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1 Commits

Author SHA1 Message Date
Jeffrey Morgan
2789ed31a7 improve scratch buffer estimates 2024-01-19 13:24:24 -05:00
68 changed files with 1286 additions and 2892 deletions

View File

@@ -23,72 +23,29 @@ jobs:
with:
go-version: '1.21'
cache: true
- if: ${{ startsWith(matrix.os, 'windows-') }}
shell: pwsh
run: |
$path = vswhere -latest -products * -requires Microsoft.VisualStudio.Component.VC.Tools.x86.x64 -property installationPath
if ($path) {
$path = join-path $path 'Common7\Tools\vsdevcmd.bat'
if (test-path $path) {
cmd /s /c """$path"" $args && set" | where { $_ -match '(\w+)=(.*)' } | foreach {
echo "$($Matches[1])=$($Matches[2])" | Out-File -FilePath $Env:GITHUB_ENV -Encoding utf8 -Append
}
}
}
echo "C:\Program Files\Git\usr\bin" | Out-File -FilePath $Env:GITHUB_PATH -Encoding utf8 -Append
- run: go get ./...
- run: go generate -x ./...
- 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:${{ matrix.cuda-version }}-devel-ubuntu20.04
steps:
- run: |
apt-get update && apt-get install -y git build-essential curl
curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.28.1/cmake-3.28.1-linux-x86_64.tar.gz \
| tar -zx -C /usr --strip-components 1
env:
DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version: '1.21'
cache: true
- run: go get ./...
- run: |
git config --global --add safe.directory /__w/ollama/ollama
go generate -x ./...
env:
OLLAMA_SKIP_CPU_GENERATE: '1'
- uses: actions/upload-artifact@v4
with:
name: cuda-${{ matrix.cuda-version }}-libraries
path: llm/llama.cpp/build/**/lib/*
generate-rocm:
strategy:
matrix:
rocm-version:
- '5.7.1'
- '6.0'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
- run: |
apt-get update && apt-get install -y git build-essential curl rocm-libs
curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.28.1/cmake-3.28.1-linux-x86_64.tar.gz \
| tar -zx -C /usr --strip-components 1
env:
DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version: '1.21'
cache: true
- run: go get ./...
- run: |
git config --global --add safe.directory /__w/ollama/ollama
go generate -x ./...
env:
OLLAMA_SKIP_CPU_GENERATE: '1'
- uses: actions/upload-artifact@v4
with:
name: rocm-${{ matrix.rocm-version }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: |
llm/llama.cpp/build/**/lib/*
lint:
needs: generate
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
@@ -112,19 +69,10 @@ jobs:
with:
go-version: '1.21'
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: actions/download-artifact@v4
with:
name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
path: llm/llama.cpp/build
- uses: golangci/golangci-lint-action@v3
test:
needs: generate
@@ -156,7 +104,3 @@ jobs:
path: llm/llama.cpp/build
- run: go build
- run: go test -v ./...
- uses: actions/upload-artifact@v4
with:
name: ${{ matrix.os }}-binaries
path: ollama

View File

@@ -1,135 +1,27 @@
ARG GOLANG_VERSION=1.21.3
ARG CMAKE_VERSION=3.22.1
ARG CUDA_VERSION=11.3.1
FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
# 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
ARG TARGETARCH
ARG GOFLAGS="'-ldflags=-w -s'"
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-7:5.7.1-complete AS rocm-5-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
FROM --platform=linux/amd64 rocm/dev-centos-7:6.0-complete AS rocm-6-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
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
RUN apt-get update && apt-get install -y git build-essential cmake
ADD https://dl.google.com/go/go1.21.3.linux-$TARGETARCH.tar.gz /tmp/go1.21.3.tar.gz
RUN mkdir -p /usr/local && tar xz -C /usr/local </tmp/go1.21.3.tar.gz
COPY . .
COPY --from=cpu_avx-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=cpu_avx2-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=cuda-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-5-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-6-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
ARG GOFLAGS
ARG CGO_CFLAGS
RUN go build .
ENV GOARCH=$TARGETARCH
ENV GOFLAGS=$GOFLAGS
RUN /usr/local/go/bin/go generate ./... \
&& /usr/local/go/bin/go build .
# Intermediate stage used for ./scripts/build_linux.sh
FROM --platform=linux/arm64 cpu-build-arm64 AS build-arm64
ENV CGO_ENABLED 1
ARG GOLANG_VERSION
WORKDIR /go/src/github.com/jmorganca/ollama
COPY . .
COPY --from=cuda-build-arm64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
ARG GOFLAGS
ARG CGO_CFLAGS
RUN go build .
# Runtime stages
FROM --platform=linux/amd64 ubuntu:22.04 as runtime-amd64
FROM ubuntu:22.04
RUN apt-get update && apt-get install -y ca-certificates
COPY --from=build-amd64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
FROM --platform=linux/arm64 ubuntu:22.04 as runtime-arm64
RUN apt-get update && apt-get install -y ca-certificates
COPY --from=build-arm64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
# Radeon images are much larger so we keep it distinct from the CPU/CUDA image
FROM --platform=linux/amd64 rocm/dev-centos-7:5.7.1-complete as runtime-rocm
RUN update-pciids
COPY --from=build-amd64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
COPY --from=0 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
EXPOSE 11434
ENV OLLAMA_HOST 0.0.0.0
ENTRYPOINT ["/bin/ollama"]
CMD ["serve"]
FROM runtime-$TARGETARCH
EXPOSE 11434
ENV OLLAMA_HOST 0.0.0.0
ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# set some environment variable for better NVIDIA compatibility
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/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

