⬆️ Update ggerganov/llama.cpp (#1750 )

Signed-off-by: GitHub <noreply@github.com> Co-authored-by: mudler <mudler@users.noreply.github.com>
⬆️ Update ggerganov/llama.cpp (#1740 )
2026-02-03 11:13:31 -05:00 · 2024-02-24 00:06:46 +01:00 · 2024-02-23 00:07:15 +01:00 · 2024-02-22 16:35:06 +01:00 · 2024-02-22 09:33:23 +00:00 · 2024-02-22 00:15:08 +01:00
295 changed files with 9714 additions and 7377 deletions
--- a/.github/ISSUE_TEMPLATE/bug_report.md
+++ b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -2,9 +2,7 @@
 name: Bug report
 about: Create a report to help us improve
 title: ''
-labels: bug
-assignees: mudler
-
+labels: bug, unconfirmed, up-for-grabs
 ---

 <!-- Thanks for helping us to improve LocalAI! We welcome all bug reports. Please fill out each area of the template so we can better help you. Comments like this will be hidden when you post but you can delete them if you wish. -->
--- a/.github/ISSUE_TEMPLATE/feature_request.md
+++ b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -2,9 +2,7 @@
 name: Feature request
 about: Suggest an idea for this project
 title: ''
-labels: enhancement
-assignees: mudler
-
+labels: enhancement, up-for-grabs
 ---

 <!-- Thanks for helping us to improve LocalAI! We welcome all feature requests. Please fill out each area of the template so we can better help you. Comments like this will be hidden when you post but you can delete them if you wish. -->
--- a/.github/bump_docs.sh
+++ b/.github/bump_docs.sh
@@ -0,0 +1,7 @@
+#!/bin/bash
+set -xe
+REPO=$1
+
+LATEST_TAG=$(curl -s "https://api.github.com/repos/$REPO/releases/latest" | jq -r '.name')
+
+cat <<< $(jq ".version = \"$LATEST_TAG\"" docs/data/version.json) > docs/data/version.json
--- a/.github/workflows/bump_docs.yaml
+++ b/.github/workflows/bump_docs.yaml
@@ -0,0 +1,31 @@
+name: Bump dependencies
+on:
+  schedule:
+    - cron: 0 20 * * *
+  workflow_dispatch:
+jobs:
+  bump:
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - repository: "mudler/LocalAI"
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Bump dependencies 🔧
+        run: |
+          bash .github/bump_docs.sh ${{ matrix.repository }}
+      - name: Create Pull Request
+        uses: peter-evans/create-pull-request@v5
+        with:
+          token: ${{ secrets.UPDATE_BOT_TOKEN }}
+          push-to-fork: ci-forks/LocalAI
+          commit-message: ':arrow_up: Update docs version ${{ matrix.repository }}'
+          title: ':arrow_up: Update docs version ${{ matrix.repository }}'
+          branch: "update/docs"
+          body: Bump of ${{ matrix.repository }} version inside docs
+          signoff: true
+
+
+
--- a/.github/workflows/image-pr.yml
+++ b/.github/workflows/image-pr.yml
@@ -0,0 +1,108 @@
+---
+name: 'build container images tests'
+
+on:
+  pull_request:
+
+concurrency:
+  group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
+jobs:
+  extras-image-build:
+    uses: ./.github/workflows/image_build.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      ffmpeg: ${{ matrix.ffmpeg }}
+      image-type: ${{ matrix.image-type }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      # Pushing with all jobs in parallel
+      # eats the bandwidth of all the nodes
+      max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
+      matrix:
+        include:
+          - build-type: ''
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-ffmpeg'
+            ffmpeg: 'true'
+            image-type: 'extras'
+            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "1"
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-cublas-cuda12-ffmpeg'
+            ffmpeg: 'true'
+            image-type: 'extras'
+            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas'
+            ffmpeg: 'false'
+            image-type: 'extras'
+            base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
+            runs-on: 'arc-runner-set'
+  core-image-build:
+    uses: ./.github/workflows/image_build.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      ffmpeg: ${{ matrix.ffmpeg }}
+      image-type: ${{ matrix.image-type }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      matrix:
+        include:
+          - build-type: ''
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-ffmpeg-core'
+            ffmpeg: 'true'
+            image-type: 'core'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+          - build-type: 'sycl_f16'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
+            tag-suffix: 'sycl-f16-ffmpeg-core'
+            ffmpeg: 'true'
+            image-type: 'core'
+            runs-on: 'arc-runner-set'
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "1"
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-cublas-cuda12-ffmpeg-core'
+            ffmpeg: 'true'
+            image-type: 'core'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
--- a/.github/workflows/image.yml
+++ b/.github/workflows/image.yml
@@ -2,7 +2,6 @@
 name: 'build container images'

 on:
-  pull_request:
  push:
    branches:
      - master
@@ -26,9 +25,12 @@ jobs:
      cuda-minor-version: ${{ matrix.cuda-minor-version }}
      platforms: ${{ matrix.platforms }}
      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
    secrets:
-      dockerUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-      dockerPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
    strategy:
      # Pushing with all jobs in parallel
      # eats the bandwidth of all the nodes
@@ -43,6 +45,7 @@ jobs:
            ffmpeg: ''
            image-type: 'extras'
            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
          - build-type: ''
            platforms: 'linux/amd64'
            tag-latest: 'false'
@@ -50,6 +53,7 @@ jobs:
            ffmpeg: 'true'
            image-type: 'extras'
            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
          - build-type: 'cublas'
            cuda-major-version: "11"
            cuda-minor-version: "7"
@@ -59,6 +63,7 @@ jobs:
            ffmpeg: ''
            image-type: 'extras'
            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
          - build-type: 'cublas'
            cuda-major-version: "12"
            cuda-minor-version: "1"
@@ -68,6 +73,7 @@ jobs:
            ffmpeg: ''
            image-type: 'extras'
            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
          - build-type: 'cublas'
            cuda-major-version: "11"
            cuda-minor-version: "7"
@@ -77,6 +83,7 @@ jobs:
            ffmpeg: 'true'
            image-type: 'extras'
            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
          - build-type: 'cublas'
            cuda-major-version: "12"
            cuda-minor-version: "1"
@@ -86,6 +93,7 @@ jobs:
            ffmpeg: 'true'
            image-type: 'extras'
            runs-on: 'arc-runner-set'
+            base-image: "ubuntu:22.04"
          - build-type: ''
            #platforms: 'linux/amd64,linux/arm64'
            platforms: 'linux/amd64'
@@ -93,6 +101,23 @@ jobs:
            tag-suffix: ''
            ffmpeg: ''
            image-type: 'extras'
+            base-image: "ubuntu:22.04"
+            runs-on: 'arc-runner-set'
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas-ffmpeg'
+            ffmpeg: 'true'
+            image-type: 'extras'
+            base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
+            runs-on: 'arc-runner-set'
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas'
+            ffmpeg: 'false'
+            image-type: 'extras'
+            base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
            runs-on: 'arc-runner-set'
  core-image-build:
    uses: ./.github/workflows/image_build.yml
@@ -106,19 +131,71 @@ jobs:
      cuda-minor-version: ${{ matrix.cuda-minor-version }}
      platforms: ${{ matrix.platforms }}
      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
    secrets:
-      dockerUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-      dockerPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
    strategy:
      matrix:
        include:
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas-ffmpeg-core'
+            ffmpeg: 'true'
+            image-type: 'core'
+            base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
+            runs-on: 'arc-runner-set'
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas-core'
+            ffmpeg: 'false'
+            image-type: 'core'
+            base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
+            runs-on: 'arc-runner-set'
          - build-type: ''
            platforms: 'linux/amd64'
            tag-latest: 'false'
            tag-suffix: '-ffmpeg-core'
            ffmpeg: 'true'
            image-type: 'core'
+            base-image: "ubuntu:22.04"
            runs-on: 'ubuntu-latest'
+          - build-type: 'sycl_f16'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
+            tag-suffix: '-sycl-f16-core'
+            ffmpeg: 'false'
+            image-type: 'core'
+            runs-on: 'arc-runner-set'
+          - build-type: 'sycl_f32'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
+            tag-suffix: '-sycl-f32-core'
+            ffmpeg: 'false'
+            image-type: 'core'
+            runs-on: 'arc-runner-set'
+          - build-type: 'sycl_f16'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
+            tag-suffix: '-sycl-f16-ffmpeg-core'
+            ffmpeg: 'true'
+            image-type: 'core'
+            runs-on: 'arc-runner-set'
+          - build-type: 'sycl_f32'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
+            tag-suffix: '-sycl-f32-ffmpeg-core'
+            ffmpeg: 'true'
+            image-type: 'core'
+            runs-on: 'arc-runner-set'
          - build-type: 'cublas'
            cuda-major-version: "11"
            cuda-minor-version: "7"
@@ -127,6 +204,7 @@ jobs:
            tag-suffix: '-cublas-cuda11-core'
            ffmpeg: ''
            image-type: 'core'
+            base-image: "ubuntu:22.04"
            runs-on: 'ubuntu-latest'
          - build-type: 'cublas'
            cuda-major-version: "12"
@@ -136,6 +214,7 @@ jobs:
            tag-suffix: '-cublas-cuda12-core'
            ffmpeg: ''
            image-type: 'core'
+            base-image: "ubuntu:22.04"
            runs-on: 'ubuntu-latest'
          - build-type: 'cublas'
            cuda-major-version: "11"
@@ -146,6 +225,7 @@ jobs:
            ffmpeg: 'true'
            image-type: 'core'
            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
          - build-type: 'cublas'
            cuda-major-version: "12"
            cuda-minor-version: "1"
@@ -155,3 +235,4 @@ jobs:
            ffmpeg: 'true'
            image-type: 'core'
            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
--- a/.github/workflows/image_build.yml
+++ b/.github/workflows/image_build.yml
@@ -4,6 +4,11 @@ name: 'build container images (reusable)'
 on:
  workflow_call:
    inputs:
+      base-image:
+        description: 'Base image'
+        required: false
+        default: ''
+        type: string
      build-type:
        description: 'Build type'
        default: ''
@@ -46,6 +51,10 @@ on:
        required: true
      dockerPassword:
        required: true
+      quayUsername:
+        required: true
+      quayPassword:
+        required: true
 jobs:
  reusable_image-build:
    runs-on: ${{ inputs.runs-on }}
@@ -60,47 +69,54 @@ jobs:
          && sudo apt-get install -y git
      - name: Checkout
        uses: actions/checkout@v4
-      # - name: Release space from worker
-      #   run: |
-      #     echo "Listing top largest packages"
-      #     pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-      #     head -n 30 <<< "${pkgs}"
-      #     echo
-      #     df -h
-      #     echo
-      #     sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
-      #     sudo apt-get remove --auto-remove android-sdk-platform-tools || true
-      #     sudo apt-get purge --auto-remove android-sdk-platform-tools || true
-      #     sudo rm -rf /usr/local/lib/android
-      #     sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
-      #     sudo rm -rf /usr/share/dotnet
-      #     sudo apt-get remove -y '^mono-.*' || true
-      #     sudo apt-get remove -y '^ghc-.*' || true
-      #     sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
-      #     sudo apt-get remove -y 'php.*' || true
-      #     sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
-      #     sudo apt-get remove -y '^google-.*' || true
-      #     sudo apt-get remove -y azure-cli || true
-      #     sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
-      #     sudo apt-get remove -y '^gfortran-.*' || true
-      #     sudo apt-get remove -y microsoft-edge-stable || true
-      #     sudo apt-get remove -y firefox || true
-      #     sudo apt-get remove -y powershell || true
-      #     sudo apt-get remove -y r-base-core || true
-      #     sudo apt-get autoremove -y
-      #     sudo apt-get clean
-      #     echo
-      #     echo "Listing top largest packages"
-      #     pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-      #     head -n 30 <<< "${pkgs}"
-      #     echo
-      #     sudo rm -rfv build || true
-      #     df -h
+      - name: Release space from worker
+        if: inputs.runs-on == 'ubuntu-latest'
+        run: |
+          echo "Listing top largest packages"
+          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+          head -n 30 <<< "${pkgs}"
+          echo
+          df -h
+          echo
+          sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
+          sudo apt-get remove --auto-remove android-sdk-platform-tools || true
+          sudo apt-get purge --auto-remove android-sdk-platform-tools || true
+          sudo rm -rf /usr/local/lib/android
+          sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
+          sudo rm -rf /usr/share/dotnet
+          sudo apt-get remove -y '^mono-.*' || true
+          sudo apt-get remove -y '^ghc-.*' || true
+          sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
+          sudo apt-get remove -y 'php.*' || true
+          sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
+          sudo apt-get remove -y '^google-.*' || true
+          sudo apt-get remove -y azure-cli || true
+          sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
+          sudo apt-get remove -y '^gfortran-.*' || true
+          sudo apt-get remove -y microsoft-edge-stable || true
+          sudo apt-get remove -y firefox || true
+          sudo apt-get remove -y powershell || true
+          sudo apt-get remove -y r-base-core || true
+          sudo apt-get autoremove -y
+          sudo apt-get clean
+          echo
+          echo "Listing top largest packages"
+          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+          head -n 30 <<< "${pkgs}"
+          echo
+          sudo rm -rfv build || true
+          sudo rm -rf /usr/share/dotnet || true
+          sudo rm -rf /opt/ghc || true
+          sudo rm -rf "/usr/local/share/boost" || true
+          sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
+          df -h
      - name: Docker meta
        id: meta
        uses: docker/metadata-action@v5
        with:
-          images: quay.io/go-skynet/local-ai
+          images: |
+            quay.io/go-skynet/local-ai
+            localai/localai
          tags: |
            type=ref,event=branch
            type=semver,pattern={{raw}}
@@ -122,10 +138,17 @@ jobs:
        if: github.event_name != 'pull_request'
        uses: docker/login-action@v3
        with:
-          registry: quay.io
          username: ${{ secrets.dockerUsername }}
          password: ${{ secrets.dockerPassword }}

+      - name: Login to DockerHub
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v3
+        with:
+          registry: quay.io
+          username: ${{ secrets.quayUsername }}
+          password: ${{ secrets.quayPassword }}
+
      - name: Build and push
        uses: docker/build-push-action@v5
        with:
@@ -136,6 +159,7 @@ jobs:
            CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
            FFMPEG=${{ inputs.ffmpeg }}
            IMAGE_TYPE=${{ inputs.image-type }}
+            BASE_IMAGE=${{ inputs.base-image }}
          context: .
          file: ./Dockerfile
          platforms: ${{ inputs.platforms }}
--- a/.github/workflows/release.yaml
+++ b/.github/workflows/release.yaml
@@ -5,6 +5,10 @@ on: push
 permissions:
  contents: write

+concurrency:
+  group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
 jobs:
  build-linux:
    strategy:
@@ -16,6 +20,10 @@ jobs:
            defines: '-DLLAMA_AVX2=OFF'
          - build: 'avx512'
            defines: '-DLLAMA_AVX512=ON'
+          - build: 'cuda12'
+            defines: ''
+          - build: 'cuda11'
+            defines: ''
    runs-on: ubuntu-latest
    steps:
      - name: Clone
@@ -29,19 +37,47 @@ jobs:
        run: |
          sudo apt-get update
          sudo apt-get install build-essential ffmpeg
-
+      - name: Install CUDA Dependencies
+        if: ${{ matrix.build == 'cuda12' || matrix.build == 'cuda11' }}
+        run: |
+          if [ "${{ matrix.build }}" == "cuda12" ]; then
+            export CUDA_VERSION=12-3
+          else
+            export CUDA_VERSION=11-7
+          fi
+          curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
+          sudo dpkg -i cuda-keyring_1.1-1_all.deb
+          sudo apt-get update
+          sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
+      - name: Cache grpc
+        id: cache-grpc
+        uses: actions/cache@v3
+        with:
+          path: grpc
+          key: ${{ runner.os }}-grpc
+      - name: Build grpc
+        if: steps.cache-grpc.outputs.cache-hit != 'true'
+        run: |
          git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-              cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-                -DgRPC_BUILD_TESTS=OFF \
-                ../.. && sudo make -j12 install
-
+          cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
+            -DgRPC_BUILD_TESTS=OFF \
+            ../.. && sudo make -j12
+      - name: Install gRPC
+        run: |
+          cd grpc && cd cmake/build && sudo make -j12 install
      - name: Build
        id: build
        env:
          CMAKE_ARGS: "${{ matrix.defines }}"
          BUILD_ID: "${{ matrix.build }}"
        run: |
-          STATIC=true make dist
+          if [ "${{ matrix.build }}" == "cuda12" ] || [ "${{ matrix.build }}" == "cuda11" ]; then
+            export BUILD_TYPE=cublas
+            export PATH=/usr/local/cuda/bin:$PATH
+            make dist
+          else
+            STATIC=true make dist
+          fi
      - uses: actions/upload-artifact@v3
        with:
          name: ${{ matrix.build }}
@@ -74,10 +110,7 @@ jobs:
          go-version: '>=1.21.0'
      - name: Dependencies
        run: |
-          git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-              cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-                -DgRPC_BUILD_TESTS=OFF \
-                ../.. && make -j12 install && rm -rf grpc
+          brew install protobuf grpc
      - name: Build
        id: build
        env:
@@ -96,4 +129,4 @@ jobs:
        if: startsWith(github.ref, 'refs/tags/')
        with:
          files: |
-            release/*
+            release/*
--- a/.github/workflows/test-extra.yml
+++ b/.github/workflows/test-extra.yml
@@ -133,7 +133,7 @@ jobs:



-  tests-bark:
+  tests-petals:
    runs-on: ubuntu-latest
    steps:
      - name: Clone
@@ -156,11 +156,82 @@ jobs:
          
          sudo rm -rfv /usr/bin/conda || true

-      - name: Test bark
+      - name: Test petals
        run: |
           export PATH=$PATH:/opt/conda/bin
-           make -C backend/python/bark
-           make -C backend/python/bark test
+           make -C backend/python/petals
+           make -C backend/python/petals test
+
+           
+
+  # tests-bark:
+  #   runs-on: ubuntu-latest
+  #   steps:
+  #     - name: Release space from worker
+  #       run: |
+  #           echo "Listing top largest packages"
+  #           pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+  #           head -n 30 <<< "${pkgs}"
+  #           echo
+  #           df -h
+  #           echo
+  #           sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
+  #           sudo apt-get remove --auto-remove android-sdk-platform-tools || true
+  #           sudo apt-get purge --auto-remove android-sdk-platform-tools || true
+  #           sudo rm -rf /usr/local/lib/android
+  #           sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
+  #           sudo rm -rf /usr/share/dotnet
+  #           sudo apt-get remove -y '^mono-.*' || true
+  #           sudo apt-get remove -y '^ghc-.*' || true
+  #           sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
+  #           sudo apt-get remove -y 'php.*' || true
+  #           sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
+  #           sudo apt-get remove -y '^google-.*' || true
+  #           sudo apt-get remove -y azure-cli || true
+  #           sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
+  #           sudo apt-get remove -y '^gfortran-.*' || true
+  #           sudo apt-get remove -y microsoft-edge-stable || true
+  #           sudo apt-get remove -y firefox || true
+  #           sudo apt-get remove -y powershell || true
+  #           sudo apt-get remove -y r-base-core || true
+  #           sudo apt-get autoremove -y
+  #           sudo apt-get clean
+  #           echo
+  #           echo "Listing top largest packages"
+  #           pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+  #           head -n 30 <<< "${pkgs}"
+  #           echo
+  #           sudo rm -rfv build || true
+  #           sudo rm -rf /usr/share/dotnet || true
+  #           sudo rm -rf /opt/ghc || true
+  #           sudo rm -rf "/usr/local/share/boost" || true
+  #           sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
+  #           df -h
+  #     - name: Clone
+  #       uses: actions/checkout@v4
+  #       with: 
+  #         submodules: true
+  #     - name: Dependencies
+  #       run: |
+  #         sudo apt-get update
+  #         sudo apt-get install build-essential ffmpeg
+  #         curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
+  #            sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
+  #             gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
+  #            sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
+  #            sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
+  #            sudo apt-get update && \
+  #            sudo apt-get install -y conda
+  #         sudo apt-get install -y ca-certificates cmake curl patch
+  #         sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
+          
+  #         sudo rm -rfv /usr/bin/conda || true
+
+  #     - name: Test bark
+  #       run: |
+  #          export PATH=$PATH:/opt/conda/bin
+  #          make -C backend/python/bark
+  #          make -C backend/python/bark test

           
  # Below tests needs GPU. Commented out for now
@@ -191,29 +262,56 @@ jobs:
  #          export PATH=$PATH:/opt/conda/bin
  #          make -C backend/python/vllm
  #          make -C backend/python/vllm test
-  # tests-vallex:
-  #   runs-on: ubuntu-latest
-  #   steps:
-  #     - name: Clone
-  #       uses: actions/checkout@v4
-  #       with: 
-  #         submodules: true
-  #     - name: Dependencies
-  #       run: |
-  #         sudo apt-get update
-  #         sudo apt-get install build-essential ffmpeg
-  #         curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
-  #            sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
-  #             gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
-  #            sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
-  #            sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
-  #            sudo apt-get update && \
-  #            sudo apt-get install -y conda
-  #         sudo apt-get install -y ca-certificates cmake curl patch
-  #         sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2    
-  #         sudo rm -rfv /usr/bin/conda || true
-  #     - name: Test vall-e-x
-  #       run: |
-  #          export PATH=$PATH:/opt/conda/bin
-  #          make -C backend/python/vall-e-x
-  #          make -C backend/python/vall-e-x test
+  tests-vallex:
+    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
+          curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
+             sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
+              gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
+             sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
+             sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
+             sudo apt-get update && \
+             sudo apt-get install -y conda
+          sudo apt-get install -y ca-certificates cmake curl patch
+          sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2    
+          sudo rm -rfv /usr/bin/conda || true
+      - name: Test vall-e-x
+        run: |
+           export PATH=$PATH:/opt/conda/bin
+           make -C backend/python/vall-e-x
+           make -C backend/python/vall-e-x test
+
+  tests-coqui:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Clone
+        uses: actions/checkout@v4
+        with: 
+          submodules: true
+      - name: Dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install build-essential ffmpeg
+          curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
+             sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
+              gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
+             sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
+             sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
+             sudo apt-get update && \
+             sudo apt-get install -y conda
+          sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng          
+          sudo rm -rfv /usr/bin/conda || true
+
+      - name: Test coqui
+        run: |
+           export PATH=$PATH:/opt/conda/bin
+           make -C backend/python/coqui
+           make -C backend/python/coqui test
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -86,11 +86,22 @@ jobs:
          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)
          GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
-
+      - name: Cache grpc
+        id: cache-grpc
+        uses: actions/cache@v3
+        with:
+          path: grpc
+          key: ${{ runner.os }}-grpc
+      - name: Build grpc
+        if: steps.cache-grpc.outputs.cache-hit != 'true'
+        run: |
          git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-              cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-                -DgRPC_BUILD_TESTS=OFF \
-                ../.. && sudo make -j12 install
+          cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
+            -DgRPC_BUILD_TESTS=OFF \
+            ../.. && sudo make -j12
+      - name: Install gRPC
+        run: |
+          cd grpc && cd cmake/build && sudo make -j12 install
      - name: Test
        run: |
          GO_TAGS="stablediffusion tts" make test
@@ -114,10 +125,7 @@ jobs:
        run: go version
      - name: Dependencies
        run: |
-          git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-              cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-                -DgRPC_BUILD_TESTS=OFF \
-                ../.. && make -j12 install && rm -rf grpc
+          brew install protobuf grpc
      - name: Test
        run: |
          export C_INCLUDE_PATH=/usr/local/include
--- a/.gitmodules
+++ b/.gitmodules
@@ -1,3 +1,6 @@
 [submodule "docs/themes/hugo-theme-relearn"]
 	path = docs/themes/hugo-theme-relearn
 	url = https://github.com/McShelby/hugo-theme-relearn.git
+[submodule "docs/themes/lotusdocs"]
+	path = docs/themes/lotusdocs
+	url = https://github.com/colinwilson/lotusdocs
--- a/55
+++ b/55
@@ -1,10 +1,10 @@
-ARG GO_VERSION=1.21-bullseye
 ARG IMAGE_TYPE=extras
+ARG BASE_IMAGE=ubuntu:22.04
+
 # extras or core
+FROM ${BASE_IMAGE} as requirements-core

