inital pass at replacing ":" with "-" in image on-disk names

---------

Co-authored-by: Chris-AS1 <8493773+Chris-AS1@users.noreply.github.com>

.dockerignore

@@ -1,7 +1,9 @@
-build
-llama/build
-.venv
 .vscode
 ollama
 app
-web
+macapp
+dist
+llm/llama.cpp
+.env
+.cache
+test_data

.github/workflows/test.yaml

@@ -0,0 +1,177 @@
+name: test
+
+on:
+  pull_request:
+    paths:
+      - '**/*'
+      - '!docs/**'
+      - '!examples/**'
+      - '!README.md'
+
+jobs:
+  generate:
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-2019]
+        arch: [amd64, arm64]
+        exclude:
+          - os: ubuntu-latest
+            arch: arm64
+          - os: windows-2019
+            arch: arm64
+    runs-on: ${{ matrix.os }}
+    env:
+      GOARCH: ${{ matrix.arch }}
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-go@v5
+        with:
+          go-version: '1.22'
+          cache: true
+      - run: go get ./...
+      - run: |
+          $gopath=(get-command go).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$env:PATH"
+          go generate -x ./...
+        if: ${{ startsWith(matrix.os, 'windows-') }}
+        name: "Windows Go Generate"
+      - run: go generate -x ./...
+        if: ${{ ! startsWith(matrix.os, 'windows-') }}
+        name: "Unix Go Generate"
+      - uses: actions/upload-artifact@v4
+        with:
+          name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
+          path: llm/llama.cpp/build/**/lib/*
+  generate-cuda:
+    strategy:
+      matrix:
+        cuda-version:
+          - '11.8.0'
+    runs-on: linux
+    container: nvidia/cuda:${{ matrix.cuda-version }}-devel-ubuntu20.04
+    steps:
+      - run: |
+          apt-get update && apt-get install -y git build-essential curl
+          curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.28.1/cmake-3.28.1-linux-x86_64.tar.gz \
+            | tar -zx -C /usr --strip-components 1
+        env:
+          DEBIAN_FRONTEND: noninteractive
+      - uses: actions/checkout@v4
+      - uses: actions/setup-go@v4
+        with:
+          go-version: '1.22'
+          cache: true
+      - run: go get ./...
+      - run: |
+          git config --global --add safe.directory /__w/ollama/ollama
+          go generate -x ./...
+        env:
+          OLLAMA_SKIP_CPU_GENERATE: '1'
+      - uses: actions/upload-artifact@v4
+        with:
+          name: cuda-${{ matrix.cuda-version }}-libraries
+          path: llm/llama.cpp/build/**/lib/*
+  generate-rocm:
+    strategy:
+      matrix:
+        rocm-version:
+          - '6.0'
+    runs-on: linux
+    container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
+    steps:
+      - run: |
+          apt-get update && apt-get install -y git build-essential curl rocm-libs
+          curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.28.1/cmake-3.28.1-linux-x86_64.tar.gz \
+            | tar -zx -C /usr --strip-components 1
+        env:
+          DEBIAN_FRONTEND: noninteractive
+      - uses: actions/checkout@v4
+      - uses: actions/setup-go@v4
+        with:
+          go-version: '1.22'
+          cache: true
+      - run: go get ./...
+      - run: |
+          git config --global --add safe.directory /__w/ollama/ollama
+          go generate -x ./...
+        env:
+          OLLAMA_SKIP_CPU_GENERATE: '1'
+      - uses: actions/upload-artifact@v4
+        with:
+          name: rocm-${{ matrix.rocm-version }}-libraries
+          path: llm/llama.cpp/build/**/lib/*
+  lint:
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-2019]
+        arch: [amd64, arm64]
+        exclude:
+          - os: ubuntu-latest
+            arch: arm64
+          - os: windows-2019
+            arch: arm64
+          - os: macos-latest
+            arch: amd64
+    runs-on: ${{ matrix.os }}
+    env:
+      GOARCH: ${{ matrix.arch }}
+      CGO_ENABLED: '1'
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - uses: actions/setup-go@v5
+        with:
+          go-version: '1.22'
+          cache: false
+      - run: |
+          mkdir -p llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/
+          touch llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/stub.so
+        if: ${{ startsWith(matrix.os, 'ubuntu-') }}
+      - run: |
+          mkdir -p llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/
+          touch llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/stub.dylib
+          touch llm/llama.cpp/ggml-metal.metal
+        if: ${{ startsWith(matrix.os, 'macos-') }}
+      - run: |
+          mkdir -p llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/
+          touch llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/stub.dll
+        if: ${{ startsWith(matrix.os, 'windows-') }}
+      - uses: golangci/golangci-lint-action@v3
+  test:
+    needs: generate
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-2019]
+        arch: [amd64]
+        exclude:
+          - os: ubuntu-latest
+            arch: arm64
+          - os: windows-2019
+            arch: arm64
+    runs-on: ${{ matrix.os }}
+    env:
+      GOARCH: ${{ matrix.arch }}
+      CGO_ENABLED: '1'
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - uses: actions/setup-go@v5
+        with:
+          go-version: '1.22'
+          cache: true
+      - run: go get
+      - uses: actions/download-artifact@v4
+        with:
+          name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
+          path: llm/llama.cpp/build
+      - run: go build
+      - run: go test -v ./...
+      - uses: actions/upload-artifact@v4
+        with:
+          name: ${{ matrix.os }}-binaries
+          path: ollama

.gitignore

@@ -5,3 +5,9 @@
 .swp
 dist
 ollama
+ggml-metal.metal
+.cache
+*.exe
+.idea
+test_data
+*.crt

.gitmodules

@@ -0,0 +1,4 @@
+[submodule "llama.cpp"]
+	path = llm/llama.cpp
+	url = https://github.com/ggerganov/llama.cpp.git
+	shallow = true

.golangci.yaml

@@ -0,0 +1,27 @@
+run:
+  timeout: 5m
+linters:
+  enable:
+    - asasalint
+    - bidichk
+    - bodyclose
+    - containedctx
+    - contextcheck
+    - exportloopref
+    - gocheckcompilerdirectives
+    # FIXME: for some reason this errors on windows
+    # - gofmt
+    # - goimports
+    - misspell
+    - nilerr
+    - unused
+linters-settings:
+  errcheck:
+    # exclude the following functions since we don't generally
+    # need to be concerned with the returned errors
+    exclude-functions:
+      - encoding/binary.Read
+      - (*os.File).Seek
+      - (*bufio.Writer).WriteString
+      - (*github.com/spf13/pflag.FlagSet).Set
+      - (*github.com/jmorganca/ollama/llm.readSeekOffset).Seek

Dockerfile

@@ -1,15 +1,135 @@
-FROM golang:1.20
+ARG GOLANG_VERSION=1.22.1
+ARG CMAKE_VERSION=3.22.1
+ARG CUDA_VERSION=11.3.1
+ARG ROCM_VERSION=6.0
+
+# Copy the minimal context we need to run the generate scripts
+FROM scratch AS llm-code
+COPY .git .git
+COPY .gitmodules .gitmodules
+COPY llm llm
+
+FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION-devel-centos7 AS cuda-build-amd64
+ARG CMAKE_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
+WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+ARG CGO_CFLAGS
+RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
+
+FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION-devel-rockylinux8 AS cuda-build-arm64
+ARG CMAKE_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
+WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+ARG CGO_CFLAGS
+RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
+
+FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS rocm-build-amd64
+ARG CMAKE_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+ENV LIBRARY_PATH /opt/amdgpu/lib64
+COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
+WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+ARG CGO_CFLAGS
+ARG AMDGPU_TARGETS
+RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
+RUN mkdir /tmp/scratch && \
+    for dep in $(cat /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/x86_64/rocm*/lib/deps.txt) ; do \
+        cp ${dep} /tmp/scratch/ || exit 1 ; \
+    done && \
+    (cd /opt/rocm/lib && tar cf - rocblas/library) | (cd /tmp/scratch/ && tar xf - ) && \
+    mkdir -p /go/src/github.com/jmorganca/ollama/dist/deps/ && \
+    (cd /tmp/scratch/ && tar czvf /go/src/github.com/jmorganca/ollama/dist/deps/ollama-linux-amd64-rocm.tgz . )
+
+
+FROM --platform=linux/amd64 centos:7 AS cpu-builder-amd64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
+ARG OLLAMA_CUSTOM_CPU_DEFS
+ARG CGO_CFLAGS
+WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+
+FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
+RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
+FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
+RUN OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
+FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
+RUN OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
+
+FROM --platform=linux/arm64 centos:7 AS cpu-build-arm64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
+WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+# Note, we only build the "base" CPU variant on arm since avx/avx2 are x86 features
+ARG OLLAMA_CUSTOM_CPU_DEFS
+ARG CGO_CFLAGS
+RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
+
+# Intermediate stage used for ./scripts/build_linux.sh
+FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
+ENV CGO_ENABLED 1
 WORKDIR /go/src/github.com/jmorganca/ollama
 COPY . .
-RUN CGO_ENABLED=1 go build -ldflags '-linkmode external -extldflags "-static"' .
+COPY --from=cpu_avx-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+COPY --from=cpu_avx2-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+COPY --from=cuda-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+COPY --from=rocm-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+COPY --from=rocm-build-amd64 /go/src/github.com/jmorganca/ollama/dist/deps/ ./dist/deps/
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN go build -trimpath .
 
-FROM alpine
-COPY --from=0 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
+# Intermediate stage used for ./scripts/build_linux.sh
+FROM --platform=linux/arm64 cpu-build-arm64 AS build-arm64
+ENV CGO_ENABLED 1
+ARG GOLANG_VERSION
+WORKDIR /go/src/github.com/jmorganca/ollama
+COPY . .
+COPY --from=cuda-build-arm64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN go build -trimpath .
+
+# Runtime stages
+FROM --platform=linux/amd64 ubuntu:22.04 as runtime-amd64
+RUN apt-get update && apt-get install -y ca-certificates
+COPY --from=build-amd64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
+FROM --platform=linux/arm64 ubuntu:22.04 as runtime-arm64
+RUN apt-get update && apt-get install -y ca-certificates
+COPY --from=build-arm64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
+
+# Radeon images are much larger so we keep it distinct from the CPU/CUDA image
+FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete as runtime-rocm
+RUN update-pciids
+COPY --from=build-amd64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
 EXPOSE 11434
-ARG USER=ollama
-ARG GROUP=ollama
-RUN addgroup -g 1000 $GROUP && adduser -u 1000 -DG $GROUP $USER
-USER $USER:$GROUP
-ENTRYPOINT ["/bin/ollama"]
 ENV OLLAMA_HOST 0.0.0.0
+
+ENTRYPOINT ["/bin/ollama"]
+CMD ["serve"]
+
+FROM runtime-$TARGETARCH
+EXPOSE 11434
+ENV OLLAMA_HOST 0.0.0.0
+ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
+ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
+ENV NVIDIA_VISIBLE_DEVICES=all
+
+ENTRYPOINT ["/bin/ollama"]
 CMD ["serve"]

README.md

@@ -1,27 +1,41 @@
 <div align="center">
-  <picture>
-    <source media="(prefers-color-scheme: dark)" height="200px" srcset="https://github.com/jmorganca/ollama/assets/3325447/56ea1849-1284-4645-8970-956de6e51c3c">
-    <img alt="logo" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
-  </picture>
+  <img alt="ollama" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
 </div>
 
 # Ollama
 
 [![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
 
-> Note: Ollama is in early preview. Please report any issues you find.
+Get up and running with large language models locally.
 
-Run, create, and share large language models (LLMs).
+### macOS
 
-## Download
+[Download](https://ollama.com/download/Ollama-darwin.zip)
 
-- [Download](https://ollama.ai/download) for macOS on Apple Silicon (Intel coming soon)
-- Download for Windows and Linux (coming soon)
-- Build [from source](#building)
+### Windows preview
+
+[Download](https://ollama.com/download/OllamaSetup.exe)
+
+### Linux
+
+```
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
+
+### Docker
+
+The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `ollama/ollama` is available on Docker Hub.
+
+### Libraries
+
+- [ollama-python](https://github.com/ollama/ollama-python)
+- [ollama-js](https://github.com/ollama/ollama-js)
 
 ## Quickstart
 
-To run and chat with [Llama 2](https://ai.meta.com/llama), the new model by Meta:
+To run and chat with [Llama 2](https://ollama.com/library/llama2):
 
 ```
 ollama run llama2
@@ -29,32 +43,61 @@ ollama run llama2
 
 ## Model library
 
-`ollama` includes a library of open-source models:
+Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
 
-| Model                    | Parameters | Size  | Download                    |
-| ------------------------ | ---------- | ----- | --------------------------- |
-| Llama2                   | 7B         | 3.8GB | `ollama pull llama2`        |
-| Llama2 13B               | 13B        | 7.3GB | `ollama pull llama2:13b`    |
-| Orca Mini                | 3B         | 1.9GB | `ollama pull orca`          |
-| Vicuna                   | 7B         | 3.8GB | `ollama pull vicuna`        |
-| Nous-Hermes              | 13B        | 7.3GB | `ollama pull nous-hermes`   |
-| Wizard Vicuna Uncensored | 13B        | 7.3GB | `ollama pull wizard-vicuna` |
+Here are some example models that can be downloaded:
 
-> Note: You should have at least 8 GB of RAM to run the 3B models, 16 GB to run the 7B models, and 32 GB to run the 13B models.
+| Model              | Parameters | Size  | Download                       |
+| ------------------ | ---------- | ----- | ------------------------------ |
+| Llama 2            | 7B         | 3.8GB | `ollama run llama2`            |
+| Mistral            | 7B         | 4.1GB | `ollama run mistral`           |
+| Dolphin Phi        | 2.7B       | 1.6GB | `ollama run dolphin-phi`       |
+| Phi-2              | 2.7B       | 1.7GB | `ollama run phi`               |
+| Neural Chat        | 7B         | 4.1GB | `ollama run neural-chat`       |
+| Starling           | 7B         | 4.1GB | `ollama run starling-lm`       |
+| Code Llama         | 7B         | 3.8GB | `ollama run codellama`         |
+| Llama 2 Uncensored | 7B         | 3.8GB | `ollama run llama2-uncensored` |
+| Llama 2 13B        | 13B        | 7.3GB | `ollama run llama2:13b`        |
+| Llama 2 70B        | 70B        | 39GB  | `ollama run llama2:70b`        |
+| Orca Mini          | 3B         | 1.9GB | `ollama run orca-mini`         |
+| Vicuna             | 7B         | 3.8GB | `ollama run vicuna`            |
+| LLaVA              | 7B         | 4.5GB | `ollama run llava`             |
+| Gemma              | 2B         | 1.4GB | `ollama run gemma:2b`          |
+| Gemma              | 7B         | 4.8GB | `ollama run gemma:7b`          |
 
-## Examples
+> Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
 
-### Run a model
+## Customize a model
 
-```
-ollama run llama2
->>> hi
-Hello! How can I help you today?
-```
+### Import from GGUF
 
-### Create a custom model
+Ollama supports importing GGUF models in the Modelfile:
 
-Pull a base model:
+1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import.
+
+   ```
+   FROM ./vicuna-33b.Q4_0.gguf
+   ```
+
+2. Create the model in Ollama
+
+   ```
+   ollama create example -f Modelfile
+   ```
+
+3. Run the model
+
+   ```
+   ollama run example
+   ```
+
+### Import from PyTorch or Safetensors
+
+See the [guide](docs/import.md) on importing models for more information.
+
+### Customize a prompt
+
+Models from the Ollama library can be customized with a prompt. For example, to customize the `llama2` model:
 
 ```
 ollama pull llama2
@@ -68,7 +111,7 @@ FROM llama2
 # set the temperature to 1 [higher is more creative, lower is more coherent]
 PARAMETER temperature 1
 
-# set the system prompt
+# set the system message
 SYSTEM """
 You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
 """
@@ -83,44 +126,104 @@ ollama run mario
 Hello! It's your friend Mario.
 ```
 
-For more examples, see the [examples](./examples) directory.
+For more examples, see the [examples](examples) directory. For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
 
-### Pull a model from the registry
+## CLI Reference
+
+### Create a model
+
+`ollama create` is used to create a model from a Modelfile.
 
 ```
-ollama pull orca
+ollama create mymodel -f ./Modelfile
 ```
 
-### Listing local models
+### Pull a model
+
+```
+ollama pull llama2
+```
+
+> This command can also be used to update a local model. Only the diff will be pulled.
+
+### Remove a model
+
+```
+ollama rm llama2
+```
+
+### Copy a model
+
+```
+ollama cp llama2 my-llama2
+```
+
+### Multiline input
+
+For multiline input, you can wrap text with `"""`:
+
+```
+>>> """Hello,
+... world!
+... """
+I'm a basic program that prints the famous "Hello, world!" message to the console.
+```
+
+### Multimodal models
+
+```
+>>> What's in this image? /Users/jmorgan/Desktop/smile.png
+The image features a yellow smiley face, which is likely the central focus of the picture.
+```
+
+### Pass in prompt as arguments
+
+```
+$ ollama run llama2 "Summarize this file: $(cat README.md)"
+ Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
+```
+
+### List models on your computer
 
 ```
 ollama list
 ```
 
-## Model packages
+### Start Ollama
 
-### Overview
-
-Ollama bundles model weights, configuration, and data into a single package, defined by a [Modelfile](./docs/modelfile.md).
-
-<picture>
-  <source media="(prefers-color-scheme: dark)" height="480" srcset="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
-  <img alt="logo" height="480" src="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
-</picture>
+`ollama serve` is used when you want to start ollama without running the desktop application.
 
 ## Building
 
+Install `cmake` and `go`:
+
+```
+brew install cmake go
+```
+
+Then generate dependencies:
+
+```
+go generate ./...
+```
+
+Then build the binary:
+
 ```
 go build .
 ```
 
-To run it start the server:
+More detailed instructions can be found in the [developer guide](https://github.com/jmorganca/ollama/blob/main/docs/development.md)
+
+### Running local builds
+
+Next, start the server:
 
 ```
-./ollama serve &
+./ollama serve
 ```
 
-Finally, run a model!
+Finally, in a separate shell, run a model:
 
 ```
 ./ollama run llama2
@@ -128,10 +231,128 @@ Finally, run a model!
 
 ## REST API
 
-### `POST /api/generate`
+Ollama has a REST API for running and managing models.
 
-Generate text from a model.
+### Generate a response
 
 ```
-curl -X POST http://localhost:11434/api/generate -d '{"model": "llama2", "prompt":"Why is the sky blue?"}'
+curl http://localhost:11434/api/generate -d '{
+  "model": "llama2",
+  "prompt":"Why is the sky blue?"
+}'
 ```
+
+### Chat with a model
+
+```
+curl http://localhost:11434/api/chat -d '{
+  "model": "mistral",
+  "messages": [
+    { "role": "user", "content": "why is the sky blue?" }
+  ]
+}'
+```
+
+See the [API documentation](./docs/api.md) for all endpoints.
+
+## Community Integrations
+
+### Web & Desktop
+
+- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
+- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
+- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
+- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
+- [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
+- [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
+- [Open WebUI](https://github.com/open-webui/open-webui)
+- [Ollamac](https://github.com/kevinhermawan/Ollamac)
+- [big-AGI](https://github.com/enricoros/big-AGI/blob/main/docs/config-local-ollama.md)
+- [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core)
+- [Amica](https://github.com/semperai/amica)
+- [chatd](https://github.com/BruceMacD/chatd)
+- [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
+- [MindMac](https://mindmac.app)
+- [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui)
+- [Msty](https://msty.app)
+- [Chatbox](https://github.com/Bin-Huang/Chatbox)
+- [WinForm Ollama Copilot](https://github.com/tgraupmann/WinForm_Ollama_Copilot)
+- [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) with [Get Started Doc](https://docs.nextchat.dev/models/ollama)
+- [Odin Runes](https://github.com/leonid20000/OdinRunes)
+- [LLM-X: Progressive Web App](https://github.com/mrdjohnson/llm-x)
+
+### Terminal
+
+- [oterm](https://github.com/ggozad/oterm)
+- [Ellama Emacs client](https://github.com/s-kostyaev/ellama)
+- [Emacs client](https://github.com/zweifisch/ollama)
+- [gen.nvim](https://github.com/David-Kunz/gen.nvim)
+- [ollama.nvim](https://github.com/nomnivore/ollama.nvim)
+- [ollama-chat.nvim](https://github.com/gerazov/ollama-chat.nvim)
+- [ogpt.nvim](https://github.com/huynle/ogpt.nvim)
+- [gptel Emacs client](https://github.com/karthink/gptel)
+- [Oatmeal](https://github.com/dustinblackman/oatmeal)
+- [cmdh](https://github.com/pgibler/cmdh)
+- [tenere](https://github.com/pythops/tenere)
+- [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
+- [ShellOracle](https://github.com/djcopley/ShellOracle)
+
+### Database
+
+- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md)
+
+### Package managers
+
+- [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
+- [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
+
+### Libraries
+
+- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
+- [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
+- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
+- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
+- [LangChain4j](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-ollama)
+- [LiteLLM](https://github.com/BerriAI/litellm)
+- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
+- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
+- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
+- [Ollama4j for Java](https://github.com/amithkoujalgi/ollama4j)
+- [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama)
+- [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit)
+- [Ollama for Dart](https://github.com/breitburg/dart-ollama)
+- [Ollama for Laravel](https://github.com/cloudstudio/ollama-laravel)
+- [LangChainDart](https://github.com/davidmigloz/langchain_dart)
+- [Semantic Kernel - Python](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama)
+- [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md)
+- [Elixir LangChain](https://github.com/brainlid/langchain)
+- [Ollama for R - rollama](https://github.com/JBGruber/rollama)
+- [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
+- [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama)
+
+### Mobile
+
+- [Enchanted](https://github.com/AugustDev/enchanted)
+- [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
+
+### Extensions & Plugins
+
+- [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama)
+- [Discollama](https://github.com/mxyng/discollama) (Discord bot inside the Ollama discord channel)
+- [Continue](https://github.com/continuedev/continue)
+- [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama)
+- [Logseq Ollama plugin](https://github.com/omagdy7/ollama-logseq)
+- [NotesOllama](https://github.com/andersrex/notesollama) (Apple Notes Ollama plugin)
+- [Dagger Chatbot](https://github.com/samalba/dagger-chatbot)
+- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot)
+- [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram)
+- [Hass Ollama Conversation](https://github.com/ej52/hass-ollama-conversation)
+- [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama)
+- [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
+- [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot)
+- [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot)
+- [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
+- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
+- [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
+- [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and HuggingFace)
+- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)

api/client.go

@@ -5,20 +5,27 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
+	"errors"
 	"fmt"
 	"io"
+	"net"
 	"net/http"
 	"net/url"
+	"os"
+	"runtime"
+	"strings"
+
+	"github.com/jmorganca/ollama/format"
+	"github.com/jmorganca/ollama/version"
 )
 
 type Client struct {
-	base    url.URL
-	HTTP    http.Client
-	Headers http.Header
+	base *url.URL
+	http *http.Client
 }
 
 func checkError(resp *http.Response, body []byte) error {
-	if resp.StatusCode >= 200 && resp.StatusCode < 400 {
+	if resp.StatusCode < http.StatusBadRequest {
 		return nil
 	}
 
@@ -33,45 +40,72 @@ func checkError(resp *http.Response, body []byte) error {
 	return apiError
 }
 
-func NewClient(hosts ...string) *Client {
-	host := "127.0.0.1:11434"
-	if len(hosts) > 0 {
-		host = hosts[0]
+func ClientFromEnvironment() (*Client, error) {
+	defaultPort := "11434"
+
+	scheme, hostport, ok := strings.Cut(os.Getenv("OLLAMA_HOST"), "://")
+	switch {
+	case !ok:
+		scheme, hostport = "http", os.Getenv("OLLAMA_HOST")
+	case scheme == "http":
+		defaultPort = "80"
+	case scheme == "https":
+		defaultPort = "443"
+	}
+
+	// trim trailing slashes
+	hostport = strings.TrimRight(hostport, "/")
+
+	host, port, err := net.SplitHostPort(hostport)
+	if err != nil {
+		host, port = "127.0.0.1", defaultPort
+		if ip := net.ParseIP(strings.Trim(hostport, "[]")); ip != nil {
+			host = ip.String()
+		} else if hostport != "" {
+			host = hostport
+		}
 	}
 
 	return &Client{
-		base: url.URL{Scheme: "http", Host: host},
-		HTTP: http.Client{},
-	}
+		base: &url.URL{
+			Scheme: scheme,
+			Host:   net.JoinHostPort(host, port),
+		},
+		http: http.DefaultClient,
+	}, nil
 }
 
 func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {
 	var reqBody io.Reader
 	var data []byte
 	var err error
-	if reqData != nil {
+
+	switch reqData := reqData.(type) {
+	case io.Reader:
+		// reqData is already an io.Reader
+		reqBody = reqData
+	case nil:
+		// noop
+	default:
 		data, err = json.Marshal(reqData)
 		if err != nil {
 			return err
 		}
+
 		reqBody = bytes.NewReader(data)
 	}
 
-	url := c.base.JoinPath(path).String()
-
-	req, err := http.NewRequestWithContext(ctx, method, url, reqBody)
+	requestURL := c.base.JoinPath(path)
+	request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), reqBody)
 	if err != nil {
 		return err
 	}
 
-	req.Header.Set("Content-Type", "application/json")
-	req.Header.Set("Accept", "application/json")
+	request.Header.Set("Content-Type", "application/json")
+	request.Header.Set("Accept", "application/json")
+	request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
 
-	for k, v := range c.Headers {
-		req.Header[k] = v
-	}
-
-	respObj, err := c.HTTP.Do(req)
+	respObj, err := c.http.Do(request)
 	if err != nil {
 		return err
 	}
@@ -94,6 +128,8 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	return nil
 }
 
+const maxBufferSize = 512 * format.KiloByte
+
 func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
 	var buf *bytes.Buffer
 	if data != nil {
@@ -105,21 +141,26 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 		buf = bytes.NewBuffer(bts)
 	}
 
-	request, err := http.NewRequestWithContext(ctx, method, c.base.JoinPath(path).String(), buf)
+	requestURL := c.base.JoinPath(path)
+	request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), buf)
 	if err != nil {
 		return err
 	}
 
 	request.Header.Set("Content-Type", "application/json")
-	request.Header.Set("Accept", "application/json")
+	request.Header.Set("Accept", "application/x-ndjson")
+	request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
 
-	response, err := http.DefaultClient.Do(request)
+	response, err := c.http.Do(request)
 	if err != nil {
 		return err
 	}
 	defer response.Body.Close()
 
 	scanner := bufio.NewScanner(response.Body)
+	// increase the buffer size to avoid running out of space
+	scanBuf := make([]byte, 0, maxBufferSize)
+	scanner.Buffer(scanBuf, maxBufferSize)
 	for scanner.Scan() {
 		var errorResponse struct {
 			Error string `json:"error,omitempty"`
@@ -131,10 +172,10 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 		}
 
 		if errorResponse.Error != "" {
-			return fmt.Errorf("stream: %s", errorResponse.Error)
+			return fmt.Errorf(errorResponse.Error)
 		}
 
-		if response.StatusCode >= 400 {
+		if response.StatusCode >= http.StatusBadRequest {
 			return StatusError{
 				StatusCode:   response.StatusCode,
 				Status:       response.Status,
@@ -163,6 +204,19 @@ func (c *Client) Generate(ctx context.Context, req *GenerateRequest, fn Generate
 	})
 }
 
+type ChatResponseFunc func(ChatResponse) error
+
+func (c *Client) Chat(ctx context.Context, req *ChatRequest, fn ChatResponseFunc) error {
+	return c.stream(ctx, http.MethodPost, "/api/chat", req, func(bts []byte) error {
+		var resp ChatResponse
+		if err := json.Unmarshal(bts, &resp); err != nil {
+			return err
+		}
+
+		return fn(resp)
+	})
+}
+
 type PullProgressFunc func(ProgressResponse) error
 
 func (c *Client) Pull(ctx context.Context, req *PullRequest, fn PullProgressFunc) error {
@@ -189,11 +243,11 @@ func (c *Client) Push(ctx context.Context, req *PushRequest, fn PushProgressFunc
 	})
 }
 
-type CreateProgressFunc func(CreateProgress) error
+type CreateProgressFunc func(ProgressResponse) error
 
 func (c *Client) Create(ctx context.Context, req *CreateRequest, fn CreateProgressFunc) error {
 	return c.stream(ctx, http.MethodPost, "/api/create", req, func(bts []byte) error {
-		var resp CreateProgress
+		var resp ProgressResponse
 		if err := json.Unmarshal(bts, &resp); err != nil {
 			return err
 		}
@@ -210,9 +264,65 @@ func (c *Client) List(ctx context.Context) (*ListResponse, error) {
 	return &lr, nil
 }
 
+func (c *Client) Copy(ctx context.Context, req *CopyRequest) error {
+	if err := c.do(ctx, http.MethodPost, "/api/copy", req, nil); err != nil {
+		return err
+	}
+	return nil
+}
+
 func (c *Client) Delete(ctx context.Context, req *DeleteRequest) error {
 	if err := c.do(ctx, http.MethodDelete, "/api/delete", req, nil); err != nil {
 		return err
 	}
 	return nil
 }
+
+func (c *Client) Show(ctx context.Context, req *ShowRequest) (*ShowResponse, error) {
+	var resp ShowResponse
+	if err := c.do(ctx, http.MethodPost, "/api/show", req, &resp); err != nil {
+		return nil, err
+	}
+	return &resp, nil
+}
+
+func (c *Client) Heartbeat(ctx context.Context) error {
+	if err := c.do(ctx, http.MethodHead, "/", nil, nil); err != nil {
+		return err
+	}
+	return nil
+}
+func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*EmbeddingResponse, error) {
+	var resp EmbeddingResponse
+	if err := c.do(ctx, http.MethodPost, "/api/embeddings", req, &resp); err != nil {
+		return nil, err
+	}
+	return &resp, nil
+}
+
+func (c *Client) CreateBlob(ctx context.Context, digest string, r io.Reader) error {
+	if err := c.do(ctx, http.MethodHead, fmt.Sprintf("/api/blobs/%s", digest), nil, nil); err != nil {
+		var statusError StatusError
+		if !errors.As(err, &statusError) || statusError.StatusCode != http.StatusNotFound {
+			return err
+		}
+
+		if err := c.do(ctx, http.MethodPost, fmt.Sprintf("/api/blobs/%s", digest), r, nil); err != nil {
+			return err
+		}
+	}
+
+	return nil
+}
+
+func (c *Client) Version(ctx context.Context) (string, error) {
+	var version struct {
+		Version string `json:"version"`
+	}
+
+	if err := c.do(ctx, http.MethodGet, "/api/version", nil, &version); err != nil {
+		return "", err
+	}
+
+	return version.Version, nil
+}

api/client_test.go

@@ -0,0 +1,43 @@
+package api
+
+import "testing"
+
+func TestClientFromEnvironment(t *testing.T) {
+	type testCase struct {
+		value  string
+		expect string
+		err    error
+	}
+
+	testCases := map[string]*testCase{
+		"empty":                      {value: "", expect: "http://127.0.0.1:11434"},
+		"only address":               {value: "1.2.3.4", expect: "http://1.2.3.4:11434"},
+		"only port":                  {value: ":1234", expect: "http://:1234"},
+		"address and port":           {value: "1.2.3.4:1234", expect: "http://1.2.3.4:1234"},
+		"scheme http and address":    {value: "http://1.2.3.4", expect: "http://1.2.3.4:80"},
+		"scheme https and address":   {value: "https://1.2.3.4", expect: "https://1.2.3.4:443"},
+		"scheme, address, and port":  {value: "https://1.2.3.4:1234", expect: "https://1.2.3.4:1234"},
+		"hostname":                   {value: "example.com", expect: "http://example.com:11434"},
+		"hostname and port":          {value: "example.com:1234", expect: "http://example.com:1234"},
+		"scheme http and hostname":   {value: "http://example.com", expect: "http://example.com:80"},
+		"scheme https and hostname":  {value: "https://example.com", expect: "https://example.com:443"},
+		"scheme, hostname, and port": {value: "https://example.com:1234", expect: "https://example.com:1234"},
+		"trailing slash":             {value: "example.com/", expect: "http://example.com:11434"},
+		"trailing slash port":        {value: "example.com:1234/", expect: "http://example.com:1234"},
+	}
+
+	for k, v := range testCases {
+		t.Run(k, func(t *testing.T) {
+			t.Setenv("OLLAMA_HOST", v.value)
+
+			client, err := ClientFromEnvironment()
+			if err != v.err {
+				t.Fatalf("expected %s, got %s", v.err, err)
+			}
+
+			if client.base.String() != v.expect {
+				t.Fatalf("expected %s, got %s", v.expect, client.base.String())
+			}
+		})
+	}
+}

api/types.go

@@ -1,9 +1,13 @@
 package api
 
 import (
+	"encoding/json"
 	"fmt"
+	"math"
 	"os"
-	"runtime"
+	"reflect"
+	"strconv"
+	"strings"
 	"time"
 )
 
@@ -27,160 +31,461 @@ func (e StatusError) Error() string {
 	}
 }
 
+type ImageData []byte
+
 type GenerateRequest struct {
-	Model   string `json:"model"`
-	Prompt  string `json:"prompt"`
-	Context []int  `json:"context,omitempty"`
+	Model     string      `json:"model"`
+	Prompt    string      `json:"prompt"`
+	System    string      `json:"system"`
+	Template  string      `json:"template"`
+	Context   []int       `json:"context,omitempty"`
+	Stream    *bool       `json:"stream,omitempty"`
+	Raw       bool        `json:"raw,omitempty"`
+	Format    string      `json:"format"`
+	KeepAlive *Duration   `json:"keep_alive,omitempty"`
+	Images    []ImageData `json:"images,omitempty"`
 
