feat(l4t): add support for extras images

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

.devcontainer/docker-compose-devcontainer.yml

@@ -7,7 +7,7 @@ services:
       args:
       - FFMPEG=true
       - IMAGE_TYPE=extras
-      - GO_TAGS=stablediffusion p2p tts
+      - GO_TAGS=p2p tts
     env_file:
       - ../.env
     ports:

.env

@@ -38,12 +38,12 @@
 ## Uncomment and set to true to enable rebuilding from source
 # REBUILD=true
 
-## Enable go tags, available: stablediffusion, tts
+## Enable go tags, available: p2p, tts
-## stablediffusion: image generation with stablediffusion
+## p2p: enable distributed inferencing
 ## tts: enables text-to-speech with go-piper 
 ## (requires REBUILD=true)
 #
-# GO_TAGS=stablediffusion
+# GO_TAGS=p2p
 
 ## Path where to store generated images
 # LOCALAI_IMAGE_PATH=/tmp/generated/images

.github/workflows/dependabot_auto.yml

@@ -14,7 +14,7 @@ jobs:
     steps:
       - name: Dependabot metadata
         id: metadata
-        uses: dependabot/fetch-metadata@v2.2.0
+        uses: dependabot/fetch-metadata@v2.3.0
         with:
           github-token: "${{ secrets.GITHUB_TOKEN }}"
           skip-commit-verification: true

.github/workflows/notify-models.yaml

@@ -18,7 +18,7 @@ jobs:
       with:
         model: 'hermes-2-theta-llama-3-8b' # 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@v2.7.0
+    - uses: GrantBirki/git-diff-action@v2.8.0
       id: git-diff-action
       with:
             json_diff_file_output: diff.json
@@ -99,7 +99,7 @@ jobs:
         docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master-ffmpeg-core 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@v2.7.0
+    - uses: GrantBirki/git-diff-action@v2.8.0
       id: git-diff-action
       with:
             json_diff_file_output: diff.json

.github/workflows/release.yaml

@@ -237,40 +237,7 @@ jobs:
           detached: true
           connect-timeout-seconds: 180
           limit-access-to-actor: true
-  build-stablediffusion:
+
-    runs-on: ubuntu-latest
-    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: |
-          sudo apt-get update
-          sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler ccache upx-ucl
-          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
-      - name: Build stablediffusion
-        run: |
-          export PATH=$PATH:$GOPATH/bin
-          make backend-assets/grpc/stablediffusion
-          mkdir -p release && cp backend-assets/grpc/stablediffusion release
-        env:
-          GO_TAGS: stablediffusion
-      - uses: actions/upload-artifact@v4
-        with:
-          name: stablediffusion
-          path: release/
-      - name: Release
-        uses: softprops/action-gh-release@v2
-        if: startsWith(github.ref, 'refs/tags/')
-        with:
-          files: |
-            release/*
 
   build-macOS-x86_64:
     runs-on: macos-13

.github/workflows/test-extra.yml

@@ -78,57 +78,6 @@ jobs:
           make --jobs=5 --output-sync=target -C backend/python/diffusers
           make --jobs=5 --output-sync=target -C backend/python/diffusers test
 
-  tests-parler-tts:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v4
-        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 parler-tts
-        run: |
-           make --jobs=5 --output-sync=target -C backend/python/parler-tts
-           make --jobs=5 --output-sync=target -C backend/python/parler-tts test
-      - name: Setup tmate session if tests fail
-        if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.19
-        with:
-          detached: true
-          connect-timeout-seconds: 180
-          limit-access-to-actor: true
-
-  tests-openvoice:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v4
-        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 openvoice
-        run: |
-           make --jobs=5 --output-sync=target -C backend/python/openvoice
-           make --jobs=5 --output-sync=target -C backend/python/openvoice test
-
   # tests-transformers-musicgen:
   #   runs-on: ubuntu-latest
   #   steps:

.github/workflows/test.yml

@@ -105,9 +105,7 @@ jobs:
           # Pre-build piper before we start tests in order to have shared libraries in place
           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/ && \
+          sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/
-          # Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
-          PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
         env:
           CUDA_VERSION: 12-4
       - name: Cache grpc
@@ -129,7 +127,7 @@ jobs:
           cd grpc && cd cmake/build && sudo make --jobs 5 install
       - name: Test
         run: |
-          PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
+          PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
         uses: mxschmitt/action-tmate@v3.19

.vscode/launch.json

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

Dockerfile

@@ -15,8 +15,7 @@ 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,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,openvoice:/build/backend/python/openvoice/run.sh,kokoro:/build/backend/python/kokoro/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
+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,autogptq:/build/backend/python/autogptq/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 \
@@ -69,14 +68,10 @@ ENV PATH=/opt/rocm/bin:${PATH}
 # OpenBLAS requirements and stable diffusion
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
-        libopenblas-dev \
+        libopenblas-dev && \
-        libopencv-dev && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
-# Set up OpenCV
-RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
-
 WORKDIR /build
 
 ###################################
@@ -251,7 +246,7 @@ RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shall
 
 FROM requirements-drivers AS builder-base
 
-ARG GO_TAGS="stablediffusion tts p2p"
+ARG GO_TAGS="tts p2p"
 ARG GRPC_BACKENDS
 ARG MAKEFLAGS
 ARG LD_FLAGS="-s -w"
@@ -285,35 +280,12 @@ RUN <<EOT bash
     fi
 EOT
 
-
-###################################
-###################################
-
-# This first portion of builder holds the layers specifically used to build backend-assets/grpc/stablediffusion
-# In most cases, builder is the image you should be using - however, this can save build time if one just needs to copy backend-assets/grpc/stablediffusion and nothing else.
-FROM builder-base AS builder-sd
-
-# stablediffusion does not tolerate a newer version of abseil, copy only over enough elements to build it
-COPY Makefile .
-COPY go.mod .
-COPY go.sum .
-COPY backend/backend.proto ./backend/backend.proto
-COPY backend/go/image/stablediffusion ./backend/go/image/stablediffusion
-COPY pkg/grpc ./pkg/grpc
-COPY pkg/stablediffusion ./pkg/stablediffusion
-RUN git init
-RUN make sources/go-stable-diffusion
-RUN touch prepare-sources
-
-# Actually build the backend
-RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make backend-assets/grpc/stablediffusion
-
 ###################################
 ###################################
 
 # 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-sd AS builder
+FROM builder-base AS builder
 
 # Install the pre-built GRPC
 COPY --from=grpc /opt/grpc /usr/local
@@ -331,7 +303,7 @@ RUN make prepare
 ## We only leave the most CPU-optimized variant and the fallback for the cublas/hipblas build
 ## (both will use CUDA or hipblas for the actual computation)
 RUN if [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
-        SKIP_GRPC_BACKEND="backend-assets/grpc/llama-cpp-avx backend-assets/grpc/llama-cpp-avx2" 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
@@ -353,8 +325,6 @@ ARG FFMPEG
 
 COPY --from=grpc /opt/grpc /usr/local
 
-COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion /build/backend-assets/grpc/stablediffusion
-
 COPY .devcontainer-scripts /.devcontainer-scripts
 
 # Add FFmpeg
@@ -384,12 +354,14 @@ FROM requirements-drivers
 
 ARG FFMPEG
 ARG BUILD_TYPE
+ARG BUILD_PLATFORM
 ARG TARGETARCH
 ARG IMAGE_TYPE=extras
 ARG EXTRA_BACKENDS
 ARG MAKEFLAGS
 
 ENV BUILD_TYPE=${BUILD_TYPE}
+ENV BUILD_PLATFORM=${BUILD_PLATFORM}
 ENV REBUILD=false
 ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
 ENV MAKEFLAGS=${MAKEFLAGS}
@@ -427,9 +399,6 @@ COPY --from=builder /build/local-ai ./
 # Copy shared libraries for piper
 COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
 
-# do not let stablediffusion rebuild (requires an older version of absl)
-COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
-
 # 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
@@ -443,8 +412,8 @@ RUN if [[ ( "${IMAGE_TYPE}" == "extras ")]]; then \
 RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
         make -C backend/python/coqui \
     ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "parler-tts" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
+    if [[ ( "${EXTRA_BACKENDS}" =~ "faster-whisper" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/parler-tts \
+        make -C backend/python/faster-whisper \
     ; fi && \
     if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
         make -C backend/python/diffusers \
@@ -453,9 +422,6 @@ RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAG
 RUN if [[ ( "${EXTRA_BACKENDS}" =~ "kokoro" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
         make -C backend/python/kokoro \
     ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "openvoice" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/openvoice \
-    ; fi && \
     if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
         make -C backend/python/exllama2 \
     ; fi && \
@@ -474,9 +440,6 @@ RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE
     ; fi && \
     if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
         make -C backend/python/rerankers \
-    ; fi && \
-    if [[ ( "${EXTRA_BACKENDS}" =~ "mamba" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
-        make -C backend/python/mamba \
     ; fi
 
 # Make sure the models directory exists

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?=92bc493917d43b83e592349e138b54c90b1c3ea7
+CPPLLAMA_VERSION?=5598f475be3e31430fbe17ebb85654ec90dc201e
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggerganov/whisper.cpp
@@ -18,10 +18,6 @@ WHISPER_CPP_VERSION?=6266a9f9e56a5b925e9892acf650f3eb1245814d
 PIPER_REPO?=https://github.com/mudler/go-piper
 PIPER_VERSION?=e10ca041a885d4a8f3871d52924b47792d5e5aa0
 
-# stablediffusion version
-STABLEDIFFUSION_REPO?=https://github.com/mudler/go-stable-diffusion
-STABLEDIFFUSION_VERSION?=4a3cd6aeae6f66ee57eae9a0075f8c58c3a6a38f
-
 # bark.cpp
 BARKCPP_REPO?=https://github.com/PABannier/bark.cpp.git
 BARKCPP_VERSION?=v1.0.0
@@ -179,11 +175,6 @@ ifeq ($(STATIC),true)
 	LD_FLAGS+=-linkmode external -extldflags -static
 endif
 
-ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
-#	OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
-	OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
-endif
-
 ifeq ($(findstring tts,$(GO_TAGS)),tts)
 #	OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
 #	OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
@@ -195,6 +186,7 @@ endif
 ALL_GRPC_BACKENDS=backend-assets/grpc/huggingface
 ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx
 ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx2
+ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx512
 ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-fallback
 ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-ggml
 ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-grpc
@@ -273,19 +265,6 @@ sources/go-piper:
 sources/go-piper/libpiper_binding.a: sources/go-piper
 	$(MAKE) -C sources/go-piper libpiper_binding.a example/main piper.o
 