-
-FROM golang:$GO_VERSION as requirements-core
-
+ARG GO_VERSION=1.21.7
 ARG BUILD_TYPE
 ARG CUDA_MAJOR_VERSION=11
 ARG CUDA_MINOR_VERSION=7
@@ -12,15 +12,17 @@ ARG TARGETARCH
 ARG TARGETVARIANT

 ENV BUILD_TYPE=${BUILD_TYPE}
+ENV DEBIAN_FRONTEND=noninteractive
+ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh"

-ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh"
-
-ENV GALLERIES='[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]'
-ARG GO_TAGS="stablediffusion tts"
+ARG GO_TAGS="stablediffusion tinydream tts"

 RUN apt-get update && \
-    apt-get install -y ca-certificates curl patch pip cmake && apt-get clean
+    apt-get install -y ca-certificates curl patch pip cmake git && apt-get clean

+# Install Go
+RUN curl -L -s https://go.dev/dl/go$GO_VERSION.linux-$TARGETARCH.tar.gz | tar -v -C /usr/local -xz
+ENV PATH $PATH:/usr/local/go/bin

 COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
 RUN update-ca-certificates
@@ -32,15 +34,19 @@ RUN echo "Target Variant: $TARGETVARIANT"
 # CuBLAS requirements
 RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
    apt-get install -y software-properties-common && \
-    apt-add-repository contrib && \
-    curl -O https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.0-1_all.deb && \
-    dpkg -i cuda-keyring_1.0-1_all.deb && \
-    rm -f cuda-keyring_1.0-1_all.deb && \
+    curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
+    dpkg -i cuda-keyring_1.1-1_all.deb && \
+    rm -f cuda-keyring_1.1-1_all.deb && \
    apt-get update && \
-    apt-get install -y cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}  && apt-get clean \
+    apt-get install -y cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}  && apt-get clean \
    ; fi
+
+# Cuda
 ENV PATH /usr/local/cuda/bin:${PATH}

+# HipBLAS requirements
+ENV PATH /opt/rocm/bin:${PATH}
+
 # OpenBLAS requirements and stable diffusion
 RUN apt-get install -y \
    libopenblas-dev \
@@ -64,15 +70,14 @@ RUN curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmo
    echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list && \
    echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list && \
    apt-get update && \
-    apt-get install -y conda
+    apt-get install -y conda && apt-get clean

 ENV PATH="/root/.cargo/bin:${PATH}"
+RUN apt-get install -y python3-pip && apt-get clean
 RUN pip install --upgrade pip
+
 RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
-
-
-# \
-#    ; fi
+RUN apt-get install -y espeak-ng espeak && apt-get clean

 ###################################
 ###################################
@@ -130,10 +135,11 @@ ARG CUDA_MAJOR_VERSION=11
 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
 ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
 ENV NVIDIA_VISIBLE_DEVICES=all
+ENV PIP_CACHE_PURGE=true

 # Add FFmpeg
 RUN if [ "${FFMPEG}" = "true" ]; then \
-    apt-get install -y ffmpeg \
+    apt-get install -y ffmpeg && apt-get clean \
    ; fi

 WORKDIR /build
@@ -171,6 +177,9 @@ RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
 RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
 	PATH=$PATH:/opt/conda/bin make -C backend/python/vllm \
    ; fi
+RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
+	PATH=$PATH:/opt/conda/bin make -C backend/python/mamba \
+    ; fi
 RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
 	PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers \
    ; fi
@@ -192,6 +201,12 @@ RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
 RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
 	PATH=$PATH:/opt/conda/bin make -C backend/python/transformers-musicgen \
    ; fi
+RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
+	PATH=$PATH:/opt/conda/bin make -C backend/python/coqui \
+    ; fi
+
+# Make sure the models directory exists
+RUN mkdir -p /build/models

 # Define the health check command
 HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
--- a/2
+++ b/2
@@ -1,6 +1,6 @@
 MIT License

-Copyright (c) 2023 Ettore Di Giacinto
+Copyright (c) 2023-2024 Ettore Di Giacinto (mudler@localai.io)

 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
--- a/181
+++ b/181
@@ -8,21 +8,18 @@ GOLLAMA_VERSION?=aeba71ee842819da681ea537e78846dc75949ac0

 GOLLAMA_STABLE_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7

-CPPLLAMA_VERSION?=88ae8952b65cbf32eb1f5703681ea592e510e570
+CPPLLAMA_VERSION?=fd43d66f46ee3b5345fb8a74a252d86ccd34a409

 # gpt4all version
 GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
 GPT4ALL_VERSION?=27a8b020c36b0df8f8b82a252d261cda47cf44b8

-# go-ggml-transformers version
-GOGGMLTRANSFORMERS_VERSION?=ffb09d7dd71e2cbc6c5d7d05357d230eea6f369a
-
 # go-rwkv version
 RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
-RWKV_VERSION?=c898cd0f62df8f2a7830e53d1d513bef4f6f792b
+RWKV_VERSION?=633c5a3485c403cb2520693dc0991a25dace9f0f

 # whisper.cpp version
-WHISPER_CPP_VERSION?=940de9dbe9c90624dc99521cb34c8a97b86d543c
+WHISPER_CPP_VERSION?=37a709f6558c6d9783199e2b8cbb136e1c41d346

 # bert.cpp version
 BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
@@ -31,7 +28,10 @@ BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
 PIPER_VERSION?=d6b6275ba037dabdba4a8b65dfdf6b2a73a67f07

 # stablediffusion version
-STABLEDIFFUSION_VERSION?=902db5f066fd137697e3b69d0fa10d4782bd2c2f
+STABLEDIFFUSION_VERSION?=d5d2be8e7e395c2d73ceef61e6fe8d240f2cd831
+
+# tinydream version
+TINYDREAM_VERSION?=772a9c0d9aaf768290e63cca3c904fe69faf677a

 export BUILD_TYPE?=
 export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
@@ -97,6 +97,8 @@ endif

 ifeq ($(BUILD_TYPE),hipblas)
 	ROCM_HOME ?= /opt/rocm
+	ROCM_PATH ?= /opt/rocm
+	LD_LIBRARY_PATH ?= /opt/rocm/lib:/opt/rocm/llvm/lib
 	export CXX=$(ROCM_HOME)/llvm/bin/clang++
 	export CC=$(ROCM_HOME)/llvm/bin/clang
 	# llama-ggml has no hipblas support, so override it here.
@@ -105,7 +107,7 @@ ifeq ($(BUILD_TYPE),hipblas)
 	GPU_TARGETS ?= gfx900,gfx90a,gfx1030,gfx1031,gfx1100
 	AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
 	CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
-	CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link
+	CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link -L${ROCM_HOME}/lib/llvm/lib
 endif

 ifeq ($(BUILD_TYPE),metal)
@@ -129,15 +131,29 @@ ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
 	OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
 endif

+ifeq ($(findstring tinydream,$(GO_TAGS)),tinydream)
+#	OPTIONAL_TARGETS+=go-tiny-dream/libtinydream.a
+	OPTIONAL_GRPC+=backend-assets/grpc/tinydream
+endif
+
 ifeq ($(findstring tts,$(GO_TAGS)),tts)
 #	OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
 #	OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
-	PIPER_CGO_CXXFLAGS+=-I$(shell pwd)/sources/go-piper/piper/src/cpp -I$(shell pwd)/sources/go-piper/piper/build/fi/include -I$(shell pwd)/sources/go-piper/piper/build/pi/include -I$(shell pwd)/sources/go-piper/piper/build/si/include
- 	PIPER_CGO_LDFLAGS+=-L$(shell pwd)/sources/go-piper/piper/build/fi/lib -L$(shell pwd)/sources/go-piper/piper/build/pi/lib -L$(shell pwd)/sources/go-piper/piper/build/si/lib -lfmt -lspdlog -lucd
+	PIPER_CGO_CXXFLAGS+=-I$(CURDIR)/sources/go-piper/piper/src/cpp -I$(CURDIR)/sources/go-piper/piper/build/fi/include -I$(CURDIR)/sources/go-piper/piper/build/pi/include -I$(CURDIR)/sources/go-piper/piper/build/si/include
+	PIPER_CGO_LDFLAGS+=-L$(CURDIR)/sources/go-piper/piper/build/fi/lib -L$(CURDIR)/sources/go-piper/piper/build/pi/lib -L$(CURDIR)/sources/go-piper/piper/build/si/lib -lfmt -lspdlog -lucd
 	OPTIONAL_GRPC+=backend-assets/grpc/piper
 endif

-ALL_GRPC_BACKENDS=backend-assets/grpc/langchain-huggingface backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/llama backend-assets/grpc/llama-cpp backend-assets/grpc/llama-ggml backend-assets/grpc/gpt4all backend-assets/grpc/dolly backend-assets/grpc/gpt2 backend-assets/grpc/gptj backend-assets/grpc/gptneox backend-assets/grpc/mpt backend-assets/grpc/replit backend-assets/grpc/starcoder backend-assets/grpc/rwkv backend-assets/grpc/whisper $(OPTIONAL_GRPC)
+ALL_GRPC_BACKENDS=backend-assets/grpc/langchain-huggingface
+ALL_GRPC_BACKENDS+=backend-assets/grpc/bert-embeddings
+ALL_GRPC_BACKENDS+=backend-assets/grpc/llama
+ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp
+ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-ggml
+ALL_GRPC_BACKENDS+=backend-assets/grpc/gpt4all
+ALL_GRPC_BACKENDS+=backend-assets/grpc/rwkv
+ALL_GRPC_BACKENDS+=backend-assets/grpc/whisper
+ALL_GRPC_BACKENDS+=$(OPTIONAL_GRPC)
+
 GRPC_BACKENDS?=$(ALL_GRPC_BACKENDS) $(OPTIONAL_GRPC)

 # If empty, then we build all
@@ -145,6 +161,10 @@ ifeq ($(GRPC_BACKENDS),)
 	GRPC_BACKENDS=$(ALL_GRPC_BACKENDS)
 endif

+ifeq ($(BUILD_API_ONLY),true)
+	GRPC_BACKENDS=
+endif
+
 .PHONY: all test build vendor

 all: help
@@ -172,6 +192,14 @@ sources/go-stable-diffusion:
 sources/go-stable-diffusion/libstablediffusion.a:
 	$(MAKE) -C sources/go-stable-diffusion libstablediffusion.a

+## tiny-dream
+sources/go-tiny-dream:
+	git clone --recurse-submodules https://github.com/M0Rf30/go-tiny-dream sources/go-tiny-dream
+	cd sources/go-tiny-dream && git checkout -b build $(TINYDREAM_VERSION) && git submodule update --init --recursive --depth 1
+
+sources/go-tiny-dream/libtinydream.a:
+	$(MAKE) -C sources/go-tiny-dream libtinydream.a
+
 ## RWKV
 sources/go-rwkv:
 	git clone --recurse-submodules $(RWKV_REPO) sources/go-rwkv
@@ -197,14 +225,6 @@ backend-assets/espeak-ng-data: sources/go-piper
 sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a: sources/gpt4all
 	$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ libgpt4all.a

-## CEREBRAS GPT
-sources/go-ggml-transformers:
-	git clone --recurse-submodules https://github.com/go-skynet/go-ggml-transformers.cpp sources/go-ggml-transformers
-	cd sources/go-ggml-transformers && git checkout -b build $(GOGPT2_VERSION) && git submodule update --init --recursive --depth 1
-
-sources/go-ggml-transformers/libtransformers.a: sources/go-ggml-transformers
-	$(MAKE) -C sources/go-ggml-transformers BUILD_TYPE=$(BUILD_TYPE) libtransformers.a
-
 sources/whisper.cpp:
 	git clone https://github.com/ggerganov/whisper.cpp.git sources/whisper.cpp
 	cd sources/whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
@@ -232,18 +252,18 @@ sources/go-piper/libpiper_binding.a: sources/go-piper
 backend/cpp/llama/llama.cpp:
 	LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama llama.cpp	

-get-sources: backend/cpp/llama/llama.cpp sources/go-llama sources/go-llama-ggml sources/go-ggml-transformers sources/gpt4all sources/go-piper sources/go-rwkv sources/whisper.cpp sources/go-bert sources/go-stable-diffusion
+get-sources: backend/cpp/llama/llama.cpp sources/go-llama sources/go-llama-ggml sources/gpt4all sources/go-piper sources/go-rwkv sources/whisper.cpp sources/go-bert sources/go-stable-diffusion sources/go-tiny-dream
 	touch $@

 replace:
-	$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/sources/gpt4all/gpt4all-bindings/golang
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/sources/go-ggml-transformers
-	$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/sources/go-rwkv
-	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(shell pwd)/sources/whisper.cpp
-	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(shell pwd)/sources/whisper.cpp/bindings/go
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(shell pwd)/sources/go-bert
-	$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/sources/go-stable-diffusion
-	$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(shell pwd)/sources/go-piper
+	$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(CURDIR)/sources/gpt4all/gpt4all-bindings/golang
+	$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(CURDIR)/sources/go-rwkv
+	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(CURDIR)/sources/whisper.cpp
+	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(CURDIR)/sources/whisper.cpp/bindings/go
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(CURDIR)/sources/go-bert
+	$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(CURDIR)/sources/go-stable-diffusion
+	$(GOCMD) mod edit -replace github.com/M0Rf30/go-tiny-dream=$(CURDIR)/sources/go-tiny-dream
+	$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(CURDIR)/sources/go-piper

 prepare-sources: get-sources replace
 	$(GOCMD) mod download
@@ -255,12 +275,12 @@ rebuild: ## Rebuilds the project
 	$(MAKE) -C sources/go-llama clean
 	$(MAKE) -C sources/go-llama-ggml clean
 	$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ clean
-	$(MAKE) -C sources/go-ggml-transformers clean
 	$(MAKE) -C sources/go-rwkv clean
 	$(MAKE) -C sources/whisper.cpp clean
 	$(MAKE) -C sources/go-stable-diffusion clean
 	$(MAKE) -C sources/go-bert clean
 	$(MAKE) -C sources/go-piper clean
+	$(MAKE) -C sources/go-tiny-dream clean
 	$(MAKE) build

 prepare: prepare-sources $(OPTIONAL_TARGETS)
@@ -272,19 +292,17 @@ clean: ## Remove build related file
 	rm -rf ./sources
 	rm -rf $(BINARY_NAME)
 	rm -rf release/
-	rm -rf ./backend/cpp/grpc/grpc_repo
-	rm -rf ./backend/cpp/grpc/build
-	rm -rf ./backend/cpp/grpc/installed_packages
+	rm -rf backend-assets
+	$(MAKE) -C backend/cpp/grpc clean
 	$(MAKE) -C backend/cpp/llama clean

 ## Build:

-build: grpcs prepare ## Build the project
+build: backend-assets grpcs prepare ## Build the project
 	$(info ${GREEN}I local-ai build info:${RESET})
 	$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
 	$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
 	$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
-
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./

 dist: build
@@ -301,7 +319,7 @@ run: prepare ## run local-ai
 test-models/testmodel:
 	mkdir test-models
 	mkdir test-dir
-	wget -q https://huggingface.co/nnakasato/ggml-model-test/resolve/main/ggml-model-q4.bin -O test-models/testmodel
+	wget -q https://huggingface.co/TheBloke/orca_mini_3B-GGML/resolve/main/orca-mini-3b.ggmlv3.q4_0.bin -O test-models/testmodel
 	wget -q https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
 	wget -q https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin -O test-models/bert
 	wget -q https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
@@ -395,9 +413,11 @@ protogen-python:
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama/ --grpc_python_out=backend/python/exllama/ backend/backend.proto
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/bark/ --grpc_python_out=backend/python/bark/ backend/backend.proto
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/diffusers/ --grpc_python_out=backend/python/diffusers/ backend/backend.proto
+	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/coqui/ --grpc_python_out=backend/python/coqui/ backend/backend.proto
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/vall-e-x/ --grpc_python_out=backend/python/vall-e-x/ backend/backend.proto
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/vllm/ --grpc_python_out=backend/python/vllm/ backend/backend.proto
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/petals/ --grpc_python_out=backend/python/petals/ backend/backend.proto
+	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/mamba/ --grpc_python_out=backend/python/mamba/ backend/backend.proto
 	python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama2/ --grpc_python_out=backend/python/exllama2/ backend/backend.proto

 ## GRPC
@@ -405,8 +425,10 @@ protogen-python:
 prepare-extra-conda-environments:
 	$(MAKE) -C backend/python/autogptq
 	$(MAKE) -C backend/python/bark
+	$(MAKE) -C backend/python/coqui
 	$(MAKE) -C backend/python/diffusers
 	$(MAKE) -C backend/python/vllm
+	$(MAKE) -C backend/python/mamba
 	$(MAKE) -C backend/python/sentencetransformers
 	$(MAKE) -C backend/python/transformers
 	$(MAKE) -C backend/python/transformers-musicgen
@@ -423,12 +445,18 @@ test-extra: prepare-test-extra
 	$(MAKE) -C backend/python/transformers test
 	$(MAKE) -C backend/python/diffusers test

+backend-assets:
+	mkdir -p backend-assets
+ifeq ($(BUILD_API_ONLY),true)
+	touch backend-assets/keep
+endif
+
 backend-assets/grpc:
 	mkdir -p backend-assets/grpc

 backend-assets/grpc/llama: backend-assets/grpc sources/go-llama/libbinding.a
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/sources/go-llama
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-llama LIBRARY_PATH=$(shell pwd)/sources/go-llama \
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(CURDIR)/sources/go-llama
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-llama LIBRARY_PATH=$(CURDIR)/sources/go-llama \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./backend/go/llm/llama/
 # TODO: every binary should have its own folder instead, so can have different  implementations
 ifeq ($(BUILD_TYPE),metal)
@@ -447,17 +475,17 @@ ADDED_CMAKE_ARGS=-Dabsl_DIR=${INSTALLED_LIB_CMAKE}/absl \

 backend/cpp/llama/grpc-server:
 ifdef BUILD_GRPC_FOR_BACKEND_LLAMA
-	backend/cpp/grpc/script/build_grpc.sh ${INSTALLED_PACKAGES}
+	$(MAKE) -C backend/cpp/grpc build
 	export _PROTOBUF_PROTOC=${INSTALLED_PACKAGES}/bin/proto && \
 	export _GRPC_CPP_PLUGIN_EXECUTABLE=${INSTALLED_PACKAGES}/bin/grpc_cpp_plugin && \
-	export PATH=${PATH}:${INSTALLED_PACKAGES}/bin && \
+	export PATH="${INSTALLED_PACKAGES}/bin:${PATH}" && \
 	CMAKE_ARGS="${CMAKE_ARGS} ${ADDED_CMAKE_ARGS}" LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama grpc-server
 else
 	echo "BUILD_GRPC_FOR_BACKEND_LLAMA is not defined."
 	LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama grpc-server			
 endif
 ## BACKEND CPP LLAMA END
-		
+
 ##
 backend-assets/grpc/llama-cpp: backend-assets/grpc backend/cpp/llama/grpc-server
 	cp -rfv backend/cpp/llama/grpc-server backend-assets/grpc/llama-cpp
@@ -467,52 +495,20 @@ ifeq ($(BUILD_TYPE),metal)
 endif

 backend-assets/grpc/llama-ggml: backend-assets/grpc sources/go-llama-ggml/libbinding.a
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/sources/go-llama-ggml
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-llama-ggml LIBRARY_PATH=$(shell pwd)/sources/go-llama-ggml \
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(CURDIR)/sources/go-llama-ggml
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-llama-ggml LIBRARY_PATH=$(CURDIR)/sources/go-llama-ggml \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-ggml ./backend/go/llm/llama-ggml/

 backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/sources/gpt4all/gpt4all-bindings/golang/ \
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(CURDIR)/sources/gpt4all/gpt4all-bindings/golang/ \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./backend/go/llm/gpt4all/

-backend-assets/grpc/dolly: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/dolly ./backend/go/llm/dolly/
-
-backend-assets/grpc/gpt2: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt2 ./backend/go/llm/gpt2/
-
-backend-assets/grpc/gptj: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptj ./backend/go/llm/gptj/
-
-backend-assets/grpc/gptneox: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptneox ./backend/go/llm/gptneox/
-
-backend-assets/grpc/mpt: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/mpt ./backend/go/llm/mpt/
-
-backend-assets/grpc/replit: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/replit ./backend/go/llm/replit/
-
-backend-assets/grpc/falcon-ggml: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon-ggml ./backend/go/llm/falcon-ggml/
-
-backend-assets/grpc/starcoder: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/starcoder ./backend/go/llm/starcoder/
-
 backend-assets/grpc/rwkv: backend-assets/grpc sources/go-rwkv/librwkv.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-rwkv LIBRARY_PATH=$(shell pwd)/sources/go-rwkv \
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-rwkv LIBRARY_PATH=$(CURDIR)/sources/go-rwkv \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./backend/go/llm/rwkv

 backend-assets/grpc/bert-embeddings: backend-assets/grpc sources/go-bert/libgobert.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-bert LIBRARY_PATH=$(shell pwd)/sources/go-bert \
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-bert LIBRARY_PATH=$(CURDIR)/sources/go-bert \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./backend/go/llm/bert/

 backend-assets/grpc/langchain-huggingface: backend-assets/grpc
@@ -521,16 +517,39 @@ backend-assets/grpc/langchain-huggingface: backend-assets/grpc
 backend-assets/grpc/stablediffusion: backend-assets/grpc
 	if [ ! -f backend-assets/grpc/stablediffusion ]; then \
 		$(MAKE) sources/go-stable-diffusion/libstablediffusion.a; \
-		CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/sources/go-stable-diffusion/ \
-		$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./backend/go/image/; \
+		CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-stable-diffusion/ LIBRARY_PATH=$(CURDIR)/sources/go-stable-diffusion/ \
+		$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./backend/go/image/stablediffusion; \
 	fi

+backend-assets/grpc/tinydream: backend-assets/grpc sources/go-tiny-dream/libtinydream.a
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(CURDIR)/go-tiny-dream \
+	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/tinydream ./backend/go/image/tinydream
+
 backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data sources/go-piper/libpiper_binding.a
-	CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/sources/go-piper \
+	CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(CURDIR)/sources/go-piper \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./backend/go/tts/

 backend-assets/grpc/whisper: backend-assets/grpc sources/whisper.cpp/libwhisper.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/whisper.cpp LIBRARY_PATH=$(shell pwd)/sources/whisper.cpp \
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/whisper.cpp LIBRARY_PATH=$(CURDIR)/sources/whisper.cpp \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./backend/go/transcribe/

 grpcs: prepare $(GRPC_BACKENDS)
+
+DOCKER_IMAGE?=local-ai
+IMAGE_TYPE?=core
+BASE_IMAGE?=ubuntu:22.04
+
+docker:
+	docker build \
+		--build-arg BASE_IMAGE=$(BASE_IMAGE) \
+		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
+		--build-arg GO_TAGS=$(GO_TAGS) \
+		--build-arg BUILD_TYPE=$(BUILD_TYPE) \
+		-t $(DOCKER_IMAGE) .
+
+docker-image-intel:
+	docker build \
+		--build-arg BASE_IMAGE=intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04 \
+		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
+		--build-arg GO_TAGS="none" \
+		--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
--- a/README.md
+++ b/README.md
@@ -20,16 +20,15 @@
 </a>
 </p>

+[<img src="https://img.shields.io/badge/dockerhub-images-important.svg?logo=Docker">](https://hub.docker.com/r/localai/localai)
+[<img src="https://img.shields.io/badge/quay.io-images-important.svg?">](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest)
+
 > :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/)
 >
 > [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)

 [![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[![Build and Release](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[![Bump dependencies](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai)

-**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU.
-
-<p  align="center"><b>Follow LocalAI </b></p>
-
 <p align="center">
 <a href="https://twitter.com/LocalAI_API" target="blank">
 <img src="https://img.shields.io/twitter/follow/LocalAI_API?label=Follow: LocalAI_API&style=social" alt="Follow LocalAI_API"/>
@@ -38,61 +37,38 @@
 <img src="https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted" alt="Join LocalAI Discord Community"/>
 </a>

-<p  align="center"><b>Connect with the Creator </b></p>
-
-<p align="center">
-<a href="https://twitter.com/mudler_it" target="blank">
-<img src="https://img.shields.io/twitter/follow/mudler_it?label=Follow: mudler_it&style=social" alt="Follow mudler_it"/>
-</a>
-<a href='https://github.com/mudler'>
-<img alt="Follow on Github" src="https://img.shields.io/badge/Follow-mudler-black?logo=github&link=https%3A%2F%2Fgithub.com%2Fmudler">
-</a>
-</p>
-
-<p  align="center"><b>Share LocalAI Repository</b></p>
-
-<p align="center">
-
-<a href="https://twitter.com/intent/tweet?text=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.&url=https://github.com/go-skynet/LocalAI&hashtags=LocalAI,AI" target="blank">
-<img src="https://img.shields.io/twitter/follow/_LocalAI?label=Share Repo on Twitter&style=social" alt="Follow _LocalAI"/></a>
-<a href="https://t.me/share/url?text=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.&url=https://github.com/go-skynet/LocalAI" target="_blank"><img src="https://img.shields.io/twitter/url?label=Telegram&logo=Telegram&style=social&url=https://github.com/go-skynet/LocalAI" alt="Share on Telegram"/></a>
-<a href="https://api.whatsapp.com/send?text=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.%20https://github.com/go-skynet/LocalAI"><img src="https://img.shields.io/twitter/url?label=whatsapp&logo=whatsapp&style=social&url=https://github.com/go-skynet/LocalAI" /></a> <a href="https://www.reddit.com/submit?url=https://github.com/go-skynet/LocalAI&title=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.
-" target="blank">
-<img src="https://img.shields.io/twitter/url?label=Reddit&logo=Reddit&style=social&url=https://github.com/go-skynet/LocalAI" alt="Share on Reddit"/>
-</a> <a href="mailto:?subject=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.%3A%0Ahttps://github.com/go-skynet/LocalAI" target="_blank"><img src="https://img.shields.io/twitter/url?label=Gmail&logo=Gmail&style=social&url=https://github.com/go-skynet/LocalAI"/></a> <a href="https://www.buymeacoffee.com/mudler" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy Me A Coffee" height="23" width="100" style="border-radius:1px"></a>
-
-</p>
-
-## 💻 [Getting started](https://localai.io/basics/getting_started/index.html)
+**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU.

