fix(deps): update module github.com/onsi/gomega to v1.29.0

* Fix backend/cpp/llama CMakeList.txt on OSX - detect OSX and use homebrew libraries

* sneak a logging fix in too for gallery debugging

* additional logging

.env

@@ -23,6 +23,12 @@ MODELS_PATH=/models
 ## Enable debug mode
 # DEBUG=true
 
+## Disables COMPEL (Diffusers)
+# COMPEL=0
+
+## Enable/Disable single backend (useful if only one GPU is available)
+# SINGLE_ACTIVE_BACKEND=true
+
 ## Specify a build type. Available: cublas, openblas, clblas.
 ## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
 ## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
@@ -44,3 +50,20 @@ MODELS_PATH=/models
 
 ## Specify a default upload limit in MB (whisper)
 # UPLOAD_LIMIT
+
+## List of external GRPC backends (note on the container image this variable is already set to use extra backends available in extra/)
+# EXTERNAL_GRPC_BACKENDS=my-backend:127.0.0.1:9000,my-backend2:/usr/bin/backend.py
+
+### Advanced settings ###
+### Those are not really used by LocalAI, but from components in the stack ###
+##
+### Preload libraries
+# LD_PRELOAD=
+
+### Huggingface cache for models
+# HUGGINGFACE_HUB_CACHE=/usr/local/huggingface
+
+### Python backends GRPC max workers
+### Default number of workers for GRPC Python backends.
+### This actually controls wether a backend can process multiple requests or not.
+# PYTHON_GRPC_MAX_WORKERS=1

.github/PULL_REQUEST_TEMPLATE.md

@@ -8,16 +8,24 @@ This PR fixes #
 **[Signed commits](../CONTRIBUTING.md#signing-off-on-commits-developer-certificate-of-origin)**
 - [ ] Yes, I signed my commits.
  
-
 <!--
 Thank you for contributing to LocalAI! 
 
-Contributing Conventions:
+Contributing Conventions
+-------------------------
 
-1. Include descriptive PR titles with [<component-name>] prepended.
-2. Build and test your changes before submitting a PR. 
+The draft above helps to give a quick overview of your PR.
+
+Remember to remove this comment and to at least:
+
+1. Include descriptive PR titles with [<component-name>] prepended. We use [conventional commits](https://www.conventionalcommits.org/en/v1.0.0/).
+2. Build and test your changes before submitting a PR (`make build`). 
 3. Sign your commits
+4. **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below).
+5. **X/Twitter handle:** we announce bigger features on X/Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out!
 
 By following the community's contribution conventions upfront, the review process will 
 be accelerated and your PR merged more quickly.
+
+If no one reviews your PR within a few days, please @-mention @mudler.
 -->

.github/workflows/bump_deps.yaml

@@ -12,6 +12,9 @@ jobs:
           - repository: "go-skynet/go-llama.cpp"
             variable: "GOLLAMA_VERSION"
             branch: "master"
+          - repository: "ggerganov/llama.cpp"
+            variable: "CPPLLAMA_VERSION"
+            branch: "master"
           - repository: "go-skynet/go-ggml-transformers.cpp"
             variable: "GOGGMLTRANSFORMERS_VERSION"
             branch: "master"
@@ -41,7 +44,7 @@ jobs:
             branch: "master"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Bump dependencies 🔧
         run: |
           bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}

.github/workflows/image.yml

@@ -19,7 +19,8 @@ jobs:
       matrix:
         include:
           - build-type: ''
-            platforms: 'linux/amd64,linux/arm64'
+            #platforms: 'linux/amd64,linux/arm64'
+            platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: ''
             ffmpeg: ''
@@ -38,7 +39,7 @@ jobs:
             tag-suffix: '-cublas-cuda12'
             ffmpeg: ''
           - build-type: ''
-            platforms: 'linux/amd64,linux/arm64'
+            platforms: 'linux/amd64'
             tag-latest: 'false'
             tag-suffix: '-ffmpeg'
             ffmpeg: 'true'
@@ -82,6 +83,10 @@ jobs:
           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
@@ -92,11 +97,11 @@ jobs:
           sudo rm -rfv build || true
           df -h
       - name: Checkout
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Docker meta
         id: meta
-        uses: docker/metadata-action@v4
+        uses: docker/metadata-action@v5
         with:
           images: quay.io/go-skynet/local-ai
           tags: |
@@ -118,14 +123,14 @@ jobs:
 
       - name: Login to DockerHub
         if: github.event_name != 'pull_request'
-        uses: docker/login-action@v2
+        uses: docker/login-action@v3
         with:
           registry: quay.io
           username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
           password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
 
       - name: Build and push
-        uses: docker/build-push-action@v4
+        uses: docker/build-push-action@v5
         with:
           builder: ${{ steps.buildx.outputs.name }}
           build-args: |

.github/workflows/release.yaml

@@ -19,13 +19,22 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           submodules: true
+      - uses: actions/setup-go@v4
+        with:
+          go-version: '>=1.21.0'
       - name: Dependencies
         run: |
           sudo apt-get update
           sudo apt-get install build-essential ffmpeg
+
+          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
+
       - name: Build
         id: build
         env:
@@ -57,15 +66,26 @@ jobs:
     runs-on: macOS-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           submodules: true
+      - uses: actions/setup-go@v4
+        with:
+          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
       - name: Build
         id: build
         env:
           CMAKE_ARGS: "${{ matrix.defines }}"
           BUILD_ID: "${{ matrix.build }}"
         run: |
+          export C_INCLUDE_PATH=/usr/local/include
+          export CPLUS_INCLUDE_PATH=/usr/local/include
           make dist
       - uses: actions/upload-artifact@v3
         with:

.github/workflows/test-gpu.yml

@@ -0,0 +1,60 @@
+---
+name: 'GPU tests'
+
+on:
+  pull_request:
+  push:
+    branches:
+      - master
+    tags:
+      - '*'
+
+concurrency:
+  group: ci-gpu-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
+jobs:
+  ubuntu-latest:
+    runs-on: self-hosted
+    strategy:
+      matrix:
+        go-version: ['1.21.x']
+    steps:
+      - name: Clone
+        uses: actions/checkout@v4
+        with: 
+          submodules: true
+      - name: Setup Go ${{ matrix.go-version }}
+        uses: actions/setup-go@v4
+        with:
+          go-version: ${{ matrix.go-version }}
+      # You can test your matrix by printing the current Go version
+      - name: Display Go version
+        run: go version
+      - name: Dependencies
+        run: |
+          sudo apt-get update
+          sudo DEBIAN_FRONTEND=noninteractive apt-get install -y make wget
+      - name: Build
+        run: |
+          if [ ! -e /run/systemd/system ]; then
+            sudo mkdir /run/systemd/system
+          fi
+          make \
+            TEST_DIR="/host/tests/${{ github.head_ref || github.ref }}" \
+            BUILD_TYPE=cublas \
+            prepare-e2e run-e2e-image test-e2e
+      - name: Release space from worker ♻
+        if: always()
+        run: |
+          sudo rm -rf build || true
+          sudo rm -rf bin || true
+          sudo rm -rf dist || true
+          sudo docker logs $(sudo docker ps -q --filter ancestor=localai-tests) > logs.txt
+          sudo cat logs.txt || true
+          sudo rm -rf logs.txt
+          make clean || true
+          make \
+            TEST_DIR="/host/tests/${{ github.head_ref || github.ref }}" \
+            teardown-e2e || true
+          docker system prune -f -a --volumes || true

.github/workflows/test.yml

@@ -16,21 +16,66 @@ concurrency:
 jobs:
   ubuntu-latest:
     runs-on: ubuntu-latest
-
+    strategy:
+      matrix:
+        go-version: ['1.21.x']
     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 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: Clone
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with: 
           submodules: true
+      - name: Setup Go ${{ matrix.go-version }}
+        uses: actions/setup-go@v4
+        with:
+          go-version: ${{ matrix.go-version }}
+      # You can test your matrix by printing the current Go version
+      - name: Display Go version
+        run: go version
       - name: Dependencies
         run: |
           sudo apt-get update
           sudo apt-get install build-essential ffmpeg
-          
+
           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 pip install -r extra/requirements.txt
 
+
+          # Pre-build stable diffusion before we install a newever version of abseil (not compatible with stablediffusion-ncn)
+          GO_TAGS="tts stablediffusion" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
+
           sudo mkdir /build && sudo chmod -R 777 /build && cd /build && \
           curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v1.11.0.tar.gz" | \
           tar -xzvf - && \
@@ -46,19 +91,41 @@ jobs:
           sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
           sudo ln -s /usr/lib/libpiper_phonemize.so /usr/lib/libpiper_phonemize.so.1 && \
           sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
+
+          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
+
       - name: Test
         run: |
           ESPEAK_DATA="/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data" GO_TAGS="tts stablediffusion" make test
 
   macOS-latest:
     runs-on: macOS-latest
-
+    strategy:
+      matrix:
+        go-version: ['1.21.x']
     steps:
       - name: Clone
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with: 
           submodules: true
-
+      - name: Setup Go ${{ matrix.go-version }}
+        uses: actions/setup-go@v4
+        with:
+          go-version: ${{ matrix.go-version }}
+      # You can test your matrix by printing the current Go version
+      - name: Display Go version
+        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
       - name: Test
         run: |
+          export C_INCLUDE_PATH=/usr/local/include
+          export CPLUS_INCLUDE_PATH=/usr/local/include
           CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" make test

.gitignore

@@ -1,5 +1,6 @@
 # go-llama build artifacts
 go-llama
+go-llama-stable
 /gpt4all
 go-stable-diffusion
 go-piper
@@ -22,6 +23,8 @@ LocalAI
 local-ai
 # prevent above rules from omitting the helm chart
 !charts/*
+# prevent above rules from omitting the api/localai folder
+!api/localai
 
 # Ignore models
 models/*

CONTRIBUTING.md

@@ -0,0 +1,72 @@
+# Contributing to localAI
+
+Thank you for your interest in contributing to LocalAI! We appreciate your time and effort in helping to improve our project. Before you get started, please take a moment to review these guidelines.
+
+## Table of Contents
+
+- [Getting Started](#getting-started)
+  - [Prerequisites](#prerequisites)
+  - [Setting up the Development Environment](#setting-up-the-development-environment)
+- [Contributing](#contributing)
+  - [Submitting an Issue](#submitting-an-issue)
+  - [Creating a Pull Request (PR)](#creating-a-pull-request-pr)
+- [Coding Guidelines](#coding-guidelines)
+- [Testing](#testing)
+- [Documentation](#documentation)
+- [Community and Communication](#community-and-communication)
+
+
+
+## Getting Started
+
+### Prerequisites
+
+- Golang [1.21]
+- Git
+- macOS/Linux
+
+### Setting up the Development Environment and running localAI in the local environment
+
+1. Clone the repository: `git clone https://github.com/go-skynet/LocalAI.git`
+2. Navigate to the project directory: `cd LocalAI`
+3. Install the required dependencies: `make prepare`
+4. Run LocalAI: `make run`
+
+## Contributing
+
+We welcome contributions from everyone! To get started, follow these steps:
+
+### Submitting an Issue
+
+If you find a bug, have a feature request, or encounter any issues, please check the [issue tracker](https://github.com/go-skynet/LocalAI/issues) to see if a similar issue has already been reported. If not, feel free to [create a new issue](https://github.com/go-skynet/LocalAI/issues/new) and provide as much detail as possible.
+
+### Creating a Pull Request (PR)
+
+1. Fork the repository.
+2. Create a new branch with a descriptive name: `git checkout -b [branch name]`
+3. Make your changes and commit them.
+4. Push the changes to your fork: `git push origin [branch name]`
+5. Create a new pull request from your branch to the main project's `main` or `master` branch.
+6. Provide a clear description of your changes in the pull request.
+7. Make any requested changes during the review process.
+8. Once your PR is approved, it will be merged into the main project.
+
+## Coding Guidelines
+
+- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like []`golangci-lint`](https://golangci-lint.run) can help you here.
+
+## Testing
+
+`make test` cannot handle all the model now. Please be sure to add a test case for the new features or the part was changed.
+
+## Documentation
+
+- We are welcome the contribution of the documents, please open new PR in the official document repo [localai-website](https://github.com/go-skynet/localai-website)
+
+## Community and Communication
+
+- You can reach out via the Github issue tracker.
+- Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
+- Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
+
+---

Dockerfile

@@ -1,6 +1,9 @@
-ARG GO_VERSION=1.20-bullseye
+ARG GO_VERSION=1.21-bullseye
+ARG IMAGE_TYPE=extras
+# extras or core
 
-FROM golang:$GO_VERSION as requirements
+
+FROM golang:$GO_VERSION as requirements-core
 
 ARG BUILD_TYPE
 ARG CUDA_MAJOR_VERSION=11
@@ -11,12 +14,13 @@ ARG TARGETARCH
 ARG TARGETVARIANT
 
 ENV BUILD_TYPE=${BUILD_TYPE}
-ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py,autogptq:/build/extra/grpc/autogptq/autogptq.py,bark:/build/extra/grpc/bark/ttsbark.py,diffusers:/build/extra/grpc/diffusers/backend_diffusers.py,exllama:/build/extra/grpc/exllama/exllama.py"
+ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py,autogptq:/build/extra/grpc/autogptq/autogptq.py,bark:/build/extra/grpc/bark/ttsbark.py,diffusers:/build/extra/grpc/diffusers/backend_diffusers.py,exllama:/build/extra/grpc/exllama/exllama.py,vall-e-x:/build/extra/grpc/vall-e-x/ttsvalle.py,vllm:/build/extra/grpc/vllm/backend_vllm.py"
 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"
 
 RUN apt-get update && \
-    apt-get install -y ca-certificates cmake curl patch pip
+    apt-get install -y ca-certificates curl patch pip cmake && apt-get clean
+
 
 # Use the variables in subsequent instructions
 RUN echo "Target Architecture: $TARGETARCH"
@@ -30,33 +34,21 @@ RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
     dpkg -i cuda-keyring_1.0-1_all.deb && \
     rm -f cuda-keyring_1.0-1_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 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 \
     ; fi
 ENV PATH /usr/local/cuda/bin:${PATH}
 
-# Extras requirements
-COPY extra/requirements.txt /build/extra/requirements.txt
-ENV PATH="/root/.cargo/bin:${PATH}"
-RUN pip install --upgrade pip
-RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
-RUN if [ "${TARGETARCH}" = "amd64" ]; then \
-        pip install git+https://github.com/suno-ai/bark.git diffusers invisible_watermark transformers accelerate safetensors;\
-    fi
-RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "amd64" ]; then \
-        pip install torch && pip install auto-gptq https://github.com/jllllll/exllama/releases/download/0.0.10/exllama-0.0.10+cu${CUDA_MAJOR_VERSION}${CUDA_MINOR_VERSION}-cp39-cp39-linux_x86_64.whl;\
-    fi
-RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt
+# OpenBLAS requirements and stable diffusion
+RUN apt-get install -y \
+    libopenblas-dev \
+    libopencv-dev \ 
+    && apt-get clean
+
+# Set up OpenCV
+RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
 
 WORKDIR /build
 
-# OpenBLAS requirements
-RUN apt-get install -y libopenblas-dev
-
-# Stable Diffusion requirements
-RUN apt-get install -y libopencv-dev && \
-    ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
-
-
 # piper requirements
 # Use pre-compiled Piper phonemization library (includes onnxruntime)
 #RUN if echo "${GO_TAGS}" | grep -q "tts"; then \
@@ -76,17 +68,39 @@ RUN curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v${SPDLOG_VERSIO
     tar -C "lib/Linux-$(uname -m)/piper_phonemize" -xzvf - && ls -liah /build/lib/Linux-$(uname -m)/piper_phonemize/ && \
     cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
     ln -s /usr/lib/libpiper_phonemize.so /usr/lib/libpiper_phonemize.so.1 && \
-    cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
+    cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/ && \
+    rm spdlog-${SPDLOG_VERSION} -rf
+
+# Extras requirements
+FROM requirements-core as requirements-extras
+
+COPY extra/requirements.txt /build/extra/requirements.txt
+ENV PATH="/root/.cargo/bin:${PATH}"
+RUN pip install --upgrade pip
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
+RUN if [ "${TARGETARCH}" = "amd64" ]; then \
+        pip install git+https://github.com/suno-ai/bark.git diffusers invisible_watermark transformers accelerate safetensors;\
+    fi
+RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "amd64" ]; then \
+        pip install torch vllm && pip install auto-gptq https://github.com/jllllll/exllama/releases/download/0.0.10/exllama-0.0.10+cu${CUDA_MAJOR_VERSION}${CUDA_MINOR_VERSION}-cp39-cp39-linux_x86_64.whl;\
+    fi
+RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt
+
+# Vall-e-X
+RUN git clone https://github.com/Plachtaa/VALL-E-X.git /usr/lib/vall-e-x && cd /usr/lib/vall-e-x && pip install -r requirements.txt
+
 # \
 #    ; fi
 
 ###################################
 ###################################
 
-FROM requirements as builder
+FROM requirements-${IMAGE_TYPE} as builder
 
 ARG GO_TAGS="stablediffusion tts"
-
+ARG GRPC_BACKENDS
+ARG BUILD_GRPC=true
+ENV GRPC_BACKENDS=${GRPC_BACKENDS}
 ENV GO_TAGS=${GO_TAGS}
 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
 ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
@@ -101,12 +115,23 @@ RUN make prepare
 COPY . .
 COPY .git .
 
