chore(gosec): fix CI

downgrade to latest known version of the gosec action

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

.devcontainer-scripts/utils.sh

@@ -9,7 +9,6 @@
 # Param 2: email
 #
 config_user() {
-    echo "Configuring git for $1 <$2>"
     local gcn=$(git config --global user.name)
     if [ -z "${gcn}" ]; then
         echo "Setting up git user / remote"
@@ -25,7 +24,6 @@ config_user() {
 # Param 2: remote url
 #
 config_remote() {
-    echo "Adding git remote and fetching $2 as $1"
     local gr=$(git remote -v | grep $1)
     if [ -z "${gr}" ]; then
         git remote add $1 $2

.github/check_and_update.py

@@ -29,14 +29,9 @@ def calculate_sha256(file_path):
 def manual_safety_check_hf(repo_id):
     scanResponse = requests.get('https://huggingface.co/api/models/' + repo_id + "/scan")
     scan = scanResponse.json()
-    # Check if 'hasUnsafeFile' exists in the response
+    if scan['hasUnsafeFile']:
-    if 'hasUnsafeFile' in scan:
+        return scan
-        if scan['hasUnsafeFile']:
+    return None
-            return scan
-        else:
-            return None
-    else:
-        return None
 
 download_type, repo_id_or_url = parse_uri(uri)
 

.github/ci/modelslist.go

@@ -6,7 +6,6 @@ import (
 	"io/ioutil"
 	"os"
 
-	"github.com/microcosm-cc/bluemonday"
 	"gopkg.in/yaml.v3"
 )
 
@@ -280,12 +279,6 @@ func main() {
 		return
 	}
 
-	// Ensure that all arbitrary text content is sanitized before display
-	for i, m := range models {
-		models[i].Name = bluemonday.StrictPolicy().Sanitize(m.Name)
-		models[i].Description = bluemonday.StrictPolicy().Sanitize(m.Description)
-	}
-
 	// render the template
 	data := struct {
 		Models          []*GalleryModel

.github/dependabot.yml

@@ -9,8 +9,6 @@ updates:
     directory: "/"
     schedule:
       interval: "weekly"
-    ignore:
-    - dependency-name: "github.com/mudler/LocalAI/pkg/grpc/proto"
   - package-ecosystem: "github-actions"
     # Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
     directory: "/"

.github/workflows/deploy-explorer.yaml

@@ -33,7 +33,7 @@ jobs:
         run: |
           CGO_ENABLED=0 make build-api
       - name: rm
-        uses: appleboy/ssh-action@v1.1.0
+        uses: appleboy/ssh-action@v1.0.3
         with:
             host: ${{ secrets.EXPLORER_SSH_HOST }}
             username: ${{ secrets.EXPLORER_SSH_USERNAME }}
@@ -53,7 +53,7 @@ jobs:
             rm: true
             target: ./local-ai
       - name: restarting
-        uses: appleboy/ssh-action@v1.1.0
+        uses: appleboy/ssh-action@v1.0.3
         with:
             host: ${{ secrets.EXPLORER_SSH_HOST }}
             username: ${{ secrets.EXPLORER_SSH_USERNAME }}

.github/workflows/image.yml

@@ -13,78 +13,6 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  hipblas-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: 2
-      matrix:
-        include:
-          - build-type: 'hipblas'
-            platforms: 'linux/amd64'
-            tag-latest: 'auto'
-            tag-suffix: '-hipblas-ffmpeg'
-            ffmpeg: 'true'
-            image-type: 'extras'
-            aio: "-aio-gpu-hipblas"
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
-            grpc-base-image: "ubuntu:22.04"
-            latest-image: 'latest-gpu-hipblas'
-            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: 'false'
-            image-type: 'extras'
-            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"
-          - build-type: 'hipblas'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            tag-suffix: '-hipblas-ffmpeg-core'
-            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"
-          - build-type: 'hipblas'
-            platforms: 'linux/amd64'
-            tag-latest: 'false'
-            tag-suffix: '-hipblas-core'
-            ffmpeg: 'false'
-            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"
   self-hosted-jobs:
     uses: ./.github/workflows/image_build.yml
     with:
@@ -111,7 +39,7 @@ jobs:
     strategy:
       # Pushing with all jobs in parallel
       # eats the bandwidth of all the nodes
-      max-parallel: ${{ github.event_name != 'pull_request' && 5 || 8 }}
+      max-parallel: ${{ github.event_name != 'pull_request' && 6 || 10 }}
       matrix:
         include:
           # Extra images
@@ -194,6 +122,29 @@ jobs:
             base-image: "ubuntu:22.04"
             runs-on: 'arc-runner-set'
             makeflags: "--jobs=3 --output-sync=target"
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-hipblas-ffmpeg'
+            ffmpeg: 'true'
+            image-type: 'extras'
+            aio: "-aio-gpu-hipblas"
+            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            grpc-base-image: "ubuntu:22.04"
+            latest-image: 'latest-gpu-hipblas'
+            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: 'false'
+            image-type: 'extras'
+            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"
           - build-type: 'sycl_f16'
             platforms: 'linux/amd64'
             tag-latest: 'auto'
@@ -261,6 +212,26 @@ jobs:
             image-type: 'core'
             runs-on: 'arc-runner-set'
             makeflags: "--jobs=3 --output-sync=target"
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas-ffmpeg-core'
+            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"
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas-core'
+            ffmpeg: 'false'
+            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"
 
   core-image-build:
     uses: ./.github/workflows/image_build.yml

.github/workflows/notify-models.yaml

@@ -79,7 +79,7 @@ jobs:
         args: ${{ steps.summarize.outputs.message }}
     - name: Setup tmate session if fails
       if: ${{ failure() }}
-      uses: mxschmitt/action-tmate@v3.19
+      uses: mxschmitt/action-tmate@v3.18
       with:
         detached: true
         connect-timeout-seconds: 180
@@ -161,7 +161,7 @@ jobs:
         TWITTER_ACCESS_TOKEN_SECRET: ${{ secrets.TWITTER_ACCESS_TOKEN_SECRET }}
     - name: Setup tmate session if fails
       if: ${{ failure() }}
-      uses: mxschmitt/action-tmate@v3.19
+      uses: mxschmitt/action-tmate@v3.18
       with:
         detached: true
         connect-timeout-seconds: 180

.github/workflows/release.yaml

@@ -123,7 +123,7 @@ jobs:
             release/*
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -232,7 +232,7 @@ jobs:
             release/*
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -308,7 +308,7 @@ jobs:
             release/*
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -350,7 +350,7 @@ jobs:
             release/*
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180

.github/workflows/secscan.yaml

@@ -18,7 +18,7 @@ jobs:
         if: ${{ github.actor != 'dependabot[bot]' }}
       - name: Run Gosec Security Scanner
         if: ${{ github.actor != 'dependabot[bot]' }}
-        uses: securego/gosec@v2.21.4
+        uses: securego/gosec@v2.21.0
         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/test-extra.yml

@@ -105,14 +105,6 @@ jobs:
   tests-parler-tts:
     runs-on: ubuntu-latest
     steps:
-      - 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: Clone
         uses: actions/checkout@v4
         with:

.github/workflows/test.yml

@@ -133,7 +133,7 @@ jobs:
           PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -178,26 +178,17 @@ jobs:
         uses: actions/checkout@v4
         with:
           submodules: true
-      - name: Dependencies
-        run: |
-          # Install protoc
-          curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
-          unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-          rm protoc.zip
-          go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
-          go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
-          PATH="$PATH:$HOME/go/bin" make protogen-go
       - name: Build images
         run: |
           docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
           BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
       - name: Test
         run: |
-            PATH="$PATH:$HOME/go/bin" LOCALAI_MODELS_DIR=$PWD/models LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio \
+          LOCALAI_MODELS_DIR=$PWD/models LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio \
             make run-e2e-aio
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -235,7 +226,7 @@ jobs:
           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@v3.19
+        uses: mxschmitt/action-tmate@v3.18
         with:
           detached: true
           connect-timeout-seconds: 180

CONTRIBUTING.md

@@ -15,6 +15,8 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
 - [Documentation](#documentation)
 - [Community and Communication](#community-and-communication)
 
+
+
 ## Getting Started
 
 ### Prerequisites
@@ -52,7 +54,7 @@ If you find a bug, have a feature request, or encounter any issues, please check
 
 ## Coding Guidelines
 
-- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like [`golangci-lint`](https://golangci-lint.run) can help you here.
+- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like []`golangci-lint`](https://golangci-lint.run) can help you here.
 
