiting for the result
-    std::set<int> waiting_task_ids;
-    // the main result queue
-    std::vector<task_result> queue_results;
-    std::mutex mutex_results;
-    std::condition_variable condition_results;
-
-    void add_waiting_task_id(int task_id) {
-        std::unique_lock<std::mutex> lock(mutex_results);
-        waiting_task_ids.insert(task_id);
-    }
-
-    void remove_waiting_task_id(int task_id) {
-        std::unique_lock<std::mutex> lock(mutex_results);
-        waiting_task_ids.erase(task_id);
-    }
-
-    // This function blocks the thread until there is a response for this task_id
-    task_result recv(int task_id) {
-        while (true)
-        {
-            std::unique_lock<std::mutex> lock(mutex_results);
-            condition_results.wait(lock, [&]{
-                return !queue_results.empty();
-            });
-            LOG_VERBOSE("condition_results unblock", {});
-
-            for (int i = 0; i < (int) queue_results.size(); i++)
-            {
-                if (queue_results[i].id == task_id)
-                {
-                    assert(queue_results[i].multitask_id == -1);
-                    task_result res = queue_results[i];
-                    queue_results.erase(queue_results.begin() + i);
-                    return res;
-                }
-            }
-        }
-
-        // should never reach here
-    }
-
-    // Register the function to update multitask
-    void on_multitask_update(callback_multitask_t callback) {
-        callback_update_multitask = callback;
-    }
-
-    // Send a new result to a waiting task_id
-    void send(task_result result) {
-        std::unique_lock<std::mutex> lock(mutex_results);
-        LOG_VERBOSE("send new result", {});
-        for (auto& task_id : waiting_task_ids) {
-            // LOG_TEE("waiting task id %i \n", task_id);
-            // for now, tasks that have associated parent multitasks just get erased once multitask picks up the result
-            if (result.multitask_id == task_id)
-            {
-                LOG_VERBOSE("callback_update_multitask", {});
-                callback_update_multitask(task_id, result.id, result);
-                continue;
-            }
-
-            if (result.id == task_id)
-            {
-                LOG_VERBOSE("queue_results.push_back", {});
-                queue_results.push_back(result);
-                condition_results.notify_one();
-                return;
-            }
-        }
-    }
-};
-
-//
-// base64 utils (TODO: move to common in the future)
-//
-
-static const std::string base64_chars =
-             "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
-             "abcdefghijklmnopqrstuvwxyz"
-             "0123456789+/";
-
-static inline bool is_base64(uint8_t c)
-{
-    return (isalnum(c) || (c == '+') || (c == '/'));
-}
-
-static inline std::vector<uint8_t> base64_decode(const std::string & encoded_string)
-{
-    int i = 0;
-    int j = 0;
-    int in_ = 0;
-
-    int in_len = encoded_string.size();
-
-    uint8_t char_array_4[4];
-    uint8_t char_array_3[3];
-
-    std::vector<uint8_t> ret;
-
-    while (in_len-- && (encoded_string[in_] != '=') && is_base64(encoded_string[in_]))
-    {
-        char_array_4[i++] = encoded_string[in_]; in_++;
-        if (i == 4)
-        {
-            for (i = 0; i <4; i++)
-            {
-                char_array_4[i] = base64_chars.find(char_array_4[i]);
-            }
-
-            char_array_3[0] = ((char_array_4[0]      ) << 2) + ((char_array_4[1] & 0x30) >> 4);
-            char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
-            char_array_3[2] = ((char_array_4[2] & 0x3) << 6) +   char_array_4[3];
-
-            for (i = 0; (i < 3); i++)
-            {
-                ret.push_back(char_array_3[i]);
-            }
-            i = 0;
-        }
-    }
-
-    if (i)
-    {
-        for (j = i; j <4; j++)
-        {
-            char_array_4[j] = 0;
-        }
-
-        for (j = 0; j <4; j++)
-        {
-            char_array_4[j] = base64_chars.find(char_array_4[j]);
-        }
-
-        char_array_3[0] = ((char_array_4[0]      ) << 2) + ((char_array_4[1] & 0x30) >> 4);
-        char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
-        char_array_3[2] = ((char_array_4[2] & 0x3) << 6) +   char_array_4[3];
-
-        for (j = 0; (j < i - 1); j++)
-        {
-            ret.push_back(char_array_3[j]);
-        }
-    }
-
-    return ret;
-
-}
-
-
-
-//
-// tokenizer and input processing utils
-//
-
-static bool json_is_array_of_numbers(const json & data) {
-    if (data.is_array()) {
-        for (const auto & e : data) {
-            if (!e.is_number_integer()) {
-                return false;
-            }
-        }
-        return true;
-    }
-    return false;
-}
-
-// is array having BOTH numbers & strings?
-static bool json_is_array_of_mixed_numbers_strings(const json & data) {
-    bool seen_string = false;
-    bool seen_number = false;
-    if (data.is_array()) {
-        for (const auto & e : data) {
-            seen_string |= e.is_string();
-            seen_number |= e.is_number_integer();
-            if (seen_number && seen_string) {
-                return true;
-            }
-        }
-    }
-    return false;
-}
-
-// get value by path(key1 / key2)
-static json json_get_nested_values(const std::vector<std::string> & paths, const json & js) {
-    json result = json::object();
-
-    for (const std::string & path : paths) {
-        json current = js;
-        const auto keys = string_split<std::string>(path, /*separator*/ '/');
-        bool valid_path = true;
-        for (const std::string & k : keys) {
-            if (valid_path && current.is_object() && current.contains(k)) {
-                current = current[k];
-            } else {
-                valid_path = false;
-            }
-        }
-        if (valid_path) {
-            result[path] = current;
-        }
-    }
-    return result;
-}
-
-
-/**
- * this handles 2 cases:
- * - only string, example: "string"
- * - mixed string and tokens, example: [12, 34, "string", 56, 78]
- */
-static llama_tokens tokenize_mixed(const llama_vocab * vocab, const json & json_prompt, bool add_special, bool parse_special) {
-    // If `add_bos` is true, we only add BOS, when json_prompt is a string,
-    // or the first element of the json_prompt array is a string.
-    llama_tokens prompt_tokens;
-
-    if (json_prompt.is_array()) {
-        bool first = true;
-        for (const auto & p : json_prompt) {
-            if (p.is_string()) {
-                auto s = p.template get<std::string>();
-
-                llama_tokens p;
-                if (first) {