99
Dockerfile.build Normal file
View File

@@ -0,0 +1,99 @@
ARG GOLANG_VERSION=1.21.3
ARG CMAKE_VERSION=3.22.1
ARG CUDA_VERSION=11.3.1
# 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:$CUDA_VERSION-devel-centos7 AS cuda-build-amd64
ARG CMAKE_VERSION
ARG CGO_CFLAGS
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION-devel-rockylinux8 AS cuda-build-arm64
ARG CMAKE_VERSION
ARG CGO_CFLAGS
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
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
FROM --platform=linux/amd64 rocm/dev-centos-7:5.7.1-complete AS rocm-5-build-amd64
ARG CMAKE_VERSION
ARG CGO_CFLAGS
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
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
FROM --platform=linux/amd64 rocm/dev-centos-7:6.0-complete AS rocm-6-build-amd64
ARG CMAKE_VERSION
ARG CGO_CFLAGS
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
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
FROM --platform=linux/amd64 centos:7 AS cpu-build-amd64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
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:$PATH
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
RUN sh gen_linux.sh
FROM --platform=linux/arm64 centos:7 AS cpu-build-arm64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${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
RUN sh gen_linux.sh
FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
ENV CGO_ENABLED 1
ARG GOFLAGS
ARG CGO_CFLAGS
WORKDIR /go/src/github.com/jmorganca/ollama
COPY . .
COPY --from=cuda-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-5-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-6-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
RUN go build .
FROM --platform=linux/arm64 cpu-build-arm64 AS build-arm64
ENV CGO_ENABLED 1
ARG GOLANG_VERSION
ARG GOFLAGS
ARG CGO_CFLAGS
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/
RUN go build .
FROM build-$TARGETARCH