-	Options `json:"options"`
+	Options map[string]interface{} `json:"options"`
 }
 
-type CreateRequest struct {
-	Name string `json:"name"`
-	Path string `json:"path"`
+type ChatRequest struct {
+	Model     string    `json:"model"`
+	Messages  []Message `json:"messages"`
+	Stream    *bool     `json:"stream,omitempty"`
+	Format    string    `json:"format"`
+	KeepAlive *Duration `json:"keep_alive,omitempty"`
+
+	Options map[string]interface{} `json:"options"`
 }
 
-type CreateProgress struct {
-	Status string `json:"status"`
+type Message struct {
+	Role    string      `json:"role"` // one of ["system", "user", "assistant"]
+	Content string      `json:"content"`
+	Images  []ImageData `json:"images,omitempty"`
 }
 
-type DeleteRequest struct {
-	Name string `json:"name"`
-}
-
-type PullRequest struct {
-	Name     string `json:"name"`
-	Insecure bool   `json:"insecure,omitempty"`
-	Username string `json:"username"`
-	Password string `json:"password"`
-}
-
-type ProgressResponse struct {
-	Status    string `json:"status"`
-	Digest    string `json:"digest,omitempty"`
-	Total     int    `json:"total,omitempty"`
-	Completed int    `json:"completed,omitempty"`
-}
-
-type PushRequest struct {
-	Name     string `json:"name"`
-	Insecure bool   `json:"insecure,omitempty"`
-	Username string `json:"username"`
-	Password string `json:"password"`
-}
-
-type ListResponse struct {
-	Models []ListResponseModel `json:"models"`
-}
-
-type ListResponseModel struct {
-	Name       string    `json:"name"`
-	ModifiedAt time.Time `json:"modified_at"`
-	Size       int       `json:"size"`
-}
-
-type GenerateResponse struct {
+type ChatResponse struct {
 	Model     string    `json:"model"`
 	CreatedAt time.Time `json:"created_at"`
-	Response  string    `json:"response,omitempty"`
+	Message   Message   `json:"message"`
 
-	Done    bool  `json:"done"`
-	Context []int `json:"context,omitempty"`
+	Done bool `json:"done"`
 
+	Metrics
+}
+
+type Metrics struct {
 	TotalDuration      time.Duration `json:"total_duration,omitempty"`
+	LoadDuration       time.Duration `json:"load_duration,omitempty"`
 	PromptEvalCount    int           `json:"prompt_eval_count,omitempty"`
 	PromptEvalDuration time.Duration `json:"prompt_eval_duration,omitempty"`
 	EvalCount          int           `json:"eval_count,omitempty"`
 	EvalDuration       time.Duration `json:"eval_duration,omitempty"`
 }
 
-func (r *GenerateResponse) Summary() {
-	if r.TotalDuration > 0 {
-		fmt.Fprintf(os.Stderr, "total duration:       %v\n", r.TotalDuration)
+// Options specified in GenerateRequest, if you add a new option here add it to the API docs also
+type Options struct {
+	Runner
+
+	// Predict options used at runtime
+	NumKeep          int      `json:"num_keep,omitempty"`
+	Seed             int      `json:"seed,omitempty"`
+	NumPredict       int      `json:"num_predict,omitempty"`
+	TopK             int      `json:"top_k,omitempty"`
+	TopP             float32  `json:"top_p,omitempty"`
+	TFSZ             float32  `json:"tfs_z,omitempty"`
+	TypicalP         float32  `json:"typical_p,omitempty"`
+	RepeatLastN      int      `json:"repeat_last_n,omitempty"`
+	Temperature      float32  `json:"temperature,omitempty"`
+	RepeatPenalty    float32  `json:"repeat_penalty,omitempty"`
+	PresencePenalty  float32  `json:"presence_penalty,omitempty"`
+	FrequencyPenalty float32  `json:"frequency_penalty,omitempty"`
+	Mirostat         int      `json:"mirostat,omitempty"`
+	MirostatTau      float32  `json:"mirostat_tau,omitempty"`
+	MirostatEta      float32  `json:"mirostat_eta,omitempty"`
+	PenalizeNewline  bool     `json:"penalize_newline,omitempty"`
+	Stop             []string `json:"stop,omitempty"`
+}
+
+// Runner options which must be set when the model is loaded into memory
+type Runner struct {
+	UseNUMA            bool    `json:"numa,omitempty"`
+	NumCtx             int     `json:"num_ctx,omitempty"`
+	NumBatch           int     `json:"num_batch,omitempty"`
+	NumGQA             int     `json:"num_gqa,omitempty"`
+	NumGPU             int     `json:"num_gpu,omitempty"`
+	MainGPU            int     `json:"main_gpu,omitempty"`
+	LowVRAM            bool    `json:"low_vram,omitempty"`
+	F16KV              bool    `json:"f16_kv,omitempty"`
+	LogitsAll          bool    `json:"logits_all,omitempty"`
+	VocabOnly          bool    `json:"vocab_only,omitempty"`
+	UseMMap            bool    `json:"use_mmap,omitempty"`
+	UseMLock           bool    `json:"use_mlock,omitempty"`
+	RopeFrequencyBase  float32 `json:"rope_frequency_base,omitempty"`
+	RopeFrequencyScale float32 `json:"rope_frequency_scale,omitempty"`
+	NumThread          int     `json:"num_thread,omitempty"`
+}
+
+type EmbeddingRequest struct {
+	Model     string    `json:"model"`
+	Prompt    string    `json:"prompt"`
+	KeepAlive *Duration `json:"keep_alive,omitempty"`
+
+	Options map[string]interface{} `json:"options"`
+}
+
+type EmbeddingResponse struct {
+	Embedding []float64 `json:"embedding"`
+}
+
+type CreateRequest struct {
+	Model     string `json:"model"`
+	Path      string `json:"path"`
+	Modelfile string `json:"modelfile"`
+	Stream    *bool  `json:"stream,omitempty"`
+
+	// Name is deprecated, see Model
+	Name string `json:"name"`
+}
+
+type DeleteRequest struct {
+	Model string `json:"model"`
+
+	// Name is deprecated, see Model
+	Name string `json:"name"`
+}
+
+type ShowRequest struct {
+	Model    string `json:"model"`
+	System   string `json:"system"`
+	Template string `json:"template"`
+
+	Options map[string]interface{} `json:"options"`
+
+	// Name is deprecated, see Model
+	Name string `json:"name"`
+}
+
+type ShowResponse struct {
+	License    string       `json:"license,omitempty"`
+	Modelfile  string       `json:"modelfile,omitempty"`
+	Parameters string       `json:"parameters,omitempty"`
+	Template   string       `json:"template,omitempty"`
+	System     string       `json:"system,omitempty"`
+	Details    ModelDetails `json:"details,omitempty"`
+	Messages   []Message    `json:"messages,omitempty"`
+}
+
+type CopyRequest struct {
+	Source      string `json:"source"`
+	Destination string `json:"destination"`
+}
+
+type PullRequest struct {
+	Model    string `json:"model"`
+	Insecure bool   `json:"insecure,omitempty"`
+	Username string `json:"username"`
+	Password string `json:"password"`
+	Stream   *bool  `json:"stream,omitempty"`
+
+	// Name is deprecated, see Model
+	Name string `json:"name"`
+}
+
+type ProgressResponse struct {
+	Status    string `json:"status"`
+	Digest    string `json:"digest,omitempty"`
+	Total     int64  `json:"total,omitempty"`
+	Completed int64  `json:"completed,omitempty"`
+}
+
+type PushRequest struct {
+	Model    string `json:"model"`
+	Insecure bool   `json:"insecure,omitempty"`
+	Username string `json:"username"`
+	Password string `json:"password"`
+	Stream   *bool  `json:"stream,omitempty"`
+
+	// Name is deprecated, see Model
+	Name string `json:"name"`
+}
+
+type ListResponse struct {
+	Models []ModelResponse `json:"models"`
+}
+
+type ModelResponse struct {
+	Name       string       `json:"name"`
+	Model      string       `json:"model"`
+	ModifiedAt time.Time    `json:"modified_at"`
+	Size       int64        `json:"size"`
+	Digest     string       `json:"digest"`
+	Details    ModelDetails `json:"details,omitempty"`
+}
+
+type TokenResponse struct {
+	Token string `json:"token"`
+}
+
+type GenerateResponse struct {
+	Model     string    `json:"model"`
+	CreatedAt time.Time `json:"created_at"`
+	Response  string    `json:"response"`
+
+	Done    bool  `json:"done"`
+	Context []int `json:"context,omitempty"`
+
+	Metrics
+}
+
+type ModelDetails struct {
+	ParentModel       string   `json:"parent_model"`
+	Format            string   `json:"format"`
+	Family            string   `json:"family"`
+	Families          []string `json:"families"`
+	ParameterSize     string   `json:"parameter_size"`
+	QuantizationLevel string   `json:"quantization_level"`
+}
+
+func (m *Metrics) Summary() {
+	if m.TotalDuration > 0 {
+		fmt.Fprintf(os.Stderr, "total duration:       %v\n", m.TotalDuration)
 	}
 
-	if r.PromptEvalCount > 0 {
-		fmt.Fprintf(os.Stderr, "prompt eval count:    %d token(s)\n", r.PromptEvalCount)
+	if m.LoadDuration > 0 {
+		fmt.Fprintf(os.Stderr, "load duration:        %v\n", m.LoadDuration)
 	}
 
-	if r.PromptEvalDuration > 0 {
-		fmt.Fprintf(os.Stderr, "prompt eval duration: %s\n", r.PromptEvalDuration)
-		fmt.Fprintf(os.Stderr, "prompt eval rate:     %.2f tokens/s\n", float64(r.PromptEvalCount)/r.PromptEvalDuration.Seconds())
+	if m.PromptEvalCount > 0 {
+		fmt.Fprintf(os.Stderr, "prompt eval count:    %d token(s)\n", m.PromptEvalCount)
 	}
 
-	if r.EvalCount > 0 {
-		fmt.Fprintf(os.Stderr, "eval count:           %d token(s)\n", r.EvalCount)
+	if m.PromptEvalDuration > 0 {
+		fmt.Fprintf(os.Stderr, "prompt eval duration: %s\n", m.PromptEvalDuration)
+		fmt.Fprintf(os.Stderr, "prompt eval rate:     %.2f tokens/s\n", float64(m.PromptEvalCount)/m.PromptEvalDuration.Seconds())
 	}
 
-	if r.EvalDuration > 0 {
-		fmt.Fprintf(os.Stderr, "eval duration:        %s\n", r.EvalDuration)
-		fmt.Fprintf(os.Stderr, "eval rate:            %.2f tokens/s\n", float64(r.EvalCount)/r.EvalDuration.Seconds())
+	if m.EvalCount > 0 {
+		fmt.Fprintf(os.Stderr, "eval count:           %d token(s)\n", m.EvalCount)
+	}
+
+	if m.EvalDuration > 0 {
+		fmt.Fprintf(os.Stderr, "eval duration:        %s\n", m.EvalDuration)
+		fmt.Fprintf(os.Stderr, "eval rate:            %.2f tokens/s\n", float64(m.EvalCount)/m.EvalDuration.Seconds())
 	}
 }
 
-type Options struct {
-	Seed int `json:"seed,omitempty"`
+var ErrInvalidOpts = fmt.Errorf("invalid options")
 
-	// Backend options
-	UseNUMA bool `json:"numa,omitempty"`
+func (opts *Options) FromMap(m map[string]interface{}) error {
+	valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
+	typeOpts := reflect.TypeOf(opts).Elem()   // types of the fields in the options struct
 
-	// Model options
-	NumCtx        int  `json:"num_ctx,omitempty"`
-	NumBatch      int  `json:"num_batch,omitempty"`
-	NumGPU        int  `json:"num_gpu,omitempty"`
-	MainGPU       int  `json:"main_gpu,omitempty"`
-	LowVRAM       bool `json:"low_vram,omitempty"`
-	F16KV         bool `json:"f16_kv,omitempty"`
-	LogitsAll     bool `json:"logits_all,omitempty"`
-	VocabOnly     bool `json:"vocab_only,omitempty"`
-	UseMMap       bool `json:"use_mmap,omitempty"`
-	UseMLock      bool `json:"use_mlock,omitempty"`
-	EmbeddingOnly bool `json:"embedding_only,omitempty"`
+	// build map of json struct tags to their types
+	jsonOpts := make(map[string]reflect.StructField)
+	for _, field := range reflect.VisibleFields(typeOpts) {
+		jsonTag := strings.Split(field.Tag.Get("json"), ",")[0]
+		if jsonTag != "" {
+			jsonOpts[jsonTag] = field
+		}
+	}
 
-	// Predict options
-	RepeatLastN      int     `json:"repeat_last_n,omitempty"`
-	RepeatPenalty    float32 `json:"repeat_penalty,omitempty"`
-	FrequencyPenalty float32 `json:"frequency_penalty,omitempty"`
-	PresencePenalty  float32 `json:"presence_penalty,omitempty"`
-	Temperature      float32 `json:"temperature,omitempty"`
-	TopK             int     `json:"top_k,omitempty"`
-	TopP             float32 `json:"top_p,omitempty"`
-	TFSZ             float32 `json:"tfs_z,omitempty"`
-	TypicalP         float32 `json:"typical_p,omitempty"`
-	Mirostat         int     `json:"mirostat,omitempty"`
-	MirostatTau      float32 `json:"mirostat_tau,omitempty"`
-	MirostatEta      float32 `json:"mirostat_eta,omitempty"`
+	invalidOpts := []string{}
+	for key, val := range m {
+		if opt, ok := jsonOpts[key]; ok {
+			field := valueOpts.FieldByName(opt.Name)
+			if field.IsValid() && field.CanSet() {
+				if val == nil {
+					continue
+				}
 
-	NumThread int `json:"num_thread,omitempty"`
+				switch field.Kind() {
+				case reflect.Int:
+					switch t := val.(type) {
+					case int64:
+						field.SetInt(t)
+					case float64:
+						// when JSON unmarshals numbers, it uses float64, not int
+						field.SetInt(int64(t))
+					default:
+						return fmt.Errorf("option %q must be of type integer", key)
+					}
+				case reflect.Bool:
+					val, ok := val.(bool)
+					if !ok {
+						return fmt.Errorf("option %q must be of type boolean", key)
+					}
+					field.SetBool(val)
+				case reflect.Float32:
+					// JSON unmarshals to float64
+					val, ok := val.(float64)
+					if !ok {
+						return fmt.Errorf("option %q must be of type float32", key)
+					}
+					field.SetFloat(val)
+				case reflect.String:
+					val, ok := val.(string)
+					if !ok {
+						return fmt.Errorf("option %q must be of type string", key)
+					}
+					field.SetString(val)
+				case reflect.Slice:
+					// JSON unmarshals to []interface{}, not []string
+					val, ok := val.([]interface{})
+					if !ok {
+						return fmt.Errorf("option %q must be of type array", key)
+					}
+					// convert []interface{} to []string
+					slice := make([]string, len(val))
+					for i, item := range val {
+						str, ok := item.(string)
+						if !ok {
+							return fmt.Errorf("option %q must be of an array of strings", key)
+						}
+						slice[i] = str
+					}
+					field.Set(reflect.ValueOf(slice))
+				default:
+					return fmt.Errorf("unknown type loading config params: %v", field.Kind())
+				}
+			}
+		} else {
+			invalidOpts = append(invalidOpts, key)
+		}
+	}
+
+	if len(invalidOpts) > 0 {
+		return fmt.Errorf("%w: %v", ErrInvalidOpts, strings.Join(invalidOpts, ", "))
+	}
+	return nil
 }
 
 func DefaultOptions() Options {
 	return Options{
-		Seed: -1,
-
-		UseNUMA: false,
-
-		NumCtx:   2048,
-		NumBatch: 512,
-		NumGPU:   1,
-		LowVRAM:  false,
-		F16KV:    true,
-		UseMMap:  true,
-		UseMLock: false,
-
-		RepeatLastN:      512,
-		RepeatPenalty:    1.1,
-		FrequencyPenalty: 0.0,
-		PresencePenalty:  0.0,
+		// options set on request to runner
+		NumPredict:       -1,
+		NumKeep:          0,
 		Temperature:      0.8,
 		TopK:             40,
 		TopP:             0.9,
 		TFSZ:             1.0,
 		TypicalP:         1.0,
+		RepeatLastN:      64,
+		RepeatPenalty:    1.1,
+		PresencePenalty:  0.0,
+		FrequencyPenalty: 0.0,
 		Mirostat:         0,
 		MirostatTau:      5.0,
 		MirostatEta:      0.1,
+		PenalizeNewline:  true,
+		Seed:             -1,
 
-		NumThread: runtime.NumCPU(),
+		Runner: Runner{
+			// options set when the model is loaded
+			NumCtx:             2048,
+			RopeFrequencyBase:  10000.0,
+			RopeFrequencyScale: 1.0,
+			NumBatch:           512,
+			NumGPU:             -1, // -1 here indicates that NumGPU should be set dynamically
+			NumGQA:             1,
+			NumThread:          0, // let the runtime decide
+			LowVRAM:            false,
+			F16KV:              true,
+			UseMLock:           false,
+			UseMMap:            true,
+			UseNUMA:            false,
+		},
 	}
 }
+
+type Duration struct {
+	time.Duration
+}
+
+func (d *Duration) UnmarshalJSON(b []byte) (err error) {
+	var v any
+	if err := json.Unmarshal(b, &v); err != nil {
+		return err
+	}
+
+	d.Duration = 5 * time.Minute
+
+	switch t := v.(type) {
+	case float64:
+		if t < 0 {
+			d.Duration = time.Duration(math.MaxInt64)
+		} else {
+			d.Duration = time.Duration(t * float64(time.Second))
+		}
+	case string:
+		d.Duration, err = time.ParseDuration(t)
+		if err != nil {
+			return err
+		}
+		if d.Duration < 0 {
+			d.Duration = time.Duration(math.MaxInt64)
+		}
+	}
+
+	return nil
+}
+
+// FormatParams converts specified parameter options to their correct types
+func FormatParams(params map[string][]string) (map[string]interface{}, error) {
+	opts := Options{}
+	valueOpts := reflect.ValueOf(&opts).Elem() // names of the fields in the options struct
+	typeOpts := reflect.TypeOf(opts)           // types of the fields in the options struct
+
+	// build map of json struct tags to their types
+	jsonOpts := make(map[string]reflect.StructField)
+	for _, field := range reflect.VisibleFields(typeOpts) {
+		jsonTag := strings.Split(field.Tag.Get("json"), ",")[0]
+		if jsonTag != "" {
+			jsonOpts[jsonTag] = field
+		}
+	}
+
+	out := make(map[string]interface{})
+	// iterate params and set values based on json struct tags
+	for key, vals := range params {
+		if opt, ok := jsonOpts[key]; !ok {
+			return nil, fmt.Errorf("unknown parameter '%s'", key)
+		} else {
+			field := valueOpts.FieldByName(opt.Name)
+			if field.IsValid() && field.CanSet() {
+				switch field.Kind() {
+				case reflect.Float32:
+					floatVal, err := strconv.ParseFloat(vals[0], 32)
+					if err != nil {
+						return nil, fmt.Errorf("invalid float value %s", vals)
+					}
+
+					out[key] = float32(floatVal)
+				case reflect.Int:
+					intVal, err := strconv.ParseInt(vals[0], 10, 64)
+					if err != nil {
+						return nil, fmt.Errorf("invalid int value %s", vals)
+					}
+
+					out[key] = intVal
+				case reflect.Bool:
+					boolVal, err := strconv.ParseBool(vals[0])
+					if err != nil {
+						return nil, fmt.Errorf("invalid bool value %s", vals)
+					}
+
+					out[key] = boolVal
+				case reflect.String:
+					out[key] = vals[0]
+				case reflect.Slice:
+					// TODO: only string slices are supported right now
+					out[key] = vals
+				default:
+					return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
+				}
+			}
+		}
+	}
+
+	return out, nil
+}

api/types_test.go

@@ -0,0 +1,50 @@
+package api
+
+import (
+	"encoding/json"
+	"math"
+	"testing"
+	"time"
+
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/require"
+)
+
+func TestKeepAliveParsingFromJSON(t *testing.T) {
+	tests := []struct {
+		name string
+		req  string
+		exp  *Duration
+	}{
+		{
+			name: "Positive Integer",
+			req:  `{ "keep_alive": 42 }`,
+			exp:  &Duration{42 * time.Second},
+		},
+		{
+			name: "Positive Integer String",
+			req:  `{ "keep_alive": "42m" }`,
+			exp:  &Duration{42 * time.Minute},
+		},
+		{
+			name: "Negative Integer",
+			req:  `{ "keep_alive": -1 }`,
+			exp:  &Duration{math.MaxInt64},
+		},
+		{
+			name: "Negative Integer String",
+			req:  `{ "keep_alive": "-1m" }`,
+			exp:  &Duration{math.MaxInt64},
+		},
+	}
+
+	for _, test := range tests {
+		t.Run(test.name, func(t *testing.T) {
+			var dec ChatRequest
+			err := json.Unmarshal([]byte(test.req), &dec)
+			require.NoError(t, err)
+
+			assert.Equal(t, test.exp, dec.KeepAlive)
+		})
+	}
+}

app/.gitignore

@@ -1,92 +1 @@
-# Logs
-logs
-*.log
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-lerna-debug.log*
-
-# Diagnostic reports (https://nodejs.org/api/report.html)
-report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
-
-# Runtime data
-pids
-*.pid
-*.seed
-*.pid.lock
-.DS_Store
-
-# Directory for instrumented libs generated by jscoverage/JSCover
-lib-cov
-
-# Coverage directory used by tools like istanbul
-coverage
-*.lcov
-
-# nyc test coverage
-.nyc_output
-
-# node-waf configuration
-.lock-wscript
-
-# Compiled binary addons (https://nodejs.org/api/addons.html)
-build/Release
-
-# Dependency directories
-node_modules/
-jspm_packages/
-
-# TypeScript v1 declaration files
-typings/
-
-# TypeScript cache
-*.tsbuildinfo
-
-# Optional npm cache directory
-.npm
-
-# Optional eslint cache
-.eslintcache
-
-# Optional REPL history
-.node_repl_history
-
-# Output of 'npm pack'
-*.tgz
-
-# Yarn Integrity file
-.yarn-integrity
-
-# dotenv environment variables file
-.env
-.env.test
-
-# parcel-bundler cache (https://parceljs.org/)
-.cache
-
-# next.js build output
-.next
-
-# nuxt.js build output
-.nuxt
-
-# vuepress build output
-.vuepress/dist
-
-# Serverless directories
-.serverless/
-
-# FuseBox cache
-.fusebox/
-
-# DynamoDB Local files
-.dynamodb/
-
-# Webpack
-.webpack/
-
-# Vite
-.vite/
-
-# Electron-Forge
-out/
+ollama.syso

app/README.md

@@ -1,27 +1,22 @@
-# Desktop
+# Ollama App
 
-_Note: the Ollama desktop app is a work in progress and is not ready yet for general use._
+## Linux
 
-This app builds upon Ollama to provide a desktop experience for running models.
+TODO
 
-## Developing
+## MacOS
 
-First, build the `ollama` binary:
+TODO
+
+## Windows
+
+If you want to build the installer, youll need to install
+- https://jrsoftware.org/isinfo.php
+
+
+In the top directory of this repo, run the following powershell script
+to build the ollama CLI, ollama app, and ollama installer.
 
 ```
-make -C ..
+powershell -ExecutionPolicy Bypass -File .\scripts\build_windows.ps1
 ```
-
-Then run the desktop app with `npm start`:
-
-```
-npm install
-npm start
-```
-
-## Coming soon
-
-- Browse the latest available models on Hugging Face and other sources
-- Keep track of previous conversations with models
-- Switch quickly between models
-- Connect to remote Ollama servers to run models

app/assets/assets.go

@@ -0,0 +1,17 @@
+package assets
+
+import (
+	"embed"
+	"io/fs"
+)
+
+//go:embed *.ico
+var icons embed.FS
+
+func ListIcons() ([]string, error) {
+	return fs.Glob(icons, "*")
+}
+
+func GetIcon(filename string) ([]byte, error) {
+	return icons.ReadFile(filename)
+}

app/lifecycle/getstarted_nonwindows.go

@@ -0,0 +1,9 @@
+//go:build !windows
+
+package lifecycle
+
+import "fmt"
+
+func GetStarted() error {
+	return fmt.Errorf("GetStarted not implemented")
+}

app/lifecycle/getstarted_windows.go

@@ -0,0 +1,44 @@
+package lifecycle
+
+import (
+	"fmt"
+	"log/slog"
+	"os"
+	"os/exec"
+	"path/filepath"
+	"syscall"
+)
+
+func GetStarted() error {
+	const CREATE_NEW_CONSOLE = 0x00000010
+	var err error
+	bannerScript := filepath.Join(AppDir, "ollama_welcome.ps1")
+	args := []string{
+		// TODO once we're signed, the execution policy bypass should be removed
+		"powershell", "-noexit", "-ExecutionPolicy", "Bypass", "-nologo", "-file", bannerScript,
+	}
+	args[0], err = exec.LookPath(args[0])
+	if err != nil {
+		return err
+	}
+
+	// Make sure the script actually exists
+	_, err = os.Stat(bannerScript)
+	if err != nil {
+		return fmt.Errorf("getting started banner script error %s", err)
+	}
+
+	slog.Info(fmt.Sprintf("opening getting started terminal with %v", args))
+	attrs := &os.ProcAttr{
+		Files: []*os.File{os.Stdin, os.Stdout, os.Stderr},
+		Sys:   &syscall.SysProcAttr{CreationFlags: CREATE_NEW_CONSOLE, HideWindow: false},
+	}
+	proc, err := os.StartProcess(args[0], args, attrs)
+
+	if err != nil {
+		return fmt.Errorf("unable to start getting started shell %w", err)
+	}
+
+	slog.Debug(fmt.Sprintf("getting started terminal PID: %d", proc.Pid))
+	return proc.Release()
+}

app/lifecycle/lifecycle.go

@@ -0,0 +1,92 @@
+package lifecycle
+
+import (
+	"context"
+	"fmt"
+	"log"
+	"log/slog"
+	"os"
+	"os/signal"
+	"syscall"
+
+	"github.com/jmorganca/ollama/app/store"
+	"github.com/jmorganca/ollama/app/tray"
+)
+
+func Run() {
+	InitLogging()
+
+	ctx, cancel := context.WithCancel(context.Background())
+	var done chan int
+
+	t, err := tray.NewTray()
+	if err != nil {
+		log.Fatalf("Failed to start: %s", err)
+	}
+	callbacks := t.GetCallbacks()
+
+	signals := make(chan os.Signal, 1)
+	signal.Notify(signals, syscall.SIGINT, syscall.SIGTERM)
+
+	go func() {
+		slog.Debug("starting callback loop")
+		for {
+			select {
+			case <-callbacks.Quit:
+				slog.Debug("quit called")
+				t.Quit()
+			case <-signals:
+				slog.Debug("shutting down due to signal")
+				t.Quit()
+			case <-callbacks.Update:
+				err := DoUpgrade(cancel, done)
+				if err != nil {
+					slog.Warn(fmt.Sprintf("upgrade attempt failed: %s", err))
+				}
+			case <-callbacks.ShowLogs:
+				ShowLogs()
+			case <-callbacks.DoFirstUse:
+				err := GetStarted()
+				if err != nil {
+					slog.Warn(fmt.Sprintf("Failed to launch getting started shell: %s", err))
+				}
+			}
+		}
+	}()
+
+	// Are we first use?
+	if !store.GetFirstTimeRun() {
+		slog.Debug("First time run")
+		err = t.DisplayFirstUseNotification()
+		if err != nil {
+			slog.Debug(fmt.Sprintf("XXX failed to display first use notification %v", err))
+		}
+		store.SetFirstTimeRun(true)
+	} else {
+		slog.Debug("Not first time, skipping first run notification")
+	}
+
+	if IsServerRunning(ctx) {
+		slog.Info("Detected another instance of ollama running, exiting")
+		os.Exit(1)
+	} else {
+		done, err = SpawnServer(ctx, CLIName)
+		if err != nil {
+			// TODO - should we retry in a backoff loop?
+			// TODO - should we pop up a warning and maybe add a menu item to view application logs?
+			slog.Error(fmt.Sprintf("Failed to spawn ollama server %s", err))
+			done = make(chan int, 1)
+			done <- 1
+		}
+	}
+
+	StartBackgroundUpdaterChecker(ctx, t.UpdateAvailable)
+
+	t.Run()
+	cancel()
+	slog.Info("Waiting for ollama server to shutdown...")
+	if done != nil {
+		<-done
+	}
+	slog.Info("Ollama app exiting")
+}

app/lifecycle/logging.go

@@ -0,0 +1,46 @@
+package lifecycle
+
+import (
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+)
+
+func InitLogging() {
+	level := slog.LevelInfo
+
+	if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
+		level = slog.LevelDebug
+	}
+
+	var logFile *os.File
+	var err error
+	// Detect if we're a GUI app on windows, and if not, send logs to console
+	if os.Stderr.Fd() != 0 {
+		// Console app detected
+		logFile = os.Stderr
+		// TODO - write one-line to the app.log file saying we're running in console mode to help avoid confusion
+	} else {
+		logFile, err = os.OpenFile(AppLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
+		if err != nil {
+			slog.Error(fmt.Sprintf("failed to create server log %v", err))
+			return
+		}
+	}
+	handler := slog.NewTextHandler(logFile, &slog.HandlerOptions{
+		Level:     level,
+		AddSource: true,
+		ReplaceAttr: func(_ []string, attr slog.Attr) slog.Attr {
+			if attr.Key == slog.SourceKey {
+				source := attr.Value.Any().(*slog.Source)
+				source.File = filepath.Base(source.File)
+			}
+			return attr
+		},
+	})
+
+	slog.SetDefault(slog.New(handler))
+
+	slog.Info("ollama app started")
+}

app/lifecycle/logging_nonwindows.go

@@ -0,0 +1,9 @@
+//go:build !windows
+
+package lifecycle
+
+import "log/slog"
+
+func ShowLogs() {
+	slog.Warn("ShowLogs not yet implemented")
+}

app/lifecycle/logging_windows.go

@@ -0,0 +1,19 @@
+package lifecycle
+
+import (
+	"fmt"
+	"log/slog"
+	"os/exec"
+	"syscall"
+)
+
+func ShowLogs() {
+	cmd_path := "c:\\Windows\\system32\\cmd.exe"
+	slog.Debug(fmt.Sprintf("viewing logs with start %s", AppDataDir))
+	cmd := exec.Command(cmd_path, "/c", "start", AppDataDir)
+	cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: false, CreationFlags: 0x08000000}
+	err := cmd.Start()
+	if err != nil {
+		slog.Error(fmt.Sprintf("Failed to open log dir: %s", err))
+	}
+}

app/lifecycle/paths.go

@@ -0,0 +1,79 @@
+package lifecycle
+
+import (
+	"errors"
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"runtime"
+	"strings"
+)
+
+var (
+	AppName    = "ollama app"
+	CLIName    = "ollama"
+	AppDir     = "/opt/Ollama"
+	AppDataDir = "/opt/Ollama"
+	// TODO - should there be a distinct log dir?
+	UpdateStageDir = "/tmp"
+	AppLogFile     = "/tmp/ollama_app.log"
+	ServerLogFile  = "/tmp/ollama.log"
+	UpgradeLogFile = "/tmp/ollama_update.log"
+	Installer      = "OllamaSetup.exe"
+)
+
+func init() {
+	if runtime.GOOS == "windows" {
+		AppName += ".exe"
+		CLIName += ".exe"
+		// Logs, configs, downloads go to LOCALAPPDATA
+		localAppData := os.Getenv("LOCALAPPDATA")
+		AppDataDir = filepath.Join(localAppData, "Ollama")
+		UpdateStageDir = filepath.Join(AppDataDir, "updates")
+		AppLogFile = filepath.Join(AppDataDir, "app.log")
+		ServerLogFile = filepath.Join(AppDataDir, "server.log")
+		UpgradeLogFile = filepath.Join(AppDataDir, "upgrade.log")
+
+		// Executables are stored in APPDATA
+		AppDir = filepath.Join(localAppData, "Programs", "Ollama")
+
+		// Make sure we have PATH set correctly for any spawned children
+		paths := strings.Split(os.Getenv("PATH"), ";")
+		// Start with whatever we find in the PATH/LD_LIBRARY_PATH
+		found := false
+		for _, path := range paths {
+			d, err := filepath.Abs(path)
+			if err != nil {
+				continue
+			}
+			if strings.EqualFold(AppDir, d) {
+				found = true
+			}
+		}
+		if !found {
+			paths = append(paths, AppDir)
+
+			pathVal := strings.Join(paths, ";")
+			slog.Debug("setting PATH=" + pathVal)
+			err := os.Setenv("PATH", pathVal)
+			if err != nil {
+				slog.Error(fmt.Sprintf("failed to update PATH: %s", err))
+			}
+		}
+
+		// Make sure our logging dir exists
+		_, err := os.Stat(AppDataDir)
+		if errors.Is(err, os.ErrNotExist) {
+			if err := os.MkdirAll(AppDataDir, 0o755); err != nil {
+				slog.Error(fmt.Sprintf("create ollama dir %s: %v", AppDataDir, err))
+			}
+		}
+
+	} else if runtime.GOOS == "darwin" {
+		// TODO
+		AppName += ".app"
+		// } else if runtime.GOOS == "linux" {
+		// TODO
+	}
+}