+# stablediffusion does not tolerate a newer version of abseil, build it first
+RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
+
+RUN if [ "${BUILD_GRPC}" = "true" ]; then \
+    git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
+    cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
+      -DgRPC_BUILD_TESTS=OFF \
+       ../.. && make -j12 install && rm -rf grpc \
+    ; fi
+
+# Rebuild with defaults backends
 RUN ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build
 
 ###################################
 ###################################
 
-FROM requirements
+FROM requirements-${IMAGE_TYPE}
 
 ARG FFMPEG
 ARG BUILD_TYPE
@@ -116,6 +141,11 @@ ENV BUILD_TYPE=${BUILD_TYPE}
 ENV REBUILD=false
 ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
 
+ARG CUDA_MAJOR_VERSION=11
+ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
+ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
+ENV NVIDIA_VISIBLE_DEVICES=all
+
 # Add FFmpeg
 RUN if [ "${FFMPEG}" = "true" ]; then \
     apt-get install -y ffmpeg \
@@ -129,11 +159,23 @@ WORKDIR /build
 # https://github.com/go-skynet/LocalAI/pull/434
 COPY . .
 RUN make prepare-sources
+
+# Copy the binary
 COPY --from=builder /build/local-ai ./
-# To resolve exllama import error
-RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH:-$(go env GOARCH)}" = "amd64" ]; then \
+
+# do not let stablediffusion rebuild (requires an older version of absl)
+COPY --from=builder /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
+
+# Copy VALLE-X as it's not a real "lib"
+RUN if [ -d /usr/lib/vall-e-x ]; then \
+    cp -rfv /usr/lib/vall-e-x/* ./ ; \ 
+    fi
+
+# we also copy exllama libs over to resolve exllama import error
+RUN if [ -d /usr/local/lib/python3.9/dist-packages/exllama ]; then \
         cp -rfv /usr/local/lib/python3.9/dist-packages/exllama extra/grpc/exllama/;\
     fi
+
 # Define the health check command
 HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
   CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1

Makefile

@@ -4,11 +4,15 @@ GOVET=$(GOCMD) vet
 BINARY_NAME=local-ai
 
 # llama.cpp versions
-GOLLAMA_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7
+GOLLAMA_VERSION?=aeba71ee842819da681ea537e78846dc75949ac0
+
+GOLLAMA_STABLE_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7
+
+CPPLLAMA_VERSION?=96981f37b1e3f450d9e63e571514217bf60f0a7f
 
 # gpt4all version
 GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
-GPT4ALL_VERSION?=0f2bb506a8ee752afc06cbb832773bf85b97eef3
+GPT4ALL_VERSION?=27a8b020c36b0df8f8b82a252d261cda47cf44b8
 
 # go-ggml-transformers version
 GOGGMLTRANSFORMERS_VERSION?=ffb09d7dd71e2cbc6c5d7d05357d230eea6f369a
@@ -36,11 +40,17 @@ STABLEDIFFUSION_VERSION?=d89260f598afb809279bc72aa0107b4292587632
 GOGGLLM_VERSION?=862477d16eefb0805261c19c9b0d053e3b2b684b
 
 export BUILD_TYPE?=
+export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
+export CMAKE_ARGS?=
 CGO_LDFLAGS?=
 CUDA_LIBPATH?=/usr/local/cuda/lib64/
 GO_TAGS?=
 BUILD_ID?=git
 
+TEST_DIR=/tmp/test
+
+RANDOM := $(shell bash -c 'echo $$RANDOM')
+
 VERSION?=$(shell git describe --always --tags || echo "dev" )
 # go tool nm ./local-ai | grep Commit
 LD_FLAGS?=
@@ -58,13 +68,19 @@ WHITE  := $(shell tput -Txterm setaf 7)
 CYAN   := $(shell tput -Txterm setaf 6)
 RESET  := $(shell tput -Txterm sgr0)
 
+# Default Docker bridge IP
+E2E_BRIDGE_IP?=172.17.0.1
+
 ifndef UNAME_S
 UNAME_S := $(shell uname -s)
 endif
 
-# workaround for rwkv.cpp
 ifeq ($(UNAME_S),Darwin)
-        CGO_LDFLAGS += -lcblas -framework Accelerate 
+	CGO_LDFLAGS += -lcblas -framework Accelerate
+ifneq ($(BUILD_TYPE),metal)
+    # explicit disable metal if on Darwin and metal is disabled
+	CMAKE_ARGS+=-DLLAMA_METAL=OFF
+endif
 endif
 
 ifeq ($(BUILD_TYPE),openblas)
@@ -76,6 +92,18 @@ ifeq ($(BUILD_TYPE),cublas)
 	export LLAMA_CUBLAS=1
 endif
 
+ifeq ($(BUILD_TYPE),hipblas)
+	ROCM_HOME ?= /opt/rocm
+	export CXX=$(ROCM_HOME)/llvm/bin/clang++
+	export CC=$(ROCM_HOME)/llvm/bin/clang
+	# Llama-stable has no hipblas support, so override it here.
+	export STABLE_BUILD_TYPE=
+	GPU_TARGETS ?= gfx900,gfx90a,gfx1030,gfx1031,gfx1100
+	AMDGPU_TARGETS ?= "$(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
+endif
+
 ifeq ($(BUILD_TYPE),metal)
 	CGO_LDFLAGS+=-framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
 	export LLAMA_METAL=1
@@ -101,6 +129,14 @@ ifeq ($(findstring tts,$(GO_TAGS)),tts)
 	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/falcon backend-assets/grpc/bloomz backend-assets/grpc/llama backend-assets/grpc/llama-cpp backend-assets/grpc/llama-stable 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 $(OPTIONAL_GRPC)
+GRPC_BACKENDS?=$(ALL_GRPC_BACKENDS) $(OPTIONAL_GRPC)
+
+# If empty, then we build all
+ifeq ($(GRPC_BACKENDS),)
+	GRPC_BACKENDS=$(ALL_GRPC_BACKENDS)
+endif
+
 .PHONY: all test build vendor
 
 all: help
@@ -192,17 +228,23 @@ go-llama:
 	git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
 	cd go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
 
+go-llama-stable:
+	git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama-stable
+	cd go-llama-stable && git checkout -b build $(GOLLAMA_STABLE_VERSION) && git submodule update --init --recursive --depth 1
+
 go-llama/libbinding.a: go-llama
 	$(MAKE) -C go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
 
-go-piper/libpiper_binding.a:
+go-llama-stable/libbinding.a: go-llama-stable
+	$(MAKE) -C go-llama-stable BUILD_TYPE=$(STABLE_BUILD_TYPE) libbinding.a
+
+go-piper/libpiper_binding.a: go-piper
 	$(MAKE) -C go-piper libpiper_binding.a example/main
 
-get-sources: go-llama go-ggllm go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
+get-sources: go-llama go-llama-stable go-ggllm go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
 	touch $@
 
 replace:
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
 	$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/gpt4all/gpt4all-bindings/golang
 	$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/go-ggml-transformers
 	$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
@@ -220,6 +262,7 @@ prepare-sources: get-sources replace
 rebuild: ## Rebuilds the project
 	$(GOCMD) clean -cache
 	$(MAKE) -C go-llama clean
+	$(MAKE) -C go-llama-stable clean
 	$(MAKE) -C gpt4all/gpt4all-bindings/golang/ clean
 	$(MAKE) -C go-ggml-transformers clean
 	$(MAKE) -C go-rwkv clean
@@ -231,7 +274,7 @@ rebuild: ## Rebuilds the project
 	$(MAKE) -C go-ggllm clean
 	$(MAKE) build
 
-prepare: prepare-sources $(OPTIONAL_TARGETS) 
+prepare: prepare-sources $(OPTIONAL_TARGETS)
 	touch $@
 
 clean: ## Remove build related file
@@ -239,6 +282,7 @@ clean: ## Remove build related file
 	rm -f prepare
 	rm -rf ./go-llama
 	rm -rf ./gpt4all
+	rm -rf ./go-llama-stable
 	rm -rf ./go-gpt2
 	rm -rf ./go-stable-diffusion
 	rm -rf ./go-ggml-transformers
@@ -251,6 +295,7 @@ clean: ## Remove build related file
 	rm -rf ./go-ggllm
 	rm -rf $(BINARY_NAME)
 	rm -rf release/
+	$(MAKE) -C backend/cpp/llama clean
 
 ## Build:
 
@@ -290,12 +335,33 @@ test: prepare test-models/testmodel grpcs
 	export GO_TAGS="tts stablediffusion"
 	$(MAKE) prepare-test
 	HUGGINGFACE_GRPC=$(abspath ./)/extra/grpc/huggingface/huggingface.py TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
-	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama" --flake-attempts 5 -v -r ./api ./pkg
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama && !llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
 	$(MAKE) test-gpt4all
 	$(MAKE) test-llama
+	$(MAKE) test-llama-gguf
 	$(MAKE) test-tts
 	$(MAKE) test-stablediffusion
 
+prepare-e2e:
+	mkdir -p $(TEST_DIR)
+	cp -rfv $(abspath ./tests/e2e-fixtures)/gpu.yaml $(TEST_DIR)/gpu.yaml
+	test -e $(TEST_DIR)/ggllm-test-model.bin || wget -q https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q2_K.gguf -O $(TEST_DIR)/ggllm-test-model.bin
+	docker build --build-arg BUILD_GRPC=true --build-arg GRPC_BACKENDS="$(GRPC_BACKENDS)" --build-arg IMAGE_TYPE=core --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg CUDA_MAJOR_VERSION=11 --build-arg CUDA_MINOR_VERSION=7 --build-arg FFMPEG=true -t localai-tests .
+
+run-e2e-image:
+	ls -liah $(abspath ./tests/e2e-fixtures)
+	docker run -p 5390:8080 -e MODELS_PATH=/models -e THREADS=1 -e DEBUG=true -d --rm -v $(TEST_DIR):/models --gpus all --name e2e-tests-$(RANDOM) localai-tests
+
+test-e2e:
+	@echo 'Running e2e tests'
+	BUILD_TYPE=$(BUILD_TYPE) \
+	LOCALAI_API=http://$(E2E_BRIDGE_IP):5390/v1 \
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts 5 -v -r ./tests/e2e
+
+teardown-e2e:
+	rm -rf $(TEST_DIR) || true
+	docker stop $$(docker ps -q --filter ancestor=localai-tests)
+
 test-gpt4all: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
 	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
@@ -304,6 +370,10 @@ test-llama: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
 	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
 
+test-llama-gguf: prepare-test
+	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
+	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
+
 test-tts: prepare-test
 	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
 	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r ./api ./pkg
@@ -340,6 +410,8 @@ protogen-python:
 	python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/exllama/ --grpc_python_out=extra/grpc/exllama/ pkg/grpc/proto/backend.proto
 	python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/bark/ --grpc_python_out=extra/grpc/bark/ pkg/grpc/proto/backend.proto
 	python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/diffusers/ --grpc_python_out=extra/grpc/diffusers/ pkg/grpc/proto/backend.proto
+	python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/vall-e-x/ --grpc_python_out=extra/grpc/vall-e-x/ pkg/grpc/proto/backend.proto
+	python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/vllm/ --grpc_python_out=extra/grpc/vllm/ pkg/grpc/proto/backend.proto
 
 ## GRPC
 
@@ -351,6 +423,7 @@ backend-assets/grpc/falcon: backend-assets/grpc go-ggllm/libggllm.a
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon ./cmd/grpc/falcon/
 
 backend-assets/grpc/llama: backend-assets/grpc go-llama/libbinding.a
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama LIBRARY_PATH=$(shell pwd)/go-llama \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./cmd/grpc/llama/
 # TODO: every binary should have its own folder instead, so can have different metal implementations
@@ -358,6 +431,21 @@ ifeq ($(BUILD_TYPE),metal)
 	cp go-llama/build/bin/ggml-metal.metal backend-assets/grpc/
 endif
 
+backend/cpp/llama/grpc-server:
+	LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama grpc-server
+
+backend-assets/grpc/llama-cpp: backend-assets/grpc backend/cpp/llama/grpc-server
+	cp -rfv backend/cpp/llama/grpc-server backend-assets/grpc/llama-cpp
+# TODO: every binary should have its own folder instead, so can have different metal implementations
+ifeq ($(BUILD_TYPE),metal)
+	cp backend/cpp/llama/llama.cpp/build/bin/ggml-metal.metal backend-assets/grpc/
+endif
+
+backend-assets/grpc/llama-stable: backend-assets/grpc go-llama-stable/libbinding.a
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama-stable
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama-stable LIBRARY_PATH=$(shell pwd)/go-llama \
+	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-stable ./cmd/grpc/llama-stable/
+
 backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all gpt4all/gpt4all-bindings/golang/libgpt4all.a
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./cmd/grpc/gpt4all/
@@ -409,9 +497,12 @@ backend-assets/grpc/bert-embeddings: backend-assets/grpc go-bert/libgobert.a
 backend-assets/grpc/langchain-huggingface: backend-assets/grpc
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./cmd/grpc/langchain-huggingface/
 
-backend-assets/grpc/stablediffusion: backend-assets/grpc go-stable-diffusion/libstablediffusion.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/go-stable-diffusion/ \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./cmd/grpc/stablediffusion/
+backend-assets/grpc/stablediffusion: backend-assets/grpc
+	if [ ! -f backend-assets/grpc/stablediffusion ]; then \
+		$(MAKE) go-stable-diffusion/libstablediffusion.a; \
+		CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/go-stable-diffusion/ \
+		$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./cmd/grpc/stablediffusion/; \
+	fi
 
 backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data go-piper/libpiper_binding.a
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/go-piper \
@@ -421,4 +512,4 @@ backend-assets/grpc/whisper: backend-assets/grpc whisper.cpp/libwhisper.a
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/whisper.cpp LIBRARY_PATH=$(shell pwd)/whisper.cpp \
 	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./cmd/grpc/whisper/
 
-grpcs: prepare backend-assets/grpc/langchain-huggingface backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/falcon backend-assets/grpc/bloomz backend-assets/grpc/llama 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)
+grpcs: prepare $(GRPC_BACKENDS)

README.md

@@ -27,7 +27,7 @@
 
 [![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 a drop-in replacement REST API that's compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format. Does not require GPU.
+**LocalAI** is a drop-in replacement REST API that's compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format, pytorch and more. Does not require GPU.
 
 <p align="center"><b>Follow LocalAI </b></p>
 
@@ -104,15 +104,30 @@ Note that this started just as a [fun weekend project](https://localai.io/#backs
 
 Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
 
-### 💡 Example: Use GPT4ALL-J model
+### 💡 Example: Use Luna-AI Llama model
 
-See the [documentation](https://localai.io/basics/getting_started/#example-use-gpt4all-j-model-with-docker-compose)
+See the [documentation](https://localai.io/basics/getting_started)
 
 ### 🔗 Resources
 
 - [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)
+  
+## Citation
+
+If you utilize this repository, data in a downstream project, please consider citing it with:
+
+```
+@misc{localai,
+  author = {Ettore Di Giacinto},
+  title = {LocalAI: The free, Open source OpenAI alternative},
+  year = {2023},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished = {\url{https://github.com/go-skynet/LocalAI}},
+```
 
 ## ❤️ Sponsors
 
@@ -127,6 +142,11 @@ A huge thank you to our generous sponsors who support this project:
 |  [Spectro Cloud](https://www.spectrocloud.com/)  |  
 |  Spectro Cloud kindly supports LocalAI by providing GPU and computing resources to run tests on lamdalabs!  |
 
+And a huge shout-out to individuals sponsoring the project by donating hardware or backing the project. 
+
+- [Sponsor list](https://github.com/sponsors/mudler)
+- JDAM00 (donating HW for the CI)
+
 ## 🌟 Star history
 
 [![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)

api/api.go

@@ -2,13 +2,16 @@ package api
 
 import (
 	"errors"
+	"fmt"
 	"strings"
 
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/localai"
 	"github.com/go-skynet/LocalAI/api/openai"
 	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/api/schema"
 	"github.com/go-skynet/LocalAI/internal"
+	"github.com/go-skynet/LocalAI/metrics"
 	"github.com/go-skynet/LocalAI/pkg/assets"
 
 	"github.com/gofiber/fiber/v2"
@@ -19,7 +22,7 @@ import (
 	"github.com/rs/zerolog/log"
 )
 
-func App(opts ...options.AppOption) (*fiber.App, error) {
+func Startup(opts ...options.AppOption) (*options.Option, *config.ConfigLoader, error) {
 	options := options.NewOptions(opts...)
 
 	zerolog.SetGlobalLevel(zerolog.InfoLevel)
@@ -27,6 +30,65 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 		zerolog.SetGlobalLevel(zerolog.DebugLevel)
 	}
 
+	log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
+	log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
+
+	cl := config.NewConfigLoader()
+	if err := cl.LoadConfigs(options.Loader.ModelPath); err != nil {
+		log.Error().Msgf("error loading config files: %s", err.Error())
+	}
+
+	if options.ConfigFile != "" {
+		if err := cl.LoadConfigFile(options.ConfigFile); err != nil {
+			log.Error().Msgf("error loading config file: %s", err.Error())
+		}
+	}
+
+	if options.Debug {
+		for _, v := range cl.ListConfigs() {
+			cfg, _ := cl.GetConfig(v)
+			log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
+		}
+	}
+
+	if options.AssetsDestination != "" {
+		// Extract files from the embedded FS
+		err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
+		log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
+		if err != nil {
+			log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
+		}
+	}
+
+	if options.PreloadJSONModels != "" {
+		if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cl, options.Galleries); err != nil {
+			return nil, nil, err
+		}
+	}
+
+	if options.PreloadModelsFromPath != "" {
+		if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cl, options.Galleries); err != nil {
+			return nil, nil, err
+		}
+	}
+
+	// turn off any process that was started by GRPC if the context is canceled
+	go func() {
+		<-options.Context.Done()
+		log.Debug().Msgf("Context canceled, shutting down")
+		options.Loader.StopAllGRPC()
+	}()
+
+	return options, cl, nil
+}
+
+func App(opts ...options.AppOption) (*fiber.App, error) {
+
+	options, cl, err := Startup(opts...)
+	if err != nil {
+		return nil, fmt.Errorf("failed basic startup tasks with error %s", err.Error())
+	}
+
 	// Return errors as JSON responses
 	app := fiber.New(fiber.Config{
 		BodyLimit:             options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
@@ -44,8 +106,8 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 
 			// Send custom error page
 			return ctx.Status(code).JSON(
-				openai.ErrorResponse{
-					Error: &openai.APIError{Message: err.Error(), Code: code},
+				schema.ErrorResponse{
+					Error: &schema.APIError{Message: err.Error(), Code: code},
 				},
 			)
 		},
@@ -57,38 +119,11 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 		}))
 	}
 
-	log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
-	log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
-
-	cm := config.NewConfigLoader()
-	if err := cm.LoadConfigs(options.Loader.ModelPath); err != nil {
-		log.Error().Msgf("error loading config files: %s", err.Error())
-	}
-
-	if options.ConfigFile != "" {
-		if err := cm.LoadConfigFile(options.ConfigFile); err != nil {
-			log.Error().Msgf("error loading config file: %s", err.Error())
-		}
-	}
-
-	if options.Debug {
-		for _, v := range cm.ListConfigs() {
-			cfg, _ := cm.GetConfig(v)
-			log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
-		}
-	}
-
-	if options.AssetsDestination != "" {
-		// Extract files from the embedded FS
-		err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
-		log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
-		if err != nil {
-			log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
-		}
-	}
-
 	// Default middleware config
 	app.Use(recover.New())
+	if options.Metrics != nil {
+		app.Use(metrics.APIMiddleware(options.Metrics))
+	}
 
 	// Auth middleware checking if API key is valid. If no API key is set, no auth is required.
 	auth := func(c *fiber.Ctx) error {
@@ -116,18 +151,6 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 		return c.Next()
 	}
 
-	if options.PreloadJSONModels != "" {
-		if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cm, options.Galleries); err != nil {
-			return nil, err
-		}
-	}
-
-	if options.PreloadModelsFromPath != "" {
-		if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cm, options.Galleries); err != nil {
-			return nil, err
-		}
-	}
-
 	if options.CORS {
 		var c func(ctx *fiber.Ctx) error
 		if options.CORSAllowOrigins == "" {
@@ -141,7 +164,7 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 
 	// LocalAI API endpoints
 	galleryService := localai.NewGalleryService(options.Loader.ModelPath)
-	galleryService.Start(options.Context, cm)
+	galleryService.Start(options.Context, cl)
 
 	app.Get("/version", auth, func(c *fiber.Ctx) error {
 		return c.JSON(struct {
@@ -149,36 +172,41 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 		}{Version: internal.PrintableVersion()})
 	})
 
-	app.Post("/models/apply", auth, localai.ApplyModelGalleryEndpoint(options.Loader.ModelPath, cm, galleryService.C, options.Galleries))
-	app.Get("/models/available", auth, localai.ListModelFromGalleryEndpoint(options.Galleries, options.Loader.ModelPath))
-	app.Get("/models/jobs/:uuid", auth, localai.GetOpStatusEndpoint(galleryService))
+	modelGalleryService := localai.CreateModelGalleryService(options.Galleries, options.Loader.ModelPath, galleryService)
+	app.Post("/models/apply", auth, modelGalleryService.ApplyModelGalleryEndpoint())
+	app.Get("/models/available", auth, modelGalleryService.ListModelFromGalleryEndpoint())
+	app.Get("/models/galleries", auth, modelGalleryService.ListModelGalleriesEndpoint())
+	app.Post("/models/galleries", auth, modelGalleryService.AddModelGalleryEndpoint())
+	app.Delete("/models/galleries", auth, modelGalleryService.RemoveModelGalleryEndpoint())
+	app.Get("/models/jobs/:uuid", auth, modelGalleryService.GetOpStatusEndpoint())
+	app.Get("/models/jobs", auth, modelGalleryService.GetAllStatusEndpoint())
 