-                    p = common_tokenize(vocab, s, add_special, parse_special);
-                    first = false;
-                } else {
-                    p = common_tokenize(vocab, s, false, parse_special);
-                }
-
-                prompt_tokens.insert(prompt_tokens.end(), p.begin(), p.end());
-            } else {
-                if (first) {
-                    first = false;
-                }
-
-                prompt_tokens.push_back(p.template get<llama_token>());
-            }
-        }
-    } else {
-        auto s = json_prompt.template get<std::string>();
-        prompt_tokens = common_tokenize(vocab, s, add_special, parse_special);
-    }
-
-    return prompt_tokens;
-}
-
-/**
- * break the input "prompt" object into multiple prompt if needed, then tokenize them
- * this supports these cases:
- * - "prompt": "string"
- * - "prompt": [12, 34, 56]
- * - "prompt": [12, 34, "string", 56, 78]
- * and multiple prompts (multi-tasks):
- * - "prompt": ["string1", "string2"]
- * - "prompt": ["string1", [12, 34, 56]]
- * - "prompt": [[12, 34, 56], [78, 90, 12]]
- * - "prompt": [[12, 34, "string", 56, 78], [12, 34, 56]]
- */
-static std::vector<llama_tokens> tokenize_input_prompts(const llama_vocab * vocab, const json & json_prompt, bool add_special, bool parse_special) {
-    std::vector<llama_tokens> result;
-    if (json_prompt.is_string() || json_is_array_of_mixed_numbers_strings(json_prompt)) {
-        // string or mixed
-        result.push_back(tokenize_mixed(vocab, json_prompt, add_special, parse_special));
-    } else if (json_is_array_of_numbers(json_prompt)) {
-        // array of tokens
-        result.push_back(json_prompt.get<llama_tokens>());
-    } else if (json_prompt.is_array()) {
-        // array of prompts
-        result.reserve(json_prompt.size());
-        for (const auto & p : json_prompt) {
-            if (p.is_string() || json_is_array_of_mixed_numbers_strings(p)) {
-                result.push_back(tokenize_mixed(vocab, p, add_special, parse_special));
-            } else if (json_is_array_of_numbers(p)) {
-                // array of tokens
-                result.push_back(p.get<llama_tokens>());
-            } else {
-                throw std::runtime_error("element of \"prompt\" must be a string, an list of tokens, or a list of mixed strings & tokens");
-            }
-        }
-    } else {
-        throw std::runtime_error("\"prompt\" must be a string, an list of tokens, a list of mixed strings & tokens, or a list of prompts");
-    }
-    if (result.empty()) {
-        throw std::runtime_error("\"prompt\" must not be empty");
-    }
-    return result;
-}
-
-
-
-
-//
-// utils for interacting with libmtmd
-// (may need to refactor in near future)
-//
-
-/**
- * server_tokens is a helper to manage the input tokens and image for the server.
- * it is made this way to simplify the logic of KV cache management.
- */
-struct server_tokens {
-    bool has_mtmd = false;
-
-private: // disallow accessing these members directly, risking out-of-sync
-
-    // map a **start** position in tokens to the image chunk
-    std::unordered_map<llama_pos, mtmd::input_chunk_ptr> map_pos_to_image;
-
-    // list of tokens
-    // it can include LLAMA_TOKEN_NULL, which is used to indicate a token that is not a text token
-    // a mtmd_input_chunk can occupy multiple tokens, one llama_token per **position**
-    // important: for models using mrope, an image can contain multiple tokens but will use only one **position**
-    llama_tokens tokens;
-
-    // for ex. with input of 5 text tokens and 2 images:
-    //      [0] [1] [2] [3] [4] [img0] [img0] [img0] [img1] [img1]
-    // pos  0   1   2   3   4   5      6      7      8      9
-    // map_pos_to_image will contain: {5, img0}, {8, img1}
-
-public:
-    server_tokens() = default;
-    ~server_tokens() = default;
-
-    // Prevent copying
-    server_tokens(const server_tokens&) = delete;
-    server_tokens& operator=(const server_tokens&) = delete;
-
-    // Allow moving (usually implicitly generated if members are movable)
-    server_tokens(server_tokens&&) = default;
-    server_tokens& operator=(server_tokens&&) = default;
-
-    // Allow accessing elements using [] operator
-    llama_token operator[](size_t index) { return tokens[index]; }
-    const llama_token& operator[](size_t index) const { return tokens[index]; }
-
-    server_tokens(mtmd::input_chunks & mtmd_chunks, bool has_mtmd) : has_mtmd(has_mtmd) {
-        for (size_t i = 0; i < mtmd_chunks.size(); ++i) {
-            push_back(mtmd_chunks[i]);
-        }
-    }
-
-    server_tokens(llama_tokens & tokens, bool has_mtmd) : has_mtmd(has_mtmd), tokens(tokens) {}
-
-    // for debugging
-    std::string str() const {
-        std::ostringstream oss;
-        oss << "tokens: ";
-        for (const auto & t : tokens) {
-            if (t == LLAMA_TOKEN_NULL) {
-                oss << "<embd> ";
-            } else {
-                oss << t << " ";
-            }
-        }
-        oss << "\n";
-        oss << "image pos: ";
-        for (const auto & it : map_pos_to_image) {
-            oss << it.first << ", ";
-        }
-        return oss.str();
-    }
-
-    const mtmd::input_chunk_ptr & find_chunk(llama_pos pos) const {
-        auto it = map_pos_to_image.find(pos);
-        if (it != map_pos_to_image.end()) {
-            return it->second;
-        } else {
-            throw std::runtime_error("Chunk not found");
-        }
-    }
-
-    void push_back(llama_token tok) {
-        if (tok == LLAMA_TOKEN_NULL) {
-            throw std::runtime_error("Invalid token");
-        }
-        tokens.emplace_back(tok);
-    }
-
-    // will create a copy of the chunk if it contains non-text data
-    void push_back(const mtmd_input_chunk * chunk) {
-        auto type = mtmd_input_chunk_get_type(chunk);
-        if (type == MTMD_INPUT_CHUNK_TYPE_IMAGE) {
-            GGML_ASSERT(has_mtmd);
-            auto img_tokens = mtmd_input_chunk_get_tokens_image(chunk);
-            const int n_pos = mtmd_image_tokens_get_n_pos(img_tokens);
-            llama_pos start_pos = tokens.size();
-            for (int i = 0; i < n_pos; ++i) {
-                tokens.emplace_back(LLAMA_TOKEN_NULL);
-            }
-            mtmd::input_chunk_ptr new_chunk(mtmd_input_chunk_copy(chunk));
-            map_pos_to_image[start_pos] = std::move(new_chunk);
-        } else if (type == MTMD_INPUT_CHUNK_TYPE_TEXT) {
-            size_t n_tokens;
-            auto text_tokens = mtmd_input_chunk_get_tokens_text(chunk, &n_tokens);
-            for (size_t i = 0; i < n_tokens; ++i) {
-                push_back(text_tokens[i]);