-## stable diffusion (onnx)
-sources/go-stable-diffusion:
-	mkdir -p sources/go-stable-diffusion
-	cd sources/go-stable-diffusion && \
-	git init && \
-	git remote add origin $(STABLEDIFFUSION_REPO) && \
-	git fetch origin && \
-	git checkout $(STABLEDIFFUSION_VERSION) && \
-	git submodule update --init --recursive --depth 1 --single-branch
-
-sources/go-stable-diffusion/libstablediffusion.a: sources/go-stable-diffusion
-	CPATH="$(CPATH):/usr/include/opencv4" $(MAKE) -C sources/go-stable-diffusion libstablediffusion.a
-
 ## stablediffusion (ggml)
 sources/stablediffusion-ggml.cpp:
 	git clone --recursive $(STABLEDIFFUSION_GGML_REPO) sources/stablediffusion-ggml.cpp && \
@@ -331,20 +310,18 @@ sources/whisper.cpp:
 sources/whisper.cpp/libwhisper.a: sources/whisper.cpp
 	cd sources/whisper.cpp && $(MAKE) libwhisper.a libggml.a
 
-get-sources: sources/go-llama.cpp sources/go-piper sources/stablediffusion-ggml.cpp sources/bark.cpp sources/whisper.cpp sources/go-stable-diffusion backend/cpp/llama/llama.cpp
+get-sources: sources/go-llama.cpp sources/go-piper sources/stablediffusion-ggml.cpp sources/bark.cpp sources/whisper.cpp backend/cpp/llama/llama.cpp
 
 replace:
 	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(CURDIR)/sources/whisper.cpp
 	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(CURDIR)/sources/whisper.cpp/bindings/go
 	$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(CURDIR)/sources/go-piper
-	$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(CURDIR)/sources/go-stable-diffusion
 	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(CURDIR)/sources/go-llama.cpp
 
 dropreplace:
 	$(GOCMD) mod edit -dropreplace github.com/ggerganov/whisper.cpp
 	$(GOCMD) mod edit -dropreplace github.com/ggerganov/whisper.cpp/bindings/go
 	$(GOCMD) mod edit -dropreplace github.com/mudler/go-piper
-	$(GOCMD) mod edit -dropreplace github.com/mudler/go-stable-diffusion
 	$(GOCMD) mod edit -dropreplace github.com/go-skynet/go-llama.cpp
 
 prepare-sources: get-sources replace
@@ -355,7 +332,6 @@ rebuild: ## Rebuilds the project
 	$(GOCMD) clean -cache
 	$(MAKE) -C sources/go-llama.cpp clean
 	$(MAKE) -C sources/whisper.cpp clean
-	$(MAKE) -C sources/go-stable-diffusion clean
 	$(MAKE) -C sources/go-piper clean
 	$(MAKE) build
 
@@ -470,7 +446,7 @@ prepare-test: grpcs
 
 test: prepare test-models/testmodel.ggml grpcs
 	@echo 'Running tests'
-	export GO_TAGS="tts stablediffusion debug"
+	export GO_TAGS="tts debug"
 	$(MAKE) prepare-test
 	HUGGINGFACE_GRPC=$(abspath ./)/backend/python/transformers/run.sh 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 && !llama-gguf"  --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
@@ -558,10 +534,10 @@ protogen-go-clean:
 	$(RM) bin/*
 
 .PHONY: protogen-python
-protogen-python: autogptq-protogen bark-protogen coqui-protogen diffusers-protogen exllama2-protogen mamba-protogen rerankers-protogen transformers-protogen parler-tts-protogen kokoro-protogen vllm-protogen openvoice-protogen
+protogen-python: autogptq-protogen bark-protogen coqui-protogen diffusers-protogen exllama2-protogen rerankers-protogen transformers-protogen kokoro-protogen vllm-protogen faster-whisper-protogen
 
 .PHONY: protogen-python-clean
-protogen-python-clean: autogptq-protogen-clean bark-protogen-clean coqui-protogen-clean diffusers-protogen-clean  exllama2-protogen-clean mamba-protogen-clean rerankers-protogen-clean transformers-protogen-clean parler-tts-protogen-clean kokoro-protogen-clean vllm-protogen-clean openvoice-protogen-clean
+protogen-python-clean: autogptq-protogen-clean bark-protogen-clean coqui-protogen-clean diffusers-protogen-clean  exllama2-protogen-clean rerankers-protogen-clean transformers-protogen-clean kokoro-protogen-clean vllm-protogen-clean faster-whisper-protogen-clean
 
 .PHONY: autogptq-protogen
 autogptq-protogen:
@@ -595,6 +571,14 @@ diffusers-protogen:
 diffusers-protogen-clean:
 	$(MAKE) -C backend/python/diffusers protogen-clean
 
+.PHONY: faster-whisper-protogen
+faster-whisper-protogen:
+	$(MAKE) -C backend/python/faster-whisper protogen
+
+.PHONY: faster-whisper-protogen-clean
+faster-whisper-protogen-clean:
+	$(MAKE) -C backend/python/faster-whisper protogen-clean
+
 .PHONY: exllama2-protogen
 exllama2-protogen:
 	$(MAKE) -C backend/python/exllama2 protogen
@@ -603,14 +587,6 @@ exllama2-protogen:
 exllama2-protogen-clean:
 	$(MAKE) -C backend/python/exllama2 protogen-clean
 
-.PHONY: mamba-protogen
-mamba-protogen:
-	$(MAKE) -C backend/python/mamba protogen
-
-.PHONY: mamba-protogen-clean
-mamba-protogen-clean:
-	$(MAKE) -C backend/python/mamba protogen-clean
-
 .PHONY: rerankers-protogen
 rerankers-protogen:
 	$(MAKE) -C backend/python/rerankers protogen
@@ -627,14 +603,6 @@ transformers-protogen:
 transformers-protogen-clean:
 	$(MAKE) -C backend/python/transformers protogen-clean
 
-.PHONY: parler-tts-protogen
-parler-tts-protogen:
-	$(MAKE) -C backend/python/parler-tts protogen
-
-.PHONY: parler-tts-protogen-clean
-parler-tts-protogen-clean:
-	$(MAKE) -C backend/python/parler-tts protogen-clean
-
 .PHONY: kokoro-protogen
 kokoro-protogen:
 	$(MAKE) -C backend/python/kokoro protogen
@@ -643,14 +611,6 @@ kokoro-protogen:
 kokoro-protogen-clean:
 	$(MAKE) -C backend/python/kokoro protogen-clean
 
-.PHONY: openvoice-protogen
-openvoice-protogen:
-	$(MAKE) -C backend/python/openvoice protogen
-
-.PHONY: openvoice-protogen-clean
-openvoice-protogen-clean:
-	$(MAKE) -C backend/python/openvoice protogen-clean
-
 .PHONY: vllm-protogen
 vllm-protogen:
 	$(MAKE) -C backend/python/vllm protogen
@@ -666,13 +626,11 @@ prepare-extra-conda-environments: protogen-python
 	$(MAKE) -C backend/python/bark
 	$(MAKE) -C backend/python/coqui
 	$(MAKE) -C backend/python/diffusers
+	$(MAKE) -C backend/python/faster-whisper
 	$(MAKE) -C backend/python/vllm
-	$(MAKE) -C backend/python/mamba
 	$(MAKE) -C backend/python/rerankers
 	$(MAKE) -C backend/python/transformers
-	$(MAKE) -C backend/python/parler-tts
 	$(MAKE) -C backend/python/kokoro
-	$(MAKE) -C backend/python/openvoice
 	$(MAKE) -C backend/python/exllama2
 
 prepare-test-extra: protogen-python
@@ -742,6 +700,13 @@ backend-assets/grpc/llama-cpp-avx2: backend-assets/grpc backend/cpp/llama/llama.
 	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-avx2" build-llama-cpp-grpc-server
 	cp -rfv backend/cpp/llama-avx2/grpc-server backend-assets/grpc/llama-cpp-avx2
 
+backend-assets/grpc/llama-cpp-avx512: backend-assets/grpc backend/cpp/llama/llama.cpp
+	cp -rf backend/cpp/llama backend/cpp/llama-avx512
+	$(MAKE) -C backend/cpp/llama-avx512 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-avx512" build-llama-cpp-grpc-server
+	cp -rfv backend/cpp/llama-avx512/grpc-server backend-assets/grpc/llama-cpp-avx512
+
 backend-assets/grpc/llama-cpp-avx: backend-assets/grpc backend/cpp/llama/llama.cpp
 	cp -rf backend/cpp/llama backend/cpp/llama-avx
 	$(MAKE) -C backend/cpp/llama-avx purge
@@ -816,13 +781,6 @@ ifneq ($(UPX),)
 	$(UPX) backend-assets/grpc/piper
 endif
 
-backend-assets/grpc/stablediffusion: sources/go-stable-diffusion sources/go-stable-diffusion/libstablediffusion.a backend-assets/grpc
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" CPATH="$(CPATH):$(CURDIR)/sources/go-stable-diffusion/:/usr/include/opencv4" LIBRARY_PATH=$(CURDIR)/sources/go-stable-diffusion/ \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./backend/go/image/stablediffusion
-ifneq ($(UPX),)
-	$(UPX) backend-assets/grpc/stablediffusion
-endif
-
 backend-assets/grpc/silero-vad: backend-assets/grpc backend-assets/lib/libonnxruntime.so.1
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" CPATH="$(CPATH):$(CURDIR)/sources/onnxruntime/include/" LIBRARY_PATH=$(CURDIR)/backend-assets/lib \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/silero-vad ./backend/go/vad/silero
@@ -903,7 +861,7 @@ swagger:
 
 .PHONY: gen-assets
 gen-assets:
-	$(GOCMD) run core/dependencies_manager/manager.go embedded/webui_static.yaml core/http/static/assets
+	$(GOCMD) run core/dependencies_manager/manager.go webui_static.yaml core/http/static/assets
 
 ## Documentation
 docs/layouts/_default:

README.md

@@ -39,7 +39,7 @@
 </p>
 
 <p align="center">
-<a href="https://trendshift.io/repositories/1484" target="_blank"><img src="https://trendshift.io/api/badge/repositories/1484" alt="go-skynet%2FLocalAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://trendshift.io/repositories/5539" target="_blank"><img src="https://trendshift.io/api/badge/repositories/5539" alt="mudler%2FLocalAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 </p>
 