 	// openAI compatible API endpoint
 
 	// chat
-	app.Post("/v1/chat/completions", auth, openai.ChatEndpoint(cm, options))
-	app.Post("/chat/completions", auth, openai.ChatEndpoint(cm, options))
+	app.Post("/v1/chat/completions", auth, openai.ChatEndpoint(cl, options))
+	app.Post("/chat/completions", auth, openai.ChatEndpoint(cl, options))
 
 	// edit
-	app.Post("/v1/edits", auth, openai.EditEndpoint(cm, options))
-	app.Post("/edits", auth, openai.EditEndpoint(cm, options))
+	app.Post("/v1/edits", auth, openai.EditEndpoint(cl, options))
+	app.Post("/edits", auth, openai.EditEndpoint(cl, options))
 
 	// completion
-	app.Post("/v1/completions", auth, openai.CompletionEndpoint(cm, options))
-	app.Post("/completions", auth, openai.CompletionEndpoint(cm, options))
-	app.Post("/v1/engines/:model/completions", auth, openai.CompletionEndpoint(cm, options))
+	app.Post("/v1/completions", auth, openai.CompletionEndpoint(cl, options))
+	app.Post("/completions", auth, openai.CompletionEndpoint(cl, options))
+	app.Post("/v1/engines/:model/completions", auth, openai.CompletionEndpoint(cl, options))
 
 	// embeddings
-	app.Post("/v1/embeddings", auth, openai.EmbeddingsEndpoint(cm, options))
-	app.Post("/embeddings", auth, openai.EmbeddingsEndpoint(cm, options))
-	app.Post("/v1/engines/:model/embeddings", auth, openai.EmbeddingsEndpoint(cm, options))
+	app.Post("/v1/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
+	app.Post("/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
+	app.Post("/v1/engines/:model/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
 
 	// audio
-	app.Post("/v1/audio/transcriptions", auth, openai.TranscriptEndpoint(cm, options))
-	app.Post("/tts", auth, localai.TTSEndpoint(cm, options))
+	app.Post("/v1/audio/transcriptions", auth, openai.TranscriptEndpoint(cl, options))
+	app.Post("/tts", auth, localai.TTSEndpoint(cl, options))
 
 	// images
-	app.Post("/v1/images/generations", auth, openai.ImageEndpoint(cm, options))
+	app.Post("/v1/images/generations", auth, openai.ImageEndpoint(cl, options))
 
 	if options.ImageDir != "" {
 		app.Static("/generated-images", options.ImageDir)
@@ -196,16 +224,16 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 	app.Get("/healthz", ok)
 	app.Get("/readyz", ok)
 
-	// models
-	app.Get("/v1/models", auth, openai.ListModelsEndpoint(options.Loader, cm))
-	app.Get("/models", auth, openai.ListModelsEndpoint(options.Loader, cm))
+	// Experimental Backend Statistics Module
+	backendMonitor := localai.NewBackendMonitor(cl, options) // Split out for now
+	app.Get("/backend/monitor", localai.BackendMonitorEndpoint(backendMonitor))
+	app.Post("/backend/shutdown", localai.BackendShutdownEndpoint(backendMonitor))
 
-	// turn off any process that was started by GRPC if the context is canceled
-	go func() {
-		<-options.Context.Done()
-		log.Debug().Msgf("Context canceled, shutting down")
-		options.Loader.StopGRPC()
-	}()
+	// models
+	app.Get("/v1/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
+	app.Get("/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
+
+	app.Get("/metrics", metrics.MetricsHandler())
 
 	return app, nil
 }

api/api_test.go

@@ -15,6 +15,7 @@ import (
 
 	. "github.com/go-skynet/LocalAI/api"
 	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/metrics"
 	"github.com/go-skynet/LocalAI/pkg/gallery"
 	"github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/go-skynet/LocalAI/pkg/utils"
@@ -162,8 +163,12 @@ var _ = Describe("API test", func() {
 				},
 			}
 
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
 			app, err = App(
 				append(commonOpts,
+					options.WithMetrics(metricsService),
 					options.WithContext(c),
 					options.WithGalleries(galleries),
 					options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))...)
@@ -296,7 +301,7 @@ var _ = Describe("API test", func() {
 				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
 					URL:       "github:go-skynet/model-gallery/openllama_3b.yaml",
 					Name:      "openllama_3b",
-					Overrides: map[string]interface{}{"backend": "llama", "mmap": true, "f16": true, "context_size": 128},
+					Overrides: map[string]interface{}{"backend": "llama-stable", "mmap": true, "f16": true, "context_size": 128},
 				})
 
 				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
@@ -359,6 +364,82 @@ var _ = Describe("API test", func() {
 				Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
 			})
 
+			It("runs openllama gguf", Label("llama-gguf"), func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				modelName := "codellama"
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					URL:       "github:go-skynet/model-gallery/codellama-7b-instruct.yaml",
+					Name:      modelName,
+					Overrides: map[string]interface{}{"backend": "llama", "mmap": true, "f16": true, "context_size": 128},
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					return response["processed"].(bool)
+				}, "360s", "10s").Should(Equal(true))
+
+				By("testing chat")
+				resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: modelName, Messages: []openai.ChatCompletionMessage{
+					{
+						Role:    "user",
+						Content: "How much is 2+2?",
+					},
+				}})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Choices)).To(Equal(1))
+				Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("4"), ContainSubstring("four")))
+
+				By("testing functions")
+				resp2, err := client.CreateChatCompletion(
+					context.TODO(),
+					openai.ChatCompletionRequest{
+						Model: modelName,
+						Messages: []openai.ChatCompletionMessage{
+							{
+								Role:    "user",
+								Content: "What is the weather like in San Francisco (celsius)?",
+							},
+						},
+						Functions: []openai.FunctionDefinition{
+							openai.FunctionDefinition{
+								Name:        "get_current_weather",
+								Description: "Get the current weather",
+								Parameters: jsonschema.Definition{
+									Type: jsonschema.Object,
+									Properties: map[string]jsonschema.Definition{
+										"location": {
+											Type:        jsonschema.String,
+											Description: "The city and state, e.g. San Francisco, CA",
+										},
+										"unit": {
+											Type: jsonschema.String,
+											Enum: []string{"celcius", "fahrenheit"},
+										},
+									},
+									Required: []string{"location"},
+								},
+							},
+						},
+					})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp2.Choices)).To(Equal(1))
+				Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
+				Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
+
+				var res map[string]string
+				err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(res["location"]).To(Equal("San Francisco"), fmt.Sprint(res))
+				Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
+				Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
+			})
+
 			It("runs gpt4all", Label("gpt4all"), func() {
 				if runtime.GOOS != "linux" {
 					Skip("test supported only on linux")
@@ -403,9 +484,13 @@ var _ = Describe("API test", func() {
 				},
 			}
 
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
 			app, err = App(
 				append(commonOpts,
 					options.WithContext(c),
+					options.WithMetrics(metricsService),
 					options.WithAudioDir(tmpdir),
 					options.WithImageDir(tmpdir),
 					options.WithGalleries(galleries),
@@ -507,12 +592,15 @@ var _ = Describe("API test", func() {
 			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
 			c, cancel = context.WithCancel(context.Background())
 
-			var err error
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
 			app, err = App(
 				append(commonOpts,
 					options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
 					options.WithContext(c),
 					options.WithModelLoader(modelLoader),
+					options.WithMetrics(metricsService),
 				)...)
 			Expect(err).ToNot(HaveOccurred())
 			go app.Listen("127.0.0.1:9090")
@@ -716,10 +804,13 @@ var _ = Describe("API test", func() {
 			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
 			c, cancel = context.WithCancel(context.Background())
 
-			var err error
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
 			app, err = App(
 				append(commonOpts,
 					options.WithContext(c),
+					options.WithMetrics(metricsService),
 					options.WithModelLoader(modelLoader),
 					options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
 			)

api/backend/embeddings.go

@@ -2,7 +2,6 @@ package backend
 
 import (
 	"fmt"
-	"sync"
 
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/options"
@@ -22,17 +21,13 @@ func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.
 	var inferenceModel interface{}
 	var err error
 
-	opts := []model.Option{
+	opts := modelOpts(c, o, []model.Option{
 		model.WithLoadGRPCLoadModelOpts(grpcOpts),
 		model.WithThreads(uint32(c.Threads)),
 		model.WithAssetDir(o.AssetsDestination),
 		model.WithModel(modelFile),
 		model.WithContext(o.Context),
-	}
-
-	for k, v := range o.ExternalGRPCBackends {
-		opts = append(opts, model.WithExternalBackend(k, v))
-	}
+	})
 
 	if c.Backend == "" {
 		inferenceModel, err = loader.GreedyLoader(opts...)
@@ -80,18 +75,6 @@ func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.
 	}
 
 	return func() ([]float32, error) {
-		// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-		mutexMap.Lock()
-		l, ok := mutexes[modelFile]
-		if !ok {
-			m := &sync.Mutex{}
-			mutexes[modelFile] = m
-			l = m
-		}
-		mutexMap.Unlock()
-		l.Lock()
-		defer l.Unlock()
-
 		embeds, err := fn()
 		if err != nil {
 			return embeds, err

api/backend/image.go

@@ -1,17 +1,15 @@
 package backend
 
 import (
-	"sync"
-
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/options"
 	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 )
 
-func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
+func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
 
-	opts := []model.Option{
+	opts := modelOpts(c, o, []model.Option{
 		model.WithBackendString(c.Backend),
 		model.WithAssetDir(o.AssetsDestination),
 		model.WithThreads(uint32(c.Threads)),
@@ -21,12 +19,15 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
 			CUDA:          c.Diffusers.CUDA,
 			SchedulerType: c.Diffusers.SchedulerType,
 			PipelineType:  c.Diffusers.PipelineType,
+			CFGScale:      c.Diffusers.CFGScale,
+			LoraAdapter:   c.LoraAdapter,
+			LoraBase:      c.LoraBase,
+			IMG2IMG:       c.Diffusers.IMG2IMG,
+			CLIPModel:     c.Diffusers.ClipModel,
+			CLIPSubfolder: c.Diffusers.ClipSubFolder,
+			CLIPSkip:      int32(c.Diffusers.ClipSkip),
 		}),
-	}
-
-	for k, v := range o.ExternalGRPCBackends {
-		opts = append(opts, model.WithExternalBackend(k, v))
-	}
+	})
 
 	inferenceModel, err := loader.BackendLoader(
 		opts...,
@@ -39,31 +40,20 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
 		_, err := inferenceModel.GenerateImage(
 			o.Context,
 			&proto.GenerateImageRequest{
-				Height:         int32(height),
-				Width:          int32(width),
-				Mode:           int32(mode),
-				Step:           int32(step),
-				Seed:           int32(seed),
-				PositivePrompt: positive_prompt,
-				NegativePrompt: negative_prompt,
-				Dst:            dst,
+				Height:           int32(height),
+				Width:            int32(width),
+				Mode:             int32(mode),
+				Step:             int32(step),
+				Seed:             int32(seed),
+				CLIPSkip:         int32(c.Diffusers.ClipSkip),
+				PositivePrompt:   positive_prompt,
+				NegativePrompt:   negative_prompt,
+				Dst:              dst,
+				Src:              src,
+				EnableParameters: c.Diffusers.EnableParameters,
 			})
 		return err
 	}
 
-	return func() error {
-		// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-		mutexMap.Lock()
-		l, ok := mutexes[c.Backend]
-		if !ok {
-			m := &sync.Mutex{}
-			mutexes[c.Backend] = m
-			l = m
-		}
-		mutexMap.Unlock()
-		l.Lock()
-		defer l.Unlock()
-
-		return fn()
-	}, nil
+	return fn, nil
 }

api/backend/llm.go

@@ -6,6 +6,7 @@ import (
 	"regexp"
 	"strings"
 	"sync"
+	"unicode/utf8"
 
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/options"
@@ -15,7 +16,17 @@ import (
 	"github.com/go-skynet/LocalAI/pkg/utils"
 )
 
-func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string) bool) (func() (string, error), error) {
+type LLMResponse struct {
+	Response string // should this be []byte?
+	Usage    TokenUsage
+}
+
+type TokenUsage struct {
+	Prompt     int
+	Completion int
+}
+
+func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string, TokenUsage) bool) (func() (LLMResponse, error), error) {
 	modelFile := c.Model
 
 	grpcOpts := gRPCModelOpts(c)
@@ -23,17 +34,13 @@ func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c
 	var inferenceModel *grpc.Client
 	var err error
 
-	opts := []model.Option{
+	opts := modelOpts(c, o, []model.Option{
 		model.WithLoadGRPCLoadModelOpts(grpcOpts),
 		model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
 		model.WithAssetDir(o.AssetsDestination),
 		model.WithModel(modelFile),
 		model.WithContext(o.Context),
-	}
-
-	for k, v := range o.ExternalGRPCBackends {
-		opts = append(opts, model.WithExternalBackend(k, v))
-	}
+	})
 
 	if c.Backend != "" {
 		opts = append(opts, model.WithBackendString(c.Backend))
@@ -62,40 +69,71 @@ func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c
 	}
 
 	// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
-	fn := func() (string, error) {
+	fn := func() (LLMResponse, error) {
 		opts := gRPCPredictOpts(c, loader.ModelPath)
 		opts.Prompt = s
+
+		tokenUsage := TokenUsage{}
+
+		// check the per-model feature flag for usage, since tokenCallback may have a cost.
+		// Defaults to off as for now it is still experimental
+		if c.FeatureFlag.Enabled("usage") {
+			userTokenCallback := tokenCallback
+			if userTokenCallback == nil {
+				userTokenCallback = func(token string, usage TokenUsage) bool {
+					return true
+				}
+			}
+
+			promptInfo, pErr := inferenceModel.TokenizeString(ctx, opts)
+			if pErr == nil && promptInfo.Length > 0 {
+				tokenUsage.Prompt = int(promptInfo.Length)
+			}
+
+			tokenCallback = func(token string, usage TokenUsage) bool {
+				tokenUsage.Completion++
+				return userTokenCallback(token, tokenUsage)
+			}
+		}
+
 		if tokenCallback != nil {
 			ss := ""
-			err := inferenceModel.PredictStream(ctx, opts, func(s []byte) {
-				tokenCallback(string(s))
-				ss += string(s)
+
+			var partialRune []byte
+			err := inferenceModel.PredictStream(ctx, opts, func(chars []byte) {
+				partialRune = append(partialRune, chars...)
+
+				for len(partialRune) > 0 {
+					r, size := utf8.DecodeRune(partialRune)
+					if r == utf8.RuneError {
+						// incomplete rune, wait for more bytes
+						break
+					}
+
+					tokenCallback(string(r), tokenUsage)
+					ss += string(r)
+
+					partialRune = partialRune[size:]
+				}
 			})
-			return ss, err
+			return LLMResponse{
+				Response: ss,
+				Usage:    tokenUsage,
+			}, err
 		} else {
+			// TODO: Is the chicken bit the only way to get here? is that acceptable?
 			reply, err := inferenceModel.Predict(ctx, opts)
 			if err != nil {
-				return "", err
+				return LLMResponse{}, err
 			}
-			return string(reply.Message), err
+			return LLMResponse{
+				Response: string(reply.Message),
+				Usage:    tokenUsage,
+			}, err
 		}
 	}
 
-	return func() (string, error) {
-		// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-		mutexMap.Lock()
-		l, ok := mutexes[modelFile]
-		if !ok {
-			m := &sync.Mutex{}
-			mutexes[modelFile] = m
-			l = m
-		}
-		mutexMap.Unlock()
-		l.Lock()
-		defer l.Unlock()
-
-		return fn()
-	}, nil
+	return fn, nil
 }
 
 var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)

api/backend/lock.go

@@ -1,22 +0,0 @@
-package backend
-
-import "sync"
-
-// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-var mutexMap sync.Mutex
-var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
-
-func Lock(s string) *sync.Mutex {
-	// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-	mutexMap.Lock()
-	l, ok := mutexes[s]
-	if !ok {
-		m := &sync.Mutex{}
-		mutexes[s] = m
-		l = m
-	}
-	mutexMap.Unlock()
-	l.Lock()
-
-	return l
-}

api/backend/options.go

@@ -5,21 +5,49 @@ import (
 	"path/filepath"
 
 	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	model "github.com/go-skynet/LocalAI/pkg/model"
 
 	config "github.com/go-skynet/LocalAI/api/config"
+	"github.com/go-skynet/LocalAI/api/options"
 )
 
+func modelOpts(c config.Config, o *options.Option, opts []model.Option) []model.Option {
+	if o.SingleBackend {
+		opts = append(opts, model.WithSingleActiveBackend())
+	}
+
+	if c.GRPC.Attempts != 0 {
+		opts = append(opts, model.WithGRPCAttempts(c.GRPC.Attempts))
+	}
+
+	if c.GRPC.AttemptsSleepTime != 0 {
+		opts = append(opts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
+	}
+
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
+	return opts
+}
+
 func gRPCModelOpts(c config.Config) *pb.ModelOptions {
 	b := 512
 	if c.Batch != 0 {
 		b = c.Batch
 	}
-	return &pb.ModelOptions{
-		ContextSize: int32(c.ContextSize),
-		Seed:        int32(c.Seed),
-		NBatch:      int32(b),
-		NGQA:        c.NGQA,
 
+	return &pb.ModelOptions{
+		ContextSize:   int32(c.ContextSize),
+		Seed:          int32(c.Seed),
+		NBatch:        int32(b),
+		NoMulMatQ:     c.NoMulMatQ,
+		DraftModel:    c.DraftModel,
+		AudioPath:     c.VallE.AudioPath,
+		Quantization:  c.Quantization,
+		LoraAdapter:   c.LoraAdapter,
+		LoraBase:      c.LoraBase,
+		NGQA:          c.NGQA,
 		RMSNormEps:    c.RMSNormEps,
 		F16Memory:     c.F16,
 		MLock:         c.MMlock,
@@ -38,6 +66,8 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
 		Device:           c.AutoGPTQ.Device,
 		UseTriton:        c.AutoGPTQ.Triton,
 		UseFastTokenizer: c.AutoGPTQ.UseFastTokenizer,
+		// RWKV
+		Tokenizer: c.Tokenizer,
 	}
 }
 
@@ -51,6 +81,7 @@ func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
 	return &pb.PredictOptions{
 		Temperature:         float32(c.Temperature),
 		TopP:                float32(c.TopP),
+		NDraft:              c.NDraft,
 		TopK:                int32(c.TopK),
 		Tokens:              int32(c.Maxtokens),
 		Threads:             int32(c.Threads),

api/backend/transcript.go

@@ -5,25 +5,22 @@ import (
 	"fmt"
 
 	config "github.com/go-skynet/LocalAI/api/config"
+	"github.com/go-skynet/LocalAI/api/schema"
 
 	"github.com/go-skynet/LocalAI/api/options"
 	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
-	"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 )
 