 ## Testing
 
@@ -82,3 +84,5 @@ We are welcome the contribution of the documents, please open new PR or create a
 - You can reach out via the Github issue tracker.
 - Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
 - Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
+
+---

Dockerfile

@@ -9,8 +9,6 @@ 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
 
@@ -23,25 +21,13 @@ RUN apt-get update && \
         build-essential \
         ccache \
         ca-certificates \
-        curl libssl-dev \
+        cmake \
+        curl \
         git \
         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
@@ -202,8 +188,6 @@ 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}
 
@@ -212,24 +196,12 @@ WORKDIR /build
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         ca-certificates \
-        build-essential curl libssl-dev \
+        build-essential \
+        cmake \
         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
@@ -325,10 +297,10 @@ COPY .git .
 RUN make prepare
 
 ## Build the binary
-## If it's CUDA or hipblas, we want to skip some of the llama-compat backends to save space
+## If it's CUDA, we want to skip some of the llama-compat backends to save space
-## We only leave the most CPU-optimized variant and the fallback for the cublas/hipblas build
+## We only leave the most CPU-optimized variant and the fallback for the cublas build
-## (both will use CUDA or hipblas for the actual computation)
+## (both will use CUDA for the actual computation)
-RUN if [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
+RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
         SKIP_GRPC_BACKEND="backend-assets/grpc/llama-cpp-avx backend-assets/grpc/llama-cpp-avx2" make build; \
     else \
         make build; \
@@ -366,8 +338,9 @@ RUN if [ "${FFMPEG}" = "true" ]; then \
 
 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.
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
 
 RUN go install github.com/go-delve/delve/cmd/dlv@latest
 

Makefile

@@ -8,7 +8,7 @@ DETECT_LIBS?=true
 # llama.cpp versions
 GOLLAMA_REPO?=https://github.com/go-skynet/go-llama.cpp
 GOLLAMA_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
-CPPLLAMA_VERSION?=0a1c750c80147687df267114c81956757cc14382
+CPPLLAMA_VERSION?=e6b7801bd189d102d901d3e72035611a25456ef1
 
 # go-rwkv version
 RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
@@ -16,7 +16,7 @@ RWKV_VERSION?=661e7ae26d442f5cfebd2a0881b44e8c55949ec6
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggerganov/whisper.cpp
-WHISPER_CPP_VERSION?=0fbaac9c891055796456df7b9122a70c220f9ca1
+WHISPER_CPP_VERSION?=a551933542d956ae84634937acd2942eb40efaaf
 
 # bert.cpp version
 BERT_REPO?=https://github.com/go-skynet/go-bert.cpp
@@ -359,9 +359,6 @@ clean-tests:
 	rm -rf test-dir
 	rm -rf core/http/backend-assets
 
-clean-dc: clean
-	cp -r /build/backend-assets /workspace/backend-assets
-
 ## Build:
 build: prepare backend-assets grpcs ## Build the project
 	$(info ${GREEN}I local-ai build info:${RESET})
@@ -468,15 +465,15 @@ run-e2e-image:
 	ls -liah $(abspath ./tests/e2e-fixtures)
 	docker run -p 5390:8080 -e MODELS_PATH=/models -e THREADS=1 -e DEBUG=true -d --rm -v $(TEST_DIR):/models --gpus all --name e2e-tests-$(RANDOM) localai-tests
 
-run-e2e-aio: protogen-go
+run-e2e-aio:
 	@echo 'Running e2e AIO tests'
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e-aio
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts 5 -v -r ./tests/e2e-aio
 
 test-e2e:
 	@echo 'Running e2e tests'
 	BUILD_TYPE=$(BUILD_TYPE) \
 	LOCALAI_API=http://$(E2E_BRIDGE_IP):5390/v1 \
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts 5 -v -r ./tests/e2e
 
 teardown-e2e:
 	rm -rf $(TEST_DIR) || true
@@ -484,24 +481,24 @@ teardown-e2e:
 
 test-llama: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r $(TEST_PATHS)
 
 test-llama-gguf: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r $(TEST_PATHS)
 
 test-tts: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r $(TEST_PATHS)
 
 test-stablediffusion: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r $(TEST_PATHS)
 
 test-stores: backend-assets/grpc/local-store
 	mkdir -p tests/integration/backend-assets/grpc
 	cp -f backend-assets/grpc/local-store tests/integration/backend-assets/grpc/
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stores" --flake-attempts $(TEST_FLAKES) -v -r tests/integration
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stores" --flake-attempts 1 -v -r tests/integration
 
 test-container:
 	docker build --target requirements -t local-ai-test-container .