 > :bulb: Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) [:book: Documentation website](https://localai.io/)

aio/cpu/image-gen.yaml

@@ -1,56 +1,17 @@
 name: stablediffusion
-backend: stablediffusion
+backend: stablediffusion-ggml
+cfg_scale: 4.5
+
+options:
+- sampler:euler
 parameters:
-  model: stablediffusion_assets
+  model: stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf
-
+step: 25
-license: "BSD-3"
-urls:
-- https://github.com/EdVince/Stable-Diffusion-NCNN
-- https://github.com/EdVince/Stable-Diffusion-NCNN/blob/main/LICENSE
-
-description: |
-     Stable Diffusion in NCNN with c++, supported txt2img and img2img
 
 download_files:
-- filename: "stablediffusion_assets/AutoencoderKL-256-256-fp16-opt.param"
+- filename: "stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf"
-  sha256: "18ca4b66685e21406bcf64c484b3b680b4949900415536d599cc876579c85c82"
+  sha256: "b8944e9fe0b69b36ae1b5bb0185b3a7b8ef14347fe0fa9af6c64c4829022261f"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-256-256-fp16-opt.param"
+  uri: "huggingface://second-state/stable-diffusion-v1-5-GGUF/stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf"
-- filename: "stablediffusion_assets/AutoencoderKL-512-512-fp16-opt.param"
-  sha256: "cf45f63aacf3dbbab0f59ed92a6f2c14d9a1801314631cd3abe91e3c85639a20"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-512-512-fp16-opt.param"
-- filename: "stablediffusion_assets/AutoencoderKL-base-fp16.param"
-  sha256: "0254a056dce61b0c27dc9ec1b78b53bcf55315c540f55f051eb841aa992701ba"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-base-fp16.param"
-- filename: "stablediffusion_assets/AutoencoderKL-encoder-512-512-fp16.bin"
-  sha256: "ddcb79a9951b9f91e05e087739ed69da2c1c4ae30ba4168cce350b49d617c9fa"
-  uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-encoder-512-512-fp16.bin"
-- filename: "stablediffusion_assets/AutoencoderKL-fp16.bin"
-  sha256: "f02e71f80e70252734724bbfaed5c4ddd3a8ed7e61bb2175ff5f53099f0e35dd"
-  uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-fp16.bin"
-- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.bin"
-  sha256: "1c9a12f4e1dd1b295a388045f7f28a2352a4d70c3dc96a542189a3dd7051fdd6"
-  uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/FrozenCLIPEmbedder-fp16.bin"
-- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.param"
-  sha256: "471afbe678dd1fd3fe764ef9c6eccaccb0a7d7e601f27b462aa926b20eb368c9"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/FrozenCLIPEmbedder-fp16.param"
-- filename: "stablediffusion_assets/log_sigmas.bin"
-  sha256: "a2089f8aa4c61f9c200feaec541ab3f5c94233b28deb6d5e8bcd974fa79b68ac"
-  uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/raw/main/x86/linux/assets/log_sigmas.bin"
-- filename: "stablediffusion_assets/UNetModel-256-256-MHA-fp16-opt.param"
-  sha256: "a58c380229f09491776df837b7aa7adffc0a87821dc4708b34535da2e36e3da1"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-256-256-MHA-fp16-opt.param"
-- filename: "stablediffusion_assets/UNetModel-512-512-MHA-fp16-opt.param"
-  sha256: "f12034067062827bd7f43d1d21888d1f03905401acf6c6eea22be23c259636fa"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-512-512-MHA-fp16-opt.param"
-- filename: "stablediffusion_assets/UNetModel-base-MHA-fp16.param"
-  sha256: "696f6975de49f4325b53ce32aff81861a6d6c07cd9ce3f0aae2cc405350af38d"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-base-MHA-fp16.param"
-- filename: "stablediffusion_assets/UNetModel-MHA-fp16.bin"
-  sha256: "d618918d011bfc1f644c0f2a33bf84931bd53b28a98492b0a8ed6f3a818852c3"
-  uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/UNetModel-MHA-fp16.bin"
-- filename: "stablediffusion_assets/vocab.txt"
-  sha256: "e30e57b6f1e47616982ef898d8922be24e535b4fa3d0110477b3a6f02ebbae7d"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/vocab.txt"
 
 usage: |
         curl http://localhost:8080/v1/images/generations \

backend/backend.proto

@@ -21,7 +21,8 @@ service Backend {
   rpc Status(HealthMessage) returns (StatusResponse) {}
 
   rpc StoresSet(StoresSetOptions) returns (Result) {}
-  rpc StoresReset(StoresResetOptions) returns (Result) {}
+  rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
+  rpc StoresGet(StoresGetOptions) returns (StoresGetResult) {}
   rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
 
   rpc Rerank(RerankRequest) returns (RerankResult) {}
@@ -77,10 +78,19 @@ message StoresSetOptions {
   repeated StoresValue Values = 2;
 }
 
-message StoresResetOptions {
+message StoresDeleteOptions {
   repeated StoresKey Keys = 1;
 }
 
+message StoresGetOptions {
+  repeated StoresKey Keys = 1;
+}
+
+message StoresGetResult {
+  repeated StoresKey Keys = 1;
+  repeated StoresValue Values = 2;
+}
+
 message StoresFindOptions {
   StoresKey Key = 1;
   int32 TopK = 2;
@@ -153,6 +163,11 @@ message Reply {
   double timing_token_generation = 5;
 }
 
+message GrammarTrigger {
+  string word = 1;
+  bool at_start = 2; 
+}
+
 message ModelOptions {
   string Model = 1;
   int32 ContextSize = 2;
@@ -237,6 +252,8 @@ message ModelOptions {
 
   string CacheTypeKey = 63;
   string CacheTypeValue = 64;
+
+  repeated GrammarTrigger GrammarTriggers = 65;
 }
 
 message Result {

backend/cpp/llama/grpc-server.cpp

@@ -468,6 +468,9 @@ struct llama_server_context
     bool add_bos_token      = true;
     bool has_eos_token      = true;
 
+    bool grammar_lazy = false;
+    std::vector<common_grammar_trigger> grammar_trigger_words;
+
     int32_t n_ctx;  // total context for all clients / slots
 
     // system prompt
@@ -706,6 +709,8 @@ struct llama_server_context
         slot->sparams.grammar           = json_value(data, "grammar",           default_sparams.grammar);
         slot->sparams.n_probs           = json_value(data, "n_probs",           default_sparams.n_probs);
         slot->sparams.min_keep          = json_value(data, "min_keep",          default_sparams.min_keep);
+        slot->sparams.grammar_trigger_words = grammar_trigger_words;
+        slot->sparams.grammar_lazy = grammar_lazy;
 
         if (slot->n_predict > 0 && slot->params.n_predict > slot->n_predict) {
             // Might be better to reject the request with a 400 ?
@@ -2374,6 +2379,21 @@ static void params_parse(const backend::ModelOptions* request,
     if ( request->ropefreqscale() != 0.0f ) {
         params.rope_freq_scale = request->ropefreqscale();
     }
+
+    if (request->grammartriggers_size() > 0) {
+        LOG_INFO("configuring grammar triggers", {});
+        llama.grammar_lazy = true;
+        for (int i = 0; i < request->grammartriggers_size(); i++) {
+            common_grammar_trigger trigger;
+            trigger.word = request->grammartriggers(i).word();
+            trigger.at_start = request->grammartriggers(i).at_start();
+            llama.grammar_trigger_words.push_back(trigger);
+            LOG_INFO("grammar trigger", {
+                { "word", trigger.word },
+                { "at_start", trigger.at_start }
+            });
+        }
+    }
 }
 
 
@@ -2522,6 +2542,18 @@ public:
         return grpc::Status::OK;
     }
 
+    grpc::Status TokenizeString(ServerContext* context, const backend::PredictOptions* request, backend::TokenizationResponse* response){
+         json data = parse_options(false, request, llama);
+
+         std::vector<llama_token> tokens = llama.tokenize(data["prompt"],false);
+
+         for (int i=0 ; i< tokens.size(); i++){
+            response->add_tokens(tokens[i]);
+         }
+
+        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();
 

backend/go/image/stablediffusion/main.go

@@ -1,21 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	grpc "github.com/mudler/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &Image{}); err != nil {
-		panic(err)
-	}
-}

backend/go/image/stablediffusion/stablediffusion.go

@@ -1,33 +0,0 @@
-package main
-
-// This is a wrapper to statisfy the GRPC service interface
-// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
-import (
-	"github.com/mudler/LocalAI/pkg/grpc/base"
-	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
-	"github.com/mudler/LocalAI/pkg/stablediffusion"
-)
-
-type Image struct {
-	base.SingleThread
-	stablediffusion *stablediffusion.StableDiffusion
-}
-
-func (image *Image) Load(opts *pb.ModelOptions) error {
-	var err error
-	// Note: the Model here is a path to a directory containing the model files
-	image.stablediffusion, err = stablediffusion.New(opts.ModelFile)
-	return err
-}
-
-func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
-	return image.stablediffusion.GenerateImage(
-		int(opts.Height),
-		int(opts.Width),
-		int(opts.Mode),
-		int(opts.Step),
-		int(opts.Seed),
-		opts.PositivePrompt,
-		opts.NegativePrompt,
-		opts.Dst)
-}

backend/go/stores/store.go

@@ -4,36 +4,101 @@ 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"
-	"context"
 	"fmt"
 	"math"
-	"runtime"
+	"slices"
 
 	"github.com/mudler/LocalAI/pkg/grpc/base"
 	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
-	chromem "github.com/philippgille/chromem-go"
 
 	"github.com/rs/zerolog/log"
 )
 
 type Store struct {
 	base.SingleThread
-	*chromem.DB
+
-	*chromem.Collection
+	// The sorted keys
+	keys [][]float32
+	// The sorted values
+	values [][]byte
+
+	// If for every K it holds that ||k||^2 = 1, then we can use the normalized distance functions
+	// TODO: Should we normalize incoming keys if they are not instead?
+	keysAreNormalized bool
+	// The first key decides the length of the keys
+	keyLen int
+}
+
+// TODO: Only used for sorting using Go's builtin implementation. The interfaces are columnar because
+// that's theoretically best for memory layout and cache locality, but this isn't optimized yet.
+type Pair struct {
+	Key   []float32
+	Value []byte
 }
 
 func NewStore() *Store {
-	return &Store{}
+	return &Store{
+		keys:              make([][]float32, 0),
+		values:            make([][]byte, 0),
+		keysAreNormalized: true,
+		keyLen:            -1,
+	}
+}
+
+func compareSlices(k1, k2 []float32) int {
+	assert(len(k1) == len(k2), fmt.Sprintf("compareSlices: len(k1) = %d, len(k2) = %d", len(k1), len(k2)))
+
+	return slices.Compare(k1, k2)
+}
+
+func hasKey(unsortedSlice [][]float32, target []float32) bool {
+	return slices.ContainsFunc(unsortedSlice, func(k []float32) bool {
+		return compareSlices(k, target) == 0
+	})
+}
+
+func findInSortedSlice(sortedSlice [][]float32, target []float32) (int, bool) {
+	return slices.BinarySearchFunc(sortedSlice, target, func(k, t []float32) int {
+		return compareSlices(k, t)
+	})
+}
+
+func isSortedPairs(kvs []Pair) bool {
+	for i := 1; i < len(kvs); i++ {
+		if compareSlices(kvs[i-1].Key, kvs[i].Key) > 0 {
+			return false
+		}
+	}
+
+	return true
+}
+
+func isSortedKeys(keys [][]float32) bool {
+	for i := 1; i < len(keys); i++ {
+		if compareSlices(keys[i-1], keys[i]) > 0 {
+			return false
+		}
+	}
+
+	return true
+}
+
+func sortIntoKeySlicese(keys []*pb.StoresKey) [][]float32 {
+	ks := make([][]float32, len(keys))
+
+	for i, k := range keys {
+		ks[i] = k.Floats
+	}
+
+	slices.SortFunc(ks, compareSlices)
+
+	assert(len(ks) == len(keys), fmt.Sprintf("len(ks) = %d, len(keys) = %d", len(ks), len(keys)))
+	assert(isSortedKeys(ks), "keys are not sorted")
+
+	return ks
 }
 
 func (s *Store) Load(opts *pb.ModelOptions) error {
-	db := chromem.NewDB()
-	collection, err := db.CreateCollection("all-documents", nil, nil)
-	if err != nil {
-		return err
-	}
-	s.DB = db
-	s.Collection = collection
 	return nil
 }
 