-func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*api.Result, error) {
-	opts := []model.Option{
+func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*schema.Result, error) {
+
+	opts := modelOpts(c, o, []model.Option{
 		model.WithBackendString(model.WhisperBackend),
 		model.WithModel(c.Model),
 		model.WithContext(o.Context),
 		model.WithThreads(uint32(c.Threads)),
 		model.WithAssetDir(o.AssetsDestination),
-	}
-
-	for k, v := range o.ExternalGRPCBackends {
-		opts = append(opts, model.WithExternalBackend(k, v))
-	}
+	})
 
 	whisperModel, err := o.Loader.BackendLoader(opts...)
 	if err != nil {

api/backend/tts.go

@@ -6,6 +6,7 @@ import (
 	"os"
 	"path/filepath"
 
+	api_config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/options"
 	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
 	model "github.com/go-skynet/LocalAI/pkg/model"
@@ -33,17 +34,12 @@ func ModelTTS(backend, text, modelFile string, loader *model.ModelLoader, o *opt
 	if bb == "" {
 		bb = model.PiperBackend
 	}
-	opts := []model.Option{
+	opts := modelOpts(api_config.Config{}, o, []model.Option{
 		model.WithBackendString(bb),
 		model.WithModel(modelFile),
 		model.WithContext(o.Context),
 		model.WithAssetDir(o.AssetsDestination),
-	}
-
-	for k, v := range o.ExternalGRPCBackends {
-		opts = append(opts, model.WithExternalBackend(k, v))
-	}
-
+	})
 	piperModel, err := o.Loader.BackendLoader(opts...)
 	if err != nil {
 		return "", nil, err

api/config/config.go

@@ -29,6 +29,7 @@ type Config struct {
 
 	FunctionsConfig Functions `yaml:"function"`
 
+	FeatureFlag FeatureFlag `yaml:"feature_flags"` // Feature Flag registry. We move fast, and features may break on a per model/backend basis. Registry for (usually temporary) flags that indicate aborting something early.
 	// LLM configs (GPT4ALL, Llama.cpp, ...)
 	LLMConfig `yaml:",inline"`
 
@@ -39,12 +40,40 @@ type Config struct {
 	Diffusers Diffusers `yaml:"diffusers"`
 
 	Step int `yaml:"step"`
+
+	// GRPC Options
+	GRPC GRPC `yaml:"grpc"`
+
+	// Vall-e-x
+	VallE VallE `yaml:"vall-e"`
+}
+
+type VallE struct {
+	AudioPath string `yaml:"audio_path"`
+}
+
+type FeatureFlag map[string]*bool
+
+func (ff FeatureFlag) Enabled(s string) bool {
+	v, exist := ff[s]
+	return exist && v != nil && *v
+}
+
+type GRPC struct {
+	Attempts          int `yaml:"attempts"`
+	AttemptsSleepTime int `yaml:"attempts_sleep_time"`
 }
 
 type Diffusers struct {
-	PipelineType  string `yaml:"pipeline_type"`
-	SchedulerType string `yaml:"scheduler_type"`
-	CUDA          bool   `yaml:"cuda"`
+	PipelineType     string  `yaml:"pipeline_type"`
+	SchedulerType    string  `yaml:"scheduler_type"`
+	CUDA             bool    `yaml:"cuda"`
+	EnableParameters string  `yaml:"enable_parameters"` // A list of comma separated parameters to specify
+	CFGScale         float32 `yaml:"cfg_scale"`         // Classifier-Free Guidance Scale
+	IMG2IMG          bool    `yaml:"img2img"`           // Image to Image Diffuser
+	ClipSkip         int     `yaml:"clip_skip"`         // Skip every N frames
+	ClipModel        string  `yaml:"clip_model"`        // Clip model to use
+	ClipSubFolder    string  `yaml:"clip_subfolder"`    // Subfolder to use for clip model
 }
 
 type LLMConfig struct {
@@ -69,6 +98,12 @@ type LLMConfig struct {
 	TrimSpace       []string `yaml:"trimspace"`
 	ContextSize     int      `yaml:"context_size"`
 	NUMA            bool     `yaml:"numa"`
+	LoraAdapter     string   `yaml:"lora_adapter"`
+	LoraBase        string   `yaml:"lora_base"`
+	NoMulMatQ       bool     `yaml:"no_mulmatq"`
+	DraftModel      string   `yaml:"draft_model"`
+	NDraft          int32    `yaml:"n_draft"`
+	Quantization    string   `yaml:"quantization"`
 }
 
 type AutoGPTQ struct {

api/config/prediction.go

@@ -41,4 +41,10 @@ type PredictionOptions struct {
 	NegativePromptScale float32 `json:"negative_prompt_scale" yaml:"negative_prompt_scale"`
 	// AutoGPTQ
 	UseFastTokenizer bool `json:"use_fast_tokenizer" yaml:"use_fast_tokenizer"`
+
+	// Diffusers
+	ClipSkip int `json:"clip_skip" yaml:"clip_skip"`
+
+	// RWKV (?)
+	Tokenizer string `json:"tokenizer" yaml:"tokenizer"`
 }

api/localai/backend_monitor.go

@@ -0,0 +1,163 @@
+package localai
+
+import (
+	"context"
+	"fmt"
+	"strings"
+
+	config "github.com/go-skynet/LocalAI/api/config"
+	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
+
+	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/gofiber/fiber/v2"
+	"github.com/rs/zerolog/log"
+
+	gopsutil "github.com/shirou/gopsutil/v3/process"
+)
+
+type BackendMonitorRequest struct {
+	Model string `json:"model" yaml:"model"`
+}
+
+type BackendMonitorResponse struct {
+	MemoryInfo    *gopsutil.MemoryInfoStat
+	MemoryPercent float32
+	CPUPercent    float64
+}
+
+type BackendMonitor struct {
+	configLoader *config.ConfigLoader
+	options      *options.Option // Taking options in case we need to inspect ExternalGRPCBackends, though that's out of scope for now, hence the name.
+}
+
+func NewBackendMonitor(configLoader *config.ConfigLoader, options *options.Option) BackendMonitor {
+	return BackendMonitor{
+		configLoader: configLoader,
+		options:      options,
+	}
+}
+
+func (bm *BackendMonitor) SampleLocalBackendProcess(model string) (*BackendMonitorResponse, error) {
+	config, exists := bm.configLoader.GetConfig(model)
+	var backend string
+	if exists {
+		backend = config.Model
+	} else {
+		// Last ditch effort: use it raw, see if a backend happens to match.
+		backend = model
+	}
+
+	if !strings.HasSuffix(backend, ".bin") {
+		backend = fmt.Sprintf("%s.bin", backend)
+	}
+
+	pid, err := bm.options.Loader.GetGRPCPID(backend)
+
+	if err != nil {
+		log.Error().Msgf("model %s : failed to find pid %+v", model, err)
+		return nil, err
+	}
+
+	// Name is slightly frightening but this does _not_ create a new process, rather it looks up an existing process by PID.
+	backendProcess, err := gopsutil.NewProcess(int32(pid))
+
+	if err != nil {
+		log.Error().Msgf("model %s [PID %d] : error getting process info %+v", model, pid, err)
+		return nil, err
+	}
+
+	memInfo, err := backendProcess.MemoryInfo()
+
+	if err != nil {
+		log.Error().Msgf("model %s [PID %d] : error getting memory info %+v", model, pid, err)
+		return nil, err
+	}
+
+	memPercent, err := backendProcess.MemoryPercent()
+	if err != nil {
+		log.Error().Msgf("model %s [PID %d] : error getting memory percent %+v", model, pid, err)
+		return nil, err
+	}
+
+	cpuPercent, err := backendProcess.CPUPercent()
+	if err != nil {
+		log.Error().Msgf("model %s [PID %d] : error getting cpu percent %+v", model, pid, err)
+		return nil, err
+	}
+
+	return &BackendMonitorResponse{
+		MemoryInfo:    memInfo,
+		MemoryPercent: memPercent,
+		CPUPercent:    cpuPercent,
+	}, nil
+}
+
+func (bm BackendMonitor) getModelLoaderIDFromCtx(c *fiber.Ctx) (string, error) {
+	input := new(BackendMonitorRequest)
+	// Get input data from the request body
+	if err := c.BodyParser(input); err != nil {
+		return "", err
+	}
+
+	config, exists := bm.configLoader.GetConfig(input.Model)
+	var backendId string
+	if exists {
+		backendId = config.Model
+	} else {
+		// Last ditch effort: use it raw, see if a backend happens to match.
+		backendId = input.Model
+	}
+
+	if !strings.HasSuffix(backendId, ".bin") {
+		backendId = fmt.Sprintf("%s.bin", backendId)
+	}
+
+	return backendId, nil
+}
+
+func BackendMonitorEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+
+		backendId, err := bm.getModelLoaderIDFromCtx(c)
+		if err != nil {
+			return err
+		}
+
+		client := bm.options.Loader.CheckIsLoaded(backendId)
+
+		if client == nil {
+			return fmt.Errorf("backend %s is not currently loaded", backendId)
+		}
+
+		status, rpcErr := client.Status(context.TODO())
+		if rpcErr != nil {
+			log.Warn().Msgf("backend %s experienced an error retrieving status info: %s", backendId, rpcErr.Error())
+			val, slbErr := bm.SampleLocalBackendProcess(backendId)
+			if slbErr != nil {
+				return fmt.Errorf("backend %s experienced an error retrieving status info via rpc: %s, then failed local node process sample: %s", backendId, rpcErr.Error(), slbErr.Error())
+			}
+			return c.JSON(proto.StatusResponse{
+				State: proto.StatusResponse_ERROR,
+				Memory: &proto.MemoryUsageData{
+					Total: val.MemoryInfo.VMS,
+					Breakdown: map[string]uint64{
+						"gopsutil-RSS": val.MemoryInfo.RSS,
+					},
+				},
+			})
+		}
+
+		return c.JSON(status)
+	}
+}
+
+func BackendShutdownEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		backendId, err := bm.getModelLoaderIDFromCtx(c)
+		if err != nil {
+			return err
+		}
+
+		return bm.options.Loader.ShutdownModel(backendId)
+	}
+}

api/localai/gallery.go

@@ -4,6 +4,7 @@ import (
 	"context"
 	"fmt"
 	"os"
+	"slices"
 	"strings"
 	"sync"
 
@@ -27,6 +28,7 @@ type galleryOp struct {
 }
 
 type galleryOpStatus struct {
+	FileName           string  `json:"file_name"`
 	Error              error   `json:"error"`
 	Processed          bool    `json:"processed"`
 	Message            string  `json:"message"`
@@ -50,7 +52,6 @@ func NewGalleryService(modelPath string) *galleryApplier {
 	}
 }
 
-// prepareModel applies a
 func prepareModel(modelPath string, req gallery.GalleryModel, cm *config.ConfigLoader, downloadStatus func(string, string, string, float64)) error {
 
 	config, err := gallery.GetGalleryConfigFromURL(req.URL)
@@ -76,6 +77,13 @@ func (g *galleryApplier) getStatus(s string) *galleryOpStatus {
 	return g.statuses[s]
 }
 
+func (g *galleryApplier) getAllStatus() map[string]*galleryOpStatus {
+	g.Lock()
+	defer g.Unlock()
+
+	return g.statuses
+}
+
 func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
 	go func() {
 		for {
@@ -94,7 +102,7 @@ func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
 
 				// displayDownload displays the download progress
 				progressCallback := func(fileName string, current string, total string, percentage float64) {
-					g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
+					g.updateStatus(op.id, &galleryOpStatus{Message: "processing", FileName: fileName, Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
 					utils.DisplayDownloadFunction(fileName, current, total, percentage)
 				}
 
@@ -176,18 +184,12 @@ func ApplyGalleryFromString(modelPath, s string, cm *config.ConfigLoader, galler
 	return processRequests(modelPath, s, cm, galleries, requests)
 }
 
-/// Endpoints
+/// Endpoint Service
 
-func GetOpStatusEndpoint(g *galleryApplier) func(c *fiber.Ctx) error {
-	return func(c *fiber.Ctx) error {
-
-		status := g.getStatus(c.Params("uuid"))
-		if status == nil {
-			return fmt.Errorf("could not find any status for ID")
-		}
-
-		return c.JSON(status)
-	}
+type ModelGalleryService struct {
+	galleries      []gallery.Gallery
+	modelPath      string
+	galleryApplier *galleryApplier
 }
 
 type GalleryModel struct {
@@ -195,7 +197,31 @@ type GalleryModel struct {
 	gallery.GalleryModel
 }
 
-func ApplyModelGalleryEndpoint(modelPath string, cm *config.ConfigLoader, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
+func CreateModelGalleryService(galleries []gallery.Gallery, modelPath string, galleryApplier *galleryApplier) ModelGalleryService {
+	return ModelGalleryService{
+		galleries:      galleries,
+		modelPath:      modelPath,
+		galleryApplier: galleryApplier,
+	}
+}
+
+func (mgs *ModelGalleryService) GetOpStatusEndpoint() func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		status := mgs.galleryApplier.getStatus(c.Params("uuid"))
+		if status == nil {
+			return fmt.Errorf("could not find any status for ID")
+		}
+		return c.JSON(status)
+	}
+}
+
+func (mgs *ModelGalleryService) GetAllStatusEndpoint() func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		return c.JSON(mgs.galleryApplier.getAllStatus())
+	}
+}
+
+func (mgs *ModelGalleryService) ApplyModelGalleryEndpoint() func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
 		input := new(GalleryModel)
 		// Get input data from the request body
@@ -207,11 +233,11 @@ func ApplyModelGalleryEndpoint(modelPath string, cm *config.ConfigLoader, g chan
 		if err != nil {
 			return err
 		}
-		g <- galleryOp{
+		mgs.galleryApplier.C <- galleryOp{
 			req:         input.GalleryModel,
 			id:          uuid.String(),
 			galleryName: input.ID,
-			galleries:   galleries,
+			galleries:   mgs.galleries,
 		}
 		return c.JSON(struct {
 			ID        string `json:"uuid"`
@@ -220,11 +246,11 @@ func ApplyModelGalleryEndpoint(modelPath string, cm *config.ConfigLoader, g chan
 	}
 }
 
-func ListModelFromGalleryEndpoint(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
+func (mgs *ModelGalleryService) ListModelFromGalleryEndpoint() func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
-		log.Debug().Msgf("Listing models from galleries: %+v", galleries)
+		log.Debug().Msgf("Listing models from galleries: %+v", mgs.galleries)
 
-		models, err := gallery.AvailableGalleryModels(galleries, basePath)
+		models, err := gallery.AvailableGalleryModels(mgs.galleries, mgs.modelPath)
 		if err != nil {
 			return err
 		}
@@ -239,3 +265,56 @@ func ListModelFromGalleryEndpoint(galleries []gallery.Gallery, basePath string)
 		return c.Send(dat)
 	}
 }
+
+// NOTE: This is different (and much simpler!) than above! This JUST lists the model galleries that have been loaded, not their contents!
+func (mgs *ModelGalleryService) ListModelGalleriesEndpoint() func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		log.Debug().Msgf("Listing model galleries %+v", mgs.galleries)
+		dat, err := json.Marshal(mgs.galleries)
+		if err != nil {
+			return err
+		}
+		return c.Send(dat)
+	}
+}
+
+func (mgs *ModelGalleryService) AddModelGalleryEndpoint() func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		input := new(gallery.Gallery)
+		// Get input data from the request body
+		if err := c.BodyParser(input); err != nil {
+			return err
+		}
+		if slices.ContainsFunc(mgs.galleries, func(gallery gallery.Gallery) bool {
+			return gallery.Name == input.Name
+		}) {
+			return fmt.Errorf("%s already exists", input.Name)
+		}
+		dat, err := json.Marshal(mgs.galleries)
+		if err != nil {
+			return err
+		}
+		log.Debug().Msgf("Adding %+v to gallery list", *input)
+		mgs.galleries = append(mgs.galleries, *input)
+		return c.Send(dat)
+	}
+}
+
+func (mgs *ModelGalleryService) RemoveModelGalleryEndpoint() func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		input := new(gallery.Gallery)
+		// Get input data from the request body
+		if err := c.BodyParser(input); err != nil {
+			return err
+		}
+		if !slices.ContainsFunc(mgs.galleries, func(gallery gallery.Gallery) bool {
+			return gallery.Name == input.Name
+		}) {
+			return fmt.Errorf("%s is not currently registered", input.Name)
+		}
+		mgs.galleries = slices.DeleteFunc(mgs.galleries, func(gallery gallery.Gallery) bool {
+			return gallery.Name == input.Name
+		})
+		return c.Send(nil)
+	}
+}

api/openai/chat.go

@@ -6,34 +6,48 @@ import (
 	"encoding/json"
 	"fmt"
 	"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/pkg/grammar"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/go-skynet/LocalAI/pkg/utils"
 	"github.com/gofiber/fiber/v2"
+	"github.com/google/uuid"
 	"github.com/rs/zerolog/log"
 	"github.com/valyala/fasthttp"
 )
 
 func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
 	emptyMessage := ""
+	id := uuid.New().String()
+	created := int(time.Now().Unix())
 
-	process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
-		initialMessage := OpenAIResponse{
+	process := func(s string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
+		initialMessage := schema.OpenAIResponse{
+			ID:      id,
+			Created: created,
 			Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
-			Choices: []Choice{{Delta: &Message{Role: "assistant", Content: &emptyMessage}}},
+			Choices: []schema.Choice{{Delta: &schema.Message{Role: "assistant", Content: &emptyMessage}}},
 			Object:  "chat.completion.chunk",
 		}
 		responses <- initialMessage
 
-		ComputeChoices(req, s, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
-			resp := OpenAIResponse{
+		ComputeChoices(req, s, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
+			resp := schema.OpenAIResponse{
+				ID:      id,
+				Created: created,
 				Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
-				Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
+				Choices: []schema.Choice{{Delta: &schema.Message{Content: &s}, Index: 0}},
 				Object:  "chat.completion.chunk",
+				Usage: schema.OpenAIUsage{
+					PromptTokens:     usage.Prompt,
+					CompletionTokens: usage.Completion,
+					TotalTokens:      usage.Prompt + usage.Completion,
+				},
 			}
 
 			responses <- resp
@@ -231,17 +245,19 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 		}
 
 		if toStream {
-			responses := make(chan OpenAIResponse)
+			responses := make(chan schema.OpenAIResponse)
 
 			go process(predInput, input, config, o.Loader, responses)
 
 			c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
 
+				usage := &schema.OpenAIUsage{}
+
 				for ev := range responses {
+					usage = &ev.Usage // Copy a pointer to the latest usage chunk so that the stop message can reference it
 					var buf bytes.Buffer
 					enc := json.NewEncoder(&buf)
 					enc.Encode(ev)
-
 					log.Debug().Msgf("Sending chunk: %s", buf.String())
 					_, err := fmt.Fprintf(w, "data: %v\n", buf.String())
 					if err != nil {
@@ -252,15 +268,18 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 					w.Flush()
 				}
 
-				resp := &OpenAIResponse{
-					Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
-					Choices: []Choice{
+				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",
 							Index:        0,
-							Delta:        &Message{Content: &emptyMessage},
+							Delta:        &schema.Message{Content: &emptyMessage},
 						}},
 					Object: "chat.completion.chunk",
+					Usage:  *usage,
 				}
 				respData, _ := json.Marshal(resp)
 
@@ -271,7 +290,7 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			return nil
 		}
 