 ## 🔥🔥 Hot topics / Roadmap

 [Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)

-🆕 New! [LLM finetuning guide](https://localai.io/advanced/fine-tuning/)
+- Parallel function calling: https://github.com/mudler/LocalAI/pull/1726
+- Upload file API: https://github.com/mudler/LocalAI/pull/1703
+- Tools API support: https://github.com/mudler/LocalAI/pull/1715
+- LLaVa 1.6: https://github.com/mudler/LocalAI/pull/1714
+- ROCm container images: https://github.com/mudler/LocalAI/pull/1595
+- Intel GPU support (sycl): https://github.com/mudler/LocalAI/issues/1653
+- Deprecation of old backends: https://github.com/mudler/LocalAI/issues/1651
+- Mamba support: https://github.com/mudler/LocalAI/pull/1589
+- Start and share models with config file: https://github.com/mudler/LocalAI/pull/1522
+- 🐸 Coqui: https://github.com/mudler/LocalAI/pull/1489
+- Img2vid https://github.com/mudler/LocalAI/pull/1442

 Hot topics (looking for contributors):
 - Backends v2: https://github.com/mudler/LocalAI/issues/1126
 - Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
-
+- Assistant API: https://github.com/mudler/LocalAI/issues/1273
+  
 If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22

+## 💻 [Getting started](https://localai.io/basics/getting_started/index.html)

+For a detailed step-by-step introduction, refer to the [Getting Started](https://localai.io/basics/getting_started/index.html) guide. For those in a hurry, here's a straightforward one-liner to launch a LocalAI instance with [phi-2](https://huggingface.co/microsoft/phi-2) using `docker`:

-<hr>
-
-In a nutshell:
-
- Local, OpenAI drop-in alternative REST API. You own your data.
- NO GPU required. NO Internet access is required either
-  - Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. See also the [build section](https://localai.io/basics/build/index.html).
- Supports multiple models
- 🏃 Once loaded the first time, it keep models loaded in memory for faster inference
- ⚡ Doesn't shell-out, but uses C++ bindings for a faster inference and better performance.
-
-LocalAI was created by [Ettore Di Giacinto](https://github.com/mudler/) and is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome!
-
-Note that this started just as a [fun weekend project](https://localai.io/#backstory) in order to try to create the necessary pieces for a full AI assistant like `ChatGPT`: the community is growing fast and we are working hard to make it better and more stable. If you want to help, please consider contributing (see below)!
+```
+docker run -ti -p 8080:8080 localai/localai:v2.7.0-ffmpeg-core phi-2
+```

 ## 🚀 [Features](https://localai.io/features/)

@@ -121,17 +97,27 @@ WebUIs:

 Model galleries
 - https://github.com/go-skynet/model-gallery
+  
+UI / Management Programs
+- [LocalAI Manager](https://io.midori-ai.xyz/howtos/easy-model-installer/)

 Other:
 - Helm chart https://github.com/go-skynet/helm-charts
+- VSCode extension https://github.com/badgooooor/localai-vscode-plugin
+- Local Smart assistant https://github.com/mudler/LocalAGI
+- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation
+- Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord
+- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
+- Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot
+- Examples: https://github.com/mudler/LocalAI/tree/master/examples/

 ### 🔗 Resources

- 🆕 New! [LLM finetuning guide](https://localai.io/advanced/fine-tuning/)
+- 🆕 New! [LLM finetuning guide](https://localai.io/docs/advanced/fine-tuning/)
 - [How to build locally](https://localai.io/basics/build/index.html)
 - [How to install in Kubernetes](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes)
- [Projects integrating LocalAI](https://localai.io/integrations/)
- [How tos section](https://localai.io/howtos/) (curated by our community)
+- [Projects integrating LocalAI](https://localai.io/docs/integrations/)
+- [How tos section](https://io.midori-ai.xyz/howtos/) (curated by our community)

 ## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)

@@ -194,7 +180,6 @@ LocalAI couldn't have been built without the help of great software already avai
 - https://github.com/ggerganov/whisper.cpp
 - https://github.com/saharNooby/rwkv.cpp
 - https://github.com/rhasspy/piper
- https://github.com/cmp-nct/ggllm.cpp

 ## 🤗 Contributors

--- a/api/ctx/fiber.go
+++ b/api/ctx/fiber.go
@@ -0,0 +1,43 @@
+package fiberContext
+
+import (
+	"fmt"
+	"strings"
+
+	"github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/gofiber/fiber/v2"
+	"github.com/rs/zerolog/log"
+)
+
+// ModelFromContext returns the model from the context
+// If no model is specified, it will take the first available
+// Takes a model string as input which should be the one received from the user request.
+// It returns the model name resolved from the context and an error if any.
+func ModelFromContext(ctx *fiber.Ctx, loader *model.ModelLoader, modelInput string, firstModel bool) (string, error) {
+	if ctx.Params("model") != "" {
+		modelInput = ctx.Params("model")
+	}
+
+	// Set model from bearer token, if available
+	bearer := strings.TrimLeft(ctx.Get("authorization"), "Bearer ")
+	bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
+
+	// If no model was specified, take the first available
+	if modelInput == "" && !bearerExists && firstModel {
+		models, _ := loader.ListModels()
+		if len(models) > 0 {
+			modelInput = models[0]
+			log.Debug().Msgf("No model specified, using: %s", modelInput)
+		} else {
+			log.Debug().Msgf("No model specified, returning error")
+			return "", fmt.Errorf("no model specified")
+		}
+	}
+
+	// If a model is found in bearer token takes precedence
+	if bearerExists {
+		log.Debug().Msgf("Using model from bearer token: %s", bearer)
+		modelInput = bearer
+	}
+	return modelInput, nil
+}
--- a/api/localai/backend_monitor.go
+++ b/api/localai/backend_monitor.go
@@ -5,10 +5,10 @@ import (
 	"fmt"
 	"strings"

-	config "github.com/go-skynet/LocalAI/api/config"
+	config "github.com/go-skynet/LocalAI/core/config"
 	"github.com/go-skynet/LocalAI/pkg/grpc/proto"

-	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/core/options"
 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"

--- a/api/localai/gallery.go
+++ b/api/localai/gallery.go
@@ -11,7 +11,7 @@ import (
 	json "github.com/json-iterator/go"
 	"gopkg.in/yaml.v3"

-	config "github.com/go-skynet/LocalAI/api/config"
+	config "github.com/go-skynet/LocalAI/core/config"
 	"github.com/go-skynet/LocalAI/pkg/gallery"
 	"github.com/go-skynet/LocalAI/pkg/utils"

@@ -130,6 +130,12 @@ func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
 					continue
 				}

+				err = cm.Preload(g.modelPath)
+				if err != nil {
+					updateError(err)
+					continue
+				}
+
 				g.updateStatus(op.id, &galleryOpStatus{Processed: true, Message: "completed", Progress: 100})
 			}
 		}
--- a/api/localai/localai.go
+++ b/api/localai/localai.go
@@ -1,10 +1,12 @@
 package localai

 import (
-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
+	fiberContext "github.com/go-skynet/LocalAI/api/ctx"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/rs/zerolog/log"

-	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/core/options"
 	"github.com/gofiber/fiber/v2"
 )

@@ -18,12 +20,31 @@ func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 	return func(c *fiber.Ctx) error {

 		input := new(TTSRequest)
+
 		// Get input data from the request body
 		if err := c.BodyParser(input); err != nil {
 			return err
 		}

-		filePath, _, err := backend.ModelTTS(input.Backend, input.Input, input.Model, o.Loader, o)
+		modelFile, err := fiberContext.ModelFromContext(c, o.Loader, input.Model, false)
+		if err != nil {
+			modelFile = input.Model
+			log.Warn().Msgf("Model not found in context: %s", input.Model)
+		}
+		cfg, err := config.Load(modelFile, o.Loader.ModelPath, cm, false, 0, 0, false)
+		if err != nil {
+			modelFile = input.Model
+			log.Warn().Msgf("Model not found in context: %s", input.Model)
+		} else {
+			modelFile = cfg.Model
+		}
+		log.Debug().Msgf("Request for model: %s", modelFile)
+
+		if input.Backend != "" {
+			cfg.Backend = input.Backend
+		}
+
+		filePath, _, err := backend.ModelTTS(cfg.Backend, input.Input, modelFile, o.Loader, o, *cfg)
 		if err != nil {
 			return err
 		}
--- a/api/openai/chat.go
+++ b/api/openai/chat.go
@@ -8,10 +8,10 @@ import (
 	"strings"
 	"time"

-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/core/schema"
 	"github.com/go-skynet/LocalAI/pkg/grammar"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/go-skynet/LocalAI/pkg/utils"
@@ -55,15 +55,111 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 		})
 		close(responses)
 	}
+	processTools := func(noAction string, prompt string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
+		result := ""
+		_, tokenUsage, _ := ComputeChoices(req, prompt, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
+			result += s
+			// TODO: Change generated BNF grammar to be compliant with the schema so we can
+			// stream the result token by token here.
+			return true
+		})
+
+		results := parseFunctionCall(result, config.FunctionsConfig.ParallelCalls)
+		noActionToRun := len(results) > 0 && results[0].name == noAction
+
+		switch {
+		case noActionToRun:
+			initialMessage := schema.OpenAIResponse{
+				ID:      id,
+				Created: created,
+				Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
+				Choices: []schema.Choice{{Delta: &schema.Message{Role: "assistant", Content: &emptyMessage}}},
+				Object:  "chat.completion.chunk",
+			}
+			responses <- initialMessage
+
+			result, err := handleQuestion(config, req, o, results[0].arguments, prompt)
+			if err != nil {
+				log.Error().Msgf("error handling question: %s", err.Error())
+				return
+			}
+
+			resp := schema.OpenAIResponse{
+				ID:      id,
+				Created: created,
+				Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
+				Choices: []schema.Choice{{Delta: &schema.Message{Content: &result}, Index: 0}},
+				Object:  "chat.completion.chunk",
+				Usage: schema.OpenAIUsage{
+					PromptTokens:     tokenUsage.Prompt,
+					CompletionTokens: tokenUsage.Completion,
+					TotalTokens:      tokenUsage.Prompt + tokenUsage.Completion,
+				},
+			}
+
+			responses <- resp
+
+		default:
+			for i, ss := range results {
+				name, args := ss.name, ss.arguments
+
+				initialMessage := schema.OpenAIResponse{
+					ID:      id,
+					Created: created,
+					Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
+					Choices: []schema.Choice{{
+						Delta: &schema.Message{
+							Role: "assistant",
+							ToolCalls: []schema.ToolCall{
+								{
+									Index: i,
+									ID:    id,
+									Type:  "function",
+									FunctionCall: schema.FunctionCall{
+										Name: name,
+									},
+								},
+							},
+						}}},
+					Object: "chat.completion.chunk",
+				}
+				responses <- initialMessage
+
+				responses <- schema.OpenAIResponse{
+					ID:      id,
+					Created: created,
+					Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
+					Choices: []schema.Choice{{
+						Delta: &schema.Message{
+							Role: "assistant",
+							ToolCalls: []schema.ToolCall{
+								{
+									Index: i,
+									ID:    id,
+									Type:  "function",
+									FunctionCall: schema.FunctionCall{
+										Arguments: args,
+									},
+								},
+							},
+						}}},
+					Object: "chat.completion.chunk",
+				}
+			}
+		}
+
+		close(responses)
+	}
+
 	return func(c *fiber.Ctx) error {
 		processFunctions := false
 		funcs := grammar.Functions{}
-		modelFile, input, err := readInput(c, o, true)
+		modelFile, input, err := readRequest(c, o, true)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}

-		config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
+		config, input, err := mergeRequestWithConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
@@ -116,13 +212,13 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)

 			// Update input grammar
 			jsStruct := funcs.ToJSONStructure()
-			config.Grammar = jsStruct.Grammar("")
+			config.Grammar = jsStruct.Grammar("", config.FunctionsConfig.ParallelCalls)
 		} else if input.JSONFunctionGrammarObject != nil {
-			config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
+			config.Grammar = input.JSONFunctionGrammarObject.Grammar("", config.FunctionsConfig.ParallelCalls)
 		}

 		// functions are not supported in stream mode (yet?)
-		toStream := input.Stream && !processFunctions
+		toStream := input.Stream

 		log.Debug().Msgf("Parameters: %+v", config)

@@ -145,6 +241,7 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			}
 			r := config.Roles[role]
 			contentExists := i.Content != nil && i.StringContent != ""
+
 			// First attempt to populate content via a chat message specific template
 			if config.TemplateConfig.ChatMessage != "" {
 				chatMessageData := model.ChatMessageTemplateData{
@@ -152,6 +249,7 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 					Role:         r,
 					RoleName:     role,
 					Content:      i.StringContent,
+					FunctionName: i.Name,
 					MessageIndex: messageIndex,
 				}
 				templatedChatMessage, err := o.Loader.EvaluateTemplateForChatMessage(config.TemplateConfig.ChatMessage, chatMessageData)
@@ -219,7 +317,12 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			c.Set("Transfer-Encoding", "chunked")
 		}

-		templateFile := config.Model
+		templateFile := ""
+
+		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
+		if o.Loader.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
+			templateFile = config.Model
+		}

 		if config.TemplateConfig.Chat != "" && !processFunctions {
 			templateFile = config.TemplateConfig.Chat
@@ -229,18 +332,19 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			templateFile = config.TemplateConfig.Functions
 		}

-		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-		templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.ChatPromptTemplate, templateFile, model.PromptTemplateData{
-			SystemPrompt:         config.SystemPrompt,
-			SuppressSystemPrompt: suppressConfigSystemPrompt,
-			Input:                predInput,
-			Functions:            funcs,
-		})
-		if err == nil {
-			predInput = templatedInput
-			log.Debug().Msgf("Template found, input modified to: %s", predInput)
-		} else {
-			log.Debug().Msgf("Template failed loading: %s", err.Error())
+		if templateFile != "" {
+			templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.ChatPromptTemplate, templateFile, model.PromptTemplateData{
+				SystemPrompt:         config.SystemPrompt,
+				SuppressSystemPrompt: suppressConfigSystemPrompt,
+				Input:                predInput,
+				Functions:            funcs,
+			})
+			if err == nil {
+				predInput = templatedInput
+				log.Debug().Msgf("Template found, input modified to: %s", predInput)
+			} else {
+				log.Debug().Msgf("Template failed loading: %s", err.Error())
+			}
 		}

 		log.Debug().Msgf("Prompt (after templating): %s", predInput)
@@ -248,17 +352,24 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			log.Debug().Msgf("Grammar: %+v", config.Grammar)
 		}

-		if toStream {
+		switch {
+		case toStream:
 			responses := make(chan schema.OpenAIResponse)

-			go process(predInput, input, config, o.Loader, responses)
+			if !processFunctions {
+				go process(predInput, input, config, o.Loader, responses)
+			} else {
+				go processTools(noActionName, predInput, input, config, o.Loader, responses)
+			}

 			c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
-
 				usage := &schema.OpenAIUsage{}
-
+				toolsCalled := false
 				for ev := range responses {
 					usage = &ev.Usage // Copy a pointer to the latest usage chunk so that the stop message can reference it
+					if len(ev.Choices[0].Delta.ToolCalls) > 0 {
+						toolsCalled = true
+					}
 					var buf bytes.Buffer
 					enc := json.NewEncoder(&buf)
 					enc.Encode(ev)
@@ -272,13 +383,20 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 					w.Flush()
 				}

+				finishReason := "stop"
+				if toolsCalled {
+					finishReason = "tool_calls"
+				} else if toolsCalled && len(input.Tools) == 0 {
+					finishReason = "function_call"
+				}
+
 				resp := &schema.OpenAIResponse{
 					ID:      id,
 					Created: created,
 					Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
 					Choices: []schema.Choice{
 						{
-							FinishReason: "stop",
+							FinishReason: finishReason,
 							Index:        0,
 							Delta:        &schema.Message{Content: &emptyMessage},
 						}},
@@ -292,102 +410,182 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 				w.Flush()
 			}))
 			return nil
-		}

-		result, tokenUsage, err := ComputeChoices(input, predInput, config, o, o.Loader, func(s string, c *[]schema.Choice) {
-			if processFunctions {
-				// As we have to change the result before processing, we can't stream the answer (yet?)
-				ss := map[string]interface{}{}
-				// This prevent newlines to break JSON parsing for clients
-				s = utils.EscapeNewLines(s)
-				json.Unmarshal([]byte(s), &ss)
-				log.Debug().Msgf("Function return: %s %+v", s, ss)
+		// no streaming mode
+		default:
+			result, tokenUsage, err := ComputeChoices(input, predInput, config, o, o.Loader, func(s string, c *[]schema.Choice) {
+				if !processFunctions {
+					// no function is called, just reply and use stop as finish reason
+					*c = append(*c, schema.Choice{FinishReason: "stop", Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
+					return
+				}

-				// The grammar defines the function name as "function", while OpenAI returns "name"
-				func_name := ss["function"]
-				// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
-				args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
-				d, _ := json.Marshal(args)
+				results := parseFunctionCall(s, config.FunctionsConfig.ParallelCalls)
+				noActionsToRun := len(results) > 0 && results[0].name == noActionName

-				ss["arguments"] = string(d)
-				ss["name"] = func_name
+				switch {
+				case noActionsToRun:
+					result, err := handleQuestion(config, input, o, results[0].arguments, predInput)
+					if err != nil {
+						log.Error().Msgf("error handling question: %s", err.Error())
+						return
+					}
+					*c = append(*c, schema.Choice{
+						Message: &schema.Message{Role: "assistant", Content: &result}})
+				default:
+					toolChoice := schema.Choice{
+						Message: &schema.Message{
+							Role: "assistant",
+						},
+					}

-				// if do nothing, reply with a message
-				if func_name == noActionName {
-					log.Debug().Msgf("nothing to do, computing a reply")
+					if len(input.Tools) > 0 {
+						toolChoice.FinishReason = "tool_calls"
+					}

-					// If there is a message that the LLM already sends as part of the JSON reply, use it
-					arguments := map[string]interface{}{}
-					json.Unmarshal([]byte(d), &arguments)
-					m, exists := arguments["message"]
-					if exists {
-						switch message := m.(type) {
-						case string:
-							if message != "" {
-								log.Debug().Msgf("Reply received from LLM: %s", message)
-								message = backend.Finetune(*config, predInput, message)
-								log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
-
-								*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &message}})
-								return
-							}
+					for _, ss := range results {
+						name, args := ss.name, ss.arguments
+						if len(input.Tools) > 0 {
+							// If we are using tools, we condense the function calls into
+							// a single response choice with all the tools
+							toolChoice.Message.ToolCalls = append(toolChoice.Message.ToolCalls,
+								schema.ToolCall{
+									ID:   id,
+									Type: "function",
+									FunctionCall: schema.FunctionCall{
+										Name:      name,
+										Arguments: args,
+									},
+								},
+							)
+						} else {
+							// otherwise we return more choices directly
+							*c = append(*c, schema.Choice{
+								FinishReason: "function_call",
+								Message: &schema.Message{
+									Role: "assistant",
+									FunctionCall: map[string]interface{}{
+										"name":      name,
+										"arguments": args,
+									},
+								},
+							})
 						}
 					}

-					log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
-					// Otherwise ask the LLM to understand the JSON output and the context, and return a message
-					// Note: This costs (in term of CPU) another computation
-					config.Grammar = ""
-					images := []string{}
-					for _, m := range input.Messages {
-						images = append(images, m.StringImages...)
+					if len(input.Tools) > 0 {
+						// we need to append our result if we are using tools
+						*c = append(*c, toolChoice)
 					}
-					predFunc, err := backend.ModelInference(input.Context, predInput, images, o.Loader, *config, o, nil)
-					if err != nil {
-						log.Error().Msgf("inference error: %s", err.Error())
-						return
-					}
-
-					prediction, err := predFunc()
-					if err != nil {
-						log.Error().Msgf("inference error: %s", err.Error())
-						return
-					}
-
-					fineTunedResponse := backend.Finetune(*config, predInput, prediction.Response)
-					*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &fineTunedResponse}})
-				} else {
-					// otherwise reply with the function call
-					*c = append(*c, schema.Choice{
-						FinishReason: "function_call",
-						Message:      &schema.Message{Role: "assistant", FunctionCall: ss},
-					})
 				}

-				return
+			}, nil)
+			if err != nil {
+				return err
 			}
-			*c = append(*c, schema.Choice{FinishReason: "stop", Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
-		}, nil)
-		if err != nil {
-			return err
+
+			resp := &schema.OpenAIResponse{
+				ID:      id,
+				Created: created,
+				Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
+				Choices: result,
+				Object:  "chat.completion",
+				Usage: schema.OpenAIUsage{
+					PromptTokens:     tokenUsage.Prompt,
+					CompletionTokens: tokenUsage.Completion,
+					TotalTokens:      tokenUsage.Prompt + tokenUsage.Completion,
+				},
+			}
+			respData, _ := json.Marshal(resp)
+			log.Debug().Msgf("Response: %s", respData)
+
+			// Return the prediction in the response body
+			return c.JSON(resp)
 		}