@@ -46,25 +111,156 @@ func (s *Store) StoresSet(opts *pb.StoresSetOptions) error {
 	if len(opts.Keys) != len(opts.Values) {
 		return fmt.Errorf("len(keys) = %d, len(values) = %d", len(opts.Keys), len(opts.Values))
 	}
-	docs := []chromem.Document{}
+
+	if s.keyLen == -1 {
+		s.keyLen = len(opts.Keys[0].Floats)
+	} else {
+		if len(opts.Keys[0].Floats) != s.keyLen {
+			return fmt.Errorf("Try to add key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen)
+		}
+	}
+
+	kvs := make([]Pair, len(opts.Keys))
 
 	for i, k := range opts.Keys {
-		docs = append(docs, chromem.Document{
+		if s.keysAreNormalized && !isNormalized(k.Floats) {
-			ID:      k.String(),
+			s.keysAreNormalized = false
-			Content: opts.Values[i].String(),
+			var sample []float32
-		})
+			if len(s.keys) > 5 {
+				sample = k.Floats[:5]
+			} else {
+				sample = k.Floats
+			}
+			log.Debug().Msgf("Key is not normalized: %v", sample)
+		}
+
+		kvs[i] = Pair{
+			Key:   k.Floats,
+			Value: opts.Values[i].Bytes,
+		}
 	}
 
-	return s.Collection.AddDocuments(context.Background(), docs, runtime.NumCPU())
+	slices.SortFunc(kvs, func(a, b Pair) int {
+		return compareSlices(a.Key, b.Key)
+	})
+
+	assert(len(kvs) == len(opts.Keys), fmt.Sprintf("len(kvs) = %d, len(opts.Keys) = %d", len(kvs), len(opts.Keys)))
+	assert(isSortedPairs(kvs), "keys are not sorted")
+
+	l := len(kvs) + len(s.keys)
+	merge_ks := make([][]float32, 0, l)
+	merge_vs := make([][]byte, 0, l)
+
+	i, j := 0, 0
+	for {
+		if i+j >= l {
+			break
+		}
+
+		if i >= len(kvs) {
+			merge_ks = append(merge_ks, s.keys[j])
+			merge_vs = append(merge_vs, s.values[j])
+			j++
+			continue
+		}
+
+		if j >= len(s.keys) {
+			merge_ks = append(merge_ks, kvs[i].Key)
+			merge_vs = append(merge_vs, kvs[i].Value)
+			i++
+			continue
+		}
+
+		c := compareSlices(kvs[i].Key, s.keys[j])
+		if c < 0 {
+			merge_ks = append(merge_ks, kvs[i].Key)
+			merge_vs = append(merge_vs, kvs[i].Value)
+			i++
+		} else if c > 0 {
+			merge_ks = append(merge_ks, s.keys[j])
+			merge_vs = append(merge_vs, s.values[j])
+			j++
+		} else {
+			merge_ks = append(merge_ks, kvs[i].Key)
+			merge_vs = append(merge_vs, kvs[i].Value)
+			i++
+			j++
+		}
+	}
+
+	assert(len(merge_ks) == l, fmt.Sprintf("len(merge_ks) = %d, l = %d", len(merge_ks), l))
+	assert(isSortedKeys(merge_ks), "merge keys are not sorted")
+
+	s.keys = merge_ks
+	s.values = merge_vs
+
+	return nil
 }
 
-func (s *Store) StoresReset(opts *pb.StoresResetOptions) error {
+func (s *Store) StoresDelete(opts *pb.StoresDeleteOptions) error {
-	err := s.DB.DeleteCollection("all-documents")
+	if len(opts.Keys) == 0 {
-	if err != nil {
+		return fmt.Errorf("no keys to delete")
-		return err
 	}
-	s.Collection, err = s.CreateCollection("all-documents", nil, nil)
+
-	return err
+	if len(opts.Keys) == 0 {
+		return fmt.Errorf("no keys to add")
+	}
+
+	if s.keyLen == -1 {
+		s.keyLen = len(opts.Keys[0].Floats)
+	} else {
+		if len(opts.Keys[0].Floats) != s.keyLen {
+			return fmt.Errorf("Trying to delete key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen)
+		}
+	}
+
+	ks := sortIntoKeySlicese(opts.Keys)
+
+	l := len(s.keys) - len(ks)
+	merge_ks := make([][]float32, 0, l)
+	merge_vs := make([][]byte, 0, l)
+
+	tail_ks := s.keys
+	tail_vs := s.values
+	for _, k := range ks {
+		j, found := findInSortedSlice(tail_ks, k)
+
+		if found {
+			merge_ks = append(merge_ks, tail_ks[:j]...)
+			merge_vs = append(merge_vs, tail_vs[:j]...)
+			tail_ks = tail_ks[j+1:]
+			tail_vs = tail_vs[j+1:]
+		} else {
+			assert(!hasKey(s.keys, k), fmt.Sprintf("Key exists, but was not found: t=%d, %v", len(tail_ks), k))
+		}
+
+		log.Debug().Msgf("Delete: found = %v, t = %d, j = %d, len(merge_ks) = %d, len(merge_vs) = %d", found, len(tail_ks), j, len(merge_ks), len(merge_vs))
+	}
+
+	merge_ks = append(merge_ks, tail_ks...)
+	merge_vs = append(merge_vs, tail_vs...)
+
+	assert(len(merge_ks) <= len(s.keys), fmt.Sprintf("len(merge_ks) = %d, len(s.keys) = %d", len(merge_ks), len(s.keys)))
+
+	s.keys = merge_ks
+	s.values = merge_vs
+
+	assert(len(s.keys) >= l, fmt.Sprintf("len(s.keys) = %d, l = %d", len(s.keys), l))
+	assert(isSortedKeys(s.keys), "keys are not sorted")
+	assert(func() bool {
+		for _, k := range ks {
+			if _, found := findInSortedSlice(s.keys, k); found {
+				return false
+			}
+		}
+		return true
+	}(), "Keys to delete still present")
+
+	if len(s.keys) != l {
+		log.Debug().Msgf("Delete: Some keys not found: len(s.keys) = %d, l = %d", len(s.keys), l)
+	}
+
+	return nil
 }
 
 func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error) {
@@ -115,12 +311,16 @@ func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error)
 }
 
 func isNormalized(k []float32) bool {
-	var sum float32
+	var sum float64
+
 	for _, v := range k {
-		sum += v
+		v64 := float64(v)
+		sum += v64*v64
 	}
 
-	return sum == 1.0
+	s := math.Sqrt(sum)
+
+	return s >= 0.99 && s <= 1.01
 }
 
 // TODO: This we could replace with handwritten SIMD code
@@ -132,7 +332,7 @@ func normalizedCosineSimilarity(k1, k2 []float32) float32 {
 		dot += k1[i] * k2[i]
 	}
 
-	assert(dot >= -1 && dot <= 1, fmt.Sprintf("dot = %f", dot))
+	assert(dot >= -1.01 && dot <= 1.01, fmt.Sprintf("dot = %f", dot))
 
 	// 2.0 * (1.0 - dot) would be the Euclidean distance
 	return dot
@@ -222,7 +422,7 @@ func cosineSimilarity(k1, k2 []float32, mag1 float64) float32 {
 
 	sim := float32(dot / (mag1 * math.Sqrt(mag2)))
 
-	assert(sim >= -1 && sim <= 1, fmt.Sprintf("sim = %f", sim))
+	assert(sim >= -1.01 && sim <= 1.01, fmt.Sprintf("sim = %f", sim))
 
 	return sim
 }

backend/python/autogptq/requirements-l4t.txt

@@ -0,0 +1,2 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch

backend/python/autogptq/requirements.txt

@@ -1,6 +1,6 @@
 accelerate
 auto-gptq==0.7.1
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi
 transformers

backend/python/bark/requirements-l4t.txt

@@ -0,0 +1,5 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+torchaudio
+transformers
+accelerate

backend/python/bark/requirements.txt

@@ -1,4 +1,4 @@
 bark==0.1.5
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi

backend/python/common/libbackend.sh

@@ -132,11 +132,16 @@ function installRequirements() {
     declare -a requirementFiles=(
         "${EDIR}/requirements-install.txt"
         "${EDIR}/requirements.txt"
-        "${EDIR}/requirements-${BUILD_TYPE}.txt"
     )
 
-    if [ "x${BUILD_TYPE}" != "x${BUILD_PROFILE}" ]; then
+    if [ -n "${BUILD_PLATFORM}" ]; then
-        requirementFiles+=("${EDIR}/requirements-${BUILD_PROFILE}.txt")
+        requirementFiles+=("${EDIR}/requirements-${BUILD_PLATFORM}.txt")
+    else
+        requirementFiles+=("${EDIR}/requirements-${BUILD_TYPE}.txt")
+
+        if [ "x${BUILD_TYPE}" != "x${BUILD_PROFILE}" ]; then
+            requirementFiles+=("${EDIR}/requirements-${BUILD_PROFILE}.txt")
+        fi
     fi
 
     # if BUILD_TYPE is empty, we are a CPU build, so we should try to install the CPU requirements
@@ -146,8 +151,14 @@ function installRequirements() {
 
     requirementFiles+=("${EDIR}/requirements-after.txt")
 
-    if [ "x${BUILD_TYPE}" != "x${BUILD_PROFILE}" ]; then
+    if [ -n "${BUILD_PLATFORM}" ]; then
-        requirementFiles+=("${EDIR}/requirements-${BUILD_PROFILE}-after.txt")
+        requirementFiles+=("${EDIR}/requirements-${BUILD_PLATFORM}-after.txt")
+    else
+        if [ "x${BUILD_TYPE}" != "x${BUILD_PROFILE}" ]; then
+            requirementFiles+=("${EDIR}/requirements-${BUILD_PROFILE}-after.txt")
+        else
+            requirementFiles+=("${EDIR}/requirements-${BUILD_TYPE}-after.txt")
+        fi
     fi
 
     for reqFile in ${requirementFiles[@]}; do

backend/python/common/template/requirements.txt

@@ -1,3 +1,3 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 grpcio-tools

backend/python/coqui/requirements-l4t.txt

@@ -0,0 +1,6 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+torchaudio
+transformers
+accelerate
+coqui-tts

backend/python/coqui/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi
 packaging==24.1

backend/python/diffusers/requirements-l4t.txt

@@ -0,0 +1,10 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+diffusers
+opencv-python
+transformers
+accelerate
+compel
+peft
+sentencepiece
+optimum-quanto

backend/python/diffusers/requirements.txt

@@ -1,5 +1,5 @@
 setuptools
-grpcio==1.69.0
+grpcio==1.70.0
 pillow
 protobuf
 certifi

backend/python/exllama2/requirements-l4t.txt

@@ -0,0 +1,4 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+transformers
+accelerate

backend/python/exllama2/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi
 wheel

backend/python/faster-whisper/Makefile

@@ -1,8 +1,9 @@
 .DEFAULT_GOAL := install
 
 .PHONY: install
-install: protogen
+install:
 	bash install.sh
+	$(MAKE) protogen
 