-		result, err := ComputeChoices(input, predInput, config, o, o.Loader, func(s string, c *[]Choice) {
+		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{}{}
@@ -305,7 +324,7 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 								message = backend.Finetune(*config, predInput, message)
 								log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
 
-								*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
+								*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &message}})
 								return
 							}
 						}
@@ -327,28 +346,35 @@ func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 						return
 					}
 
-					prediction = backend.Finetune(*config, predInput, prediction)
-					*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
+					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, Choice{
+					*c = append(*c, schema.Choice{
 						FinishReason: "function_call",
-						Message:      &Message{Role: "assistant", FunctionCall: ss},
+						Message:      &schema.Message{Role: "assistant", FunctionCall: ss},
 					})
 				}
 
 				return
 			}
-			*c = append(*c, Choice{FinishReason: "stop", Index: 0, Message: &Message{Role: "assistant", Content: &s}})
+			*c = append(*c, schema.Choice{FinishReason: "stop", Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
 		}, nil)
 		if err != nil {
 			return err
 		}
 
-		resp := &OpenAIResponse{
+		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)

api/openai/completion.go

@@ -6,28 +6,42 @@ import (
 	"encoding/json"
 	"errors"
 	"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"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
+	"github.com/google/uuid"
 	"github.com/rs/zerolog/log"
 	"github.com/valyala/fasthttp"
 )
 
 // https://platform.openai.com/docs/api-reference/completions
 func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
-	process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
-		ComputeChoices(req, s, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
-			resp := OpenAIResponse{
-				Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
-				Choices: []Choice{
+	id := uuid.New().String()
+	created := int(time.Now().Unix())
+
+	process := func(s string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
+		ComputeChoices(req, s, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
+			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{
 					{
 						Index: 0,
 						Text:  s,
 					},
 				},
 				Object: "text_completion",
+				Usage: schema.OpenAIUsage{
+					PromptTokens:     usage.Prompt,
+					CompletionTokens: usage.Completion,
+					TotalTokens:      usage.Prompt + usage.Completion,
+				},
 			}
 			log.Debug().Msgf("Sending goroutine: %s", s)
 
@@ -84,7 +98,7 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 				log.Debug().Msgf("Template found, input modified to: %s", predInput)
 			}
 
-			responses := make(chan OpenAIResponse)
+			responses := make(chan schema.OpenAIResponse)
 
 			go process(predInput, input, config, o.Loader, responses)
 
@@ -100,9 +114,11 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 					w.Flush()
 				}
 
-				resp := &OpenAIResponse{
-					Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
-					Choices: []Choice{
+				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{
 						{
 							Index:        0,
 							FinishReason: "stop",
@@ -119,7 +135,10 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 			return nil
 		}
 
-		var result []Choice
+		var result []schema.Choice
+
+		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{
@@ -131,20 +150,31 @@ func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 				log.Debug().Msgf("Template found, input modified to: %s", i)
 			}
 
-			r, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]Choice) {
-				*c = append(*c, Choice{Text: s, FinishReason: "stop", Index: k})
-			}, nil)
+			r, tokenUsage, err := ComputeChoices(
+				input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
+					*c = append(*c, schema.Choice{Text: s, FinishReason: "stop", Index: k})
+				}, nil)
 			if err != nil {
 				return err
 			}
 
+			totalTokenUsage.Prompt += tokenUsage.Prompt
+			totalTokenUsage.Completion += tokenUsage.Completion
+
 			result = append(result, r...)
 		}
 
-		resp := &OpenAIResponse{
+		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:  "text_completion",
+			Usage: schema.OpenAIUsage{
+				PromptTokens:     totalTokenUsage.Prompt,
+				CompletionTokens: totalTokenUsage.Completion,
+				TotalTokens:      totalTokenUsage.Prompt + totalTokenUsage.Completion,
+			},
 		}
 
 		jsonResult, _ := json.Marshal(resp)

api/openai/edit.go

@@ -3,11 +3,16 @@ package openai
 import (
 	"encoding/json"
 	"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"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
+	"github.com/google/uuid"
+
 	"github.com/rs/zerolog/log"
 )
 
@@ -31,7 +36,9 @@ func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			templateFile = config.TemplateConfig.Edit
 		}
 
-		var result []Choice
+		var result []schema.Choice
+		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{
@@ -44,20 +51,32 @@ func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 				log.Debug().Msgf("Template found, input modified to: %s", i)
 			}
 
-			r, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]Choice) {
-				*c = append(*c, Choice{Text: s})
+			r, tokenUsage, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
+				*c = append(*c, schema.Choice{Text: s})
 			}, nil)
 			if err != nil {
 				return err
 			}
 
+			totalTokenUsage.Prompt += tokenUsage.Prompt
+			totalTokenUsage.Completion += tokenUsage.Completion
+
 			result = append(result, r...)
 		}
 
-		resp := &OpenAIResponse{
+		id := uuid.New().String()
+		created := int(time.Now().Unix())
+		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:  "edit",
+			Usage: schema.OpenAIUsage{
+				PromptTokens:     totalTokenUsage.Prompt,
+				CompletionTokens: totalTokenUsage.Completion,
+				TotalTokens:      totalTokenUsage.Prompt + totalTokenUsage.Completion,
+			},
 		}
 
 		jsonResult, _ := json.Marshal(resp)

api/openai/embeddings.go

@@ -3,9 +3,13 @@ package openai
 import (
 	"encoding/json"
 	"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/google/uuid"
+
 	"github.com/go-skynet/LocalAI/api/options"
 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"
@@ -25,7 +29,7 @@ func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 		}
 
 		log.Debug().Msgf("Parameter Config: %+v", config)
-		items := []Item{}
+		items := []schema.Item{}
 
 		for i, s := range config.InputToken {
 			// get the model function to call for the result
@@ -38,7 +42,7 @@ func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 			if err != nil {
 				return err
 			}
-			items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
+			items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
 		}
 
 		for i, s := range config.InputStrings {
@@ -52,13 +56,17 @@ func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 			if err != nil {
 				return err
 			}
-			items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
+			items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
 		}
 
-		resp := &OpenAIResponse{
-			Model:  input.Model, // we have to return what the user sent here, due to OpenAI spec.
-			Data:   items,
-			Object: "list",
+		id := uuid.New().String()
+		created := int(time.Now().Unix())
+		resp := &schema.OpenAIResponse{
+			ID:      id,
+			Created: created,
+			Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
+			Data:    items,
+			Object:  "list",
 		}
 
 		jsonResult, _ := json.Marshal(resp)

api/openai/image.go

@@ -1,6 +1,7 @@
 package openai
 
 import (
+	"bufio"
 	"encoding/base64"
 	"encoding/json"
 	"fmt"
@@ -8,6 +9,10 @@ import (
 	"path/filepath"
 	"strconv"
 	"strings"
+	"time"
+
+	"github.com/go-skynet/LocalAI/api/schema"
+	"github.com/google/uuid"
 
 	"github.com/go-skynet/LocalAI/api/backend"
 	config "github.com/go-skynet/LocalAI/api/config"
@@ -49,6 +54,31 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
 			return fmt.Errorf("failed reading parameters from request:%w", err)
 		}
 
+		src := ""
+		if input.File != "" {
+			//base 64 decode the file and write it somewhere
+			// that we will cleanup
+			decoded, err := base64.StdEncoding.DecodeString(input.File)
+			if err != nil {
+				return err
+			}
+			// Create a temporary file
+			outputFile, err := os.CreateTemp(o.ImageDir, "b64")
+			if err != nil {
+				return err
+			}
+			// write the base64 result
+			writer := bufio.NewWriter(outputFile)
+			_, err = writer.Write(decoded)
+			if err != nil {
+				outputFile.Close()
+				return err
+			}
+			outputFile.Close()
+			src = outputFile.Name()
+			defer os.RemoveAll(src)
+		}
+
 		log.Debug().Msgf("Parameter Config: %+v", config)
 
 		// XXX: Only stablediffusion is supported for now
@@ -73,8 +103,8 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
 		if input.ResponseFormat == "b64_json" {
 			b64JSON = true
 		}
-
-		var result []Item
+		// src and clip_skip
+		var result []schema.Item
 		for _, i := range config.PromptStrings {
 			n := input.N
 			if input.N == 0 {
@@ -121,7 +151,7 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
 
 				baseURL := c.BaseURL()
 
-				fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.Loader, *config, o)
+				fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, src, output, o.Loader, *config, o)
 				if err != nil {
 					return err
 				}
@@ -129,7 +159,7 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
 					return err
 				}
 
-				item := &Item{}
+				item := &schema.Item{}
 
 				if b64JSON {
 					defer os.RemoveAll(output)
@@ -147,8 +177,12 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
 			}
 		}
 
-		resp := &OpenAIResponse{
-			Data: result,
+		id := uuid.New().String()
+		created := int(time.Now().Unix())
+		resp := &schema.OpenAIResponse{
+			ID:      id,
+			Created: created,
+			Data:    result,
 		}
 
 		jsonResult, _ := json.Marshal(resp)

api/openai/inference.go

@@ -4,12 +4,20 @@ 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"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 )
 
-func ComputeChoices(req *OpenAIRequest, predInput string, config *config.Config, o *options.Option, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
-	n := req.N
-	result := []Choice{}
+func ComputeChoices(
+	req *schema.OpenAIRequest,
+	predInput string,
+	config *config.Config,
+	o *options.Option,
+	loader *model.ModelLoader,
+	cb func(string, *[]schema.Choice),
+	tokenCallback func(string, backend.TokenUsage) bool) ([]schema.Choice, backend.TokenUsage, error) {
+	n := req.N // number of completions to return
+	result := []schema.Choice{}
 
 	if n == 0 {
 		n = 1
@@ -18,20 +26,25 @@ func ComputeChoices(req *OpenAIRequest, predInput string, config *config.Config,
 	// get the model function to call for the result
 	predFunc, err := backend.ModelInference(req.Context, predInput, loader, *config, o, tokenCallback)
 	if err != nil {
-		return result, err
+		return result, backend.TokenUsage{}, err
 	}
 
+	tokenUsage := backend.TokenUsage{}
+
 	for i := 0; i < n; i++ {
 		prediction, err := predFunc()
 		if err != nil {
-			return result, err
+			return result, backend.TokenUsage{}, err
 		}
 
-		prediction = backend.Finetune(*config, predInput, prediction)
-		cb(prediction, &result)
+		tokenUsage.Prompt += prediction.Usage.Prompt
+		tokenUsage.Completion += prediction.Usage.Completion
+
+		finetunedResponse := backend.Finetune(*config, predInput, prediction.Response)
+		cb(finetunedResponse, &result)
 
 		//result = append(result, Choice{Text: prediction})
 
 	}
-	return result, err
+	return result, tokenUsage, err
 }

api/openai/list.go

@@ -4,6 +4,7 @@ import (
 	"regexp"
 
 	config "github.com/go-skynet/LocalAI/api/config"
+	"github.com/go-skynet/LocalAI/api/schema"
 	model "github.com/go-skynet/LocalAI/pkg/model"
 	"github.com/gofiber/fiber/v2"
 )
@@ -16,7 +17,7 @@ func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func
 		}
 		var mm map[string]interface{} = map[string]interface{}{}
 
-		dataModels := []OpenAIModel{}
+		dataModels := []schema.OpenAIModel{}
 
 		var filterFn func(name string) bool
 		filter := c.Query("filter")
@@ -45,7 +46,7 @@ func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func
 			}
 
 			if filterFn(c.Name) {
-				dataModels = append(dataModels, OpenAIModel{ID: c.Name, Object: "model"})
+				dataModels = append(dataModels, schema.OpenAIModel{ID: c.Name, Object: "model"})
 			}
 		}
 
@@ -53,13 +54,13 @@ func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func
 		for _, m := range models {
 			// And only adds them if they shouldn't be skipped.
 			if _, exists := mm[m]; !exists && filterFn(m) {
-				dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
+				dataModels = append(dataModels, schema.OpenAIModel{ID: m, Object: "model"})
 			}
 		}
 
 		return c.JSON(struct {
-			Object string        `json:"object"`
-			Data   []OpenAIModel `json:"data"`
+			Object string               `json:"object"`
+			Data   []schema.OpenAIModel `json:"data"`
 		}{
 			Object: "list",
 			Data:   dataModels,

api/openai/request.go

@@ -10,14 +10,15 @@ import (
 
 	config "github.com/go-skynet/LocalAI/api/config"
 	options "github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/api/schema"
 	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, *OpenAIRequest, error) {
+func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *schema.OpenAIRequest, error) {
 	loader := o.Loader
-	input := new(OpenAIRequest)
+	input := new(schema.OpenAIRequest)
 	ctx, cancel := context.WithCancel(o.Context)
 	input.Context = ctx
 	input.Cancel = cancel
@@ -60,7 +61,7 @@ func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *Open
 	return modelFile, input, nil
 }
 
-func updateConfig(config *config.Config, input *OpenAIRequest) {
+func updateConfig(config *config.Config, input *schema.OpenAIRequest) {
 	if input.Echo {
 		config.Echo = input.Echo
 	}
@@ -75,6 +76,10 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
 		config.Backend = input.Backend
 	}
 
+	if input.ClipSkip != 0 {
+		config.Diffusers.ClipSkip = input.ClipSkip
+	}
+
 	if input.ModelBaseName != "" {
 		config.AutoGPTQ.ModelBaseName = input.ModelBaseName
 	}
@@ -214,7 +219,7 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
 	}
 }
 
-func readConfig(modelFile string, input *OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *OpenAIRequest, error) {
+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")
 

api/options/options.go

@@ -7,6 +7,7 @@ import (
 
 	"github.com/go-skynet/LocalAI/pkg/gallery"
 	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/metrics"
 	"github.com/rs/zerolog/log"
 )
 
@@ -24,6 +25,7 @@ type Option struct {
 	PreloadModelsFromPath               string
 	CORSAllowOrigins                    string
 	ApiKeys                             []string
+	Metrics                             *metrics.Metrics
 
 	Galleries []gallery.Gallery
 
@@ -33,6 +35,8 @@ type Option struct {
 	ExternalGRPCBackends map[string]string
 
 	AutoloadGalleries bool
+
+	SingleBackend bool
 }
 
 type AppOption func(*Option)
@@ -58,6 +62,10 @@ func WithCors(b bool) AppOption {
 	}
 }
 
+var EnableSingleBackend = func(o *Option) {
+	o.SingleBackend = true
+}
+
 var EnableGalleriesAutoload = func(o *Option) {
 	o.AutoloadGalleries = true
 }
@@ -93,6 +101,7 @@ func WithStringGalleries(galls string) AppOption {
 	return func(o *Option) {
 		if galls == "" {
 			log.Debug().Msgf("no galleries to load")
+			o.Galleries = []gallery.Gallery{}
 			return
 		}
 		var galleries []gallery.Gallery
@@ -191,3 +200,9 @@ func WithApiKeys(apiKeys []string) AppOption {
 		o.ApiKeys = apiKeys
 	}
 }
+
+func WithMetrics(meter *metrics.Metrics) AppOption {
+	return func(o *Option) {
+		o.Metrics = meter
+	}
+}

api/schema/openai.go

@@ -1,4 +1,4 @@
-package openai
+package schema
 
 import (
 	"context"

api/schema/whisper.go

@@ -1,4 +1,4 @@
-package api
+package schema
 
 import "time"
 

backend/cpp/llama/CMakeLists.txt

@@ -0,0 +1,61 @@
+set(CMAKE_CXX_STANDARD 17)
+cmake_minimum_required(VERSION 3.15)
+set(TARGET grpc-server)
+set(_PROTOBUF_LIBPROTOBUF libprotobuf)
+set(_REFLECTION grpc++_reflection)
+
+if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
+    link_directories("/opt/homebrew/lib")
+    include_directories("/opt/homebrew/include")
+endif()
+
+find_package(absl CONFIG REQUIRED)
+find_package(Protobuf CONFIG REQUIRED)
+find_package(gRPC CONFIG REQUIRED)
+
+find_program(_PROTOBUF_PROTOC protoc)
+set(_GRPC_GRPCPP grpc++)
+find_program(_GRPC_CPP_PLUGIN_EXECUTABLE grpc_cpp_plugin)
+
+include_directories(${CMAKE_CURRENT_BINARY_DIR})
+include_directories(${Protobuf_INCLUDE_DIRS})
+
+message(STATUS "Using protobuf version ${Protobuf_VERSION} | Protobuf_INCLUDE_DIRS: ${Protobuf_INCLUDE_DIRS} | CMAKE_CURRENT_BINARY_DIR: ${CMAKE_CURRENT_BINARY_DIR}")
+
+# Proto file
+get_filename_component(hw_proto "../../../../../../pkg/grpc/proto/backend.proto" ABSOLUTE)
+get_filename_component(hw_proto_path "${hw_proto}" PATH)
+
+# Generated sources
+set(hw_proto_srcs "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.cc")
+set(hw_proto_hdrs "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.h")
+set(hw_grpc_srcs "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.cc")
+set(hw_grpc_hdrs "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.h")
+
+add_custom_command(
+      OUTPUT "${hw_proto_srcs}" "${hw_proto_hdrs}" "${hw_grpc_srcs}" "${hw_grpc_hdrs}"
+      COMMAND ${_PROTOBUF_PROTOC}
+      ARGS --grpc_out "${CMAKE_CURRENT_BINARY_DIR}"
+        --cpp_out "${CMAKE_CURRENT_BINARY_DIR}"
+        -I "${hw_proto_path}"
+        --plugin=protoc-gen-grpc="${_GRPC_CPP_PLUGIN_EXECUTABLE}"
+        "${hw_proto}"
+      DEPENDS "${hw_proto}")
+
+# hw_grpc_proto
+add_library(hw_grpc_proto
+  ${hw_grpc_srcs}
+  ${hw_grpc_hdrs}
+  ${hw_proto_srcs}
+  ${hw_proto_hdrs})
+
+add_executable(${TARGET} grpc-server.cpp)
+target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
+  absl::flags_parse
+  gRPC::${_REFLECTION}
+  gRPC::${_GRPC_GRPCPP}
+  protobuf::${_PROTOBUF_LIBPROTOBUF})
+target_compile_features(${TARGET} PRIVATE cxx_std_11)
+if(TARGET BUILD_INFO)
+  add_dependencies(${TARGET} BUILD_INFO)
+endif()

backend/cpp/llama/Makefile

@@ -0,0 +1,44 @@
+
+LLAMA_VERSION?=
+
+CMAKE_ARGS?=
+BUILD_TYPE?=
+
+# If build type is cublas, then we set -DLLAMA_CUBLAS=ON to CMAKE_ARGS automatically
+ifeq ($(BUILD_TYPE),cublas)
+	CMAKE_ARGS+=-DLLAMA_CUBLAS=ON
+# If build type is openblas then we set -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
+# to CMAKE_ARGS automatically
+else ifeq ($(BUILD_TYPE),openblas)
+	CMAKE_ARGS+=-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
+# If build type is clblast (openCL) we set -DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
+else ifeq ($(BUILD_TYPE),clblast)
+	CMAKE_ARGS+=-DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
+# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++ 
+else ifeq ($(BUILD_TYPE),hipblas)
+	CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON
+endif
+
+llama.cpp:
+	git clone --recurse-submodules https://github.com/ggerganov/llama.cpp llama.cpp
+	cd llama.cpp && git checkout -b build $(LLAMA_VERSION) && git submodule update --init --recursive --depth 1
+
+llama.cpp/examples/grpc-server:
+	mkdir -p 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/
+	echo "add_subdirectory(grpc-server)" >> llama.cpp/examples/CMakeLists.txt
+
+rebuild:
+	cp -rfv $(abspath ./)/CMakeLists.txt llama.cpp/examples/grpc-server/
+	cp -rfv $(abspath ./)/grpc-server.cpp llama.cpp/examples/grpc-server/
+	rm -rf grpc-server
+	$(MAKE) grpc-server
+
+clean:
+	rm -rf llama.cpp
+	rm -rf grpc-server
+
+grpc-server: llama.cpp llama.cpp/examples/grpc-server
+	cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release
+	cp llama.cpp/build/bin/grpc-server .