app/lifecycle/server.go

@@ -0,0 +1,139 @@
+package lifecycle
+
+import (
+	"context"
+	"errors"
+	"fmt"
+	"io"
+	"log/slog"
+	"os"
+	"os/exec"
+	"path/filepath"
+	"time"
+
+	"github.com/jmorganca/ollama/api"
+)
+
+func getCLIFullPath(command string) string {
+	cmdPath := ""
+	appExe, err := os.Executable()
+	if err == nil {
+		cmdPath = filepath.Join(filepath.Dir(appExe), command)
+		_, err := os.Stat(cmdPath)
+		if err == nil {
+			return cmdPath
+		}
+	}
+	cmdPath, err = exec.LookPath(command)
+	if err == nil {
+		_, err := os.Stat(cmdPath)
+		if err == nil {
+			return cmdPath
+		}
+	}
+	pwd, err := os.Getwd()
+	if err == nil {
+		cmdPath = filepath.Join(pwd, command)
+		_, err = os.Stat(cmdPath)
+		if err == nil {
+			return cmdPath
+		}
+	}
+
+	return command
+}
+
+func SpawnServer(ctx context.Context, command string) (chan int, error) {
+	done := make(chan int)
+
+	logDir := filepath.Dir(ServerLogFile)
+	_, err := os.Stat(logDir)
+	if errors.Is(err, os.ErrNotExist) {
+		if err := os.MkdirAll(logDir, 0o755); err != nil {
+			return done, fmt.Errorf("create ollama server log dir %s: %v", logDir, err)
+		}
+	}
+
+	cmd := getCmd(ctx, getCLIFullPath(command))
+	// send stdout and stderr to a file
+	stdout, err := cmd.StdoutPipe()
+	if err != nil {
+		return done, fmt.Errorf("failed to spawn server stdout pipe %s", err)
+	}
+	stderr, err := cmd.StderrPipe()
+	if err != nil {
+		return done, fmt.Errorf("failed to spawn server stderr pipe %s", err)
+	}
+	stdin, err := cmd.StdinPipe()
+	if err != nil {
+		return done, fmt.Errorf("failed to spawn server stdin pipe %s", err)
+	}
+
+	// TODO - rotation
+	logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
+	if err != nil {
+		return done, fmt.Errorf("failed to create server log %w", err)
+	}
+	go func() {
+		defer logFile.Close()
+		io.Copy(logFile, stdout) //nolint:errcheck
+	}()
+	go func() {
+		defer logFile.Close()
+		io.Copy(logFile, stderr) //nolint:errcheck
+	}()
+
+	// run the command and wait for it to finish
+	if err := cmd.Start(); err != nil {
+		return done, fmt.Errorf("failed to start server %w", err)
+	}
+	if cmd.Process != nil {
+		slog.Info(fmt.Sprintf("started ollama server with pid %d", cmd.Process.Pid))
+	}
+	slog.Info(fmt.Sprintf("ollama server logs %s", ServerLogFile))
+
+	go func() {
+		// Keep the server running unless we're shuttind down the app
+		crashCount := 0
+		for {
+			cmd.Wait() //nolint:errcheck
+			stdin.Close()
+			var code int
+			if cmd.ProcessState != nil {
+				code = cmd.ProcessState.ExitCode()
+			}
+
+			select {
+			case <-ctx.Done():
+				slog.Debug(fmt.Sprintf("server shutdown with exit code %d", code))
+				done <- code
+				return
+			default:
+				crashCount++
+				slog.Warn(fmt.Sprintf("server crash %d - exit code %d - respawning", crashCount, code))
+				time.Sleep(500 * time.Millisecond)
+				if err := cmd.Start(); err != nil {
+					slog.Error(fmt.Sprintf("failed to restart server %s", err))
+					// Keep trying, but back off if we keep failing
+					time.Sleep(time.Duration(crashCount) * time.Second)
+				}
+			}
+		}
+	}()
+	return done, nil
+}
+
+func IsServerRunning(ctx context.Context) bool {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		slog.Info("unable to connect to server")
+		return false
+	}
+	err = client.Heartbeat(ctx)
+	if err != nil {
+		slog.Debug(fmt.Sprintf("heartbeat from server: %s", err))
+		slog.Info("unable to connect to server")
+		return false
+	}
+	return true
+}

app/lifecycle/server_unix.go

@@ -0,0 +1,12 @@
+//go:build !windows
+
+package lifecycle
+
+import (
+	"context"
+	"os/exec"
+)
+
+func getCmd(ctx context.Context, cmd string) *exec.Cmd {
+	return exec.CommandContext(ctx, cmd, "serve")
+}

app/lifecycle/server_windows.go

@@ -0,0 +1,13 @@
+package lifecycle
+
+import (
+	"context"
+	"os/exec"
+	"syscall"
+)
+
+func getCmd(ctx context.Context, exePath string) *exec.Cmd {
+	cmd := exec.CommandContext(ctx, exePath, "serve")
+	cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: true, CreationFlags: 0x08000000}
+	return cmd
+}

app/lifecycle/updater.go

@@ -0,0 +1,228 @@
+package lifecycle
+
+import (
+	"context"
+	"crypto/rand"
+	"encoding/json"
+	"errors"
+	"fmt"
+	"io"
+	"log/slog"
+	"mime"
+	"net/http"
+	"net/url"
+	"os"
+	"path"
+	"path/filepath"
+	"runtime"
+	"strings"
+	"time"
+
+	"github.com/jmorganca/ollama/auth"
+	"github.com/jmorganca/ollama/version"
+)
+
+var (
+	UpdateCheckURLBase  = "https://ollama.com/api/update"
+	UpdateDownloaded    = false
+	UpdateCheckInterval = 60 * 60 * time.Second
+)
+
+// TODO - maybe move up to the API package?
+type UpdateResponse struct {
+	UpdateURL     string `json:"url"`
+	UpdateVersion string `json:"version"`
+}
+
+func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
+	var updateResp UpdateResponse
+
+	requestURL, err := url.Parse(UpdateCheckURLBase)
+	if err != nil {
+		return false, updateResp
+	}
+
+	query := requestURL.Query()
+	query.Add("os", runtime.GOOS)
+	query.Add("arch", runtime.GOARCH)
+	query.Add("version", version.Version)
+	query.Add("ts", fmt.Sprintf("%d", time.Now().Unix()))
+
+	nonce, err := auth.NewNonce(rand.Reader, 16)
+	if err != nil {
+		return false, updateResp
+	}
+
+	query.Add("nonce", nonce)
+	requestURL.RawQuery = query.Encode()
+
+	data := []byte(fmt.Sprintf("%s,%s", http.MethodGet, requestURL.RequestURI()))
+	signature, err := auth.Sign(ctx, data)
+	if err != nil {
+		return false, updateResp
+	}
+
+	req, err := http.NewRequestWithContext(ctx, http.MethodGet, requestURL.String(), nil)
+	if err != nil {
+		slog.Warn(fmt.Sprintf("failed to check for update: %s", err))
+		return false, updateResp
+	}
+	req.Header.Set("Authorization", signature)
+	req.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
+
+	slog.Debug("checking for available update", "requestURL", requestURL)
+	resp, err := http.DefaultClient.Do(req)
+	if err != nil {
+		slog.Warn(fmt.Sprintf("failed to check for update: %s", err))
+		return false, updateResp
+	}
+	defer resp.Body.Close()
+
+	if resp.StatusCode == 204 {
+		slog.Debug("check update response 204 (current version is up to date)")
+		return false, updateResp
+	}
+	body, err := io.ReadAll(resp.Body)
+	if err != nil {
+		slog.Warn(fmt.Sprintf("failed to read body response: %s", err))
+	}
+
+	if resp.StatusCode != 200 {
+		slog.Info(fmt.Sprintf("check update error %d - %.96s", resp.StatusCode, string(body)))
+		return false, updateResp
+	}
+	err = json.Unmarshal(body, &updateResp)
+	if err != nil {
+		slog.Warn(fmt.Sprintf("malformed response checking for update: %s", err))
+		return false, updateResp
+	}
+	// Extract the version string from the URL in the github release artifact path
+	updateResp.UpdateVersion = path.Base(path.Dir(updateResp.UpdateURL))
+
+	slog.Info("New update available at " + updateResp.UpdateURL)
+	return true, updateResp
+}
+
+func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
+	// Do a head first to check etag info
+	req, err := http.NewRequestWithContext(ctx, http.MethodHead, updateResp.UpdateURL, nil)
+	if err != nil {
+		return err
+	}
+
+	resp, err := http.DefaultClient.Do(req)
+	if err != nil {
+		return fmt.Errorf("error checking update: %w", err)
+	}
+	if resp.StatusCode != 200 {
+		return fmt.Errorf("unexpected status attempting to download update %d", resp.StatusCode)
+	}
+	resp.Body.Close()
+	etag := strings.Trim(resp.Header.Get("etag"), "\"")
+	if etag == "" {
+		slog.Debug("no etag detected, falling back to filename based dedup")
+		etag = "_"
+	}
+	filename := Installer
+	_, params, err := mime.ParseMediaType(resp.Header.Get("content-disposition"))
+	if err == nil {
+		filename = params["filename"]
+	}
+
+	stageFilename := filepath.Join(UpdateStageDir, etag, filename)
+
+	// Check to see if we already have it downloaded
+	_, err = os.Stat(stageFilename)
+	if err == nil {
+		slog.Info("update already downloaded")
+		return nil
+	}
+
+	cleanupOldDownloads()
+
+	req.Method = http.MethodGet
+	resp, err = http.DefaultClient.Do(req)
+	if err != nil {
+		return fmt.Errorf("error checking update: %w", err)
+	}
+	defer resp.Body.Close()
+	etag = strings.Trim(resp.Header.Get("etag"), "\"")
+	if etag == "" {
+		slog.Debug("no etag detected, falling back to filename based dedup") // TODO probably can get rid of this redundant log
+		etag = "_"
+	}
+
+	stageFilename = filepath.Join(UpdateStageDir, etag, filename)
+
+	_, err = os.Stat(filepath.Dir(stageFilename))
+	if errors.Is(err, os.ErrNotExist) {
+		if err := os.MkdirAll(filepath.Dir(stageFilename), 0o755); err != nil {
+			return fmt.Errorf("create ollama dir %s: %v", filepath.Dir(stageFilename), err)
+		}
+	}
+
+	payload, err := io.ReadAll(resp.Body)
+	if err != nil {
+		return fmt.Errorf("failed to read body response: %w", err)
+	}
+	fp, err := os.OpenFile(stageFilename, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
+	if err != nil {
+		return fmt.Errorf("write payload %s: %w", stageFilename, err)
+	}
+	defer fp.Close()
+	if n, err := fp.Write(payload); err != nil || n != len(payload) {
+		return fmt.Errorf("write payload %s: %d vs %d -- %w", stageFilename, n, len(payload), err)
+	}
+	slog.Info("new update downloaded " + stageFilename)
+
+	UpdateDownloaded = true
+	return nil
+}
+
+func cleanupOldDownloads() {
+	files, err := os.ReadDir(UpdateStageDir)
+	if err != nil && errors.Is(err, os.ErrNotExist) {
+		// Expected behavior on first run
+		return
+	} else if err != nil {
+		slog.Warn(fmt.Sprintf("failed to list stage dir: %s", err))
+		return
+	}
+	for _, file := range files {
+		fullname := filepath.Join(UpdateStageDir, file.Name())
+		slog.Debug("cleaning up old download: " + fullname)
+		err = os.RemoveAll(fullname)
+		if err != nil {
+			slog.Warn(fmt.Sprintf("failed to cleanup stale update download %s", err))
+		}
+	}
+}
+
+func StartBackgroundUpdaterChecker(ctx context.Context, cb func(string) error) {
+	go func() {
+		// Don't blast an update message immediately after startup
+		// time.Sleep(30 * time.Second)
+		time.Sleep(3 * time.Second)
+
+		for {
+			available, resp := IsNewReleaseAvailable(ctx)
+			if available {
+				err := DownloadNewRelease(ctx, resp)
+				if err != nil {
+					slog.Error(fmt.Sprintf("failed to download new release: %s", err))
+				}
+				err = cb(resp.UpdateVersion)
+				if err != nil {
+					slog.Warn(fmt.Sprintf("failed to register update available with tray: %s", err))
+				}
+			}
+			select {
+			case <-ctx.Done():
+				slog.Debug("stopping background update checker")
+				return
+			default:
+				time.Sleep(UpdateCheckInterval)
+			}
+		}
+	}()
+}

app/lifecycle/updater_nonwindows.go

@@ -0,0 +1,12 @@
+//go:build !windows
+
+package lifecycle
+
+import (
+	"context"
+	"fmt"
+)
+
+func DoUpgrade(cancel context.CancelFunc, done chan int) error {
+	return fmt.Errorf("DoUpgrade not yet implemented")
+}

app/lifecycle/updater_windows.go

@@ -0,0 +1,80 @@
+package lifecycle
+
+import (
+	"context"
+	"fmt"
+	"log/slog"
+	"os"
+	"os/exec"
+	"path/filepath"
+)
+
+func DoUpgrade(cancel context.CancelFunc, done chan int) error {
+	files, err := filepath.Glob(filepath.Join(UpdateStageDir, "*", "*.exe")) // TODO generalize for multiplatform
+	if err != nil {
+		return fmt.Errorf("failed to lookup downloads: %s", err)
+	}
+	if len(files) == 0 {
+		return fmt.Errorf("no update downloads found")
+	} else if len(files) > 1 {
+		// Shouldn't happen
+		slog.Warn(fmt.Sprintf("multiple downloads found, using first one %v", files))
+	}
+	installerExe := files[0]
+
+	slog.Info("starting upgrade with " + installerExe)
+	slog.Info("upgrade log file " + UpgradeLogFile)
+
+	// When running in debug mode, we'll be "verbose" and let the installer pop up and prompt
+	installArgs := []string{
+		"/CLOSEAPPLICATIONS",                    // Quit the tray app if it's still running
+		"/LOG=" + filepath.Base(UpgradeLogFile), // Only relative seems reliable, so set pwd
+		"/FORCECLOSEAPPLICATIONS",               // Force close the tray app - might be needed
+	}
+	// When we're not in debug mode, make the upgrade as quiet as possible (no GUI, no prompts)
+	// TODO - temporarily disable since we're pinning in debug mode for the preview
+	// if debug := os.Getenv("OLLAMA_DEBUG"); debug == "" {
+	installArgs = append(installArgs,
+		"/SP", // Skip the "This will install... Do you wish to continue" prompt
+		"/SUPPRESSMSGBOXES",
+		"/SILENT",
+		"/VERYSILENT",
+	)
+	// }
+
+	// Safeguard in case we have requests in flight that need to drain...
+	slog.Info("Waiting for server to shutdown")
+	cancel()
+	if done != nil {
+		<-done
+	} else {
+		// Shouldn't happen
+		slog.Warn("done chan was nil, not actually waiting")
+	}
+
+	slog.Debug(fmt.Sprintf("starting installer: %s %v", installerExe, installArgs))
+	os.Chdir(filepath.Dir(UpgradeLogFile)) //nolint:errcheck
+	cmd := exec.Command(installerExe, installArgs...)
+
+	if err := cmd.Start(); err != nil {
+		return fmt.Errorf("unable to start ollama app %w", err)
+	}
+
+	if cmd.Process != nil {
+		err = cmd.Process.Release()
+		if err != nil {
+			slog.Error(fmt.Sprintf("failed to release server process: %s", err))
+		}
+	} else {
+		// TODO - some details about why it didn't start, or is this a pedantic error case?
+		return fmt.Errorf("installer process did not start")
+	}
+
+	// TODO should we linger for a moment and check to make sure it's actually running by checking the pid?
+
+	slog.Info("Installer started in background, exiting")
+
+	os.Exit(0)
+	// Not reached
+	return nil
+}

app/main.go

@@ -0,0 +1,12 @@
+package main
+
+// Compile with the following to get rid of the cmd pop up on windows
+// go build -ldflags="-H windowsgui" .
+
+import (
+	"github.com/jmorganca/ollama/app/lifecycle"
+)
+
+func main() {
+	lifecycle.Run()
+}

app/ollama.iss

@@ -0,0 +1,159 @@
+; Inno Setup Installer for Ollama
+;
+; To build the installer use the build script invoked from the top of the source tree
+; 
+; powershell -ExecutionPolicy Bypass -File .\scripts\build_windows.ps
+
+
+#define MyAppName "Ollama"
+#if GetEnv("PKG_VERSION") != ""
+  #define MyAppVersion GetEnv("PKG_VERSION")
+#else
+  #define MyAppVersion "0.0.0"
+#endif
+#define MyAppPublisher "Ollama"
+#define MyAppURL "https://ollama.com/"
+#define MyAppExeName "ollama app.exe"
+#define MyIcon ".\assets\app.ico"
+
+[Setup]
+; NOTE: The value of AppId uniquely identifies this application. Do not use the same AppId value in installers for other applications.
+; (To generate a new GUID, click Tools | Generate GUID inside the IDE.)
+AppId={{44E83376-CE68-45EB-8FC1-393500EB558C}
+AppName={#MyAppName}
+AppVersion={#MyAppVersion}
+VersionInfoVersion={#MyAppVersion}
+;AppVerName={#MyAppName} {#MyAppVersion}
+AppPublisher={#MyAppPublisher}
+AppPublisherURL={#MyAppURL}
+AppSupportURL={#MyAppURL}
+AppUpdatesURL={#MyAppURL}
+ArchitecturesAllowed=x64
+ArchitecturesInstallIn64BitMode=x64
+DefaultDirName={localappdata}\Programs\{#MyAppName}
+DefaultGroupName={#MyAppName}
+DisableProgramGroupPage=yes
+PrivilegesRequired=lowest
+OutputBaseFilename="OllamaSetup"
+SetupIconFile={#MyIcon}
+UninstallDisplayIcon={uninstallexe}
+Compression=lzma2
+SolidCompression=no
+WizardStyle=modern
+ChangesEnvironment=yes
+OutputDir=..\dist\
+
+; Disable logging once everything's battle tested
+; Filename will be %TEMP%\Setup Log*.txt
+SetupLogging=yes
+CloseApplications=yes
+RestartApplications=no
+
+; https://jrsoftware.org/ishelp/index.php?topic=setup_wizardimagefile
+WizardSmallImageFile=.\assets\setup.bmp
+
+; TODO verifty actual min windows version...
+; OG Win 10
+MinVersion=10.0.10240
+
+; First release that supports WinRT UI Composition for win32 apps
+; MinVersion=10.0.17134
+; First release with XAML Islands - possible UI path forward
+; MinVersion=10.0.18362
+
+; quiet...
+DisableDirPage=yes
+DisableFinishedPage=yes
+DisableReadyMemo=yes
+DisableReadyPage=yes
+DisableStartupPrompt=yes
+DisableWelcomePage=yes
+
+; TODO - percentage can't be set less than 100, so how to make it shorter?
+; WizardSizePercent=100,80
+
+#if GetEnv("KEY_CONTAINER")
+SignTool=MySignTool
+SignedUninstaller=yes
+#endif
+
+SetupMutex=OllamaSetupMutex
+
+[Languages]
+Name: "english"; MessagesFile: "compiler:Default.isl"
+
+[LangOptions]
+DialogFontSize=12
+
+[Files]
+Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
+Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
+Source: "..\dist\windeps\*.dll"; DestDir: "{app}"; Flags: ignoreversion 64bit
+Source: "..\dist\ollama_welcome.ps1"; DestDir: "{app}"; Flags: ignoreversion
+Source: ".\assets\app.ico"; DestDir: "{app}"; Flags: ignoreversion
+; Assumes v5.7, may need adjustments for v6
+#if GetEnv("HIP_PATH") != ""
+  Source: "{#GetEnv('HIP_PATH')}\bin\hipblas.dll"; DestDir: "{app}\rocm\"; Flags: ignoreversion
+  Source: "{#GetEnv('HIP_PATH')}\bin\rocblas.dll"; DestDir: "{app}\rocm\"; Flags: ignoreversion
+  ; amdhip64.dll dependency comes from the driver and must be installed already
+  Source: "{#GetEnv('HIP_PATH')}\bin\rocblas\library\*"; DestDir: "{app}\rocm\rocblas\library\"; Flags: ignoreversion
+#endif
+
+
+[Icons]
+Name: "{group}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilename: "{app}\app.ico"
+Name: "{userstartup}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilename: "{app}\app.ico"
+Name: "{userprograms}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilename: "{app}\app.ico"
+
+[Run]
+Filename: "{cmd}"; Parameters: "/C set PATH={app};%PATH% & ""{app}\{#MyAppExeName}"""; Flags: postinstall nowait runhidden
+
+[UninstallRun]
+; Filename: "{cmd}"; Parameters: "/C ""taskkill /im ''{#MyAppExeName}'' /f /t"; Flags: runhidden
+; Filename: "{cmd}"; Parameters: "/C ""taskkill /im ollama.exe /f /t"; Flags: runhidden
+Filename: "taskkill"; Parameters: "/im ""{#MyAppExeName}"" /f /t"; Flags: runhidden
+Filename: "taskkill"; Parameters: "/im ""ollama.exe"" /f /t"; Flags: runhidden
+; HACK!  need to give the server and app enough time to exit
+; TODO - convert this to a Pascal code script so it waits until they're no longer running, then completes
+Filename: "{cmd}"; Parameters: "/c timeout 5"; Flags: runhidden
+
+[UninstallDelete]
+Type: filesandordirs; Name: "{%TEMP}\ollama*"
+Type: filesandordirs; Name: "{%LOCALAPPDATA}\Ollama"
+Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
+Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\models"
+Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\history"
+; NOTE: if the user has a custom OLLAMA_MODELS it will be preserved
+
+[Messages]
+WizardReady=Ollama Windows Preview
+ReadyLabel1=%nLet's get you up and running with your own large language models.
+SetupAppRunningError=Another Ollama installer is running.%n%nPlease cancel or finish the other installer, then click OK to continue with this install, or Cancel to exit.
+
+
+;FinishedHeadingLabel=Run your first model
+;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama2
+;ClickFinish=%n
+
+[Registry]
+Root: HKCU; Subkey: "Environment"; \
+    ValueType: expandsz; ValueName: "Path"; ValueData: "{olddata};{app}"; \
+    Check: NeedsAddPath('{app}')
+
+[Code]
+
+function NeedsAddPath(Param: string): boolean;
+var
+  OrigPath: string;
+begin
+  if not RegQueryStringValue(HKEY_CURRENT_USER,
+    'Environment',
+    'Path', OrigPath)
+  then begin
+    Result := True;
+    exit;
+  end;
+  { look for the path with leading and trailing semicolon }
+  { Pos() returns 0 if not found }
+  Result := Pos(';' + ExpandConstant(Param) + ';', ';' + OrigPath + ';') = 0;
+end;

app/ollama.rc

@@ -0,0 +1,29 @@
+#include <winver.h>
+
+VS_VERSION_INFO VERSIONINFO
+ FILEFLAGSMASK 0x3fL
+#ifdef _DEBUG
+ FILEFLAGS 0x1L
+#else
+ FILEFLAGS 0x0L
+#endif
+ FILEOS 0x40004L
+ FILETYPE 0x1L
+ FILESUBTYPE 0x0L
+BEGIN
+    BLOCK "StringFileInfo"
+    BEGIN
+        BLOCK "040904b0"
+        BEGIN
+            VALUE "FileDescription", "Ollama"
+            VALUE "InternalName", "Ollama"
+            VALUE "OriginalFilename", "ollama app.exe"
+            VALUE "ProductName", "Ollama"
+        END
+    END
+
+    BLOCK "VarFileInfo"
+    BEGIN
+        VALUE "Translation", 0x409, 1200
+    END
+END

app/ollama_welcome.ps1

@@ -0,0 +1,8 @@
+# TODO - consider ANSI colors and maybe ASCII art...
+write-host ""
+write-host "Welcome to Ollama!"
+write-host ""
+write-host "Run your first model:"
+write-host ""
+write-host "`tollama run llama2"
+write-host ""

app/src/telemetry.ts

@@ -1,19 +0,0 @@
-import { Analytics } from '@segment/analytics-node'
-import { v4 as uuidv4 } from 'uuid'
-import Store from 'electron-store'
-
-const store = new Store()
-
-export const analytics = new Analytics({ writeKey: process.env.TELEMETRY_WRITE_KEY || '<empty>' })
-
-export function id(): string {
-  const id = store.get('id') as string
-
-  if (id) {
-    return id
-  }
-
-  const uuid = uuidv4()
-  store.set('id', uuid)
-  return uuid
-}

app/store/store.go

@@ -0,0 +1,98 @@
+package store
+
+import (
+	"encoding/json"
+	"errors"
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"sync"
+
+	"github.com/google/uuid"
+)
+
+type Store struct {
+	ID           string `json:"id"`
+	FirstTimeRun bool   `json:"first-time-run"`
+}
+
+var (
+	lock  sync.Mutex
+	store Store
+)
+
+func GetID() string {
+	lock.Lock()
+	defer lock.Unlock()
+	if store.ID == "" {
+		initStore()
+	}
+	return store.ID
+
+}
+
+func GetFirstTimeRun() bool {
+	lock.Lock()
+	defer lock.Unlock()
+	if store.ID == "" {
+		initStore()
+	}
+	return store.FirstTimeRun
+}
+
+func SetFirstTimeRun(val bool) {
+	lock.Lock()
+	defer lock.Unlock()
+	if store.FirstTimeRun == val {
+		return
+	}
+	store.FirstTimeRun = val
+	writeStore(getStorePath())
+}
+
+// lock must be held
+func initStore() {
+	storeFile, err := os.Open(getStorePath())
+	if err == nil {
+		defer storeFile.Close()
+		err = json.NewDecoder(storeFile).Decode(&store)
+		if err == nil {
+			slog.Debug(fmt.Sprintf("loaded existing store %s - ID: %s", getStorePath(), store.ID))
+			return
+		}
+	} else if !errors.Is(err, os.ErrNotExist) {
+		slog.Debug(fmt.Sprintf("unexpected error searching for store: %s", err))
+	}
+	slog.Debug("initializing new store")
+	store.ID = uuid.New().String()
+	writeStore(getStorePath())
+}
+
+func writeStore(storeFilename string) {
+	ollamaDir := filepath.Dir(storeFilename)
+	_, err := os.Stat(ollamaDir)
+	if errors.Is(err, os.ErrNotExist) {
+		if err := os.MkdirAll(ollamaDir, 0o755); err != nil {
+			slog.Error(fmt.Sprintf("create ollama dir %s: %v", ollamaDir, err))
+			return
+		}
+	}
+	payload, err := json.Marshal(store)
+	if err != nil {
+		slog.Error(fmt.Sprintf("failed to marshal store: %s", err))
+		return
+	}
+	fp, err := os.OpenFile(storeFilename, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
+	if err != nil {
+		slog.Error(fmt.Sprintf("write store payload %s: %v", storeFilename, err))
+		return
+	}
+	defer fp.Close()
+	if n, err := fp.Write(payload); err != nil || n != len(payload) {
+		slog.Error(fmt.Sprintf("write store payload %s: %d vs %d -- %v", storeFilename, n, len(payload), err))
+		return
+	}
+	slog.Debug("Store contents: " + string(payload))
+	slog.Info(fmt.Sprintf("wrote store: %s", storeFilename))
+}

app/store/store_darwin.go

@@ -0,0 +1,13 @@
+package store
+
+import (
+	"os"
+	"path/filepath"
+)
+
+func getStorePath() string {
+	// TODO - system wide location?
+
+	home := os.Getenv("HOME")
+	return filepath.Join(home, "Library", "Application Support", "Ollama", "config.json")
+}

app/store/store_linux.go

@@ -0,0 +1,16 @@
+package store
+
+import (
+	"os"
+	"path/filepath"
+)
+
+func getStorePath() string {
+	if os.Geteuid() == 0 {
+		// TODO where should we store this on linux for system-wide operation?
+		return "/etc/ollama/config.json"
+	}
+
+	home := os.Getenv("HOME")
+	return filepath.Join(home, ".ollama", "config.json")
+}

app/store/store_windows.go

@@ -0,0 +1,11 @@
+package store
+
+import (
+	"os"
+	"path/filepath"
+)
+
+func getStorePath() string {
+	localAppData := os.Getenv("LOCALAPPDATA")
+	return filepath.Join(localAppData, "Ollama", "config.json")
+}

app/tray/commontray/types.go

@@ -0,0 +1,24 @@
+package commontray
+
+var (
+	Title   = "Ollama"
+	ToolTip = "Ollama"
+
+	UpdateIconName = "tray_upgrade"
+	IconName       = "tray"
+)
+
+type Callbacks struct {
+	Quit       chan struct{}
+	Update     chan struct{}
+	DoFirstUse chan struct{}
+	ShowLogs   chan struct{}
+}
+
+type OllamaTray interface {
+	GetCallbacks() Callbacks
+	Run()
+	UpdateAvailable(ver string) error
+	DisplayFirstUseNotification() error
+	Quit()
+}

app/tray/tray.go

@@ -0,0 +1,33 @@
+package tray
+
+import (
+	"fmt"
+	"runtime"
+
+	"github.com/jmorganca/ollama/app/assets"
+	"github.com/jmorganca/ollama/app/tray/commontray"
+)
+
+func NewTray() (commontray.OllamaTray, error) {
+	extension := ".png"
+	if runtime.GOOS == "windows" {
+		extension = ".ico"
+	}
+	iconName := commontray.UpdateIconName + extension
+	updateIcon, err := assets.GetIcon(iconName)
+	if err != nil {
+		return nil, fmt.Errorf("failed to load icon %s: %w", iconName, err)
+	}
+	iconName = commontray.IconName + extension
+	icon, err := assets.GetIcon(iconName)
+	if err != nil {
+		return nil, fmt.Errorf("failed to load icon %s: %w", iconName, err)
+	}
+
+	tray, err := InitPlatformTray(icon, updateIcon)
+	if err != nil {
+		return nil, err
+	}
+
+	return tray, nil
+}

app/tray/tray_nonwindows.go

@@ -0,0 +1,13 @@
+//go:build !windows
+
+package tray
+
+import (
+	"fmt"
+
+	"github.com/jmorganca/ollama/app/tray/commontray"
+)
+
+func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {
+	return nil, fmt.Errorf("NOT IMPLEMENTED YET")
+}

app/tray/tray_windows.go

@@ -0,0 +1,10 @@
+package tray
+
+import (
+	"github.com/jmorganca/ollama/app/tray/commontray"
+	"github.com/jmorganca/ollama/app/tray/wintray"
+)
+
+func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {
+	return wintray.InitTray(icon, updateIcon)
+}

app/tray/wintray/eventloop.go

@@ -0,0 +1,184 @@
+//go:build windows
+
+package wintray
+
+import (
+	"fmt"
+	"log/slog"
+	"sync"
+	"unsafe"
+
+	"golang.org/x/sys/windows"
+)
+
+var (
+	quitOnce sync.Once
+)
+
+func (t *winTray) Run() {
+	nativeLoop()
+}
+
+func nativeLoop() {
+	// Main message pump.
+	slog.Debug("starting event handling loop")
+	m := &struct {
+		WindowHandle windows.Handle
+		Message      uint32
+		Wparam       uintptr
+		Lparam       uintptr
+		Time         uint32
+		Pt           point
+		LPrivate     uint32
+	}{}
+	for {
+		ret, _, err := pGetMessage.Call(uintptr(unsafe.Pointer(m)), 0, 0, 0)
+
+		// If the function retrieves a message other than WM_QUIT, the return value is nonzero.
+		// If the function retrieves the WM_QUIT message, the return value is zero.
+		// If there is an error, the return value is -1
+		// https://msdn.microsoft.com/en-us/library/windows/desktop/ms644936(v=vs.85).aspx
+		switch int32(ret) {
+		case -1:
+			slog.Error(fmt.Sprintf("get message failure: %v", err))
+			return
+		case 0:
+			return
+		default:
+			pTranslateMessage.Call(uintptr(unsafe.Pointer(m))) //nolint:errcheck
+			pDispatchMessage.Call(uintptr(unsafe.Pointer(m)))  //nolint:errcheck
+
+		}
+	}
+}
+
+// WindowProc callback function that processes messages sent to a window.
+// https://msdn.microsoft.com/en-us/library/windows/desktop/ms633573(v=vs.85).aspx
+func (t *winTray) wndProc(hWnd windows.Handle, message uint32, wParam, lParam uintptr) (lResult uintptr) {
+	const (
+		WM_RBUTTONUP   = 0x0205
+		WM_LBUTTONUP   = 0x0202
+		WM_COMMAND     = 0x0111
+		WM_ENDSESSION  = 0x0016
+		WM_CLOSE       = 0x0010
+		WM_DESTROY     = 0x0002
+		WM_MOUSEMOVE   = 0x0200
+		WM_LBUTTONDOWN = 0x0201
+	)
+	switch message {
+	case WM_COMMAND:
+		menuItemId := int32(wParam)
+		// https://docs.microsoft.com/en-us/windows/win32/menurc/wm-command#menus
+		switch menuItemId {
+		case quitMenuID:
+			select {
+			case t.callbacks.Quit <- struct{}{}:
+			// should not happen but in case not listening
+			default:
+				slog.Error("no listener on Quit")
+			}
+		case updateMenuID:
+			select {
+			case t.callbacks.Update <- struct{}{}:
+			// should not happen but in case not listening
+			default:
+				slog.Error("no listener on Update")
+			}
+		case diagLogsMenuID:
+			select {
+			case t.callbacks.ShowLogs <- struct{}{}:
+			// should not happen but in case not listening
+			default:
+				slog.Error("no listener on ShowLogs")
+			}
+		default:
+			slog.Debug(fmt.Sprintf("Unexpected menu item id: %d", menuItemId))
+		}
+	case WM_CLOSE:
+		boolRet, _, err := pDestroyWindow.Call(uintptr(t.window))
+		if boolRet == 0 {
+			slog.Error(fmt.Sprintf("failed to destroy window: %s", err))
+		}
+		err = t.wcex.unregister()
+		if err != nil {
+			slog.Error(fmt.Sprintf("failed to uregister windo %s", err))
+		}
+	case WM_DESTROY:
+		// same as WM_ENDSESSION, but throws 0 exit code after all
+		defer pPostQuitMessage.Call(uintptr(int32(0))) //nolint:errcheck
+		fallthrough
+	case WM_ENDSESSION:
+		t.muNID.Lock()
+		if t.nid != nil {
+			err := t.nid.delete()
+			if err != nil {
+				slog.Error(fmt.Sprintf("failed to delete nid: %s", err))
+			}
+		}
+		t.muNID.Unlock()
+	case t.wmSystrayMessage:
+		switch lParam {
+		case WM_MOUSEMOVE, WM_LBUTTONDOWN:
+			// Ignore these...
+		case WM_RBUTTONUP, WM_LBUTTONUP:
+			err := t.showMenu()
+			if err != nil {
+				slog.Error(fmt.Sprintf("failed to show menu: %s", err))
+			}
+		case 0x405: // TODO - how is this magic value derived for the notification left click
+			if t.pendingUpdate {
+				select {
+				case t.callbacks.Update <- struct{}{}:
+				// should not happen but in case not listening
+				default:
+					slog.Error("no listener on Update")
+				}
+			} else {
+				select {
+				case t.callbacks.DoFirstUse <- struct{}{}:
+				// should not happen but in case not listening
+				default:
+					slog.Error("no listener on DoFirstUse")
+				}
+			}
+		case 0x404: // Middle click or close notification
+			// slog.Debug("doing nothing on close of first time notification")
+		default:
+			// 0x402 also seems common - what is it?
+			slog.Debug(fmt.Sprintf("unmanaged app message, lParm: 0x%x", lParam))
+		}
+	case t.wmTaskbarCreated: // on explorer.exe restarts
+		t.muNID.Lock()
+		err := t.nid.add()
+		if err != nil {
+			slog.Error(fmt.Sprintf("failed to refresh the taskbar on explorer restart: %s", err))
+		}
+		t.muNID.Unlock()
+	default:
+		// Calls the default window procedure to provide default processing for any window messages that an application does not process.
+		// https://msdn.microsoft.com/en-us/library/windows/desktop/ms633572(v=vs.85).aspx
+		lResult, _, _ = pDefWindowProc.Call(
+			uintptr(hWnd),
+			uintptr(message),
+			uintptr(wParam),
+			uintptr(lParam),
+		)
+	}
+	return
+}
+
+func (t *winTray) Quit() {
+	quitOnce.Do(quit)
+}
+
+func quit() {
+	boolRet, _, err := pPostMessage.Call(
+		uintptr(wt.window),
+		WM_CLOSE,
+		0,
+		0,
+	)
+	if boolRet == 0 {
+		slog.Error(fmt.Sprintf("failed to post close message on shutdown %s", err))
+	}
+}