-		resp := &schema.OpenAIResponse{
-			ID:      id,
-			Created: created,
-			Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
-			Choices: result,
-			Object:  "chat.completion",
-			Usage: schema.OpenAIUsage{
-				PromptTokens:     tokenUsage.Prompt,
-				CompletionTokens: tokenUsage.Completion,
-				TotalTokens:      tokenUsage.Prompt + tokenUsage.Completion,
-			},
-		}
-		respData, _ := json.Marshal(resp)
-		log.Debug().Msgf("Response: %s", respData)
-
-		// Return the prediction in the response body
-		return c.JSON(resp)
 	}
 }
+
+func handleQuestion(config *config.Config, input *schema.OpenAIRequest, o *options.Option, args, prompt string) (string, error) {
+	log.Debug().Msgf("nothing to do, computing a reply")
+
+	// If there is a message that the LLM already sends as part of the JSON reply, use it
+	arguments := map[string]interface{}{}
+	json.Unmarshal([]byte(args), &arguments)
+	m, exists := arguments["message"]
+	if exists {
+		switch message := m.(type) {
+		case string:
+			if message != "" {
+				log.Debug().Msgf("Reply received from LLM: %s", message)
+				message = backend.Finetune(*config, prompt, message)
+				log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
+
+				return message, nil
+			}
+		}
+	}
+
+	log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
+	// Otherwise ask the LLM to understand the JSON output and the context, and return a message
+	// Note: This costs (in term of CPU/GPU) another computation
+	config.Grammar = ""
+	images := []string{}
+	for _, m := range input.Messages {
+		images = append(images, m.StringImages...)
+	}
+
+	predFunc, err := backend.ModelInference(input.Context, prompt, images, o.Loader, *config, o, nil)
+	if err != nil {
+		log.Error().Msgf("inference error: %s", err.Error())
+		return "", err
+	}
+
+	prediction, err := predFunc()
+	if err != nil {
+		log.Error().Msgf("inference error: %s", err.Error())
+		return "", err
+	}
+	return backend.Finetune(*config, prompt, prediction.Response), nil
+}
+
+type funcCallResults struct {
+	name      string
+	arguments string
+}
+
+func parseFunctionCall(llmresult string, multipleResults bool) []funcCallResults {
+	results := []funcCallResults{}
+
+	// TODO: use generics to avoid this code duplication
+	if multipleResults {
+		ss := []map[string]interface{}{}
+		s := utils.EscapeNewLines(llmresult)
+		json.Unmarshal([]byte(s), &ss)
+		log.Debug().Msgf("Function return: %s %+v", s, ss)
+
+		for _, s := range ss {
+			func_name := s["function"]
+			args := s["arguments"]
+			d, _ := json.Marshal(args)
+			results = append(results, funcCallResults{name: func_name.(string), arguments: string(d)})
+		}
+	} else {
+		// As we have to change the result before processing, we can't stream the answer token-by-token (yet?)
+		ss := map[string]interface{}{}
+		// This prevent newlines to break JSON parsing for clients
+		s := utils.EscapeNewLines(llmresult)
+		json.Unmarshal([]byte(s), &ss)
+		log.Debug().Msgf("Function return: %s %+v", s, ss)
+
+		// The grammar defines the function name as "function", while OpenAI returns "name"
+		func_name := ss["function"]
+		// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
+		args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
+		d, _ := json.Marshal(args)
+
+		results = append(results, funcCallResults{name: func_name.(string), arguments: string(d)})
+	}
+
+	return results
+}
--- a/api/openai/completion.go
+++ b/api/openai/completion.go
@@ -8,10 +8,10 @@ import (
 	"fmt"
 	"time"

-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/core/schema"
 	"github.com/go-skynet/LocalAI/pkg/grammar"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
@@ -53,14 +53,14 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 	}

 	return func(c *fiber.Ctx) error {
-		modelFile, input, err := readInput(c, o, true)
+		modelFile, input, err := readRequest(c, o, true)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}

 		log.Debug().Msgf("`input`: %+v", input)

-		config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
+		config, input, err := mergeRequestWithConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
@@ -81,7 +81,12 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 			c.Set("Transfer-Encoding", "chunked")
 		}

-		templateFile := config.Model
+		templateFile := ""
+
+		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
+		if o.Loader.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
+			templateFile = config.Model
+		}

 		if config.TemplateConfig.Completion != "" {
 			templateFile = config.TemplateConfig.Completion
@@ -94,13 +99,14 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe

 			predInput := config.PromptStrings[0]

-			// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-			templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
-				Input: predInput,
-			})
-			if err == nil {
-				predInput = templatedInput
-				log.Debug().Msgf("Template found, input modified to: %s", predInput)
+			if templateFile != "" {
+				templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
+					Input: predInput,
+				})
+				if err == nil {
+					predInput = templatedInput
+					log.Debug().Msgf("Template found, input modified to: %s", predInput)
+				}
 			}

 			responses := make(chan schema.OpenAIResponse)
@@ -145,14 +151,16 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 		totalTokenUsage := backend.TokenUsage{}

 		for k, i := range config.PromptStrings {
-			// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-			templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
-				SystemPrompt: config.SystemPrompt,
-				Input:        i,
-			})
-			if err == nil {
-				i = templatedInput
-				log.Debug().Msgf("Template found, input modified to: %s", i)
+			if templateFile != "" {
+				// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
+				templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
+					SystemPrompt: config.SystemPrompt,
+					Input:        i,
+				})
+				if err == nil {
+					i = templatedInput
+					log.Debug().Msgf("Template found, input modified to: %s", i)
+				}
 			}

 			r, tokenUsage, err := ComputeChoices(
--- a/api/openai/edit.go
+++ b/api/openai/edit.go
@@ -5,10 +5,10 @@ import (
 	"fmt"
 	"time"

-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/core/schema"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
 	"github.com/google/uuid"
@@ -18,19 +18,24 @@ import (

 func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
-		modelFile, input, err := readInput(c, o, true)
+		modelFile, input, err := readRequest(c, o, true)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}

-		config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
+		config, input, err := mergeRequestWithConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}

 		log.Debug().Msgf("Parameter Config: %+v", config)

-		templateFile := config.Model
+		templateFile := ""
+
+		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
+		if o.Loader.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
+			templateFile = config.Model
+		}

 		if config.TemplateConfig.Edit != "" {
 			templateFile = config.TemplateConfig.Edit
@@ -40,15 +45,16 @@ func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 		totalTokenUsage := backend.TokenUsage{}

 		for _, i := range config.InputStrings {
-			// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-			templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.EditPromptTemplate, templateFile, model.PromptTemplateData{
-				Input:        i,
-				Instruction:  input.Instruction,
-				SystemPrompt: config.SystemPrompt,
-			})
-			if err == nil {
-				i = templatedInput
-				log.Debug().Msgf("Template found, input modified to: %s", i)
+			if templateFile != "" {
+				templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.EditPromptTemplate, templateFile, model.PromptTemplateData{
+					Input:        i,
+					Instruction:  input.Instruction,
+					SystemPrompt: config.SystemPrompt,
+				})
+				if err == nil {
+					i = templatedInput
+					log.Debug().Msgf("Template found, input modified to: %s", i)
+				}
 			}

 			r, tokenUsage, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
--- a/api/openai/embeddings.go
+++ b/api/openai/embeddings.go
@@ -5,12 +5,12 @@ import (
 	"fmt"
 	"time"

-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/schema"
 	"github.com/google/uuid"

-	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/core/options"
 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"
 )
@@ -18,12 +18,12 @@ import (
 // https://platform.openai.com/docs/api-reference/embeddings
 func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
-		model, input, err := readInput(c, o, true)
+		model, input, err := readRequest(c, o, true)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}

-		config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
+		config, input, err := mergeRequestWithConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
--- a/api/openai/files.go
+++ b/api/openai/files.go
@@ -0,0 +1,218 @@
+package openai
+
+import (
+	"encoding/json"
+	"errors"
+	"fmt"
+	"os"
+	"path/filepath"
+	"time"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/utils"
+	"github.com/gofiber/fiber/v2"
+	"github.com/rs/zerolog/log"
+)
+
+var uploadedFiles []File
+
+const uploadedFilesFile = "uploadedFiles.json"
+
+// File represents the structure of a file object from the OpenAI API.
+type File struct {
+	ID        string    `json:"id"`         // Unique identifier for the file
+	Object    string    `json:"object"`     // Type of the object (e.g., "file")
+	Bytes     int       `json:"bytes"`      // Size of the file in bytes
+	CreatedAt time.Time `json:"created_at"` // The time at which the file was created
+	Filename  string    `json:"filename"`   // The name of the file
+	Purpose   string    `json:"purpose"`    // The purpose of the file (e.g., "fine-tune", "classifications", etc.)
+}
+
+func saveUploadConfig(uploadDir string) {
+	file, err := json.MarshalIndent(uploadedFiles, "", " ")
+	if err != nil {
+		log.Error().Msgf("Failed to JSON marshal the uploadedFiles: %s", err)
+	}
+
+	err = os.WriteFile(filepath.Join(uploadDir, uploadedFilesFile), file, 0644)
+	if err != nil {
+		log.Error().Msgf("Failed to save uploadedFiles to file: %s", err)
+	}
+}
+
+func LoadUploadConfig(uploadPath string) {
+	uploadFilePath := filepath.Join(uploadPath, uploadedFilesFile)
+
+	_, err := os.Stat(uploadFilePath)
+	if os.IsNotExist(err) {
+		log.Debug().Msgf("No uploadedFiles file found at %s", uploadFilePath)
+		return
+	}
+
+	file, err := os.ReadFile(uploadFilePath)
+	if err != nil {
+		log.Error().Msgf("Failed to read file: %s", err)
+	} else {
+		err = json.Unmarshal(file, &uploadedFiles)
+		if err != nil {
+			log.Error().Msgf("Failed to JSON unmarshal the file into uploadedFiles: %s", err)
+		}
+	}
+}
+
+// UploadFilesEndpoint https://platform.openai.com/docs/api-reference/files/create
+func UploadFilesEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		file, err := c.FormFile("file")
+		if err != nil {
+			return err
+		}
+
+		// Check the file size
+		if file.Size > int64(o.UploadLimitMB*1024*1024) {
+			return c.Status(fiber.StatusBadRequest).SendString(fmt.Sprintf("File size %d exceeds upload limit %d", file.Size, o.UploadLimitMB))
+		}
+
+		purpose := c.FormValue("purpose", "") //TODO put in purpose dirs
+		if purpose == "" {
+			return c.Status(fiber.StatusBadRequest).SendString("Purpose is not defined")
+		}
+
+		// Sanitize the filename to prevent directory traversal
+		filename := utils.SanitizeFileName(file.Filename)
+
+		savePath := filepath.Join(o.UploadDir, filename)
+
+		// Check if file already exists
+		if _, err := os.Stat(savePath); !os.IsNotExist(err) {
+			return c.Status(fiber.StatusBadRequest).SendString("File already exists")
+		}
+
+		err = c.SaveFile(file, savePath)
+		if err != nil {
+			return c.Status(fiber.StatusInternalServerError).SendString("Failed to save file: " + err.Error())
+		}
+
+		f := File{
+			ID:        fmt.Sprintf("file-%d", time.Now().Unix()),
+			Object:    "file",
+			Bytes:     int(file.Size),
+			CreatedAt: time.Now(),
+			Filename:  file.Filename,
+			Purpose:   purpose,
+		}
+
+		uploadedFiles = append(uploadedFiles, f)
+		saveUploadConfig(o.UploadDir)
+		return c.Status(fiber.StatusOK).JSON(f)
+	}
+}
+
+// ListFilesEndpoint https://platform.openai.com/docs/api-reference/files/list
+func ListFilesEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
+	type ListFiles struct {
+		Data   []File
+		Object string
+	}
+
+	return func(c *fiber.Ctx) error {
+		var listFiles ListFiles
+
+		purpose := c.Query("purpose")
+		if purpose == "" {
+			listFiles.Data = uploadedFiles
+		} else {
+			for _, f := range uploadedFiles {
+				if purpose == f.Purpose {
+					listFiles.Data = append(listFiles.Data, f)
+				}
+			}
+		}
+		listFiles.Object = "list"
+		return c.Status(fiber.StatusOK).JSON(listFiles)
+	}
+}
+
+func getFileFromRequest(c *fiber.Ctx) (*File, error) {
+	id := c.Params("file_id")
+	if id == "" {
+		return nil, fmt.Errorf("file_id parameter is required")
+	}
+
+	for _, f := range uploadedFiles {
+		if id == f.ID {
+			return &f, nil
+		}
+	}
+
+	return nil, fmt.Errorf("unable to find file id %s", id)
+}
+
+// GetFilesEndpoint https://platform.openai.com/docs/api-reference/files/retrieve
+func GetFilesEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		file, err := getFileFromRequest(c)
+		if err != nil {
+			return c.Status(fiber.StatusInternalServerError).SendString(err.Error())
+		}
+
+		return c.JSON(file)
+	}
+}
+
+// DeleteFilesEndpoint https://platform.openai.com/docs/api-reference/files/delete
+func DeleteFilesEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
+	type DeleteStatus struct {
+		Id      string
+		Object  string
+		Deleted bool
+	}
+
+	return func(c *fiber.Ctx) error {
+		file, err := getFileFromRequest(c)
+		if err != nil {
+			return c.Status(fiber.StatusInternalServerError).SendString(err.Error())
+		}
+
+		err = os.Remove(filepath.Join(o.UploadDir, file.Filename))
+		if err != nil {
+			// If the file doesn't exist then we should just continue to remove it
+			if !errors.Is(err, os.ErrNotExist) {
+				return c.Status(fiber.StatusInternalServerError).SendString(fmt.Sprintf("Unable to delete file: %s, %v", file.Filename, err))
+			}
+		}
+
+		// Remove upload from list
+		for i, f := range uploadedFiles {
+			if f.ID == file.ID {
+				uploadedFiles = append(uploadedFiles[:i], uploadedFiles[i+1:]...)
+				break
+			}
+		}
+
+		saveUploadConfig(o.UploadDir)
+		return c.JSON(DeleteStatus{
+			Id:      file.ID,
+			Object:  "file",
+			Deleted: true,
+		})
+	}
+}
+
+// GetFilesContentsEndpoint https://platform.openai.com/docs/api-reference/files/retrieve-contents
+func GetFilesContentsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		file, err := getFileFromRequest(c)
+		if err != nil {
+			return c.Status(fiber.StatusInternalServerError).SendString(err.Error())
+		}
+
+		fileContents, err := os.ReadFile(filepath.Join(o.UploadDir, file.Filename))
+		if err != nil {
+			return c.Status(fiber.StatusInternalServerError).SendString(err.Error())
+		}
+
+		return c.Send(fileContents)
+	}
+}
--- a/api/openai/files_test.go
+++ b/api/openai/files_test.go
@@ -0,0 +1,287 @@
+package openai
+
+import (
+	"encoding/json"
+	"fmt"
+	"io"
+	"mime/multipart"
+	"net/http"
+	"net/http/httptest"
+	"os"
+	"path/filepath"
+	"strings"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	utils2 "github.com/go-skynet/LocalAI/pkg/utils"
+	"github.com/gofiber/fiber/v2"
+	"github.com/stretchr/testify/assert"
+
+	"testing"
+)
+
+type ListFiles struct {
+	Data   []File
+	Object string
+}
+
+func startUpApp() (app *fiber.App, option *options.Option, loader *config.ConfigLoader) {
+	// Preparing the mocked objects
+	loader = &config.ConfigLoader{}
+
+	option = &options.Option{
+		UploadLimitMB: 10,
+		UploadDir:     "test_dir",
+	}
+
+	_ = os.RemoveAll(option.UploadDir)
+
+	app = fiber.New(fiber.Config{
+		BodyLimit: 20 * 1024 * 1024, // sets the limit to 20MB.
+	})
+
+	// Create a Test Server
+	app.Post("/files", UploadFilesEndpoint(loader, option))
+	app.Get("/files", ListFilesEndpoint(loader, option))
+	app.Get("/files/:file_id", GetFilesEndpoint(loader, option))
+	app.Delete("/files/:file_id", DeleteFilesEndpoint(loader, option))
+	app.Get("/files/:file_id/content", GetFilesContentsEndpoint(loader, option))
+
+	return
+}
+
+func TestUploadFileExceedSizeLimit(t *testing.T) {
+	// Preparing the mocked objects
+	loader := &config.ConfigLoader{}
+
+	option := &options.Option{
+		UploadLimitMB: 10,
+		UploadDir:     "test_dir",
+	}
+
+	_ = os.RemoveAll(option.UploadDir)
+
+	app := fiber.New(fiber.Config{
+		BodyLimit: 20 * 1024 * 1024, // sets the limit to 20MB.
+	})
+
+	// Create a Test Server
+	app.Post("/files", UploadFilesEndpoint(loader, option))
+	app.Get("/files", ListFilesEndpoint(loader, option))
+	app.Get("/files/:file_id", GetFilesEndpoint(loader, option))
+	app.Delete("/files/:file_id", DeleteFilesEndpoint(loader, option))
+	app.Get("/files/:file_id/content", GetFilesContentsEndpoint(loader, option))
+
+	t.Run("UploadFilesEndpoint file size exceeds limit", func(t *testing.T) {
+		resp, err := CallFilesUploadEndpoint(t, app, "foo.txt", "file", "fine-tune", 11, option)
+		assert.NoError(t, err)
+
+		assert.Equal(t, fiber.StatusBadRequest, resp.StatusCode)
+		assert.Contains(t, bodyToString(resp, t), "exceeds upload limit")
+	})
+	t.Run("UploadFilesEndpoint purpose not defined", func(t *testing.T) {
+		resp, _ := CallFilesUploadEndpoint(t, app, "foo.txt", "file", "", 5, option)
+
+		assert.Equal(t, fiber.StatusBadRequest, resp.StatusCode)
+		assert.Contains(t, bodyToString(resp, t), "Purpose is not defined")
+	})
+	t.Run("UploadFilesEndpoint file already exists", func(t *testing.T) {
+		f1 := CallFilesUploadEndpointWithCleanup(t, app, "foo.txt", "file", "fine-tune", 5, option)
+
+		resp, err := CallFilesUploadEndpoint(t, app, "foo.txt", "file", "fine-tune", 5, option)
+		fmt.Println(f1)
+		fmt.Printf("ERror: %v", err)
+
+		assert.Equal(t, fiber.StatusBadRequest, resp.StatusCode)
+		assert.Contains(t, bodyToString(resp, t), "File already exists")
+	})
+	t.Run("UploadFilesEndpoint file uploaded successfully", func(t *testing.T) {
+		file := CallFilesUploadEndpointWithCleanup(t, app, "test.txt", "file", "fine-tune", 5, option)
+
+		// Check if file exists in the disk
+		filePath := filepath.Join(option.UploadDir, utils2.SanitizeFileName("test.txt"))
+		_, err := os.Stat(filePath)
+
+		assert.False(t, os.IsNotExist(err))
+		assert.Equal(t, file.Bytes, 5242880)
+		assert.NotEmpty(t, file.CreatedAt)
+		assert.Equal(t, file.Filename, "test.txt")
+		assert.Equal(t, file.Purpose, "fine-tune")
+	})
+	t.Run("ListFilesEndpoint without purpose parameter", func(t *testing.T) {
+		resp, err := CallListFilesEndpoint(t, app, "")
+		assert.NoError(t, err)
+
+		assert.Equal(t, 200, resp.StatusCode)
+
+		listFiles := responseToListFile(t, resp)
+		if len(listFiles.Data) != len(uploadedFiles) {
+			t.Errorf("Expected %v files, got %v files", len(uploadedFiles), len(listFiles.Data))
+		}
+	})
+	t.Run("ListFilesEndpoint with valid purpose parameter", func(t *testing.T) {
+		_ = CallFilesUploadEndpointWithCleanup(t, app, "test.txt", "file", "fine-tune", 5, option)
+
+		resp, err := CallListFilesEndpoint(t, app, "fine-tune")
+		assert.NoError(t, err)
+
+		listFiles := responseToListFile(t, resp)
+		if len(listFiles.Data) != 1 {
+			t.Errorf("Expected 1 file, got %v files", len(listFiles.Data))
+		}
+	})
+	t.Run("ListFilesEndpoint with invalid query parameter", func(t *testing.T) {
+		resp, err := CallListFilesEndpoint(t, app, "not-so-fine-tune")
+		assert.NoError(t, err)
+		assert.Equal(t, 200, resp.StatusCode)
+
+		listFiles := responseToListFile(t, resp)
+
+		if len(listFiles.Data) != 0 {
+			t.Errorf("Expected 0 file, got %v files", len(listFiles.Data))
+		}
+	})
+	t.Run("GetFilesContentsEndpoint get file content", func(t *testing.T) {
+		req := httptest.NewRequest("GET", "/files", nil)
+		resp, _ := app.Test(req)
+		assert.Equal(t, 200, resp.StatusCode)
+
+		var listFiles ListFiles
+		if err := json.Unmarshal(bodyToByteArray(resp, t), &listFiles); err != nil {
+			t.Errorf("Failed to decode response: %v", err)
+			return
+		}
+
+		if len(listFiles.Data) != 0 {
+			t.Errorf("Expected 0 file, got %v files", len(listFiles.Data))
+		}
+	})
+}
+
+func CallListFilesEndpoint(t *testing.T, app *fiber.App, purpose string) (*http.Response, error) {
+	var target string
+	if purpose != "" {
+		target = fmt.Sprintf("/files?purpose=%s", purpose)
+	} else {
+		target = "/files"
+	}
+	req := httptest.NewRequest("GET", target, nil)
+	return app.Test(req)
+}
+
+func CallFilesContentEndpoint(t *testing.T, app *fiber.App, fileId string) (*http.Response, error) {
+	request := httptest.NewRequest("GET", "/files?file_id="+fileId, nil)
+	return app.Test(request)
+}
+
+func CallFilesUploadEndpoint(t *testing.T, app *fiber.App, fileName, tag, purpose string, fileSize int, o *options.Option) (*http.Response, error) {
+	// Create a file that exceeds the limit
+	file := createTestFile(t, fileName, fileSize, o)
+
+	// Creating a new HTTP Request
+	body, writer := newMultipartFile(file.Name(), tag, purpose)
+
+	req := httptest.NewRequest(http.MethodPost, "/files", body)
+	req.Header.Set(fiber.HeaderContentType, writer.FormDataContentType())
+	return app.Test(req)
+}
+
+func CallFilesUploadEndpointWithCleanup(t *testing.T, app *fiber.App, fileName, tag, purpose string, fileSize int, o *options.Option) File {
+	// Create a file that exceeds the limit
+	file := createTestFile(t, fileName, fileSize, o)
+
+	// Creating a new HTTP Request
+	body, writer := newMultipartFile(file.Name(), tag, purpose)
+
+	req := httptest.NewRequest(http.MethodPost, "/files", body)
+	req.Header.Set(fiber.HeaderContentType, writer.FormDataContentType())
+	resp, err := app.Test(req)
+	assert.NoError(t, err)
+	f := responseToFile(t, resp)
+
+	id := f.ID
+	t.Cleanup(func() {
+		_, err := CallFilesDeleteEndpoint(t, app, id)
+		assert.NoError(t, err)
+	})
+
+	return f
+
+}
+
+func CallFilesDeleteEndpoint(t *testing.T, app *fiber.App, fileId string) (*http.Response, error) {
+	target := fmt.Sprintf("/files/%s", fileId)
+	req := httptest.NewRequest(http.MethodDelete, target, nil)
+	return app.Test(req)
+}
+
+// Helper to create multi-part file
+func newMultipartFile(filePath, tag, purpose string) (*strings.Reader, *multipart.Writer) {
+	body := new(strings.Builder)
+	writer := multipart.NewWriter(body)
+	file, _ := os.Open(filePath)
+	defer file.Close()
+	part, _ := writer.CreateFormFile(tag, filepath.Base(filePath))
+	io.Copy(part, file)
+
+	if purpose != "" {
+		_ = writer.WriteField("purpose", purpose)
+	}
+
+	writer.Close()
+	return strings.NewReader(body.String()), writer
+}
+
+// Helper to create test files
+func createTestFile(t *testing.T, name string, sizeMB int, option *options.Option) *os.File {
+	err := os.MkdirAll(option.UploadDir, 0755)
+	if err != nil {
+
+		t.Fatalf("Error MKDIR: %v", err)
+	}
+
+	file, _ := os.Create(name)
+	file.WriteString(strings.Repeat("a", sizeMB*1024*1024)) // sizeMB MB File
+
+	t.Cleanup(func() {
+		os.Remove(name)
+		os.RemoveAll(option.UploadDir)
+	})
+	return file
+}
+
+func bodyToString(resp *http.Response, t *testing.T) string {
+	return string(bodyToByteArray(resp, t))
+}
+
+func bodyToByteArray(resp *http.Response, t *testing.T) []byte {
+	bodyBytes, err := io.ReadAll(resp.Body)
+	if err != nil {
+		t.Fatal(err)
+	}
+	return bodyBytes
+}
+
+func responseToFile(t *testing.T, resp *http.Response) File {
+	var file File
+	responseToString := bodyToString(resp, t)
+
+	err := json.NewDecoder(strings.NewReader(responseToString)).Decode(&file)
+	if err != nil {
+		t.Errorf("Failed to decode response: %s", err)
+	}
+
+	return file
+}
+
+func responseToListFile(t *testing.T, resp *http.Response) ListFiles {
+	var listFiles ListFiles
+	responseToString := bodyToString(resp, t)
+
+	err := json.NewDecoder(strings.NewReader(responseToString)).Decode(&listFiles)
+	if err != nil {
+		fmt.Printf("Failed to decode response: %s", err)
+	}
+
+	return listFiles
+}
--- a/api/openai/image.go
+++ b/api/openai/image.go
@@ -13,12 +13,12 @@ import (
 	"strings"
 	"time"

-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/schema"
 	"github.com/google/uuid"

-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"
@@ -61,7 +61,7 @@ func downloadFile(url string) (string, error) {
 */
 func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
-		m, input, err := readInput(c, o, false)
+		m, input, err := readRequest(c, o, false)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
@@ -71,7 +71,7 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
 		}
 		log.Debug().Msgf("Loading model: %+v", m)