-            }
-        } else {
-            GGML_ABORT("Invalid chunk type");
-        }
-    }
-
-    // for compatibility with context shift and prompt truncation
-    void insert(const llama_tokens & inp_tokens) {
-        GGML_ASSERT(!has_mtmd); // only allow this if mtmd is disabled
-        tokens.insert(tokens.end(), inp_tokens.begin(), inp_tokens.end());
-    }
-
-    // for compatibility with speculative decoding, ctx shift, slot save/load
-    const llama_tokens & get_text_tokens() const {
-        GGML_ASSERT(!has_mtmd); // only allow this if mtmd is disabled
-        return tokens;
-    }
-
-    // for compatibility with speculative decoding
-    void set_token(llama_pos pos, llama_token id) {
-        GGML_ASSERT(!has_mtmd); // only allow this if mtmd is disabled
-        tokens[pos] = id;
-    }
-
-    size_t size() const {
-        return tokens.size();
-    }
-
-    bool empty() const {
-        return tokens.empty();
-    }
-
-    void clear() {
-        tokens.clear();
-    }
-
-    void resize(size_t n) {
-        GGML_ASSERT(n <= tokens.size());
-        if (has_mtmd) {
-            // we throw an error if we try to remove a token in the middle of an image
-            // for ex. with input of 5 text tokens and 2 images:
-            //    [0] [1] [2] [3] [4] [img0] [img0] [img0] [img1] [img1]
-            // n  1   2   3   4   5   6      7      8      9      10
-            // allowed to resize      ^                    ^
-            // disallowed to resize          ^      ^             ^
-            if (n > 0) {
-                llama_token last_token = tokens[n - 1];
-                // make sure we never remove tokens in the middle of an image
-                if (last_token == LLAMA_TOKEN_NULL) {
-                    find_chunk(n - 1); // will throw an error if the token is not begin-of-chunk
-                }
-            }
-            // remove all image chunks that are not used anymore
-            for (auto it = map_pos_to_image.begin(); it != map_pos_to_image.end(); ) {
-                llama_pos pos = it->first;
-                if (pos >= (llama_pos)n) {
-                    it = map_pos_to_image.erase(it);
-                } else {
-                    ++it;
-                }
-            }
-        }
-        tokens.resize(n);
-    }
-
-    std::string detokenize(const llama_context * ctx, bool special) const {
-        llama_tokens text_tokens;
-        text_tokens.reserve(tokens.size());
-        for (const auto & t : tokens) {
-            if (t != LLAMA_TOKEN_NULL) {
-                text_tokens.push_back(t);
-            }
-        }
-        return common_detokenize(ctx, text_tokens, special);
-    }
-
-    size_t get_common_prefix(const server_tokens & b) const {
-        size_t max_idx = std::min(tokens.size(), b.tokens.size());
-        for (size_t i = 0; i < max_idx; ++i) {
-            auto & ai =   tokens[i];
-            auto & bi = b.tokens[i];
-
-            if (ai == LLAMA_TOKEN_NULL && bi == LLAMA_TOKEN_NULL) {
-                GGML_ASSERT(has_mtmd);
-                const auto & a_chunk =   find_chunk(i);
-                const auto & b_chunk = b.find_chunk(i);
-                GGML_ASSERT(a_chunk && b_chunk);
-                const auto * a_img = mtmd_input_chunk_get_tokens_image(a_chunk.get());
-                const auto * b_img = mtmd_input_chunk_get_tokens_image(b_chunk.get());
-                std::string ai_id  = mtmd_image_tokens_get_id(a_img);
-                std::string bi_id  = mtmd_image_tokens_get_id(b_img);
-                size_t a_pos       = mtmd_image_tokens_get_n_pos(a_img);
-                size_t b_pos       = mtmd_image_tokens_get_n_pos(b_img);
-                if (ai_id == bi_id && a_pos == b_pos) {
-                    GGML_ASSERT(a_pos > 0 && "Invalid image token"); // should never happen
-                    i += a_pos - 1; // will be +1 by the for loop
-                    continue;
-                } else {
-                    return i;
-                }
-            } else if (ai == bi) {
-                continue;
-            } else {
-                return i;
-            }
-        }
-        return max_idx; // all tokens are equal
-    }
-
-    // make sure all text tokens are within the vocab range
-    bool validate(const struct llama_context * ctx) const {
-        const llama_model * model = llama_get_model(ctx);
-        const llama_vocab * vocab = llama_model_get_vocab(model);
-        const int32_t n_vocab = llama_vocab_n_tokens(vocab);
-
-        for (size_t i = 0; i < tokens.size(); ++i) {
-            auto & t = tokens[i];
-            if (t == LLAMA_TOKEN_NULL) {
-                try {
-                    const auto & chunk = find_chunk(i);
-                    const auto * img_tokens = mtmd_input_chunk_get_tokens_image(chunk.get());
-                    size_t n_pos = mtmd_image_tokens_get_n_pos(img_tokens);
-                    i += n_pos - 1; // will be +1 by the for loop
-                } catch (const std::exception & e) {
-                    return false;
-                }
-            } else if (t < 0 || t >= n_vocab) {
-                return false;
-            }
-        }
-        return true;
-    }
-
-    // encode and decode the image chunk
-    int32_t process_chunk(
-                llama_context * ctx,
-                mtmd_context * mctx,
-                llama_pos n_past,
-                int32_t seq_id,
-                llama_pos & n_pos_out) {
-        auto it = map_pos_to_image.find(n_past);
-        if (it == map_pos_to_image.end()) {
-            throw std::runtime_error("Chunk not found");
-        }
-     //   SRV_INF("%s\n", "processing image...");
-        int32_t n_batch = llama_n_batch(ctx);
-        int64_t t0 = ggml_time_ms();
-        llama_pos new_n_past = n_past;
-        int32_t result = mtmd_helper_eval_chunk_single(mctx, ctx,
-            it->second.get(), // chunk
-            n_past,
-            seq_id,
-            n_batch,
-            true, // logits last
-            &new_n_past);
-        //SRV_INF("image processed in %" PRId64 " ms\n", ggml_time_ms() - t0);
-        if (result != 0) {
-            LOG_ERR("mtmd_helper_eval failed with status %d", result);
-            n_pos_out = n_past;
-            return result;
-        }
-        n_pos_out = new_n_past;
-        return 0;
-    }
-};
-
-// Computes FNV-1a hash of the data
-static std::string fnv_hash(const uint8_t * data, size_t len) {
-    const uint64_t fnv_prime = 0x100000001b3ULL;
-    uint64_t hash = 0xcbf29ce484222325ULL;
-
-    for (size_t i = 0; i < len; ++i) {
-        hash ^= data[i];
-        hash *= fnv_prime;
-    }
-    return std::to_string(hash);
-}