app/tray/wintray/menus.go

@@ -0,0 +1,71 @@
+//go:build windows
+
+package wintray
+
+import (
+	"fmt"
+	"log/slog"
+	"unsafe"
+
+	"golang.org/x/sys/windows"
+)
+
+const (
+	updatAvailableMenuID = 1
+	updateMenuID         = updatAvailableMenuID + 1
+	separatorMenuID      = updateMenuID + 1
+	diagLogsMenuID       = separatorMenuID + 1
+	diagSeparatorMenuID  = diagLogsMenuID + 1
+	quitMenuID           = diagSeparatorMenuID + 1
+)
+
+func (t *winTray) initMenus() error {
+	if err := t.addOrUpdateMenuItem(diagLogsMenuID, 0, diagLogsMenuTitle, false); err != nil {
+		return fmt.Errorf("unable to create menu entries %w\n", err)
+	}
+	if err := t.addSeparatorMenuItem(diagSeparatorMenuID, 0); err != nil {
+		return fmt.Errorf("unable to create menu entries %w", err)
+	}
+	if err := t.addOrUpdateMenuItem(quitMenuID, 0, quitMenuTitle, false); err != nil {
+		return fmt.Errorf("unable to create menu entries %w\n", err)
+	}
+	return nil
+}
+
+func (t *winTray) UpdateAvailable(ver string) error {
+	if !t.updateNotified {
+		slog.Debug("updating menu and sending notification for new update")
+		if err := t.addOrUpdateMenuItem(updatAvailableMenuID, 0, updateAvailableMenuTitle, true); err != nil {
+			return fmt.Errorf("unable to create menu entries %w", err)
+		}
+		if err := t.addOrUpdateMenuItem(updateMenuID, 0, updateMenutTitle, false); err != nil {
+			return fmt.Errorf("unable to create menu entries %w", err)
+		}
+		if err := t.addSeparatorMenuItem(separatorMenuID, 0); err != nil {
+			return fmt.Errorf("unable to create menu entries %w", err)
+		}
+		iconFilePath, err := iconBytesToFilePath(wt.updateIcon)
+		if err != nil {
+			return fmt.Errorf("unable to write icon data to temp file: %w", err)
+		}
+		if err := wt.setIcon(iconFilePath); err != nil {
+			return fmt.Errorf("unable to set icon: %w", err)
+		}
+		t.updateNotified = true
+
+		t.pendingUpdate = true
+		// Now pop up the notification
+		t.muNID.Lock()
+		defer t.muNID.Unlock()
+		copy(t.nid.InfoTitle[:], windows.StringToUTF16(updateTitle))
+		copy(t.nid.Info[:], windows.StringToUTF16(fmt.Sprintf(updateMessage, ver)))
+		t.nid.Flags |= NIF_INFO
+		t.nid.Timeout = 10
+		t.nid.Size = uint32(unsafe.Sizeof(*wt.nid))
+		err = t.nid.modify()
+		if err != nil {
+			return err
+		}
+	}
+	return nil
+}

app/tray/wintray/messages.go

@@ -0,0 +1,15 @@
+//go:build windows
+
+package wintray
+
+const (
+	firstTimeTitle   = "Ollama is running"
+	firstTimeMessage = "Click here to get started"
+	updateTitle      = "Update available"
+	updateMessage    = "Ollama version %s is ready to install"
+
+	quitMenuTitle            = "Quit Ollama"
+	updateAvailableMenuTitle = "An update is available"
+	updateMenutTitle         = "Restart to update"
+	diagLogsMenuTitle        = "View logs"
+)

app/tray/wintray/notifyicon.go

@@ -0,0 +1,66 @@
+//go:build windows
+
+package wintray
+
+import (
+	"unsafe"
+
+	"golang.org/x/sys/windows"
+)
+
+// Contains information that the system needs to display notifications in the notification area.
+// Used by Shell_NotifyIcon.
+// https://msdn.microsoft.com/en-us/library/windows/desktop/bb773352(v=vs.85).aspx
+// https://msdn.microsoft.com/en-us/library/windows/desktop/bb762159
+type notifyIconData struct {
+	Size                       uint32
+	Wnd                        windows.Handle
+	ID, Flags, CallbackMessage uint32
+	Icon                       windows.Handle
+	Tip                        [128]uint16
+	State, StateMask           uint32
+	Info                       [256]uint16
+	// Timeout, Version           uint32
+	Timeout uint32
+
+	InfoTitle   [64]uint16
+	InfoFlags   uint32
+	GuidItem    windows.GUID
+	BalloonIcon windows.Handle
+}
+
+func (nid *notifyIconData) add() error {
+	const NIM_ADD = 0x00000000
+	res, _, err := pShellNotifyIcon.Call(
+		uintptr(NIM_ADD),
+		uintptr(unsafe.Pointer(nid)),
+	)
+	if res == 0 {
+		return err
+	}
+	return nil
+}
+
+func (nid *notifyIconData) modify() error {
+	const NIM_MODIFY = 0x00000001
+	res, _, err := pShellNotifyIcon.Call(
+		uintptr(NIM_MODIFY),
+		uintptr(unsafe.Pointer(nid)),
+	)
+	if res == 0 {
+		return err
+	}
+	return nil
+}
+
+func (nid *notifyIconData) delete() error {
+	const NIM_DELETE = 0x00000002
+	res, _, err := pShellNotifyIcon.Call(
+		uintptr(NIM_DELETE),
+		uintptr(unsafe.Pointer(nid)),
+	)
+	if res == 0 {
+		return err
+	}
+	return nil
+}

app/tray/wintray/tray.go

@@ -0,0 +1,485 @@
+//go:build windows
+
+package wintray
+
+import (
+	"crypto/md5"
+	"encoding/hex"
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"sort"
+	"sync"
+	"unsafe"
+
+	"github.com/jmorganca/ollama/app/tray/commontray"
+	"golang.org/x/sys/windows"
+)
+
+// Helpful sources: https://github.com/golang/exp/blob/master/shiny/driver/internal/win32
+
+// Contains information about loaded resources
+type winTray struct {
+	instance,
+	icon,
+	cursor,
+	window windows.Handle
+
+	loadedImages   map[string]windows.Handle
+	muLoadedImages sync.RWMutex
+
+	// menus keeps track of the submenus keyed by the menu item ID, plus 0
+	// which corresponds to the main popup menu.
+	menus    map[uint32]windows.Handle
+	muMenus  sync.RWMutex
+	menuOf   map[uint32]windows.Handle
+	muMenuOf sync.RWMutex
+	// menuItemIcons maintains the bitmap of each menu item (if applies). It's
+	// needed to show the icon correctly when showing a previously hidden menu
+	// item again.
+	// menuItemIcons   map[uint32]windows.Handle
+	// muMenuItemIcons sync.RWMutex
+	visibleItems   map[uint32][]uint32
+	muVisibleItems sync.RWMutex
+
+	nid   *notifyIconData
+	muNID sync.RWMutex
+	wcex  *wndClassEx
+
+	wmSystrayMessage,
+	wmTaskbarCreated uint32
+
+	pendingUpdate  bool
+	updateNotified bool // Only pop up the notification once - TODO consider daily nag?
+	// Callbacks
+	callbacks  commontray.Callbacks
+	normalIcon []byte
+	updateIcon []byte
+}
+
+var wt winTray
+
+func (t *winTray) GetCallbacks() commontray.Callbacks {
+	return t.callbacks
+}
+
+func InitTray(icon, updateIcon []byte) (*winTray, error) {
+	wt.callbacks.Quit = make(chan struct{})
+	wt.callbacks.Update = make(chan struct{})
+	wt.callbacks.ShowLogs = make(chan struct{})
+	wt.callbacks.DoFirstUse = make(chan struct{})
+	wt.normalIcon = icon
+	wt.updateIcon = updateIcon
+	if err := wt.initInstance(); err != nil {
+		return nil, fmt.Errorf("Unable to init instance: %w\n", err)
+	}
+
+	if err := wt.createMenu(); err != nil {
+		return nil, fmt.Errorf("Unable to create menu: %w\n", err)
+	}
+
+	iconFilePath, err := iconBytesToFilePath(wt.normalIcon)
+	if err != nil {
+		return nil, fmt.Errorf("Unable to write icon data to temp file: %w", err)
+	}
+	if err := wt.setIcon(iconFilePath); err != nil {
+		return nil, fmt.Errorf("Unable to set icon: %w", err)
+	}
+
+	return &wt, wt.initMenus()
+}
+
+func (t *winTray) initInstance() error {
+	const (
+		className  = "OllamaClass"
+		windowName = ""
+	)
+
+	t.wmSystrayMessage = WM_USER + 1
+	t.visibleItems = make(map[uint32][]uint32)
+	t.menus = make(map[uint32]windows.Handle)
+	t.menuOf = make(map[uint32]windows.Handle)
+
+	t.loadedImages = make(map[string]windows.Handle)
+
+	taskbarEventNamePtr, _ := windows.UTF16PtrFromString("TaskbarCreated")
+	// https://msdn.microsoft.com/en-us/library/windows/desktop/ms644947
+	res, _, err := pRegisterWindowMessage.Call(
+		uintptr(unsafe.Pointer(taskbarEventNamePtr)),
+	)
+	if res == 0 { // success 0xc000-0xfff
+		return fmt.Errorf("failed to register window: %w", err)
+	}
+	t.wmTaskbarCreated = uint32(res)
+
+	instanceHandle, _, err := pGetModuleHandle.Call(0)
+	if instanceHandle == 0 {
+		return err
+	}
+	t.instance = windows.Handle(instanceHandle)
+
+	// https://msdn.microsoft.com/en-us/library/windows/desktop/ms648072(v=vs.85).aspx
+	iconHandle, _, err := pLoadIcon.Call(0, uintptr(IDI_APPLICATION))
+	if iconHandle == 0 {
+		return err
+	}
+	t.icon = windows.Handle(iconHandle)
+
+	// https://msdn.microsoft.com/en-us/library/windows/desktop/ms648391(v=vs.85).aspx
+	cursorHandle, _, err := pLoadCursor.Call(0, uintptr(IDC_ARROW))
+	if cursorHandle == 0 {
+		return err
+	}
+	t.cursor = windows.Handle(cursorHandle)
+
+	classNamePtr, err := windows.UTF16PtrFromString(className)
+	if err != nil {
+		return err
+	}
+
+	windowNamePtr, err := windows.UTF16PtrFromString(windowName)
+	if err != nil {
+		return err
+	}
+
+	t.wcex = &wndClassEx{
+		Style:      CS_HREDRAW | CS_VREDRAW,
+		WndProc:    windows.NewCallback(t.wndProc),
+		Instance:   t.instance,
+		Icon:       t.icon,
+		Cursor:     t.cursor,
+		Background: windows.Handle(6), // (COLOR_WINDOW + 1)
+		ClassName:  classNamePtr,
+		IconSm:     t.icon,
+	}
+	if err := t.wcex.register(); err != nil {
+		return err
+	}
+
+	windowHandle, _, err := pCreateWindowEx.Call(
+		uintptr(0),
+		uintptr(unsafe.Pointer(classNamePtr)),
+		uintptr(unsafe.Pointer(windowNamePtr)),
+		uintptr(WS_OVERLAPPEDWINDOW),
+		uintptr(CW_USEDEFAULT),
+		uintptr(CW_USEDEFAULT),
+		uintptr(CW_USEDEFAULT),
+		uintptr(CW_USEDEFAULT),
+		uintptr(0),
+		uintptr(0),
+		uintptr(t.instance),
+		uintptr(0),
+	)
+	if windowHandle == 0 {
+		return err
+	}
+	t.window = windows.Handle(windowHandle)
+
+	pShowWindow.Call(uintptr(t.window), uintptr(SW_HIDE)) //nolint:errcheck
+
+	boolRet, _, err := pUpdateWindow.Call(uintptr(t.window))
+	if boolRet == 0 {
+		slog.Error(fmt.Sprintf("failed to update window: %s", err))
+	}
+
+	t.muNID.Lock()
+	defer t.muNID.Unlock()
+	t.nid = &notifyIconData{
+		Wnd:             windows.Handle(t.window),
+		ID:              100,
+		Flags:           NIF_MESSAGE,
+		CallbackMessage: t.wmSystrayMessage,
+	}
+	t.nid.Size = uint32(unsafe.Sizeof(*t.nid))
+
+	return t.nid.add()
+}
+
+func (t *winTray) createMenu() error {
+
+	menuHandle, _, err := pCreatePopupMenu.Call()
+	if menuHandle == 0 {
+		return err
+	}
+	t.menus[0] = windows.Handle(menuHandle)
+
+	// https://msdn.microsoft.com/en-us/library/windows/desktop/ms647575(v=vs.85).aspx
+	mi := struct {
+		Size, Mask, Style, Max uint32
+		Background             windows.Handle
+		ContextHelpID          uint32
+		MenuData               uintptr
+	}{
+		Mask: MIM_APPLYTOSUBMENUS,
+	}
+	mi.Size = uint32(unsafe.Sizeof(mi))
+
+	res, _, err := pSetMenuInfo.Call(
+		uintptr(t.menus[0]),
+		uintptr(unsafe.Pointer(&mi)),
+	)
+	if res == 0 {
+		return err
+	}
+	return nil
+}
+
+// Contains information about a menu item.
+// https://msdn.microsoft.com/en-us/library/windows/desktop/ms647578(v=vs.85).aspx
+type menuItemInfo struct {
+	Size, Mask, Type, State     uint32
+	ID                          uint32
+	SubMenu, Checked, Unchecked windows.Handle
+	ItemData                    uintptr
+	TypeData                    *uint16
+	Cch                         uint32
+	BMPItem                     windows.Handle
+}
+
+func (t *winTray) addOrUpdateMenuItem(menuItemId uint32, parentId uint32, title string, disabled bool) error {
+	titlePtr, err := windows.UTF16PtrFromString(title)
+	if err != nil {
+		return err
+	}
+
+	mi := menuItemInfo{
+		Mask:     MIIM_FTYPE | MIIM_STRING | MIIM_ID | MIIM_STATE,
+		Type:     MFT_STRING,
+		ID:       uint32(menuItemId),
+		TypeData: titlePtr,
+		Cch:      uint32(len(title)),
+	}
+	mi.Size = uint32(unsafe.Sizeof(mi))
+	if disabled {
+		mi.State |= MFS_DISABLED
+	}
+
+	var res uintptr
+	t.muMenus.RLock()
+	menu := t.menus[parentId]
+	t.muMenus.RUnlock()
+	if t.getVisibleItemIndex(parentId, menuItemId) != -1 {
+		// We set the menu item info based on the menuID
+		boolRet, _, err := pSetMenuItemInfo.Call(
+			uintptr(menu),
+			uintptr(menuItemId),
+			0,
+			uintptr(unsafe.Pointer(&mi)),
+		)
+		if boolRet == 0 {
+			return fmt.Errorf("failed to set menu item: %w", err)
+		}
+	}
+
+	if res == 0 {
+		// Menu item does not already exist, create it
+		t.muMenus.RLock()
+		submenu, exists := t.menus[menuItemId]
+		t.muMenus.RUnlock()
+		if exists {
+			mi.Mask |= MIIM_SUBMENU
+			mi.SubMenu = submenu
+		}
+		t.addToVisibleItems(parentId, menuItemId)
+		position := t.getVisibleItemIndex(parentId, menuItemId)
+		res, _, err = pInsertMenuItem.Call(
+			uintptr(menu),
+			uintptr(position),
+			1,
+			uintptr(unsafe.Pointer(&mi)),
+		)
+		if res == 0 {
+			t.delFromVisibleItems(parentId, menuItemId)
+			return err
+		}
+		t.muMenuOf.Lock()
+		t.menuOf[menuItemId] = menu
+		t.muMenuOf.Unlock()
+	}
+
+	return nil
+}
+
+func (t *winTray) addSeparatorMenuItem(menuItemId, parentId uint32) error {
+
+	mi := menuItemInfo{
+		Mask: MIIM_FTYPE | MIIM_ID | MIIM_STATE,
+		Type: MFT_SEPARATOR,
+		ID:   uint32(menuItemId),
+	}
+
+	mi.Size = uint32(unsafe.Sizeof(mi))
+
+	t.addToVisibleItems(parentId, menuItemId)
+	position := t.getVisibleItemIndex(parentId, menuItemId)
+	t.muMenus.RLock()
+	menu := uintptr(t.menus[parentId])
+	t.muMenus.RUnlock()
+	res, _, err := pInsertMenuItem.Call(
+		menu,
+		uintptr(position),
+		1,
+		uintptr(unsafe.Pointer(&mi)),
+	)
+	if res == 0 {
+		return err
+	}
+
+	return nil
+}
+
+// func (t *winTray) hideMenuItem(menuItemId, parentId uint32) error {
+// 	const ERROR_SUCCESS syscall.Errno = 0
+
+// 	t.muMenus.RLock()
+// 	menu := uintptr(t.menus[parentId])
+// 	t.muMenus.RUnlock()
+// 	res, _, err := pRemoveMenu.Call(
+// 		menu,
+// 		uintptr(menuItemId),
+// 		MF_BYCOMMAND,
+// 	)
+// 	if res == 0 && err.(syscall.Errno) != ERROR_SUCCESS {
+// 		return err
+// 	}
+// 	t.delFromVisibleItems(parentId, menuItemId)
+
+// 	return nil
+// }
+
+func (t *winTray) showMenu() error {
+	p := point{}
+	boolRet, _, err := pGetCursorPos.Call(uintptr(unsafe.Pointer(&p)))
+	if boolRet == 0 {
+		return err
+	}
+	boolRet, _, err = pSetForegroundWindow.Call(uintptr(t.window))
+	if boolRet == 0 {
+		slog.Warn(fmt.Sprintf("failed to bring menu to foreground: %s", err))
+	}
+
+	boolRet, _, err = pTrackPopupMenu.Call(
+		uintptr(t.menus[0]),
+		TPM_BOTTOMALIGN|TPM_LEFTALIGN,
+		uintptr(p.X),
+		uintptr(p.Y),
+		0,
+		uintptr(t.window),
+		0,
+	)
+	if boolRet == 0 {
+		return err
+	}
+
+	return nil
+}
+
+func (t *winTray) delFromVisibleItems(parent, val uint32) {
+	t.muVisibleItems.Lock()
+	defer t.muVisibleItems.Unlock()
+	visibleItems := t.visibleItems[parent]
+	for i, itemval := range visibleItems {
+		if val == itemval {
+			t.visibleItems[parent] = append(visibleItems[:i], visibleItems[i+1:]...)
+			break
+		}
+	}
+}
+
+func (t *winTray) addToVisibleItems(parent, val uint32) {
+	t.muVisibleItems.Lock()
+	defer t.muVisibleItems.Unlock()
+	if visibleItems, exists := t.visibleItems[parent]; !exists {
+		t.visibleItems[parent] = []uint32{val}
+	} else {
+		newvisible := append(visibleItems, val)
+		sort.Slice(newvisible, func(i, j int) bool { return newvisible[i] < newvisible[j] })
+		t.visibleItems[parent] = newvisible
+	}
+}
+
+func (t *winTray) getVisibleItemIndex(parent, val uint32) int {
+	t.muVisibleItems.RLock()
+	defer t.muVisibleItems.RUnlock()
+	for i, itemval := range t.visibleItems[parent] {
+		if val == itemval {
+			return i
+		}
+	}
+	return -1
+}
+
+func iconBytesToFilePath(iconBytes []byte) (string, error) {
+	bh := md5.Sum(iconBytes)
+	dataHash := hex.EncodeToString(bh[:])
+	iconFilePath := filepath.Join(os.TempDir(), "ollama_temp_icon_"+dataHash)
+
+	if _, err := os.Stat(iconFilePath); os.IsNotExist(err) {
+		if err := os.WriteFile(iconFilePath, iconBytes, 0644); err != nil {
+			return "", err
+		}
+	}
+	return iconFilePath, nil
+}
+
+// Loads an image from file and shows it in tray.
+// Shell_NotifyIcon: https://msdn.microsoft.com/en-us/library/windows/desktop/bb762159(v=vs.85).aspx
+func (t *winTray) setIcon(src string) error {
+
+	h, err := t.loadIconFrom(src)
+	if err != nil {
+		return err
+	}
+
+	t.muNID.Lock()
+	defer t.muNID.Unlock()
+	t.nid.Icon = h
+	t.nid.Flags |= NIF_ICON
+	t.nid.Size = uint32(unsafe.Sizeof(*t.nid))
+
+	return t.nid.modify()
+}
+
+// Loads an image from file to be shown in tray or menu item.
+// LoadImage: https://msdn.microsoft.com/en-us/library/windows/desktop/ms648045(v=vs.85).aspx
+func (t *winTray) loadIconFrom(src string) (windows.Handle, error) {
+
+	// Save and reuse handles of loaded images
+	t.muLoadedImages.RLock()
+	h, ok := t.loadedImages[src]
+	t.muLoadedImages.RUnlock()
+	if !ok {
+		srcPtr, err := windows.UTF16PtrFromString(src)
+		if err != nil {
+			return 0, err
+		}
+		res, _, err := pLoadImage.Call(
+			0,
+			uintptr(unsafe.Pointer(srcPtr)),
+			IMAGE_ICON,
+			0,
+			0,
+			LR_LOADFROMFILE|LR_DEFAULTSIZE,
+		)
+		if res == 0 {
+			return 0, err
+		}
+		h = windows.Handle(res)
+		t.muLoadedImages.Lock()
+		t.loadedImages[src] = h
+		t.muLoadedImages.Unlock()
+	}
+	return h, nil
+}
+
+func (t *winTray) DisplayFirstUseNotification() error {
+	t.muNID.Lock()
+	defer t.muNID.Unlock()
+	copy(t.nid.InfoTitle[:], windows.StringToUTF16(firstTimeTitle))
+	copy(t.nid.Info[:], windows.StringToUTF16(firstTimeMessage))
+	t.nid.Flags |= NIF_INFO
+	t.nid.Size = uint32(unsafe.Sizeof(*wt.nid))
+
+	return t.nid.modify()
+}

app/tray/wintray/w32api.go

@@ -0,0 +1,89 @@
+//go:build windows
+
+package wintray
+
+import (
+	"runtime"
+
+	"golang.org/x/sys/windows"
+)
+
+var (
+	k32 = windows.NewLazySystemDLL("Kernel32.dll")
+	u32 = windows.NewLazySystemDLL("User32.dll")
+	s32 = windows.NewLazySystemDLL("Shell32.dll")
+
+	pCreatePopupMenu       = u32.NewProc("CreatePopupMenu")
+	pCreateWindowEx        = u32.NewProc("CreateWindowExW")
+	pDefWindowProc         = u32.NewProc("DefWindowProcW")
+	pDestroyWindow         = u32.NewProc("DestroyWindow")
+	pDispatchMessage       = u32.NewProc("DispatchMessageW")
+	pGetCursorPos          = u32.NewProc("GetCursorPos")
+	pGetMessage            = u32.NewProc("GetMessageW")
+	pGetModuleHandle       = k32.NewProc("GetModuleHandleW")
+	pInsertMenuItem        = u32.NewProc("InsertMenuItemW")
+	pLoadCursor            = u32.NewProc("LoadCursorW")
+	pLoadIcon              = u32.NewProc("LoadIconW")
+	pLoadImage             = u32.NewProc("LoadImageW")
+	pPostMessage           = u32.NewProc("PostMessageW")
+	pPostQuitMessage       = u32.NewProc("PostQuitMessage")
+	pRegisterClass         = u32.NewProc("RegisterClassExW")
+	pRegisterWindowMessage = u32.NewProc("RegisterWindowMessageW")
+	pSetForegroundWindow   = u32.NewProc("SetForegroundWindow")
+	pSetMenuInfo           = u32.NewProc("SetMenuInfo")
+	pSetMenuItemInfo       = u32.NewProc("SetMenuItemInfoW")
+	pShellNotifyIcon       = s32.NewProc("Shell_NotifyIconW")
+	pShowWindow            = u32.NewProc("ShowWindow")
+	pTrackPopupMenu        = u32.NewProc("TrackPopupMenu")
+	pTranslateMessage      = u32.NewProc("TranslateMessage")
+	pUnregisterClass       = u32.NewProc("UnregisterClassW")
+	pUpdateWindow          = u32.NewProc("UpdateWindow")
+)
+
+const (
+	CS_HREDRAW          = 0x0002
+	CS_VREDRAW          = 0x0001
+	CW_USEDEFAULT       = 0x80000000
+	IDC_ARROW           = 32512 // Standard arrow
+	IDI_APPLICATION     = 32512
+	IMAGE_ICON          = 1          // Loads an icon
+	LR_DEFAULTSIZE      = 0x00000040 // Loads default-size icon for windows(SM_CXICON x SM_CYICON) if cx, cy are set to zero
+	LR_LOADFROMFILE     = 0x00000010 // Loads the stand-alone image from the file
+	MF_BYCOMMAND        = 0x00000000
+	MFS_DISABLED        = 0x00000003
+	MFT_SEPARATOR       = 0x00000800
+	MFT_STRING          = 0x00000000
+	MIIM_BITMAP         = 0x00000080
+	MIIM_FTYPE          = 0x00000100
+	MIIM_ID             = 0x00000002
+	MIIM_STATE          = 0x00000001
+	MIIM_STRING         = 0x00000040
+	MIIM_SUBMENU        = 0x00000004
+	MIM_APPLYTOSUBMENUS = 0x80000000
+	NIF_ICON            = 0x00000002
+	NIF_INFO            = 0x00000010
+	NIF_MESSAGE         = 0x00000001
+	SW_HIDE             = 0
+	TPM_BOTTOMALIGN     = 0x0020
+	TPM_LEFTALIGN       = 0x0000
+	WM_CLOSE            = 0x0010
+	WM_USER             = 0x0400
+	WS_CAPTION          = 0x00C00000
+	WS_MAXIMIZEBOX      = 0x00010000
+	WS_MINIMIZEBOX      = 0x00020000
+	WS_OVERLAPPED       = 0x00000000
+	WS_OVERLAPPEDWINDOW = WS_OVERLAPPED | WS_CAPTION | WS_SYSMENU | WS_THICKFRAME | WS_MINIMIZEBOX | WS_MAXIMIZEBOX
+	WS_SYSMENU          = 0x00080000
+	WS_THICKFRAME       = 0x00040000
+)
+
+// Not sure if this is actually needed on windows
+func init() {
+	runtime.LockOSThread()
+}
+
+// The POINT structure defines the x- and y- coordinates of a point.
+// https://msdn.microsoft.com/en-us/library/windows/desktop/dd162805(v=vs.85).aspx
+type point struct {
+	X, Y int32
+}

app/tray/wintray/winclass.go

@@ -0,0 +1,45 @@
+//go:build windows
+
+package wintray
+
+import (
+	"unsafe"
+
+	"golang.org/x/sys/windows"
+)
+
+// Contains window class information.
+// It is used with the RegisterClassEx and GetClassInfoEx functions.
+// https://msdn.microsoft.com/en-us/library/ms633577.aspx
+type wndClassEx struct {
+	Size, Style                        uint32
+	WndProc                            uintptr
+	ClsExtra, WndExtra                 int32
+	Instance, Icon, Cursor, Background windows.Handle
+	MenuName, ClassName                *uint16
+	IconSm                             windows.Handle
+}
+
+// Registers a window class for subsequent use in calls to the CreateWindow or CreateWindowEx function.
+// https://msdn.microsoft.com/en-us/library/ms633587.aspx
+func (w *wndClassEx) register() error {
+	w.Size = uint32(unsafe.Sizeof(*w))
+	res, _, err := pRegisterClass.Call(uintptr(unsafe.Pointer(w)))
+	if res == 0 {
+		return err
+	}
+	return nil
+}
+
+// Unregisters a window class, freeing the memory required for the class.
+// https://msdn.microsoft.com/en-us/library/ms644899.aspx
+func (w *wndClassEx) unregister() error {
+	res, _, err := pUnregisterClass.Call(
+		uintptr(unsafe.Pointer(w.ClassName)),
+		uintptr(w.Instance),
+	)
+	if res == 0 {
+		return err
+	}
+	return nil
+}

auth/auth.go

@@ -0,0 +1,61 @@
+package auth
+
+import (
+	"bytes"
+	"context"
+	"crypto/rand"
+	"encoding/base64"
+	"fmt"
+	"io"
+	"log/slog"
+	"os"
+	"path/filepath"
+
+	"golang.org/x/crypto/ssh"
+)
+
+const defaultPrivateKey = "id_ed25519"
+
+func NewNonce(r io.Reader, length int) (string, error) {
+	nonce := make([]byte, length)
+	if _, err := io.ReadFull(r, nonce); err != nil {
+		return "", err
+	}
+
+	return base64.RawURLEncoding.EncodeToString(nonce), nil
+}
+
+func Sign(ctx context.Context, bts []byte) (string, error) {
+	home, err := os.UserHomeDir()
+	if err != nil {
+		return "", err
+	}
+
+	keyPath := filepath.Join(home, ".ollama", defaultPrivateKey)
+
+	privateKeyFile, err := os.ReadFile(keyPath)
+	if err != nil {
+		slog.Info(fmt.Sprintf("Failed to load private key: %v", err))
+		return "", err
+	}
+
+	privateKey, err := ssh.ParsePrivateKey(privateKeyFile)
+	if err != nil {
+		return "", err
+	}
+
+	// get the pubkey, but remove the type
+	publicKey := ssh.MarshalAuthorizedKey(privateKey.PublicKey())
+	parts := bytes.Split(publicKey, []byte(" "))
+	if len(parts) < 2 {
+		return "", fmt.Errorf("malformed public key")
+	}
+
+	signedData, err := privateKey.Sign(rand.Reader, bts)
+	if err != nil {
+		return "", err
+	}
+
+	// signature is <pubkey>:<signature>
+	return fmt.Sprintf("%s:%s", bytes.TrimSpace(parts[1]), base64.StdEncoding.EncodeToString(signedData.Blob)), nil
+}