-		config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
+		config, input, err := mergeRequestWithConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
@@ -122,8 +122,12 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx

 		log.Debug().Msgf("Parameter Config: %+v", config)

-		// XXX: Only stablediffusion is supported for now
-		if config.Backend == "" {
+		switch config.Backend {
+		case "stablediffusion":
+			config.Backend = model.StableDiffusionBackend
+		case "tinydream":
+			config.Backend = model.TinyDreamBackend
+		case "":
 			config.Backend = model.StableDiffusionBackend
 		}

--- a/api/openai/inference.go
+++ b/api/openai/inference.go
@@ -1,10 +1,10 @@
 package openai

 import (
-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/core/schema"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 )

--- a/api/openai/list.go
+++ b/api/openai/list.go
@@ -3,8 +3,8 @@ package openai
 import (
 	"regexp"

-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/schema"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/schema"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
 )
--- a/api/openai/request.go
+++ b/api/openai/request.go
@@ -7,20 +7,19 @@ import (
 	"fmt"
 	"io/ioutil"
 	"net/http"
-	"os"
-	"path/filepath"
 	"strings"

-	config "github.com/go-skynet/LocalAI/api/config"
-	options "github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/api/schema"
+	fiberContext "github.com/go-skynet/LocalAI/api/ctx"
+	config "github.com/go-skynet/LocalAI/core/config"
+	options "github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/core/schema"
+	"github.com/go-skynet/LocalAI/pkg/grammar"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"
 )

-func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *schema.OpenAIRequest, error) {
-	loader := o.Loader
+func readRequest(c *fiber.Ctx, o *options.Option, firstModel bool) (string, *schema.OpenAIRequest, error) {
 	input := new(schema.OpenAIRequest)
 	ctx, cancel := context.WithCancel(o.Context)
 	input.Context = ctx
@@ -30,38 +29,13 @@ func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *sche
 		return "", nil, fmt.Errorf("failed parsing request body: %w", err)
 	}

-	modelFile := input.Model
-
-	if c.Params("model") != "" {
-		modelFile = c.Params("model")
-	}
-
 	received, _ := json.Marshal(input)

 	log.Debug().Msgf("Request received: %s", string(received))

-	// Set model from bearer token, if available
-	bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
-	bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
+	modelFile, err := fiberContext.ModelFromContext(c, o.Loader, input.Model, firstModel)

-	// If no model was specified, take the first available
-	if modelFile == "" && !bearerExists && randomModel {
-		models, _ := loader.ListModels()
-		if len(models) > 0 {
-			modelFile = models[0]
-			log.Debug().Msgf("No model specified, using: %s", modelFile)
-		} else {
-			log.Debug().Msgf("No model specified, returning error")
-			return "", nil, fmt.Errorf("no model specified")
-		}
-	}
-
-	// If a model is found in bearer token takes precedence
-	if bearerExists {
-		log.Debug().Msgf("Using model from bearer token: %s", bearer)
-		modelFile = bearer
-	}
-	return modelFile, input, nil
+	return modelFile, input, err
 }

 // this function check if the string is an URL, if it's an URL downloads the image in memory
@@ -95,7 +69,7 @@ func getBase64Image(s string) (string, error) {
 	return "", fmt.Errorf("not valid string")
 }

-func updateConfig(config *config.Config, input *schema.OpenAIRequest) {
+func updateRequestConfig(config *config.Config, input *schema.OpenAIRequest) {
 	if input.Echo {
 		config.Echo = input.Echo
 	}
@@ -163,6 +137,20 @@ func updateConfig(config *config.Config, input *schema.OpenAIRequest) {
 		}
 	}

+	if len(input.Tools) > 0 {
+		for _, tool := range input.Tools {
+			input.Functions = append(input.Functions, tool.Function)
+		}
+	}
+
+	if input.ToolsChoice != nil {
+		var toolChoice grammar.Tool
+		json.Unmarshal([]byte(input.ToolsChoice.(string)), &toolChoice)
+		input.FunctionCall = map[string]interface{}{
+			"name": toolChoice.Function.Name,
+		}
+	}
+
 	// Decode each request's message content
 	index := 0
 	for i, m := range input.Messages {
@@ -282,55 +270,11 @@ func updateConfig(config *config.Config, input *schema.OpenAIRequest) {
 	}
 }

-func readConfig(modelFile string, input *schema.OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *schema.OpenAIRequest, error) {
-	// Load a config file if present after the model name
-	modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
-
-	var cfg *config.Config
-
-	defaults := func() {
-		cfg = config.DefaultConfig(modelFile)
-		cfg.ContextSize = ctx
-		cfg.Threads = threads
-		cfg.F16 = f16
-		cfg.Debug = debug
-	}
-
-	cfgExisting, exists := cm.GetConfig(modelFile)
-	if !exists {
-		if _, err := os.Stat(modelConfig); err == nil {
-			if err := cm.LoadConfig(modelConfig); err != nil {
-				return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
-			}
-			cfgExisting, exists = cm.GetConfig(modelFile)
-			if exists {
-				cfg = &cfgExisting
-			} else {
-				defaults()
-			}
-		} else {
-			defaults()
-		}
-	} else {
-		cfg = &cfgExisting
-	}
+func mergeRequestWithConfig(modelFile string, input *schema.OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *schema.OpenAIRequest, error) {
+	cfg, err := config.Load(modelFile, loader.ModelPath, cm, debug, threads, ctx, f16)

 	// Set the parameters for the language model prediction
-	updateConfig(cfg, input)
+	updateRequestConfig(cfg, input)

-	// Don't allow 0 as setting
-	if cfg.Threads == 0 {
-		if threads != 0 {
-			cfg.Threads = threads
-		} else {
-			cfg.Threads = 4
-		}
-	}
-
-	// Enforce debug flag if passed from CLI
-	if debug {
-		cfg.Debug = true
-	}
-
-	return cfg, input, nil
+	return cfg, input, err
 }
--- a/api/openai/transcription.go
+++ b/api/openai/transcription.go
@@ -8,9 +8,9 @@ import (
 	"path"
 	"path/filepath"

-	"github.com/go-skynet/LocalAI/api/backend"
-	config "github.com/go-skynet/LocalAI/api/config"
-	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/core/backend"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"

 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"
@@ -19,12 +19,12 @@ import (
 // https://platform.openai.com/docs/api-reference/audio/create
 func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
-		m, input, err := readInput(c, o, false)
+		m, input, err := readRequest(c, o, false)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}

-		config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
+		config, input, err := mergeRequestWithConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
 		if err != nil {
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
--- a/backend/backend.proto
+++ b/backend/backend.proto
@@ -112,7 +112,6 @@ message ModelOptions {
  int32 CLIPSkip = 33;
  string ControlNet = 48;

-  // RWKV
  string Tokenizer = 34;

  // LLM (llama.cpp)
@@ -135,6 +134,8 @@ message ModelOptions {
  float YarnAttnFactor = 45;
  float YarnBetaFast = 46;
  float YarnBetaSlow = 47;
+
+  string Type = 49;
 }

 message Result {
--- a/backend/backend_grpc.pb.go
+++ b/backend/backend_grpc.pb.go
@@ -0,0 +1,457 @@
+// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
+// versions:
+// - protoc-gen-go-grpc v1.2.0
+// - protoc             v4.23.4
+// source: backend/backend.proto
+
+package proto
+
+import (
+	context "context"
+	grpc "google.golang.org/grpc"
+	codes "google.golang.org/grpc/codes"
+	status "google.golang.org/grpc/status"
+)
+
+// This is a compile-time assertion to ensure that this generated file
+// is compatible with the grpc package it is being compiled against.
+// Requires gRPC-Go v1.32.0 or later.
+const _ = grpc.SupportPackageIsVersion7
+
+// BackendClient is the client API for Backend service.
+//
+// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream.
+type BackendClient interface {
+	Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error)
+	Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error)
+	LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error)
+	PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error)
+	Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error)
+	GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error)
+	AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error)
+	TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error)
+	TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error)
+	Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error)
+}
+
+type backendClient struct {
+	cc grpc.ClientConnInterface
+}
+
+func NewBackendClient(cc grpc.ClientConnInterface) BackendClient {
+	return &backendClient{cc}
+}
+
+func (c *backendClient) Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error) {
+	out := new(Reply)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Health", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error) {
+	out := new(Reply)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Predict", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error) {
+	out := new(Result)
+	err := c.cc.Invoke(ctx, "/backend.Backend/LoadModel", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error) {
+	stream, err := c.cc.NewStream(ctx, &Backend_ServiceDesc.Streams[0], "/backend.Backend/PredictStream", opts...)
+	if err != nil {
+		return nil, err
+	}
+	x := &backendPredictStreamClient{stream}
+	if err := x.ClientStream.SendMsg(in); err != nil {
+		return nil, err
+	}
+	if err := x.ClientStream.CloseSend(); err != nil {
+		return nil, err
+	}
+	return x, nil
+}
+
+type Backend_PredictStreamClient interface {
+	Recv() (*Reply, error)
+	grpc.ClientStream
+}
+
+type backendPredictStreamClient struct {
+	grpc.ClientStream
+}
+
+func (x *backendPredictStreamClient) Recv() (*Reply, error) {
+	m := new(Reply)
+	if err := x.ClientStream.RecvMsg(m); err != nil {
+		return nil, err
+	}
+	return m, nil
+}
+
+func (c *backendClient) Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error) {
+	out := new(EmbeddingResult)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Embedding", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error) {
+	out := new(Result)
+	err := c.cc.Invoke(ctx, "/backend.Backend/GenerateImage", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error) {
+	out := new(TranscriptResult)
+	err := c.cc.Invoke(ctx, "/backend.Backend/AudioTranscription", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error) {
+	out := new(Result)
+	err := c.cc.Invoke(ctx, "/backend.Backend/TTS", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error) {
+	out := new(TokenizationResponse)
+	err := c.cc.Invoke(ctx, "/backend.Backend/TokenizeString", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error) {
+	out := new(StatusResponse)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Status", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+// BackendServer is the server API for Backend service.
+// All implementations must embed UnimplementedBackendServer
+// for forward compatibility
+type BackendServer interface {
+	Health(context.Context, *HealthMessage) (*Reply, error)
+	Predict(context.Context, *PredictOptions) (*Reply, error)
+	LoadModel(context.Context, *ModelOptions) (*Result, error)
+	PredictStream(*PredictOptions, Backend_PredictStreamServer) error
+	Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error)
+	GenerateImage(context.Context, *GenerateImageRequest) (*Result, error)
+	AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error)
+	TTS(context.Context, *TTSRequest) (*Result, error)
+	TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error)
+	Status(context.Context, *HealthMessage) (*StatusResponse, error)
+	mustEmbedUnimplementedBackendServer()
+}
+
+// UnimplementedBackendServer must be embedded to have forward compatible implementations.
+type UnimplementedBackendServer struct {
+}
+
+func (UnimplementedBackendServer) Health(context.Context, *HealthMessage) (*Reply, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Health not implemented")
+}
+func (UnimplementedBackendServer) Predict(context.Context, *PredictOptions) (*Reply, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
+}
+func (UnimplementedBackendServer) LoadModel(context.Context, *ModelOptions) (*Result, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method LoadModel not implemented")
+}
+func (UnimplementedBackendServer) PredictStream(*PredictOptions, Backend_PredictStreamServer) error {
+	return status.Errorf(codes.Unimplemented, "method PredictStream not implemented")
+}
+func (UnimplementedBackendServer) Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Embedding not implemented")
+}
+func (UnimplementedBackendServer) GenerateImage(context.Context, *GenerateImageRequest) (*Result, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method GenerateImage not implemented")
+}
+func (UnimplementedBackendServer) AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method AudioTranscription not implemented")
+}
+func (UnimplementedBackendServer) TTS(context.Context, *TTSRequest) (*Result, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method TTS not implemented")
+}
+func (UnimplementedBackendServer) TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method TokenizeString not implemented")
+}
+func (UnimplementedBackendServer) Status(context.Context, *HealthMessage) (*StatusResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Status not implemented")
+}
+func (UnimplementedBackendServer) mustEmbedUnimplementedBackendServer() {}
+
+// UnsafeBackendServer may be embedded to opt out of forward compatibility for this service.
+// Use of this interface is not recommended, as added methods to BackendServer will
+// result in compilation errors.
+type UnsafeBackendServer interface {
+	mustEmbedUnimplementedBackendServer()
+}
+
+func RegisterBackendServer(s grpc.ServiceRegistrar, srv BackendServer) {
+	s.RegisterService(&Backend_ServiceDesc, srv)
+}
+
+func _Backend_Health_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(HealthMessage)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Health(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Health",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Health(ctx, req.(*HealthMessage))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(PredictOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Predict(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Predict",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Predict(ctx, req.(*PredictOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_LoadModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(ModelOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).LoadModel(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/LoadModel",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).LoadModel(ctx, req.(*ModelOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_PredictStream_Handler(srv interface{}, stream grpc.ServerStream) error {
+	m := new(PredictOptions)
+	if err := stream.RecvMsg(m); err != nil {
+		return err
+	}
+	return srv.(BackendServer).PredictStream(m, &backendPredictStreamServer{stream})
+}
+
+type Backend_PredictStreamServer interface {
+	Send(*Reply) error
+	grpc.ServerStream
+}
+
+type backendPredictStreamServer struct {
+	grpc.ServerStream
+}
+
+func (x *backendPredictStreamServer) Send(m *Reply) error {
+	return x.ServerStream.SendMsg(m)
+}
+
+func _Backend_Embedding_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(PredictOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Embedding(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Embedding",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Embedding(ctx, req.(*PredictOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_GenerateImage_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(GenerateImageRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).GenerateImage(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/GenerateImage",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).GenerateImage(ctx, req.(*GenerateImageRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_AudioTranscription_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(TranscriptRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).AudioTranscription(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/AudioTranscription",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).AudioTranscription(ctx, req.(*TranscriptRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_TTS_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(TTSRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).TTS(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/TTS",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).TTS(ctx, req.(*TTSRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_TokenizeString_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(PredictOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).TokenizeString(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/TokenizeString",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).TokenizeString(ctx, req.(*PredictOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_Status_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(HealthMessage)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Status(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Status",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Status(ctx, req.(*HealthMessage))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+// Backend_ServiceDesc is the grpc.ServiceDesc for Backend service.
+// It's only intended for direct use with grpc.RegisterService,
+// and not to be introspected or modified (even as a copy)
+var Backend_ServiceDesc = grpc.ServiceDesc{
+	ServiceName: "backend.Backend",
+	HandlerType: (*BackendServer)(nil),
+	Methods: []grpc.MethodDesc{
+		{
+			MethodName: "Health",
+			Handler:    _Backend_Health_Handler,
+		},
+		{
+			MethodName: "Predict",
+			Handler:    _Backend_Predict_Handler,
+		},
+		{
+			MethodName: "LoadModel",
+			Handler:    _Backend_LoadModel_Handler,
+		},
+		{
+			MethodName: "Embedding",
+			Handler:    _Backend_Embedding_Handler,
+		},
+		{
+			MethodName: "GenerateImage",
+			Handler:    _Backend_GenerateImage_Handler,
+		},
+		{
+			MethodName: "AudioTranscription",
+			Handler:    _Backend_AudioTranscription_Handler,
+		},
+		{
+			MethodName: "TTS",
+			Handler:    _Backend_TTS_Handler,
+		},
+		{
+			MethodName: "TokenizeString",
+			Handler:    _Backend_TokenizeString_Handler,
+		},
+		{
+			MethodName: "Status",
+			Handler:    _Backend_Status_Handler,
+		},
+	},
+	Streams: []grpc.StreamDesc{
+		{
+			StreamName:    "PredictStream",
+			Handler:       _Backend_PredictStream_Handler,
+			ServerStreams: true,
+		},
+	},
+	Metadata: "backend/backend.proto",
+}
--- a/backend/cpp/grpc/Makefile
+++ b/backend/cpp/grpc/Makefile
@@ -0,0 +1,66 @@
+# Basic platform detection
+HOST_SYSTEM = $(shell uname | cut -f 1 -d_)
+SYSTEM ?= $(HOST_SYSTEM)
+
+TAG_LIB_GRPC?=v1.59.0
+GIT_REPO_LIB_GRPC?=https://github.com/grpc/grpc.git
+GIT_CLONE_DEPTH?=1
+NUM_BUILD_THREADS?=$(shell nproc --ignore=1)
+
+INSTALLED_PACKAGES=installed_packages
+GRPC_REPO=grpc_repo
+GRPC_BUILD=grpc_build
+
+export CMAKE_ARGS?=
+CMAKE_ARGS+=-DCMAKE_BUILD_TYPE=Release
+CMAKE_ARGS+=-DgRPC_INSTALL=ON
+CMAKE_ARGS+=-DEXECUTABLE_OUTPUT_PATH=../$(INSTALLED_PACKAGES)/grpc/bin
+CMAKE_ARGS+=-DLIBRARY_OUTPUT_PATH=../$(INSTALLED_PACKAGES)/grpc/lib
+CMAKE_ARGS+=-DgRPC_BUILD_TESTS=OFF
+CMAKE_ARGS+=-DgRPC_BUILD_CSHARP_EXT=OFF
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_CPP_PLUGIN=ON
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_CSHARP_PLUGIN=OFF
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_NODE_PLUGIN=OFF
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_OBJECTIVE_C_PLUGIN=OFF
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_PHP_PLUGIN=OFF
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_PYTHON_PLUGIN=ON
+CMAKE_ARGS+=-DgRPC_BUILD_GRPC_RUBY_PLUGIN=OFF
+CMAKE_ARGS+=-Dprotobuf_WITH_ZLIB=ON
+CMAKE_ARGS+=-DRE2_BUILD_TESTING=OFF
+CMAKE_ARGS+=-DCMAKE_INSTALL_PREFIX=../$(INSTALLED_PACKAGES)
+
+# windows need to set OPENSSL_NO_ASM. Results in slower crypto performance but doesn't build otherwise.
+# May be resolvable, but for now its set. More info: https://stackoverflow.com/a/75240504/480673
+ifeq ($(SYSTEM),MSYS)
+CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
+endif
+ifeq ($(SYSTEM),MINGW64)
+CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
+endif
+ifeq ($(SYSTEM),MINGW32)
+CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
+endif
+ifeq ($(SYSTEM),CYGWIN)
+CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
+endif
+
+$(INSTALLED_PACKAGES): grpc_build
+
+$(GRPC_REPO):
+	git clone --depth $(GIT_CLONE_DEPTH) -b $(TAG_LIB_GRPC) $(GIT_REPO_LIB_GRPC) $(GRPC_REPO)/grpc
+	cd $(GRPC_REPO)/grpc && git submodule update --init --recursive --depth $(GIT_CLONE_DEPTH)
+
+$(GRPC_BUILD): $(GRPC_REPO)
+	mkdir -p $(GRPC_BUILD)
+	cd $(GRPC_BUILD) && cmake $(CMAKE_ARGS) ../$(GRPC_REPO)/grpc && cmake --build . -- -j ${NUM_BUILD_THREADS} && cmake --build . --target install -- -j ${NUM_BUILD_THREADS}
+
+build: $(INSTALLED_PACKAGES)
+
+rebuild:
+	rm -rf grpc_build
+	$(MAKE) grpc_build
+
+clean:
+	rm -rf grpc_build
+	rm -rf grpc_repo
+	rm -rf installed_packages
--- a/backend/cpp/grpc/script/build_grpc.sh
+++ b/backend/cpp/grpc/script/build_grpc.sh
@@ -1,81 +0,0 @@
-#!/bin/bash
-
-# Builds locally from sources the packages needed by the llama cpp backend.
-
-# Makes sure a few base packages exist.
-# sudo apt-get --no-upgrade -y install g++ gcc binutils cmake git build-essential autoconf libtool pkg-config 
-
-SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
-echo "Script directory: $SCRIPT_DIR"
-
-CPP_INSTALLED_PACKAGES_DIR=$1
-if [ -z ${CPP_INSTALLED_PACKAGES_DIR} ]; then 
-    echo "CPP_INSTALLED_PACKAGES_DIR env variable not set. Don't know where to install: failed."; 
-    echo
-    exit -1
-fi
-
-if [ -d "${CPP_INSTALLED_PACKAGES_DIR}" ]; then
-  echo "gRPC installation directory already exists. Nothing to do."
-  exit 0
-fi
-
-# The depth when cloning a git repo. 1 speeds up the clone when the repo history is not needed.
-GIT_CLONE_DEPTH=1
-
-NUM_BUILD_THREADS=$(nproc --ignore=1)
-
-# Google gRPC --------------------------------------------------------------------------------------
-TAG_LIB_GRPC="v1.59.0"
-GIT_REPO_LIB_GRPC="https://github.com/grpc/grpc.git"
-GRPC_REPO_DIR="${SCRIPT_DIR}/../grpc_repo"
-GRPC_BUILD_DIR="${SCRIPT_DIR}/../grpc_build"
-SRC_DIR_LIB_GRPC="${GRPC_REPO_DIR}/grpc"
-
-echo "SRC_DIR_LIB_GRPC: ${SRC_DIR_LIB_GRPC}"
-echo "GRPC_REPO_DIR: ${GRPC_REPO_DIR}"
-echo "GRPC_BUILD_DIR: ${GRPC_BUILD_DIR}"
-
-mkdir -pv ${GRPC_REPO_DIR}
-
-rm   -rf ${GRPC_BUILD_DIR}
-mkdir -pv ${GRPC_BUILD_DIR}
-
-mkdir -pv ${CPP_INSTALLED_PACKAGES_DIR}
-	
-if [ -d "${SRC_DIR_LIB_GRPC}" ]; then
-  echo "gRPC source already exists locally. Not cloned again."
-else  
-  ( cd ${GRPC_REPO_DIR} && \
-    git clone --depth ${GIT_CLONE_DEPTH} -b ${TAG_LIB_GRPC} ${GIT_REPO_LIB_GRPC} && \
-    cd ${SRC_DIR_LIB_GRPC} && \
-    git submodule update --init --recursive --depth ${GIT_CLONE_DEPTH} 
-  )    
-fi
-
-( cd ${GRPC_BUILD_DIR} && \
-  cmake -G "Unix Makefiles" \
-     -DCMAKE_BUILD_TYPE=Release \
-     -DgRPC_INSTALL=ON \
-     -DEXECUTABLE_OUTPUT_PATH=${CPP_INSTALLED_PACKAGES_DIR}/grpc/bin \
-     -DLIBRARY_OUTPUT_PATH=${CPP_INSTALLED_PACKAGES_DIR}/grpc/lib \
-     -DgRPC_BUILD_TESTS=OFF \
-     -DgRPC_BUILD_CSHARP_EXT=OFF \
-     -DgRPC_BUILD_GRPC_CPP_PLUGIN=ON \
-     -DgRPC_BUILD_GRPC_CSHARP_PLUGIN=OFF \
-     -DgRPC_BUILD_GRPC_NODE_PLUGIN=OFF \
-     -DgRPC_BUILD_GRPC_OBJECTIVE_C_PLUGIN=OFF \
-     -DgRPC_BUILD_GRPC_PHP_PLUGIN=OFF \
-     -DgRPC_BUILD_GRPC_PYTHON_PLUGIN=ON \
-     -DgRPC_BUILD_GRPC_RUBY_PLUGIN=OFF \
-     -Dprotobuf_WITH_ZLIB=ON \
-     -DRE2_BUILD_TESTING=OFF \
-     -DCMAKE_INSTALL_PREFIX=${CPP_INSTALLED_PACKAGES_DIR}/ \
-     ${SRC_DIR_LIB_GRPC}  && \
-  cmake --build .  -- -j ${NUM_BUILD_THREADS} && \
-  cmake --build .  --target install -- -j ${NUM_BUILD_THREADS} 
-)
-
-rm -rf ${GRPC_BUILD_DIR}
-rm -rf ${GRPC_REPO_DIR}
-
--- a/backend/cpp/llama/CMakeLists.txt
+++ b/backend/cpp/llama/CMakeLists.txt
@@ -2,24 +2,36 @@
 ## XXX: In some versions of CMake clip wasn't being built before llama.
 ## This is an hack for now, but it should be fixed in the future.
 set(TARGET myclip)
-add_library(${TARGET} clip.cpp clip.h)
+add_library(${TARGET} clip.cpp clip.h llava.cpp llava.h)
 install(TARGETS ${TARGET} LIBRARY)
-target_link_libraries(${TARGET} PRIVATE common ggml ${CMAKE_THREAD_LIBS_INIT})
+target_include_directories(myclip PUBLIC .)
+target_include_directories(myclip PUBLIC ../..)
+target_include_directories(myclip PUBLIC ../../common)
+target_link_libraries(${TARGET} PRIVATE common ggml llama ${CMAKE_THREAD_LIBS_INIT})
 target_compile_features(${TARGET} PRIVATE cxx_std_11)
 if (NOT MSVC)
    target_compile_options(${TARGET} PRIVATE -Wno-cast-qual) # stb_image.h
 endif()
+# END CLIP hack
+

 set(TARGET grpc-server)
-# END CLIP hack
 set(CMAKE_CXX_STANDARD 17)
 cmake_minimum_required(VERSION 3.15)
 set(TARGET grpc-server)
 set(_PROTOBUF_LIBPROTOBUF libprotobuf)
 set(_REFLECTION grpc++_reflection)
+
 if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
-    link_directories("/opt/homebrew/lib")
-    include_directories("/opt/homebrew/include")
+    # Set correct Homebrew install folder for Apple Silicon and Intel Macs
+    if (CMAKE_HOST_SYSTEM_PROCESSOR MATCHES "arm64")
+        set(HOMEBREW_DEFAULT_PREFIX "/opt/homebrew")
+    else()
+        set(HOMEBREW_DEFAULT_PREFIX "/usr/local")
+    endif()
+
+    link_directories("${HOMEBREW_DEFAULT_PREFIX}/lib")
+    include_directories("${HOMEBREW_DEFAULT_PREFIX}/include")
 endif()

 find_package(absl CONFIG REQUIRED)
@@ -62,7 +74,7 @@ add_library(hw_grpc_proto
  ${hw_proto_srcs}
  ${hw_proto_hdrs} )