README.md

@@ -66,24 +66,11 @@ docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
 # docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12 
 ```
 
-To load models:
-
-```bash
-# From the model gallery (see available models with `local-ai models list`, in the WebUI from the model tab, or visiting https://models.localai.io)
-local-ai run llama-3.2-1b-instruct:q4_k_m
-# Start LocalAI with the phi-2 model directly from huggingface
-local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
-# Install and run a model from the Ollama OCI registry
-local-ai run ollama://gemma:2b
-# Run a model from a configuration file
-local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
-# Install and run a model from a standard OCI registry (e.g., Docker Hub)
-local-ai run oci://localai/phi-2:latest
-```
-
 [💻 Getting started](https://localai.io/basics/getting_started/index.html)
 
-## 📰 Latest project news
+## 🔥🔥 Hot topics / Roadmap
+
+[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
 
 - Aug 2024:  🆕 FLUX-1, [P2P Explorer](https://explorer.localai.io)
 - July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723
@@ -96,12 +83,8 @@ local-ai run oci://localai/phi-2:latest
 - May 2024: Chat, TTS, and Image generation in the WebUI: https://github.com/mudler/LocalAI/pull/2222
 - April 2024: Reranker API: https://github.com/mudler/LocalAI/pull/2121
 
-Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
+Hot topics (looking for contributors):
 
-## 🔥🔥 Hot topics (looking for help):
-
-- Multimodal with vLLM and Video understanding: https://github.com/mudler/LocalAI/pull/3729
-- Realtime API https://github.com/mudler/LocalAI/issues/3714
 - 🔥🔥 Distributed, P2P Global community pools: https://github.com/mudler/LocalAI/issues/3113
 - WebUI improvements: https://github.com/mudler/LocalAI/issues/2156
 - Backends v2: https://github.com/mudler/LocalAI/issues/1126

aio/cpu/vision.yaml

@@ -2,7 +2,7 @@ backend: llama-cpp
 context_size: 4096
 f16: true
 mmap: true
-name: gpt-4o
+name: gpt-4-vision-preview
 
 roles:
   user: "USER:"

aio/gpu-8g/vision.yaml

@@ -2,7 +2,7 @@ backend: llama-cpp
 context_size: 4096
 f16: true
 mmap: true
-name: gpt-4o
+name: gpt-4-vision-preview
 
 roles:
   user: "USER:"

aio/intel/vision.yaml

@@ -2,7 +2,7 @@ backend: llama-cpp
 context_size: 4096
 mmap: false
 f16: false
-name: gpt-4o
+name: gpt-4-vision-preview
 
 roles:
   user: "USER:"

backend/backend.proto

@@ -26,19 +26,6 @@ service Backend {
   rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
 
   rpc Rerank(RerankRequest) returns (RerankResult) {}
-
-  rpc GetMetrics(MetricsRequest) returns (MetricsResponse);
-}
-
-// Define the empty request
-message MetricsRequest {}
-
-message MetricsResponse {
-  int32 slot_id = 1;
-  string prompt_json_for_slot = 2;  // Stores the prompt as a JSON string.
-  float tokens_per_second = 3;
-  int32 tokens_generated = 4;
-  int32 prompt_tokens_processed = 5;
 }
 
 message RerankRequest {
@@ -147,9 +134,6 @@ message PredictOptions {
   repeated string Images = 42;
   bool UseTokenizerTemplate = 43;
   repeated Message Messages = 44;
-  repeated string Videos = 45;
-  repeated string Audios = 46;
-  string CorrelationId = 47;
 }
 
 // The response message containing the result
@@ -219,7 +203,6 @@ message ModelOptions {
   int32  SwapSpace = 53;
   int32  MaxModelLen = 54;
   int32  TensorParallelSize = 55;
-  string LoadFormat = 58;
 
   string MMProj = 41;
 

backend/cpp/llama/grpc-server.cpp

@@ -13,7 +13,6 @@
 #include <getopt.h>
 #include "clip.h"
 #include "llava.h"
-#include "log.h"
 #include "stb_image.h"
 #include "common.h"
 #include "json.hpp"
@@ -113,7 +112,7 @@ static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
     std::string ret;
     for (; begin != end; ++begin)
     {
-        ret += common_token_to_piece(ctx, *begin);
+        ret += llama_token_to_piece(ctx, *begin);
     }
     return ret;
 }
@@ -121,7 +120,7 @@ static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
 // format incomplete utf-8 multibyte character for output
 static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
 {
-    std::string out = token == -1 ? "" : common_token_to_piece(ctx, token);
+    std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
     // if the size is 1 and first bit is 1, meaning it's a partial character
     //   (size > 1 meaning it's already a known token)
     if (out.size() == 1 && (out[0] & 0x80) == 0x80)
@@ -203,8 +202,8 @@ struct llama_client_slot
     std::string stopping_word;
 
     // sampling
-    struct common_sampler_params sparams;
+    struct gpt_sampler_params sparams;
-    common_sampler *ctx_sampling = nullptr;
+    gpt_sampler *ctx_sampling = nullptr;
 
     int32_t ga_i = 0;   // group-attention state
     int32_t ga_n = 1;   // group-attention factor
@@ -257,7 +256,7 @@ struct llama_client_slot
         images.clear();
     }
 
-    bool has_budget(common_params &global_params) {
+    bool has_budget(gpt_params &global_params) {
         if (params.n_predict == -1 && global_params.n_predict == -1)
         {
             return true; // limitless
@@ -391,39 +390,6 @@ struct llama_metrics {
     }
 };
 
-struct llava_embd_batch {
-    std::vector<llama_pos>      pos;
-    std::vector<int32_t>        n_seq_id;
-    std::vector<llama_seq_id>   seq_id_0;
-    std::vector<llama_seq_id *> seq_ids;
-    std::vector<int8_t>         logits;
-    llama_batch batch;
-    llava_embd_batch(float * embd, int32_t n_tokens, llama_pos pos_0, llama_seq_id seq_id) {
-        pos     .resize(n_tokens);
-        n_seq_id.resize(n_tokens);
-        seq_ids .resize(n_tokens + 1);
-        logits  .resize(n_tokens);
-        seq_id_0.resize(1);
-        seq_id_0[0] = seq_id;
-        seq_ids [n_tokens] = nullptr;
-        batch = {
-            /*n_tokens       =*/ n_tokens,
-            /*tokens         =*/ nullptr,
-            /*embd           =*/ embd,
-            /*pos            =*/ pos.data(),
-            /*n_seq_id       =*/ n_seq_id.data(),
-            /*seq_id         =*/ seq_ids.data(),
-            /*logits         =*/ logits.data(),
-        };
-        for (int i = 0; i < n_tokens; i++) {
-            batch.pos     [i] = pos_0 + i;
-            batch.n_seq_id[i] = 1;
-            batch.seq_id  [i] = seq_id_0.data();
-            batch.logits  [i] = false;
-        }
-    }
-};
-
 struct llama_server_context
 {
     llama_model *model = nullptr;
@@ -431,7 +397,7 @@ struct llama_server_context
 
     clip_ctx *clp_ctx = nullptr;
 
-    common_params params;
+    gpt_params params;
 
     llama_batch batch;
 
@@ -474,7 +440,7 @@ struct llama_server_context
         }
     }
 
-    bool load_model(const common_params &params_)
+    bool load_model(const gpt_params &params_)
     {
         params = params_;
         if (!params.mmproj.empty()) {
@@ -482,7 +448,7 @@ struct llama_server_context
             LOG_INFO("Multi Modal Mode Enabled", {});
             clp_ctx = clip_model_load(params.mmproj.c_str(), /*verbosity=*/ 1);
             if(clp_ctx == nullptr) {
-                LOG_ERR("unable to load clip model: %s", params.mmproj.c_str());
+                LOG_ERROR("unable to load clip model", {{"model", params.mmproj}});
                 return false;
             }
 
@@ -491,12 +457,12 @@ struct llama_server_context
             }
         }
 
-        common_init_result common_init = common_init_from_params(params);
+        llama_init_result llama_init = llama_init_from_gpt_params(params);
-        model = common_init.model;
+        model = llama_init.model;
-        ctx = common_init.context;
+        ctx = llama_init.context;
         if (model == nullptr)
         {
-            LOG_ERR("unable to load model: %s", params.model.c_str());
+            LOG_ERROR("unable to load model", {{"model", params.model}});
             return false;
         }
 
@@ -504,7 +470,7 @@ struct llama_server_context
             const int n_embd_clip = clip_n_mmproj_embd(clp_ctx);
             const int n_embd_llm  = llama_n_embd(model);
             if (n_embd_clip != n_embd_llm) {
-                LOG("%s: embedding dim of the multimodal projector (%d) is not equal to that of LLaMA (%d). Make sure that you use the correct mmproj file.\n", __func__, n_embd_clip, n_embd_llm);
+                LOG_TEE("%s: embedding dim of the multimodal projector (%d) is not equal to that of LLaMA (%d). Make sure that you use the correct mmproj file.\n", __func__, n_embd_clip, n_embd_llm);
                 llama_free(ctx);
                 llama_free_model(model);
                 return false;
@@ -523,21 +489,11 @@ struct llama_server_context
         std::vector<char> buf(1);
         int res = llama_chat_apply_template(model, nullptr, chat, 1, true, buf.data(), buf.size());
         if (res < 0) {