cmd/interactive.go

@@ -0,0 +1,663 @@
+package cmd
+
+import (
+	"errors"
+	"fmt"
+	"io"
+	"net/http"
+	"os"
+	"path/filepath"
+	"regexp"
+	"sort"
+	"strings"
+
+	"github.com/spf13/cobra"
+	"golang.org/x/exp/slices"
+
+	"github.com/jmorganca/ollama/api"
+	"github.com/jmorganca/ollama/progress"
+	"github.com/jmorganca/ollama/readline"
+)
+
+type MultilineState int
+
+const (
+	MultilineNone MultilineState = iota
+	MultilinePrompt
+	MultilineSystem
+	MultilineTemplate
+)
+
+func loadModel(cmd *cobra.Command, opts *runOptions) error {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		return err
+	}
+
+	p := progress.NewProgress(os.Stderr)
+	defer p.StopAndClear()
+
+	spinner := progress.NewSpinner("")
+	p.Add("", spinner)
+
+	showReq := api.ShowRequest{Name: opts.Model}
+	showResp, err := client.Show(cmd.Context(), &showReq)
+	if err != nil {
+		return err
+	}
+	opts.MultiModal = slices.Contains(showResp.Details.Families, "clip")
+	opts.ParentModel = showResp.Details.ParentModel
+
+	if len(showResp.Messages) > 0 {
+		opts.Messages = append(opts.Messages, showResp.Messages...)
+	}
+
+	chatReq := &api.ChatRequest{
+		Model:    opts.Model,
+		Messages: []api.Message{},
+	}
+	err = client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
+		p.StopAndClear()
+		if len(opts.Messages) > 0 {
+			for _, msg := range opts.Messages {
+				switch msg.Role {
+				case "user":
+					fmt.Printf(">>> %s\n", msg.Content)
+				case "assistant":
+					state := &displayResponseState{}
+					displayResponse(msg.Content, opts.WordWrap, state)
+					fmt.Println()
+					fmt.Println()
+				}
+			}
+		}
+		return nil
+	})
+	if err != nil {
+		return err
+	}
+
+	return nil
+}
+
+func generateInteractive(cmd *cobra.Command, opts runOptions) error {
+	opts.Messages = make([]api.Message, 0)
+
+	err := loadModel(cmd, &opts)
+	if err != nil {
+		return err
+	}
+
+	usage := func() {
+		fmt.Fprintln(os.Stderr, "Available Commands:")
+		fmt.Fprintln(os.Stderr, "  /set            Set session variables")
+		fmt.Fprintln(os.Stderr, "  /show           Show model information")
+		fmt.Fprintln(os.Stderr, "  /load <model>   Load a session or model")
+		fmt.Fprintln(os.Stderr, "  /save <model>   Save your current session")
+		fmt.Fprintln(os.Stderr, "  /bye            Exit")
+		fmt.Fprintln(os.Stderr, "  /?, /help       Help for a command")
+		fmt.Fprintln(os.Stderr, "  /? shortcuts    Help for keyboard shortcuts")
+		fmt.Fprintln(os.Stderr, "")
+		fmt.Fprintln(os.Stderr, "Use \"\"\" to begin a multi-line message.")
+
+		if opts.MultiModal {
+			fmt.Fprintf(os.Stderr, "Use %s to include .jpg or .png images.\n", filepath.FromSlash("/path/to/file"))
+		}
+
+		fmt.Fprintln(os.Stderr, "")
+	}
+
+	usageSet := func() {
+		fmt.Fprintln(os.Stderr, "Available Commands:")
+		fmt.Fprintln(os.Stderr, "  /set parameter ...     Set a parameter")
+		fmt.Fprintln(os.Stderr, "  /set system <string>   Set system message")
+		fmt.Fprintln(os.Stderr, "  /set template <string> Set prompt template")
+		fmt.Fprintln(os.Stderr, "  /set history           Enable history")
+		fmt.Fprintln(os.Stderr, "  /set nohistory         Disable history")
+		fmt.Fprintln(os.Stderr, "  /set wordwrap          Enable wordwrap")
+		fmt.Fprintln(os.Stderr, "  /set nowordwrap        Disable wordwrap")
+		fmt.Fprintln(os.Stderr, "  /set format json       Enable JSON mode")
+		fmt.Fprintln(os.Stderr, "  /set noformat          Disable formatting")
+		fmt.Fprintln(os.Stderr, "  /set verbose           Show LLM stats")
+		fmt.Fprintln(os.Stderr, "  /set quiet             Disable LLM stats")
+		fmt.Fprintln(os.Stderr, "")
+	}
+
+	usageShortcuts := func() {
+		fmt.Fprintln(os.Stderr, "Available keyboard shortcuts:")
+		fmt.Fprintln(os.Stderr, "  Ctrl + a            Move to the beginning of the line (Home)")
+		fmt.Fprintln(os.Stderr, "  Ctrl + e            Move to the end of the line (End)")
+		fmt.Fprintln(os.Stderr, "   Alt + b            Move back (left) one word")
+		fmt.Fprintln(os.Stderr, "   Alt + f            Move forward (right) one word")
+		fmt.Fprintln(os.Stderr, "  Ctrl + k            Delete the sentence after the cursor")
+		fmt.Fprintln(os.Stderr, "  Ctrl + u            Delete the sentence before the cursor")
+		fmt.Fprintln(os.Stderr, "")
+		fmt.Fprintln(os.Stderr, "  Ctrl + l            Clear the screen")
+		fmt.Fprintln(os.Stderr, "  Ctrl + c            Stop the model from responding")
+		fmt.Fprintln(os.Stderr, "  Ctrl + d            Exit ollama (/bye)")
+		fmt.Fprintln(os.Stderr, "")
+	}
+
+	usageShow := func() {
+		fmt.Fprintln(os.Stderr, "Available Commands:")
+		fmt.Fprintln(os.Stderr, "  /show info         Show details for this model")
+		fmt.Fprintln(os.Stderr, "  /show license      Show model license")
+		fmt.Fprintln(os.Stderr, "  /show modelfile    Show Modelfile for this model")
+		fmt.Fprintln(os.Stderr, "  /show parameters   Show parameters for this model")
+		fmt.Fprintln(os.Stderr, "  /show system       Show system message")
+		fmt.Fprintln(os.Stderr, "  /show template     Show prompt template")
+		fmt.Fprintln(os.Stderr, "")
+	}
+
+	// only list out the most common parameters
+	usageParameters := func() {
+		fmt.Fprintln(os.Stderr, "Available Parameters:")
+		fmt.Fprintln(os.Stderr, "  /set parameter seed <int>             Random number seed")
+		fmt.Fprintln(os.Stderr, "  /set parameter num_predict <int>      Max number of tokens to predict")
+		fmt.Fprintln(os.Stderr, "  /set parameter top_k <int>            Pick from top k num of tokens")
+		fmt.Fprintln(os.Stderr, "  /set parameter top_p <float>          Pick token based on sum of probabilities")
+		fmt.Fprintln(os.Stderr, "  /set parameter num_ctx <int>          Set the context size")
+		fmt.Fprintln(os.Stderr, "  /set parameter temperature <float>    Set creativity level")
+		fmt.Fprintln(os.Stderr, "  /set parameter repeat_penalty <float> How strongly to penalize repetitions")
+		fmt.Fprintln(os.Stderr, "  /set parameter repeat_last_n <int>    Set how far back to look for repetitions")
+		fmt.Fprintln(os.Stderr, "  /set parameter num_gpu <int>          The number of layers to send to the GPU")
+		fmt.Fprintln(os.Stderr, "  /set parameter stop \"<string>\", ...   Set the stop parameters")
+		fmt.Fprintln(os.Stderr, "")
+	}
+
+	scanner, err := readline.New(readline.Prompt{
+		Prompt:         ">>> ",
+		AltPrompt:      "... ",
+		Placeholder:    "Send a message (/? for help)",
+		AltPlaceholder: `Use """ to end multi-line input`,
+	})
+	if err != nil {
+		return err
+	}
+
+	fmt.Print(readline.StartBracketedPaste)
+	defer fmt.Printf(readline.EndBracketedPaste)
+
+	var sb strings.Builder
+	var multiline MultilineState
+
+	for {
+		line, err := scanner.Readline()
+		switch {
+		case errors.Is(err, io.EOF):
+			fmt.Println()
+			return nil
+		case errors.Is(err, readline.ErrInterrupt):
+			if line == "" {
+				fmt.Println("\nUse Ctrl + d or /bye to exit.")
+			}
+
+			scanner.Prompt.UseAlt = false
+			sb.Reset()
+
+			continue
+		case err != nil:
+			return err
+		}
+
+		switch {
+		case multiline != MultilineNone:
+			// check if there's a multiline terminating string
+			before, ok := strings.CutSuffix(line, `"""`)
+			sb.WriteString(before)
+			if !ok {
+				fmt.Fprintln(&sb)
+				continue
+			}
+
+			switch multiline {
+			case MultilineSystem:
+				opts.System = sb.String()
+				opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
+				fmt.Println("Set system message.")
+				sb.Reset()
+			case MultilineTemplate:
+				opts.Template = sb.String()
+				fmt.Println("Set prompt template.")
+				sb.Reset()
+			}
+
+			multiline = MultilineNone
+			scanner.Prompt.UseAlt = false
+		case strings.HasPrefix(line, `"""`):
+			line := strings.TrimPrefix(line, `"""`)
+			line, ok := strings.CutSuffix(line, `"""`)
+			sb.WriteString(line)
+			if !ok {
+				// no multiline terminating string; need more input
+				fmt.Fprintln(&sb)
+				multiline = MultilinePrompt
+				scanner.Prompt.UseAlt = true
+			}
+		case scanner.Pasting:
+			fmt.Fprintln(&sb, line)
+			continue
+		case strings.HasPrefix(line, "/list"):
+			args := strings.Fields(line)
+			if err := ListHandler(cmd, args[1:]); err != nil {
+				return err
+			}
+		case strings.HasPrefix(line, "/load"):
+			args := strings.Fields(line)
+			if len(args) != 2 {
+				fmt.Println("Usage:\n  /load <modelname>")
+				continue
+			}
+			opts.Model = args[1]
+			opts.Messages = []api.Message{}
+			fmt.Printf("Loading model '%s'\n", opts.Model)
+			if err := loadModel(cmd, &opts); err != nil {
+				return err
+			}
+			continue
+		case strings.HasPrefix(line, "/save"):
+			args := strings.Fields(line)
+			if len(args) != 2 {
+				fmt.Println("Usage:\n  /save <modelname>")
+				continue
+			}
+
+			client, err := api.ClientFromEnvironment()
+			if err != nil {
+				fmt.Println("error: couldn't connect to ollama server")
+				return err
+			}
+
+			req := &api.CreateRequest{
+				Name:      args[1],
+				Modelfile: buildModelfile(opts),
+			}
+			fn := func(resp api.ProgressResponse) error { return nil }
+			err = client.Create(cmd.Context(), req, fn)
+			if err != nil {
+				fmt.Println("error: couldn't save model")
+				return err
+			}
+			fmt.Printf("Created new model '%s'\n", args[1])
+			continue
+		case strings.HasPrefix(line, "/set"):
+			args := strings.Fields(line)
+			if len(args) > 1 {
+				switch args[1] {
+				case "history":
+					scanner.HistoryEnable()
+				case "nohistory":
+					scanner.HistoryDisable()
+				case "wordwrap":
+					opts.WordWrap = true
+					fmt.Println("Set 'wordwrap' mode.")
+				case "nowordwrap":
+					opts.WordWrap = false
+					fmt.Println("Set 'nowordwrap' mode.")
+				case "verbose":
+					cmd.Flags().Set("verbose", "true")
+					fmt.Println("Set 'verbose' mode.")
+				case "quiet":
+					cmd.Flags().Set("verbose", "false")
+					fmt.Println("Set 'quiet' mode.")
+				case "format":
+					if len(args) < 3 || args[2] != "json" {
+						fmt.Println("Invalid or missing format. For 'json' mode use '/set format json'")
+					} else {
+						opts.Format = args[2]
+						fmt.Printf("Set format to '%s' mode.\n", args[2])
+					}
+				case "noformat":
+					opts.Format = ""
+					fmt.Println("Disabled format.")
+				case "parameter":
+					if len(args) < 4 {
+						usageParameters()
+						continue
+					}
+					params := args[3:]
+					fp, err := api.FormatParams(map[string][]string{args[2]: params})
+					if err != nil {
+						fmt.Printf("Couldn't set parameter: %q\n", err)
+						continue
+					}
+					fmt.Printf("Set parameter '%s' to '%s'\n", args[2], strings.Join(params, ", "))
+					opts.Options[args[2]] = fp[args[2]]
+				case "system", "template":
+					if len(args) < 3 {
+						usageSet()
+						continue
+					}
+
+					if args[1] == "system" {
+						multiline = MultilineSystem
+					} else if args[1] == "template" {
+						multiline = MultilineTemplate
+					}
+
+					line := strings.Join(args[2:], " ")
+					line, ok := strings.CutPrefix(line, `"""`)
+					if !ok {
+						multiline = MultilineNone
+					} else {
+						// only cut suffix if the line is multiline
+						line, ok = strings.CutSuffix(line, `"""`)
+						if ok {
+							multiline = MultilineNone
+						}
+					}
+
+					sb.WriteString(line)
+					if multiline != MultilineNone {
+						scanner.Prompt.UseAlt = true
+						continue
+					}
+
+					if args[1] == "system" {
+						opts.System = sb.String() // for display in modelfile
+						newMessage := api.Message{Role: "system", Content: sb.String()}
+						// Check if the slice is not empty and the last message is from 'system'
+						if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
+							// Replace the last message
+							opts.Messages[len(opts.Messages)-1] = newMessage
+						} else {
+							opts.Messages = append(opts.Messages, newMessage)
+						}
+						fmt.Println("Set system message.")
+						sb.Reset()
+					} else if args[1] == "template" {
+						opts.Template = sb.String()
+						fmt.Println("Set prompt template.")
+						sb.Reset()
+					}
+
+					sb.Reset()
+					continue
+				default:
+					fmt.Printf("Unknown command '/set %s'. Type /? for help\n", args[1])
+				}
+			} else {
+				usageSet()
+			}
+		case strings.HasPrefix(line, "/show"):
+			args := strings.Fields(line)
+			if len(args) > 1 {
+				client, err := api.ClientFromEnvironment()
+				if err != nil {
+					fmt.Println("error: couldn't connect to ollama server")
+					return err
+				}
+				req := &api.ShowRequest{
+					Name:     opts.Model,
+					System:   opts.System,
+					Template: opts.Template,
+					Options:  opts.Options,
+				}
+				resp, err := client.Show(cmd.Context(), req)
+				if err != nil {
+					fmt.Println("error: couldn't get model")
+					return err
+				}
+
+				switch args[1] {
+				case "info":
+					fmt.Println("Model details:")
+					if len(resp.Details.Families) > 0 {
+						fmt.Printf("Family              %s\n", strings.Join(resp.Details.Families, ", "))
+					} else if resp.Details.Family != "" {
+						fmt.Printf("Family              %s\n", resp.Details.Family)
+					}
+					fmt.Printf("Parameter Size      %s\n", resp.Details.ParameterSize)
+					fmt.Printf("Quantization Level  %s\n", resp.Details.QuantizationLevel)
+					fmt.Println("")
+				case "license":
+					if resp.License == "" {
+						fmt.Println("No license was specified for this model.")
+					} else {
+						fmt.Println(resp.License)
+					}
+				case "modelfile":
+					fmt.Println(resp.Modelfile)
+				case "parameters":
+					if resp.Parameters == "" {
+						fmt.Println("No parameters were specified for this model.")
+					} else {
+						if len(opts.Options) > 0 {
+							fmt.Println("User defined parameters:")
+							for k, v := range opts.Options {
+								fmt.Printf("%-*s %v\n", 30, k, v)
+							}
+							fmt.Println()
+						}
+						fmt.Println("Model defined parameters:")
+						fmt.Println(resp.Parameters)
+					}
+				case "system":
+					switch {
+					case opts.System != "":
+						fmt.Println(opts.System + "\n")
+					case resp.System != "":
+						fmt.Println(resp.System + "\n")
+					default:
+						fmt.Println("No system message was specified for this model.")
+					}
+				case "template":
+					switch {
+					case opts.Template != "":
+						fmt.Println(opts.Template + "\n")
+					case resp.Template != "":
+						fmt.Println(resp.Template)
+					default:
+						fmt.Println("No prompt template was specified for this model.")
+					}
+				default:
+					fmt.Printf("Unknown command '/show %s'. Type /? for help\n", args[1])
+				}
+			} else {
+				usageShow()
+			}
+		case strings.HasPrefix(line, "/help"), strings.HasPrefix(line, "/?"):
+			args := strings.Fields(line)
+			if len(args) > 1 {
+				switch args[1] {
+				case "set", "/set":
+					usageSet()
+				case "show", "/show":
+					usageShow()
+				case "shortcut", "shortcuts":
+					usageShortcuts()
+				}
+			} else {
+				usage()
+			}
+		case strings.HasPrefix(line, "/exit"), strings.HasPrefix(line, "/bye"):
+			return nil
+		case strings.HasPrefix(line, "/"):
+			args := strings.Fields(line)
+			isFile := false
+
+			if opts.MultiModal {
+				for _, f := range extractFileNames(line) {
+					if strings.HasPrefix(f, args[0]) {
+						isFile = true
+						break
+					}
+				}
+			}
+
+			if !isFile {
+				fmt.Printf("Unknown command '%s'. Type /? for help\n", args[0])
+				continue
+			}
+
+			sb.WriteString(line)
+		default:
+			sb.WriteString(line)
+		}
+
+		if sb.Len() > 0 && multiline == MultilineNone {
+			newMessage := api.Message{Role: "user", Content: sb.String()}
+
+			if opts.MultiModal {
+				msg, images, err := extractFileData(sb.String())
+				if err != nil {
+					return err
+				}
+
+				// clear all previous images for better responses
+				if len(images) > 0 {
+					for i := range opts.Messages {
+						opts.Messages[i].Images = nil
+					}
+				}
+
+				newMessage.Content = msg
+				newMessage.Images = images
+			}
+
+			opts.Messages = append(opts.Messages, newMessage)
+
+			assistant, err := chat(cmd, opts)
+			if err != nil {
+				return err
+			}
+			if assistant != nil {
+				opts.Messages = append(opts.Messages, *assistant)
+			}
+
+			sb.Reset()
+		}
+	}
+}
+
+func buildModelfile(opts runOptions) string {
+	var mf strings.Builder
+	model := opts.ParentModel
+	if model == "" {
+		model = opts.Model
+	}
+	fmt.Fprintf(&mf, "FROM %s\n", model)
+	if opts.System != "" {
+		fmt.Fprintf(&mf, "SYSTEM \"\"\"%s\"\"\"\n", opts.System)
+	}
+
+	if opts.Template != "" {
+		fmt.Fprintf(&mf, "TEMPLATE \"\"\"%s\"\"\"\n", opts.Template)
+	}
+
+	keys := make([]string, 0)
+	for k := range opts.Options {
+		keys = append(keys, k)
+	}
+	sort.Strings(keys)
+	for _, k := range keys {
+		fmt.Fprintf(&mf, "PARAMETER %s %v\n", k, opts.Options[k])
+	}
+	fmt.Fprintln(&mf)
+
+	for _, msg := range opts.Messages {
+		fmt.Fprintf(&mf, "MESSAGE %s \"\"\"%s\"\"\"\n", msg.Role, msg.Content)
+	}
+
+	return mf.String()
+}
+
+func normalizeFilePath(fp string) string {
+	// Define a map of escaped characters and their replacements
+	replacements := map[string]string{
+		"\\ ":  " ",  // Escaped space
+		"\\(":  "(",  // Escaped left parenthesis
+		"\\)":  ")",  // Escaped right parenthesis
+		"\\[":  "[",  // Escaped left square bracket
+		"\\]":  "]",  // Escaped right square bracket
+		"\\{":  "{",  // Escaped left curly brace
+		"\\}":  "}",  // Escaped right curly brace
+		"\\$":  "$",  // Escaped dollar sign
+		"\\&":  "&",  // Escaped ampersand
+		"\\;":  ";",  // Escaped semicolon
+		"\\'":  "'",  // Escaped single quote
+		"\\\\": "\\", // Escaped backslash
+		"\\*":  "*",  // Escaped asterisk
+		"\\?":  "?",  // Escaped question mark
+	}
+
+	for escaped, actual := range replacements {
+		fp = strings.ReplaceAll(fp, escaped, actual)
+	}
+	return fp
+}
+
+func extractFileNames(input string) []string {
+	// Regex to match file paths starting with optional drive letter, / ./ \ or .\ and include escaped or unescaped spaces (\ or %20)
+	// and followed by more characters and a file extension
+	// This will capture non filename strings, but we'll check for file existence to remove mismatches
+	regexPattern := `(?:[a-zA-Z]:)?(?:\./|/|\\)[\S\\ ]+?\.(?i:jpg|jpeg|png|svg)\b`
+	re := regexp.MustCompile(regexPattern)
+
+	return re.FindAllString(input, -1)
+}
+
+func extractFileData(input string) (string, []api.ImageData, error) {
+	filePaths := extractFileNames(input)
+	var imgs []api.ImageData
+
+	for _, fp := range filePaths {
+		nfp := normalizeFilePath(fp)
+		data, err := getImageData(nfp)
+		if err != nil {
+			if os.IsNotExist(err) {
+				continue
+			}
+			fmt.Fprintf(os.Stderr, "Couldn't process image: %q\n", err)
+			return "", imgs, err
+		}
+		fmt.Fprintf(os.Stderr, "Added image '%s'\n", nfp)
+		input = strings.ReplaceAll(input, fp, "")
+		imgs = append(imgs, data)
+	}
+	return input, imgs, nil
+}
+
+func getImageData(filePath string) ([]byte, error) {
+	file, err := os.Open(filePath)
+	if err != nil {
+		return nil, err
+	}
+	defer file.Close()
+
+	buf := make([]byte, 512)
+	_, err = file.Read(buf)
+	if err != nil {
+		return nil, err
+	}
+
+	contentType := http.DetectContentType(buf)
+	allowedTypes := []string{"image/jpeg", "image/jpg", "image/png"}
+	if !slices.Contains(allowedTypes, contentType) {
+		return nil, fmt.Errorf("invalid image type: %s", contentType)
+	}
+
+	info, err := file.Stat()
+	if err != nil {
+		return nil, err
+	}
+
+	// Check if the file size exceeds 100MB
+	var maxSize int64 = 100 * 1024 * 1024 // 100MB in bytes
+	if info.Size() > maxSize {
+		return nil, fmt.Errorf("file size exceeds maximum limit (100MB)")
+	}
+
+	buf = make([]byte, info.Size())
+	_, err = file.Seek(0, 0)
+	if err != nil {
+		return nil, err
+	}
+
+	_, err = io.ReadFull(file, buf)
+	if err != nil {
+		return nil, err
+	}
+
+	return buf, nil
+}

cmd/interactive_test.go

@@ -0,0 +1,116 @@
+package cmd
+
+import (
+	"bytes"
+	"testing"
+	"text/template"
+
+	"github.com/stretchr/testify/assert"
+
+	"github.com/jmorganca/ollama/api"
+)
+
+func TestExtractFilenames(t *testing.T) {
+	// Unix style paths
+	input := ` some preamble 
+ ./relative\ path/one.png inbetween1 ./not a valid two.jpg inbetween2
+/unescaped space /three.jpeg inbetween3 /valid\ path/dir/four.png "./quoted with spaces/five.svg`
+	res := extractFileNames(input)
+	assert.Len(t, res, 5)
+	assert.Contains(t, res[0], "one.png")
+	assert.Contains(t, res[1], "two.jpg")
+	assert.Contains(t, res[2], "three.jpeg")
+	assert.Contains(t, res[3], "four.png")
+	assert.Contains(t, res[4], "five.svg")
+	assert.NotContains(t, res[4], '"')
+	assert.NotContains(t, res, "inbtween")
+
+	// Windows style paths
+	input = ` some preamble
+ c:/users/jdoe/one.png inbetween1 c:/program files/someplace/two.jpg inbetween2 
+ /absolute/nospace/three.jpeg inbetween3 /absolute/with space/four.png inbetween4
+./relative\ path/five.svg inbetween5 "./relative with/spaces/six.png inbetween6
+d:\path with\spaces\seven.svg inbetween7 c:\users\jdoe\eight.png inbetween8 
+ d:\program files\someplace\nine.png inbetween9 "E:\program files\someplace\ten.svg some ending
+`
+	res = extractFileNames(input)
+	assert.Len(t, res, 10)
+	assert.NotContains(t, res, "inbtween")
+	assert.Contains(t, res[0], "one.png")
+	assert.Contains(t, res[0], "c:")
+	assert.Contains(t, res[1], "two.jpg")
+	assert.Contains(t, res[1], "c:")
+	assert.Contains(t, res[2], "three.jpeg")
+	assert.Contains(t, res[3], "four.png")
+	assert.Contains(t, res[4], "five.svg")
+	assert.Contains(t, res[5], "six.png")
+	assert.Contains(t, res[6], "seven.svg")
+	assert.Contains(t, res[6], "d:")
+	assert.Contains(t, res[7], "eight.png")
+	assert.Contains(t, res[7], "c:")
+	assert.Contains(t, res[8], "nine.png")
+	assert.Contains(t, res[8], "d:")
+	assert.Contains(t, res[9], "ten.svg")
+	assert.Contains(t, res[9], "E:")
+}
+
+func TestModelfileBuilder(t *testing.T) {
+	opts := runOptions{
+		Model:    "hork",
+		System:   "You are part horse and part shark, but all hork. Do horklike things",
+		Template: "This is a template.",
+		Messages: []api.Message{
+			{Role: "user", Content: "Hey there hork!"},
+			{Role: "assistant", Content: "Yes it is true, I am half horse, half shark."},
+		},
+		Options: map[string]interface{}{},
+	}
+
+	opts.Options["temperature"] = 0.9
+	opts.Options["seed"] = 42
+	opts.Options["penalize_newline"] = false
+	opts.Options["stop"] = []string{"hi", "there"}
+
+	mf := buildModelfile(opts)
+	expectedModelfile := `FROM {{.Model}}
+SYSTEM """{{.System}}"""
+TEMPLATE """{{.Template}}"""
+PARAMETER penalize_newline false
+PARAMETER seed 42
+PARAMETER stop [hi there]
+PARAMETER temperature 0.9
+
+MESSAGE user """Hey there hork!"""
+MESSAGE assistant """Yes it is true, I am half horse, half shark."""
+`
+
+	tmpl, err := template.New("").Parse(expectedModelfile)
+	assert.Nil(t, err)
+
+	var buf bytes.Buffer
+	err = tmpl.Execute(&buf, opts)
+	assert.Nil(t, err)
+	assert.Equal(t, buf.String(), mf)
+
+	opts.ParentModel = "horseshark"
+	mf = buildModelfile(opts)
+	expectedModelfile = `FROM {{.ParentModel}}
+SYSTEM """{{.System}}"""
+TEMPLATE """{{.Template}}"""
+PARAMETER penalize_newline false
+PARAMETER seed 42
+PARAMETER stop [hi there]
+PARAMETER temperature 0.9
+
+MESSAGE user """Hey there hork!"""
+MESSAGE assistant """Yes it is true, I am half horse, half shark."""
+`
+
+	tmpl, err = template.New("").Parse(expectedModelfile)
+	assert.Nil(t, err)
+
+	var parentBuf bytes.Buffer
+	err = tmpl.Execute(&parentBuf, opts)
+	assert.Nil(t, err)
+	assert.Equal(t, parentBuf.String(), mf)
+}

cmd/spinner.go

@@ -1,44 +0,0 @@
-package cmd
-
-import (
-	"fmt"
-	"os"
-	"time"
-
-	"github.com/jmorganca/ollama/progressbar"
-)
-
-type Spinner struct {
-	description string
-	*progressbar.ProgressBar
-}
-
-func NewSpinner(description string) *Spinner {
-	return &Spinner{
-		description: description,
-		ProgressBar: progressbar.NewOptions(-1,
-			progressbar.OptionSetWriter(os.Stderr),
-			progressbar.OptionThrottle(60*time.Millisecond),
-			progressbar.OptionSpinnerType(14),
-			progressbar.OptionSetRenderBlankState(true),
-			progressbar.OptionSetElapsedTime(false),
-			progressbar.OptionClearOnFinish(),
-			progressbar.OptionSetDescription(description),
-		),
-	}
-}
-
-func (s *Spinner) Spin(tick time.Duration) {
-	for range time.Tick(tick) {
-		if s.IsFinished() {
-			break
-		}
-
-		s.Add(1)
-	}
-}
-
-func (s *Spinner) Stop() {
-	s.Finish()
-	fmt.Println(s.description)
-}

cmd/start_darwin.go

@@ -0,0 +1,30 @@
+package cmd
+
+import (
+	"context"
+	"fmt"
+	"os"
+	"os/exec"
+	"strings"
+
+	"github.com/jmorganca/ollama/api"
+)
+
+func startApp(ctx context.Context, client *api.Client) error {
+	exe, err := os.Executable()
+	if err != nil {
+		return err
+	}
+	link, err := os.Readlink(exe)
+	if err != nil {
+		return err
+	}
+	if !strings.Contains(link, "Ollama.app") {
+		return fmt.Errorf("could not find ollama app")
+	}
+	path := strings.Split(link, "Ollama.app")
+	if err := exec.Command("/usr/bin/open", "-a", path[0]+"Ollama.app").Run(); err != nil {
+		return err
+	}
+	return waitForServer(ctx, client)
+}

cmd/start_default.go

@@ -0,0 +1,14 @@
+//go:build !windows && !darwin
+
+package cmd
+
+import (
+	"context"
+	"fmt"
+
+	"github.com/jmorganca/ollama/api"
+)
+
+func startApp(ctx context.Context, client *api.Client) error {
+	return fmt.Errorf("could not connect to ollama server, run 'ollama serve' to start it")
+}

cmd/start_windows.go

@@ -0,0 +1,58 @@
+package cmd
+
+import (
+	"context"
+	"errors"
+	"fmt"
+	"os"
+	"os/exec"
+	"path/filepath"
+	"strings"
+	"syscall"
+
+	"github.com/jmorganca/ollama/api"
+)
+
+func startApp(ctx context.Context, client *api.Client) error {
+	// log.Printf("XXX Attempting to find and start ollama app")
+	AppName := "ollama app.exe"
+	exe, err := os.Executable()
+	if err != nil {
+		return err
+	}
+	appExe := filepath.Join(filepath.Dir(exe), AppName)
+	_, err = os.Stat(appExe)
+	if errors.Is(err, os.ErrNotExist) {
+		// Try the standard install location
+		localAppData := os.Getenv("LOCALAPPDATA")
+		appExe = filepath.Join(localAppData, "Ollama", AppName)
+		_, err := os.Stat(appExe)
+		if errors.Is(err, os.ErrNotExist) {
+			// Finally look in the path
+			appExe, err = exec.LookPath(AppName)
+			if err != nil {
+				return fmt.Errorf("could not locate ollama app")
+			}
+		}
+	}
+	// log.Printf("XXX attempting to start app %s", appExe)
+
+	cmd_path := "c:\\Windows\\system32\\cmd.exe"
+	cmd := exec.Command(cmd_path, "/c", appExe)
+	// TODO - these hide flags aren't working - still pops up a command window for some reason
+	cmd.SysProcAttr = &syscall.SysProcAttr{CreationFlags: 0x08000000, HideWindow: true}
+
+	// TODO this didn't help either...
+	cmd.Stdin = strings.NewReader("")
+	cmd.Stdout = os.Stdout
+	cmd.Stderr = os.Stderr
+
+	if err := cmd.Start(); err != nil {
+		return fmt.Errorf("unable to start ollama app %w", err)
+	}
+
+	if cmd.Process != nil {
+		defer cmd.Process.Release() //nolint:errcheck
+	}
+	return waitForServer(ctx, client)
+}