-add_executable(${TARGET} grpc-server.cpp json.hpp )
+add_executable(${TARGET} grpc-server.cpp utils.hpp json.hpp)
 target_link_libraries(${TARGET} PRIVATE common llama myclip ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
  absl::flags_parse
  gRPC::${_REFLECTION}
--- a/backend/cpp/llama/Makefile
+++ b/backend/cpp/llama/Makefile
@@ -3,6 +3,7 @@ LLAMA_VERSION?=

 CMAKE_ARGS?=
 BUILD_TYPE?=
+ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh

 # If build type is cublas, then we set -DLLAMA_CUBLAS=ON to CMAKE_ARGS automatically
 ifeq ($(BUILD_TYPE),cublas)
@@ -19,6 +20,14 @@ else ifeq ($(BUILD_TYPE),hipblas)
 	CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON
 endif

+ifeq ($(BUILD_TYPE),sycl_f16)
+	CMAKE_ARGS+=-DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
+endif
+
+ifeq ($(BUILD_TYPE),sycl_f32)
+	CMAKE_ARGS+=-DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
+endif
+
 llama.cpp:
 	git clone --recurse-submodules https://github.com/ggerganov/llama.cpp llama.cpp
 	if [ -z "$(LLAMA_VERSION)" ]; then \
@@ -31,10 +40,14 @@ llama.cpp/examples/grpc-server:
 	cp -r $(abspath ./)/CMakeLists.txt llama.cpp/examples/grpc-server/
 	cp -r $(abspath ./)/grpc-server.cpp llama.cpp/examples/grpc-server/
 	cp -rfv $(abspath ./)/json.hpp llama.cpp/examples/grpc-server/
+	cp -rfv $(abspath ./)/utils.hpp llama.cpp/examples/grpc-server/
 	echo "add_subdirectory(grpc-server)" >> llama.cpp/examples/CMakeLists.txt
 ## XXX: In some versions of CMake clip wasn't being built before llama.
 ## This is an hack for now, but it should be fixed in the future.
 	cp -rfv llama.cpp/examples/llava/clip.h llama.cpp/examples/grpc-server/clip.h
+	cp -rfv llama.cpp/examples/llava/llava.cpp llama.cpp/examples/grpc-server/llava.cpp
+	echo '#include "llama.h"' > llama.cpp/examples/grpc-server/llava.h
+	cat llama.cpp/examples/llava/llava.h >> llama.cpp/examples/grpc-server/llava.h
 	cp -rfv llama.cpp/examples/llava/clip.cpp llama.cpp/examples/grpc-server/clip.cpp

 rebuild:
@@ -49,5 +62,10 @@ clean:
 	rm -rf grpc-server

 grpc-server: llama.cpp llama.cpp/examples/grpc-server
+ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+	bash -c "source $(ONEAPI_VARS); \
+	cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release"	
+else
 	cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release
+endif
 	cp llama.cpp/build/bin/grpc-server .
--- a/backend/cpp/llama/grpc-server.cpp
+++ b/backend/cpp/llama/grpc-server.cpp
--- a/backend/cpp/llama/utils.hpp
+++ b/backend/cpp/llama/utils.hpp
@@ -0,0 +1,510 @@
+// https://github.com/ggerganov/llama.cpp/blob/master/examples/server/utils.hpp
+
+#pragma once
+
+#include <string>
+#include <vector>
+#include <set>
+#include <mutex>
+#include <condition_variable>
+#include <unordered_map>
+
+#include "json.hpp"
+
+#include "../llava/clip.h"
+
+using json = nlohmann::json;
+
+extern bool server_verbose;
+
+#ifndef SERVER_VERBOSE
+#define SERVER_VERBOSE 1
+#endif
+
+#if SERVER_VERBOSE != 1
+#define LOG_VERBOSE(MSG, ...)
+#else
+#define LOG_VERBOSE(MSG, ...)                                            \
+    do                                                                   \
+    {                                                                    \
+        if (server_verbose)                                              \
+        {                                                                \
+            server_log("VERBOSE", __func__, __LINE__, MSG, __VA_ARGS__); \
+        }                                                                \
+    } while (0)
+#endif
+
+#define LOG_ERROR(  MSG, ...) server_log("ERROR",   __func__, __LINE__, MSG, __VA_ARGS__)
+#define LOG_WARNING(MSG, ...) server_log("WARNING", __func__, __LINE__, MSG, __VA_ARGS__)
+#define LOG_INFO(   MSG, ...) server_log("INFO",    __func__, __LINE__, MSG, __VA_ARGS__)
+
+//
+// parallel
+//
+
+enum server_state {
+    SERVER_STATE_LOADING_MODEL,  // Server is starting up, model not fully loaded yet
+    SERVER_STATE_READY,          // Server is ready and model is loaded
+    SERVER_STATE_ERROR           // An error occurred, load_model failed
+};
+
+enum task_type {
+    TASK_TYPE_COMPLETION,
+    TASK_TYPE_CANCEL,
+    TASK_TYPE_NEXT_RESPONSE
+};
+
+struct task_server {
+    int id = -1; // to be filled by llama_server_queue
+    int target_id;
+    task_type type;
+    json data;
+    bool infill_mode = false;
+    bool embedding_mode = false;
+    int multitask_id = -1;
+};
+
+struct task_result {
+    int id;
+    int multitask_id = -1;
+    bool stop;
+    bool error;
+    json result_json;
+};
+
+struct task_multi {
+    int id;
+    std::set<int> subtasks_remaining{};
+    std::vector<task_result> results{};
+};
+
+// TODO: can become bool if we can't find use of more states
+enum slot_state
+{
+    IDLE,
+    PROCESSING,
+};
+
+enum slot_command
+{
+    NONE,
+    LOAD_PROMPT,
+    RELEASE,
+};
+
+struct slot_params
+{
+    bool stream       = true;
+    bool cache_prompt = false; // remember the prompt to avoid reprocessing all prompt
+
+    uint32_t seed      = -1; // RNG seed
+    int32_t  n_keep    =  0; // number of tokens to keep from initial prompt
+    int32_t  n_predict = -1; // new tokens to predict
+
+    std::vector<std::string> antiprompt;
+
+    json input_prefix;
+    json input_suffix;
+};
+
+struct slot_image
+{
+    int32_t id;
+
+    bool request_encode_image = false;
+    float * image_embedding = nullptr;
+    int32_t image_tokens = 0;
+
+    clip_image_u8 * img_data;
+
+    std::string prefix_prompt; // before of this image
+};
+
+// completion token output with probabilities
+struct completion_token_output
+{
+    struct token_prob
+    {
+        llama_token tok;
+        float prob;
+    };
+
+    std::vector<token_prob> probs;
+    llama_token tok;
+    std::string text_to_send;
+};
+
+static inline void server_log(const char *level, const char *function, int line,
+                       const char *message, const nlohmann::ordered_json &extra)
+{
+    nlohmann::ordered_json log
+    {
+        {"timestamp", time(nullptr)},
+        {"level",     level},
+        {"function",  function},
+        {"line",      line},
+        {"message",   message},
+    };
+
+    if (!extra.empty())
+    {
+        log.merge_patch(extra);
+    }
+
+    const std::string str = log.dump(-1, ' ', false, json::error_handler_t::replace);
+    printf("%.*s\n", (int)str.size(), str.data());
+    fflush(stdout);
+}
+
+//
+// server utils
+//
+
+template <typename T>
+static T json_value(const json &body, const std::string &key, const T &default_value)
+{
+    // Fallback null to default value
+    return body.contains(key) && !body.at(key).is_null()
+        ? body.value(key, default_value)
+        : default_value;
+}
+
+inline std::string format_chatml(std::vector<json> messages)
+{
+    std::ostringstream chatml_msgs;
+
+    for (auto it = messages.begin(); it != messages.end(); ++it) {
+        chatml_msgs << "<|im_start|>"
+                    << json_value(*it, "role",    std::string("user")) << '\n';
+        chatml_msgs << json_value(*it, "content", std::string(""))
+                    << "<|im_end|>\n";
+    }
+
+    chatml_msgs << "<|im_start|>assistant" << '\n';
+
+    return chatml_msgs.str();
+}
+
+//
+// work queue utils
+//
+
+struct llama_server_queue {
+    int id = 0;
+    std::mutex mutex_tasks;
+    // queues
+    std::vector<task_server> queue_tasks;
+    std::vector<task_server> queue_tasks_deferred;
+    std::vector<task_multi> queue_multitasks;
+    std::condition_variable condition_tasks;
+    // callback functions
+    std::function<void(task_server&)> callback_new_task;
+    std::function<void(task_multi&)> callback_finish_multitask;
+    std::function<void(void)> callback_all_task_finished;
+
+    // Add a new task to the end of the queue
+    int post(task_server task) {
+        std::unique_lock<std::mutex> lock(mutex_tasks);
+        if (task.id == -1) {
+            task.id = id++;
+        }
+        queue_tasks.push_back(std::move(task));
+        condition_tasks.notify_one();
+        return task.id;
+    }
+
+    // Add a new task, but defer until one slot is available
+    void defer(task_server task) {
+        std::unique_lock<std::mutex> lock(mutex_tasks);
+        queue_tasks_deferred.push_back(std::move(task));
+    }
+
+    // Get the next id for creating anew task
+    int get_new_id() {
+        std::unique_lock<std::mutex> lock(mutex_tasks);
+        return id++;
+    }
+
+    // Register function to process a new task
+    void on_new_task(std::function<void(task_server&)> callback) {
+        callback_new_task = callback;
+    }
+
+    // Register function to process a multitask
+    void on_finish_multitask(std::function<void(task_multi&)> callback) {
+        callback_finish_multitask = callback;
+    }
+
+    // Register the function to be called when the batch of tasks is finished
+    void on_all_tasks_finished(std::function<void(void)> callback) {
+        callback_all_task_finished = callback;
+    }
+
+    // Call when the state of one slot is changed
+    void notify_slot_changed() {
+        // move deferred tasks back to main loop
+        std::unique_lock<std::mutex> lock(mutex_tasks);
+        for (auto & task : queue_tasks_deferred) {
+            queue_tasks.push_back(std::move(task));
+        }
+        queue_tasks_deferred.clear();
+    }
+
+    // Start the main loop. This call is blocking
+    [[noreturn]]
+    void start_loop() {
+        while (true) {
+            // new task arrived
+            LOG_VERBOSE("have new task", {});
+            {
+                while (true)
+                {
+                    std::unique_lock<std::mutex> lock(mutex_tasks);
+                    if (queue_tasks.empty()) {
+                        lock.unlock();
+                        break;
+                    }
+                    task_server task = queue_tasks.front();
+                    queue_tasks.erase(queue_tasks.begin());
+                    lock.unlock();
+                    LOG_VERBOSE("callback_new_task", {});
+                    callback_new_task(task);
+                }
+                LOG_VERBOSE("callback_all_task_finished", {});
+                // process and update all the multitasks
+                auto queue_iterator = queue_multitasks.begin();
+                while (queue_iterator != queue_multitasks.end())
+                {
+                    if (queue_iterator->subtasks_remaining.empty())
+                    {
+                        // all subtasks done == multitask is done
+                        task_multi current_multitask = *queue_iterator;
+                        callback_finish_multitask(current_multitask);
+                        // remove this multitask
+                        queue_iterator = queue_multitasks.erase(queue_iterator);
+                    }
+                    else
+                    {
+                        ++queue_iterator;
+                    }
+                }
+                // all tasks in the current loop is finished
+                callback_all_task_finished();
+            }
+            LOG_VERBOSE("wait for new task", {});
+            // wait for new task
+            {
+                std::unique_lock<std::mutex> lock(mutex_tasks);
+                if (queue_tasks.empty()) {
+                    condition_tasks.wait(lock, [&]{
+                        return !queue_tasks.empty();
+                    });
+                }
+            }
+        }
+    }
+
+    //
+    // functions to manage multitasks
+    //
+
+    // add a multitask by specifying the id of all subtask (subtask is a task_server)
+    void add_multitask(int multitask_id, std::vector<int>& sub_ids)
+    {
+        std::lock_guard<std::mutex> lock(mutex_tasks);
+        task_multi multi;
+        multi.id = multitask_id;
+        std::copy(sub_ids.begin(), sub_ids.end(), std::inserter(multi.subtasks_remaining, multi.subtasks_remaining.end()));
+        queue_multitasks.push_back(multi);
+    }
+
+    // updatethe remaining subtasks, while appending results to multitask
+    void update_multitask(int multitask_id, int subtask_id, task_result& result)
+    {
+        std::lock_guard<std::mutex> lock(mutex_tasks);
+        for (auto& multitask : queue_multitasks)
+        {
+            if (multitask.id == multitask_id)
+            {
+                multitask.subtasks_remaining.erase(subtask_id);
+                multitask.results.push_back(result);
+            }
+        }
+    }
+};
+
+struct llama_server_response {
+    typedef std::function<void(int, int, task_result&)> callback_multitask_t;
+    callback_multitask_t callback_update_multitask;
+    // for keeping track of all tasks waiting for the result
+    std::set<int> waiting_task_ids;
+    // the main result queue
+    std::vector<task_result> queue_results;
+    std::mutex mutex_results;
+    std::condition_variable condition_results;
+
+    void add_waiting_task_id(int task_id) {
+        std::unique_lock<std::mutex> lock(mutex_results);
+        waiting_task_ids.insert(task_id);
+    }
+
+    void remove_waiting_task_id(int task_id) {
+        std::unique_lock<std::mutex> lock(mutex_results);
+        waiting_task_ids.erase(task_id);
+    }
+
+    // This function blocks the thread until there is a response for this task_id
+    task_result recv(int task_id) {
+        while (true)
+        {
+            std::unique_lock<std::mutex> lock(mutex_results);
+            condition_results.wait(lock, [&]{
+                return !queue_results.empty();
+            });
+            LOG_VERBOSE("condition_results unblock", {});
+
+            for (int i = 0; i < (int) queue_results.size(); i++)
+            {
+                if (queue_results[i].id == task_id)
+                {
+                    assert(queue_results[i].multitask_id == -1);
+                    task_result res = queue_results[i];
+                    queue_results.erase(queue_results.begin() + i);
+                    return res;
+                }
+            }
+        }
+
+        // should never reach here
+    }
+
+    // Register the function to update multitask
+    void on_multitask_update(callback_multitask_t callback) {
+        callback_update_multitask = callback;
+    }
+
+    // Send a new result to a waiting task_id
+    void send(task_result result) {
+        std::unique_lock<std::mutex> lock(mutex_results);
+        LOG_VERBOSE("send new result", {});
+        for (auto& task_id : waiting_task_ids) {
+            // LOG_TEE("waiting task id %i \n", task_id);
+            // for now, tasks that have associated parent multitasks just get erased once multitask picks up the result
+            if (result.multitask_id == task_id)
+            {
+                LOG_VERBOSE("callback_update_multitask", {});
+                callback_update_multitask(task_id, result.id, result);
+                continue;
+            }
+
+            if (result.id == task_id)
+            {
+                LOG_VERBOSE("queue_results.push_back", {});
+                queue_results.push_back(result);
+                condition_results.notify_one();
+                return;
+            }
+        }
+    }
+};
+
+//
+// base64 utils (TODO: move to common in the future)
+//
+
+static const std::string base64_chars =
+             "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+             "abcdefghijklmnopqrstuvwxyz"
+             "0123456789+/";
+
+static inline bool is_base64(uint8_t c)
+{
+    return (isalnum(c) || (c == '+') || (c == '/'));
+}
+
+static inline std::vector<uint8_t> base64_decode(const std::string & encoded_string)
+{
+    int i = 0;
+    int j = 0;
+    int in_ = 0;
+
+    int in_len = encoded_string.size();
+
+    uint8_t char_array_4[4];
+    uint8_t char_array_3[3];
+
+    std::vector<uint8_t> ret;
+
+    while (in_len-- && (encoded_string[in_] != '=') && is_base64(encoded_string[in_]))
+    {
+        char_array_4[i++] = encoded_string[in_]; in_++;
+        if (i == 4)
+        {
+            for (i = 0; i <4; i++)
+            {
+                char_array_4[i] = base64_chars.find(char_array_4[i]);
+            }
+
+            char_array_3[0] = ((char_array_4[0]      ) << 2) + ((char_array_4[1] & 0x30) >> 4);
+            char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
+            char_array_3[2] = ((char_array_4[2] & 0x3) << 6) +   char_array_4[3];
+
+            for (i = 0; (i < 3); i++)
+            {
+                ret.push_back(char_array_3[i]);
+            }
+            i = 0;
+        }
+    }
+
+    if (i)
+    {
+        for (j = i; j <4; j++)
+        {
+            char_array_4[j] = 0;
+        }
+
+        for (j = 0; j <4; j++)
+        {
+            char_array_4[j] = base64_chars.find(char_array_4[j]);
+        }
+
+        char_array_3[0] = ((char_array_4[0]      ) << 2) + ((char_array_4[1] & 0x30) >> 4);
+        char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
+        char_array_3[2] = ((char_array_4[2] & 0x3) << 6) +   char_array_4[3];
+
+        for (j = 0; (j < i - 1); j++)
+        {
+            ret.push_back(char_array_3[j]);
+        }
+    }
+
+    return ret;
+}
+
+//
+// random string / id
+//
+
+static std::string random_string()
+{
+    static const std::string str("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz");
+
+    std::random_device rd;
+    std::mt19937 generator(rd());
+
+    std::string result(32, ' ');
+
+    for (int i = 0; i < 32; ++i) {
+        result[i] = str[generator() % str.size()];
+    }
+
+    return result;
+}
+
+static std::string gen_chatcmplid()
+{
+    std::stringstream chatcmplid;
+    chatcmplid << "chatcmpl-" << random_string();
+    return chatcmplid.str();
+}
--- a/backend/go/image/stablediffusion/main.go
+++ b/backend/go/image/stablediffusion/main.go
@@ -15,7 +15,7 @@ var (
 func main() {
 	flag.Parse()

-	if err := grpc.StartServer(*addr, &StableDiffusion{}); err != nil {
+	if err := grpc.StartServer(*addr, &Image{}); err != nil {
 		panic(err)
 	}
 }
--- a/backend/go/image/stablediffusion/stablediffusion.go
+++ b/backend/go/image/stablediffusion/stablediffusion.go
@@ -8,20 +8,20 @@ import (
 	"github.com/go-skynet/LocalAI/pkg/stablediffusion"
 )

-type StableDiffusion struct {
+type Image struct {
 	base.SingleThread
 	stablediffusion *stablediffusion.StableDiffusion
 }

-func (sd *StableDiffusion) Load(opts *pb.ModelOptions) error {
+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
-	sd.stablediffusion, err = stablediffusion.New(opts.ModelFile)
+	image.stablediffusion, err = stablediffusion.New(opts.ModelFile)
 	return err
 }

-func (sd *StableDiffusion) GenerateImage(opts *pb.GenerateImageRequest) error {
-	return sd.stablediffusion.GenerateImage(
+func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
+	return image.stablediffusion.GenerateImage(
 		int(opts.Height),
 		int(opts.Width),
 		int(opts.Mode),
--- a/backend/go/image/tinydream/main.go
+++ b/backend/go/image/tinydream/main.go
@@ -5,8 +5,6 @@ package main
 import (
 	"flag"

-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

@@ -17,7 +15,7 @@ var (
 func main() {
 	flag.Parse()