View File

@@ -1,5 +1,8 @@
<div align="center">
<img alt="ollama" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
<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>
</div>
# Ollama
@@ -10,7 +13,7 @@ Get up and running with large language models locally.
### macOS
[Download](https://ollama.com/download/Ollama-darwin.zip)
[Download](https://ollama.ai/download/Ollama-darwin.zip)
### Windows
@@ -19,7 +22,7 @@ Coming soon! For now, you can install Ollama on Windows via WSL2.
### Linux & WSL2
```
curl -fsSL https://ollama.com/install.sh | sh
curl https://ollama.ai/install.sh | sh
```
[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
@@ -28,14 +31,9 @@ curl -fsSL https://ollama.com/install.sh | sh
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://ollama.com/library/llama2):
To run and chat with [Llama 2](https://ollama.ai/library/llama2):
```
ollama run llama2
@@ -43,7 +41,7 @@ ollama run llama2
## Model library
Ollama supports a list of open-source models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
Ollama supports a list of open-source models available on [ollama.ai/library](https://ollama.ai/library 'ollama model library')
Here are some example open-source models that can be downloaded:
@@ -200,21 +198,18 @@ brew install cmake go
```
Then generate dependencies:
```
go generate ./...
```
Then build the binary:
```
go build .
```
More detailed instructions can be found in the [developer guide](https://github.com/jmorganca/ollama/blob/main/docs/development.md)
### Running local builds
### Running local builds
Next, start the server:
```
@@ -253,10 +248,13 @@ curl http://localhost:11434/api/chat -d '{
See the [API documentation](./docs/api.md) for all endpoints.
## Integrations
- [ollama-python](https://github.com/jmorganca/ollama-python)
## Community Integrations
### Web & Desktop
- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
@@ -269,7 +267,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Amica](https://github.com/semperai/amica)
- [chatd](https://github.com/BruceMacD/chatd)
- [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
- [MindMac](https://mindmac.app)
### Terminal
@@ -282,7 +280,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [gptel Emacs client](https://github.com/karthink/gptel)
- [Oatmeal](https://github.com/dustinblackman/oatmeal)
- [cmdh](https://github.com/pgibler/cmdh)
- [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
### Database
@@ -309,8 +306,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [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)
- [Ollama for R - rollama](https://github.com/JBGruber/rollama)
- [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
### Mobile
@@ -331,6 +327,4 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [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)
- [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)
- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)

View File

@@ -34,26 +34,24 @@ func (e StatusError) Error() string {
type ImageData []byte
type GenerateRequest struct {
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"`
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"`
Images []ImageData `json:"images,omitempty"`
Options map[string]interface{} `json:"options"`
}
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"`
Model string `json:"model"`
Messages []Message `json:"messages"`
Stream *bool `json:"stream,omitempty"`
Format string `json:"format"`
Options map[string]interface{} `json:"options"`
}
@@ -128,9 +126,8 @@ type Runner struct {
}
type EmbeddingRequest struct {
Model string `json:"model"`
Prompt string `json:"prompt"`
KeepAlive *Duration `json:"keep_alive,omitempty"`
Model string `json:"model"`
Prompt string `json:"prompt"`
Options map[string]interface{} `json:"options"`
}
@@ -174,7 +171,6 @@ type ShowResponse struct {
Template string `json:"template,omitempty"`
System string `json:"system,omitempty"`
Details ModelDetails `json:"details,omitempty"`
Messages []Message `json:"messages,omitempty"`
}
type CopyRequest struct {
@@ -240,7 +236,6 @@ type GenerateResponse struct {
}
type ModelDetails struct {
ParentModel string `json:"parent_model"`
Format string `json:"format"`
Family string `json:"family"`
Families []string `json:"families"`
@@ -415,18 +410,15 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
switch t := v.(type) {
case float64:
if t < 0 {
d.Duration = time.Duration(math.MaxInt64)
} else {
d.Duration = time.Duration(t * float64(time.Second))
t = math.MaxFloat64
}
d.Duration = time.Duration(t)
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

View File

@@ -25,7 +25,6 @@ import (
"github.com/olekukonko/tablewriter"
"github.com/spf13/cobra"
"golang.org/x/crypto/ssh"
"golang.org/x/exp/slices"
"golang.org/x/term"
"github.com/jmorganca/ollama/api"
@@ -147,68 +146,19 @@ func RunHandler(cmd *cobra.Command, args []string) error {
}
name := args[0]
// check if the model exists on the server
show, err := client.Show(cmd.Context(), &api.ShowRequest{Name: name})