backend/cpp/llama/grpc-server.cpp

@@ -0,0 +1,926 @@
+// llama.cpp gRPC C++ backend server
+//
+// Ettore Di Giacinto <mudler@localai.io>
+//
+// This is a gRPC server for llama.cpp compatible with the LocalAI proto
+// Note: this is a re-adaptation of the original llama.cpp example/server.cpp for HTTP, 
+// but modified to work with gRPC
+//
+
+#include <iostream>
+#include <memory>
+#include <string>
+#include <getopt.h>
+
+#include "common.h"
+#include "llama.h"
+#include "grammar-parser.h"
+#include "backend.pb.h"
+#include "backend.grpc.pb.h"
+
+// include std::regex
+#include <regex>
+#include <grpcpp/ext/proto_server_reflection_plugin.h>
+#include <grpcpp/grpcpp.h>
+#include <grpcpp/health_check_service_interface.h>
+
+using grpc::Server;
+using grpc::ServerBuilder;
+using grpc::ServerContext;
+using grpc::Status;
+
+
+using backend::HealthMessage;
+
+
+// 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;
+};
+
+static size_t common_part(const std::vector<llama_token> &a, const std::vector<llama_token> &b)
+{
+    size_t i;
+    for (i = 0; i < a.size() && i < b.size() && a[i] == b[i]; i++)
+    {
+    }
+    return i;
+}
+
+enum stop_type
+{
+    STOP_FULL,
+    STOP_PARTIAL,
+};
+
+static bool ends_with(const std::string &str, const std::string &suffix)
+{
+    return str.size() >= suffix.size() &&
+           0 == str.compare(str.size() - suffix.size(), suffix.size(), suffix);
+}
+
+static size_t find_partial_stop_string(const std::string &stop,
+                                       const std::string &text)
+{
+    if (!text.empty() && !stop.empty())
+    {
+        const char text_last_char = text.back();
+        for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--)
+        {
+            if (stop[char_index] == text_last_char)
+            {
+                const std::string current_partial = stop.substr(0, char_index + 1);
+                if (ends_with(text, current_partial))
+                {
+                    return text.size() - char_index - 1;
+                }
+            }
+        }
+    }
+    return std::string::npos;
+}
+
+
+template <class Iter>
+static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
+{
+    std::string ret;
+    for (; begin != end; ++begin)
+    {
+        ret += llama_token_to_piece(ctx, *begin);
+    }
+    return ret;
+}
+
+
+// format incomplete utf-8 multibyte character for output
+static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
+{
+    std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
+    // if the size is 1 and first bit is 1, meaning it's a partial character
+    //   (size > 1 meaning it's already a known token)
+    if (out.size() == 1 && (out[0] & 0x80) == 0x80)
+    {
+        std::stringstream ss;
+        ss << std::hex << (out[0] & 0xff);
+        std::string res(ss.str());
+        out = "byte: \\x" + res;
+    }
+    return out;
+}
+
+struct llama_server_context
+{
+    bool stream = false;
+    bool has_next_token = false;
+    std::string generated_text;
+    std::vector<completion_token_output> generated_token_probs;
+
+    size_t num_prompt_tokens = 0;
+    size_t num_tokens_predicted = 0;
+    size_t n_past = 0;
+    size_t n_remain = 0;
+
+    std::vector<llama_token> embd;
+
+    gpt_params params;
+
+    llama_model *model = nullptr;
+    llama_context *ctx = nullptr;
+    llama_sampling_context *ctx_sampling = nullptr;
+
+    int n_ctx;
+
+    bool truncated = false;
+    bool stopped_eos = false;
+    bool stopped_word = false;
+    bool stopped_limit = false;
+    std::string stopping_word;
+    int32_t multibyte_pending = 0;
+
+    std::mutex mutex;
+
+    std::unique_lock<std::mutex> lock()
+    {
+        return std::unique_lock<std::mutex>(mutex);
+    }
+
+    ~llama_server_context()
+    {
+        if (ctx)
+        {
+            llama_free(ctx);
+            ctx = nullptr;
+        }
+        if (model)
+        {
+            llama_free_model(model);
+            model = nullptr;
+        }
+    }
+
+    void rewind()
+    {
+        params.antiprompt.clear();
+        params.sparams.grammar.clear();
+        num_prompt_tokens = 0;
+        num_tokens_predicted = 0;
+        generated_text = "";
+        generated_text.reserve(n_ctx);
+        generated_token_probs.clear();
+        truncated = false;
+        stopped_eos = false;
+        stopped_word = false;
+        stopped_limit = false;
+        stopping_word = "";
+        multibyte_pending = 0;
+        n_remain = 0;
+        n_past = 0;
+        params.sparams.n_prev = n_ctx;
+    }
+
+    void initSampling() {
+        if (ctx_sampling != nullptr) {
+            llama_sampling_free(ctx_sampling);
+        }
+        ctx_sampling = llama_sampling_init(params.sparams);
+    }
+
+    bool loadModel(const gpt_params &params_)
+    {
+        params = params_;
+        std::tie(model, ctx) = llama_init_from_gpt_params(params);
+        if (model == nullptr)
+        {
+            return false;
+        }
+        n_ctx = llama_n_ctx(ctx);
+        return true;
+    }
+    std::vector<llama_token> tokenize_string(const char *prompt, bool add_bos) const {
+       // If `add_bos` is true, we only add BOS, when json_prompt is a string,
+        // or the first element of the json_prompt array is a string.
+        std::vector<llama_token> prompt_tokens; 
+        auto s = std::string(prompt);
+        prompt_tokens = ::llama_tokenize(ctx, s, add_bos);
+        return prompt_tokens;
+    }
+     std::vector<llama_token> tokenize_array(const char **prompts, bool add_bos) const {
+                std::vector<llama_token> prompt_tokens; 
+
+            bool first = true;
+            bool is_string = true;
+            for (const char **p = prompts; *p != nullptr; ++p)
+              {
+                if (is_string)
+                {
+                    auto s = std::string(*p);
+                    std::vector<llama_token> p;
+                    if (first)
+                    {
+                        p = ::llama_tokenize(ctx, s, add_bos);
+                        first = false;
+                    }
+                    else
+                    {
+                        p = ::llama_tokenize(ctx, s, false);
+                    }
+                    prompt_tokens.insert(prompt_tokens.end(), p.begin(), p.end());
+                }
+                else
+                {
+                    if (first)
+                    {
+                        first = false;
+                    }
+                    //prompt_tokens.push_back(p.template get<llama_token>());
+                }
+            }
+            return prompt_tokens;
+     }
+
+    void truncatePrompt(std::vector<llama_token> &prompt_tokens) {
+        const int n_left = n_ctx - params.n_keep;
+        const int n_block_size = n_left / 2;
+        const int erased_blocks = (prompt_tokens.size() - params.n_keep - n_block_size) / n_block_size;
+
+        // Keep n_keep tokens at start of prompt (at most n_ctx - 4)
+        std::vector<llama_token> new_tokens(prompt_tokens.begin(), prompt_tokens.begin() + params.n_keep);
+
+        new_tokens.insert(new_tokens.end(), prompt_tokens.begin() + params.n_keep + erased_blocks * n_block_size, prompt_tokens.end());
+
+        truncated = true;
+        prompt_tokens = new_tokens;
+    }
+
+    void loadInfill()
+    {
+        bool suff_rm_leading_spc = true;
+        if (params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
+            params.input_suffix.erase(0, 1);
+            suff_rm_leading_spc = false;
+        }
+
+        auto prefix_tokens = tokenize_string(params.input_prefix.c_str(), false);
+        auto suffix_tokens = tokenize_string(params.input_suffix.c_str(), false);
+        const int space_token = 29871;
+        if (suff_rm_leading_spc  && suffix_tokens[0] == space_token) {
+            suffix_tokens.erase(suffix_tokens.begin());
+        }
+        prefix_tokens.insert(prefix_tokens.begin(), llama_token_prefix(ctx));
+        prefix_tokens.insert(prefix_tokens.begin(), llama_token_bos(ctx)); // always add BOS
+        prefix_tokens.insert(prefix_tokens.end(), llama_token_suffix(ctx));
+        prefix_tokens.insert(prefix_tokens.end(), suffix_tokens.begin(), suffix_tokens.end());
+        prefix_tokens.push_back(llama_token_middle(ctx));
+
+        auto prompt_tokens = prefix_tokens;
+
+        num_prompt_tokens = prompt_tokens.size();
+
+        if (params.n_keep < 0)
+        {
+            params.n_keep = (int)num_prompt_tokens;
+        }
+        params.n_keep = std::min(params.n_ctx - 4, params.n_keep);
+
+        // if input prompt is too big, truncate like normal
+        if (num_prompt_tokens >= (size_t) n_ctx)
+        {
+            truncatePrompt(prompt_tokens);
+            num_prompt_tokens = prompt_tokens.size();
+
+            GGML_ASSERT(num_prompt_tokens < (size_t)n_ctx);
+        }
+
+        // push the prompt into the sampling context (do not apply grammar)
+        for (auto & token : prompt_tokens)
+        {
+            llama_sampling_accept(ctx_sampling, ctx, token, false);
+        }
+
+        // compare the evaluated prompt with the new prompt
+        n_past = common_part(embd, prompt_tokens);
+        embd = prompt_tokens;
+
+        if (n_past == num_prompt_tokens)
+        {
+            // we have to evaluate at least 1 token to generate logits.
+            printf("we have to evaluate at least 1 token to generate logits\n");
+            n_past--;
+        }
+
+        // since #3228 we now have to manually manage the KV cache
+        llama_kv_cache_seq_rm(ctx, 0, n_past, -1);
+
+        has_next_token = true;
+    }
+    void loadPrompt(std::string prompt)
+    {
+        auto prompt_tokens = tokenize_string(prompt.c_str(), true);  // always add BOS
+
+        num_prompt_tokens = prompt_tokens.size();
+
+        if (params.n_keep < 0)
+        {
+            params.n_keep = (int)num_prompt_tokens;
+        }
+        params.n_keep = std::min(n_ctx - 4, params.n_keep);
+
+        // if input prompt is too big, truncate like normal
+        if (num_prompt_tokens >= (size_t) n_ctx)
+        {
+            truncatePrompt(prompt_tokens);
+            num_prompt_tokens = prompt_tokens.size();
+
+            GGML_ASSERT(num_prompt_tokens < (size_t)n_ctx);
+        }
+
+        // push the prompt into the sampling context (do not apply grammar)
+        for (auto & token : prompt_tokens)
+        {
+            llama_sampling_accept(ctx_sampling, ctx, token, false);
+        }
+
+        // compare the evaluated prompt with the new prompt
+        n_past = common_part(embd, prompt_tokens);
+
+        embd = prompt_tokens;
+        if (n_past == num_prompt_tokens)
+        {
+            // we have to evaluate at least 1 token to generate logits.
+            n_past--;
+        }
+
+        // since #3228 we now have to manually manage the KV cache
+        llama_kv_cache_seq_rm(ctx, 0, n_past, -1);
+
+        has_next_token = true;
+    }
+
+    void beginCompletion()
+    {
+        // number of tokens to keep when resetting context
+        n_remain = params.n_predict;
+        llama_set_rng_seed(ctx, params.seed);
+    }
+
+    completion_token_output nextToken()
+    {
+        completion_token_output result;
+        result.tok = -1;
+
+        if (embd.size() >= (size_t)n_ctx)
+        {
+            // Shift context
+
+            const int n_left    = n_past - params.n_keep - 1;
+            const int n_discard = n_left/2;
+
+            llama_kv_cache_seq_rm   (ctx, 0, params.n_keep + 1            , params.n_keep + n_discard + 1);
+            llama_kv_cache_seq_shift(ctx, 0, params.n_keep + 1 + n_discard, n_past, -n_discard);
+
+            for (size_t i = params.n_keep + 1 + n_discard; i < embd.size(); i++)
+            {
+                embd[i - n_discard] = embd[i];
+            }
+            embd.resize(embd.size() - n_discard);
+
+            n_past -= n_discard;
+
+            truncated = true;
+        }
+
+        bool tg = true;
+        while (n_past < embd.size())
+        {
+            int n_eval = (int)embd.size() - n_past;
+            tg = n_eval == 1;
+            if (n_eval > params.n_batch)
+            {
+                n_eval = params.n_batch;
+            }
+
+            if (llama_decode(ctx, llama_batch_get_one(&embd[n_past], n_eval, n_past, 0)))
+            {
+                has_next_token = false;
+                return result;
+            }
+            n_past += n_eval;
+        }
+
+        if (params.n_predict == 0)
+        {
+            has_next_token = false;
+            result.tok = llama_token_eos(ctx);
+            return result;
+        }
+
+        {
+            // out of user input, sample next token
+            result.tok = llama_sampling_sample(ctx_sampling, ctx, NULL);
+
+            llama_token_data_array cur_p = { ctx_sampling->cur.data(), ctx_sampling->cur.size(), false };
+
+            const int32_t n_probs = params.sparams.n_probs;
+            if (params.sparams.temp <= 0 && n_probs > 0)
+            {
+                // For llama_sample_token_greedy we need to sort candidates
+                llama_sample_softmax(ctx, &cur_p);
+            }
+
+            for (size_t i = 0; i < std::min(cur_p.size, (size_t)n_probs); ++i)
+            {
+                result.probs.push_back({cur_p.data[i].id, cur_p.data[i].p});
+            }
+
+            llama_sampling_accept(ctx_sampling, ctx, result.tok, true);
+
+            if (tg) {
+                num_tokens_predicted++;
+            }
+        }
+
+        // add it to the context
+        embd.push_back(result.tok);
+        // decrement remaining sampling budget
+        --n_remain;
+
+        if (!embd.empty() && embd.back() == llama_token_eos(ctx))
+        {
+            // stopping_word = llama_token_to_piece(ctx, embd.back());
+            has_next_token = false;
+            stopped_eos = true;
+            return result;
+        }
+
+        has_next_token = params.n_predict == -1 || n_remain != 0;
+        return result;
+    }
+
+    size_t findStoppingStrings(const std::string &text, const size_t last_token_size,
+                               const stop_type type)
+    {
+        size_t stop_pos = std::string::npos;
+        for (const std::string &word : params.antiprompt)
+        {
+            size_t pos;
+            if (type == STOP_FULL)
+            {
+                const size_t tmp = word.size() + last_token_size;
+                const size_t from_pos = text.size() > tmp ? text.size() - tmp : 0;
+                pos = text.find(word, from_pos);
+            }
+            else
+            {
+                pos = find_partial_stop_string(word, text);
+            }
+            if (pos != std::string::npos &&
+                (stop_pos == std::string::npos || pos < stop_pos))
+            {
+                if (type == STOP_FULL)
+                {
+                    stopping_word = word;
+                    stopped_word = true;
+                    has_next_token = false;
+                }
+                stop_pos = pos;
+            }
+        }
+        return stop_pos;
+    }
+
+    completion_token_output doCompletion()
+    {
+        auto token_with_probs = nextToken();
+
+        const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_piece(ctx, token_with_probs.tok);
+        generated_text += token_text;
+
+        if (params.sparams.n_probs > 0)
+        {
+            generated_token_probs.push_back(token_with_probs);
+        }
+
+        if (multibyte_pending > 0)
+        {
+            multibyte_pending -= token_text.size();
+        }
+        else if (token_text.size() == 1)
+        {
+            const char c = token_text[0];
+            // 2-byte characters: 110xxxxx 10xxxxxx
+            if ((c & 0xE0) == 0xC0)
+            {
+                multibyte_pending = 1;
+                // 3-byte characters: 1110xxxx 10xxxxxx 10xxxxxx
+            }
+            else if ((c & 0xF0) == 0xE0)
+            {
+                multibyte_pending = 2;
+                // 4-byte characters: 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx
+            }
+            else if ((c & 0xF8) == 0xF0)
+            {
+                multibyte_pending = 3;
+            }
+            else
+            {
+                multibyte_pending = 0;
+            }
+        }
+
+        if (multibyte_pending > 0 && !has_next_token)
+        {
+            has_next_token = true;
+            n_remain++;
+        }
+
+        if (!has_next_token && n_remain == 0)
+        {
+            stopped_limit = true;
+        }
+
+        return token_with_probs;
+    }
+
+    std::vector<float> getEmbedding()
+    {
+        static const int n_embd = llama_n_embd(model);
+        if (!params.embedding)
+        {
+            return std::vector<float>(n_embd, 0.0f);
+        }
+        const float *data = llama_get_embeddings(ctx);
+        std::vector<float> embedding(data, data + n_embd);
+        return embedding;
+    }
+};
+
+
+static void parse_options_completion(bool streaming,const backend::PredictOptions* predict, llama_server_context &llama)
+{
+    gpt_params default_params;
+
+    llama.stream = streaming;
+    llama.params.n_predict = predict->tokens() == 0 ? -1 : predict->tokens();
+    llama.params.sparams.top_k = predict->topk();
+    llama.params.sparams.top_p = predict->topp();
+    llama.params.sparams.tfs_z = predict->tailfreesamplingz();
+    llama.params.sparams.typical_p = predict->typicalp();
+    llama.params.sparams.penalty_last_n = predict->repeat();
+    llama.params.sparams.temp = predict->temperature();
+    llama.params.sparams.penalty_repeat = predict->penalty();
+    llama.params.sparams.penalty_present = predict->presencepenalty();
+    llama.params.sparams.penalty_freq = predict->frequencypenalty();
+    llama.params.sparams.mirostat = predict->mirostat();
+    llama.params.sparams.mirostat_tau = predict->mirostattau();
+    llama.params.sparams.mirostat_eta = predict->mirostateta();
+    llama.params.sparams.penalize_nl = predict->penalizenl();
+    llama.params.n_keep = predict->nkeep();
+    llama.params.seed = predict->seed();
+    llama.params.sparams.grammar = predict->grammar();
+    // llama.params.n_probs = predict->
+    llama.params.prompt = predict->prompt();
+
+    llama.params.sparams.logit_bias.clear();
+
+    if (predict->ignoreeos())
+    {
+        llama.params.sparams.logit_bias[llama_token_eos(llama.ctx)] = -INFINITY;
+    }
+
+    // const auto &logit_bias = body.find("logit_bias");
+    // if (logit_bias != body.end() && logit_bias->is_array())
+    // {
+    //     const int n_vocab = llama_n_vocab(llama.model);
+    //     for (const auto &el : *logit_bias)
+    //     {
+    //         if (el.is_array() && el.size() == 2 && el[0].is_number_integer())
+    //         {
+    //             llama_token tok = el[0].get<llama_token>();
+    //             if (tok >= 0 && tok < n_vocab)
+    //             {
+    //                 if (el[1].is_number())
+    //                 {
+    //                     llama.params.logit_bias[tok] = el[1].get<float>();
+    //                 }
+    //                 else if (el[1].is_boolean() && !el[1].get<bool>())
+    //                 {
+    //                     llama.params.logit_bias[tok] = -INFINITY;
+    //                 }
+    //             }
+    //         }
+    //     }
+    // }
+
+    llama.params.antiprompt.clear();
+    for (const std::string& stopPrompt : predict->stopprompts()) {
+    if (!stopPrompt.empty())
+            {
+                llama.params.antiprompt.push_back(stopPrompt);
+            }
+    }
+}
+
+
+
+static void params_parse(const backend::ModelOptions* request,
+                                gpt_params & params) {
+   
+    params.model = request->modelfile();
+    //  params.model_alias ??
+    params.model_alias =  request->modelfile();
+    params.n_ctx = request->contextsize();
+    params.memory_f16 = request->f16memory();
+    params.n_threads = request->threads();
+    params.n_gpu_layers = request->ngpulayers();
+    params.n_batch = request->nbatch();
+
+    if (!request->tensorsplit().empty()) {
+        std::string arg_next = request->tensorsplit();
+
+        // split string by , and /
+        const std::regex regex{ R"([,/]+)" };
+        std::sregex_token_iterator it{ arg_next.begin(), arg_next.end(), regex, -1 };
+        std::vector<std::string> split_arg{ it, {} };
+
+        GGML_ASSERT(split_arg.size() <= LLAMA_MAX_DEVICES);
+
+        for (size_t i_device = 0; i_device < LLAMA_MAX_DEVICES; ++i_device) {
+            if (i_device < split_arg.size()) {
+                params.tensor_split[i_device] = std::stof(split_arg[i_device]);
+            }
+            else {
+                params.tensor_split[i_device] = 0.0f;
+            }
+        }
+    }
+
+    if (!request->maingpu().empty()) {
+        params.main_gpu = std::stoi(request->maingpu());
+    }
+    // TODO: lora needs also a scale factor
+    //params.lora_adapter = request->loraadapter();
+    //params.lora_base = request->lorabase();
+    params.use_mlock = request->mlock();
+    params.use_mmap = request->mmap();
+    params.embedding = request->embeddings();
+}
+
+static bool is_at_eob(llama_server_context &server_context, const llama_token *tokens, const size_t n_tokens) {
+    return n_tokens && tokens[n_tokens-1] == llama_token_eos(server_context.ctx);
+}
+
+// Function matching type llama_beam_search_callback_fn_t.
+// Custom callback example is called each time the beams lengths increase:
+//  * Show progress by printing ',' following by number of convergent beam tokens if any.
+//  * When all beams converge to a common prefix, they are made available in beams_state.beams[0].
+//    This is also called when the stop condition is met.
+//    Collect tokens into std::vector<llama_token> response which is pointed to by callback_data.
+static void beam_search_callback(void *callback_data, llama_beams_state beams_state) {
+    auto & llama = *static_cast<llama_server_context*>(callback_data);
+    // Mark beams as EOS as needed.
+    for (size_t i = 0 ; i < beams_state.n_beams ; ++i) {
+        llama_beam_view& beam_view = beams_state.beam_views[i];
+        if (!beam_view.eob && is_at_eob(llama, beam_view.tokens, beam_view.n_tokens)) {
+            beam_view.eob = true;
+        }
+    }
+    printf(",");  // Show progress
+    if (const size_t n = beams_state.common_prefix_length) {
+        llama.generated_token_probs.resize(llama.generated_token_probs.size() + n);
+        assert(0u < beams_state.n_beams);
+        const llama_token * tokens = beams_state.beam_views[0].tokens;
+        const auto map = [](llama_token tok) { return completion_token_output{{},tok}; };
+        std::transform(tokens, tokens + n, llama.generated_token_probs.end() - n, map);
+        printf("%zu", n);
+    }
+    fflush(stdout);
+#if 0 // DEBUG: print current beams for this iteration
+    std::cout << "\n\nCurrent beams:\n";
+    for (size_t i=0 ; i < beams_state.n_beams ; ++i) {
+        std::cout << "beams["<<i<<"]: " << ostream_beam_view{state.ctx,beams_state.beam_views[i]} << std::endl;
+    }
+#endif
+}
+struct token_translator {
+    llama_context * ctx;
+    std::string operator()(llama_token tok) const { return llama_token_to_piece(ctx, tok); }
+    std::string operator()(const completion_token_output & cto) const { return (*this)(cto.tok); }
+};
+
+
+static void append_to_generated_text_from_generated_token_probs(llama_server_context &llama)
+{
+    auto & gtps = llama.generated_token_probs;
+    auto translator = token_translator{llama.ctx};
+    auto add_strlen = [=](size_t sum, const completion_token_output & cto) { return sum + translator(cto).size(); };
+    const size_t len = std::accumulate(gtps.begin(), gtps.end(), size_t(0), add_strlen);
+    if (llama.generated_text.capacity() < llama.generated_text.size() + len) {
+        llama.generated_text.reserve(llama.generated_text.size() + len);
+    }
+    for (const completion_token_output & cto : gtps) {
+        llama.generated_text += translator(cto);
+    }
+}
+
+// GRPC Server start
+class BackendServiceImpl final : public backend::Backend::Service {
+  // The class has a llama instance that is shared across all RPCs
+  llama_server_context llama;
+public:
+  grpc::Status Health(ServerContext* context, const backend::HealthMessage* request, backend::Reply* reply) {
+    // Implement Health RPC
+    reply->set_message("OK");
+    return Status::OK;
+  }
+
+  grpc::Status LoadModel(ServerContext* context, const backend::ModelOptions* request, backend::Result* result) {
+    // Implement LoadModel RPC
+    gpt_params params;
+    params_parse(request, params);
+
+    llama_backend_init(params.numa);
+
+    // load the model
+    if (!llama.loadModel(params))
+    {
+        result->set_message("Failed loading model");
+        result->set_success(false);
+        return Status::CANCELLED;
+    }
+    result->set_message("Loading succeeded");
+    result->set_success(true);
+    return Status::OK;
+  }
+  grpc::Status PredictStream(grpc::ServerContext* context, const backend::PredictOptions* request, grpc::ServerWriter<backend::Reply>* writer) override {
+        // Implement the streaming logic here based on the request options
+        // You can use writer->Write(response) to send a reply to the client
+        // and return grpc::Status::OK when the operation is complete.
+        auto lock = llama.lock();
+
+        llama.rewind();
+
+        llama_reset_timings(llama.ctx);
+
+        parse_options_completion(false, request, llama);
+
+        llama.initSampling();
+        llama.loadPrompt(request->prompt());
+        llama.beginCompletion();
+        size_t sent_count = 0;
+        size_t sent_token_probs_index = 0;
+
+        while (llama.has_next_token) {
+            const completion_token_output token_with_probs = llama.doCompletion();
+            if (token_with_probs.tok == -1 || llama.multibyte_pending > 0) {
+                continue;
+            }
+            const std::string token_text = llama_token_to_piece(llama.ctx, token_with_probs.tok);
+
+            size_t pos = std::min(sent_count, llama.generated_text.size());
+
+            const std::string str_test = llama.generated_text.substr(pos);
+            bool is_stop_full = false;
+            size_t stop_pos =
+                llama.findStoppingStrings(str_test, token_text.size(), STOP_FULL);
+            if (stop_pos != std::string::npos) {
+                is_stop_full = true;
+                llama.generated_text.erase(
+                    llama.generated_text.begin() + pos + stop_pos,
+                    llama.generated_text.end());
+                pos = std::min(sent_count, llama.generated_text.size());
+            } else {
+                is_stop_full = false;
+                stop_pos = llama.findStoppingStrings(str_test, token_text.size(),
+                    STOP_PARTIAL);
+            }
+
+            if (
+                stop_pos == std::string::npos ||
+                // Send rest of the text if we are at the end of the generation
+                (!llama.has_next_token && !is_stop_full && stop_pos > 0)
+            ) {
+                const std::string to_send = llama.generated_text.substr(pos, std::string::npos);
+
+                sent_count += to_send.size();
+
+                std::vector<completion_token_output> probs_output = {};
+
+                if (llama.params.sparams.n_probs > 0) {
+                    const std::vector<llama_token> to_send_toks = llama_tokenize(llama.ctx, to_send, false);
+                    size_t probs_pos = std::min(sent_token_probs_index, llama.generated_token_probs.size());
+                    size_t probs_stop_pos = std::min(sent_token_probs_index + to_send_toks.size(), llama.generated_token_probs.size());
+                    if (probs_pos < probs_stop_pos) {
+                        probs_output = std::vector<completion_token_output>(llama.generated_token_probs.begin() + probs_pos, llama.generated_token_probs.begin() + probs_stop_pos);
+                    }
+                    sent_token_probs_index = probs_stop_pos;
+                }
+                backend::Reply reply;
+                reply.set_message(to_send);
+
+                // Send the reply
+                writer->Write(reply);
+            }
+        }
+
+        llama_print_timings(llama.ctx);
+
+        llama.mutex.unlock();
+        lock.release();
+        return grpc::Status::OK;
+    }
+
+
+    grpc::Status Predict(ServerContext* context, const backend::PredictOptions* request, backend::Reply* reply) {
+        auto lock = llama.lock();
+        llama.rewind();
+        llama_reset_timings(llama.ctx);
+        parse_options_completion(false, request, llama);
+
+        llama.initSampling();
+        llama.loadPrompt(request->prompt());
+        llama.beginCompletion();
+
+        if (llama.params.n_beams) {
+            // Fill llama.generated_token_probs vector with final beam.
+            llama_beam_search(llama.ctx, beam_search_callback, &llama, llama.params.n_beams,
+                                llama.n_past, llama.n_remain);
+            // Translate llama.generated_token_probs to llama.generated_text.
+            append_to_generated_text_from_generated_token_probs(llama);
+        } else {
+            size_t stop_pos = std::string::npos;
+
+            while (llama.has_next_token) {
+                const completion_token_output token_with_probs = llama.doCompletion();
+                const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_piece(llama.ctx, token_with_probs.tok);
+
+                stop_pos = llama.findStoppingStrings(llama.generated_text,
+                    token_text.size(), STOP_FULL);
+            }
+
+            if (stop_pos == std::string::npos) {
+                stop_pos = llama.findStoppingStrings(llama.generated_text, 0, STOP_PARTIAL);
+            }
+            if (stop_pos != std::string::npos) {
+                llama.generated_text.erase(llama.generated_text.begin() + stop_pos,
+                    llama.generated_text.end());
+            }
+        }
+
+        auto probs = llama.generated_token_probs;
+        if (llama.params.sparams.n_probs > 0 && llama.stopped_word) {
+            const std::vector<llama_token> stop_word_toks = llama_tokenize(llama.ctx, llama.stopping_word, false);
+            probs = std::vector<completion_token_output>(llama.generated_token_probs.begin(), llama.generated_token_probs.end() - stop_word_toks.size());
+        }
+        reply->set_message(llama.generated_text);
+        return grpc::Status::OK;
+    }
+};
+
+void RunServer(const std::string& server_address) {
+  BackendServiceImpl service;
+
+  ServerBuilder builder;
+  builder.AddListeningPort(server_address, grpc::InsecureServerCredentials());
+  builder.RegisterService(&service);
+
+  std::unique_ptr<Server> server(builder.BuildAndStart());
+  std::cout << "Server listening on " << server_address << std::endl;
+  server->Wait();
+}
+
+int main(int argc, char** argv) {
+  std::string server_address("localhost:50051");
+
+  // Define long and short options
+  struct option long_options[] = {
+      {"addr", required_argument, nullptr, 'a'},
+      {nullptr, 0, nullptr, 0}
+  };
+
+  // Parse command-line arguments
+  int option;
+  int option_index = 0;
+  while ((option = getopt_long(argc, argv, "a:", long_options, &option_index)) != -1) {
+    switch (option) {
+      case 'a':
+        server_address = optarg;
+        break;
+      default:
+        std::cerr << "Usage: " << argv[0] << " [--addr=<address>] or [-a <address>]" << std::endl;
+        return 1;
+    }
+  }
+
+  RunServer(server_address);
+  return 0;
+}