 .PHONY: protogen
 protogen: backend_pb2_grpc.py backend_pb2.py
@@ -12,14 +13,8 @@ protogen-clean:
 	$(RM) backend_pb2_grpc.py backend_pb2.py
 
 backend_pb2_grpc.py backend_pb2.py:
-	python3 -m grpc_tools.protoc -I../.. --python_out=. --grpc_python_out=. backend.proto
+	bash protogen.sh
 
 .PHONY: clean
 clean: protogen-clean
-	rm -rf venv __pycache__
+	rm -rf venv __pycache__
-
-.PHONY: test
-test: protogen
-	@echo "Testing openvoice..."
-	bash test.sh
-	@echo "openvoice tested."

backend/python/faster-whisper/backend.py

@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+"""
+This is an extra gRPC server of LocalAI for Bark TTS
+"""
+from concurrent import futures
+import time
+import argparse
+import signal
+import sys
+import os
+import backend_pb2
+import backend_pb2_grpc
+
+from faster_whisper import WhisperModel
+
+import grpc
+
+
+_ONE_DAY_IN_SECONDS = 60 * 60 * 24
+
+# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
+MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
+COQUI_LANGUAGE = os.environ.get('COQUI_LANGUAGE', None)
+
+# Implement the BackendServicer class with the service methods
+class BackendServicer(backend_pb2_grpc.BackendServicer):
+    """
+    BackendServicer is the class that implements the gRPC service
+    """
+    def Health(self, request, context):
+        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
+    def LoadModel(self, request, context):
+        device = "cpu"
+        # Get device
+        # device = "cuda" if request.CUDA else "cpu"
+        if request.CUDA:
+            device = "cuda"
+
+        try:
+            print("Preparing models, please wait", file=sys.stderr)
+            self.model = WhisperModel(request.Model, device=device, compute_type="float16")
+        except Exception as err:
+            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
+        # Implement your logic here for the LoadModel service
+        # Replace this with your desired response
+        return backend_pb2.Result(message="Model loaded successfully", success=True)
+
+    def AudioTranscription(self, request, context):
+        resultSegments = []
+        text = ""
+        try:
+            segments, info = self.model.transcribe(request.dst, beam_size=5, condition_on_previous_text=False)
+            id = 0
+            for segment in segments:
+                print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+                resultSegments.append(backend_pb2.TranscriptSegment(id=id, start=segment.start, end=segment.end, text=segment.text))
+                text += segment.text
+                id += 1            
+        except Exception as err:
+            print(f"Unexpected {err=}, {type(err)=}", file=sys.stderr)
+
+        return backend_pb2.TranscriptResult(segments=resultSegments, text=text)
+
+def serve(address):
+    server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))
+    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
+    server.add_insecure_port(address)
+    server.start()
+    print("Server started. Listening on: " + address, file=sys.stderr)
+
+    # Define the signal handler function
+    def signal_handler(sig, frame):
+        print("Received termination signal. Shutting down...")
+        server.stop(0)
+        sys.exit(0)
+
+    # Set the signal handlers for SIGINT and SIGTERM
+    signal.signal(signal.SIGINT, signal_handler)
+    signal.signal(signal.SIGTERM, signal_handler)
+
+    try:
+        while True:
+            time.sleep(_ONE_DAY_IN_SECONDS)
+    except KeyboardInterrupt:
+        server.stop(0)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Run the gRPC server.")
+    parser.add_argument(
+        "--addr", default="localhost:50051", help="The address to bind the server to."
+    )
+    args = parser.parse_args()
+
+    serve(args.addr)

backend/python/faster-whisper/install.sh

@@ -12,5 +12,3 @@ if [ "x${BUILD_PROFILE}" == "xintel" ]; then
 fi
 
 installRequirements
-
-python -m unidic download

backend/python/faster-whisper/requirements-cpu.txt

@@ -0,0 +1,8 @@
+faster-whisper
+opencv-python
+accelerate
+compel
+peft
+sentencepiece
+torch==2.4.1
+optimum-quanto

backend/python/faster-whisper/requirements-cublas11.txt

@@ -0,0 +1,9 @@
+--extra-index-url https://download.pytorch.org/whl/cu118
+torch==2.4.1+cu118
+faster-whisper
+opencv-python
+accelerate
+compel
+peft
+sentencepiece
+optimum-quanto

backend/python/faster-whisper/requirements-cublas12.txt

@@ -0,0 +1,8 @@
+torch==2.4.1
+faster-whisper
+opencv-python
+accelerate
+compel
+peft
+sentencepiece
+optimum-quanto

backend/python/faster-whisper/requirements-hipblas.txt

@@ -0,0 +1,3 @@
+--extra-index-url https://download.pytorch.org/whl/rocm6.0
+torch
+faster-whisper

backend/python/faster-whisper/requirements-intel.txt

@@ -1,8 +1,6 @@
 --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
 intel-extension-for-pytorch==2.3.110+xpu
 torch==2.3.1+cxx11.abi
-torchaudio==2.3.1+cxx11.abi
 oneccl_bind_pt==2.3.100+xpu
 optimum[openvino]
-transformers
+faster-whisper
-accelerate

backend/python/faster-whisper/requirements-l4t.txt

@@ -0,0 +1,9 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+faster-whisper
+opencv-python
+accelerate
+compel
+peft
+sentencepiece
+optimum-quanto

backend/python/faster-whisper/requirements.txt

@@ -0,0 +1,3 @@
+grpcio==1.70.0
+protobuf
+grpcio-tools

backend/python/kokoro/requirements-l4t.txt

@@ -0,0 +1,3 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+transformers

backend/python/kokoro/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 phonemizer
 scipy

backend/python/mamba/Makefile

@@ -1,29 +0,0 @@
-.PHONY: mamba
-mamba: protogen
-	bash install.sh 
-
-.PHONY: run
-run: protogen
-	@echo "Running mamba..."
-	bash run.sh
-	@echo "mamba run."
-
-.PHONY: test
-test: protogen
-	@echo "Testing mamba..."
-	bash test.sh
-	@echo "mamba tested."
-
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
-
-.PHONY: protogen-clean
-protogen-clean:
-	$(RM) backend_pb2_grpc.py backend_pb2.py
-
-backend_pb2_grpc.py backend_pb2.py:
-	python3 -m grpc_tools.protoc -I../.. --python_out=. --grpc_python_out=. backend.proto
-
-.PHONY: clean
-clean: protogen-clean
-	$(RM) -r venv __pycache__

backend/python/mamba/README.md

@@ -1,5 +0,0 @@
-# Creating a separate environment for the mamba project
-
-```
-make mamba
-```

backend/python/mamba/backend.py

@@ -1,179 +0,0 @@
-#!/usr/bin/env python3
-from concurrent import futures
-import time
-import argparse
-import signal
-import sys
-import os
-
-import backend_pb2
-import backend_pb2_grpc
-
-import grpc
-
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel
-
-_ONE_DAY_IN_SECONDS = 60 * 60 * 24
-
-# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
-MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
-MAMBA_CHAT= os.environ.get('MAMBA_CHAT', '1') == '1'
-
-# Implement the BackendServicer class with the service methods
-class BackendServicer(backend_pb2_grpc.BackendServicer):
-    """
-    A gRPC servicer that implements the Backend service defined in backend.proto.
-    """
-    def generate(self,prompt, max_new_tokens):
-        """
-        Generates text based on the given prompt and maximum number of new tokens.
-
-        Args:
-            prompt (str): The prompt to generate text from.
-            max_new_tokens (int): The maximum number of new tokens to generate.
-
-        Returns:
-            str: The generated text.
-        """
-        self.generator.end_beam_search()
-
-        # Tokenizing the input
-        ids = self.generator.tokenizer.encode(prompt)
-
-        self.generator.gen_begin_reuse(ids)
-        initial_len = self.generator.sequence[0].shape[0]
-        has_leading_space = False
-        decoded_text = ''
-        for i in range(max_new_tokens):
-            token = self.generator.gen_single_token()
-            if i == 0 and self.generator.tokenizer.tokenizer.IdToPiece(int(token)).startswith('▁'):
-                has_leading_space = True
-
-            decoded_text = self.generator.tokenizer.decode(self.generator.sequence[0][initial_len:])
-            if has_leading_space:
-                decoded_text = ' ' + decoded_text
-
-            if token.item() == self.generator.tokenizer.eos_token_id:
-                break
-        return decoded_text
-
-    def Health(self, request, context):
-        """
-        Returns a health check message.
-
-        Args:
-            request: The health check request.
-            context: The gRPC context.
-
-        Returns:
-            backend_pb2.Reply: The health check reply.
-        """
-        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
-
-    def LoadModel(self, request, context):
-        """
-        Loads a language model.
-
-        Args:
-            request: The load model request.
-            context: The gRPC context.
-
-        Returns:
-            backend_pb2.Result: The load model result.
-        """
-        try:
-            tokenizerModel = request.Tokenizer
-            if tokenizerModel == "":
-                tokenizerModel = request.Model
-
-            tokenizer = AutoTokenizer.from_pretrained(tokenizerModel)
-            if MAMBA_CHAT:
-                tokenizer.eos_token = "<|endoftext|>"
-                tokenizer.pad_token = tokenizer.eos_token
-            self.tokenizer = tokenizer
-            self.model = MambaLMHeadModel.from_pretrained(request.Model, device="cuda", dtype=torch.float16)
-        except Exception as err:
-            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
-        return backend_pb2.Result(message="Model loaded successfully", success=True)
-
-    def Predict(self, request, context):
-        """
-        Generates text based on the given prompt and sampling parameters.
-
-        Args:
-            request: The predict request.
-            context: The gRPC context.
-
-        Returns:
-            backend_pb2.Result: The predict result.
-        """
-        if request.TopP == 0:
-            request.TopP = 0.9
-
-        max_tokens = request.Tokens
-
-        if request.Tokens == 0:
-            max_tokens = 2000
-
-        # encoded_input = self.tokenizer(request.Prompt)
-        tokens = self.tokenizer(request.Prompt, return_tensors="pt")
-        input_ids = tokens.input_ids.to(device="cuda")
-        out = self.model.generate(input_ids=input_ids, max_length=max_tokens, temperature=request.Temperature,
-                                     top_p=request.TopP, eos_token_id=self.tokenizer.eos_token_id)
-
-        decoded = self.tokenizer.batch_decode(out)
-       
-        generated_text = decoded[0]
-
-        # Remove prompt from response if present
-        if request.Prompt in generated_text:
-            generated_text = generated_text.replace(request.Prompt, "")
-
-        return backend_pb2.Reply(message=bytes(generated_text, encoding='utf-8'))
-
-    def PredictStream(self, request, context):
-        """
-        Generates text based on the given prompt and sampling parameters, and streams the results.
-
-        Args:
-            request: The predict stream request.
-            context: The gRPC context.
-
-        Returns:
-            backend_pb2.Result: The predict stream result.
-        """
-        yield self.Predict(request, context)
-
-def serve(address):
-    server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))
-    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
-    server.add_insecure_port(address)
-    server.start()
-    print("Server started. Listening on: " + address, file=sys.stderr)
-
-    # Define the signal handler function
-    def signal_handler(sig, frame):
-        print("Received termination signal. Shutting down...")
-        server.stop(0)
-        sys.exit(0)
-
-    # Set the signal handlers for SIGINT and SIGTERM
-    signal.signal(signal.SIGINT, signal_handler)
-    signal.signal(signal.SIGTERM, signal_handler)
-
-    try:
-        while True:
-            time.sleep(_ONE_DAY_IN_SECONDS)
-    except KeyboardInterrupt:
-        server.stop(0)
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Run the gRPC server.")
-    parser.add_argument(
-        "--addr", default="localhost:50051", help="The address to bind the server to."
-    )
-    args = parser.parse_args()
-
-    serve(args.addr)