backend/go/bark-cpp/Makefile

@@ -0,0 +1,51 @@
+INCLUDE_PATH := $(abspath ./)
+LIBRARY_PATH := $(abspath ./)
+
+AR?=ar
+
+CMAKE_ARGS?=-DGGML_NATIVE=OFF
+BUILD_TYPE?=
+GOCMD=go
+# keep standard at C11 and C++11
+CXXFLAGS = -I. -I$(INCLUDE_PATH)/sources/bark.cpp/examples -I$(INCLUDE_PATH)/sources/bark.cpp/encodec.cpp/ggml/include -I$(INCLUDE_PATH)/sources/bark.cpp/spm-headers -I$(INCLUDE_PATH)/sources/bark.cpp -O3 -DNDEBUG -std=c++17 -fPIC
+LDFLAGS  = -L$(LIBRARY_PATH) -L$(LIBRARY_PATH)/sources/bark.cpp/build/examples -lbark -lstdc++ -lm
+
+# bark.cpp
+BARKCPP_REPO?=https://github.com/PABannier/bark.cpp.git
+BARKCPP_VERSION?=5d5be84f089ab9ea53b7a793f088d3fbf7247495
+
+# warnings
+CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
+
+## bark.cpp
+sources/bark.cpp:
+	git clone --recursive $(BARKCPP_REPO) sources/bark.cpp && \
+	cd sources/bark.cpp && \
+	git checkout $(BARKCPP_VERSION) && \
+	git submodule update --init --recursive --depth 1 --single-branch
+
+sources/bark.cpp/build/libbark.a: sources/bark.cpp
+	cd sources/bark.cpp && \
+	mkdir -p build && \
+	cd build && \
+	cmake $(CMAKE_ARGS) .. && \
+	cmake --build . --config Release
+
+gobark.o:
+	$(CXX) $(CXXFLAGS) gobark.cpp -o gobark.o -c $(LDFLAGS)
+
+libbark.a: sources/bark.cpp/build/libbark.a gobark.o
+	cp $(INCLUDE_PATH)/sources/bark.cpp/build/libbark.a ./
+	$(AR) rcs libbark.a gobark.o
+
+bark-cpp: libbark.a
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH="$(CURDIR)" LIBRARY_PATH=$(CURDIR) \
+	$(GOCMD) build -v -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o bark-cpp ./
+
+package:
+	bash package.sh
+
+build: bark-cpp package
+
+clean:
+	rm -f gobark.o libbark.a

backend/go/bark-cpp/gobark.cpp

@@ -48,7 +48,7 @@ int tts(char *text,int  threads, char *dst ) {
 
     // generate audio
     if (!bark_generate_audio(c, text, threads)) {
-        fprintf(stderr, "%s: An error occured. If the problem persists, feel free to open an issue to report it.\n", __func__);
+        fprintf(stderr, "%s: An error occurred. If the problem persists, feel free to open an issue to report it.\n", __func__);
         return 1;
     }
 

backend/go/bark-cpp/gobark.go

@@ -1,7 +1,7 @@
 package main
 
-// #cgo CXXFLAGS: -I${SRCDIR}/../../../sources/bark.cpp/ -I${SRCDIR}/../../../sources/bark.cpp/encodec.cpp -I${SRCDIR}/../../../sources/bark.cpp/examples -I${SRCDIR}/../../../sources/bark.cpp/spm-headers
+// #cgo CXXFLAGS: -I${SRCDIR}/sources/bark.cpp/ -I${SRCDIR}/sources/bark.cpp/encodec.cpp -I${SRCDIR}/sources/bark.cpp/encodec.cpp/ggml/include -I${SRCDIR}/sources/bark.cpp/examples -I${SRCDIR}/sources/bark.cpp/spm-headers
-// #cgo LDFLAGS: -L${SRCDIR}/ -L${SRCDIR}/../../../sources/bark.cpp/build/examples -L${SRCDIR}/../../../sources/bark.cpp/build/encodec.cpp/ -lbark -lencodec -lcommon
+// #cgo LDFLAGS: -L${SRCDIR}/ -L${SRCDIR}/sources/bark.cpp/build/examples -L${SRCDIR}/sources/bark.cpp/build/encodec.cpp/ggml/src/ -L${SRCDIR}/sources/bark.cpp/build/encodec.cpp/ -lbark -lencodec -lcommon -lggml -lgomp
 // #include <gobark.h>
 // #include <stdlib.h>
 import "C"