-	if err := grpc.StartServer(*addr, &transformers.MPT{}); err != nil {
+	if err := grpc.StartServer(*addr, &Image{}); err != nil {
 		panic(err)
 	}
 }
--- a/backend/go/image/tinydream/tinydream.go
+++ b/backend/go/image/tinydream/tinydream.go
@@ -0,0 +1,32 @@
+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/go-skynet/LocalAI/pkg/grpc/base"
+	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	"github.com/go-skynet/LocalAI/pkg/tinydream"
+)
+
+type Image struct {
+	base.SingleThread
+	tinydream *tinydream.TinyDream
+}
+
+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.tinydream, err = tinydream.New(opts.ModelFile)
+	return err
+}
+
+func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
+	return image.tinydream.GenerateImage(
+		int(opts.Height),
+		int(opts.Width),
+		int(opts.Step),
+		int(opts.Seed),
+		opts.PositivePrompt,
+		opts.NegativePrompt,
+		opts.Dst)
+}
--- a/backend/go/llm/dolly/main.go
+++ b/backend/go/llm/dolly/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.Dolly{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/falcon-ggml/main.go
+++ b/backend/go/llm/falcon-ggml/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.Falcon{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/gpt2/main.go
+++ b/backend/go/llm/gpt2/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.GPT2{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/gptj/main.go
+++ b/backend/go/llm/gptj/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.GPTJ{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/gptneox/main.go
+++ b/backend/go/llm/gptneox/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.GPTNeoX{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/replit/main.go
+++ b/backend/go/llm/replit/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.Replit{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/starcoder/main.go
+++ b/backend/go/llm/starcoder/main.go
@@ -1,23 +0,0 @@
-package main
-
-// Note: this is started internally by LocalAI and a server is allocated for each model
-
-import (
-	"flag"
-
-	transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
-
-	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-)
-
-var (
-	addr = flag.String("addr", "localhost:50051", "the address to connect to")
-)
-
-func main() {
-	flag.Parse()
-
-	if err := grpc.StartServer(*addr, &transformers.Starcoder{}); err != nil {
-		panic(err)
-	}
-}
--- a/backend/go/llm/transformers/dolly.go
+++ b/backend/go/llm/transformers/dolly.go
@@ -1,44 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type Dolly struct {
-	base.SingleThread
-
-	dolly *transformers.Dolly
-}
-
-func (llm *Dolly) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewDolly(opts.ModelFile)
-	llm.dolly = model
-	return err
-}
-
-func (llm *Dolly) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.dolly.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *Dolly) PredictStream(opts *pb.PredictOptions, results chan string) error {
-
-	go func() {
-		res, err := llm.dolly.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-
-	return nil
-}
--- a/backend/go/llm/transformers/falcon.go
+++ b/backend/go/llm/transformers/falcon.go
@@ -1,43 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type Falcon struct {
-	base.SingleThread
-
-	falcon *transformers.Falcon
-}
-
-func (llm *Falcon) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewFalcon(opts.ModelFile)
-	llm.falcon = model
-	return err
-}
-
-func (llm *Falcon) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *Falcon) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-
-	return nil
-}
--- a/backend/go/llm/transformers/gpt2.go
+++ b/backend/go/llm/transformers/gpt2.go
@@ -1,42 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type GPT2 struct {
-	base.SingleThread
-
-	gpt2 *transformers.GPT2
-}
-
-func (llm *GPT2) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.New(opts.ModelFile)
-	llm.gpt2 = model
-	return err
-}
-
-func (llm *GPT2) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.gpt2.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *GPT2) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.gpt2.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-	return nil
-}
--- a/backend/go/llm/transformers/gptj.go
+++ b/backend/go/llm/transformers/gptj.go
@@ -1,42 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type GPTJ struct {
-	base.SingleThread
-
-	gptj *transformers.GPTJ
-}
-
-func (llm *GPTJ) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewGPTJ(opts.ModelFile)
-	llm.gptj = model
-	return err
-}
-
-func (llm *GPTJ) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.gptj.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *GPTJ) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.gptj.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-	return nil
-}
--- a/backend/go/llm/transformers/gptneox.go
+++ b/backend/go/llm/transformers/gptneox.go
@@ -1,42 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type GPTNeoX struct {
-	base.SingleThread
-
-	gptneox *transformers.GPTNeoX
-}
-
-func (llm *GPTNeoX) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewGPTNeoX(opts.ModelFile)
-	llm.gptneox = model
-	return err
-}
-
-func (llm *GPTNeoX) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.gptneox.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *GPTNeoX) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.gptneox.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-	return nil
-}
--- a/backend/go/llm/transformers/mpt.go
+++ b/backend/go/llm/transformers/mpt.go
@@ -1,42 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type MPT struct {
-	base.SingleThread
-
-	mpt *transformers.MPT
-}
-
-func (llm *MPT) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewMPT(opts.ModelFile)
-	llm.mpt = model
-	return err
-}
-
-func (llm *MPT) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.mpt.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *MPT) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.mpt.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-	return nil
-}
--- a/backend/go/llm/transformers/predict.go
+++ b/backend/go/llm/transformers/predict.go
@@ -1,26 +0,0 @@
-package transformers
-
-import (
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-func buildPredictOptions(opts *pb.PredictOptions) []transformers.PredictOption {
-	predictOptions := []transformers.PredictOption{
-		transformers.SetTemperature(float64(opts.Temperature)),
-		transformers.SetTopP(float64(opts.TopP)),
-		transformers.SetTopK(int(opts.TopK)),
-		transformers.SetTokens(int(opts.Tokens)),
-		transformers.SetThreads(int(opts.Threads)),
-	}
-
-	if opts.Batch != 0 {
-		predictOptions = append(predictOptions, transformers.SetBatch(int(opts.Batch)))
-	}
-
-	if opts.Seed != 0 {
-		predictOptions = append(predictOptions, transformers.SetSeed(int(opts.Seed)))
-	}
-
-	return predictOptions
-}
--- a/backend/go/llm/transformers/replit.go
+++ b/backend/go/llm/transformers/replit.go
@@ -1,42 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type Replit struct {
-	base.SingleThread
-
-	replit *transformers.Replit
-}
-
-func (llm *Replit) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewReplit(opts.ModelFile)
-	llm.replit = model
-	return err
-}
-
-func (llm *Replit) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.replit.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *Replit) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.replit.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-	return nil
-}
--- a/backend/go/llm/transformers/starcoder.go
+++ b/backend/go/llm/transformers/starcoder.go
@@ -1,43 +0,0 @@
-package transformers
-
-// 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 (
-	"fmt"
-
-	"github.com/go-skynet/LocalAI/pkg/grpc/base"
-	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
-
-	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
-)
-
-type Starcoder struct {
-	base.SingleThread
-
-	starcoder *transformers.Starcoder
-}
-
-func (llm *Starcoder) Load(opts *pb.ModelOptions) error {
-	model, err := transformers.NewStarcoder(opts.ModelFile)
-	llm.starcoder = model
-	return err
-}
-
-func (llm *Starcoder) Predict(opts *pb.PredictOptions) (string, error) {
-	return llm.starcoder.Predict(opts.Prompt, buildPredictOptions(opts)...)
-}
-
-// fallback to Predict
-func (llm *Starcoder) PredictStream(opts *pb.PredictOptions, results chan string) error {
-	go func() {
-		res, err := llm.starcoder.Predict(opts.Prompt, buildPredictOptions(opts)...)
-
-		if err != nil {
-			fmt.Println("err: ", err)
-		}
-		results <- res
-		close(results)
-	}()
-
-	return nil
-}
--- a/backend/go/transcribe/transcript.go
+++ b/backend/go/transcribe/transcript.go
@@ -8,7 +8,7 @@ import (

 	"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
 	"github.com/go-audio/wav"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/schema"
 )

 func sh(c string) (string, error) {
--- a/backend/go/transcribe/whisper.go
+++ b/backend/go/transcribe/whisper.go
@@ -4,7 +4,7 @@ package main
 // It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
 import (
 	"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
-	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/go-skynet/LocalAI/core/schema"
 	"github.com/go-skynet/LocalAI/pkg/grpc/base"
 	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
 )
--- a/backend/python/autogptq/Makefile
+++ b/backend/python/autogptq/Makefile
@@ -1,5 +1,4 @@
 .PHONY: autogptq
 autogptq:
-	@echo "Creating virtual environment..."
-	@conda env create --name autogptq --file autogptq.yml
-	@echo "Virtual environment created."
+	$(MAKE) -C ../common-env/transformers
+
--- a/backend/python/autogptq/backend_pb2.py
+++ b/backend/python/autogptq/backend_pb2.py
--- a/backend/python/autogptq/run.sh
+++ b/backend/python/autogptq/run.sh
@@ -6,7 +6,7 @@
 export PATH=$PATH:/opt/conda/bin

 # Activate conda environment
-source activate autogptq
+source activate transformers

 # get the directory where the bash script is located
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
--- a/backend/python/bark/Makefile
+++ b/backend/python/bark/Makefile
@@ -1,8 +1,6 @@
 .PHONY: ttsbark
 ttsbark:
-	@echo "Creating virtual environment..."
-	@conda env create --name ttsbark --file ttsbark.yml
-	@echo "Virtual environment created."
+	$(MAKE) -C ../common-env/transformers

 .PHONY: run
 run:
--- a/backend/python/bark/backend_pb2.py
+++ b/backend/python/bark/backend_pb2.py
--- a/backend/python/bark/run.sh
+++ b/backend/python/bark/run.sh
@@ -6,7 +6,7 @@
 export PATH=$PATH:/opt/conda/bin

 # Activate conda environment
-source activate ttsbark
+source activate transformers

 # get the directory where the bash script is located
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
--- a/backend/python/bark/test.sh
+++ b/backend/python/bark/test.sh
@@ -3,7 +3,7 @@
 ## A bash script wrapper that runs the bark server with conda

 # Activate conda environment
-source activate ttsbark
+source activate transformers

 # get the directory where the bash script is located
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
--- a/backend/python/common-env/transformers/Makefile
+++ b/backend/python/common-env/transformers/Makefile
@@ -0,0 +1,14 @@
+CONDA_ENV_PATH = "transformers.yml"
+
+ifeq ($(BUILD_TYPE), cublas)
+	CONDA_ENV_PATH = "transformers-nvidia.yml"
+endif
+
+ifeq ($(BUILD_TYPE), hipblas)
+	CONDA_ENV_PATH = "transformers-rocm.yml"
+endif
+
+.PHONY: transformers
+transformers:
+	@echo "Installing $(CONDA_ENV_PATH)..."
+	bash install.sh $(CONDA_ENV_PATH)
--- a/backend/python/common-env/transformers/install.sh
+++ b/backend/python/common-env/transformers/install.sh
@@ -0,0 +1,24 @@
+#!/bin/bash
+set -ex
+
+# Check if environment exist
+conda_env_exists(){
+    ! conda list --name "${@}" >/dev/null 2>/dev/null
+}
+
+if conda_env_exists "transformers" ; then
+    echo "Creating virtual environment..."
+    conda env create --name transformers --file $1
+    echo "Virtual environment created."
+else 
+    echo "Virtual environment already exists."
+fi
+
+if [ "$PIP_CACHE_PURGE" = true ] ; then
+    export PATH=$PATH:/opt/conda/bin
+
+    # Activate conda environment
+    source activate transformers
+
+    pip cache purge
+fi
--- a/backend/python/common-env/transformers/transformers-nvidia.yml
+++ b/backend/python/common-env/transformers/transformers-nvidia.yml
@@ -1,4 +1,4 @@
-name: bark
+name: transformers
 channels:
  - defaults
 dependencies:
@@ -33,8 +33,11 @@ dependencies:
      - boto3==1.28.61
      - botocore==1.31.61
      - certifi==2023.7.22
+      - TTS==0.22.0
      - charset-normalizer==3.3.0
      - datasets==2.14.5
+      - sentence-transformers==2.2.2
+      - sentencepiece==0.1.99
      - dill==0.3.7
      - einops==0.7.0
      - encodec==0.1.1
@@ -43,7 +46,7 @@ dependencies:
      - fsspec==2023.6.0
      - funcy==2.0
      - grpcio==1.59.0
-      - huggingface-hub==0.16.4
+      - huggingface-hub
      - idna==3.4
      - jinja2==3.1.2
      - jmespath==1.0.1
@@ -51,7 +54,7 @@ dependencies:
      - mpmath==1.3.0
      - multidict==6.0.4
      - multiprocess==0.70.15
-      - networkx==3.1
+      - networkx
      - numpy==1.26.0
      - nvidia-cublas-cu12==12.1.3.1
      - nvidia-cuda-cupti-cu12==12.1.105
@@ -66,7 +69,7 @@ dependencies:
      - nvidia-nvjitlink-cu12==12.2.140
      - nvidia-nvtx-cu12==12.1.105
      - packaging==23.2
-      - pandas==2.1.1
+      - pandas
      - peft==0.5.0
      - protobuf==4.24.4
      - psutil==5.9.5
@@ -82,15 +85,35 @@ dependencies:
      - scipy==1.11.3
      - six==1.16.0
      - sympy==1.12
-      - tokenizers==0.14.0
-      - torch==2.1.0
-      - torchaudio==2.1.0
+      - tokenizers
+      - torch==2.1.2
+      - torchaudio==2.1.2
      - tqdm==4.66.1
-      - transformers==4.34.0
      - triton==2.1.0
      - typing-extensions==4.8.0
      - tzdata==2023.3
      - urllib3==1.26.17
      - xxhash==3.4.1
+      - auto-gptq==0.6.0
      - yarl==1.9.2
-prefix: /opt/conda/envs/bark
+      - soundfile
+      - langid
+      - wget
+      - unidecode
+      - pyopenjtalk-prebuilt
+      - pypinyin
+      - inflect
+      - cn2an
+      - jieba
+      - eng_to_ipa
+      - openai-whisper
+      - matplotlib
+      - gradio==3.41.2
+      - nltk
+      - sudachipy
+      - sudachidict_core
+      - vocos
+      - vllm==0.2.7
+      - transformers>=4.36.0  # Required for Mixtral.
+      - xformers==0.0.23.post1  
+prefix: /opt/conda/envs/transformers
--- a/backend/python/common-env/transformers/transformers-rocm.yml
+++ b/backend/python/common-env/transformers/transformers-rocm.yml
@@ -0,0 +1,109 @@
+name: transformers
+channels:
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1=main
+  - _openmp_mutex=5.1=1_gnu
+  - bzip2=1.0.8=h7b6447c_0
+  - ca-certificates=2023.08.22=h06a4308_0
+  - ld_impl_linux-64=2.38=h1181459_1
+  - libffi=3.4.4=h6a678d5_0
+  - libgcc-ng=11.2.0=h1234567_1
+  - libgomp=11.2.0=h1234567_1
+  - libstdcxx-ng=11.2.0=h1234567_1
+  - libuuid=1.41.5=h5eee18b_0
+  - ncurses=6.4=h6a678d5_0
+  - openssl=3.0.11=h7f8727e_2
+  - pip=23.2.1=py311h06a4308_0
+  - python=3.11.5=h955ad1f_0
+  - readline=8.2=h5eee18b_0
+  - setuptools=68.0.0=py311h06a4308_0
+  - sqlite=3.41.2=h5eee18b_0
+  - tk=8.6.12=h1ccaba5_0
+  - wheel=0.41.2=py311h06a4308_0
+  - xz=5.4.2=h5eee18b_0
+  - zlib=1.2.13=h5eee18b_0
+  - pip:
+      - --pre
+      - --extra-index-url https://download.pytorch.org/whl/nightly/
+      - accelerate==0.23.0
+      - aiohttp==3.8.5
+      - aiosignal==1.3.1
+      - async-timeout==4.0.3
+      - attrs==23.1.0
+      - bark==0.1.5
+      - boto3==1.28.61
+      - botocore==1.31.61
+      - certifi==2023.7.22
+      - TTS==0.22.0
+      - charset-normalizer==3.3.0
+      - datasets==2.14.5
+      - sentence-transformers==2.2.2
+      - sentencepiece==0.1.99
+      - dill==0.3.7
+      - einops==0.7.0
+      - encodec==0.1.1
+      - filelock==3.12.4
+      - frozenlist==1.4.0
+      - fsspec==2023.6.0
+      - funcy==2.0
+      - grpcio==1.59.0
+      - huggingface-hub
+      - idna==3.4
+      - jinja2==3.1.2
+      - jmespath==1.0.1
+      - markupsafe==2.1.3
+      - mpmath==1.3.0
+      - multidict==6.0.4
+      - multiprocess==0.70.15
+      - networkx
+      - numpy==1.26.0
+      - packaging==23.2
+      - pandas
+      - peft==0.5.0
+      - protobuf==4.24.4
+      - psutil==5.9.5
+      - pyarrow==13.0.0
+      - python-dateutil==2.8.2
+      - pytz==2023.3.post1
+      - pyyaml==6.0.1
+      - regex==2023.10.3
+      - requests==2.31.0
+      - rouge==1.0.1
+      - s3transfer==0.7.0
+      - safetensors==0.3.3
+      - scipy==1.11.3
+      - six==1.16.0
+      - sympy==1.12
+      - tokenizers
+      - torch
+      - torchaudio
+      - tqdm==4.66.1
+      - triton==2.1.0
+      - typing-extensions==4.8.0
+      - tzdata==2023.3
+      - auto-gptq==0.6.0
+      - urllib3==1.26.17
+      - xxhash==3.4.1
+      - yarl==1.9.2
+      - soundfile
+      - langid
+      - wget
+      - unidecode
+      - pyopenjtalk-prebuilt
+      - pypinyin
+      - inflect
+      - cn2an
+      - jieba
+      - eng_to_ipa
+      - openai-whisper
+      - matplotlib
+      - gradio==3.41.2
+      - nltk
+      - sudachipy
+      - sudachidict_core
+      - vocos
+      - vllm==0.2.7
+      - transformers>=4.36.0 # Required for Mixtral.
+      - xformers==0.0.23.post1
+prefix: /opt/conda/envs/transformers
--- a/backend/python/common-env/transformers/transformers.yml
+++ b/backend/python/common-env/transformers/transformers.yml
@@ -1,4 +1,4 @@
-name: vllm
+name: transformers
 channels:
  - defaults
 dependencies:
@@ -24,76 +24,84 @@ dependencies:
  - xz=5.4.2=h5eee18b_0
  - zlib=1.2.13=h5eee18b_0
  - pip:
+      - accelerate==0.23.0
+      - aiohttp==3.8.5
      - aiosignal==1.3.1
-      - anyio==3.7.1
+      - async-timeout==4.0.3
      - attrs==23.1.0
+      - bark==0.1.5
+      - boto3==1.28.61
+      - botocore==1.31.61
      - certifi==2023.7.22
+      - TTS==0.22.0
      - charset-normalizer==3.3.0
-      - click==8.1.7
-      - cmake==3.27.6
-      - fastapi==0.103.2
+      - datasets==2.14.5
+      - sentence-transformers==2.2.2
+      - sentencepiece==0.1.99
+      - dill==0.3.7
+      - einops==0.7.0
+      - encodec==0.1.1
      - filelock==3.12.4
      - frozenlist==1.4.0
-      - fsspec==2023.9.2
+      - fsspec==2023.6.0
+      - funcy==2.0
      - grpcio==1.59.0
-      - h11==0.14.0
-      - httptools==0.6.0
-      - huggingface-hub==0.17.3
+      - huggingface-hub
      - idna==3.4
      - jinja2==3.1.2
-      - jsonschema==4.19.1
-      - jsonschema-specifications==2023.7.1
-      - lit==17.0.2
+      - jmespath==1.0.1
      - markupsafe==2.1.3
      - mpmath==1.3.0
-      - msgpack==1.0.7
-      - networkx==3.1
-      - ninja==1.11.1
+      - multidict==6.0.4
+      - multiprocess==0.70.15
+      - networkx
      - numpy==1.26.0
-      - nvidia-cublas-cu11==11.10.3.66
-      - nvidia-cuda-cupti-cu11==11.7.101
-      - nvidia-cuda-nvrtc-cu11==11.7.99
-      - nvidia-cuda-runtime-cu11==11.7.99
-      - nvidia-cudnn-cu11==8.5.0.96
-      - nvidia-cufft-cu11==10.9.0.58
-      - nvidia-curand-cu11==10.2.10.91
-      - nvidia-cusolver-cu11==11.4.0.1
-      - nvidia-cusparse-cu11==11.7.4.91
-      - nvidia-nccl-cu11==2.14.3
-      - nvidia-nvtx-cu11==11.7.91
      - packaging==23.2
-      - pandas==2.1.1
+      - pandas
+      - peft==0.5.0
      - protobuf==4.24.4
      - psutil==5.9.5
      - pyarrow==13.0.0
-      - pydantic==1.10.13
      - python-dateutil==2.8.2
-      - python-dotenv==1.0.0
      - pytz==2023.3.post1
      - pyyaml==6.0.1
-      - ray==2.7.0
-      - referencing==0.30.2
      - regex==2023.10.3
      - requests==2.31.0
-      - rpds-py==0.10.4
-      - safetensors==0.4.0
-      - sentencepiece==0.1.99
+      - rouge==1.0.1
+      - s3transfer==0.7.0
+      - safetensors==0.3.3
+      - scipy==1.11.3
      - six==1.16.0
-      - sniffio==1.3.0
-      - starlette==0.27.0
      - sympy==1.12
-      - tokenizers==0.14.1
-      - torch==2.0.1
+      - tokenizers
+      - torch==2.1.2
+      - torchaudio==2.1.2
      - tqdm==4.66.1
-      - transformers==4.34.0
-      - triton==2.0.0
+      - triton==2.1.0
      - typing-extensions==4.8.0
      - tzdata==2023.3
-      - urllib3==2.0.6
-      - uvicorn==0.23.2
-      - uvloop==0.17.0
-      - vllm==0.2.0
-      - watchfiles==0.20.0
-      - websockets==11.0.3
-      - xformers==0.0.22
-prefix: /opt/conda/envs/vllm
+      - auto-gptq==0.6.0
+      - urllib3==1.26.17
+      - xxhash==3.4.1
+      - yarl==1.9.2
+      - soundfile
+      - langid
+      - wget
+      - unidecode
+      - pyopenjtalk-prebuilt
+      - pypinyin
+      - inflect
+      - cn2an
+      - jieba
+      - eng_to_ipa
+      - openai-whisper
+      - matplotlib
+      - gradio==3.41.2
+      - nltk
+      - sudachipy
+      - sudachidict_core
+      - vocos
+      - vllm==0.2.7
+      - transformers>=4.36.0  # Required for Mixtral.
+      - xformers==0.0.23.post1  
+prefix: /opt/conda/envs/transformers
--- a/backend/python/coqui/Makefile
+++ b/backend/python/coqui/Makefile
@@ -0,0 +1,15 @@
+.PHONY: coqui
+coqui:
+	$(MAKE) -C ../common-env/transformers
+
+.PHONY: run
+run:
+	@echo "Running coqui..."
+	bash run.sh
+	@echo "coqui run."
+
+.PHONY: test
+test:
+	@echo "Testing coqui..."
+	bash test.sh
+	@echo "coqui tested."
--- a/backend/python/coqui/README.md
+++ b/backend/python/coqui/README.md
@@ -0,0 +1,11 @@
+# Creating a separate environment for ttsbark project
+
+```
+make coqui
+```
+
+# Testing the gRPC server
+
+```
+make test
+```
--- a/backend/python/coqui/backend_pb2.py
+++ b/backend/python/coqui/backend_pb2.py
--- a/backend/python/coqui/backend_pb2_grpc.py
+++ b/backend/python/coqui/backend_pb2_grpc.py
@@ -0,0 +1,363 @@
+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+import grpc
+
+import backend_pb2 as backend__pb2
+
+
+class BackendStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.Health = channel.unary_unary(
+                '/backend.Backend/Health',
+                request_serializer=backend__pb2.HealthMessage.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.Predict = channel.unary_unary(
+                '/backend.Backend/Predict',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.LoadModel = channel.unary_unary(
+                '/backend.Backend/LoadModel',
+                request_serializer=backend__pb2.ModelOptions.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.PredictStream = channel.unary_stream(
+                '/backend.Backend/PredictStream',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.Embedding = channel.unary_unary(
+                '/backend.Backend/Embedding',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.EmbeddingResult.FromString,
+                )
+        self.GenerateImage = channel.unary_unary(
+                '/backend.Backend/GenerateImage',
+                request_serializer=backend__pb2.GenerateImageRequest.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.AudioTranscription = channel.unary_unary(
+                '/backend.Backend/AudioTranscription',
+                request_serializer=backend__pb2.TranscriptRequest.SerializeToString,
+                response_deserializer=backend__pb2.TranscriptResult.FromString,
+                )
+        self.TTS = channel.unary_unary(
+                '/backend.Backend/TTS',
+                request_serializer=backend__pb2.TTSRequest.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.TokenizeString = channel.unary_unary(
+                '/backend.Backend/TokenizeString',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.TokenizationResponse.FromString,
+                )
+        self.Status = channel.unary_unary(
+                '/backend.Backend/Status',
+                request_serializer=backend__pb2.HealthMessage.SerializeToString,
+                response_deserializer=backend__pb2.StatusResponse.FromString,
+                )
+
+
+class BackendServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def Health(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Predict(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def LoadModel(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def PredictStream(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Embedding(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def GenerateImage(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def AudioTranscription(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def TTS(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def TokenizeString(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Status(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_BackendServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'Health': grpc.unary_unary_rpc_method_handler(
+                    servicer.Health,
+                    request_deserializer=backend__pb2.HealthMessage.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'Predict': grpc.unary_unary_rpc_method_handler(
+                    servicer.Predict,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'LoadModel': grpc.unary_unary_rpc_method_handler(
+                    servicer.LoadModel,
+                    request_deserializer=backend__pb2.ModelOptions.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'PredictStream': grpc.unary_stream_rpc_method_handler(
+                    servicer.PredictStream,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'Embedding': grpc.unary_unary_rpc_method_handler(
+                    servicer.Embedding,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.EmbeddingResult.SerializeToString,
+            ),
+            'GenerateImage': grpc.unary_unary_rpc_method_handler(
+                    servicer.GenerateImage,
+                    request_deserializer=backend__pb2.GenerateImageRequest.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'AudioTranscription': grpc.unary_unary_rpc_method_handler(
+                    servicer.AudioTranscription,
+                    request_deserializer=backend__pb2.TranscriptRequest.FromString,
+                    response_serializer=backend__pb2.TranscriptResult.SerializeToString,
+            ),
+            'TTS': grpc.unary_unary_rpc_method_handler(
+                    servicer.TTS,
+                    request_deserializer=backend__pb2.TTSRequest.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'TokenizeString': grpc.unary_unary_rpc_method_handler(
+                    servicer.TokenizeString,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.TokenizationResponse.SerializeToString,
+            ),
+            'Status': grpc.unary_unary_rpc_method_handler(
+                    servicer.Status,
+                    request_deserializer=backend__pb2.HealthMessage.FromString,
+                    response_serializer=backend__pb2.StatusResponse.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'backend.Backend', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+
+
+ # This class is part of an EXPERIMENTAL API.
+class Backend(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def Health(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Health',
+            backend__pb2.HealthMessage.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Predict(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Predict',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def LoadModel(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/LoadModel',
+            backend__pb2.ModelOptions.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def PredictStream(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(request, target, '/backend.Backend/PredictStream',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Embedding(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Embedding',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.EmbeddingResult.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def GenerateImage(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/GenerateImage',
+            backend__pb2.GenerateImageRequest.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def AudioTranscription(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/AudioTranscription',
+            backend__pb2.TranscriptRequest.SerializeToString,
+            backend__pb2.TranscriptResult.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def TTS(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/TTS',
+            backend__pb2.TTSRequest.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def TokenizeString(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/TokenizeString',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.TokenizationResponse.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Status(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Status',
+            backend__pb2.HealthMessage.SerializeToString,
+            backend__pb2.StatusResponse.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
--- a/backend/python/coqui/coqui_server.py
+++ b/backend/python/coqui/coqui_server.py
@@ -0,0 +1,104 @@
+#!/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
+
+import torch
+from TTS.api import TTS
+
+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):
+
+        # Get device
+        # device = "cuda" if request.CUDA else "cpu"
+        if torch.cuda.is_available():
+            print("CUDA is available", file=sys.stderr)
+            device = "cuda"
+        else:
+            print("CUDA is not available", file=sys.stderr)
+            device = "cpu"
+
+        if not torch.cuda.is_available() and request.CUDA:
+            return backend_pb2.Result(success=False, message="CUDA is not available")
+
+        self.AudioPath = None
+        # List available 🐸TTS models
+        print(TTS().list_models())
+        if os.path.isabs(request.AudioPath):
+            self.AudioPath = request.AudioPath
+        elif request.AudioPath and request.ModelFile != "" and not os.path.isabs(request.AudioPath):
+            # get base path of modelFile
+            modelFileBase = os.path.dirname(request.ModelFile)
+            # modify LoraAdapter to be relative to modelFileBase
+            self.AudioPath = os.path.join(modelFileBase, request.AudioPath)
+
+        try:
+            print("Preparing models, please wait", file=sys.stderr)
+            self.tts = TTS(request.Model).to(device)
+        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 TTS(self, request, context):
+        try:
+            self.tts.tts_to_file(text=request.text, speaker_wav=self.AudioPath, language=COQUI_LANGUAGE, file_path=request.dst)
+        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("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)
--- a/backend/python/coqui/run.sh
+++ b/backend/python/coqui/run.sh
@@ -0,0 +1,14 @@
+#!/bin/bash
+
+##
+## A bash script wrapper that runs the ttsbark server with conda
+
+export PATH=$PATH:/opt/conda/bin
+
+# Activate conda environment
+source activate transformers
+
+# get the directory where the bash script is located
+DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
+
+python $DIR/coqui_server.py $@
--- a/backend/python/coqui/test.py
+++ b/backend/python/coqui/test.py
@@ -0,0 +1,82 @@
+"""
+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", "coqui_server.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="tts_models/en/vctk/vits"))
+                print(response)
+                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="tts_models/en/vctk/vits"))
+                self.assertTrue(response.success)
+                tts_request = backend_pb2.TTSRequest(text="80s TV news production music hit for tonight's biggest story")
+                tts_response = stub.TTS(tts_request)
+                self.assertIsNotNone(tts_response)
+        except Exception as err:
+            print(err)
+            self.fail("TTS service failed")
+        finally:
+            self.tearDown()
--- a/backend/python/coqui/test.sh
+++ b/backend/python/coqui/test.sh
@@ -0,0 +1,11 @@
+#!/bin/bash
+##
+## A bash script wrapper that runs the bark server with conda
+
+# Activate conda environment
+source activate transformers
+
+# get the directory where the bash script is located
+DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
+
+python -m unittest $DIR/test.py
--- a/backend/python/diffusers/Makefile
+++ b/backend/python/diffusers/Makefile
@@ -1,8 +1,13 @@
+export CONDA_ENV_PATH = "diffusers.yml"
+
+ifeq ($(BUILD_TYPE), hipblas)
+export CONDA_ENV_PATH = "diffusers-rocm.yml"
+endif
+
 .PHONY: diffusers
 diffusers:
-	@echo "Creating virtual environment..."
-	@conda env create --name diffusers --file diffusers.yml
-	@echo "Virtual environment created."
+	@echo "Installing $(CONDA_ENV_PATH)..."
+	bash install.sh $(CONDA_ENV_PATH)