-            LOG_ERR("The chat template comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", __func__);
+            LOG_ERROR("The chat template comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
             sparams.chat_template = "<|im_start|>"; // llama_chat_apply_template only checks if <|im_start|> exist in the template
         }
     }
 
-    llama_client_slot* get_active_slot() {
-        for (llama_client_slot& slot : slots) {
-            // Check if the slot is currently processing
-            if (slot.is_processing()) {
-                return &slot;  // Return the active slot
-            }
-        }
-        return nullptr;  // No active slot found
-    }
-
     void initialize() {
         // create slots
         all_slots_are_idle = true;
@@ -611,12 +567,12 @@ struct llama_server_context
                     std::vector<llama_token> p;
                     if (first)
                     {
-                        p = common_tokenize(ctx, s, add_bos, TMP_FORCE_SPECIAL);
+                        p = ::llama_tokenize(ctx, s, add_bos, TMP_FORCE_SPECIAL);
                         first = false;
                     }
                     else
                     {
-                        p = common_tokenize(ctx, s, false, TMP_FORCE_SPECIAL);
+                        p = ::llama_tokenize(ctx, s, false, TMP_FORCE_SPECIAL);
                     }
                     prompt_tokens.insert(prompt_tokens.end(), p.begin(), p.end());
                 }
@@ -633,7 +589,7 @@ struct llama_server_context
         else
         {
             auto s = json_prompt.template get<std::string>();
-            prompt_tokens = common_tokenize(ctx, s, add_bos, TMP_FORCE_SPECIAL);
+            prompt_tokens = ::llama_tokenize(ctx, s, add_bos, TMP_FORCE_SPECIAL);
         }
 
         return prompt_tokens;
@@ -662,7 +618,7 @@ struct llama_server_context
 
     bool launch_slot_with_data(llama_client_slot* &slot, json data) {
         slot_params default_params;
-        common_sampler_params default_sparams;
+        gpt_sampler_params default_sparams;
  
         slot->params.stream             = json_value(data, "stream",            false);
         slot->params.cache_prompt       = json_value(data, "cache_prompt",      false);
@@ -802,7 +758,7 @@ struct llama_server_context
                     }
                     else if (el[0].is_string())
                     {
-                        auto toks = common_tokenize(model, el[0].get<std::string>(), false);
+                        auto toks = llama_tokenize(model, el[0].get<std::string>(), false);
                         for (auto tok : toks)
                         {
                             slot->sparams.logit_bias.push_back({tok, bias});
@@ -834,7 +790,7 @@ struct llama_server_context
                         sampler_names.emplace_back(name);
                     }
                 }
-                slot->sparams.samplers = common_sampler_types_from_names(sampler_names, false);
+                slot->sparams.samplers = gpt_sampler_types_from_names(sampler_names, false);
         }
         else
         {
@@ -856,11 +812,10 @@ struct llama_server_context
                     img_sl.img_data = clip_image_u8_init();
                     if (!clip_image_load_from_bytes(image_buffer.data(), image_buffer.size(), img_sl.img_data))
                     {
-                        LOG_ERR("%s: failed to load image, slot_id: %d, img_sl_id: %d", 
+                        LOG_ERROR("failed to load image", {
-                             __func__,
+                            {"slot_id",   slot->id},
-                             slot->id,
+                            {"img_sl_id", img_sl.id}
-                             img_sl.id
+                        });
-                        );
                         return false;
                     }
                     LOG_VERBOSE("image loaded", {
@@ -898,12 +853,12 @@ struct llama_server_context
                                     }
                                 }
                                 if (!found) {
-                                    LOG("ERROR: Image with id: %i, not found.\n", img_id);
+                                    LOG_TEE("ERROR: Image with id: %i, not found.\n", img_id);
                                     slot->images.clear();
                                     return false;
                                 }
                             } catch (const std::invalid_argument& e) {
-                                LOG("Invalid image number id in prompt\n");
+                                LOG_TEE("Invalid image number id in prompt\n");
                                 slot->images.clear();
                                 return false;
                             }
@@ -918,9 +873,9 @@ struct llama_server_context
 
         if (slot->ctx_sampling != nullptr)
         {
-            common_sampler_free(slot->ctx_sampling);
+            gpt_sampler_free(slot->ctx_sampling);
         }
-        slot->ctx_sampling = common_sampler_init(model, slot->sparams);
+        slot->ctx_sampling = gpt_sampler_init(model, slot->sparams);
         //llama_set_rng_seed(ctx, slot->params.seed);
         slot->command = LOAD_PROMPT;
 
@@ -931,7 +886,7 @@ struct llama_server_context
             {"task_id", slot->task_id},
         });
 
-      //  LOG("sampling: \n%s\n", llama_sampling_print(slot->sparams).c_str());
+      //  LOG_TEE("sampling: \n%s\n", llama_sampling_print(slot->sparams).c_str());
 
         return true;
     }
@@ -947,13 +902,13 @@ struct llama_server_context
         system_tokens.clear();
 
         if (!system_prompt.empty()) {
-            system_tokens = common_tokenize(ctx, system_prompt, add_bos_token);
+            system_tokens = ::llama_tokenize(ctx, system_prompt, add_bos_token);
 
-            common_batch_clear(batch);
+            llama_batch_clear(batch);
 
             for (int i = 0; i < (int)system_tokens.size(); ++i)
             {
-                common_batch_add(batch, system_tokens[i], i, { 0 }, false);
+                llama_batch_add(batch, system_tokens[i], i, { 0 }, false);
             }
 
             for (int32_t i = 0; i < (int32_t) batch.n_tokens; i += params.n_batch)
@@ -967,10 +922,11 @@ struct llama_server_context
                     batch.n_seq_id + i,
                     batch.seq_id   + i,
                     batch.logits   + i,
+                    0, 0, 0, // unused
                 };
                 if (llama_decode(ctx, batch_view) != 0)
                 {
-                    LOG("%s: llama_decode() failed\n", __func__);
+                    LOG_TEE("%s: llama_decode() failed\n", __func__);
                     return;
                 }
             }
@@ -982,7 +938,7 @@ struct llama_server_context
             }
         }
 
-        LOG("system prompt updated\n");
+        LOG_TEE("system prompt updated\n");
         system_need_update = false;
     }
 
@@ -1041,7 +997,7 @@ struct llama_server_context
 
     bool process_token(completion_token_output &result, llama_client_slot &slot) {
         // remember which tokens were sampled - used for repetition penalties during sampling
-        const std::string token_str = common_token_to_piece(ctx, result.tok);
+        const std::string token_str = llama_token_to_piece(ctx, result.tok);
         slot.sampled = result.tok;
 
         // search stop word and delete it
@@ -1164,7 +1120,7 @@ struct llama_server_context
             }
 
             if (!llava_image_embed_make_with_clip_img(clp_ctx, params.cpuparams.n_threads, img.img_data, &img.image_embedding, &img.image_tokens)) {
-                LOG("Error processing the given image");
+                LOG_TEE("Error processing the given image");
                 return false;
             }
 
@@ -1176,7 +1132,7 @@ struct llama_server_context
 
     void send_error(task_server& task, const std::string &error)
     {
-        LOG("task %i - error: %s\n", task.id, error.c_str());
+        LOG_TEE("task %i - error: %s\n", task.id, error.c_str());
         task_result res;
         res.id = task.id;
         res.multitask_id = task.multitask_id;
@@ -1192,7 +1148,7 @@ struct llama_server_context
         samplers.reserve(slot.sparams.samplers.size());
         for (const auto & sampler : slot.sparams.samplers)
         {
-            samplers.emplace_back(common_sampler_type_to_str(sampler));
+            samplers.emplace_back(gpt_sampler_type_to_str(sampler));
         }
 
         return json {
@@ -1248,7 +1204,7 @@ struct llama_server_context
         if (slot.sparams.n_probs > 0)
         {
             std::vector<completion_token_output> probs_output = {};
-            const std::vector<llama_token> to_send_toks = common_tokenize(ctx, tkn.text_to_send, false);
+            const std::vector<llama_token> to_send_toks = llama_tokenize(ctx, tkn.text_to_send, false);