backend/go/bark-cpp/package.sh

@@ -0,0 +1,41 @@
+#!/bin/bash
+
+# Script to copy the appropriate libraries based on architecture
+# This script is used in the final stage of the Dockerfile
+
+set -e
+
+CURDIR=$(dirname "$(realpath $0)")
+
+# Create lib directory
+mkdir -p $CURDIR/package/lib
+cp -avrf $CURDIR/bark-cpp $CURDIR/package/
+cp -rfv $CURDIR/run.sh $CURDIR/package/
+
+# Detect architecture and copy appropriate libraries
+if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
+    # x86_64 architecture
+    echo "Detected x86_64 architecture, copying x86_64 libraries..."
+    cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
+    # ARM64 architecture
+    echo "Detected ARM64 architecture, copying ARM64 libraries..."
+    cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+else
+    echo "Error: Could not detect architecture"
+    exit 1
+fi
+
+echo "Packaging completed successfully" 
+ls -liah $CURDIR/package/
+ls -liah $CURDIR/package/lib/

backend/go/bark-cpp/run.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+set -ex
+
+CURDIR=$(dirname "$(realpath $0)")
+export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
+
+# If there is a lib/ld.so, use it
+if [ -f $CURDIR/lib/ld.so ]; then
+	echo "Using lib/ld.so"
+	exec $CURDIR/lib/ld.so $CURDIR/bark-cpp "$@"
+fi
+
+exec $CURDIR/bark-cpp "$@"

backend/go/bark/Makefile

@@ -1,25 +0,0 @@
-INCLUDE_PATH := $(abspath ./)
-LIBRARY_PATH := $(abspath ./)
-
-AR?=ar
-
-BUILD_TYPE?=
-# keep standard at C11 and C++11
-CXXFLAGS = -I. -I$(INCLUDE_PATH)/../../../sources/bark.cpp/examples -I$(INCLUDE_PATH)/../../../sources/bark.cpp/spm-headers -I$(INCLUDE_PATH)/../../../sources/bark.cpp -O3 -DNDEBUG -std=c++17 -fPIC
-LDFLAGS  = -L$(LIBRARY_PATH) -L$(LIBRARY_PATH)/../../../sources/bark.cpp/build/examples -lbark -lstdc++ -lm
-
-# warnings
-CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
-
-gobark.o:
-	$(CXX) $(CXXFLAGS) gobark.cpp -o gobark.o -c $(LDFLAGS)
-
-libbark.a: gobark.o
-	cp $(INCLUDE_PATH)/../../../sources/bark.cpp/build/libbark.a ./
-	$(AR) rcs libbark.a gobark.o
-	$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml.c.o
-	$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml-alloc.c.o
-	$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml-backend.c.o
-
-clean:
-	rm -f gobark.o libbark.a

backend/go/huggingface/Makefile

@@ -0,0 +1,9 @@
+GOCMD=go
+
+huggingface:
+	CGO_ENABLED=0 $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o huggingface ./
+
+package:
+	bash package.sh
+
+build: huggingface package

backend/go/huggingface/package.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# Script to copy the appropriate libraries based on architecture
+# This script is used in the final stage of the Dockerfile
+
+set -e
+
+CURDIR=$(dirname "$(realpath $0)")
+
+mkdir -p $CURDIR/package
+cp -avrf $CURDIR/huggingface $CURDIR/package/
+cp -rfv $CURDIR/run.sh $CURDIR/package/

backend/go/huggingface/run.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+set -ex
+
+CURDIR=$(dirname "$(realpath $0)")
+
+exec $CURDIR/huggingface "$@"