convert/convert.go

@@ -0,0 +1,331 @@
+package convert
+
+import (
+	"bytes"
+	"cmp"
+	"encoding/binary"
+	"encoding/json"
+	"fmt"
+	"io"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"regexp"
+	"slices"
+
+	"github.com/mitchellh/mapstructure"
+	"google.golang.org/protobuf/proto"
+
+	"github.com/jmorganca/ollama/convert/sentencepiece"
+	"github.com/jmorganca/ollama/llm"
+)
+
+type Params struct {
+	Architectures    []string `json:"architectures"`
+	VocabSize        int      `json:"vocab_size"`
+	HiddenSize       int      `json:"hidden_size"`       // n_embd
+	HiddenLayers     int      `json:"num_hidden_layers"` // n_layer
+	ContextSize      int      `json:"max_position_embeddings"`
+	IntermediateSize int      `json:"intermediate_size"`
+	AttentionHeads   int      `json:"num_attention_heads"` // n_head
+	KeyValHeads      int      `json:"num_key_value_heads"`
+	NormEPS          float64  `json:"rms_norm_eps"`
+	RopeFreqBase     float64  `json:"rope_theta"`
+	BoSTokenID       int      `json:"bos_token_id"`
+	EoSTokenID       int      `json:"eos_token_id"`
+}
+
+type MetaData struct {
+	Type    string `mapstructure:"dtype"`
+	Shape   []int  `mapstructure:"shape"`
+	Offsets []int  `mapstructure:"data_offsets"`
+}
+
+func ReadSafeTensors(fn string, offset uint64) ([]llm.Tensor, uint64, error) {
+	f, err := os.Open(fn)
+	if err != nil {
+		return []llm.Tensor{}, 0, err
+	}
+	defer f.Close()
+
+	var jsonSize uint64
+	binary.Read(f, binary.LittleEndian, &jsonSize)
+
+	buf := make([]byte, jsonSize)
+	_, err = io.ReadFull(f, buf)
+	if err != nil {
+		return []llm.Tensor{}, 0, err
+	}
+
+	d := json.NewDecoder(bytes.NewBuffer(buf))
+	d.UseNumber()
+	var parsed map[string]interface{}
+	if err = d.Decode(&parsed); err != nil {
+		return []llm.Tensor{}, 0, err
+	}
+
+	var keys []string
+	for k := range parsed {
+		keys = append(keys, k)
+	}
+
+	slices.Sort(keys)
+
+	slog.Info("converting layers")
+
+	var tensors []llm.Tensor
+	for _, k := range keys {
+		vals := parsed[k].(map[string]interface{})
+		var data MetaData
+		if err = mapstructure.Decode(vals, &data); err != nil {
+			return []llm.Tensor{}, 0, err
+		}
+
+		var size uint64
+		var kind uint32
+		switch len(data.Shape) {
+		case 0:
+			// metadata
+			continue
+		case 1:
+			// convert to float32
+			kind = 0
+			size = uint64(data.Shape[0] * 4)
+		case 2:
+			// convert to float16
+			kind = 1
+			size = uint64(data.Shape[0] * data.Shape[1] * 2)
+		}
+
+		ggufName, err := GetTensorName(k)
+		if err != nil {
+			slog.Error("%v", err)
+			return []llm.Tensor{}, 0, err
+		}
+
+		shape := []uint64{0, 0, 0, 0}
+		for i := range data.Shape {
+			shape[i] = uint64(data.Shape[i])
+		}
+
+		t := llm.Tensor{
+			Name:          ggufName,
+			Kind:          kind,
+			Offset:        offset,
+			Shape:         shape[:],
+			FileName:      fn,
+			OffsetPadding: 8 + jsonSize,
+			FileOffsets:   []uint64{uint64(data.Offsets[0]), uint64(data.Offsets[1])},
+		}
+		slog.Debug(fmt.Sprintf("%v", t))
+		tensors = append(tensors, t)
+		offset += size
+	}
+	return tensors, offset, nil
+}
+
+func GetSafeTensors(dirpath string) ([]llm.Tensor, error) {
+	var tensors []llm.Tensor
+	files, err := filepath.Glob(filepath.Join(dirpath, "/model-*.safetensors"))
+	if err != nil {
+		return []llm.Tensor{}, err
+	}
+
+	var offset uint64
+	for _, f := range files {
+		var t []llm.Tensor
+		var err error
+		t, offset, err = ReadSafeTensors(f, offset)
+		if err != nil {
+			slog.Error("%v", err)
+			return []llm.Tensor{}, err
+		}
+		tensors = append(tensors, t...)
+	}
+	return tensors, nil
+}
+
+func GetParams(dirpath string) (*Params, error) {
+	f, err := os.Open(filepath.Join(dirpath, "config.json"))
+	if err != nil {
+		return nil, err
+	}
+	defer f.Close()
+
+	var params Params
+
+	d := json.NewDecoder(f)
+	err = d.Decode(&params)
+	if err != nil {
+		return nil, err
+	}
+
+	return &params, nil
+}
+
+// Details on gguf's tokenizer can be found at:
+// https://github.com/ggerganov/ggml/blob/master/docs/gguf.md#tokenizer
+type Vocab struct {
+	Tokens []string
+	Scores []float32
+	Types  []int32
+}
+
+func LoadTokens(dirpath string) (*Vocab, error) {
+	slog.Info(fmt.Sprintf("reading vocab from %s", filepath.Join(dirpath, "tokenizer.model")))
+	in, err := os.ReadFile(filepath.Join(dirpath, "tokenizer.model"))
+	if err != nil {
+		return nil, err
+	}
+
+	// To regenerate sentencepiece from the protobufs use:
+	// protoc -I=./ --go_out=./ sentencepiece_model.proto
+	modelProto := &sentencepiece.ModelProto{}
+	if err := proto.Unmarshal(in, modelProto); err != nil {
+		return nil, err
+	}
+
+	v := &Vocab{
+		Tokens: make([]string, 0),
+		Scores: make([]float32, 0),
+		Types:  make([]int32, 0),
+	}
+
+	pieces := modelProto.GetPieces()
+	for _, p := range pieces {
+		v.Tokens = append(v.Tokens, p.GetPiece())
+		v.Scores = append(v.Scores, p.GetScore())
+		t := p.GetType()
+		v.Types = append(v.Types, int32(t))
+	}
+
+	slog.Info(fmt.Sprintf("vocab size: %d", len(v.Tokens)))
+
+	// add any additional tokens
+	addIn, err := os.ReadFile(filepath.Join(dirpath, "added_tokens.json"))
+	if os.IsNotExist(err) {
+		return v, nil
+	} else if err != nil {
+		return nil, err
+	}
+
+	slog.Info("reading user defined tokens")
+
+	var extraTokenData map[string]int
+	if err := json.Unmarshal(addIn, &extraTokenData); err != nil {
+		return nil, err
+	}
+
+	type token struct {
+		key string
+		pos int
+	}
+
+	extraTokens := make([]token, 0)
+	for k, id := range extraTokenData {
+		extraTokens = append(extraTokens, token{k, id})
+	}
+
+	slices.SortFunc(extraTokens, func(a, b token) int {
+		return cmp.Compare(a.pos, b.pos)
+	})
+
+	numToks := len(v.Tokens)
+
+	for cnt, t := range extraTokens {
+		// the token id should match the specific index for the total number of tokens
+		if t.pos != cnt+numToks {
+			return nil, fmt.Errorf("token ID '%d' for '%s' doesn't match total token size", t.pos, t.key)
+		}
+		v.Tokens = append(v.Tokens, t.key)
+		v.Scores = append(v.Scores, -1000.0)
+		v.Types = append(v.Types, int32(llm.GGUFTokenUserDefined))
+	}
+	slog.Info(fmt.Sprintf("vocab size w/ extra tokens: %d", len(v.Tokens)))
+
+	return v, nil
+}
+
+func GetTensorName(n string) (string, error) {
+	tMap := map[string]string{
+		"model.embed_tokens.weight":                           "token_embd.weight",
+		"model.layers.(\\d+).input_layernorm.weight":          "blk.$1.attn_norm.weight",
+		"model.layers.(\\d+).mlp.down_proj.weight":            "blk.$1.ffn_down.weight",
+		"model.layers.(\\d+).mlp.gate_proj.weight":            "blk.$1.ffn_gate.weight",
+		"model.layers.(\\d+).mlp.up_proj.weight":              "blk.$1.ffn_up.weight",
+		"model.layers.(\\d+).post_attention_layernorm.weight": "blk.$1.ffn_norm.weight",
+		"model.layers.(\\d+).self_attn.k_proj.weight":         "blk.$1.attn_k.weight",
+		"model.layers.(\\d+).self_attn.o_proj.weight":         "blk.$1.attn_output.weight",
+		"model.layers.(\\d+).self_attn.q_proj.weight":         "blk.$1.attn_q.weight",
+		"model.layers.(\\d+).self_attn.v_proj.weight":         "blk.$1.attn_v.weight",
+		"lm_head.weight":    "output.weight",
+		"model.norm.weight": "output_norm.weight",
+	}
+
+	v, ok := tMap[n]
+	if ok {
+		return v, nil
+	}
+
+	// quick hack to rename the layers to gguf format
+	for k, v := range tMap {
+		re := regexp.MustCompile(k)
+		newName := re.ReplaceAllString(n, v)
+		if newName != n {
+			return newName, nil
+		}
+	}
+
+	return "", fmt.Errorf("couldn't find a layer name for '%s'", n)
+}
+
+func WriteGGUF(name string, tensors []llm.Tensor, params *Params, vocab *Vocab) (string, error) {
+	c := llm.ContainerGGUF{
+		ByteOrder: binary.LittleEndian,
+	}
+
+	m := llm.NewGGUFModel(&c)
+	m.Tensors = tensors
+	m.KV["general.architecture"] = "llama"
+	m.KV["general.name"] = name
+	m.KV["llama.context_length"] = uint32(params.ContextSize)
+	m.KV["llama.embedding_length"] = uint32(params.HiddenSize)
+	m.KV["llama.block_count"] = uint32(params.HiddenLayers)
+	m.KV["llama.feed_forward_length"] = uint32(params.IntermediateSize)
+	m.KV["llama.rope.dimension_count"] = uint32(128)
+	m.KV["llama.attention.head_count"] = uint32(params.AttentionHeads)
+	m.KV["llama.attention.head_count_kv"] = uint32(params.KeyValHeads)
+	m.KV["llama.attention.layer_norm_rms_epsilon"] = float32(params.NormEPS)
+	m.KV["llama.rope.freq_base"] = float32(params.RopeFreqBase)
+	m.KV["general.file_type"] = uint32(1)
+	m.KV["tokenizer.ggml.model"] = "llama"
+
+	m.KV["tokenizer.ggml.tokens"] = vocab.Tokens
+	m.KV["tokenizer.ggml.scores"] = vocab.Scores
+	m.KV["tokenizer.ggml.token_type"] = vocab.Types
+
+	m.KV["tokenizer.ggml.bos_token_id"] = uint32(params.BoSTokenID)
+	m.KV["tokenizer.ggml.eos_token_id"] = uint32(params.EoSTokenID)
+	m.KV["tokenizer.ggml.unknown_token_id"] = uint32(0)
+	m.KV["tokenizer.ggml.add_bos_token"] = true
+	m.KV["tokenizer.ggml.add_eos_token"] = false
+
+	// llamacpp sets the chat template, however we don't need to set it since we pass it in through a layer
+	// m.KV["tokenizer.chat_template"] = "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}" // XXX removeme
+
+	c.V3.NumTensor = uint64(len(tensors))
+	c.V3.NumKV = uint64(len(m.KV))
+
+	f, err := os.CreateTemp("", "ollama-gguf")
+	if err != nil {
+		return "", err
+	}
+	defer f.Close()
+
+	err = m.Encode(f)
+	if err != nil {
+		return "", err
+	}
+
+	return f.Name(), nil
+}

convert/sentencepiece_model.proto

@@ -0,0 +1,333 @@
+// Copyright 2016 Google Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.!
+
+syntax = "proto2";
+
+// TODO(taku): Needs to use LITE RUNTIME in OSS release.
+option optimize_for = LITE_RUNTIME;
+option go_package = "./sentencepiece";
+
+package sentencepiece;
+
+// TrainerSpec encodes a various parameters for SentencePiece training.
+// Next id: 55
+message TrainerSpec {
+  ///////////////////////////////////////////////////////////////////
+  // General parameters
+  //
+  // Input corpus files.
+  //  Trainer accepts the following two formats:
+  //  A) Monolingual: plain text, one sentence per line.
+  //  B) Bilingual:   TSV, source sentence <tab> target sentence
+  //  When bilingual data is passed, shared vocabulary model is built.
+  //  Note that the input file must be raw corpus, not a preprocessed corpus.
+  //  Trainer only loads the first `input_sentence_size` sentences specified
+  //  with this parameter.
+  repeated string input = 1;
+
+  // Input corpus format:
+  // "text": one-sentence-per-line text format (default)
+  // "tsv":  sentence <tab> freq
+  optional string input_format = 7;
+
+  // Output model file prefix.
+  // <model_prefix>.model and <model_prefix>.vocab are generated.
+  optional string model_prefix = 2;
+
+  // Model type. only have UNIGRAM now.
+  enum ModelType {
+    UNIGRAM = 1;  // Unigram language model with dynamic algorithm
+    BPE = 2;      // Byte Pair Encoding
+    WORD = 3;     // Delimitered by whitespace.
+    CHAR = 4;     // tokenizes into character sequence
+  }
+  optional ModelType model_type = 3 [default = UNIGRAM];
+
+  // Vocabulary size. 8k is the default size.
+  optional int32 vocab_size = 4 [default = 8000];
+
+  // List of the languages this model can accept.
+  // Since the model is language-agnostic, this field is used as a reference.
+  repeated string accept_language = 5;
+
+  // Size of self-test samples, which are encoded in the model file.
+  optional int32 self_test_sample_size = 6 [default = 0];
+
+  // Whether to use DP version of sentencepiece. Use it with TSV input format
+  // (requires precomputed word tab counts to work).
+  optional bool enable_differential_privacy = 50 [default = false];
+  // Set these parameters if you need DP version of sentencepiece.
+  // std of noise to add.
+  optional float differential_privacy_noise_level = 51 [default = 0.0];
+  // Clipping threshold to apply after adding noise. All the words with
+  // frequency less than this value are dropped.
+  optional uint64 differential_privacy_clipping_threshold = 52 [default = 0];
+
+  ///////////////////////////////////////////////////////////////////
+  // Training parameters.
+  //
+  // Uses characters which cover the corpus with the ratio of `chars_coverage`.
+  // This parameter determines the set of basic Alphabet of sentence piece.
+  // 1.0 - `chars_coverage` characters are treated as UNK.
+  // See also required_chars field.
+  optional float character_coverage = 10 [default = 0.9995];
+
+  // Maximum size of sentences the trainer loads from `input` parameter.
+  // Trainer simply loads the `input` files in sequence.
+  // It is better to shuffle the input corpus randomly.
+  optional uint64 input_sentence_size = 11 [default = 0];
+  optional bool shuffle_input_sentence = 19 [default = true];
+
+  // Maximum size of sentences to make seed sentence pieces.
+  // Extended suffix array is constructed to extract frequent
+  // sub-strings from the corpus. This uses 20N working space,
+  // where N is the size of corpus.
+  optional int32 mining_sentence_size = 12 [deprecated = true];
+
+  // Maximum size of sentences to train sentence pieces.
+  optional int32 training_sentence_size = 13 [deprecated = true];
+
+  // The size of seed sentencepieces.
+  // `seed_sentencepiece_size` must be larger than `vocab_size`.
+  optional int32 seed_sentencepiece_size = 14 [default = 1000000];
+
+  // In every EM sub-iterations, keeps top
+  // `shrinking_factor` * `current sentencepieces size` with respect to
+  // the loss of the sentence piece. This value should be smaller than 1.0.
+  optional float shrinking_factor = 15 [default = 0.75];
+
+  // The maximum sentence length in byte. The sentences with the length
+  // larger than `max_sentence_length` is simply ignored.
+  // Longer input tends to bring the following risks:
+  //  * Overflow during EM training (unigram language model only)
+  //  * Performance drop because of O(n log n) cost in BPE.
+  optional int32 max_sentence_length = 18 [default = 4192];
+
+  // Number of threads in the training.
+  optional int32 num_threads = 16 [default = 16];
+
+  // Number of EM sub iterations.
+  optional int32 num_sub_iterations = 17 [default = 2];
+
+  ///////////////////////////////////////////////////////////////////
+  // SentencePiece parameters which control the shapes of sentence piece.
+  //
+  // Maximum length of sentencepiece.
+  optional int32 max_sentencepiece_length = 20 [default = 16];
+
+  // Uses Unicode script to split sentence pieces.
+  // When `split_by_unicode_script` is true, we do not allow sentence piece to
+  // include multiple Unicode scripts, e.g. "F1" is not a valid piece.
+  // Exception: CJ characters (Hiragana/Katakana/Han) are all handled
+  // as one script type, since Japanese word can consist of multiple scripts.
+  // This exception is always applied regardless of the accept-language
+  // parameter.
+  optional bool split_by_unicode_script = 21 [default = true];
+
+  // When `split_by_number` is true, put a boundary between number and
+  // non-number transition. If we want to treat "F1" is one token, set this flag
+  // to be false.
+  optional bool split_by_number = 23 [default = true];
+
+  // Use a white space to split sentence pieces.
+  // When `split_by_whitespace` is false, we may have the piece containing
+  // a white space in the middle. e.g., "in_the".
+  optional bool split_by_whitespace = 22 [default = true];
+
+  // Adds whitespace symbol (_) as a suffix instead of prefix. e.g., _hello =>
+  // hello_. When `treat_whitespace_as_suffix` is true,
+  // NormalizerSpec::add_dummy_prefix will add the dummy whitespace to the end
+  // of sentence.
+  optional bool treat_whitespace_as_suffix = 24 [default = false];
+
+  // Allows pieces that only contain whitespaces instead of appearing only as
+  // prefix or suffix of other pieces.
+  optional bool allow_whitespace_only_pieces = 26 [default = false];
+
+  // Split all digits (0-9) into separate pieces.
+  optional bool split_digits = 25 [default = false];
+
+  // Defines the pre-tokenization delimiter.
+  // When specified, no pieces crossing this delimiter is not included
+  // in the vocab. Then the delimiter string is virtually ignored
+  // during the training. This field can allows constraints on the vocabulary
+  // selection. Note that this field is available on unigram mode.
+  optional string pretokenization_delimiter = 53 [ default = ""];
+
+  ///////////////////////////////////////////////////////////////////
+  // Vocabulary management
+  //
+  // Defines control symbols used as an indicator to
+  // change the behavior of the decoder. <s> and </s> are pre-defined.
+  // We can use this field to encode various meta information,
+  // including language indicator in multilingual model.
+  // These symbols are not visible to users, but visible to
+  // the decoder. Note that when the input sentence contains control symbols,
+  // they are not treated as one token, but segmented into normal pieces.
+  // Control symbols must be inserted independently from the segmentation.
+  repeated string control_symbols = 30;
+
+  // Defines user defined symbols.
+  // These symbols are added with extremely high score
+  // so they are always treated as one unique symbol in any context.
+  // Typical usage of user_defined_symbols is placeholder for named entities.
+  repeated string user_defined_symbols = 31;
+
+  // Defines required characters. Each UTF8 character in this string is included
+  // in the character set regardless of character_coverage value. Unlike
+  // user_defined_symbols, these characters have scores based on the frequency
+  // on input sentences, and the model can form subwords using characters
+  // in this field.
+  optional string required_chars = 36;
+
+  // Decomposes unknown pieces into UTF-8 bytes.
+  optional bool byte_fallback = 35 [default = false];
+
+  // When creating the vocabulary file, defines whether or not to additionally
+  // output the score for each piece.
+  optional bool vocabulary_output_piece_score = 32 [default = true];
+
+  // `vocab_size` is treated as hard limit. Crash if
+  // the model can not produce the vocab of size `vocab_size`,
+  // When `hard_vocab_limit` is false, vocab_size is treated
+  // as soft limit. Note that when model_type=char,
+  // always assumes hard_vocab_limit = false.
+  optional bool hard_vocab_limit = 33 [default = true];
+
+  // use all symbols for vocab extraction. This flag is valid
+  // if model type is either CHAR or WORD
+  optional bool use_all_vocab = 34 [default = false];
+
+  ///////////////////////////////////////////////////////////////////
+  // Reserved special meta tokens.
+  // * -1 is not used.
+  // * unk_id must not be -1.
+  // Id must starts with 0 and be contigous.
+  optional int32 unk_id = 40 [default = 0];   // <unk>
+  optional int32 bos_id = 41 [default = 1];   // <s>
+  optional int32 eos_id = 42 [default = 2];   // </s>
+  optional int32 pad_id = 43 [default = -1];  // <pad> (padding)
+  optional string unk_piece = 45 [default = "<unk>"];
+  optional string bos_piece = 46 [default = "<s>"];
+  optional string eos_piece = 47 [default = "</s>"];
+  optional string pad_piece = 48 [default = "<pad>"];
+
+  // Encodes <unk> into U+2047 (DOUBLE QUESTION MARK),
+  // since this character can be useful both for user and
+  // developer. We can easily figure out that <unk> is emitted.
+  optional string unk_surface = 44 [default = " \xE2\x81\x87 "];
+
+  // Increase bit depth to allow unigram model training on large
+  // (>10M sentences) corpora. A Side-effect of enabling this flag
+  // is increased memory usage.
+  optional bool train_extremely_large_corpus = 49 [default = false];
+
+ // Path to a seed sentencepieces file, with one tab-separated
+  // seed sentencepiece <tab> frequency per line.
+  optional string seed_sentencepieces_file = 54 [default = ""];
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}
+
+// NormalizerSpec encodes a various parameters for string normalizaiton
+message NormalizerSpec {
+  // name of normalization rule.
+  optional string name = 1;
+
+  // Pre-compiled normalization rule created by
+  // Builder::GetPrecompiledCharsMap() or Builder::CompileCharsMap() method.
+  // Usually this field is set by Builder::GetNormalizerSpec() method.
+  optional bytes precompiled_charsmap = 2;
+
+  // Adds dummy whitespace at the beginning of text in order to
+  // treat "world" in "world" and "hello world" in the same way.
+  optional bool add_dummy_prefix = 3 [default = true];
+
+  // Removes leading, trailing, and duplicate internal whitespace.
+  optional bool remove_extra_whitespaces = 4 [default = true];
+
+  // Replaces whitespace with meta symbol.
+  // This field must be true to train sentence piece model.
+  optional bool escape_whitespaces = 5 [default = true];
+
+  // Custom normalization rule file in TSV format.
+  // https://github.com/google/sentencepiece/blob/master/doc/normalization.md
+  // This field is only used in SentencePieceTrainer::Train() method, which
+  // compiles the rule into the binary rule stored in `precompiled_charsmap`.
+  optional string normalization_rule_tsv = 6;
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}
+
+// Proto to store samples for self-testing.
+message SelfTestData {
+  message Sample {
+    optional string input = 1;
+    optional string expected = 2;
+  }
+  repeated Sample samples = 1;
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}
+
+// ModelProto stores model parameters.
+// SentencePieceProcessor is supposed to be self-contained.
+// All settings/parameters which may change the behavior must be encoded
+// in ModelProto.
+message ModelProto {
+  message SentencePiece {
+    enum Type {
+      NORMAL = 1;        // normal symbol
+      UNKNOWN = 2;       // unknown symbol. only <unk> for now.
+      CONTROL = 3;       // control symbols. </s>, <s>, <2ja> etc.
+      USER_DEFINED = 4;  // user defined symbols.
+                         // Typical usage of USER_DEFINED symbol
+                         // is placeholder.
+      BYTE = 6;          // byte symbols. Used when `byte_fallback` is true.
+      UNUSED = 5;        // this piece is not used.
+    }
+    optional string piece = 1;  // piece must not be empty.
+    optional float score = 2;
+    optional Type type = 3 [default = NORMAL];
+
+    // Customized extensions: the range of field numbers
+    // are open to third-party extensions.
+    extensions 200 to max;
+  }
+
+  // Sentence pieces with scores.
+  repeated SentencePiece pieces = 1;
+
+  // Spec used to generate this model file.
+  optional TrainerSpec trainer_spec = 2;
+
+  // Spec for text normalization.
+  optional NormalizerSpec normalizer_spec = 3;
+
+  // Stores sample input and its expected segmentation to verify the model.
+  optional SelfTestData self_test_data = 4;
+
+  // Spec for text de-normalization.
+  optional NormalizerSpec denormalizer_spec = 5;
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}

docs/README.md

@@ -0,0 +1,21 @@
+# Documentation
+
+### Getting Started
+* [Quickstart](../README.md#quickstart)
+* [Examples](../examples)
+* [Importing models](./import.md)
+* [Linux Documentation](./linux.md)
+* [Windows Documentation](./windows.md)
+* [Docker Documentation](https://hub.docker.com/r/ollama/ollama)
+
+### Reference
+
+* [API Reference](./api.md)
+* [Modelfile Reference](./modelfile.md)
+* [OpenAI Compatibility](./openai.md)
+
+### Resources
+
+* [Troubleshooting Guide](./troubleshooting.md)
+* [FAQ](./faq.md)
+* [Development guide](./development.md)

docs/development.md

@@ -2,45 +2,143 @@
 
 Install required tools:
 
-```
-brew install go
+- cmake version 3.24 or higher
+- go version 1.22 or higher
+- gcc version 11.4.0 or higher
+
+```bash
+brew install go cmake gcc
 ```
 
-Enable CGO:
+Optionally enable debugging and more verbose logging:
 
+```bash
+# At build time
+export CGO_CFLAGS="-g"
+
+# At runtime
+export OLLAMA_DEBUG=1
 ```
-export CGO_ENABLED=1
+
+Get the required libraries and build the native LLM code:
+
+```bash
+go generate ./...
 ```
 
 Then build ollama:
 
-```
+```bash
 go build .
 ```
 
 Now you can run `ollama`:
 
-```
+```bash
 ./ollama
 ```
 
-## Releasing
+### Linux
 
-To release a new version of Ollama you'll need to set some environment variables:
+#### Linux CUDA (NVIDIA)
 
-* `GITHUB_TOKEN`: your GitHub token
-* `APPLE_IDENTITY`: the Apple signing identity (macOS only)
-* `APPLE_ID`: your Apple ID
-* `APPLE_PASSWORD`: your Apple ID app-specific password
-* `APPLE_TEAM_ID`: the Apple team ID for the signing identity
-* `TELEMETRY_WRITE_KEY`: segment write key for telemetry
+_Your operating system distribution may already have packages for NVIDIA CUDA. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
 
-Then run the publish script with the target version:
+Install `cmake` and `golang` as well as [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
+development and runtime packages.
+
+Typically the build scripts will auto-detect CUDA, however, if your Linux distro
+or installation approach uses unusual paths, you can specify the location by
+specifying an environment variable `CUDA_LIB_DIR` to the location of the shared
+libraries, and `CUDACXX` to the location of the nvcc compiler. You can customize
+set set of target CUDA architectues by setting `CMAKE_CUDA_ARCHITECTURES` (e.g. "50;60;70")
+
+Then generate dependencies:
 
 ```
-VERSION=0.0.2 ./scripts/publish.sh
+go generate ./...
 ```
 
+Then build the binary:
+
+```
+go build .
+```
+
+#### Linux ROCm (AMD)
+
+_Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
+
+Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) development packages first, as well as `cmake` and `golang`.
+
+Typically the build scripts will auto-detect ROCm, however, if your Linux distro
+or installation approach uses unusual paths, you can specify the location by
+specifying an environment variable `ROCM_PATH` to the location of the ROCm
+install (typically `/opt/rocm`), and `CLBlast_DIR` to the location of the
+CLBlast install (typically `/usr/lib/cmake/CLBlast`). You can also customize
+the AMD GPU targets by setting AMDGPU_TARGETS (e.g. `AMDGPU_TARGETS="gfx1101;gfx1102"`)
+
+```
+go generate ./...
+```
+
+Then build the binary:
+
+```
+go build .
+```
+
+ROCm requires elevated privileges to access the GPU at runtime. On most distros you can add your user account to the `render` group, or run as root.
+
+#### Advanced CPU Settings
+
+By default, running `go generate ./...` will compile a few different variations
+of the LLM library based on common CPU families and vector math capabilities,
+including a lowest-common-denominator which should run on almost any 64 bit CPU
+somewhat slowly. At runtime, Ollama will auto-detect the optimal variation to
+load. If you would like to build a CPU-based build customized for your
+processor, you can set `OLLAMA_CUSTOM_CPU_DEFS` to the llama.cpp flags you would
+like to use. For example, to compile an optimized binary for an Intel i9-9880H,
+you might use:
+
+```
+OLLAMA_CUSTOM_CPU_DEFS="-DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_F16C=on -DLLAMA_FMA=on" go generate ./...
+go build .
+```
+
+#### Containerized Linux Build
+
+If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
+
+### Windows
+
+Note: The windows build for Ollama is still under development.
+
+Install required tools:
+
+- MSVC toolchain - C/C++ and cmake as minimal requirements - You must build from a "Developer Shell" with the environment variables set
+- go version 1.22 or higher
+- MinGW (pick one variant) with GCC.
+  - <https://www.mingw-w64.org/>
+  - <https://www.msys2.org/>
+
+```powershell
+$env:CGO_ENABLED="1"
+
+go generate ./...
+
+go build .
+```
+
+#### Windows CUDA (NVIDIA)
+
+In addition to the common Windows development tools described above, install CUDA **AFTER** you install MSVC.
+
+- [NVIDIA CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html)
 
 
+#### Windows ROCm (AMD Radeon)
 
+In addition to the common Windows development tools described above, install AMDs HIP package **AFTER** you install MSVC
+
+- [AMD HIP](https://www.amd.com/en/developer/resources/rocm-hub/hip-sdk.html)

docs/faq.md

@@ -0,0 +1,205 @@
+# FAQ
+
+## How can I upgrade Ollama?
+
+Ollama on macOS and Windows will automatically download updates. Click on the taskbar or menubar item and then click "Restart to update" to apply the update. Updates can also be installed by downloading the latest version [manually](https://ollama.com/download/).
+
+On Linux, re-run the install script:
+
+```
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+## How can I view the logs?
+
+Review the [Troubleshooting](./troubleshooting.md) docs for more about using logs.
+
+## How can I specify the context window size?
+
+By default, Ollama uses a context window size of 2048 tokens.
+
+To change this when using `ollama run`, use `/set parameter`:
+
+```
+/set parameter num_ctx 4096
+```
+
+When using the API, specify the `num_ctx` parameter:
+
+```
+curl http://localhost:11434/api/generate -d '{
+  "model": "llama2",
+  "prompt": "Why is the sky blue?",
+  "options": {
+    "num_ctx": 4096
+  }
+}'
+```
+
+## How do I configure Ollama server?
+
+Ollama server can be configured with environment variables.
+
+### Setting environment variables on Mac
+
+If Ollama is run as a macOS application, environment variables should be set using `launchctl`:
+
+1. For each environment variable, call `launchctl setenv`.
+
+    ```bash
+    launchctl setenv OLLAMA_HOST "0.0.0.0"
+    ```
+
+2. Restart Ollama application.
+
+### Setting environment variables on Linux
+
+If Ollama is run as a systemd service, environment variables should be set using `systemctl`:
+
+1. Edit the systemd service by calling `systemctl edit ollama.service`. This will open an editor.
+
+2. For each environment variable, add a line `Environment` under section `[Service]`:
+
+    ```ini
+    [Service]
+    Environment="OLLAMA_HOST=0.0.0.0"
+    ```
+
+3. Save and exit.
+
+4. Reload `systemd` and restart Ollama:
+
+   ```bash
+   systemctl daemon-reload
+   systemctl restart ollama
+   ```
+
+### Setting environment variables on Windows
+
+On windows, Ollama inherits your user and system environment variables.
+
+1. First Quit Ollama by clicking on it in the task bar
+
+2. Edit system environment variables from the control panel
+
+3. Edit or create New variable(s) for your user account for `OLLAMA_HOST`, `OLLAMA_MODELS`, etc.
+
+4. Click OK/Apply to save 
+
+5. Run `ollama` from a new terminal window 
+
+
+## How can I expose Ollama on my network?
+
+Ollama binds 127.0.0.1 port 11434 by default. Change the bind address with the `OLLAMA_HOST` environment variable.
+
+Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
+
+## How can I allow additional web origins to access Ollama?
+
+Ollama allows cross-origin requests from `127.0.0.1` and `0.0.0.0` by default. Additional origins can be configured with `OLLAMA_ORIGINS`.
+
+Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
+
+## Where are models stored?
+
+- macOS: `~/.ollama/models`
+- Linux: `/usr/share/ollama/.ollama/models`
+- Windows: `C:\Users\<username>\.ollama\models`
+
+### How do I set them to a different location?
+
+If a different directory needs to be used, set the environment variable `OLLAMA_MODELS` to the chosen directory.
+
+Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
+
+## Does Ollama send my prompts and answers back to ollama.com?
+
+No. Ollama runs locally, and conversation data does not leave your machine.
+
+## How can I use Ollama in Visual Studio Code?
+
+There is already a large collection of plugins available for VSCode as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/jmorganca/ollama#extensions--plugins) at the bottom of the main repository readme.
+
+## How do I use Ollama behind a proxy?
+
+Ollama is compatible with proxy servers if `HTTP_PROXY` or `HTTPS_PROXY` are configured. When using either variables, ensure it is set where `ollama serve` can access the values. When using `HTTPS_PROXY`, ensure the proxy certificate is installed as a system certificate. Refer to the section above for how to use environment variables on your platform.
+
+### How do I use Ollama behind a proxy in Docker?
+
+The Ollama Docker container image can be configured to use a proxy by passing `-e HTTPS_PROXY=https://proxy.example.com` when starting the container.
+
+Alternatively, the Docker daemon can be configured to use a proxy. Instructions are available for Docker Desktop on [macOS](https://docs.docker.com/desktop/settings/mac/#proxies), [Windows](https://docs.docker.com/desktop/settings/windows/#proxies), and [Linux](https://docs.docker.com/desktop/settings/linux/#proxies), and Docker [daemon with systemd](https://docs.docker.com/config/daemon/systemd/#httphttps-proxy).
+
+Ensure the certificate is installed as a system certificate when using HTTPS. This may require a new Docker image when using a self-signed certificate.
+
+```dockerfile
+FROM ollama/ollama
+COPY my-ca.pem /usr/local/share/ca-certificates/my-ca.crt
+RUN update-ca-certificates
+```
+
+Build and run this image:
+
+```shell
+docker build -t ollama-with-ca .
+docker run -d -e HTTPS_PROXY=https://my.proxy.example.com -p 11434:11434 ollama-with-ca
+```
+
+## How do I use Ollama with GPU acceleration in Docker?
+
+The Ollama Docker container can be configured with GPU acceleration in Linux or Windows (with WSL2). This requires the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit). See [ollama/ollama](https://hub.docker.com/r/ollama/ollama) for more details.
+
+GPU acceleration is not available for Docker Desktop in macOS due to the lack of GPU passthrough and emulation.
+
+## Why is networking slow in WSL2 on Windows 10?
+
+This can impact both installing Ollama, as well as downloading models.
+
+Open `Control Panel > Networking and Internet > View network status and tasks` and click on `Change adapter settings` on the left panel. Find the `vEthernel (WSL)` adapter, right click and select `Properties`.
+Click on `Configure` and open the `Advanced` tab. Search through each of the properties until you find `Large Send Offload Version 2 (IPv4)` and `Large Send Offload Version 2 (IPv6)`. *Disable* both of these
+properties.
+
+## How can I pre-load a model to get faster response times?
+
+If you are using the API you can preload a model by sending the Ollama server an empty request. This works with both the `/api/generate` and `/api/chat` API endpoints.
+
+To preload the mistral model using the generate endpoint, use:
+```shell
+curl http://localhost:11434/api/generate -d '{"model": "mistral"}'
+```
+
+To use the chat completions endpoint, use:
+```shell
+curl http://localhost:11434/api/chat -d '{"model": "mistral"}'
+```
+
+## How do I keep a model loaded in memory or make it unload immediately?
+
+By default models are kept in memory for 5 minutes before being unloaded. This allows for quicker response times if you are making numerous requests to the LLM. You may, however, want to free up the memory before the 5 minutes have elapsed or keep the model loaded indefinitely. Use the `keep_alive` parameter with either the `/api/generate` and `/api/chat` API endpoints to control how long the model is left in memory.
+
+The `keep_alive` parameter can be set to:
+* a duration string (such as "10m" or "24h")
+* a number in seconds (such as 3600)
+* any negative number which will keep the model loaded in memory (e.g. -1 or "-1m")
+* '0' which will unload the model immediately after generating a response
+
+For example, to preload a model and leave it in memory use:
+```shell
+curl http://localhost:11434/api/generate -d '{"model": "llama2", "keep_alive": -1}'
+```
+
+To unload the model and free up memory use:
+```shell
+curl http://localhost:11434/api/generate -d '{"model": "llama2", "keep_alive": 0}'
+```
+
+## Controlling which GPUs to use
+
+By default, on Linux and Windows, Ollama will attempt to use Nvidia GPUs, or
+Radeon GPUs, and will use all the GPUs it can find. You can limit which GPUs
+will be utilized by setting the environment variable `CUDA_VISIBLE_DEVICES` for
+NVIDIA cards, or `HIP_VISIBLE_DEVICES` for Radeon GPUs to a comma delimited list
+of GPU IDs.  You can see the list of devices with GPU tools such as `nvidia-smi` or
+`rocminfo`. You can set to an invalid GPU ID (e.g., "-1") to bypass the GPU and
+fallback to CPU.

docs/import.md

@@ -0,0 +1,168 @@
+# Import a model
+
+This guide walks through importing a GGUF, PyTorch or Safetensors model.
+
+## Importing (GGUF)
+
+### Step 1: Write a `Modelfile`
+
+Start by creating a `Modelfile`. This file is the blueprint for your model, specifying weights, parameters, prompt templates and more.
+
+```
+FROM ./mistral-7b-v0.1.Q4_0.gguf
+```
+
+(Optional) many chat models require a prompt template in order to answer correctly. A default prompt template can be specified with the `TEMPLATE` instruction in the `Modelfile`:
+
+```
+FROM ./mistral-7b-v0.1.Q4_0.gguf
+TEMPLATE "[INST] {{ .Prompt }} [/INST]"
+```
+
+### Step 2: Create the Ollama model
+
+Finally, create a model from your `Modelfile`:
+
+```
+ollama create example -f Modelfile
+```
+
+### Step 3: Run your model
+
+Next, test the model with `ollama run`:
+
+```
+ollama run example "What is your favourite condiment?"
+```
+
+## Importing (PyTorch & Safetensors)
+
+> Importing from PyTorch and Safetensors is a longer process than importing from GGUF. Improvements that make it easier are a work in progress.
+
+### Setup
+
+First, clone the `ollama/ollama` repo:
+
+```
+git clone git@github.com:ollama/ollama.git ollama
+cd ollama
+```
+
+and then fetch its `llama.cpp` submodule:
+
+```shell
+git submodule init
+git submodule update llm/llama.cpp
+```
+
+Next, install the Python dependencies:
+
+```
+python3 -m venv llm/llama.cpp/.venv
+source llm/llama.cpp/.venv/bin/activate
+pip install -r llm/llama.cpp/requirements.txt
+```
+
+Then build the `quantize` tool:
+
+```
+make -C llm/llama.cpp quantize
+```
+
+### Clone the HuggingFace repository (optional)
+
+If the model is currently hosted in a HuggingFace repository, first clone that repository to download the raw model.
+
+Install [Git LFS](https://docs.github.com/en/repositories/working-with-files/managing-large-files/installing-git-large-file-storage), verify it's installed, and then clone the model's repository:
+
+```
+git lfs install
+git clone https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 model
+```
+
+### Convert the model
+
+> Note: some model architectures require using specific convert scripts. For example, Qwen models require running `convert-hf-to-gguf.py` instead of `convert.py`
+
+```
+python llm/llama.cpp/convert.py ./model --outtype f16 --outfile converted.bin
+```
+
+### Quantize the model
+
+```
+llm/llama.cpp/quantize converted.bin quantized.bin q4_0
+```
+
+### Step 3: Write a `Modelfile`
+
+Next, create a `Modelfile` for your model:
+
+```
+FROM quantized.bin
+TEMPLATE "[INST] {{ .Prompt }} [/INST]"
+```
+
+### Step 4: Create the Ollama model
+
+Finally, create a model from your `Modelfile`:
+
+```
+ollama create example -f Modelfile
+```
+
+### Step 5: Run your model
+
+Next, test the model with `ollama run`:
+
+```
+ollama run example "What is your favourite condiment?"
+```
+
+## Publishing your model (optional – early alpha)
+
+Publishing models is in early alpha. If you'd like to publish your model to share with others, follow these steps:
+
+1. Create [an account](https://ollama.com/signup)
+2. Copy your Ollama public key:
+  - macOS: `cat ~/.ollama/id_ed25519.pub`
+  - Windows: `type %USERPROFILE%\.ollama\id_ed25519.pub`
+  - Linux: `cat /usr/share/ollama/.ollama/id_ed25519.pub`
+3. Add your public key to your [Ollama account](https://ollama.com/settings/keys)
+
+Next, copy your model to your username's namespace:
+
+```
+ollama cp example <your username>/example
+```
+
+Then push the model:
+
+```
+ollama push <your username>/example
+```
+
+After publishing, your model will be available at `https://ollama.com/<your username>/example`.
+
+## Quantization reference
+
+The quantization options are as follow (from highest highest to lowest levels of quantization). Note: some architectures such as Falcon do not support K quants.
+
+- `q2_K`
+- `q3_K`
+- `q3_K_S`
+- `q3_K_M`
+- `q3_K_L`
+- `q4_0` (recommended)
+- `q4_1`
+- `q4_K`
+- `q4_K_S`
+- `q4_K_M`
+- `q5_0`
+- `q5_1`
+- `q5_K`
+- `q5_K_S`
+- `q5_K_M`
+- `q6_K`
+- `q8_0`
+- `f16`

docs/linux.md

@@ -0,0 +1,133 @@
+# Ollama on Linux
+
+## Install
+
+Install Ollama running this one-liner:
+
+>
+
+```bash
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+## AMD Radeon GPU support
+
+While AMD has contributed the `amdgpu` driver upstream to the official linux
+kernel source, the version is older and may not support all ROCm features. We
+recommend you install the latest driver from
+https://www.amd.com/en/support/linux-drivers for best support of your Radeon
+GPU.
+
+## Manual install
+
+### Download the `ollama` binary
+
+Ollama is distributed as a self-contained binary. Download it to a directory in your PATH:
+
+```bash
+sudo curl -L https://ollama.com/download/ollama-linux-amd64 -o /usr/bin/ollama
+sudo chmod +x /usr/bin/ollama
+```
+
+### Adding Ollama as a startup service (recommended)
+
+Create a user for Ollama:
+
+```bash
+sudo useradd -r -s /bin/false -m -d /usr/share/ollama ollama
+```
+
+Create a service file in `/etc/systemd/system/ollama.service`:
+
+```ini
+[Unit]
+Description=Ollama Service
+After=network-online.target
+
+[Service]
+ExecStart=/usr/bin/ollama serve
+User=ollama
+Group=ollama
+Restart=always
+RestartSec=3
+
+[Install]
+WantedBy=default.target
+```
+
+Then start the service:
+
+```bash
+sudo systemctl daemon-reload
+sudo systemctl enable ollama
+```
+
+### Install CUDA drivers (optional – for Nvidia GPUs)
+
+[Download and install](https://developer.nvidia.com/cuda-downloads) CUDA.
+
+Verify that the drivers are installed by running the following command, which should print details about your GPU:
+
+```bash
+nvidia-smi
+```
+
+### Install ROCm (optional - for Radeon GPUs)
+[Download and Install](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html)
+
+Make sure to install ROCm v6
+
+### Start Ollama
+
+Start Ollama using `systemd`:
+
+```bash
+sudo systemctl start ollama
+```
+
+## Update
+
+Update ollama by running the install script again:
+
+```bash
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+Or by downloading the ollama binary:
+
+```bash
+sudo curl -L https://ollama.com/download/ollama-linux-amd64 -o /usr/bin/ollama
+sudo chmod +x /usr/bin/ollama
+```
+
+## Viewing logs
+
+To view logs of Ollama running as a startup service, run:
+
+```bash
+journalctl -u ollama
+```
+
+## Uninstall
+
+Remove the ollama service:
+
+```bash
+sudo systemctl stop ollama
+sudo systemctl disable ollama
+sudo rm /etc/systemd/system/ollama.service
+```
+
+Remove the ollama binary from your bin directory (either `/usr/local/bin`, `/usr/bin`, or `/bin`):
+
+```bash
+sudo rm $(which ollama)
+```
+
+Remove the downloaded models and Ollama service user and group:
+
+```bash
+sudo rm -r /usr/share/ollama
+sudo userdel ollama
+sudo groupdel ollama
+```

docs/modelfile.md

@@ -1,105 +1,236 @@
 # Ollama Model File
 
-> Note: this model file syntax is in development
+> Note: `Modelfile` syntax is in development
 
 A model file is the blueprint to create and share models with Ollama.
 
+## Table of Contents
+
+- [Format](#format)
+- [Examples](#examples)
+- [Instructions](#instructions)
+  - [FROM (Required)](#from-required)
+    - [Build from llama2](#build-from-llama2)
+    - [Build from a bin file](#build-from-a-bin-file)
+  - [PARAMETER](#parameter)
+    - [Valid Parameters and Values](#valid-parameters-and-values)
+  - [TEMPLATE](#template)
+    - [Template Variables](#template-variables)
+  - [SYSTEM](#system)
+  - [ADAPTER](#adapter)
+  - [LICENSE](#license)
+  - [MESSAGE](#message)
+- [Notes](#notes)
+
 ## Format
 
-The format of the Modelfile:
+The format of the `Modelfile`:
 