             size_t probs_pos      = std::min(slot.sent_token_probs_index,                       slot.generated_token_probs.size());
             size_t probs_stop_pos = std::min(slot.sent_token_probs_index + to_send_toks.size(), slot.generated_token_probs.size());
             if (probs_pos < probs_stop_pos)
@@ -1300,7 +1256,7 @@ struct llama_server_context
             std::vector<completion_token_output> probs = {};
             if (!slot.params.stream && slot.stopped_word)
             {
-                const std::vector<llama_token> stop_word_toks = common_tokenize(ctx, slot.stopping_word, false);
+                const std::vector<llama_token> stop_word_toks = llama_tokenize(ctx, slot.stopping_word, false);
                 probs = std::vector<completion_token_output>(slot.generated_token_probs.begin(), slot.generated_token_probs.end() - stop_word_toks.size());
             }
             else
@@ -1411,10 +1367,11 @@ struct llama_server_context
                     batch.n_seq_id + i,
                     batch.seq_id   + i,
                     batch.logits   + i,
+                    0, 0, 0, // unused
                 };
                 if (llama_decode(ctx, batch_view))
                 {
-                    LOG("%s : failed to eval\n", __func__);
+                    LOG_TEE("%s : failed to eval\n", __func__);
                     return false;
                 }
             }
@@ -1429,18 +1386,17 @@ struct llama_server_context
                 }
 
                 const int n_embd = llama_n_embd(model);
-                float * embd = img.image_embedding + i * n_embd;
+                llama_batch batch_img = { n_eval, nullptr, (img.image_embedding + i * n_embd), nullptr, nullptr, nullptr, nullptr, slot.n_past, 1, 0, };
-                llava_embd_batch llava_batch = llava_embd_batch(embd, n_eval, slot.n_past, 0);
+                if (llama_decode(ctx, batch_img))
-                if (llama_decode(ctx, llava_batch.batch))
                 {
-                    LOG("%s : failed to eval image\n", __func__);
+                    LOG_TEE("%s : failed to eval image\n", __func__);
                     return false;
                 }
                 slot.n_past += n_eval;
             }
             image_idx++;
 
-            common_batch_clear(batch);
+            llama_batch_clear(batch);
 
             // append prefix of next image
             const auto json_prompt = (image_idx >= (int) slot.images.size()) ?
@@ -1450,7 +1406,7 @@ struct llama_server_context
             std::vector<llama_token> append_tokens = tokenize(json_prompt, false); // has next image
             for (int i = 0; i < (int) append_tokens.size(); ++i)
             {
-                common_batch_add(batch, append_tokens[i], system_tokens.size() + slot.n_past, { slot.id }, true);
+                llama_batch_add(batch, append_tokens[i], system_tokens.size() + slot.n_past, { slot.id }, true);
                 slot.n_past += 1;
             }
         }
@@ -1582,7 +1538,7 @@ struct llama_server_context
             update_system_prompt();
         }
 
-        common_batch_clear(batch);
+        llama_batch_clear(batch);
 
         if (all_slots_are_idle)
         {
@@ -1616,7 +1572,7 @@ struct llama_server_context
                     slot.n_past = 0;
                     slot.truncated = false;
                     slot.has_next_token = true;
-                    LOG("Context exhausted. Slot %d released (%d tokens in cache)\n", slot.id, (int) slot.cache_tokens.size());
+                    LOG_TEE("Context exhausted. Slot %d released (%d tokens in cache)\n", slot.id, (int) slot.cache_tokens.size());
 
                     continue;
                     // END LOCALAI changes
@@ -1660,7 +1616,7 @@ struct llama_server_context
 
             // TODO: we always have to take into account the "system_tokens"
             //       this is not great and needs to be improved somehow
-            common_batch_add(batch, slot.sampled, system_tokens.size() + slot_npast, { slot.id }, true);
+            llama_batch_add(batch, slot.sampled, system_tokens.size() + slot_npast, { slot.id }, true);
             slot.n_past += 1;
         }
 
@@ -1754,7 +1710,7 @@ struct llama_server_context
 
                     if (!slot.params.cache_prompt)
                     {
-                        common_sampler_reset(slot.ctx_sampling);
+                        gpt_sampler_reset(slot.ctx_sampling);
 
                         slot.n_past = 0;
                         slot.n_past_se = 0;
@@ -1766,7 +1722,7 @@ struct llama_server_context
                         // push the prompt into the sampling context (do not apply grammar)
                         for (auto &token : prompt_tokens)
                         {
-                            common_sampler_accept(slot.ctx_sampling, token, false);
+                            gpt_sampler_accept(slot.ctx_sampling, token, false);
                         }
 
                         slot.n_past = common_part(slot.cache_tokens, prompt_tokens);
@@ -1858,17 +1814,16 @@ struct llama_server_context
                                 ga_i += ga_w/ga_n;
                             }
                         }
-                        common_batch_add(batch, prefix_tokens[slot.n_past], system_tokens.size() + slot_npast, {slot.id }, false);
+                        llama_batch_add(batch, prefix_tokens[slot.n_past], system_tokens.size() + slot_npast, {slot.id }, false);
                         slot_npast++;
                     }
 
                     if (has_images && !ingest_images(slot, n_batch))
                     {
-                        LOG_ERR("%s: failed processing images Slot id : %d, Task id: %d", 
+                        LOG_ERROR("failed processing images", {
-                            __func__,
+                            "slot_id", slot.id,
-                            slot.id,
+                            "task_id", slot.task_id,
-                            slot.task_id
+                        });
-                        );
                         // FIXME @phymbert: to be properly tested
                         //  early returning without changing the slot state will block the slot for ever
                         // no one at the moment is checking the return value
@@ -1908,10 +1863,10 @@ struct llama_server_context
                         const int bd = (slot.ga_w / slot.ga_n) * (slot.ga_n - 1);
                         const int dd = (slot.ga_w / slot.ga_n) - ib * bd - slot.ga_w;
 
-                        LOG("\n");
+                        LOG_TEE("\n");
-                        LOG("shift: [%6d, %6d] + %6d -> [%6d, %6d]\n", slot.ga_i, slot.n_past_se, ib * bd, slot.ga_i + ib * bd, slot.n_past_se + ib * bd);
+                        LOG_TEE("shift: [%6d, %6d] + %6d -> [%6d, %6d]\n", slot.ga_i, slot.n_past_se, ib * bd, slot.ga_i + ib * bd, slot.n_past_se + ib * bd);
-                        LOG("div:   [%6d, %6d] / %6d -> [%6d, %6d]\n", slot.ga_i + ib * bd, slot.ga_i + ib * bd + slot.ga_w, slot.ga_n, (slot.ga_i + ib * bd) / slot.ga_n, (slot.ga_i + ib * bd + slot.ga_w) / slot.ga_n);
+                        LOG_TEE("div:   [%6d, %6d] / %6d -> [%6d, %6d]\n", slot.ga_i + ib * bd, slot.ga_i + ib * bd + slot.ga_w, slot.ga_n, (slot.ga_i + ib * bd) / slot.ga_n, (slot.ga_i + ib * bd + slot.ga_w) / slot.ga_n);
-                        LOG("shift: [%6d, %6d] + %6d -> [%6d, %6d]\n", slot.ga_i + ib * bd + slot.ga_w, slot.n_past_se + ib * bd, dd, slot.ga_i + ib * bd + slot.ga_w + dd, slot.n_past_se + ib * bd + dd);
+                        LOG_TEE("shift: [%6d, %6d] + %6d -> [%6d, %6d]\n", slot.ga_i + ib * bd + slot.ga_w, slot.n_past_se + ib * bd, dd, slot.ga_i + ib * bd + slot.ga_w + dd, slot.n_past_se + ib * bd + dd);
 
                         llama_kv_cache_seq_add(ctx, slot.id, slot.ga_i, slot.n_past_se, ib * bd);
                         llama_kv_cache_seq_div(ctx, slot.id, slot.ga_i + ib * bd, slot.ga_i + ib * bd + slot.ga_w,slot.ga_n);
@@ -1921,7 +1876,7 @@ struct llama_server_context
 
                         slot.ga_i += slot.ga_w / slot.ga_n;
 
-                        LOG("\nn_past_old = %d, n_past = %d, ga_i = %d\n\n", slot.n_past_se + bd, slot.n_past_se, slot.ga_i);
+                        LOG_TEE("\nn_past_old = %d, n_past = %d, ga_i = %d\n\n", slot.n_past_se + bd, slot.n_past_se, slot.ga_i);
                     }
                     slot.n_past_se += n_tokens;
                 }
@@ -1936,6 +1891,7 @@ struct llama_server_context
                 batch.n_seq_id + i,
                 batch.seq_id   + i,
                 batch.logits   + i,
+                0, 0, 0, // unused
             };
 
             const int ret = llama_decode(ctx, batch_view);
@@ -1945,11 +1901,11 @@ struct llama_server_context