backend/go/image/stablediffusion-ggml/Makefile

@@ -1,135 +0,0 @@
-INCLUDE_PATH := $(abspath ./)
-LIBRARY_PATH := $(abspath ./)
-
-AR?=ar
-CMAKE_ARGS?=
-BUILD_TYPE?=
-ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
-# keep standard at C11 and C++11
-CXXFLAGS = -I. -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/thirdparty -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/ggml/include -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp -O3 -DNDEBUG -std=c++17 -fPIC
-
-GOCMD?=go
-CGO_LDFLAGS?=
-# Avoid parent make file overwriting CGO_LDFLAGS which is needed for hipblas
-CGO_LDFLAGS_SYCL=
-GO_TAGS?=
-LD_FLAGS?=
-
-# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
-CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
-
-# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
-ifeq ($(BUILD_TYPE),cublas)
-	CMAKE_ARGS+=-DSD_CUDA=ON
-# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-# to CMAKE_ARGS automatically
-else ifeq ($(BUILD_TYPE),openblas)
-	CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
-else ifeq ($(BUILD_TYPE),clblas)
-	CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
-# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
-else ifeq ($(BUILD_TYPE),hipblas)
-	CMAKE_ARGS+=-DSD_HIPBLAS=ON
-# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
-# But if it's OSX without metal, disable it here
-else ifeq ($(OS),Darwin)
-	ifneq ($(BUILD_TYPE),metal)
-		CMAKE_ARGS+=-DSD_METAL=OFF
-	else
-		CMAKE_ARGS+=-DSD_METAL=ON
-		CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
-		TARGET+=--target ggml-metal
-	endif
-endif
-
-ifeq ($(BUILD_TYPE),sycl_f16)
-	CMAKE_ARGS+=-DGGML_SYCL=ON \
-		-DCMAKE_C_COMPILER=icx \
-		-DCMAKE_CXX_COMPILER=icpx \
-		-DSD_SYCL=ON \
-		-DGGML_SYCL_F16=ON
-	CC=icx
-	CXX=icpx
-	CGO_LDFLAGS_SYCL += -fsycl -L${DNNLROOT}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL
-	CGO_LDFLAGS_SYCL += $(shell pkg-config --libs mkl-static-lp64-gomp)
-	CGO_CXXFLAGS += -fiopenmp -fopenmp-targets=spir64
-	CGO_CXXFLAGS += $(shell pkg-config --cflags mkl-static-lp64-gomp )
-endif
-
-ifeq ($(BUILD_TYPE),sycl_f32)
-	CMAKE_ARGS+=-DGGML_SYCL=ON \
-		-DCMAKE_C_COMPILER=icx \
-		-DCMAKE_CXX_COMPILER=icpx \
-		-DSD_SYCL=ON
-	CC=icx
-	CXX=icpx
-	CGO_LDFLAGS_SYCL += -fsycl -L${DNNLROOT}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL
-	CGO_LDFLAGS_SYCL += $(shell pkg-config --libs mkl-static-lp64-gomp)
-	CGO_CXXFLAGS += -fiopenmp -fopenmp-targets=spir64
-	CGO_CXXFLAGS += $(shell pkg-config --cflags mkl-static-lp64-gomp )
-endif
-
-# warnings
-# CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
-
-# Find all .a archives in ARCHIVE_DIR
-# (ggml can have different backends cpu, cuda, etc., each backend generates a .a archive)
-GGML_ARCHIVE_DIR := build/ggml/src/
-ALL_ARCHIVES := $(shell find $(GGML_ARCHIVE_DIR) -type f -name '*.a')
-
-# Name of the single merged library
-COMBINED_LIB := libggmlall.a
-
-# Rule to merge all the .a files into one
-$(COMBINED_LIB): $(ALL_ARCHIVES)
-	@echo "Merging all .a into $(COMBINED_LIB)"
-	rm -f $@
-	mkdir -p merge-tmp
-	for a in $(ALL_ARCHIVES); do \
-		( cd merge-tmp && ar x ../$$a ); \
-	done
-	( cd merge-tmp && ar rcs ../$@ *.o )
-	# Ensure we have a proper index
-	ranlib $@
-	# Clean up
-	rm -rf merge-tmp
-
-build/libstable-diffusion.a:
-	@echo "Building SD with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-	+bash -c "source $(ONEAPI_VARS); \
-	mkdir -p build && \
-	cd build && \
-	cmake $(CMAKE_ARGS) ../../../../../sources/stablediffusion-ggml.cpp && \
-	cmake --build . --config Release"
-else
-	mkdir -p build && \
-	cd build && \
-	cmake $(CMAKE_ARGS) ../../../../../sources/stablediffusion-ggml.cpp && \
-	cmake --build . --config Release
-endif
-	$(MAKE) $(COMBINED_LIB)
-
-gosd.o:
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-	+bash -c "source $(ONEAPI_VARS); \
-	$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c"
-else
-	$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c
-endif
-
-libsd.a: gosd.o
-	cp $(INCLUDE_PATH)/build/libstable-diffusion.a ./libsd.a
-	$(AR) rcs libsd.a gosd.o
-
-stablediffusion-ggml:
-	CGO_LDFLAGS="$(CGO_LDFLAGS) $(CGO_LDFLAGS_SYCL)" C_INCLUDE_PATH="$(INCLUDE_PATH)" LIBRARY_PATH="$(LIBRARY_PATH)" \
-	CC="$(CC)" CXX="$(CXX)" CGO_CXXFLAGS="$(CGO_CXXFLAGS)" \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o ../../../../backend-assets/grpc/stablediffusion-ggml ./
-ifneq ($(UPX),)
-	$(UPX) ../../../../backend-assets/grpc/stablediffusion-ggml
-endif
-
-clean:
-	rm -rf gosd.o libsd.a build $(COMBINED_LIB)