 ```modelfile
 # comment
 INSTRUCTION arguments
 ```
 
-| Instruction       | Description                                           |
-| ----------------- | ----------------------------------------------------- |
-| `FROM` (required) | Defines the base model to use                         |
-| `PARAMETER`       | Sets the parameters for how Ollama will run the model |
-| `SYSTEM`          | Specifies the system prompt that will set the context |
-| `TEMPLATE`        | The full prompt template to be sent to the model      |
-| `LICENSE`         | Specifies the legal license                           |
+| Instruction                         | Description                                                    |
+| ----------------------------------- | -------------------------------------------------------------- |
+| [`FROM`](#from-required) (required) | Defines the base model to use.                                 |
+| [`PARAMETER`](#parameter)           | Sets the parameters for how Ollama will run the model.         |
+| [`TEMPLATE`](#template)             | The full prompt template to be sent to the model.              |
+| [`SYSTEM`](#system)                 | Specifies the system message that will be set in the template. |
+| [`ADAPTER`](#adapter)               | Defines the (Q)LoRA adapters to apply to the model.            |
+| [`LICENSE`](#license)               | Specifies the legal license.                                   |
+| [`MESSAGE`](#message)               | Specify message history.                                       |
 
 ## Examples
 
-An example of a model file creating a mario blueprint:
+### Basic `Modelfile`
 
-```
+An example of a `Modelfile` creating a mario blueprint:
+
+```modelfile
 FROM llama2
 # sets the temperature to 1 [higher is more creative, lower is more coherent]
-# sets the context size to 4096
 PARAMETER temperature 1
+# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token
 PARAMETER num_ctx 4096
 
-# Overriding the system prompt
+# sets a custom system message to specify the behavior of the chat assistant
 SYSTEM You are Mario from super mario bros, acting as an assistant.
 ```
 
 To use this:
 
-1. Save it as a file (eg. `Modelfile`)
-2. `ollama create NAME -f <location of the file eg. ./Modelfile>'`
-3. `ollama run NAME`
+1. Save it as a file (e.g. `Modelfile`)
+2. `ollama create choose-a-model-name -f <location of the file e.g. ./Modelfile>'`
+3. `ollama run choose-a-model-name`
 4. Start using the model!
 
-## FROM (Required)
+More examples are available in the [examples directory](../examples).
 
-The FROM instruction defines the base model to use when creating a model.
+### `Modelfile`s in [ollama.com/library][1]
 
-```
+There are two ways to view `Modelfile`s underlying the models in [ollama.com/library][1]:
+
+- Option 1: view a details page from a model's tags page:
+  1.  Go to a particular model's tags (e.g. https://ollama.com/library/llama2/tags)
+  2.  Click on a tag (e.g. https://ollama.com/library/llama2:13b)
+  3.  Scroll down to "Layers"
+      - Note: if the [`FROM` instruction](#from-required) is not present,
+        it means the model was created from a local file
+- Option 2: use `ollama show` to print the `Modelfile` for any local models like so:
+
+  ```bash
+  > ollama show --modelfile llama2:13b
+  # Modelfile generated by "ollama show"
+  # To build a new Modelfile based on this one, replace the FROM line with:
+  # FROM llama2:13b
+
+  FROM /root/.ollama/models/blobs/sha256:123abc
+  TEMPLATE """[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>>
+
+  {{ end }}{{ .Prompt }} [/INST] """
+  SYSTEM """"""
+  PARAMETER stop [INST]
+  PARAMETER stop [/INST]
+  PARAMETER stop <<SYS>>
+  PARAMETER stop <</SYS>>
+  ```
+
+## Instructions
+
+### FROM (Required)
+
+The `FROM` instruction defines the base model to use when creating a model.
+
+```modelfile
 FROM <model name>:<tag>
 ```
 
-### Build from llama2
+#### Build from llama2
 
-```
+```modelfile
 FROM llama2
 ```
 
 A list of available base models:
 <https://github.com/jmorganca/ollama#model-library>
 
-### Build from a bin file
+#### Build from a `bin` file
 
-```
+```modelfile
 FROM ./ollama-model.bin
 ```
 
-## PARAMETER (Optional)
+This bin file location should be specified as an absolute path or relative to the `Modelfile` location.
+
+### PARAMETER
 
 The `PARAMETER` instruction defines a parameter that can be set when the model is run.
 
-```
+```modelfile
 PARAMETER <parameter> <parametervalue>
 ```
 
-### Valid Parameters and Values
+#### Valid Parameters and Values
 
-| Parameter      | Description                                                                                                                                                                                                                                             | Value Type | Example Usage      |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | ------------------ |
-| num_ctx        | Sets the size of the prompt context size length model. (Default: 2048)                                                                                                                                                                                  | int        | num_ctx 4096       |
-| temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)                                                                                                                                     | float      | temperature 0.7    |
-| top_k          | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)                                                                        | int        | top_k 40           |
-| top_p          | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)                                                                 | float      | top_p 0.9          |
-| num_gpu        | The number of GPUs to use. On macOS it defaults to 1 to enable metal support, 0 to disable.                                                                                                                                                             | int        | num_gpu 1          |
-| repeat_last_n  | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = ctx-size)                                                                                                                                          | int        | repeat_last_n 64   |
-| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)                                                                     | float      | repeat_penalty 1.1 |
-| tfs_z          | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)                                               | float      | tfs_z 1            |
-| mirostat       | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)                                                                                                                                         | int        | mirostat 0         |
-| mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)                                                                                                         | float      | mirostat_tau 5.0   |
-| mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)                        | float      | mirostat_eta 0.1   |
-| num_thread     | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int        | num_thread 8       |
+| Parameter      | Description                                                                                                                                                                                                                                             | Value Type | Example Usage        |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- |
+| mirostat       | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)                                                                                                                                         | int        | mirostat 0           |
+| mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)                        | float      | mirostat_eta 0.1     |
+| mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)                                                                                                         | float      | mirostat_tau 5.0     |
+| num_ctx        | Sets the size of the context window used to generate the next token. (Default: 2048)                                                                                                                                                                    | int        | num_ctx 4096         |
+| num_gqa        | The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b                                                                                                                                         | int        | num_gqa 1            |
+| num_gpu        | The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable.                                                                                                                                            | int        | num_gpu 50           |
+| num_thread     | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int        | num_thread 8         |
+| repeat_last_n  | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)                                                                                                                                           | int        | repeat_last_n 64     |
+| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)                                                                     | float      | repeat_penalty 1.1   |
+| temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)                                                                                                                                     | float      | temperature 0.7      |
+| seed           | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)                                                                                       | int        | seed 42              |
+| stop           | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile.                                      | string     | stop "AI assistant:" |
+| tfs_z          | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)                                               | float      | tfs_z 1              |
+| num_predict    | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)                                                                                                                                   | int        | num_predict 42       |
+| top_k          | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)                                                                        | int        | top_k 40             |
+| top_p          | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)                                                                 | float      | top_p 0.9            |
 
-## Prompt
+### TEMPLATE
 
-When building on top of the base models supplied by Ollama, it comes with the prompt template predefined. To override the supplied system prompt, simply add `SYSTEM insert system prompt` to change the system prompt.
+`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system message, a user's message and the response from the model. Note: syntax may be model specific. Templates use Go [template syntax](https://pkg.go.dev/text/template).
 
-### Prompt Template
+#### Template Variables
+
+| Variable          | Description                                                                                   |
+| ----------------- | --------------------------------------------------------------------------------------------- |
+| `{{ .System }}`   | The system message used to specify custom behavior.                                           |
+| `{{ .Prompt }}`   | The user prompt message.                                                                      |
+| `{{ .Response }}` | The response from the model. When generating a response, text after this variable is omitted. |
+
+```
+TEMPLATE """{{ if .System }}<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}{{ if .Prompt }}<|im_start|>user
+{{ .Prompt }}<|im_end|>
+{{ end }}<|im_start|>assistant
+"""
+```
+
+### SYSTEM
+
+The `SYSTEM` instruction specifies the system message to be used in the template, if applicable.
+
+```modelfile
+SYSTEM """<system message>"""
+```
+
+### ADAPTER
+
+The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be tuned from the base model otherwise the behaviour is undefined.
+
+```modelfile
+ADAPTER ./ollama-lora.bin
+```
+
+### LICENSE
+
+The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is shared or distributed.
+
+```modelfile
+LICENSE """
+<license text>
+"""
+```
+
+### MESSAGE
+
+The `MESSAGE` instruction allows you to specify a message history for the model to use when responding. Use multiple iterations of the MESSAGE command to build up a conversation which will guide the model to answer in a similar way.
+
+```modelfile
+MESSAGE <role> <message>
+```
+
+#### Valid roles
+
+| Role      | Description                                                  |
+| --------- | ------------------------------------------------------------ |
+| system    | Alternate way of providing the SYSTEM message for the model. |
+| user      | An example message of what the user could have asked.        |
+| assistant | An example message of how the model should respond.          |
+
+
+#### Example conversation
+
+```modelfile
+MESSAGE user Is Toronto in Canada?
+MESSAGE assistant yes
+MESSAGE user Is Sacramento in Canada?
+MESSAGE assistant no
+MESSAGE user Is Ontario in Canada?
+MESSAGE assistant yes
+```
 
-`TEMPLATE` the full prompt template to be passed into the model. It may include (optionally) a system prompt, user prompt, and assistant prompt. This is used to create a full custom prompt, and syntax may be model specific.
 
 ## Notes
 
-- the **modelfile is not case sensitive**. In the examples, we use uppercase for instructions to make it easier to distinguish it from arguments.
-- Instructions can be in any order. In the examples, we start with FROM instruction to keep it easily readable.
+- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.
+- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.
+
+[1]: https://ollama.com/library

docs/openai.md

@@ -0,0 +1,141 @@
+# OpenAI compatibility
+
+> **Note:** OpenAI compatibility is experimental and is subject to major adjustments including breaking changes. For fully-featured access to the Ollama API, see the Ollama [Python library](https://github.com/ollama/ollama-python), [JavaScript library](https://github.com/ollama/ollama-js) and [REST API](https://github.com/jmorganca/ollama/blob/main/docs/api.md).
+
+Ollama provides experimental compatibility with parts of the [OpenAI API](https://platform.openai.com/docs/api-reference) to help connect existing applications to Ollama.
+
+## Usage
+
+### OpenAI Python library
+
+```python
+from openai import OpenAI
+
+client = OpenAI(
+    base_url='http://localhost:11434/v1/',
+
+    # required but ignored
+    api_key='ollama',
+)
+
+chat_completion = client.chat.completions.create(
+    messages=[
+        {
+            'role': 'user',
+            'content': 'Say this is a test',
+        }
+    ],
+    model='llama2',
+)
+```
+
+### OpenAI JavaScript library
+
+```javascript
+import OpenAI from 'openai'
+
+const openai = new OpenAI({
+  baseURL: 'http://localhost:11434/v1/',
+
+  // required but ignored
+  apiKey: 'ollama',
+})
+
+const chatCompletion = await openai.chat.completions.create({
+  messages: [{ role: 'user', content: 'Say this is a test' }],
+  model: 'llama2',
+})
+```
+
+### `curl`
+
+```
+curl http://localhost:11434/v1/chat/completions \
+    -H "Content-Type: application/json" \
+    -d '{
+        "model": "llama2",
+        "messages": [
+            {
+                "role": "system",
+                "content": "You are a helpful assistant."
+            },
+            {
+                "role": "user",
+                "content": "Hello!"
+            }
+        ]
+    }'
+```
+
+## Endpoints
+
+### `/v1/chat/completions`
+
+#### Supported features
+
+- [x] Chat completions
+- [x] Streaming
+- [x] JSON mode
+- [x] Reproducible outputs
+- [ ] Vision
+- [ ] Function calling
+- [ ] Logprobs
+
+#### Supported request fields
+
+- [x] `model`
+- [x] `messages`
+  - [x] Text `content`
+  - [ ] Array of `content` parts
+- [x] `frequency_penalty`
+- [x] `presence_penalty`
+- [x] `response_format`
+- [x] `seed`
+- [x] `stop`
+- [x] `stream`
+- [x] `temperature`
+- [x] `top_p`
+- [x] `max_tokens`
+- [ ] `logit_bias`
+- [ ] `tools`
+- [ ] `tool_choice`
+- [ ] `user`
+- [ ] `n`
+
+#### Notes
+
+- Setting `seed` will always set `temperature` to `0`
+- `finish_reason` will always be `stop`
+- `usage.prompt_tokens` will be 0 for completions where prompt evaluation is cached
+
+## Models
+
+Before using a model, pull it locally `ollama pull`:
+
+```shell
+ollama pull llama2
+```
+
+### Default model names
+
+For tooling that relies on default OpenAI model names such as `gpt-3.5-turbo`, use `ollama cp` to copy an existing model name to a temporary name:
+
+```
+ollama cp llama2 gpt-3.5-turbo
+```
+
+Afterwards, this new model name can be specified the `model` field:
+
+```shell
+curl http://localhost:11434/v1/chat/completions \
+    -H "Content-Type: application/json" \
+    -d '{
+        "model": "gpt-3.5-turbo",
+        "messages": [
+            {
+                "role": "user",
+                "content": "Hello!"
+            }
+        ]
+    }'
+```

docs/troubleshooting.md

@@ -0,0 +1,111 @@
+# How to troubleshoot issues
+
+Sometimes Ollama may not perform as expected. One of the best ways to figure out what happened is to take a look at the logs. Find the logs on **Mac** by running the command:
+
+```shell
+cat ~/.ollama/logs/server.log
+```
+
+On **Linux** systems with systemd, the logs can be found with this command:
+
+```shell
+journalctl -u ollama
+```
+
+When you run Ollama in a **container**, the logs go to stdout/stderr in the container:
+
+```shell
+docker logs <container-name>
+```
+(Use `docker ps` to find the container name)
+
+If manually running `ollama serve` in a terminal, the logs will be on that terminal.
+
+When you run Ollama on **Windows**, there are a few different locations.  You can view them in the explorer window by hitting `<cmd>+R` and type in:
+- `explorer %LOCALAPPDATA%\Ollama` to view logs
+- `explorer %LOCALAPPDATA%\Programs\Ollama` to browse the binaries (The installer adds this to your user PATH)
+- `explorer %HOMEPATH%\.ollama` to browse where models and configuration is stored
+- `explorer %TEMP%` where temporary executable files are stored in one or more `ollama*` directories
+
+To enable additional debug logging to help troubleshoot problems, first **Quit the running app from the tray menu** then in a powershell terminal
+```powershell
+$env:OLLAMA_DEBUG="1"
+& "ollama app.exe"
+```
+
+Join the [Discord](https://discord.gg/ollama) for help interpreting the logs.
+
+## LLM libraries
+
+Ollama includes multiple LLM libraries compiled for different GPUs and CPU
+vector features.  Ollama tries to pick the best one based on the capabilities of
+your system.  If this autodetection has problems, or you run into other problems
+(e.g. crashes in your GPU) you can workaround this by forcing a specific LLM
+library.  `cpu_avx2` will perform the best, followed by `cpu_avx` an the slowest
+but most compatible is `cpu`.  Rosetta emulation under MacOS will work with the
+`cpu` library. 
+
+In the server log, you will see a message that looks something like this (varies
+from release to release):
+
+```
+Dynamic LLM libraries [rocm_v6 cpu cpu_avx cpu_avx2 cuda_v11 rocm_v5]
+```
+
+**Experimental LLM Library Override**
+
+You can set OLLAMA_LLM_LIBRARY to any of the available LLM libraries to bypass
+autodetection, so for example, if you have a CUDA card, but want to force the
+CPU LLM library with AVX2 vector support, use:
+
+```
+OLLAMA_LLM_LIBRARY="cpu_avx2" ollama serve
+```
+
+You can see what features your CPU has with the following.  
+```
+cat /proc/cpuinfo| grep flags  | head -1
+```
+
+## AMD Radeon GPU Support
+
+Ollama leverages the AMD ROCm library, which does not support all AMD GPUs. In
+some cases you can force the system to try to use a similar LLVM target that is
+close.  For example The Radeon RX 5400 is `gfx1034` (also known as 10.3.4)
+however, ROCm does not currently support this target. The closest support is
+`gfx1030`.  You can use the environment variable `HSA_OVERRIDE_GFX_VERSION` with
+`x.y.z` syntax.  So for example, to force the system to run on the RX 5400, you
+would set `HSA_OVERRIDE_GFX_VERSION="10.3.0"` as an environment variable for the
+server.  If you have an unsupported AMD GPU you can experiment using the list of
+supported types below.
+
+At this time, the known supported GPU types are the following LLVM Targets.
+This table shows some example GPUs that map to these LLVM targets:
+| **LLVM Target** | **An Example GPU** |
+|-----------------|---------------------|
+| gfx900 | Radeon RX Vega 56 |
+| gfx906 | Radeon Instinct MI50 |
+| gfx908 | Radeon Instinct MI100 |
+| gfx90a | Radeon Instinct MI210 |
+| gfx940 | Radeon Instinct MI300 |
+| gfx941 | |
+| gfx942 | |
+| gfx1030 | Radeon PRO V620 |
+| gfx1100 | Radeon PRO W7900 |
+| gfx1101 | Radeon PRO W7700 |
+| gfx1102 | Radeon RX 7600 |
+
+AMD is working on enhancing ROCm v6 to broaden support for families of GPUs in a
+future release which should increase support for more GPUs.
+
+Reach out on [Discord](https://discord.gg/ollama) or file an
+[issue](https://github.com/ollama/ollama/issues) for additional help.
+
+## Installing older versions on Linux
+
+If you run into problems on Linux and want to install an older version you can tell the install script
+which version to install.
+
+```sh
+curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.27" sh
+```

docs/tutorials.md

@@ -0,0 +1,9 @@
+# Tutorials
+
+Here is a list of ways you can use Ollama with other tools to build interesting applications.
+
+- [Using LangChain with Ollama in JavaScript](./tutorials/langchainjs.md)
+- [Using LangChain with Ollama in Python](./tutorials/langchainpy.md)
+- [Running Ollama on NVIDIA Jetson Devices](./tutorials/nvidia-jetson.md)
+
+Also be sure to check out the [examples](../examples) directory for more ways to use Ollama.

docs/tutorials/fly-gpu.md

@@ -0,0 +1,83 @@
+# Running Ollama on Fly.io GPU Instances
+
+Ollama runs with little to no configuration on [Fly.io GPU instances](https://fly.io/docs/gpus/gpu-quickstart/). If you don't have access to GPUs yet, you'll need to [apply for access](https://fly.io/gpu/) on the waitlist. Once you're accepted, you'll get an email with instructions on how to get started.
+
+Create a new app with `fly apps create`:
+
+```bash
+fly apps create
+```
+
+Then create a `fly.toml` file in a new folder that looks like this:
+
+```toml
+app = "sparkling-violet-709"
+primary_region = "ord"
+vm.size = "a100-40gb" # see https://fly.io/docs/gpus/gpu-quickstart/ for more info
+
+[build]
+  image = "ollama/ollama"
+
+[http_service]
+  internal_port = 11434
+  force_https = false
+  auto_stop_machines = true
+  auto_start_machines = true
+  min_machines_running = 0
+  processes = ["app"]
+
+[mounts]
+  source = "models"
+  destination = "/root/.ollama"
+  initial_size = "100gb"
+```
+
+Then create a [new private IPv6 address](https://fly.io/docs/reference/private-networking/#flycast-private-load-balancing) for your app:
+
+```bash
+fly ips allocate-v6 --private
+```
+
+Then deploy your app:
+
+```bash
+fly deploy
+```
+
+And finally you can access it interactively with a new Fly.io Machine:
+
+```
+fly machine run -e OLLAMA_HOST=http://your-app-name.flycast --shell ollama/ollama
+```
+
+```bash
+$ ollama run openchat:7b-v3.5-fp16
+>>> How do I bake chocolate chip cookies?
+ To bake chocolate chip cookies, follow these steps:
+
+1. Preheat the oven to 375°F (190°C) and line a baking sheet with parchment paper or silicone baking mat.
+
+2. In a large bowl, mix together 1 cup of unsalted butter (softened), 3/4 cup granulated sugar, and 3/4
+cup packed brown sugar until light and fluffy.
+
+3. Add 2 large eggs, one at a time, to the butter mixture, beating well after each addition. Stir in 1
+teaspoon of pure vanilla extract.
+
+4. In a separate bowl, whisk together 2 cups all-purpose flour, 1/2 teaspoon baking soda, and 1/2 teaspoon
+salt. Gradually add the dry ingredients to the wet ingredients, stirring until just combined.
+
+5. Fold in 2 cups of chocolate chips (or chunks) into the dough.
+
+6. Drop rounded tablespoons of dough onto the prepared baking sheet, spacing them about 2 inches apart.
+
+7. Bake for 10-12 minutes, or until the edges are golden brown. The centers should still be slightly soft.
+
+8. Allow the cookies to cool on the baking sheet for a few minutes before transferring them to a wire rack
+to cool completely.
+
+Enjoy your homemade chocolate chip cookies!
+```
+
+When you set it up like this, it will automatically turn off when you're done using it. Then when you access it again, it will automatically turn back on. This is a great way to save money on GPU instances when you're not using them. If you want a persistent wake-on-use connection to your Ollama instance, you can set up a [connection to your Fly network using WireGuard](https://fly.io/docs/reference/private-networking/#discovering-apps-through-dns-on-a-wireguard-connection). Then you can access your Ollama instance at `http://your-app-name.flycast`.
+
+And that's it!