_, err = client.Show(cmd.Context(), &api.ShowRequest{Name: name})
var statusError api.StatusError
switch {
case errors.As(err, &statusError) && statusError.StatusCode == http.StatusNotFound:
if err := PullHandler(cmd, []string{name}); err != nil {
return err
}
show, err = client.Show(cmd.Context(), &api.ShowRequest{Name: name})
if err != nil {
return err
}
case err != nil:
return err
}
interactive := true
opts := runOptions{
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
MultiModal: slices.Contains(show.Details.Families, "clip"),
ParentModel: show.Details.ParentModel,
}
format, err := cmd.Flags().GetString("format")
if err != nil {
return err
}
opts.Format = format
prompts := args[1:]
// prepend stdin to the prompt if provided
if !term.IsTerminal(int(os.Stdin.Fd())) {
in, err := io.ReadAll(os.Stdin)
if err != nil {
return err
}
prompts = append([]string{string(in)}, prompts...)
opts.WordWrap = false
interactive = false
}
opts.Prompt = strings.Join(prompts, " ")
if len(prompts) > 0 {
interactive = false
}
nowrap, err := cmd.Flags().GetBool("nowordwrap")
if err != nil {
return err
}
opts.WordWrap = !nowrap
if !interactive {
return generate(cmd, opts)
}
return generateInteractive(cmd, opts)
return RunGenerate(cmd, args)
}
func PushHandler(cmd *cobra.Command, args []string) error {
@@ -460,20 +410,63 @@ func PullHandler(cmd *cobra.Command, args []string) error {
return nil
}
func RunGenerate(cmd *cobra.Command, args []string) error {
interactive := true
opts := runOptions{
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
}
format, err := cmd.Flags().GetString("format")
if err != nil {
return err
}
opts.Format = format
prompts := args[1:]
// prepend stdin to the prompt if provided
if !term.IsTerminal(int(os.Stdin.Fd())) {
in, err := io.ReadAll(os.Stdin)
if err != nil {
return err
}
prompts = append([]string{string(in)}, prompts...)
opts.WordWrap = false
interactive = false
}
opts.Prompt = strings.Join(prompts, " ")
if len(prompts) > 0 {
interactive = false
}
nowrap, err := cmd.Flags().GetBool("nowordwrap")
if err != nil {
return err
}
opts.WordWrap = !nowrap
if !interactive {
return generate(cmd, opts)
}
return generateInteractive(cmd, opts)
}
type generateContextKey string
type runOptions struct {
Model string
ParentModel string
Prompt string
Messages []api.Message
WordWrap bool
Format string
System string
Template string
Images []api.ImageData
Options map[string]interface{}
MultiModal bool
Model string
Prompt string
Messages []api.Message
WordWrap bool
Format string
System string
Template string
Images []api.ImageData
Options map[string]interface{}
}
type displayResponseState struct {
@@ -635,18 +628,10 @@ func generate(cmd *cobra.Command, opts runOptions) error {
return nil
}
if opts.MultiModal {
opts.Prompt, opts.Images, err = extractFileData(opts.Prompt)
if err != nil {
return err
}
}
request := api.GenerateRequest{
Model: opts.Model,
Prompt: opts.Prompt,
Context: generateContext,
Images: opts.Images,
Format: opts.Format,
System: opts.System,
Template: opts.Template,

View File

@@ -6,16 +6,13 @@ import (
"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"
)
@@ -28,82 +25,45 @@ const (
MultilineTemplate
)
func loadModel(cmd *cobra.Command, opts *runOptions) error {
func modelIsMultiModal(cmd *cobra.Command, name string) bool {
// get model details
client, err := api.ClientFromEnvironment()
if err != nil {
return err
fmt.Println("error: couldn't connect to ollama server")
return false
}
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)
req := api.ShowRequest{Name: name}
resp, err := client.Show(cmd.Context(), &req)
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...)
return false
}
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
return slices.Contains(resp.Details.Families, "clip")
}
func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = make([]api.Message, 0)
multiModal := modelIsMultiModal(cmd, opts.Model)
err := loadModel(cmd, &opts)
if err != nil {
// load the model
loadOpts := runOptions{
Model: opts.Model,
Prompt: "",
Messages: []api.Message{},
}
if _, err := chat(cmd, loadOpts); 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, " /set Set session variables")
fmt.Fprintln(os.Stderr, " /show Show model information")
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, "")
}
@@ -180,6 +140,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
var sb strings.Builder
var multiline MultilineState
opts.Messages = make([]api.Message, 0)
for {
line, err := scanner.Readline()
@@ -213,7 +174,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
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:
@@ -233,6 +193,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fmt.Fprintln(&sb)
multiline = MultilinePrompt
scanner.Prompt.UseAlt = true
break
}
case scanner.Pasting:
fmt.Fprintln(&sb, line)
@@ -242,44 +203,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
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 {
@@ -355,13 +278,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
if args[1] == "system" {
opts.System = sb.String()
opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
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()
@@ -469,7 +389,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
args := strings.Fields(line)
isFile := false
if opts.MultiModal {
if multiModal {
for _, f := range extractFileNames(line) {
if strings.HasPrefix(f, args[0]) {
isFile = true
@@ -491,23 +411,34 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
if sb.Len() > 0 && multiline == MultilineNone {
newMessage := api.Message{Role: "user", Content: sb.String()}
if opts.MultiModal {
if multiModal {
msg, images, err := extractFileData(sb.String())
if err != nil {
return err
}
newMessage.Content = msg
// clear all previous images for better responses
// reset the context if we find another image
if len(images) > 0 {
for i := range opts.Messages {
opts.Messages[i].Images = nil
newMessage.Images = append(newMessage.Images, images...)
// reset the context for the new image
opts.Messages = []api.Message{}
} else {
if len(opts.Messages) > 1 {
newMessage.Images = append(newMessage.Images, opts.Messages[len(opts.Messages)-2].Images...)
}
}
newMessage.Content = msg
newMessage.Images = images
if len(newMessage.Images) == 0 {
fmt.Println("This model requires you to add a jpeg, png, or svg image.")
fmt.Println()
sb.Reset()
continue
}
}
if opts.System != "" {
opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
}
opts.Messages = append(opts.Messages, newMessage)
assistant, err := chat(cmd, opts)
@@ -523,38 +454,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
}
}
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{
@@ -601,10 +500,10 @@ func extractFileData(input string) (string, []api.ImageData, error) {
if os.IsNotExist(err) {
continue
}
fmt.Fprintf(os.Stderr, "Couldn't process image: %q\n", err)
fmt.Printf("Couldn't process image: %q\n", err)
return "", imgs, err
}
fmt.Fprintf(os.Stderr, "Added image '%s'\n", nfp)
fmt.Printf("Added image '%s'\n", nfp)
input = strings.ReplaceAll(input, fp, "")
imgs = append(imgs, data)
}
@@ -625,7 +524,7 @@ func getImageData(filePath string) ([]byte, error) {
}
contentType := http.DetectContentType(buf)
allowedTypes := []string{"image/jpeg", "image/jpg", "image/png"}
allowedTypes := []string{"image/jpeg", "image/jpg", "image/svg+xml", "image/png"}
if !slices.Contains(allowedTypes, contentType) {
return nil, fmt.Errorf("invalid image type: %s", contentType)
}

View File

@@ -1,13 +1,9 @@
package cmd
import (
"bytes"
"testing"
"text/template"
"github.com/stretchr/testify/assert"
"github.com/jmorganca/ollama/api"
)
func TestExtractFilenames(t *testing.T) {
@@ -53,64 +49,3 @@ d:\path with\spaces\seven.svg inbetween7 c:\users\jdoe\eight.png inbetween8
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)
}

View File

@@ -10,7 +10,7 @@ Create new models or modify models already in the library using the Modelfile. L
Import models using source model weights found on Hugging Face and similar sites by referring to the **[Import Documentation](./import.md)**.
Installing on Linux in most cases is easy using the script on [ollama.com/download](ollama.com/download). To get more detail about the install, including CUDA drivers, see the **[Linux Documentation](./linux.md)**.
Installing on Linux in most cases is easy using the script on Ollama.ai. To get more detail about the install, including CUDA drivers, see the **[Linux Documentation](./linux.md)**.
Many of our users like the flexibility of using our official Docker Image. Learn more about using Docker with Ollama using the **[Docker Documentation](https://hub.docker.com/r/ollama/ollama)**.

View File

@@ -49,8 +49,7 @@ Advanced parameters (optional):
- `template`: the prompt template to use (overrides what is defined in the `Modelfile`)
- `context`: the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
- `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
- `raw`: if `true` no formatting will be applied to the prompt. You may choose to use the `raw` parameter if you are specifying a full templated prompt in your request to the API
- `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
- `raw`: if `true` no formatting will be applied to the prompt. You may choose to use the `raw` parameter if you are specifying a full templated prompt in your request to the API.
#### JSON mode
@@ -380,7 +379,6 @@ Advanced parameters (optional):
- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
- `template`: the prompt template to use (overrides what is defined in the `Modelfile`)
- `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
- `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
### Examples
@@ -544,7 +542,7 @@ curl http://localhost:11434/api/chat -d '{
"role": "user",
"content": "what is in this image?",
"images": ["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"]
}
},
]
}'
```
@@ -960,7 +958,6 @@ Generate embeddings from a model
Advanced parameters:
- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
- `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
### Examples