backend/go/image/stablediffusion-ggml/gosd.cpp

@@ -1,231 +0,0 @@
-#include <stdio.h>
-#include <string.h>
-#include <time.h>
-#include <iostream>
-#include <random>
-#include <string>
-#include <vector>
-#include "gosd.h"
-
-// #include "preprocessing.hpp"
-#include "flux.hpp"
-#include "stable-diffusion.h"
-
-#define STB_IMAGE_IMPLEMENTATION
-#define STB_IMAGE_STATIC
-#include "stb_image.h"
-
-#define STB_IMAGE_WRITE_IMPLEMENTATION
-#define STB_IMAGE_WRITE_STATIC
-#include "stb_image_write.h"
-
-#define STB_IMAGE_RESIZE_IMPLEMENTATION
-#define STB_IMAGE_RESIZE_STATIC
-#include "stb_image_resize.h"
-
-// Names of the sampler method, same order as enum sample_method in stable-diffusion.h
-const char* sample_method_str[] = {
-    "euler_a",
-    "euler",
-    "heun",
-    "dpm2",
-    "dpm++2s_a",
-    "dpm++2m",
-    "dpm++2mv2",
-    "ipndm",
-    "ipndm_v",
-    "lcm",
-    "ddim_trailing",
-    "tcd",
-};
-
-// Names of the sigma schedule overrides, same order as sample_schedule in stable-diffusion.h
-const char* schedule_str[] = {
-    "default",
-    "discrete",
-    "karras",
-    "exponential",
-    "ays",
-    "gits",
-};
-
-sd_ctx_t* sd_c;
-
-sample_method_t sample_method;
-
-int load_model(char *model, char* options[], int threads, int diff) {
-    fprintf (stderr, "Loading model!\n");
-
-    char *stableDiffusionModel = "";
-    if (diff == 1 ) {
-        stableDiffusionModel = model;
-        model = "";
-    }
-
-    // decode options. Options are in form optname:optvale, or if booleans only optname.
-    char *clip_l_path  = "";
-    char *clip_g_path  = "";
-    char *t5xxl_path  = "";
-    char *vae_path  = "";
-    char *scheduler = "";
-    char *sampler = "";
-
-    // If options is not NULL, parse options
-    for (int i = 0; options[i] != NULL; i++) {
-        char *optname = strtok(options[i], ":");
-        char *optval = strtok(NULL, ":");
-        if (optval == NULL) {
-            optval = "true";
-        }
-
-        if (!strcmp(optname, "clip_l_path")) {
-            clip_l_path = optval;
-        }
-        if (!strcmp(optname, "clip_g_path")) {
-            clip_g_path = optval;
-        }
-        if (!strcmp(optname, "t5xxl_path")) {
-            t5xxl_path = optval;
-        }
-        if (!strcmp(optname, "vae_path")) {
-            vae_path = optval;
-        }
-        if (!strcmp(optname, "scheduler")) {
-            scheduler = optval;
-        }
-        if (!strcmp(optname, "sampler")) {
-            sampler = optval;
-        }
-    }
-
-    int sample_method_found = -1;
-    for (int m = 0; m < N_SAMPLE_METHODS; m++) {
-        if (!strcmp(sampler, sample_method_str[m])) {
-            sample_method_found = m;
-        }
-    }
-    if (sample_method_found == -1) {
-        fprintf(stderr, "Invalid sample method, default to EULER_A!\n");
-        sample_method_found = EULER_A;
-    }
-    sample_method = (sample_method_t)sample_method_found;
-
-    int schedule_found            = -1;
-    for (int d = 0; d < N_SCHEDULES; d++) {
-        if (!strcmp(scheduler, schedule_str[d])) {
-            schedule_found = d;
-                fprintf (stderr, "Found scheduler: %s\n", scheduler);
-
-        }
-    }
-
-    if (schedule_found == -1) {
-        fprintf (stderr, "Invalid scheduler! using DEFAULT\n");
-        schedule_found = DEFAULT;
-    }
-
-    schedule_t schedule = (schedule_t)schedule_found;
-    
-    fprintf (stderr, "Creating context\n");
-    sd_ctx_t* sd_ctx = new_sd_ctx(model,
-                                  clip_l_path,
-                                  clip_g_path,
-                                  t5xxl_path,
-                                  stableDiffusionModel,
-                                  vae_path,
-                                  "",
-                                  "",
-                                  "",
-                                  "",
-                                  "",
-                                  false,
-                                  false,
-                                  false,
-                                  threads,
-                                  SD_TYPE_COUNT,
-                                  STD_DEFAULT_RNG,
-                                  schedule,
-                                  false,
-                                  false,
-                                  false,
-                                  false);
-
-    if (sd_ctx == NULL) {
-        fprintf (stderr, "failed loading model (generic error)\n");
-        return 1;
-    }
-    fprintf (stderr, "Created context: OK\n");
-
-    sd_c = sd_ctx;
-
-    return 0;
-}
-
-int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed , char *dst, float cfg_scale) {
-
-    sd_image_t* results;
-
-    std::vector<int> skip_layers = {7, 8, 9};
-
-    fprintf (stderr, "Generating image\n");
-
-    results = txt2img(sd_c,
-                            text,
-                            negativeText,
-                            -1, //clip_skip
-                            cfg_scale, // sfg_scale
-                            3.5f,
-			    0, // eta
-                            width,
-                            height,
-                            sample_method, 
-                            steps,
-                            seed,
-                            1,
-                            NULL,
-                            0.9f,
-                            20.f,
-                            false,
-                            "",
-                            skip_layers.data(),
-                            skip_layers.size(),
-                            0,
-                            0.01,
-                            0.2);
-
-    if (results == NULL) {
-        fprintf (stderr, "NO results\n");
-        return 1;
-    }
-
-    if (results[0].data == NULL) {
-        fprintf (stderr, "Results with no data\n");
-        return 1;
-    }
-
-    fprintf (stderr, "Writing PNG\n");
-
-    fprintf (stderr, "DST: %s\n", dst);
-    fprintf (stderr, "Width: %d\n", results[0].width);
-    fprintf (stderr, "Height: %d\n", results[0].height);
-    fprintf (stderr, "Channel: %d\n", results[0].channel);
-    fprintf (stderr, "Data: %p\n", results[0].data);
-
-    stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
-                       results[0].data, 0, NULL);
-    fprintf (stderr, "Saved resulting image to '%s'\n", dst);
-
-    // TODO: free results. Why does it crash?
-
-    free(results[0].data);
-    results[0].data = NULL;
-    free(results);
-    fprintf (stderr, "gen_image is done", dst);
-
-    return 0;
-}
-
-int unload() {
-    free_sd_ctx(sd_c);
-}
-

backend/go/image/stablediffusion-ggml/gosd.go

@@ -1,96 +0,0 @@
-package main
-
-// #cgo CXXFLAGS: -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/thirdparty -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/ggml/include
-// #cgo LDFLAGS: -L${SRCDIR}/ -lsd -lstdc++ -lm -lggmlall -lgomp
-// #include <gosd.h>
-// #include <stdlib.h>
-import "C"
-
-import (
-	"fmt"
-	"os"
-	"path/filepath"
-	"strings"
-	"unsafe"
-
-	"github.com/mudler/LocalAI/pkg/grpc/base"
-	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
-	"github.com/mudler/LocalAI/pkg/utils"
-)
-
-type SDGGML struct {
-	base.SingleThread
-	threads      int
-	sampleMethod string
-	cfgScale     float32
-}
-
-func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
-
-	sd.threads = int(opts.Threads)
-
-	modelFile := C.CString(opts.ModelFile)
-	defer C.free(unsafe.Pointer(modelFile))
-
-	var options **C.char
-	// prepare the options array to pass to C
-
-	size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
-	length := C.size_t(len(opts.Options))
-	options = (**C.char)(C.malloc(length * size))
-	view := (*[1 << 30]*C.char)(unsafe.Pointer(options))[0:len(opts.Options):len(opts.Options)]
-
-	var diffusionModel int
-
-	var oo []string
-	for _, op := range opts.Options {
-		if op == "diffusion_model" {
-			diffusionModel = 1
-			continue
-		}
-
-		// If it's an option path, we resolve absolute path from the model path
-		if strings.Contains(op, ":") && strings.Contains(op, "path") {
-			data := strings.Split(op, ":")
-			data[1] = filepath.Join(opts.ModelPath, data[1])
-			if err := utils.VerifyPath(data[1], opts.ModelPath); err == nil {
-				oo = append(oo, strings.Join(data, ":"))
-			}
-		} else {
-			oo = append(oo, op)
-		}
-	}
-
-	fmt.Fprintf(os.Stderr, "Options: %+v\n", oo)
-
-	for i, x := range oo {
-		view[i] = C.CString(x)
-	}
-
-	sd.cfgScale = opts.CFGScale
-
-	ret := C.load_model(modelFile, options, C.int(opts.Threads), C.int(diffusionModel))
-	if ret != 0 {
-		return fmt.Errorf("could not load model")
-	}
-
-	return nil
-}
-
-func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
-	t := C.CString(opts.PositivePrompt)
-	defer C.free(unsafe.Pointer(t))
-
-	dst := C.CString(opts.Dst)
-	defer C.free(unsafe.Pointer(dst))
-
-	negative := C.CString(opts.NegativePrompt)
-	defer C.free(unsafe.Pointer(negative))
-
-	ret := C.gen_image(t, negative, C.int(opts.Width), C.int(opts.Height), C.int(opts.Step), C.int(opts.Seed), dst, C.float(sd.cfgScale))
-	if ret != 0 {
-		return fmt.Errorf("inference failed")
-	}
-
-	return nil
-}