backend/python/mamba/install.sh

@@ -1,9 +0,0 @@
-#!/bin/bash
-set -e
-
-LIMIT_TARGETS="cublas"
-EXTRA_PIP_INSTALL_FLAGS="--no-build-isolation"
-
-source $(dirname $0)/../common/libbackend.sh
-
-installRequirements

backend/python/mamba/requirements-after.txt

@@ -1,2 +0,0 @@
-causal-conv1d==1.4.0
-mamba-ssm==2.2.2

backend/python/mamba/requirements-cpu.txt

@@ -1,2 +0,0 @@
-torch==2.4.1
-transformers

backend/python/mamba/requirements-cublas11.txt

@@ -1,3 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
-transformers

backend/python/mamba/requirements-cublas12.txt

@@ -1,2 +0,0 @@
-torch==2.4.1
-transformers

backend/python/mamba/requirements-install.txt

@@ -1,6 +0,0 @@
-# mabma does not specify it's build dependencies per PEP517, so we need to disable build isolation
-# this also means that we need to install the basic build dependencies into the venv ourselves
-# https://github.com/Dao-AILab/causal-conv1d/issues/24
-packaging
-setuptools
-wheel

backend/python/mamba/requirements.txt

@@ -1,3 +0,0 @@
-grpcio==1.69.0
-protobuf
-certifi

backend/python/mamba/run.sh

@@ -1,6 +0,0 @@
-#!/bin/bash
-LIMIT_TARGETS="cublas"
-
-source $(dirname $0)/../common/libbackend.sh
-
-startBackend $@

backend/python/mamba/test.py

@@ -1,76 +0,0 @@
-import unittest
-import subprocess
-import time
-import backend_pb2
-import backend_pb2_grpc
-
-import grpc
-
-import unittest
-import subprocess
-import time
-import grpc
-import backend_pb2_grpc
-import backend_pb2
-
-class TestBackendServicer(unittest.TestCase):
-    """
-    TestBackendServicer is the class that tests the gRPC service.
-
-    This class contains methods to test the startup and shutdown of the gRPC service.
-    """
-    def setUp(self):
-        self.service = subprocess.Popen(["python", "backend.py", "--addr", "localhost:50051"])
-        time.sleep(10)
-
-    def tearDown(self) -> None:
-        self.service.terminate()
-        self.service.wait()
-
-    def test_server_startup(self):
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.Health(backend_pb2.HealthMessage())
-                self.assertEqual(response.message, b'OK')
-        except Exception as err:
-            print(err)
-            self.fail("Server failed to start")
-        finally:
-            self.tearDown()
-    def test_load_model(self):
-        """
-        This method tests if the model is loaded successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions(Model="facebook/opt-125m"))
-                self.assertTrue(response.success)
-                self.assertEqual(response.message, "Model loaded successfully")
-        except Exception as err:
-            print(err)
-            self.fail("LoadModel service failed")
-        finally:
-            self.tearDown()
-
-    def test_text(self):
-        """
-        This method tests if the embeddings are generated successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions(Model="facebook/opt-125m"))
-                self.assertTrue(response.success)
-                req = backend_pb2.PredictOptions(Prompt="The capital of France is")
-                resp = stub.Predict(req)
-                self.assertIsNotNone(resp.message)
-        except Exception as err:
-            print(err)
-            self.fail("text service failed")
-        finally:
-            self.tearDown()

backend/python/openvoice/backend.py

@@ -1,158 +0,0 @@
-#!/usr/bin/env python3
-"""
-Extra gRPC server for OpenVoice models.
-"""
-from concurrent import futures
-
-import argparse
-import signal
-import sys
-import os
-import torch
-from openvoice import se_extractor
-from openvoice.api import ToneColorConverter
-from melo.api import TTS
-
-import time
-import backend_pb2
-import backend_pb2_grpc
-
-import grpc
-
-
-_ONE_DAY_IN_SECONDS = 60 * 60 * 24
-
-# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
-MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
-
-# Implement the BackendServicer class with the service methods
-class BackendServicer(backend_pb2_grpc.BackendServicer):
-    """
-    A gRPC servicer for the backend service.
-
-    This class implements the gRPC methods for the backend service, including Health, LoadModel, and Embedding.
-    """
-    def Health(self, request, context):
-        """
-        A gRPC method that returns the health status of the backend service.
-
-        Args:
-            request: A HealthRequest object that contains the request parameters.
-            context: A grpc.ServicerContext object that provides information about the RPC.
-
-        Returns:
-            A Reply object that contains the health status of the backend service.
-        """
-        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
-
-    def LoadModel(self, request, context):
-        """
-        A gRPC method that loads a model into memory.
-
-        Args:
-            request: A LoadModelRequest object that contains the request parameters.
-            context: A grpc.ServicerContext object that provides information about the RPC.
-
-        Returns:
-            A Result object that contains the result of the LoadModel operation.
-        """
-        model_name = request.Model
-        try:
-
-            self.clonedVoice = False
-            # Assume directory from request.ModelFile.
-            # Only if request.LoraAdapter it's not an absolute path
-            if request.AudioPath and request.ModelFile != "" and not os.path.isabs(request.AudioPath):
-                # get base path of modelFile
-                modelFileBase = os.path.dirname(request.ModelFile)
-                request.AudioPath = os.path.join(modelFileBase, request.AudioPath)
-            if request.AudioPath != "":
-                self.clonedVoice = True
-
-            self.modelpath = request.ModelFile
-            self.speaker = request.Type
-            self.ClonedVoicePath = request.AudioPath
-            
-            ckpt_converter = request.Model+'/converter'
-            device = "cuda:0" if torch.cuda.is_available() else "cpu"
-            self.device = device
-            self.tone_color_converter = None
-            if self.clonedVoice:
-                self.tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)
-                self.tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
-       
-        except Exception as err:
-            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
-
-        return backend_pb2.Result(message="Model loaded successfully", success=True)
-
-    def TTS(self, request, context):
-        model_name = request.model
-        if model_name == "":
-            return backend_pb2.Result(success=False, message="request.model is required")
-        try:
-            # Speed is adjustable
-            speed = 1.0
-            voice = "EN"
-            if request.voice:
-                voice = request.voice
-            model = TTS(language=voice, device=self.device)
-            speaker_ids = model.hps.data.spk2id
-            speaker_key = self.speaker
-            modelpath = self.modelpath
-            for s in speaker_ids.keys():
-                print(f"Speaker: {s} - ID: {speaker_ids[s]}")
-            speaker_id = speaker_ids[speaker_key]
-            speaker_key = speaker_key.lower().replace('_', '-')
-            source_se = torch.load(f'{modelpath}/base_speakers/ses/{speaker_key}.pth', map_location=self.device)
-            model.tts_to_file(request.text, speaker_id, request.dst, speed=speed)
-            if self.clonedVoice:
-                reference_speaker = self.ClonedVoicePath
-                target_se, audio_name = se_extractor.get_se(reference_speaker, self.tone_color_converter, vad=False)
-                # Run the tone color converter
-                encode_message = "@MyShell"
-                self.tone_color_converter.convert(
-                    audio_src_path=request.dst, 
-                    src_se=source_se, 
-                    tgt_se=target_se, 
-                    output_path=request.dst,
-                    message=encode_message)
-           
-            print("[OpenVoice] TTS generated!", file=sys.stderr)
-            print("[OpenVoice] TTS saved to", request.dst, file=sys.stderr)
-            print(request, file=sys.stderr)
-        except Exception as err:
-            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
-        return backend_pb2.Result(success=True)
-
-def serve(address):
-    server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))
-    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
-    server.add_insecure_port(address)
-    server.start()
-    print("[OpenVoice] Server started. Listening on: " + address, file=sys.stderr)
-
-    # Define the signal handler function
-    def signal_handler(sig, frame):
-        print("[OpenVoice] Received termination signal. Shutting down...")
-        server.stop(0)
-        sys.exit(0)
-
-    # Set the signal handlers for SIGINT and SIGTERM
-    signal.signal(signal.SIGINT, signal_handler)
-    signal.signal(signal.SIGTERM, signal_handler)
-
-    try:
-        while True:
-            time.sleep(_ONE_DAY_IN_SECONDS)
-    except KeyboardInterrupt:
-        server.stop(0)
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Run the gRPC server.")
-    parser.add_argument(
-        "--addr", default="localhost:50051", help="The address to bind the server to."
-    )
-    args = parser.parse_args()
-    print(f"[OpenVoice] startup: {args}", file=sys.stderr)
-    serve(args.addr)

backend/python/openvoice/requirements-cpu.txt

@@ -1,7 +0,0 @@
-torch==2.4.1
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git
-whisper-timestamped
-pydub==0.25.1
-wavmark==0.0.3
-eng_to_ipa==0.0.2

backend/python/openvoice/requirements-cublas11.txt

@@ -1,8 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git
-whisper-timestamped
-pydub==0.25.1
-wavmark==0.0.3
-eng_to_ipa==0.0.2

backend/python/openvoice/requirements-cublas12.txt

@@ -1,7 +0,0 @@
-torch==2.4.1
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git
-whisper-timestamped
-pydub==0.25.1
-wavmark==0.0.3
-eng_to_ipa==0.0.2

backend/python/openvoice/requirements-hipblas.txt

@@ -1,8 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.4.1+rocm6.0
-git+https://github.com/myshell-ai/MeloTTS.git
-git+https://github.com/myshell-ai/OpenVoice.git
-whisper-timestamped
-pydub==0.25.1
-wavmark==0.0.3
-eng_to_ipa==0.0.2

backend/python/openvoice/requirements-intel.txt

@@ -1,24 +0,0 @@
---extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-intel-extension-for-pytorch==2.3.110+xpu
-torch==2.3.1+cxx11.abi
-torchaudio==2.3.1+cxx11.abi
-oneccl_bind_pt==2.3.100+xpu
-optimum[openvino]
-grpcio==1.69.0
-protobuf
-librosa==0.9.1
-faster-whisper==0.9.0
-pydub==0.25.1
-wavmark==0.0.3
-eng_to_ipa==0.0.2
-inflect==7.0.0
-unidecode==1.3.7
-whisper-timestamped==1.14.2
-openai
-python-dotenv
-pypinyin==0.50.0
-cn2an==0.5.22
-jieba==0.42.1
-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