View File

@@ -50,8 +50,7 @@ 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")
libraries, and `CUDACXX` to the location of the nvcc compiler.
Then generate dependencies:
@@ -75,8 +74,7 @@ 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"`)
CLBlast install (typically `/usr/lib/cmake/CLBlast`).
```
go generate ./...

View File

@@ -8,38 +8,35 @@ To upgrade Ollama, run the installation process again. On the Mac, click the Oll
Review the [Troubleshooting](./troubleshooting.md) docs for more about using logs.
## How do I configure Ollama server?
## How do I use Ollama server environment variables on Mac
Ollama server can be configured with environment variables.
On macOS, Ollama runs in the background and is managed by the menubar app. If adding environment variables, Ollama will need to be run manually.
### Setting environment variables on Mac
1. Click the menubar icon for Ollama and choose **Quit Ollama**.
2. Open a new terminal window and run the following command (this example uses `OLLAMA_HOST` with an IP address of `123.1.1.1`):
If Ollama is run as a macOS application, environment variables should be set using `launchctl`:
```bash
OLLAMA_HOST=123.1.1.1 ollama serve
```
1. For each environment variable, call `launchctl setenv`.
## How do I use Ollama server environment variables on Linux?
```bash
launchctl setenv OLLAMA_HOST "0.0.0.0"
```
If Ollama is installed with the install script, a systemd service was created, running as the Ollama user. To add an environment variable, such as OLLAMA_HOST, follow these steps:
2. Restart Ollama application.
1. Create a `systemd` drop-in directory and add a config file. This is only needed once.
### Setting environment variables on Linux
```bash
mkdir -p /etc/systemd/system/ollama.service.d
echo '[Service]' >>/etc/systemd/system/ollama.service.d/environment.conf
```
If Ollama is run as a systemd service, environment variables should be set using `systemctl`:
2. For each environment variable, add it to the config file:
1. Edit the systemd service by calling `systemctl edit ollama.service`. This will open an editor.
```bash
echo 'Environment="OLLAMA_HOST=0.0.0.0:11434"' >>/etc/systemd/system/ollama.service.d/environment.conf
```
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:
3. Reload `systemd` and restart Ollama:
```bash
systemctl daemon-reload
@@ -48,26 +45,26 @@ If Ollama is run as a systemd service, environment variables should be set using
## 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.
Ollama binds to 127.0.0.1 port 11434 by default. Change the bind address with the `OLLAMA_HOST` environment variable. Refer to the section above for how to use 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`.
Ollama allows cross-origin requests from `127.0.0.1` and `0.0.0.0` by default. Add additional origins with the `OLLAMA_ORIGINS` environment variable. For example, to add all ports on 192.168.1.1 and https://example.com, use:
Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
```shell
OLLAMA_ORIGINS=http://192.168.1.1:*,https://example.com
```
Refer to the section above for how to use environment variables on your platform.
## Where are models stored?
- macOS: `~/.ollama/models`.
- Linux: `/usr/share/ollama/.ollama/models`
### How do I set them to a different location?
## 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.
If a different directory needs to be used, set the environment variable `OLLAMA_MODELS` to the chosen directory. Refer to the section above for how to use environment variables on your platform.
## Does Ollama send my prompts and answers back to Ollama.ai to use in any way?

View File

@@ -15,7 +15,7 @@ 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
FROM ./q4_0.bin
TEMPLATE "[INST] {{ .Prompt }} [/INST]"
```
@@ -37,69 +37,55 @@ 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.
### Supported models
### Setup
Ollama supports a set of model architectures, with support for more coming soon:
First, clone the `ollama/ollama` repo:
- Llama & Mistral
- Falcon & RW
- BigCode
```
git clone git@github.com:ollama/ollama.git ollama
cd ollama
```
To view a model's architecture, check the `config.json` file in its HuggingFace repo. You should see an entry under `architectures` (e.g. `LlamaForCausalLM`).
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)
### Step 1: 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
git clone https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1
cd Mistral-7B-Instruct-v0.1
```
### Convert the model
### Step 2: Convert and quantize to a `.bin` file (optional, for PyTorch and Safetensors)
> Note: some model architectures require using specific convert scripts. For example, Qwen models require running `convert-hf-to-gguf.py` instead of `convert.py`
If the model is in PyTorch or Safetensors format, a [Docker image](https://hub.docker.com/r/ollama/quantize) with the tooling required to convert and quantize models is available.
First, Install [Docker](https://www.docker.com/get-started/).
Next, to convert and quantize your model, run:
```
python llm/llama.cpp/convert.py ./model --outtype f16 --outfile converted.bin
docker run --rm -v .:/model ollama/quantize -q q4_0 /model
```
### Quantize the model
This will output two files into the directory:
```
llm/llama.cpp/quantize converted.bin quantized.bin q4_0
```
- `f16.bin`: the model converted to GGUF
- `q4_0.bin` the model quantized to a 4-bit quantization (Ollama will use this file to create the Ollama model)
### Step 3: Write a `Modelfile`
Next, create a `Modelfile` for your model:
```
FROM quantized.bin
FROM ./q4_0.bin
```
(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 ./q4_0.bin
TEMPLATE "[INST] {{ .Prompt }} [/INST]"
```
@@ -123,9 +109,9 @@ ollama run example "What is your favourite condiment?"
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)
1. Create [an account](https://ollama.ai/signup)
2. Run `cat ~/.ollama/id_ed25519.pub` to view your Ollama public key. Copy this to the clipboard.
3. Add your public key to your [Ollama account](https://ollama.com/settings/keys)
3. Add your public key to your [Ollama account](https://ollama.ai/settings/keys)
Next, copy your model to your username's namespace:
@@ -139,7 +125,7 @@ Then push the model:
ollama push <your username>/example
```
After publishing, your model will be available at `https://ollama.com/<your username>/example`.
After publishing, your model will be available at `https://ollama.ai/<your username>/example`.
## Quantization reference
@@ -163,3 +149,47 @@ The quantization options are as follow (from highest highest to lowest levels of
- `q6_K`
- `q8_0`
- `f16`
## Manually converting & quantizing models
### Prerequisites
Start by cloning the `llama.cpp` repo to your machine in another directory:
```
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
```
Next, install the Python dependencies:
```
pip install -r requirements.txt
```
Finally, build the `quantize` tool:
```
make quantize
```
### Convert the model
Run the correct conversion script for your model architecture:
```shell
# LlamaForCausalLM or MistralForCausalLM
python convert.py <path to model directory>
# FalconForCausalLM
python convert-falcon-hf-to-gguf.py <path to model directory>
# GPTBigCodeForCausalLM
python convert-starcoder-hf-to-gguf.py <path to model directory>
```
### Quantize the model
```
quantize <path to model dir>/ggml-model-f32.bin <path to model dir>/q4_0.bin q4_0
```