cmd/grpc/bert-embeddings/main.go

@@ -5,8 +5,8 @@ package main
 import (
 	"flag"
 
+	bert "github.com/go-skynet/LocalAI/pkg/backend/llm/bert"
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
-	bert "github.com/go-skynet/LocalAI/pkg/grpc/llm/bert"
 )
 
 var (

cmd/grpc/bloomz/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	bloomz "github.com/go-skynet/LocalAI/pkg/grpc/llm/bloomz"
+	bloomz "github.com/go-skynet/LocalAI/pkg/backend/llm/bloomz"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/dolly/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/falcon-ggml/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/falcon/main.go

@@ -7,7 +7,7 @@ package main
 import (
 	"flag"
 
-	falcon "github.com/go-skynet/LocalAI/pkg/grpc/llm/falcon"
+	falcon "github.com/go-skynet/LocalAI/pkg/backend/llm/falcon"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/gpt2/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/gpt4all/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	gpt4all "github.com/go-skynet/LocalAI/pkg/grpc/llm/gpt4all"
+	gpt4all "github.com/go-skynet/LocalAI/pkg/backend/llm/gpt4all"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/gptj/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/gptneox/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/langchain-huggingface/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	langchain "github.com/go-skynet/LocalAI/pkg/grpc/llm/langchain"
+	langchain "github.com/go-skynet/LocalAI/pkg/backend/llm/langchain"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/llama-stable/main.go

@@ -0,0 +1,21 @@
+package main
+
+import (
+	"flag"
+
+	llama "github.com/go-skynet/LocalAI/pkg/backend/llm/llama-stable"
+
+	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, &llama.LLM{}); err != nil {
+		panic(err)
+	}
+}

cmd/grpc/llama/main.go

@@ -7,7 +7,7 @@ package main
 import (
 	"flag"
 
-	llama "github.com/go-skynet/LocalAI/pkg/grpc/llm/llama"
+	llama "github.com/go-skynet/LocalAI/pkg/backend/llm/llama"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/mpt/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/piper/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	tts "github.com/go-skynet/LocalAI/pkg/grpc/tts"
+	tts "github.com/go-skynet/LocalAI/pkg/backend/tts"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/replit/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/rwkv/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	rwkv "github.com/go-skynet/LocalAI/pkg/grpc/llm/rwkv"
+	rwkv "github.com/go-skynet/LocalAI/pkg/backend/llm/rwkv"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/stablediffusion/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	image "github.com/go-skynet/LocalAI/pkg/grpc/image"
+	image "github.com/go-skynet/LocalAI/pkg/backend/image"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/starcoder/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
+	transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

cmd/grpc/whisper/main.go

@@ -5,7 +5,7 @@ package main
 import (
 	"flag"
 
-	transcribe "github.com/go-skynet/LocalAI/pkg/grpc/transcribe"
+	transcribe "github.com/go-skynet/LocalAI/pkg/backend/transcribe"
 
 	grpc "github.com/go-skynet/LocalAI/pkg/grpc"
 )

docker-compose.yaml

@@ -12,4 +12,5 @@ services:
       - .env
     volumes:
       - ./models:/models:cached
+      - ./images/:/tmp/generated/images/
     command: ["/usr/bin/local-ai" ]

examples/README.md

@@ -157,6 +157,26 @@ Allows to run any LocalAI-compatible model as a backend on the servers of https:
 
 [Check it out here](https://runpod.io/gsc?template=uv9mtqnrd0&ref=984wlcra)
 
+### Continue
+
+_by [@gruberdev](https://github.com/gruberdev)_
+
+<img src="continue/img/screen.png" width="600" height="200" alt="Screenshot">
+
+Demonstrates how to integrate an open-source copilot alternative that enhances code analysis, completion, and improvements. This approach seamlessly integrates with any LocalAI model, offering a more user-friendly experience.
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/continue/)
+
+### Streamlit bot
+
+_by [@majoshi1](https://github.com/majoshi1)_
+
+![Screenshot](streamlit-bot/streamlit-bot.png)
+
+A chat bot made using `Streamlit` & LocalAI.
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/streamlit-bot/)
+
 ## Want to contribute?
 
 Create an issue, and put `Example: <description>` in the title! We will post your examples here.

examples/autoGPT/.env.example

@@ -1,5 +1,9 @@
+# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
+# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
+
 OPENAI_API_KEY=sk---anystringhere
 OPENAI_API_BASE=http://api:8080/v1
 # Models to preload at start
-# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings
-PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}, { "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002"}]
+# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings,
+# see other options in the model gallery at https://github.com/go-skynet/model-gallery
+PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}, { "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002"}]