                 if (n_batch == 1 || ret < 0)
                 {
                     // if you get here, it means the KV cache is full - try increasing it via the context size
-                    LOG("%s : failed to decode the batch, n_batch = %d, ret = %d\n", __func__, n_batch, ret);
+                    LOG_TEE("%s : failed to decode the batch, n_batch = %d, ret = %d\n", __func__, n_batch, ret);
                     return false;
                 }
 
-                LOG("%s : failed to find free space in the KV cache, retrying with smaller n_batch = %d\n", __func__, n_batch / 2);
+                LOG_TEE("%s : failed to find free space in the KV cache, retrying with smaller n_batch = %d\n", __func__, n_batch / 2);
 
                 // retry with half the batch size to try to find a free slot in the KV cache
                 n_batch /= 2;
@@ -1974,9 +1930,9 @@ struct llama_server_context
                 }
 
                 completion_token_output result;
-                const llama_token id = common_sampler_sample(slot.ctx_sampling, ctx, slot.i_batch - i);
+                const llama_token id = gpt_sampler_sample(slot.ctx_sampling, ctx, slot.i_batch - i);
 
-                common_sampler_accept(slot.ctx_sampling, id, true);
+                gpt_sampler_accept(slot.ctx_sampling, id, true);
 
                 slot.n_decoded += 1;
                 if (slot.n_decoded == 1)
@@ -1987,7 +1943,7 @@ struct llama_server_context
                 }
 
                 result.tok = id;
-                const auto * cur_p = common_sampler_get_candidates(slot.ctx_sampling);
+                const auto * cur_p = gpt_sampler_get_candidates(slot.ctx_sampling);
 
                 for (size_t i = 0; i < (size_t) slot.sparams.n_probs; ++i) {
                     result.probs.push_back({
@@ -2040,7 +1996,7 @@ static json format_partial_response(
 struct token_translator
 {
     llama_context * ctx;
-    std::string operator()(llama_token tok)                    const { return common_token_to_piece(ctx, tok); }
+    std::string operator()(llama_token tok)                    const { return llama_token_to_piece(ctx, tok); }
     std::string operator()(const completion_token_output &cto) const { return (*this)(cto.tok); }
 };
 
@@ -2147,9 +2103,6 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, llama
     data["ignore_eos"] = predict->ignoreeos();
     data["embeddings"] = predict->embeddings();
 
-    // 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++) {
@@ -2234,7 +2187,7 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, llama
 // }
 
 static void params_parse(const backend::ModelOptions* request,
-                                common_params & params) {
+                                gpt_params & params) {
    
     // this is comparable to: https://github.com/ggerganov/llama.cpp/blob/d9b33fe95bd257b36c84ee5769cc048230067d6f/examples/server/server.cpp#L1809
 
@@ -2342,7 +2295,7 @@ public:
 
   grpc::Status LoadModel(ServerContext* context, const backend::ModelOptions* request, backend::Result* result) {
     // Implement LoadModel RPC
-    common_params params;
+    gpt_params params;
     params_parse(request, params);
 
     llama_backend_init();
@@ -2388,11 +2341,6 @@ public:
                 int32_t tokens_evaluated = result.result_json.value("tokens_evaluated", 0);
                 reply.set_prompt_tokens(tokens_evaluated);
 
-                // Log Request Correlation Id
-                LOG_VERBOSE("correlation:", {
-                    { "id", data["correlation_id"] }
-                });
-
                 // Send the reply
                 writer->Write(reply);
 
@@ -2416,12 +2364,6 @@ public:
         std::string completion_text;
         task_result result = llama.queue_results.recv(task_id);
         if (!result.error && result.stop) {
-            
-            // Log Request Correlation Id
-            LOG_VERBOSE("correlation:", {
-                { "id", data["correlation_id"] }
-            });
-
             completion_text = result.result_json.value("content", "");
             int32_t tokens_predicted = result.result_json.value("tokens_predicted", 0);
             int32_t tokens_evaluated = result.result_json.value("tokens_evaluated", 0);
@@ -2461,31 +2403,6 @@ public:
 
         return grpc::Status::OK;
     }
-
-    grpc::Status GetMetrics(ServerContext* context, const backend::MetricsRequest* request, backend::MetricsResponse* response) {
-        llama_client_slot* active_slot = llama.get_active_slot();
-
-        if (active_slot != nullptr) {
-            // Calculate the tokens per second using existing logic
-            double tokens_per_second = 1e3 / active_slot->t_token_generation * active_slot->n_decoded;
-
-            // Populate the response with metrics
-            response->set_slot_id(active_slot->id);
-            response->set_prompt_json_for_slot(active_slot->prompt.dump());
-            response->set_tokens_per_second(tokens_per_second);
-            response->set_tokens_generated(active_slot->n_decoded);
-            response->set_prompt_tokens_processed(active_slot->num_prompt_tokens_processed);
-        } else {
-            // 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::OK;
-    } 
 };
 
 void RunServer(const std::string& server_address) {

backend/python/autogptq/requirements-cublas11.txt

@@ -1,2 +1,2 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch

backend/python/autogptq/requirements-cublas12.txt

@@ -1 +1 @@
-torch==2.4.1
+torch

backend/python/autogptq/requirements-hipblas.txt

@@ -1,2 +1,2 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
+torch

backend/python/autogptq/requirements-intel.txt

@@ -2,4 +2,4 @@
 intel-extension-for-pytorch
 torch
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==72.1.0 # https://github.com/mudler/LocalAI/issues/2406

backend/python/autogptq/requirements.txt

@@ -1,6 +1,6 @@
 accelerate
 auto-gptq==0.7.1
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi
 transformers

backend/python/bark/requirements-cpu.txt

@@ -1,4 +1,4 @@
 transformers
 accelerate
-torch==2.4.1
+torch
-torchaudio==2.4.1
+torchaudio

backend/python/bark/requirements-cublas11.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
-torchaudio==2.4.1+cu118
+torchaudio
 transformers
 accelerate

backend/python/bark/requirements-cublas12.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch
-torchaudio==2.4.1
+torchaudio
 transformers
 accelerate

backend/python/bark/requirements-hipblas.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
+torch
-torchaudio==2.4.1+rocm6.0
+torchaudio
 transformers
 accelerate

backend/python/bark/requirements-intel.txt

@@ -3,6 +3,6 @@ intel-extension-for-pytorch
 torch
 torchaudio
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==70.3.0 # https://github.com/mudler/LocalAI/issues/2406
 transformers
 accelerate

backend/python/bark/requirements.txt

@@ -1,4 +1,4 @@
 bark==0.1.5
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi

backend/python/common/template/requirements.txt

@@ -1,2 +1,2 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf

backend/python/coqui/requirements-cpu.txt

@@ -1,4 +1,3 @@
 transformers
 accelerate
-torch==2.4.1
+torch
-coqui-tts

backend/python/coqui/requirements-cublas11.txt

@@ -1,6 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
-torchaudio==2.4.1+cu118
+torchaudio
 transformers
-accelerate
+accelerate
-coqui-tts

backend/python/coqui/requirements-cublas12.txt

@@ -1,5 +1,4 @@
-torch==2.4.1
+torch
-torchaudio==2.4.1
+torchaudio
 transformers
-accelerate
+accelerate
-coqui-tts

backend/python/coqui/requirements-hipblas.txt

@@ -1,6 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
+torch
-torchaudio==2.4.1+rocm6.0
+torchaudio
 transformers
-accelerate
+accelerate
-coqui-tts

backend/python/coqui/requirements-intel.txt

@@ -3,7 +3,6 @@ intel-extension-for-pytorch
 torch
 torchaudio
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==72.1.0 # https://github.com/mudler/LocalAI/issues/2406
 transformers
-accelerate
+accelerate
-coqui-tts

backend/python/coqui/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.67.0
+TTS==0.22.0
+grpcio==1.66.1
 protobuf
-certifi
+certifi
-packaging==24.1

backend/python/coqui/test.py

@@ -19,7 +19,7 @@ class TestBackendServicer(unittest.TestCase):
         This method sets up the gRPC service by starting the server
         """
         self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
-        time.sleep(30)
+        time.sleep(10)
 
     def tearDown(self) -> None:
         """

backend/python/diffusers/requirements-cpu.txt

@@ -5,5 +5,5 @@ accelerate
 compel
 peft
 sentencepiece
-torch==2.4.1
+torch
 optimum-quanto

backend/python/diffusers/requirements-cublas11.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
 diffusers
 opencv-python
 transformers