View File

@@ -3,11 +3,9 @@
## Install
Install Ollama running this one-liner:
>
```bash
curl -fsSL https://ollama.com/install.sh | sh
curl https://ollama.ai/install.sh | sh
```
## Manual install
@@ -17,7 +15,7 @@ curl -fsSL https://ollama.com/install.sh | sh
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 curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama
sudo chmod +x /usr/bin/ollama
```
@@ -77,13 +75,13 @@ sudo systemctl start ollama
Update ollama by running the install script again:
```bash
curl -fsSL https://ollama.com/install.sh | sh
curl https://ollama.ai/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 curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama
sudo chmod +x /usr/bin/ollama
```
@@ -112,7 +110,6 @@ sudo rm $(which ollama)
```
Remove the downloaded models and Ollama service user and group:
```bash
sudo rm -r /usr/share/ollama
sudo userdel ollama

View File

@@ -19,7 +19,6 @@ A model file is the blueprint to create and share models with Ollama.
- [SYSTEM](#system)
- [ADAPTER](#adapter)
- [LICENSE](#license)
- [MESSAGE](#message)
- [Notes](#notes)
## Format
@@ -39,7 +38,6 @@ INSTRUCTION arguments
| [`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
@@ -67,13 +65,13 @@ To use this:
More examples are available in the [examples directory](../examples).
### `Modelfile`s in [ollama.com/library][1]
### `Modelfile`s in [ollama.ai/library][1]
There are two ways to view `Modelfile`s underlying the models in [ollama.com/library][1]:
There are two ways to view `Modelfile`s underlying the models in [ollama.ai/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)
1. Go to a particular model's tags (e.g. https://ollama.ai/library/llama2/tags)
2. Click on a tag (e.g. https://ollama.ai/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
@@ -86,7 +84,7 @@ There are two ways to view `Modelfile`s underlying the models in [ollama.com/lib
# FROM llama2:13b
FROM /root/.ollama/models/blobs/sha256:123abc
TEMPLATE """[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>>
TEMPLATE """[INST] {{ if and .First .System }}<<SYS>>{{ .System }}<</SYS>>
{{ end }}{{ .Prompt }} [/INST] """
SYSTEM """"""
@@ -154,23 +152,31 @@ PARAMETER <parameter> <parametervalue>
### TEMPLATE
`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).
`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system message and a user's prompt. This is used to create a full custom prompt, and syntax may be model specific. You can usually find the template for a given model in the readme for that model.
#### 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. |
| Variable | Description |
| ----------------- | ------------------------------------------------------------------------------------------------------------- |
| `{{ .System }}` | The system message used to specify custom behavior, this must also be set in the Modelfile as an instruction. |
| `{{ .Prompt }}` | The incoming prompt, this is not specified in the model file and will be set based on input. |
| `{{ .Response }}` | The response from the LLM, if not specified response is appended to the end of the template. |
| `{{ .First }}` | A boolean value used to render specific template information for the first generation of a session. |
```
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
```modelfile
TEMPLATE """
{{- if .First }}
### System:
{{ .System }}
{{- end }}
### User:
{{ .Prompt }}
### Response:
"""
SYSTEM """<system message>"""
```
### SYSTEM
@@ -199,22 +205,9 @@ LICENSE """
"""
```
### MESSAGE
The `MESSAGE` instruction allows you to specify a message history for the model to use when responding:
```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
```
## Notes
- 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
[1]: https://ollama.ai/library

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@@ -1,141 +0,0 @@
# 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!"
}
]
}'
```

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@@ -12,13 +12,6 @@ On Linux systems with systemd, the logs can be found with this command:
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.
Join the [Discord](https://discord.gg/ollama) for help interpreting the logs.