backend/go/image/stablediffusion-ggml/gosd.h

@@ -1,8 +0,0 @@
-#ifdef __cplusplus
-extern "C" {
-#endif
-int load_model(char *model, char* options[], int threads, int diffusionModel);
-int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed, char *dst, float cfg_scale);
-#ifdef __cplusplus
-}
-#endif

backend/go/llm/llama/llama.go

@@ -58,6 +58,9 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
 	if opts.Embeddings {
 		llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
 	}
+	if opts.Reranking {
+		llamaOpts = append(llamaOpts, llama.EnableReranking)
+	}
 	if opts.NGPULayers != 0 {
 		llamaOpts = append(llamaOpts, llama.SetGPULayers(int(opts.NGPULayers)))
 	}

backend/go/local-store/Makefile

@@ -0,0 +1,9 @@
+GOCMD=go
+
+local-store:
+	CGO_ENABLED=0 $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o local-store ./
+
+package:
+	bash package.sh
+
+build: local-store package

backend/go/local-store/package.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# Script to copy the appropriate libraries based on architecture
+# This script is used in the final stage of the Dockerfile
+
+set -e
+
+CURDIR=$(dirname "$(realpath $0)")
+
+mkdir -p $CURDIR/package
+cp -avrf $CURDIR/local-store $CURDIR/package/
+cp -rfv $CURDIR/run.sh $CURDIR/package/

backend/go/local-store/run.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+set -ex
+
+CURDIR=$(dirname "$(realpath $0)")
+
+exec $CURDIR/local-store "$@"

backend/go/local-store/store.go

@@ -4,6 +4,7 @@ package main
 // It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
 import (
 	"container/heap"
+	"errors"
 	"fmt"
 	"math"
 	"slices"
@@ -99,6 +100,9 @@ func sortIntoKeySlicese(keys []*pb.StoresKey) [][]float32 {
 }
 
 func (s *Store) Load(opts *pb.ModelOptions) error {
+	if opts.Model != "" {
+		return errors.New("not implemented")
+	}
 	return nil
 }
 
@@ -315,7 +319,7 @@ func isNormalized(k []float32) bool {
 
 	for _, v := range k {
 		v64 := float64(v)
-		sum += v64*v64
+		sum += v64 * v64
 	}
 
 	s := math.Sqrt(sum)

backend/go/piper/Makefile

@@ -0,0 +1,37 @@
+
+# go-piper version
+PIPER_REPO?=https://github.com/mudler/go-piper
+PIPER_VERSION?=e10ca041a885d4a8f3871d52924b47792d5e5aa0
+
+CURRENT_DIR=$(abspath ./)
+GOCMD=go
+
+PIPER_CGO_CXXFLAGS+=-I$(CURRENT_DIR)/sources/go-piper/piper/src/cpp -I$(CURRENT_DIR)/sources/go-piper/piper/build/fi/include -I$(CURRENT_DIR)/sources/go-piper/piper/build/pi/include -I$(CURRENT_DIR)/sources/go-piper/piper/build/si/include
+PIPER_CGO_LDFLAGS+=-L$(CURRENT_DIR)/sources/go-piper/piper/build/fi/lib -L$(CURRENT_DIR)/sources/go-piper/piper/build/pi/lib -L$(CURRENT_DIR)/sources/go-piper/piper/build/si/lib -lfmt -lspdlog -lucd
+
+## go-piper
+sources/go-piper:
+	mkdir -p sources/go-piper
+	cd sources/go-piper && \
+	git init && \
+	git remote add origin $(PIPER_REPO) && \
+	git fetch origin && \
+	git checkout $(PIPER_VERSION) && \
+	git submodule update --init --recursive --depth 1 --single-branch
+
+sources/go-piper/libpiper_binding.a: sources/go-piper
+	$(MAKE) -C sources/go-piper libpiper_binding.a example/main piper.o
+
+espeak-ng-data: sources/go-piper sources/go-piper/libpiper_binding.a
+	mkdir -p espeak-ng-data
+	@cp -rf sources/go-piper/piper-phonemize/pi/share/espeak-ng-data/. espeak-ng-data
+
+piper: sources/go-piper sources/go-piper/libpiper_binding.a espeak-ng-data
+	$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(CURRENT_DIR)/sources/go-piper
+	CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(CURRENT_DIR)/sources/go-piper \
+	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o piper ./
+
+package:
+	bash package.sh
+
+build: piper package

backend/go/piper/package.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+
+# Script to copy the appropriate libraries based on architecture
+# This script is used in the final stage of the Dockerfile
+
+set -e
+
+CURDIR=$(dirname "$(realpath $0)")
+
+# Create lib directory
+mkdir -p $CURDIR/package/lib
+
+cp -avrf $CURDIR/piper $CURDIR/package/
+cp -avrf $CURDIR/espeak-ng-data $CURDIR/package/
+cp -rfv $CURDIR/run.sh $CURDIR/package/
+cp -rfLv $CURDIR/sources/go-piper/piper-phonemize/pi/lib/* $CURDIR/package/lib/
+
+# Detect architecture and copy appropriate libraries
+if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
+    # x86_64 architecture
+    echo "Detected x86_64 architecture, copying x86_64 libraries..."
+    cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
+    cp -arfLv /lib/x86_64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
+elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
+    # ARM64 architecture
+    echo "Detected ARM64 architecture, copying ARM64 libraries..."
+    cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
+    cp -arfLv /lib/aarch64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
+else
+    echo "Error: Could not detect architecture"
+    exit 1
+fi
+
+echo "Packaging completed successfully" 
+ls -liah $CURDIR/package/
+ls -liah $CURDIR/package/lib/