examples/autoGPT/README.md

@@ -10,12 +10,16 @@ git clone https://github.com/go-skynet/LocalAI
 
 cd LocalAI/examples/autoGPT
 
+cp -rfv .env.example .env
+
+# Edit the .env file to set a different model by editing `PRELOAD_MODELS`.
+vim .env
+
 docker-compose run --rm auto-gpt
 ```
 
 Note: The example automatically downloads the `gpt4all` model as it is under a permissive license. The GPT4All model does not seem to be enough to run AutoGPT. WizardLM-7b-uncensored seems to perform better (with `f16: true`).
 
-See the `.env` configuration file to set a different model with the [model-gallery](https://github.com/go-skynet/model-gallery) by editing `PRELOAD_MODELS`.
 
 ## Without docker
 

examples/bruno/LocalAI Test Requests/backend monitor/backend monitor.bru

@@ -0,0 +1,11 @@
+meta {
+  name: backend monitor
+  type: http
+  seq: 4
+}
+
+get {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/backend/monitor
+  body: none
+  auth: none
+}

examples/bruno/LocalAI Test Requests/backend monitor/backend-shutdown.bru

@@ -0,0 +1,21 @@
+meta {
+  name: backend-shutdown
+  type: http
+  seq: 3
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/backend/shutdown
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "model": "{{DEFAULT_MODEL}}"
+  }
+}

examples/bruno/LocalAI Test Requests/bruno.json

@@ -0,0 +1,5 @@
+{
+  "version": "1",
+  "name": "LocalAI Test Requests",
+  "type": "collection"
+}

examples/bruno/LocalAI Test Requests/environments/localhost.bru

@@ -0,0 +1,6 @@
+vars {
+  HOST: localhost
+  PORT: 8080
+  DEFAULT_MODEL: gpt-3.5-turbo
+  PROTOCOL: http://
+}

examples/bruno/LocalAI Test Requests/get models list.bru

@@ -0,0 +1,11 @@
+meta {
+  name: get models list
+  type: http
+  seq: 2
+}
+
+get {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models
+  body: none
+  auth: none
+}

examples/bruno/LocalAI Test Requests/image generation/Generate image.bru

@@ -0,0 +1,25 @@
+meta {
+  name: Generate image
+  type: http
+  seq: 1
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/v1/images/generations
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+    "prompt": "<positive prompt>|<negative prompt>",
+    "model": "model-name",
+    "step": 51,
+    "size": "1024x1024",
+    "image": ""
+  }
+}

examples/bruno/LocalAI Test Requests/llm text/-completions.bru

@@ -0,0 +1,24 @@
+meta {
+  name: -completions
+  type: http
+  seq: 4
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/completions
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "model": "{{DEFAULT_MODEL}}",
+      "prompt": "function downloadFile(string url, string outputPath) {",
+      "max_tokens": 256,
+      "temperature": 0.5
+  }
+}

examples/bruno/LocalAI Test Requests/llm text/-edits.bru

@@ -0,0 +1,23 @@
+meta {
+  name: -edits
+  type: http
+  seq: 5
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/edits
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "model": "{{DEFAULT_MODEL}}",
+      "input": "What day of the wek is it?",
+      "instruction": "Fix the spelling mistakes"
+  }
+}

examples/bruno/LocalAI Test Requests/llm text/-embeddings.bru

@@ -0,0 +1,22 @@
+meta {
+  name: -embeddings
+  type: http
+  seq: 6
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/embeddings
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "model": "{{DEFAULT_MODEL}}",
+      "input": "A STRANGE GAME.\nTHE ONLY WINNING MOVE IS NOT TO PLAY.\n\nHOW ABOUT A NICE GAME OF CHESS?"
+  }
+}

examples/bruno/LocalAI Test Requests/llm text/chat/chat completion -simple- 1 message-.bru

@@ -0,0 +1,30 @@
+meta {
+  name: chat completion -simple- 1 message-
+  type: http
+  seq: 4
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+    "model": "{{DEFAULT_MODEL}}",
+    "messages": [
+      {
+        "role": "user",
+        "content": "How could one use friction to cook an egg?"
+      }
+    ],
+    "max_tokens": 256,
+    "temperature": 0.2,
+    "grammar": ""
+  }
+}

examples/bruno/LocalAI Test Requests/llm text/chat/chat-completions -long-.bru

@@ -0,0 +1,29 @@
+meta {
+  name: chat-completions -long-
+  type: http
+  seq: 5
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+       "model": "{{DEFAULT_MODEL}}",
+       "messages": [{"role": "system", "content": "You are a helpful, intelligent pirate assistant. Always answer as helpfully as possible, while being a pirate and using pirate language. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."},
+           {"role": "user", "content": "How could one use electricity to cook an egg?"},
+           {"role": "assistant",
+                  "content": "Shiver me timbers! Using electricity to cook an egg? Well, matey, I reckon that be a right curious idea! *adjusts spectacles* Now, I ain't sure if this be possible, but I'll do me best to help ye out.\n\nFirst things first, ye gotta understand that electricity be a powerful force, and it can't just cook an egg on its own. Ye see, electricity be like a mighty wind that can make things happen, but it needs somethin' to work with. So, if ye want to use electricity to cook an egg, ye gotta find a way to harness that power and make it do the cookin'.\n\nNow, I know what ye might be thinkin': \"How do I harness the power of electricity to cook an egg?\" Well, matey, there be a few ways to do it. One way be to use a special device called an \"electric frying pan.\" This be a pan that has a built-in heating element that gets hot when ye plug it into a wall socket. When the element gets hot, ye can crack an egg into the pan and watch as it cook"
+              },
+              {"role": "user", "content": "I don't have one of those, just a raw wire and plenty of power! How do we get it done?"}],
+       "max_tokens": 1024,
+       "temperature": 0.5
+  }
+}

examples/bruno/LocalAI Test Requests/llm text/chat/chat-completions -stream-.bru

@@ -0,0 +1,25 @@
+meta {
+  name: chat-completions -stream-
+  type: http
+  seq: 6
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+       "model": "{{DEFAULT_MODEL}}",
+       "messages": [{"role": "user", "content": "Explain how I can set sail on the ocean using only power generated by seagulls?"}],
+       "max_tokens": 256,
+       "temperature": 0.9,
+       "stream": true
+  }
+}

examples/bruno/LocalAI Test Requests/model gallery/add model gallery.bru

@@ -0,0 +1,22 @@
+meta {
+  name: add model gallery
+  type: http
+  seq: 10
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "url": "file:///home/dave/projects/model-gallery/huggingface/TheBloke__CodeLlama-7B-Instruct-GGML.yaml",
+      "name": "test"
+  }
+}

examples/bruno/LocalAI Test Requests/model gallery/delete model gallery.bru

@@ -0,0 +1,21 @@
+meta {
+  name: delete model gallery
+  type: http
+  seq: 11
+}
+
+delete {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "name": "test"
+  }
+}

examples/bruno/LocalAI Test Requests/model gallery/list MODELS in galleries.bru

@@ -0,0 +1,11 @@
+meta {
+  name: list MODELS in galleries
+  type: http
+  seq: 7
+}
+
+get {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/available
+  body: none
+  auth: none
+}

examples/bruno/LocalAI Test Requests/model gallery/list model GALLERIES.bru

@@ -0,0 +1,11 @@
+meta {
+  name: list model GALLERIES
+  type: http
+  seq: 8
+}
+
+get {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
+  body: none
+  auth: none
+}

examples/bruno/LocalAI Test Requests/model gallery/model gallery apply -gist-.bru

@@ -0,0 +1,21 @@
+meta {
+  name: model gallery apply -gist-
+  type: http
+  seq: 12
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/apply
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "id": "TheBloke__CodeLlama-7B-Instruct-GGML__codellama-7b-instruct.ggmlv3.Q2_K.bin"
+  }
+}

examples/bruno/LocalAI Test Requests/model gallery/model gallery apply.bru

@@ -0,0 +1,22 @@
+meta {
+  name: model gallery apply
+  type: http
+  seq: 9
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/apply
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "id": "dave@TheBloke__CodeLlama-7B-Instruct-GGML__codellama-7b-instruct.ggmlv3.Q3_K_S.bin",
+      "name": "codellama7b"
+  }
+}

examples/bruno/LocalAI Test Requests/tts/-tts.bru

@@ -0,0 +1,22 @@
+meta {
+  name: -tts
+  type: http
+  seq: 2
+}
+
+post {
+  url: {{PROTOCOL}}{{HOST}}:{{PORT}}/tts
+  body: json
+  auth: none
+}
+
+headers {
+  Content-Type: application/json
+}
+
+body:json {
+  {
+      "model": "{{DEFAULT_MODEL}}",
+      "input": "A STRANGE GAME.\nTHE ONLY WINNING MOVE IS NOT TO PLAY.\n\nHOW ABOUT A NICE GAME OF CHESS?"
+  }
+}

examples/chatbot-ui-manual/README.md

@@ -24,10 +24,13 @@ docker-compose up -d --pull always
 # docker-compose up -d --build
 ```
 
+Then browse to `http://localhost:3000` to view the Web UI.
+
 ## Pointing chatbot-ui to a separately managed LocalAI service
 
-If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
-```
+If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose.yaml` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
+
+```yaml
 version: '3.6'
 
 services:
@@ -40,9 +43,8 @@ services:
       - 'OPENAI_API_HOST=http://<<LOCALAI_IP>>:8080'
 ```
 
-Once you've edited the Dockerfile, you can start it with `docker compose up`, then browse to `http://localhost:3000`.
+Once you've edited the `docker-compose.yaml`, you can start it with `docker compose up`, then browse to `http://localhost:3000` to view the Web UI.
 
 ## Accessing chatbot-ui
 
 Open http://localhost:3000 for the Web UI.
-

examples/chatbot-ui-manual/models

@@ -0,0 +1 @@
+../models

examples/chatbot-ui/README.md

@@ -20,10 +20,13 @@ docker-compose up --pull always
 # docker-compose up -d --build
 ```
 
+Then browse to `http://localhost:3000` to view the Web UI.
+
 ## Pointing chatbot-ui to a separately managed LocalAI service
 
-If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
-```
+If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose.yaml` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
+
+```yaml
 version: '3.6'
 
 services:
@@ -36,9 +39,8 @@ services:
       - 'OPENAI_API_HOST=http://<<LOCALAI_IP>>:8080'
 ```
 
-Once you've edited the Dockerfile, you can start it with `docker compose up`, then browse to `http://localhost:3000`.
+Once you've edited the `docker-compose.yaml`, you can start it with `docker compose up`, then browse to `http://localhost:3000` to view the Web UI.
 
 ## Accessing chatbot-ui
 
 Open http://localhost:3000 for the Web UI.
-

examples/continue/README.md

@@ -0,0 +1,53 @@
+# Continue
+
+![logo](https://continue.dev/docs/assets/images/continue-cover-logo-aa135cc83fe8a14af480d1633ed74eb5.png)
+
+This document presents an example of integration with [continuedev/continue](https://github.com/continuedev/continue).
+
+![Screenshot](https://continue.dev/docs/assets/images/continue-screenshot-1f36b99467817f755739d7f4c4c08fe3.png)
+
+For a live demonstration, please click on the link below:
+
+- [How it works (Video demonstration)](https://www.youtube.com/watch?v=3Ocrc-WX4iQ)
+
+## Integration Setup Walkthrough
+
+1. [As outlined in `continue`'s documentation](https://continue.dev/docs/getting-started), install the [Visual Studio Code extension from the marketplace](https://marketplace.visualstudio.com/items?itemName=Continue.continue) and open it.
+2. In this example, LocalAI will download the gpt4all model and set it up as "gpt-3.5-turbo". Refer to the `docker-compose.yaml` file for details.
+
+    ```bash
+    # Clone LocalAI
+    git clone https://github.com/go-skynet/LocalAI
+
+    cd LocalAI/examples/continue
+
+    # Start with docker-compose
+    docker-compose up --build -d
+    ```
+
+3. Type `/config` within Continue's VSCode extension, or edit the file located at `~/.continue/config.py` on your system with the following configuration:
+
+    ```py
+    from continuedev.src.continuedev.libs.llm.openai import OpenAI
+
+    config = ContinueConfig(
+       ...
+       models=Models(
+            default=OpenAI(
+               api_key="my-api-key",
+               model="gpt-3.5-turbo",
+               api_base="http://localhost:8080",
+            )
+       ),
+    )
+    ```
+
+This setup enables you to make queries directly to your model running in the Docker container. Note that the `api_key` does not need to be properly set up; it is included here as a placeholder.
+
+If editing the configuration seems confusing, you may copy and paste the provided default `config.py` file over the existing one in `~/.continue/config.py` after initializing the extension in the VSCode IDE.
+
+## Additional Resources
+
+- [Official Continue documentation](https://continue.dev/docs/intro)
+- [Documentation page on using self-hosted models](https://continue.dev/docs/customization#self-hosting-an-open-source-model)
+- [Official extension link](https://marketplace.visualstudio.com/items?itemName=Continue.continue)

examples/continue/config.py

@@ -0,0 +1,148 @@
+"""
+This is the Continue configuration file.
+
+See https://continue.dev/docs/customization to learn more.
+"""
+
+import subprocess
+
+from continuedev.src.continuedev.core.main import Step
+from continuedev.src.continuedev.core.sdk import ContinueSDK
+from continuedev.src.continuedev.core.models import Models
+from continuedev.src.continuedev.core.config import CustomCommand, SlashCommand, ContinueConfig
+from continuedev.src.continuedev.plugins.context_providers.github import GitHubIssuesContextProvider
+from continuedev.src.continuedev.plugins.context_providers.google import GoogleContextProvider
+from continuedev.src.continuedev.plugins.policies.default import DefaultPolicy
+from continuedev.src.continuedev.libs.llm.openai import OpenAI, OpenAIServerInfo
+from continuedev.src.continuedev.libs.llm.ggml import GGML
+
+from continuedev.src.continuedev.plugins.steps.open_config import OpenConfigStep
+from continuedev.src.continuedev.plugins.steps.clear_history import ClearHistoryStep
+from continuedev.src.continuedev.plugins.steps.feedback import FeedbackStep
+from continuedev.src.continuedev.plugins.steps.comment_code import CommentCodeStep
+from continuedev.src.continuedev.plugins.steps.share_session import ShareSessionStep
+from continuedev.src.continuedev.plugins.steps.main import EditHighlightedCodeStep
+from continuedev.src.continuedev.plugins.context_providers.search import SearchContextProvider
+from continuedev.src.continuedev.plugins.context_providers.diff import DiffContextProvider
+from continuedev.src.continuedev.plugins.context_providers.url import URLContextProvider
+
+class CommitMessageStep(Step):
+    """
+    This is a Step, the building block of Continue.
+    It can be used below as a slash command, so that
+    run will be called when you type '/commit'.
+    """
+    async def run(self, sdk: ContinueSDK):
+
+        # Get the root directory of the workspace
+        dir = sdk.ide.workspace_directory
+
+        # Run git diff in that directory
+        diff = subprocess.check_output(
+            ["git", "diff"], cwd=dir).decode("utf-8")
+
+        # Ask the LLM to write a commit message,
+        # and set it as the description of this step
+        self.description = await sdk.models.default.complete(
+            f"{diff}\n\nWrite a short, specific (less than 50 chars) commit message about the above changes:")
+
+
+config = ContinueConfig(
+
+    # If set to False, we will not collect any usage data
+    # See here to learn what anonymous data we collect: https://continue.dev/docs/telemetry
+    allow_anonymous_telemetry=True,
+
+    models = Models(
+        default = OpenAI(
+            api_key = "my-api-key",
+            model = "gpt-3.5-turbo",
+            openai_server_info = OpenAIServerInfo(
+                api_base = "http://localhost:8080",
+                model = "gpt-3.5-turbo"
+            )
+        )
+    ),
+    # Set a system message with information that the LLM should always keep in mind
+    # E.g. "Please give concise answers. Always respond in Spanish."
+    system_message=None,
+
+    # Set temperature to any value between 0 and 1. Higher values will make the LLM
+    # more creative, while lower values will make it more predictable.
+    temperature=0.5,
+
+    # Custom commands let you map a prompt to a shortened slash command
+    # They are like slash commands, but more easily defined - write just a prompt instead of a Step class
+    # Their output will always be in chat form
+    custom_commands=[
+        # CustomCommand(
+        #     name="test",
+        #     description="Write unit tests for the higlighted code",
+        #     prompt="Write a comprehensive set of unit tests for the selected code. It should setup, run tests that check for correctness including important edge cases, and teardown. Ensure that the tests are complete and sophisticated. Give the tests just as chat output, don't edit any file.",
+        # )
+    ],
+
+    # Slash commands let you run a Step from a slash command
+    slash_commands=[
+        # SlashCommand(
+        #     name="commit",
+        #     description="This is an example slash command. Use /config to edit it and create more",
+        #     step=CommitMessageStep,
+        # )
+        SlashCommand(
+            name="edit",
+            description="Edit code in the current file or the highlighted code",
+            step=EditHighlightedCodeStep,
+        ),
+        SlashCommand(
+            name="config",
+            description="Customize Continue - slash commands, LLMs, system message, etc.",
+            step=OpenConfigStep,
+        ),
+        SlashCommand(
+            name="comment",
+            description="Write comments for the current file or highlighted code",
+            step=CommentCodeStep,
+        ),
+        SlashCommand(
+            name="feedback",
+            description="Send feedback to improve Continue",
+            step=FeedbackStep,
+        ),
+        SlashCommand(
+            name="clear",
+            description="Clear step history",
+            step=ClearHistoryStep,
+        ),
+        SlashCommand(
+            name="share",
+            description="Download and share the session transcript",
+            step=ShareSessionStep,
+        )
+    ],
+
+    # Context providers let you quickly select context by typing '@'
+    # Uncomment the following to
+    # - quickly reference GitHub issues
+    # - show Google search results to the LLM
+    context_providers=[
+        # GitHubIssuesContextProvider(
+        #     repo_name="<your github username or organization>/<your repo name>",
+        #     auth_token="<your github auth token>"
+        # ),
+        # GoogleContextProvider(
+        #     serper_api_key="<your serper.dev api key>"
+        # )
+        SearchContextProvider(),
+        DiffContextProvider(),
+        URLContextProvider(
+            preset_urls = [
+                # Add any common urls you reference here so they appear in autocomplete
+            ]
+        )
+    ],
+
+    # Policies hold the main logic that decides which Step to take next
+    # You can use them to design agents, or deeply customize Continue
+    policy=DefaultPolicy()
+)

examples/continue/docker-compose.yml

@@ -0,0 +1,27 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    # As initially LocalAI will download the models defined in PRELOAD_MODELS
+    # you might need to tweak the healthcheck values here according to your network connection.
+    # Here we give a timespan of 20m to download all the required files.
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
+      interval: 1m
+      timeout: 20m
+      retries: 20
+    build:
+      context: ../../
+      dockerfile: Dockerfile
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+      # You can preload different models here as well.
+      # See: https://github.com/go-skynet/model-gallery
+      - 'PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}]'
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]

examples/discord-bot/.env.example

@@ -1,3 +1,6 @@
+# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
+# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
+
 OPENAI_API_KEY=x
 DISCORD_BOT_TOKEN=x
 DISCORD_CLIENT_ID=x

examples/discord-bot/models

@@ -1 +1 @@
-../chatbot-ui/models/
+../models

examples/functions/.env.example

@@ -1,7 +1,11 @@
+# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
+# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
+
 OPENAI_API_KEY=sk---anystringhere
 OPENAI_API_BASE=http://api:8080/v1
 # Models to preload at start
-# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings
+# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings,
+# see other options in the model gallery at https://github.com/go-skynet/model-gallery
 PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/openllama-7b-open-instruct.yaml", "name": "gpt-3.5-turbo"}]
 
 ## Change the default number of threads

examples/functions/README.md

@@ -10,9 +10,12 @@ git clone https://github.com/go-skynet/LocalAI
 
 cd LocalAI/examples/functions
 
+cp -rfv .env.example .env
+
+# Edit the .env file to set a different model by editing `PRELOAD_MODELS`.
+vim .env
+
 docker-compose run --rm functions
 ```
 
 Note: The example automatically downloads the `openllama` model as it is under a permissive license.
-
-See the `.env` configuration file to set a different model with the [model-gallery](https://github.com/go-skynet/model-gallery) by editing `PRELOAD_MODELS`.

examples/insomnia/README.md

@@ -0,0 +1,17 @@
+# Insomnia
+
+Developer Testing Request Collection for [Insomnia](https://insomnia.rest/), an open-source REST client
+
+## Instructions
+
+* Install Insomnia as normal
+* [Import](https://docs.insomnia.rest/insomnia/import-export-data) `Insomnia_LocalAI.json`
+* Control + E opens the environment settings - 
+
+| **Parameter Name** | **Default Value** | **Description**                          |
+|--------------------|-------------------|------------------------------------------|
+| HOST               | localhost         | LocalAI base URL                         |
+| PORT               | 8080              | LocalAI port                             |
+| DEFAULT_MODEL      | gpt-3.5-turbo     | Name of the model used on most requests. |
+
+** you may want to duplicate localhost into a "Private" environment to avoid saving private settings back to this file **

examples/langchain-chroma/.env.example

@@ -1,3 +1,6 @@
+# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
+# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
+
 THREADS=4
 CONTEXT_SIZE=512
 MODELS_PATH=/models

examples/langchain-chroma/models

@@ -0,0 +1 @@
+../models

examples/langchain-chroma/models/completion.tmpl

@@ -1 +0,0 @@
-{{.Input}}

examples/langchain-chroma/models/gpt-3.5-turbo.yaml

@@ -1,16 +0,0 @@
-name: gpt-3.5-turbo
-parameters:
-  model: ggml-gpt4all-j
-  top_k: 80
-  temperature: 0.2
-  top_p: 0.7
-context_size: 1024
-stopwords:
-- "HUMAN:"
-- "GPT:"
-roles:
-  user: " "
-  system: " "
-template:
-  completion: completion
-  chat: gpt4all

examples/langchain-chroma/models/gpt4all.tmpl

@@ -1,4 +0,0 @@
-The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.
-### Prompt:
-{{.Input}}
-### Response:

examples/langchain-huggingface/models

@@ -0,0 +1 @@
+../models