 .PHONY: run
 run:
@@ -11,4 +16,4 @@ run:
 	@echo "Diffusers run."

 test:
-	bash test.sh
+	bash test.sh
--- a/backend/python/diffusers/backend_diffusers.py
+++ b/backend/python/diffusers/backend_diffusers.py
@@ -149,9 +149,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
            local = False
            modelFile = request.Model

-            cfg_scale = 7
+            self.cfg_scale = 7
            if request.CFGScale != 0:
-                cfg_scale = request.CFGScale
+                self.cfg_scale = request.CFGScale
            
            clipmodel = "runwayml/stable-diffusion-v1-5"
            if request.CLIPModel != "":
@@ -173,17 +173,14 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
            if (request.PipelineType == "StableDiffusionImg2ImgPipeline") or (request.IMG2IMG and request.PipelineType == ""):
                if fromSingleFile:
                    self.pipe = StableDiffusionImg2ImgPipeline.from_single_file(modelFile,
-                                torch_dtype=torchType,
-                                guidance_scale=cfg_scale)
+                                torch_dtype=torchType)
                else:
                    self.pipe = StableDiffusionImg2ImgPipeline.from_pretrained(request.Model,
-                                torch_dtype=torchType,
-                                guidance_scale=cfg_scale)
+                                torch_dtype=torchType)

            elif request.PipelineType == "StableDiffusionDepth2ImgPipeline":
                self.pipe = StableDiffusionDepth2ImgPipeline.from_pretrained(request.Model,
-                            torch_dtype=torchType,
-                            guidance_scale=cfg_scale)
+                            torch_dtype=torchType)
            ## img2vid
            elif request.PipelineType == "StableVideoDiffusionPipeline":
                self.img2vid=True
@@ -197,38 +194,32 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
                self.pipe = AutoPipelineForText2Image.from_pretrained(request.Model,
                                                    torch_dtype=torchType,
                                                    use_safetensors=SAFETENSORS, 
-                                                    variant=variant,
-                                                    guidance_scale=cfg_scale)
+                                                    variant=variant)
            elif request.PipelineType == "StableDiffusionPipeline":
                if fromSingleFile:
                    self.pipe = StableDiffusionPipeline.from_single_file(modelFile,
-                                                        torch_dtype=torchType,
-                                                        guidance_scale=cfg_scale)
+                                                        torch_dtype=torchType)
                else:
                    self.pipe = StableDiffusionPipeline.from_pretrained(request.Model,
-                                                        torch_dtype=torchType,
-                                                        guidance_scale=cfg_scale)
+                                                        torch_dtype=torchType)
            elif request.PipelineType == "DiffusionPipeline":
                self.pipe = DiffusionPipeline.from_pretrained(request.Model,
-                                                        torch_dtype=torchType,
-                                                        guidance_scale=cfg_scale)
+                                                        torch_dtype=torchType)
            elif request.PipelineType == "VideoDiffusionPipeline":
                self.txt2vid=True
                self.pipe = DiffusionPipeline.from_pretrained(request.Model,
-                                                        torch_dtype=torchType,
-                                                        guidance_scale=cfg_scale)
+                                                        torch_dtype=torchType)
            elif request.PipelineType == "StableDiffusionXLPipeline":
                if fromSingleFile:
                    self.pipe = StableDiffusionXLPipeline.from_single_file(modelFile,
-                                                               torch_dtype=torchType, use_safetensors=True,
-                                                               guidance_scale=cfg_scale)
+                                                               torch_dtype=torchType,
+                                                               use_safetensors=True)
                else:
                    self.pipe = StableDiffusionXLPipeline.from_pretrained(
                        request.Model, 
                        torch_dtype=torchType, 
                        use_safetensors=True, 
-                        variant=variant,
-                        guidance_scale=cfg_scale)
+                        variant=variant)

            if CLIPSKIP and request.CLIPSkip != 0:
                self.clip_skip = request.CLIPSkip
@@ -384,12 +375,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
            image = image.resize((1024, 576))

            generator = torch.manual_seed(request.seed)
-            frames = self.pipe(image, decode_chunk_size=CHUNK_SIZE, generator=generator).frames[0]
+            frames = self.pipe(image, guidance_scale=self.cfg_scale, decode_chunk_size=CHUNK_SIZE, generator=generator).frames[0]
            export_to_video(frames, request.dst, fps=FPS)
            return backend_pb2.Result(message="Media generated successfully", success=True)

        if self.txt2vid:
-            video_frames = self.pipe(prompt, num_inference_steps=steps, num_frames=int(FRAMES)).frames
+            video_frames = self.pipe(prompt, guidance_scale=self.cfg_scale, num_inference_steps=steps, num_frames=int(FRAMES)).frames
            export_to_video(video_frames, request.dst)
            return backend_pb2.Result(message="Media generated successfully", success=True)

@@ -398,13 +389,15 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
            conditioning = self.compel.build_conditioning_tensor(prompt)
            kwargs["prompt_embeds"]= conditioning
            # pass the kwargs dictionary to the self.pipe method
-            image = self.pipe( 
+            image = self.pipe(
+                guidance_scale=self.cfg_scale,
                **kwargs
                ).images[0] 
        else:
            # pass the kwargs dictionary to the self.pipe method
            image = self.pipe(
-                prompt, 
+                prompt,
+                guidance_scale=self.cfg_scale,
                **kwargs
                ).images[0]

--- a/backend/python/diffusers/backend_pb2.py
+++ b/backend/python/diffusers/backend_pb2.py
--- a/backend/python/transformers/transformers.yml
+++ b/backend/python/transformers/transformers.yml
@@ -1,4 +1,4 @@
-name: transformers
+name: diffusers
 channels:
  - defaults
 dependencies:
@@ -25,53 +25,40 @@ dependencies:
  - xz=5.4.2=h5eee18b_0
  - zlib=1.2.13=h5eee18b_0
  - pip:
+      - --pre
+      - --extra-index-url https://download.pytorch.org/whl/nightly/
+      - accelerate>=0.11.0
      - certifi==2023.7.22
      - charset-normalizer==3.3.0
-      - click==8.1.7
+      - compel==2.0.2
+      - diffusers==0.24.0
      - filelock==3.12.4
      - fsspec==2023.9.2
      - grpcio==1.59.0
-      - huggingface-hub==0.17.3
+      - huggingface-hub>=0.19.4
      - idna==3.4
-      - install==1.3.5
+      - importlib-metadata==6.8.0
      - jinja2==3.1.2
-      - joblib==1.3.2
      - markupsafe==2.1.3
      - mpmath==1.3.0
      - networkx==3.1
-      - nltk==3.8.1
      - numpy==1.26.0
-      - nvidia-cublas-cu12==12.1.3.1
-      - nvidia-cuda-cupti-cu12==12.1.105
-      - nvidia-cuda-nvrtc-cu12==12.1.105
-      - nvidia-cuda-runtime-cu12==12.1.105
-      - nvidia-cudnn-cu12==8.9.2.26
-      - nvidia-cufft-cu12==11.0.2.54
-      - nvidia-curand-cu12==10.3.2.106
-      - nvidia-cusolver-cu12==11.4.5.107
-      - nvidia-cusparse-cu12==12.1.0.106
-      - nvidia-nccl-cu12==2.18.1
-      - nvidia-nvjitlink-cu12==12.2.140
-      - nvidia-nvtx-cu12==12.1.105
+      - omegaconf
      - packaging==23.2
      - pillow==10.0.1
      - protobuf==4.24.4
+      - psutil==5.9.5
+      - pyparsing==3.1.1
      - pyyaml==6.0.1
      - regex==2023.10.3
      - requests==2.31.0
      - safetensors==0.4.0
-      - scikit-learn==1.3.1
-      - scipy==1.11.3
-      - sentence-transformers==2.2.2
-      - sentencepiece==0.1.99
      - sympy==1.12
-      - threadpoolctl==3.2.0
-      - tokenizers==0.14.1
-      - torch==2.1.0
-      - torchvision==0.16.0
      - tqdm==4.66.1
-      - transformers==4.34.0
+      - transformers>=4.25.1
      - triton==2.1.0
      - typing-extensions==4.8.0
      - urllib3==2.0.6
-prefix: /opt/conda/envs/transformers
+      - zipp==3.17.0
+      - torch
+prefix: /opt/conda/envs/diffusers
--- a/backend/python/diffusers/diffusers.yml
+++ b/backend/python/diffusers/diffusers.yml
@@ -53,6 +53,7 @@ dependencies:
      - nvidia-nccl-cu12==2.18.1
      - nvidia-nvjitlink-cu12==12.2.140
      - nvidia-nvtx-cu12==12.1.105
+      - omegaconf
      - packaging==23.2
      - pillow==10.0.1
      - protobuf==4.24.4
--- a/backend/python/diffusers/install.sh
+++ b/backend/python/diffusers/install.sh
@@ -0,0 +1,24 @@
+#!/bin/bash
+set -ex
+
+# Check if environment exist
+conda_env_exists(){
+    ! conda list --name "${@}" >/dev/null 2>/dev/null
+}
+
+if conda_env_exists "diffusers" ; then
+    echo "Creating virtual environment..."
+    conda env create --name diffusers --file $1
+    echo "Virtual environment created."
+else 
+    echo "Virtual environment already exists."
+fi
+
+if [ "$PIP_CACHE_PURGE" = true ] ; then
+    export PATH=$PATH:/opt/conda/bin
+
+    # Activate conda environment
+    source activate diffusers
+
+    pip cache purge
+fi
--- a/backend/python/exllama/Makefile
+++ b/backend/python/exllama/Makefile
@@ -1,8 +1,6 @@
 .PHONY: exllama
 exllama:
-	@echo "Creating virtual environment..."
-	@conda env create --name exllama --file exllama.yml
-	@echo "Virtual environment created."
+	$(MAKE) -C ../common-env/transformers
 	bash install.sh

 .PHONY: run
--- a/backend/python/exllama/backend_pb2.py
+++ b/backend/python/exllama/backend_pb2.py
--- a/backend/python/exllama/install.sh
+++ b/backend/python/exllama/install.sh
@@ -5,11 +5,15 @@
 export PATH=$PATH:/opt/conda/bin

 # Activate conda environment
-source activate exllama
+source activate transformers

 echo $CONDA_PREFIX


 git clone https://github.com/turboderp/exllama $CONDA_PREFIX/exllama && pushd $CONDA_PREFIX/exllama && pip install -r requirements.txt && popd

-cp -rfv $CONDA_PREFIX/exllama/* ./
+cp -rfv $CONDA_PREFIX/exllama/* ./
+
+if [ "$PIP_CACHE_PURGE" = true ] ; then
+    pip cache purge
+fi
--- a/backend/python/exllama/run.sh
+++ b/backend/python/exllama/run.sh
@@ -6,9 +6,11 @@
 export PATH=$PATH:/opt/conda/bin

 # Activate conda environment
-source activate exllama
+source activate transformers

 # get the directory where the bash script is located
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"

+cd $DIR
+
 python $DIR/exllama.py $@
--- a/backend/python/exllama2/Makefile
+++ b/backend/python/exllama2/Makefile
@@ -1,8 +1,6 @@
 .PHONY: exllama2
 exllama2:
-	@echo "Creating virtual environment..."
-	@conda env create --name exllama2 --file exllama2.yml
-	@echo "Virtual environment created."
+	$(MAKE) -C ../common-env/transformers
 	bash install.sh

 .PHONY: run
--- a/backend/python/exllama2/backend_pb2.py
+++ b/backend/python/exllama2/backend_pb2.py
--- a/backend/python/exllama2/exllama2_backend.py
+++ b/backend/python/exllama2/exllama2_backend.py
@@ -7,7 +7,8 @@ import backend_pb2_grpc
 import argparse
 import signal
 import sys
-import os, glob
+import os
+import glob

 from pathlib import Path
 import torch
@@ -21,7 +22,7 @@ from exllamav2.generator import (
 )


-from exllamav2 import(
+from exllamav2 import (
    ExLlamaV2,
    ExLlamaV2Config,
    ExLlamaV2Cache,
@@ -40,6 +41,7 @@ MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
 class BackendServicer(backend_pb2_grpc.BackendServicer):
    def Health(self, request, context):
        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
+
    def LoadModel(self, request, context):
        try:
            model_directory = request.ModelFile
@@ -50,7 +52,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):

            model = ExLlamaV2(config)

-            cache = ExLlamaV2Cache(model, lazy = True)
+            cache = ExLlamaV2Cache(model, lazy=True)
            model.load_autosplit(cache)

            tokenizer = ExLlamaV2Tokenizer(config)
@@ -59,7 +61,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):

            generator = ExLlamaV2BaseGenerator(model, cache, tokenizer)

-            self.generator= generator
+            self.generator = generator

            generator.warmup()
            self.model = model
@@ -85,17 +87,18 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):

        if request.Tokens != 0:
            tokens = request.Tokens
-        output = self.generator.generate_simple(request.Prompt, settings, tokens, seed = self.seed)
+        output = self.generator.generate_simple(
+            request.Prompt, settings, tokens)

        # Remove prompt from response if present
        if request.Prompt in output:
            output = output.replace(request.Prompt, "")

-        return backend_pb2.Result(message=bytes(t, encoding='utf-8'))
+        return backend_pb2.Result(message=bytes(output, encoding='utf-8'))

    def PredictStream(self, request, context):
        # Implement PredictStream RPC
-        #for reply in some_data_generator():
+        # for reply in some_data_generator():
        #    yield reply
        # Not implemented yet
        return self.Predict(request, context)
@@ -124,6 +127,7 @@ def serve(address):
    except KeyboardInterrupt:
        server.stop(0)

+
 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Run the gRPC server.")
    parser.add_argument(
@@ -131,4 +135,4 @@ if __name__ == "__main__":
    )
    args = parser.parse_args()

-    serve(args.addr)
+    serve(args.addr)
--- a/backend/python/exllama2/install.sh
+++ b/backend/python/exllama2/install.sh
@@ -1,14 +1,28 @@
 #!/bin/bash
-
+set -e
 ##
 ## A bash script installs the required dependencies of VALL-E-X and prepares the environment
 export PATH=$PATH:/opt/conda/bin
+export SHA=c0ddebaaaf8ffd1b3529c2bb654e650bce2f790f

 # Activate conda environment
-source activate exllama2
+source activate transformers

 echo $CONDA_PREFIX

-git clone https://github.com/turboderp/exllamav2 $CONDA_PREFIX/exllamav2 && pushd $CONDA_PREFIX/exllamav2 && pip install -r requirements.txt && popd
+git clone https://github.com/turboderp/exllamav2 $CONDA_PREFIX/exllamav2

-cp -rfv $CONDA_PREFIX/exllamav2/* ./  
+pushd $CONDA_PREFIX/exllamav2
+
+git checkout -b build $SHA
+
+# TODO: this needs to be pinned within the conda environments
+pip install -r requirements.txt
+
+popd
+
+cp -rfv $CONDA_PREFIX/exllamav2/* ./  
+
+if [ "$PIP_CACHE_PURGE" = true ] ; then
+    pip cache purge
+fi
--- a/backend/python/exllama2/run.sh
+++ b/backend/python/exllama2/run.sh
@@ -6,9 +6,11 @@
 export PATH=$PATH:/opt/conda/bin

 # Activate conda environment
-source activate exllama2
+source activate transformers

 # get the directory where the bash script is located
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"

+cd $DIR
+
 python $DIR/exllama2_backend.py $@
--- a/backend/python/mamba/Makefile
+++ b/backend/python/mamba/Makefile
@@ -0,0 +1,16 @@
+.PHONY: mamba
+mamba:
+	$(MAKE) -C ../common-env/transformers
+	bash install.sh
+
+.PHONY: run
+run:
+	@echo "Running mamba..."
+	bash run.sh
+	@echo "mamba run."
+
+.PHONY: test
+test:
+	@echo "Testing mamba..."
+	bash test.sh
+	@echo "mamba tested."
--- a/backend/python/mamba/README.md
+++ b/backend/python/mamba/README.md
@@ -0,0 +1,5 @@
+# Creating a separate environment for the mamba project
+
+```
+make mamba
+```
--- a/backend/python/mamba/backend_mamba.py
+++ b/backend/python/mamba/backend_mamba.py
@@ -0,0 +1,179 @@
+#!/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)
--- a/backend/python/mamba/backend_pb2.py
+++ b/backend/python/mamba/backend_pb2.py
--- a/backend/python/mamba/backend_pb2_grpc.py
+++ b/backend/python/mamba/backend_pb2_grpc.py
@@ -0,0 +1,363 @@
+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+import grpc
+
+import backend_pb2 as backend__pb2
+
+
+class BackendStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.Health = channel.unary_unary(
+                '/backend.Backend/Health',
+                request_serializer=backend__pb2.HealthMessage.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.Predict = channel.unary_unary(
+                '/backend.Backend/Predict',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.LoadModel = channel.unary_unary(
+                '/backend.Backend/LoadModel',
+                request_serializer=backend__pb2.ModelOptions.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.PredictStream = channel.unary_stream(
+                '/backend.Backend/PredictStream',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.Embedding = channel.unary_unary(
+                '/backend.Backend/Embedding',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.EmbeddingResult.FromString,
+                )
+        self.GenerateImage = channel.unary_unary(
+                '/backend.Backend/GenerateImage',
+                request_serializer=backend__pb2.GenerateImageRequest.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.AudioTranscription = channel.unary_unary(
+                '/backend.Backend/AudioTranscription',
+                request_serializer=backend__pb2.TranscriptRequest.SerializeToString,
+                response_deserializer=backend__pb2.TranscriptResult.FromString,
+                )
+        self.TTS = channel.unary_unary(
+                '/backend.Backend/TTS',
+                request_serializer=backend__pb2.TTSRequest.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.TokenizeString = channel.unary_unary(
+                '/backend.Backend/TokenizeString',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.TokenizationResponse.FromString,
+                )
+        self.Status = channel.unary_unary(
+                '/backend.Backend/Status',
+                request_serializer=backend__pb2.HealthMessage.SerializeToString,
+                response_deserializer=backend__pb2.StatusResponse.FromString,
+                )
+
+
+class BackendServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def Health(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Predict(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def LoadModel(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def PredictStream(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Embedding(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def GenerateImage(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def AudioTranscription(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def TTS(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def TokenizeString(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Status(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_BackendServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'Health': grpc.unary_unary_rpc_method_handler(
+                    servicer.Health,
+                    request_deserializer=backend__pb2.HealthMessage.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'Predict': grpc.unary_unary_rpc_method_handler(
+                    servicer.Predict,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'LoadModel': grpc.unary_unary_rpc_method_handler(
+                    servicer.LoadModel,
+                    request_deserializer=backend__pb2.ModelOptions.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'PredictStream': grpc.unary_stream_rpc_method_handler(
+                    servicer.PredictStream,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'Embedding': grpc.unary_unary_rpc_method_handler(
+                    servicer.Embedding,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.EmbeddingResult.SerializeToString,
+            ),
+            'GenerateImage': grpc.unary_unary_rpc_method_handler(
+                    servicer.GenerateImage,
+                    request_deserializer=backend__pb2.GenerateImageRequest.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'AudioTranscription': grpc.unary_unary_rpc_method_handler(
+                    servicer.AudioTranscription,
+                    request_deserializer=backend__pb2.TranscriptRequest.FromString,
+                    response_serializer=backend__pb2.TranscriptResult.SerializeToString,
+            ),
+            'TTS': grpc.unary_unary_rpc_method_handler(
+                    servicer.TTS,
+                    request_deserializer=backend__pb2.TTSRequest.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'TokenizeString': grpc.unary_unary_rpc_method_handler(
+                    servicer.TokenizeString,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.TokenizationResponse.SerializeToString,
+            ),
+            'Status': grpc.unary_unary_rpc_method_handler(
+                    servicer.Status,
+                    request_deserializer=backend__pb2.HealthMessage.FromString,
+                    response_serializer=backend__pb2.StatusResponse.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'backend.Backend', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+
+
+ # This class is part of an EXPERIMENTAL API.
+class Backend(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def Health(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Health',
+            backend__pb2.HealthMessage.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Predict(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Predict',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def LoadModel(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/LoadModel',
+            backend__pb2.ModelOptions.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def PredictStream(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(request, target, '/backend.Backend/PredictStream',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Embedding(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Embedding',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.EmbeddingResult.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def GenerateImage(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/GenerateImage',
+            backend__pb2.GenerateImageRequest.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def AudioTranscription(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/AudioTranscription',
+            backend__pb2.TranscriptRequest.SerializeToString,
+            backend__pb2.TranscriptResult.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def TTS(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/TTS',
+            backend__pb2.TTSRequest.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def TokenizeString(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/TokenizeString',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.TokenizationResponse.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Status(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Status',
+            backend__pb2.HealthMessage.SerializeToString,
+            backend__pb2.StatusResponse.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
--- a/Show More
+++ b/Show More