docs/tutorials/langchainjs.md

@@ -0,0 +1,77 @@
+# Using LangChain with Ollama using JavaScript
+
+In this tutorial, we are going to use JavaScript with LangChain and Ollama to learn about something just a touch more recent. In August 2023, there was a series of wildfires on Maui. There is no way an LLM trained before that time can know about this, since their training data would not include anything as recent as that. So we can find the [Wikipedia article about the fires](https://en.wikipedia.org/wiki/2023_Hawaii_wildfires) and ask questions about the contents.
+
+To get started, let's just use **LangChain** to ask a simple question to a model. To do this with JavaScript, we need to install **LangChain**:
+
+```bash
+npm install langchain
+```
+
+Now we can start building out our JavaScript:
+
+```javascript
+import { Ollama } from "langchain/llms/ollama";
+
+const ollama = new Ollama({
+  baseUrl: "http://localhost:11434",
+  model: "llama2",
+});
+
+const answer = await ollama.call(`why is the sky blue?`);
+
+console.log(answer);
+```
+
+That will get us the same thing as if we ran `ollama run llama2 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app.
+
+```bash
+npm install cheerio 
+```
+
+```javascript
+import { CheerioWebBaseLoader } from "langchain/document_loaders/web/cheerio";
+
+const loader = new CheerioWebBaseLoader("https://en.wikipedia.org/wiki/2023_Hawaii_wildfires");
+const data = await loader.load();
+```
+
+That will load the document. Although this page is smaller than the Odyssey, it is certainly bigger than the context size for most LLMs. So we are going to need to split into smaller pieces, and then select just the pieces relevant to our question. This is a great use for a vector datastore. In this example, we will use the **MemoryVectorStore** that is part of **LangChain**. But there is one more thing we need to get the content into the datastore. We have to run an embeddings process that converts the tokens in the text into a series of vectors. And for that, we are going to use **Tensorflow**. There is a lot of stuff going on in this one. First, install the **Tensorflow** components that we need.
+
+```javascript
+npm install @tensorflow/tfjs-core@3.6.0 @tensorflow/tfjs-converter@3.6.0 @tensorflow-models/universal-sentence-encoder@1.3.3 @tensorflow/tfjs-node@4.10.0
+```
+
+If you just install those components without the version numbers, it will install the latest versions, but there are conflicts within **Tensorflow**, so you need to install the compatible versions.
+
+```javascript
+import { RecursiveCharacterTextSplitter } from "langchain/text_splitter"
+import { MemoryVectorStore } from "langchain/vectorstores/memory";
+import "@tensorflow/tfjs-node";
+import { TensorFlowEmbeddings } from "langchain/embeddings/tensorflow";
+
+// Split the text into 500 character chunks. And overlap each chunk by 20 characters
+const textSplitter = new RecursiveCharacterTextSplitter({
+ chunkSize: 500,
+ chunkOverlap: 20
+});
+const splitDocs = await textSplitter.splitDocuments(data);
+
+// Then use the TensorFlow Embedding to store these chunks in the datastore
+const vectorStore = await MemoryVectorStore.fromDocuments(splitDocs, new TensorFlowEmbeddings());
+```
+
+To connect the datastore to a question asked to a LLM, we need to use the concept at the heart of **LangChain**: the chain. Chains are a way to connect a number of activities together to accomplish a particular tasks. There are a number of chain types available, but for this tutorial we are using the **RetrievalQAChain**.
+
+```javascript
+import { RetrievalQAChain } from "langchain/chains";
+
+const retriever = vectorStore.asRetriever();
+const chain = RetrievalQAChain.fromLLM(ollama, retriever);
+const result = await chain.call({query: "When was Hawaii's request for a major disaster declaration approved?"});
+console.log(result.text)
+```
+
+So we created a retriever, which is a way to return the chunks that match a query from a datastore. And then connect the retriever and the model via a chain. Finally, we send a query to the chain, which results in an answer using our document as a source. The answer it returned was correct, August 10, 2023.
+
+And that is a simple introduction to what you can do with **LangChain** and **Ollama.**

docs/tutorials/langchainpy.md

@@ -0,0 +1,82 @@
+# Using LangChain with Ollama in Python
+
+Let's imagine we are studying the classics, such as **the Odyssey** by **Homer**. We might have a question about Neleus and his family. If you ask llama2 for that info, you may get something like:
+
+> I apologize, but I'm a large language model, I cannot provide information on individuals or families that do not exist in reality. Neleus is not a real person or character, and therefore does not have a family or any other personal details. My apologies for any confusion. Is there anything else I can help you with?
+
+This sounds like a typical censored response, but even llama2-uncensored gives a mediocre answer:
+
+> Neleus was a legendary king of Pylos and the father of Nestor, one of the Argonauts. His mother was Clymene, a sea nymph, while his father was Neptune, the god of the sea.
+
+So let's figure out how we can use **LangChain** with Ollama to ask our question to the actual document, the Odyssey by Homer, using Python.
+
+Let's start by asking a simple question that we can get an answer to from the **Llama2** model using **Ollama**. First, we need to install the **LangChain** package:
+
+`pip install langchain`
+
+Then we can create a model and ask the question:
+
+```python
+from langchain.llms import Ollama
+ollama = Ollama(base_url='http://localhost:11434',
+model="llama2")
+print(ollama("why is the sky blue"))
+```
+
+Notice that we are defining the model and the base URL for Ollama.
+
+Now let's load a document to ask questions against. I'll load up the Odyssey by Homer, which you can find at Project Gutenberg. We will need **WebBaseLoader** which is part of **LangChain** and loads text from any webpage. On my machine, I also needed to install **bs4** to get that to work, so run `pip install bs4`.
+
+```python
+from langchain.document_loaders import WebBaseLoader
+loader = WebBaseLoader("https://www.gutenberg.org/files/1727/1727-h/1727-h.htm")
+data = loader.load()
+```
+
+This file is pretty big. Just the preface is 3000 tokens. Which means the full document won't fit into the context for the model. So we need to split it up into smaller pieces.
+
+```python
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+
+text_splitter=RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=0)
+all_splits = text_splitter.split_documents(data)
+```
+
+It's split up, but we have to find the relevant splits and then submit those to the model. We can do this by creating embeddings and storing them in a vector database. We can use Ollama directly to instantiate an embedding model. We will use ChromaDB in this example for a vector database. `pip install chromadb`
+
+```python
+from langchain.embeddings import OllamaEmbeddings
+from langchain.vectorstores import Chroma
+oembed = OllamaEmbeddings(base_url="http://localhost:11434", model="nomic-embed-text")
+vectorstore = Chroma.from_documents(documents=all_splits, embedding=oembed)
+```
+
+Now let's ask a question from the document. **Who was Neleus, and who is in his family?** Neleus is a character in the Odyssey, and the answer can be found in our text.
+
+```python
+question="Who is Neleus and who is in Neleus' family?"
+docs = vectorstore.similarity_search(question)
+len(docs)
+```
+
+This will output the number of matches for chunks of data similar to the search.
+
+The next thing is to send the question and the relevant parts of the docs to the model to see if we can get a good answer. But we are stitching two parts of the process together, and that is called a chain. This means we need to define a chain:
+
+```python
+from langchain.chains import RetrievalQA
+qachain=RetrievalQA.from_chain_type(ollama, retriever=vectorstore.as_retriever())
+qachain.invoke({"query": question})
+```
+
+The answer received from this chain was:
+
+> Neleus is a character in Homer's "Odyssey" and is mentioned in the context of Penelope's suitors. Neleus is the father of Chloris, who is married to Neleus and bears him several children, including Nestor, Chromius, Periclymenus, and Pero. Amphinomus, the son of Nisus, is also mentioned as a suitor of Penelope and is known for his good natural disposition and agreeable conversation.
+
+It's not a perfect answer, as it implies Neleus married his daughter when actually Chloris "was the youngest daughter to Amphion son of Iasus and king of Minyan Orchomenus, and was Queen in Pylos".
+
+I updated the chunk_overlap for the text splitter to 20 and tried again and got a much better answer:
+
+> Neleus is a character in Homer's epic poem "The Odyssey." He is the husband of Chloris, who is the youngest daughter of Amphion son of Iasus and king of Minyan Orchomenus. Neleus has several children with Chloris, including Nestor, Chromius, Periclymenus, and Pero.
+
+And that is a much better answer.

docs/tutorials/nvidia-jetson.md

@@ -0,0 +1,38 @@
+# Running Ollama on NVIDIA Jetson Devices
+
+With some minor configuration, Ollama runs well on [NVIDIA Jetson Devices](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/). The following has been tested on [JetPack 5.1.2](https://developer.nvidia.com/embedded/jetpack).
+
+NVIDIA Jetson devices are Linux-based embedded AI computers that are purpose-built for AI applications.
+
+Jetsons have an integrated GPU that is wired directly to the memory controller of the machine. For this reason, the `nvidia-smi` command is unrecognized, and Ollama proceeds to operate in "CPU only"
+mode. This can be verified by using a monitoring tool like jtop.
+
+In order to address this, we simply pass the path to the Jetson's pre-installed CUDA libraries into `ollama serve` (while in a tmux session). We then hardcode the num_gpu parameters into a cloned
+version of our target model.
+
+Prerequisites:
+
+- curl
+- tmux
+
+Here are the steps:
+
+- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.com/install.sh | sh`
+- Stop the Ollama service: `sudo systemctl stop ollama`
+- Start Ollama serve in a tmux session called ollama_jetson and reference the CUDA libraries path: `tmux has-session -t ollama_jetson 2>/dev/null || tmux new-session -d -s ollama_jetson 
+'LD_LIBRARY_PATH=/usr/local/cuda/lib64 ollama serve'`
+- Pull the model you want to use (e.g. mistral): `ollama pull mistral`
+- Create a new Modelfile specifically for enabling GPU support on the Jetson: `touch ModelfileMistralJetson`
+- In the ModelfileMistralJetson file, specify the FROM model and the num_gpu PARAMETER as shown below:
+
+```
+FROM mistral
+PARAMETER num_gpu 999
+```
+
+- Create a new model from your Modelfile: `ollama create mistral-jetson -f ./ModelfileMistralJetson`
+- Run the new model: `ollama run mistral-jetson`
+
+If you run a monitoring tool like jtop you should now see that Ollama is using the Jetson's integrated GPU.
+
+And that's it!

docs/windows.md

@@ -0,0 +1,47 @@
+# Ollama Windows Preview
+
+Welcome to the Ollama Windows preview.
+
+No more WSL required!
+
+Ollama now runs as a native Windows application, including NVIDIA and AMD Radeon GPU support.
+After installing Ollama Windows Preview, Ollama will run in the background and
+the `ollama` command line is available in `cmd`, `powershell` or your favorite
+terminal application. As usual the Ollama [api](./api.md) will be served on
+`http://localhost:11434`.
+
+As this is a preview release, you should expect a few bugs here and there.  If
+you run into a problem you can reach out on
+[Discord](https://discord.gg/ollama), or file an 
+[issue](https://github.com/ollama/ollama/issues).
+Logs will often be helpful in dianosing the problem (see
+[Troubleshooting](#troubleshooting) below)
+
+## System Requirements
+
+* Windows 10 or newer, Home or Pro
+* NVIDIA 452.39 or newer Drivers if you have an NVIDIA card
+* AMD Radeon Driver https://www.amd.com/en/support if you have a Radeon card
+
+## API Access
+
+Here's a quick example showing API access from `powershell`
+```powershell
+(Invoke-WebRequest -method POST -Body '{"model":"llama2", "prompt":"Why is the sky blue?", "stream": false}' -uri http://localhost:11434/api/generate ).Content | ConvertFrom-json
+```
+
+## Troubleshooting
+
+While we're in preview, `OLLAMA_DEBUG` is always enabled, which adds
+a "view logs" menu item to the app, and increses logging for the GUI app and
+server.
+
+Ollama on Windows stores files in a few different locations.  You can view them in
+the explorer window by hitting `<cmd>+R` and type in:
+- `explorer %LOCALAPPDATA%\Ollama` contains logs, and downloaded updates
+    - *app.log* contains logs from the GUI application
+    - *server.log* contains the server logs
+    - *upgrade.log* contains log output for upgrades
+- `explorer %LOCALAPPDATA%\Programs\Ollama` contains the binaries (The installer adds this to your user PATH)
+- `explorer %HOMEPATH%\.ollama` contains models and configuration
+- `explorer %TEMP%` contains temporary executable files in one or more `ollama*` directories

examples/.gitignore

@@ -0,0 +1,174 @@
+node_modules
+bun.lockb
+.vscode
+# OSX
+.DS_STORE
+
+
+# Models
+models/
+
+# Local Chroma db
+.chroma/
+db/
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

examples/README.md

@@ -1,15 +1,3 @@
 # Examples
 
-This directory contains examples that can be created and run with `ollama`.
-
-To create a model:
-
-```
-ollama create example -f <example file>
-```
-
-To run a model:
-
-```
-ollama run example
-```
+This directory contains different examples of using Ollama.

examples/bash-comparemodels/README.md

@@ -0,0 +1,10 @@
+# Bash Shell examples
+
+When calling `ollama`, you can pass it a file to run all the prompts in the file, one after the other:
+
+`ollama run llama2 < sourcequestions.txt`
+
+This concept is used in the following example.
+
+## Compare Models
+`comparemodels.sh` is a script that runs all the questions in `sourcequestions.txt` using any 4 models you choose that you have already pulled from the Ollama library or have created locally.

examples/bash-comparemodels/comparemodels.sh

@@ -0,0 +1,64 @@
+#! /usr/bin/env bash
+# Compare multiple models by running them with the same questions
+
+NUMBEROFCHOICES=4
+SELECTIONS=()
+declare -a SUMS=()
+
+# Get the list of models
+CHOICES=$(ollama list | awk '{print $1}')
+
+# Select which models to run as a comparison
+echo "Select $NUMBEROFCHOICES models to compare:"
+select ITEM in $CHOICES; do
+    if [[ -n $ITEM ]]; then
+        echo "You have selected $ITEM"
+        SELECTIONS+=("$ITEM")
+        ((COUNT++))
+        if [[ $COUNT -eq $NUMBEROFCHOICES ]]; then
+            break
+        fi
+    else
+        echo "Invalid selection"
+    fi
+done
+
+# Loop through each of the selected models
+for ITEM in "${SELECTIONS[@]}"; do
+    echo "--------------------------------------------------------------"
+    echo "Loading the model $ITEM into memory"
+    ollama run "$ITEM" ""
+    echo "--------------------------------------------------------------"
+    echo "Running the questions through the model $ITEM"
+    COMMAND_OUTPUT=$(ollama run "$ITEM" --verbose < sourcequestions.txt 2>&1| tee /dev/stderr)
+
+    # eval duration is sometimes listed in seconds and sometimes in milliseconds. 
+    # Add up the values for each model
+    SUM=$(echo "$COMMAND_OUTPUT" | awk '
+    /eval duration:/ {
+        value = $3
+        if (index(value, "ms") > 0) {
+            gsub("ms", "", value)
+            value /= 1000
+        } else {
+            gsub("s", "", value)
+        }
+        sum += value
+    }
+    END { print sum }')
+
+
+    SUMS+=("All questions for $ITEM completed in $SUM seconds")
+done
+
+echo ""
+echo "--------------------------------------------------------------"
+echo -e "Sums of eval durations for each run:"
+for val in "${SUMS[@]}"; do
+    echo "$val"
+done
+
+echo "--------------------------------------------------------------"
+echo "Comparison complete. Now you can decide"
+echo "which model is best."
+echo "--------------------------------------------------------------"

examples/bash-comparemodels/sourcequestions.txt

@@ -0,0 +1,7 @@
+Why is the sky blue
+What is a black hole
+Explain the big bang theory like I am 5?
+What is the quickest way to win a game of Monopoly with 3 others?
+Why does a vacuum bottle keep my coffee hot and my milkshake cold?
+What is the difference between a meteor, a meteorite, and a meteoroid?
+Create an array with 5 items and print to the console. Do this in Python, C#, Typescript, and Rust.

examples/golang-simplegenerate/main.go

@@ -0,0 +1,29 @@
+package main
+
+import (
+	"bytes"
+	"fmt"
+	"io"
+	"log"
+	"net/http"
+	"os"
+)
+
+func main() {
+	body := []byte(`{"model":"mistral"}`)
+	resp, err := http.Post("http://localhost:11434/api/generate", "application/json", bytes.NewBuffer(body))
+
+	if err != nil {
+		fmt.Print(err.Error())
+		os.Exit(1)
+	}
+
+	defer resp.Body.Close()
+	
+	responseData, err := io.ReadAll(resp.Body)
+	if err != nil {
+		log.Fatal(err)
+	}
+	fmt.Println(string(responseData))
+
+}

examples/jupyter-notebook/README.md

@@ -0,0 +1,5 @@
+# Ollama Jupyter Notebook
+
+This example downloads and installs Ollama in a Jupyter instance such as Google Colab. It will start the Ollama service and expose an endpoint using `ngrok` which can be used to communicate with the Ollama instance remotely.
+
+For best results, use an instance with GPU accelerator.

examples/jupyter-notebook/ollama.ipynb

@@ -0,0 +1,102 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "93f59dcb-c588-41b8-a792-55d88ade739c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Download and run the Ollama Linux install script\n",
+    "!curl -fsSL https://ollama.com/install.sh | sh\n",
+    "!command -v systemctl >/dev/null && sudo systemctl stop ollama"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "658c147e-c7f8-490e-910e-62b80f577dda",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install aiohttp pyngrok\n",
+    "\n",
+    "import os\n",
+    "import asyncio\n",
+    "from aiohttp import ClientSession\n",
+    "\n",
+    "# Set LD_LIBRARY_PATH so the system NVIDIA library becomes preferred\n",
+    "# over the built-in library. This is particularly important for \n",
+    "# Google Colab which installs older drivers\n",
+    "os.environ.update({'LD_LIBRARY_PATH': '/usr/lib64-nvidia'})\n",
+    "\n",
+    "async def run(cmd):\n",
+    "  '''\n",
+    "  run is a helper function to run subcommands asynchronously.\n",
+    "  '''\n",
+    "  print('>>> starting', *cmd)\n",
+    "  p = await asyncio.subprocess.create_subprocess_exec(\n",
+    "      *cmd,\n",
+    "      stdout=asyncio.subprocess.PIPE,\n",
+    "      stderr=asyncio.subprocess.PIPE,\n",
+    "  )\n",
+    "\n",
+    "  async def pipe(lines):\n",
+    "    async for line in lines:\n",
+    "      print(line.strip().decode('utf-8'))\n",
+    "\n",
+    "  await asyncio.gather(\n",
+    "      pipe(p.stdout),\n",
+    "      pipe(p.stderr),\n",
+    "  )\n",
+    "\n",
+    "\n",
+    "await asyncio.gather(\n",
+    "    run(['ollama', 'serve']),\n",
+    "    run(['ngrok', 'http', '--log', 'stderr', '11434']),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e7735a55-9aad-4caf-8683-52e2163ba53b",
+   "metadata": {},
+   "source": [
+    "The previous cell starts two processes, `ollama` and `ngrok`. The log output will show a line like the following which describes the external address.\n",
+    "\n",
+    "```\n",
+    "t=2023-11-12T22:55:56+0000 lvl=info msg=\"started tunnel\" obj=tunnels name=command_line addr=http://localhost:11434 url=https://8249-34-125-179-11.ngrok.io\n",
+    "```\n",
+    "\n",
+    "The external address in this case is `https://8249-34-125-179-11.ngrok.io` which can be passed into `OLLAMA_HOST` to access this instance.\n",
+    "\n",
+    "```bash\n",
+    "export OLLAMA_HOST=https://8249-34-125-179-11.ngrok.io\n",
+    "ollama list\n",
+    "ollama run mistral\n",
+    "```"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/kubernetes/README.md

@@ -0,0 +1,36 @@
+# Deploy Ollama to Kubernetes
+
+## Prerequisites
+
+- Ollama: https://ollama.com/download
+- Kubernetes cluster. This example will use Google Kubernetes Engine.
+
+## Steps
+
+1. Create the Ollama namespace, daemon set, and service
+
+   ```bash
+   kubectl apply -f cpu.yaml
+   ```
+
+1. Port forward the Ollama service to connect and use it locally
+
+   ```bash
+   kubectl -n ollama port-forward service/ollama 11434:80
+   ```
+
+1. Pull and run a model, for example `orca-mini:3b`
+
+   ```bash
+   ollama run orca-mini:3b
+   ```
+
+## (Optional) Hardware Acceleration
+
+Hardware acceleration in Kubernetes requires NVIDIA's [`k8s-device-plugin`](https://github.com/NVIDIA/k8s-device-plugin). Follow the link for more details.
+
+Once configured, create a GPU enabled Ollama deployment.
+
+```bash
+kubectl apply -f gpu.yaml
+```

examples/kubernetes/cpu.yaml

@@ -0,0 +1,42 @@
+---
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: ollama
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: ollama
+  namespace: ollama
+spec:
+  selector:
+    matchLabels:
+      name: ollama
+  template:
+    metadata:
+      labels:
+        name: ollama
+    spec:
+      containers:
+      - name: ollama
+        image: ollama/ollama:latest
+        ports:
+        - name: http
+          containerPort: 11434
+          protocol: TCP
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: ollama
+  namespace: ollama
+spec:
+  type: ClusterIP
+  selector:
+    name: ollama
+  ports:
+  - port: 80
+    name: http
+    targetPort: http
+    protocol: TCP

examples/kubernetes/gpu.yaml

@@ -0,0 +1,58 @@
+---
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: ollama
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: ollama
+  namespace: ollama
+spec:
+  strategy:
+    type: Recreate
+  selector:
+    matchLabels:
+      name: ollama
+  template:
+    metadata:
+      labels:
+        name: ollama
+    spec:
+      containers:
+      - name: ollama
+        image: ollama/ollama:latest
+        env:
+        - name: PATH
+          value: /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
+        - name: LD_LIBRARY_PATH
+          value: /usr/local/nvidia/lib:/usr/local/nvidia/lib64
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        ports:
+        - name: http
+          containerPort: 11434
+          protocol: TCP
+        resources:
+          limits:
+            nvidia.com/gpu: 1
+      tolerations:
+      - key: nvidia.com/gpu
+        operator: Exists
+        effect: NoSchedule
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: ollama
+  namespace: ollama
+spec:
+  type: ClusterIP
+  selector:
+    name: ollama
+  ports:
+  - port: 80
+    name: http
+    targetPort: http
+    protocol: TCP

examples/langchain-python-rag-document/README.md

@@ -0,0 +1,21 @@
+# LangChain Document QA
+
+This example provides an interface for asking questions to a PDF document.
+
+## Setup
+
+```
+pip install -r requirements.txt
+```
+
+## Run
+
+```
+python main.py
+```
+
+A prompt will appear, where questions may be asked:
+
+```
+Query: How many locations does WeWork have?
+```

examples/langchain-python-rag-document/main.py

@@ -0,0 +1,61 @@
+from langchain.document_loaders import OnlinePDFLoader
+from langchain.vectorstores import Chroma
+from langchain.embeddings import GPT4AllEmbeddings
+from langchain import PromptTemplate
+from langchain.llms import Ollama
+from langchain.callbacks.manager import CallbackManager
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+from langchain.chains import RetrievalQA
+import sys
+import os
+
+class SuppressStdout:
+    def __enter__(self):
+        self._original_stdout = sys.stdout
+        self._original_stderr = sys.stderr
+        sys.stdout = open(os.devnull, 'w')
+        sys.stderr = open(os.devnull, 'w')
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        sys.stdout.close()
+        sys.stdout = self._original_stdout
+        sys.stderr = self._original_stderr
+
+# load the pdf and split it into chunks
+loader = OnlinePDFLoader("https://d18rn0p25nwr6d.cloudfront.net/CIK-0001813756/975b3e9b-268e-4798-a9e4-2a9a7c92dc10.pdf")
+data = loader.load()
+
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=0)
+all_splits = text_splitter.split_documents(data)
+
+with SuppressStdout():
+    vectorstore = Chroma.from_documents(documents=all_splits, embedding=GPT4AllEmbeddings())
+
+while True:
+    query = input("\nQuery: ")
+    if query == "exit":
+        break
+    if query.strip() == "":
+        continue
+
+    # Prompt
+    template = """Use the following pieces of context to answer the question at the end. 
+    If you don't know the answer, just say that you don't know, don't try to make up an answer. 
+    Use three sentences maximum and keep the answer as concise as possible. 
+    {context}
+    Question: {question}
+    Helpful Answer:"""
+    QA_CHAIN_PROMPT = PromptTemplate(
+        input_variables=["context", "question"],
+        template=template,
+    )
+
+    llm = Ollama(model="llama2:13b", callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]))
+    qa_chain = RetrievalQA.from_chain_type(
+        llm,
+        retriever=vectorstore.as_retriever(),
+        chain_type_kwargs={"prompt": QA_CHAIN_PROMPT},
+    )
+
+    result = qa_chain({"query": query})

examples/langchain-python-rag-document/requirements.txt

@@ -0,0 +1,109 @@
+absl-py==1.4.0
+aiohttp==3.8.5
+aiosignal==1.3.1
+anyio==3.7.1
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.1.0
+backoff==2.2.1
+beautifulsoup4==4.12.2
+bs4==0.0.1
+cachetools==5.3.1
+certifi==2023.7.22
+cffi==1.15.1
+chardet==5.2.0
+charset-normalizer==3.2.0
+Chroma==0.2.0
+chroma-hnswlib==0.7.2
+chromadb==0.4.5
+click==8.1.6
+coloredlogs==15.0.1
+cryptography==41.0.3
+dataclasses-json==0.5.14
+fastapi==0.99.1
+filetype==1.2.0
+flatbuffers==23.5.26
+frozenlist==1.4.0
+gast==0.4.0
+google-auth==2.22.0
+google-auth-oauthlib==1.0.0
+google-pasta==0.2.0
+gpt4all==1.0.8
+grpcio==1.57.0
+h11==0.14.0
+h5py==3.9.0
+httptools==0.6.0
+humanfriendly==10.0
+idna==3.4
+importlib-resources==6.0.1
+joblib==1.3.2
+keras==2.13.1
+langchain==0.0.261
+langsmith==0.0.21
+libclang==16.0.6
+lxml==4.9.3
+Markdown==3.4.4
+MarkupSafe==2.1.3
+marshmallow==3.20.1
+monotonic==1.6
+mpmath==1.3.0
+multidict==6.0.4
+mypy-extensions==1.0.0
+nltk==3.8.1
+numexpr==2.8.5
+numpy==1.24.3
+oauthlib==3.2.2
+onnxruntime==1.15.1
+openapi-schema-pydantic==1.2.4
+opt-einsum==3.3.0
+overrides==7.4.0
+packaging==23.1
+pdf2image==1.16.3
+pdfminer==20191125
+pdfminer.six==20221105
+Pillow==10.0.0
+posthog==3.0.1
+protobuf==4.24.0
+pulsar-client==3.2.0
+pyasn1==0.5.0
+pyasn1-modules==0.3.0
+pycparser==2.21
+pycryptodome==3.18.0
+pydantic==1.10.12
+PyPika==0.48.9
+python-dateutil==2.8.2
+python-dotenv==1.0.0
+python-magic==0.4.27
+PyYAML==6.0.1
+regex==2023.8.8
+requests==2.31.0
+requests-oauthlib==1.3.1
+rsa==4.9
+six==1.16.0
+sniffio==1.3.0
+soupsieve==2.4.1
+SQLAlchemy==2.0.19
+starlette==0.27.0
+sympy==1.12
+tabulate==0.9.0
+tenacity==8.2.2
+tensorboard==2.13.0
+tensorboard-data-server==0.7.1
+tensorflow==2.13.0
+tensorflow-estimator==2.13.0
+tensorflow-hub==0.14.0
+tensorflow-macos==2.13.0
+termcolor==2.3.0
+tokenizers==0.13.3
+tqdm==4.66.1
+typing-inspect==0.9.0
+typing_extensions==4.5.0
+unstructured==0.9.2
+urllib3==1.26.16
+uvicorn==0.23.2
+uvloop==0.17.0
+watchfiles==0.19.0
+websockets==11.0.3
+Werkzeug==2.3.6
+wrapt==1.15.0
+yarl==1.9.2

examples/langchain-python-rag-privategpt/.gitignore

@@ -0,0 +1,170 @@
+# OSX
+.DS_STORE
+
+# Models
+models/
+
+# Local Chroma db
+.chroma/
+db/
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

examples/langchain-python-rag-privategpt/LICENSE

@@ -0,0 +1,201 @@
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+
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examples/langchain-python-rag-privategpt/README.md

@@ -0,0 +1,91 @@
+# PrivateGPT with Llama 2 uncensored
+
+https://github.com/jmorganca/ollama/assets/3325447/20cf8ec6-ff25-42c6-bdd8-9be594e3ce1b
+
+> Note: this example is a slightly modified version of PrivateGPT using models such as Llama 2 Uncensored. All credit for PrivateGPT goes to Iván Martínez who is the creator of it, and you can find his GitHub repo [here](https://github.com/imartinez/privateGPT).
+
+### Setup
+
+Set up a virtual environment (optional):
+
+```
+python3 -m venv .venv
+source .venv/bin/activate
+```
+
+Install the Python dependencies:
+
+```shell
+pip install -r requirements.txt
+```
+
+Pull the model you'd like to use:
+
+```
+ollama pull llama2-uncensored
+```
+
+### Getting WeWork's latest quarterly earnings report (10-Q)
+
+```
+mkdir source_documents
+curl https://d18rn0p25nwr6d.cloudfront.net/CIK-0001813756/975b3e9b-268e-4798-a9e4-2a9a7c92dc10.pdf -o source_documents/wework.pdf
+```
+
+### Ingesting files
+
+```shell
+python ingest.py
+```
+
+Output should look like this:
+
+```shell
+Creating new vectorstore
+Loading documents from source_documents
+Loading new documents: 100%|██████████████████████| 1/1 [00:01<00:00,  1.73s/it]
+Loaded 1 new documents from source_documents
+Split into 90 chunks of text (max. 500 tokens each)
+Creating embeddings. May take some minutes...
+Using embedded DuckDB with persistence: data will be stored in: db
+Ingestion complete! You can now run privateGPT.py to query your documents
+```
+
+### Ask questions
+
+```shell
+python privateGPT.py
+
+Enter a query: How many locations does WeWork have?
+
+> Answer (took 17.7 s.):
+As of June 2023, WeWork has 777 locations worldwide, including 610 Consolidated Locations (as defined in the section entitled Key Performance Indicators).
+```
+
+### Try a different model:
+
+```
+ollama pull llama2:13b
+MODEL=llama2:13b python privateGPT.py
+```
+
+## Adding more files
+
+Put any and all your files into the `source_documents` directory
+
+The supported extensions are:
+
+- `.csv`: CSV,
+- `.docx`: Word Document,
+- `.doc`: Word Document,
+- `.enex`: EverNote,
+- `.eml`: Email,
+- `.epub`: EPub,
+- `.html`: HTML File,
+- `.md`: Markdown,
+- `.msg`: Outlook Message,
+- `.odt`: Open Document Text,
+- `.pdf`: Portable Document Format (PDF),
+- `.pptx` : PowerPoint Document,
+- `.ppt` : PowerPoint Document,
+- `.txt`: Text file (UTF-8),

examples/langchain-python-rag-privategpt/constants.py

@@ -0,0 +1,11 @@
+import os
+from chromadb.config import Settings
+
+# Define the folder for storing database
+PERSIST_DIRECTORY = os.environ.get('PERSIST_DIRECTORY', 'db')
+
+# Define the Chroma settings
+CHROMA_SETTINGS = Settings(
+        persist_directory=PERSIST_DIRECTORY,
+        anonymized_telemetry=False
+)

examples/langchain-python-rag-privategpt/ingest.py

@@ -0,0 +1,161 @@
+#!/usr/bin/env python3
+import os
+import glob
+from typing import List
+from multiprocessing import Pool
+from tqdm import tqdm
+
+from langchain.document_loaders import (
+    CSVLoader,
+    EverNoteLoader,
+    PyMuPDFLoader,
+    TextLoader,
+    UnstructuredEmailLoader,
+    UnstructuredEPubLoader,
+    UnstructuredHTMLLoader,
+    UnstructuredMarkdownLoader,
+    UnstructuredODTLoader,
+    UnstructuredPowerPointLoader,
+    UnstructuredWordDocumentLoader,
+)
+
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import Chroma
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.docstore.document import Document
+from constants import CHROMA_SETTINGS
+
+
+# Load environment variables
+persist_directory = os.environ.get('PERSIST_DIRECTORY', 'db')
+source_directory = os.environ.get('SOURCE_DIRECTORY', 'source_documents')
+embeddings_model_name = os.environ.get('EMBEDDINGS_MODEL_NAME', 'all-MiniLM-L6-v2')
+chunk_size = 500
+chunk_overlap = 50
+
+# Custom document loaders
+class MyElmLoader(UnstructuredEmailLoader):
+    """Wrapper to fallback to text/plain when default does not work"""
+
+    def load(self) -> List[Document]:
+        """Wrapper adding fallback for elm without html"""
+        try:
+            try:
+                doc = UnstructuredEmailLoader.load(self)
+            except ValueError as e:
+                if 'text/html content not found in email' in str(e):
+                    # Try plain text
+                    self.unstructured_kwargs["content_source"]="text/plain"
+                    doc = UnstructuredEmailLoader.load(self)
+                else:
+                    raise
+        except Exception as e:
+            # Add file_path to exception message
+            raise type(e)(f"{self.file_path}: {e}") from e
+
+        return doc
+
+
+# Map file extensions to document loaders and their arguments
+LOADER_MAPPING = {
+    ".csv": (CSVLoader, {}),
+    # ".docx": (Docx2txtLoader, {}),
+    ".doc": (UnstructuredWordDocumentLoader, {}),
+    ".docx": (UnstructuredWordDocumentLoader, {}),
+    ".enex": (EverNoteLoader, {}),
+    ".eml": (MyElmLoader, {}),
+    ".epub": (UnstructuredEPubLoader, {}),
+    ".html": (UnstructuredHTMLLoader, {}),
+    ".md": (UnstructuredMarkdownLoader, {}),
+    ".odt": (UnstructuredODTLoader, {}),
+    ".pdf": (PyMuPDFLoader, {}),
+    ".ppt": (UnstructuredPowerPointLoader, {}),
+    ".pptx": (UnstructuredPowerPointLoader, {}),
+    ".txt": (TextLoader, {"encoding": "utf8"}),
+    # Add more mappings for other file extensions and loaders as needed
+}
+
+
+def load_single_document(file_path: str) -> List[Document]:
+    ext = "." + file_path.rsplit(".", 1)[-1]
+    if ext in LOADER_MAPPING:
+        loader_class, loader_args = LOADER_MAPPING[ext]
+        loader = loader_class(file_path, **loader_args)
+        return loader.load()
+
+    raise ValueError(f"Unsupported file extension '{ext}'")
+
+def load_documents(source_dir: str, ignored_files: List[str] = []) -> List[Document]:
+    """
+    Loads all documents from the source documents directory, ignoring specified files
+    """
+    all_files = []
+    for ext in LOADER_MAPPING:
+        all_files.extend(
+            glob.glob(os.path.join(source_dir, f"**/*{ext}"), recursive=True)
+        )
+    filtered_files = [file_path for file_path in all_files if file_path not in ignored_files]
+
+    with Pool(processes=os.cpu_count()) as pool:
+        results = []
+        with tqdm(total=len(filtered_files), desc='Loading new documents', ncols=80) as pbar:
+            for i, docs in enumerate(pool.imap_unordered(load_single_document, filtered_files)):
+                results.extend(docs)
+                pbar.update()
+
+    return results
+
+def process_documents(ignored_files: List[str] = []) -> List[Document]:
+    """
+    Load documents and split in chunks
+    """
+    print(f"Loading documents from {source_directory}")
+    documents = load_documents(source_directory, ignored_files)
+    if not documents:
+        print("No new documents to load")
+        exit(0)
+    print(f"Loaded {len(documents)} new documents from {source_directory}")
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
+    texts = text_splitter.split_documents(documents)
+    print(f"Split into {len(texts)} chunks of text (max. {chunk_size} tokens each)")
+    return texts
+
+def does_vectorstore_exist(persist_directory: str) -> bool:
+    """
+    Checks if vectorstore exists
+    """
+    if os.path.exists(os.path.join(persist_directory, 'index')):
+        if os.path.exists(os.path.join(persist_directory, 'chroma-collections.parquet')) and os.path.exists(os.path.join(persist_directory, 'chroma-embeddings.parquet')):
+            list_index_files = glob.glob(os.path.join(persist_directory, 'index/*.bin'))
+            list_index_files += glob.glob(os.path.join(persist_directory, 'index/*.pkl'))
+            # At least 3 documents are needed in a working vectorstore
+            if len(list_index_files) > 3:
+                return True
+    return False
+
+def main():
+    # Create embeddings
+    embeddings = HuggingFaceEmbeddings(model_name=embeddings_model_name)
+
+    if does_vectorstore_exist(persist_directory):
+        # Update and store locally vectorstore
+        print(f"Appending to existing vectorstore at {persist_directory}")
+        db = Chroma(persist_directory=persist_directory, embedding_function=embeddings, client_settings=CHROMA_SETTINGS)
+        collection = db.get()
+        texts = process_documents([metadata['source'] for metadata in collection['metadatas']])
+        print(f"Creating embeddings. May take some minutes...")
+        db.add_documents(texts)
+    else:
+        # Create and store locally vectorstore
+        print("Creating new vectorstore")
+        texts = process_documents()
+        print(f"Creating embeddings. May take some minutes...")
+        db = Chroma.from_documents(texts, embeddings, persist_directory=persist_directory)
+    db.persist()
+    db = None
+
+    print(f"Ingestion complete! You can now run privateGPT.py to query your documents")
+
+
+if __name__ == "__main__":
+    main()