@@ -1,17 +0,0 @@
-grpcio==1.69.0
-protobuf
-librosa
-faster-whisper
-inflect
-unidecode
-openai
-python-dotenv
-pypinyin
-cn2an==0.5.22
-numpy==1.22.0
-networkx==2.8.8
-jieba==0.42.1
-gradio==5.9.1
-langid==1.1.6
-llvmlite==0.43.0
-setuptools

backend/python/openvoice/test.py

@@ -1,82 +0,0 @@
-"""
-A test script to test the gRPC service
-"""
-import unittest
-import subprocess
-import time
-import backend_pb2
-import backend_pb2_grpc
-
-import grpc
-
-
-class TestBackendServicer(unittest.TestCase):
-    """
-    TestBackendServicer is the class that tests the gRPC service
-    """
-    def setUp(self):
-        """
-        This method sets up the gRPC service by starting the server
-        """
-        self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
-        time.sleep(30)
-
-    def tearDown(self) -> None:
-        """
-        This method tears down the gRPC service by terminating the server
-        """
-        self.service.terminate()
-        self.service.wait()
-
-    def test_server_startup(self):
-        """
-        This method tests if the server starts up successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.Health(backend_pb2.HealthMessage())
-                self.assertEqual(response.message, b'OK')
-        except Exception as err:
-            print(err)
-            self.fail("Server failed to start")
-        finally:
-            self.tearDown()
-
-    def test_load_model(self):
-        """
-        This method tests if the model is loaded successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions(Model="checkpoints_v2", 
-                                                                    Type="en-us"))
-                self.assertTrue(response.success)
-                self.assertEqual(response.message, "Model loaded successfully")
-        except Exception as err:
-            print(err)
-            self.fail("LoadModel service failed")
-        finally:
-            self.tearDown()
-
-    def test_tts(self):
-        """
-        This method tests if the embeddings are generated successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions(Model="dingzhen"))
-                self.assertTrue(response.success)
-                tts_request = backend_pb2.TTSRequest(text="80s TV news production music hit for tonight's biggest story", voice="EN")
-                tts_response = stub.TTS(tts_request)
-                self.assertIsNotNone(tts_response)
-        except Exception as err:
-            print(err)
-            self.fail("TTS service failed")
-        finally:
-            self.tearDown()

backend/python/openvoice/test.sh

@@ -1,12 +0,0 @@
-#!/bin/bash
-set -e
-
-source $(dirname $0)/../common/libbackend.sh
-
-# Download checkpoints if not present
-if [ ! -d "checkpoints_v2" ]; then
-    wget https://myshell-public-repo-host.s3.amazonaws.com/openvoice/checkpoints_v2_0417.zip -O checkpoints_v2.zip
-    unzip checkpoints_v2.zip
-fi
-
-runUnittests

backend/python/parler-tts/Makefile

@@ -1,44 +0,0 @@
-export CONDA_ENV_PATH = "parler.yml"
-SKIP_CONDA?=0
-ifeq ($(BUILD_TYPE), cublas)
-export CONDA_ENV_PATH = "parler-nvidia.yml"
-endif
-
-# Intel GPU are supposed to have dependencies installed in the main python
-# environment, so we skip conda installation for SYCL builds.
-# https://github.com/intel/intel-extension-for-pytorch/issues/538
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-export SKIP_CONDA=1
-endif
-
-.PHONY: parler-tts
-parler-tts:
-	@echo "Installing $(CONDA_ENV_PATH)..."
-	bash install.sh $(CONDA_ENV_PATH)
-	$(MAKE) protogen
-
-.PHONY: run
-run: protogen
-	@echo "Running transformers..."
-	bash run.sh
-	@echo "transformers run."
-
-.PHONY: test
-test: protogen
-	@echo "Testing transformers..."
-	bash test.sh
-	@echo "transformers tested."
-
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
-
-.PHONY: protogen-clean
-protogen-clean:
-	$(RM) backend_pb2_grpc.py backend_pb2.py
-
-backend_pb2_grpc.py backend_pb2.py:
-	bash protogen.sh
-
-.PHONY: clean
-clean: protogen-clean
-	$(RM) -r venv __pycache__

backend/python/parler-tts/backend.py

@@ -1,125 +0,0 @@
-#!/usr/bin/env python3
-"""
-Extra gRPC server for MusicgenForConditionalGeneration models.
-"""
-from concurrent import futures
-
-import argparse
-import signal
-import sys
-import os
-
-import time
-import backend_pb2
-import backend_pb2_grpc
-
-import grpc
-
-from scipy.io.wavfile import write as write_wav
-
-from parler_tts import ParlerTTSForConditionalGeneration
-from transformers import AutoTokenizer
-import soundfile as sf  
-import torch
-
-_ONE_DAY_IN_SECONDS = 60 * 60 * 24
-
-# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
-MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
-
-# Implement the BackendServicer class with the service methods
-class BackendServicer(backend_pb2_grpc.BackendServicer):
-    """
-    A gRPC servicer for the backend service.
-
-    This class implements the gRPC methods for the backend service, including Health, LoadModel, and Embedding.
-    """
-    def Health(self, request, context):
-        """
-        A gRPC method that returns the health status of the backend service.
-
-        Args:
-            request: A HealthRequest object that contains the request parameters.
-            context: A grpc.ServicerContext object that provides information about the RPC.
-
-        Returns:
-            A Reply object that contains the health status of the backend service.
-        """
-        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
-
-    def LoadModel(self, request, context):
-        """
-        A gRPC method that loads a model into memory.
-
-        Args:
-            request: A LoadModelRequest object that contains the request parameters.
-            context: A grpc.ServicerContext object that provides information about the RPC.
-
-        Returns:
-            A Result object that contains the result of the LoadModel operation.
-        """
-        model_name = request.Model
-        device = "cuda:0" if torch.cuda.is_available() else "cpu"
-        try:
-            self.model = ParlerTTSForConditionalGeneration.from_pretrained(model_name).to(device)
-            self.tokenizer = AutoTokenizer.from_pretrained(model_name)
-        except Exception as err:
-            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
-
-        return backend_pb2.Result(message="Model loaded successfully", success=True)
-
-    def TTS(self, request, context):
-        model_name = request.model
-        voice = request.voice
-        if voice == "":
-            voice = "A female speaker with a slightly low-pitched voice delivers her words quite expressively, in a very confined sounding environment with clear audio quality. She speaks very fast."
-        if model_name == "":
-            return backend_pb2.Result(success=False, message="request.model is required")
-        try:
-            device = "cuda:0" if torch.cuda.is_available() else "cpu"
-            input_ids = self.tokenizer(voice, return_tensors="pt").input_ids.to(device)
-            prompt_input_ids = self.tokenizer(request.text, return_tensors="pt").input_ids.to(device)
-           
-            generation = self.model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
-            audio_arr = generation.cpu().numpy().squeeze()
-            print("[parler-tts] TTS generated!", file=sys.stderr)
-            sf.write(request.dst, audio_arr, self.model.config.sampling_rate)
-            print("[parler-tts] TTS saved to", request.dst, file=sys.stderr)
-            print("[parler-tts] TTS for", file=sys.stderr)
-            print(request, file=sys.stderr)
-        except Exception as err:
-            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
-        return backend_pb2.Result(success=True)
-
-
-def serve(address):
-    server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))
-    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
-    server.add_insecure_port(address)
-    server.start()
-    print("[parler-tts] Server started. Listening on: " + address, file=sys.stderr)
-
-    # Define the signal handler function
-    def signal_handler(sig, frame):
-        print("[parler-tts] Received termination signal. Shutting down...")
-        server.stop(0)
-        sys.exit(0)
-
-    # Set the signal handlers for SIGINT and SIGTERM
-    signal.signal(signal.SIGINT, signal_handler)
-    signal.signal(signal.SIGTERM, signal_handler)
-
-    try:
-        while True:
-            time.sleep(_ONE_DAY_IN_SECONDS)
-    except KeyboardInterrupt:
-        server.stop(0)
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Run the gRPC server.")
-    parser.add_argument(
-        "--addr", default="localhost:50051", help="The address to bind the server to."
-    )
-    args = parser.parse_args()
-    print(f"[parler-tts] startup: {args}", file=sys.stderr)
-    serve(args.addr)

backend/python/parler-tts/install.sh

@@ -1,28 +0,0 @@
-#!/bin/bash
-set -e
-
-source $(dirname $0)/../common/libbackend.sh
-
-# This is here because the Intel pip index is broken and returns 200 status codes for every package name, it just doesn't return any package links.
-# This makes uv think that the package exists in the Intel pip index, and by default it stops looking at other pip indexes once it finds a match.
-# We need uv to continue falling through to the pypi default index to find optimum[openvino] in the pypi index
-# the --upgrade actually allows us to *downgrade* torch to the version provided in the Intel pip index
-if [ "x${BUILD_PROFILE}" == "xintel" ]; then
-    EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
-fi
-
-
-installRequirements
-
-
-# https://github.com/descriptinc/audiotools/issues/101
-# incompatible protobuf versions.
-PYDIR=python3.10
-pyenv="${MY_DIR}/venv/lib/${PYDIR}/site-packages/google/protobuf/internal/"
-
-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 +0,0 @@
-git+https://github.com/huggingface/parler-tts.git@8e465f1b5fcd223478e07175cb40494d19ffbe17
-llvmlite==0.43.0
-numba==0.60.0
-grpcio-tools==1.42.0

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

@@ -1,3 +0,0 @@
-transformers
-accelerate
-torch==2.4.1

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

@@ -1,5 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
-torchaudio==2.4.1+cu118
-transformers
-accelerate