backend/python/diffusers/requirements-cublas12.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch
 diffusers
 opencv-python
 transformers

backend/python/diffusers/requirements-intel.txt

@@ -3,7 +3,7 @@ intel-extension-for-pytorch
 torch
 torchvision
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==70.3.0 # https://github.com/mudler/LocalAI/issues/2406
 diffusers
 opencv-python
 transformers

backend/python/diffusers/requirements.txt

@@ -1,5 +1,5 @@
 setuptools
-grpcio==1.67.0
+grpcio==1.66.1
 pillow
 protobuf
 certifi

backend/python/exllama2/requirements-cpu.txt

@@ -1,3 +1,3 @@
 transformers
 accelerate
-torch==2.4.1
+torch

backend/python/exllama2/requirements-cublas11.txt

@@ -1,4 +1,4 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
 transformers
 accelerate

backend/python/exllama2/requirements-cublas12.txt

@@ -1,3 +1,3 @@
-torch==2.4.1
+torch
 transformers
 accelerate

backend/python/exllama2/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi
 wheel

backend/python/mamba/requirements-cpu.txt

@@ -1,2 +1,2 @@
-torch==2.4.1
+torch
 transformers

backend/python/mamba/requirements-cublas11.txt

@@ -1,3 +1,3 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
 transformers

backend/python/mamba/requirements-cublas12.txt

@@ -1,2 +1,2 @@
-torch==2.4.1
+torch
 transformers

backend/python/mamba/requirements.txt

@@ -1,3 +1,3 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi

backend/python/openvoice/requirements-cpu.txt

@@ -1,3 +1 @@
-torch==2.4.1
+torch
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git

backend/python/openvoice/requirements-cublas11.txt

@@ -1,4 +1,2 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git

backend/python/openvoice/requirements-cublas12.txt

@@ -1,3 +1 @@
-torch==2.4.1
+torch
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git

backend/python/openvoice/requirements-hipblas.txt

@@ -1,4 +1,2 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
+torch
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git

backend/python/openvoice/requirements-intel.txt

@@ -2,22 +2,22 @@
 intel-extension-for-pytorch
 torch
 optimum[openvino]
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 librosa==0.9.1
-faster-whisper==0.9.0
+faster-whisper==1.0.3
 pydub==0.25.1
 wavmark==0.0.3
-numpy==1.22.0
+numpy==1.26.4
 eng_to_ipa==0.0.2
 inflect==7.0.0
 unidecode==1.3.7
-whisper-timestamped==1.14.2
+whisper-timestamped==1.15.4
 openai
 python-dotenv
 pypinyin==0.50.0
 cn2an==0.5.22
 jieba==0.42.1
+gradio==4.38.1
 langid==1.1.6
 git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git

backend/python/openvoice/requirements.txt

@@ -1,10 +1,10 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 librosa
 faster-whisper
 pydub==0.25.1
 wavmark==0.0.3
-numpy==1.22.0
+numpy
 eng_to_ipa==0.0.2
 inflect
 unidecode
@@ -13,8 +13,8 @@ openai
 python-dotenv
 pypinyin
 cn2an==0.5.22
-networkx==2.8.8
 jieba==0.42.1
-gradio==3.48.0
+gradio
 langid==1.1.6
-llvmlite==0.43.0
+git+https://github.com/myshell-ai/MeloTTS.git
+git+https://github.com/myshell-ai/OpenVoice.git

backend/python/openvoice/test.py

@@ -19,7 +19,7 @@ class TestBackendServicer(unittest.TestCase):
         This method sets up the gRPC service by starting the server
         """
         self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
-        time.sleep(30)
+        time.sleep(10)
 
     def tearDown(self) -> None:
         """

backend/python/parler-tts/install.sh

@@ -15,12 +15,5 @@ installRequirements
 
 # https://github.com/descriptinc/audiotools/issues/101
 # incompatible protobuf versions.
-# PYDIR=python3.10
+PYDIR=$(ls ${MY_DIR}/venv/lib)
-# pyenv="${MY_DIR}/venv/lib/${PYDIR}/site-packages/google/protobuf/internal/"
+curl -L https://raw.githubusercontent.com/protocolbuffers/protobuf/main/python/google/protobuf/internal/builder.py -o ${MY_DIR}/venv/lib/${PYDIR}/site-packages/google/protobuf/internal/builder.py
-
-# if [ ! -d ${pyenv} ]; then
-#     echo "(parler-tts/install.sh): Error: ${pyenv} does not exist"
-#     exit 1
-# fi
-
-# curl -L https://raw.githubusercontent.com/protocolbuffers/protobuf/main/python/google/protobuf/internal/builder.py -o ${pyenv}/builder.py

backend/python/parler-tts/requirements-after.txt

@@ -1,4 +1,3 @@
 git+https://github.com/huggingface/parler-tts.git@8e465f1b5fcd223478e07175cb40494d19ffbe17
 llvmlite==0.43.0
 numba==0.60.0
-git+https://github.com/descriptinc/audiotools

backend/python/parler-tts/requirements-cpu.txt

@@ -1,3 +1,3 @@
 transformers
 accelerate
-torch==2.4.1
+torch

backend/python/parler-tts/requirements-cublas11.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
-torchaudio==2.4.1+cu118
+torchaudio
 transformers
 accelerate

backend/python/parler-tts/requirements-cublas12.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch
-torchaudio==2.4.1
+torchaudio
 transformers
 accelerate

backend/python/parler-tts/requirements-intel.txt

@@ -3,6 +3,6 @@ intel-extension-for-pytorch
 torch
 torchaudio
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==72.1.0 # https://github.com/mudler/LocalAI/issues/2406
 transformers
 accelerate

backend/python/parler-tts/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi
 llvmlite==0.43.0

backend/python/rerankers/requirements-cpu.txt

@@ -1,4 +1,4 @@
 transformers
 accelerate
-torch==2.4.1
+torch
 rerankers[transformers]

backend/python/rerankers/requirements-cublas11.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
 transformers
 accelerate
-torch==2.4.1+cu118
+torch
 rerankers[transformers]

backend/python/rerankers/requirements-cublas12.txt

@@ -1,4 +1,4 @@
 transformers
 accelerate
-torch==2.4.1
+torch
 rerankers[transformers]

backend/python/rerankers/requirements-hipblas.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
 transformers
 accelerate
-torch==2.4.1+rocm6.0
+torch
 rerankers[transformers]

backend/python/rerankers/requirements-intel.txt

@@ -5,4 +5,4 @@ accelerate
 torch
 rerankers[transformers]
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==72.1.0 # https://github.com/mudler/LocalAI/issues/2406

backend/python/rerankers/requirements.txt

@@ -1,3 +1,3 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi

backend/python/sentencetransformers/backend.py

@@ -55,7 +55,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         """
         model_name = request.Model
         try:
-            self.model = SentenceTransformer(model_name, trust_remote_code=request.TrustRemoteCode)
+            self.model = SentenceTransformer(model_name)
         except Exception as err:
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
 

backend/python/sentencetransformers/requirements-cpu.txt

@@ -1,6 +1,6 @@
-torch==2.4.1
+torch
 accelerate
 transformers
 bitsandbytes
-sentence-transformers==3.2.0
+sentence-transformers==3.0.1
 transformers

backend/python/sentencetransformers/requirements-cublas11.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
 accelerate
-sentence-transformers==3.2.0
+sentence-transformers==3.0.1
 transformers

backend/python/sentencetransformers/requirements-cublas12.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch
 accelerate
-sentence-transformers==3.2.0
+sentence-transformers==3.0.1
 transformers

backend/python/sentencetransformers/requirements-hipblas.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
+torch
 accelerate
-sentence-transformers==3.2.0
+sentence-transformers==3.0.1
 transformers

backend/python/sentencetransformers/requirements-intel.txt

@@ -4,5 +4,5 @@ torch
 optimum[openvino]
 setuptools==69.5.1 # https://github.com/mudler/LocalAI/issues/2406
 accelerate
-sentence-transformers==3.2.0
+sentence-transformers==3.0.1
 transformers

backend/python/sentencetransformers/requirements.txt

@@ -1,5 +1,3 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
-certifi
+certifi
-datasets
-einops

backend/python/transformers-musicgen/requirements-cpu.txt

@@ -1,3 +1,3 @@
 transformers
 accelerate
-torch==2.4.1
+torch

backend/python/transformers-musicgen/requirements-cublas11.txt

@@ -1,4 +1,4 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
 transformers
 accelerate
-torch==2.4.1+cu118
+torch

backend/python/transformers-musicgen/requirements-cublas12.txt

@@ -1,3 +1,3 @@
 transformers
 accelerate
-torch==2.4.1
+torch

backend/python/transformers-musicgen/requirements-hipblas.txt

@@ -1,4 +1,4 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
 transformers
 accelerate
-torch==2.4.1+rocm6.0
+torch

backend/python/transformers-musicgen/requirements-intel.txt

@@ -4,4 +4,4 @@ transformers
 accelerate
 torch
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==69.5.1 # https://github.com/mudler/LocalAI/issues/2406

backend/python/transformers-musicgen/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 scipy==1.14.0
 certifi

backend/python/transformers/backend.py