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

@@ -1,4 +0,0 @@
-torch==2.4.1
-torchaudio==2.4.1
-transformers
-accelerate

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

@@ -1,5 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.3.0+rocm6.0
-torchaudio==2.3.0+rocm6.0
-transformers
-accelerate

backend/python/parler-tts/requirements.txt

@@ -1,4 +0,0 @@
-grpcio==1.69.0
-certifi
-llvmlite==0.43.0
-setuptools

backend/python/parler-tts/run.sh

@@ -1,4 +0,0 @@
-#!/bin/bash
-source $(dirname $0)/../common/libbackend.sh
-
-startBackend $@

backend/python/parler-tts/test.py

@@ -1,81 +0,0 @@
-"""
-A test script to test the gRPC service
-"""
-import unittest
-import subprocess
-import time
-import backend_pb2
-import backend_pb2_grpc
-
-import grpc
-
-
-class TestBackendServicer(unittest.TestCase):
-    """
-    TestBackendServicer is the class that tests the gRPC service
-    """
-    def setUp(self):
-        """
-        This method sets up the gRPC service by starting the server
-        """
-        self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
-        time.sleep(10)
-
-    def tearDown(self) -> None:
-        """
-        This method tears down the gRPC service by terminating the server
-        """
-        self.service.terminate()
-        self.service.wait()
-
-    def test_server_startup(self):
-        """
-        This method tests if the server starts up successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.Health(backend_pb2.HealthMessage())
-                self.assertEqual(response.message, b'OK')
-        except Exception as err:
-            print(err)
-            self.fail("Server failed to start")
-        finally:
-            self.tearDown()
-
-    def test_load_model(self):
-        """
-        This method tests if the model is loaded successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions(Model="parler-tts/parler_tts_mini_v0.1"))
-                self.assertTrue(response.success)
-                self.assertEqual(response.message, "Model loaded successfully")
-        except Exception as err:
-            print(err)
-            self.fail("LoadModel service failed")
-        finally:
-            self.tearDown()
-
-    def test_tts(self):
-        """
-        This method tests if the embeddings are generated successfully
-        """
-        try:
-            self.setUp()
-            with grpc.insecure_channel("localhost:50051") as channel:
-                stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions(Model="parler-tts/parler_tts_mini_v0.1"))
-                self.assertTrue(response.success)
-                tts_request = backend_pb2.TTSRequest(text="Hey, how are you doing today?")
-                tts_response = stub.TTS(tts_request)
-                self.assertIsNotNone(tts_response)
-        except Exception as err:
-            print(err)
-            self.fail("TTS service failed")
-        finally:
-            self.tearDown()

backend/python/parler-tts/test.sh

@@ -1,6 +0,0 @@
-#!/bin/bash
-set -e
-
-source $(dirname $0)/../common/libbackend.sh
-
-runUnittests

backend/python/rerankers/requirements-l4t.txt

@@ -0,0 +1,5 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+transformers
+accelerate
+torch
+rerankers[transformers]

backend/python/rerankers/requirements.txt

@@ -1,3 +1,3 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi

backend/python/transformers/backend.py

@@ -21,7 +21,7 @@ import torch.cuda
 
 
 XPU=os.environ.get("XPU", "0") == "1"
-from transformers import AutoTokenizer, AutoModel, set_seed, TextIteratorStreamer, StoppingCriteriaList, StopStringCriteria
+from transformers import AutoTokenizer, AutoModel, set_seed, TextIteratorStreamer, StoppingCriteriaList, StopStringCriteria, MambaConfig, MambaForCausalLM
 from transformers import AutoProcessor, MusicgenForConditionalGeneration
 from scipy.io import wavfile
 import outetts
@@ -245,6 +245,10 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
                 autoTokenizer = False
                 self.model = SentenceTransformer(model_name, trust_remote_code=request.TrustRemoteCode)
                 self.SentenceTransformer = True
+            elif request.Type == "Mamba":
+                autoTokenizer = False
+                self.tokenizer = AutoTokenizer.from_pretrained(model_name)
+                self.model = MambaForCausalLM.from_pretrained(model_name)
             else:
                 print("Automodel", file=sys.stderr)
                 self.model = AutoModel.from_pretrained(model_name, 

backend/python/transformers/requirements-cpu.txt

@@ -5,4 +5,4 @@ accelerate
 transformers
 bitsandbytes
 outetts
-sentence-transformers==3.3.1
+sentence-transformers==3.4.1

backend/python/transformers/requirements-cublas11.txt

@@ -6,4 +6,4 @@ accelerate
 transformers
 bitsandbytes
 outetts
-sentence-transformers==3.3.1
+sentence-transformers==3.4.1

backend/python/transformers/requirements-cublas12.txt

@@ -5,4 +5,4 @@ numba==0.60.0
 transformers
 bitsandbytes
 outetts
-sentence-transformers==3.3.1
+sentence-transformers==3.4.1

backend/python/transformers/requirements-hipblas.txt

@@ -7,4 +7,4 @@ numba==0.60.0
 bitsandbytes
 outetts
 bitsandbytes
-sentence-transformers==3.3.1
+sentence-transformers==3.4.1

backend/python/transformers/requirements-intel.txt

@@ -8,4 +8,4 @@ numba==0.60.0
 intel-extension-for-transformers
 bitsandbytes
 outetts
-sentence-transformers==3.3.1
+sentence-transformers==3.4.1

backend/python/transformers/requirements-l4t.txt

@@ -0,0 +1,9 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+torch
+accelerate
+llvmlite==0.43.0
+numba==0.60.0
+transformers
+bitsandbytes
+outetts
+sentence-transformers==3.4.1

backend/python/transformers/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi
 setuptools

backend/python/vllm/requirements-after.txt

@@ -1 +0,0 @@
-vllm

backend/python/vllm/requirements-cpu.txt

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

backend/python/vllm/requirements-cublas11.txt

@@ -2,4 +2,5 @@
 accelerate
 torch==2.4.1+cu118
 transformers
-bitsandbytes
+bitsandbytes
+vllm

backend/python/vllm/requirements-cublas12.txt

@@ -1,4 +1,5 @@
 accelerate
 torch==2.4.1
 transformers
-bitsandbytes
+bitsandbytes
+vllm

backend/python/vllm/requirements-hipblas.txt

@@ -2,4 +2,5 @@
 accelerate
 torch==2.4.1+rocm6.0
 transformers
-bitsandbytes
+bitsandbytes
+vllm

backend/python/vllm/requirements-intel.txt

@@ -6,4 +6,5 @@ transformers
 optimum[openvino]
 setuptools
 bitsandbytes
-oneccl_bind_pt==2.3.100+xpu
+oneccl_bind_pt==2.3.100+xpu
+vllm

backend/python/vllm/requirements-l4t.txt

@@ -0,0 +1,7 @@
+--index-url https://pypi.jetson-ai-lab.dev/jp6/cu126/
+accelerate
+torch
+vllm
+transformers
+bitsandbytes
+flash-attn

backend/python/vllm/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.69.0
+grpcio==1.70.0
 protobuf
 certifi
 setuptools

core/application/startup.go

@@ -62,7 +62,7 @@ func New(opts ...config.AppOption) (*Application, error) {
 		}
 	}
 
-	if err := pkgStartup.InstallModels(options.Galleries, options.ModelLibraryURL, options.ModelPath, options.EnforcePredownloadScans, nil, options.ModelsURL...); err != nil {
+	if err := pkgStartup.InstallModels(options.Galleries, options.ModelPath, options.EnforcePredownloadScans, nil, options.ModelsURL...); err != nil {
 		log.Error().Err(err).Msg("error installing models")
 	}
 

core/backend/options.go

@@ -118,9 +118,19 @@ func grpcModelOpts(c config.BackendConfig) *pb.ModelOptions {
 		nGPULayers = *c.NGPULayers
 	}
 
+	triggers := make([]*pb.GrammarTrigger, 0)
+	for _, t := range c.FunctionsConfig.GrammarConfig.GrammarTriggers {
+		triggers = append(triggers, &pb.GrammarTrigger{
+			Word:    t.Word,
+			AtStart: t.AtStart,
+		})
+
+	}
+
 	return &pb.ModelOptions{
 		CUDA:                 c.CUDA || c.Diffusers.CUDA,
 		SchedulerType:        c.Diffusers.SchedulerType,
+		GrammarTriggers:      triggers,
 		PipelineType:         c.Diffusers.PipelineType,
 		CFGScale:             c.CFGScale,
 		LoraAdapter:          c.LoraAdapter,

core/backend/tokenize.go

@@ -16,12 +16,7 @@ func ModelTokenize(s string, loader *model.ModelLoader, backendConfig config.Bac
 
 	opts := ModelOptions(backendConfig, appConfig, model.WithModel(modelFile))
 
-	if backendConfig.Backend == "" {
+	inferenceModel, err = loader.Load(opts...)
-		inferenceModel, err = loader.Load(opts...)
-	} else {
-		opts = append(opts, model.WithBackendString(backendConfig.Backend))
-		inferenceModel, err = loader.Load(opts...)
-	}
 	if err != nil {
 		return schema.TokenizeResponse{}, err
 	}
@@ -35,6 +30,10 @@ func ModelTokenize(s string, loader *model.ModelLoader, backendConfig config.Bac
 		return schema.TokenizeResponse{}, err
 	}
 
+	if resp.Tokens == nil {
+		resp.Tokens = make([]int32, 0)
+	}
+
 	return schema.TokenizeResponse{
 		Tokens: resp.Tokens,
 	}, nil

core/cli/models.go

@@ -100,7 +100,7 @@ func (mi *ModelsInstall) Run(ctx *cliContext.Context) error {
 			log.Info().Str("model", modelName).Str("license", model.License).Msg("installing model")
 		}
 
-		err = startup.InstallModels(galleries, "", mi.ModelsPath, !mi.DisablePredownloadScan, progressCallback, modelName)
+		err = startup.InstallModels(galleries, mi.ModelsPath, !mi.DisablePredownloadScan, progressCallback, modelName)
 		if err != nil {
 			return err
 		}

core/cli/run.go

@@ -32,7 +32,6 @@ type RunCMD struct {
 
 	Galleries           string   `env:"LOCALAI_GALLERIES,GALLERIES" help:"JSON list of galleries" group:"models" default:"${galleries}"`
 	AutoloadGalleries   bool     `env:"LOCALAI_AUTOLOAD_GALLERIES,AUTOLOAD_GALLERIES" group:"models"`
-	RemoteLibrary       string   `env:"LOCALAI_REMOTE_LIBRARY,REMOTE_LIBRARY" default:"${remoteLibraryURL}" help:"A LocalAI remote library URL" group:"models"`
 	PreloadModels       string   `env:"LOCALAI_PRELOAD_MODELS,PRELOAD_MODELS" help:"A List of models to apply in JSON at start" group:"models"`
 	Models              []string `env:"LOCALAI_MODELS,MODELS" help:"A List of model configuration URLs to load" group:"models"`
 	PreloadModelsConfig string   `env:"LOCALAI_PRELOAD_MODELS_CONFIG,PRELOAD_MODELS_CONFIG" help:"A List of models to apply at startup. Path to a YAML config file" group:"models"`
@@ -90,7 +89,6 @@ func (r *RunCMD) Run(ctx *cliContext.Context) error {
 		config.WithDynamicConfigDirPollInterval(r.LocalaiConfigDirPollInterval),
 		config.WithF16(r.F16),
 		config.WithStringGalleries(r.Galleries),
-		config.WithModelLibraryURL(r.RemoteLibrary),
 		config.WithCors(r.CORS),
 		config.WithCorsAllowOrigins(r.CORSAllowOrigins),
 		config.WithCsrf(r.CSRF),