@@ -72,12 +72,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         Returns:
             A Result object that contains the result of the LoadModel operation.
         """
-
         model_name = request.Model
-        
-        # Check to see if the Model exists in the filesystem already.
-        if os.path.exists(request.ModelFile):
-            model_name = request.ModelFile
 
         compute = torch.float16
         if request.F16Memory == True:

backend/python/transformers/requirements-cpu.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch
 accelerate
 transformers
 bitsandbytes

backend/python/transformers/requirements-cublas11.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
+torch
 accelerate
 transformers
 bitsandbytes

backend/python/transformers/requirements-cublas12.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch
 accelerate
 transformers
 bitsandbytes

backend/python/transformers/requirements-hipblas.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
+torch
 accelerate
 transformers
 bitsandbytes

backend/python/transformers/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi
 setuptools==69.5.1 # https://github.com/mudler/LocalAI/issues/2406

backend/python/vall-e-x/requirements-cpu.txt

@@ -1,3 +1,3 @@
 accelerate
-torch==2.4.1
+torch
-torchaudio==2.4.1
+torchaudio

backend/python/vall-e-x/requirements-cublas11.txt

@@ -1,4 +1,4 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
 accelerate
-torch==2.4.1+cu118
+torch
-torchaudio==2.4.1+cu118
+torchaudio

backend/python/vall-e-x/requirements-cublas12.txt

@@ -1,3 +1,3 @@
 accelerate
-torch==2.4.1
+torch
-torchaudio==2.4.1
+torchaudio

backend/python/vall-e-x/requirements-intel.txt

@@ -4,4 +4,4 @@ accelerate
 torch
 torchaudio
 optimum[openvino]
-setuptools==75.1.0 # https://github.com/mudler/LocalAI/issues/2406
+setuptools==72.1.0 # https://github.com/mudler/LocalAI/issues/2406

backend/python/vall-e-x/requirements.txt

@@ -1,3 +1,3 @@
-grpcio==1.67.0
+grpcio==1.66.1
 protobuf
 certifi

backend/python/vllm/backend.py

@@ -5,8 +5,6 @@ import argparse
 import signal
 import sys
 import os
-from typing import List
-from PIL import Image
 
 import backend_pb2
 import backend_pb2_grpc
@@ -17,10 +15,6 @@ from vllm.engine.async_llm_engine import AsyncLLMEngine
 from vllm.sampling_params import SamplingParams
 from vllm.utils import random_uuid
 from vllm.transformers_utils.tokenizer import get_tokenizer
-from vllm.multimodal.utils import fetch_image
-from vllm.assets.video import VideoAsset
-import base64
-import io
 
 _ONE_DAY_IN_SECONDS = 60 * 60 * 24
 
@@ -95,8 +89,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
 
         if request.Quantization != "":
             engine_args.quantization = request.Quantization
-        if request.LoadFormat != "":
-            engine_args.load_format = request.LoadFormat
         if request.GPUMemoryUtilization != 0:
             engine_args.gpu_memory_utilization = request.GPUMemoryUtilization
         if request.TrustRemoteCode:
@@ -113,7 +105,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         try:
             self.llm = AsyncLLMEngine.from_engine_args(engine_args)
         except Exception as err:
-            print(f"Unexpected {err=}, {type(err)=}", file=sys.stderr)
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
 
         try:
@@ -126,7 +117,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
            )
         except Exception as err:
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
-        print("Model loaded successfully", file=sys.stderr)
+
         return backend_pb2.Result(message="Model loaded successfully", success=True)
 
     async def Predict(self, request, context):
@@ -205,35 +196,15 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         if request.Seed != 0:
             sampling_params.seed = request.Seed
 
-        # Extract image paths and process images
         prompt = request.Prompt
-
+        
-        image_paths = request.Images
+        # If tokenizer template is enabled and messages are provided instead of prompt apply the tokenizer template
-        image_data = [self.load_image(img_path) for img_path in image_paths]
-
-        videos_path = request.Videos
-        video_data = [self.load_video(video_path) for video_path in videos_path]
-
-        # If tokenizer template is enabled and messages are provided instead of prompt, apply the tokenizer template
         if not request.Prompt and request.UseTokenizerTemplate and request.Messages:
             prompt = self.tokenizer.apply_chat_template(request.Messages, tokenize=False, add_generation_prompt=True)
 
-        # Generate text using the LLM engine
+        # Generate text
         request_id = random_uuid()
-        print(f"Generating text with request_id: {request_id}", file=sys.stderr)
+        outputs = self.llm.generate(prompt, sampling_params, request_id)
-        multi_modal_data = {}
-        if image_data:
-            multi_modal_data["image"] = image_data
-        if video_data:
-            multi_modal_data["video"] = video_data
-        outputs = self.llm.generate(
-            {
-            "prompt": prompt,
-            "multi_modal_data": multi_modal_data if multi_modal_data else None,
-            },
-            sampling_params=sampling_params,
-            request_id=request_id,
-        )
 
         # Stream the results
         generated_text = ""
@@ -256,57 +227,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         if streaming:
             return
 
-        # Remove the image files from /tmp folder
-        for img_path in image_paths:
-            try:
-                os.remove(img_path)
-            except Exception as e:
-                print(f"Error removing image file: {img_path}, {e}", file=sys.stderr)
-
         # Sending the final generated text
         yield backend_pb2.Reply(message=bytes(generated_text, encoding='utf-8'))
 
-    def load_image(self, image_path: str):
-        """
-        Load an image from the given file path or base64 encoded data.
-        
-        Args:
-            image_path (str): The path to the image file or base64 encoded data.
-
-        Returns:
-            Image: The loaded image.
-        """
-        try:
-
-            image_data = base64.b64decode(image_path)
-            image = Image.open(io.BytesIO(image_data))
-            return image
-        except Exception as e:
-            print(f"Error loading image {image_path}: {e}", file=sys.stderr)
-            return None
-
-    def load_video(self, video_path: str):
-        """
-        Load a video from the given file path.
-        
-        Args:
-            video_path (str): The path to the image file.
-
-        Returns:
-            Video: The loaded video.
-        """
-        try:
-            timestamp = str(int(time.time() * 1000))  # Generate timestamp
-            p = f"/tmp/vl-{timestamp}.data"  # Use timestamp in filename
-            with open(p, "wb") as f:
-                f.write(base64.b64decode(video_path))
-            video = VideoAsset(name=p).np_ndarrays
-            os.remove(p)
-            return video
-        except Exception as e:
-            print(f"Error loading video {video_path}: {e}", file=sys.stderr)
-            return None
-
 async def serve(address):
     # Start asyncio gRPC server
     server = grpc.aio.server(migration_thread_pool=futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))

backend/python/vllm/install.sh

@@ -13,20 +13,4 @@ if [ "x${BUILD_PROFILE}" == "xintel" ]; then
     EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
 fi
 
-# We don't embed this into the images as it is a large dependency and not always needed.
+installRequirements
-# Besides, the speed inference are not actually usable in the current state for production use-cases.
-if [ "x${BUILD_TYPE}" == "x" ] && [ "x${FROM_SOURCE}" == "xtrue" ]; then
-        ensureVenv
-        # https://docs.vllm.ai/en/v0.6.1/getting_started/cpu-installation.html
-        if [ ! -d vllm ]; then
-            git clone https://github.com/vllm-project/vllm
-        fi
-        pushd vllm
-            uv pip install wheel packaging ninja "setuptools>=49.4.0" numpy typing-extensions pillow setuptools-scm grpcio==1.67.0 protobuf bitsandbytes
-            uv pip install -v -r requirements-cpu.txt --extra-index-url https://download.pytorch.org/whl/cpu
-            VLLM_TARGET_DEVICE=cpu python setup.py install
-        popd
-        rm -rf vllm
-    else
-        installRequirements
-fi

backend/python/vllm/requirements-cpu.txt

@@ -1,3 +1,3 @@
 accelerate
-torch==2.4.1
+torch
 transformers

backend/python/vllm/requirements-cublas11.txt

@@ -1,5 +1,4 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
 accelerate
-torch==2.4.1+cu118
+torch
-transformers
+transformers
-bitsandbytes