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@@ -17,7 +17,7 @@ Prerequisites:
Here are the steps:
- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.com/install.sh | sh`
- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.ai/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'`

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@@ -8,7 +8,7 @@
"outputs": [],
"source": [
"# Download and run the Ollama Linux install script\n",
"!curl -fsSL https://ollama.com/install.sh | sh\n",
"!curl https://ollama.ai/install.sh | sh\n",
"!command -v systemctl >/dev/null && sudo systemctl stop ollama"
]
},

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@@ -2,28 +2,28 @@
## Prerequisites
- Ollama: https://ollama.com/download
- Ollama: https://ollama.ai/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
```
```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
```
```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
```
```bash
ollama run orca-mini:3b
```
## (Optional) Hardware Acceleration

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@@ -1,6 +1,6 @@
# LangChain Web Summarization
This example summarizes the website, [https://ollama.com/blog/run-llama2-uncensored-locally](https://ollama.com/blog/run-llama2-uncensored-locally)
This example summarizes the website, [https://ollama.ai/blog/run-llama2-uncensored-locally](https://ollama.ai/blog/run-llama2-uncensored-locally)
## Running the Example

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@@ -2,7 +2,7 @@ from langchain.llms import Ollama
from langchain.document_loaders import WebBaseLoader
from langchain.chains.summarize import load_summarize_chain
loader = WebBaseLoader("https://ollama.com/blog/run-llama2-uncensored-locally")
loader = WebBaseLoader("https://ollama.ai/blog/run-llama2-uncensored-locally")
docs = loader.load()
llm = Ollama(model="llama2")

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@@ -40,13 +40,13 @@ You are a log file analyzer. You will receive a set of lines from a log file for
"""
```
This model is available at https://ollama.com/mattw/loganalyzer. You can customize it and add to your own namespace using the command `ollama create <namespace/modelname> -f <path-to-modelfile>` then `ollama push <namespace/modelname>`.
This model is available at https://ollama.ai/mattw/loganalyzer. You can customize it and add to your own namespace using the command `ollama create <namespace/modelname> -f <path-to-modelfile>` then `ollama push <namespace/modelname>`.
Then loganalysis.py scans all the lines in the given log file and searches for the word 'error'. When the word is found, the 10 lines before and after are set as the prompt for a call to the Generate API.
```python
data = {
"prompt": "\n".join(error_logs),
"prompt": "\n".join(error_logs),
"model": "mattw/loganalyzer"
}
```

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@@ -29,9 +29,9 @@ You can also add your own character to be chosen at random when you ask a questi
```bash
ollama pull stablebeluga2:70b-q4_K_M
```
2. Create a new character:
```bash
npm run charactergen "Lorne Greene"
```
@@ -41,15 +41,15 @@ You can also add your own character to be chosen at random when you ask a questi
3. Now you can create a model with this command:
```bash
ollama create <username>/lornegreene -f lornegreene/Modelfile
ollama create <YourNamespace>/lornegreene -f lornegreene/Modelfile
```
`username` is whatever name you set up when you signed up at [https://ollama.com/signup](https://ollama.com/signup).
`YourNamespace` is whatever name you set up when you signed up at [https://ollama.ai/signup](https://ollama.ai/signup).
4. To add this to your mentors, you will have to update the code as follows. On line 8 of `mentors.ts`, add an object to the array, replacing `<username>` with the username you used above.
4. To add this to your mentors, you will have to update the code as follows. On line 8 of `mentors.ts`, add an object to the array, replacing `<YourNamespace>` with the namespace you used above.
```bash
{ns: "<username>", char: "Lorne Greene"}
{ns: "<YourNamespace>", char: "Lorne Greene"}
```
## Review the Code

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@@ -1,91 +0,0 @@
package gpu
import (
"bufio"
"fmt"
"io"
"log/slog"
"os"
"path/filepath"
"strconv"
"strings"
)
// TODO - windows vs. non-windows vs darwin
// Discovery logic for AMD/ROCm GPUs
const (
DriverVersionFile = "/sys/module/amdgpu/version"
GPUPropertiesFileGlob = "/sys/class/kfd/kfd/topology/nodes/*/properties"
// TODO probably break these down per GPU to make the logic simpler
GPUTotalMemoryFileGlob = "/sys/class/kfd/kfd/topology/nodes/*/mem_banks/*/properties" // size_in_bytes line
GPUUsedMemoryFileGlob = "/sys/class/kfd/kfd/topology/nodes/*/mem_banks/*/used_memory"
)
func AMDDetected() bool {
_, err := AMDDriverVersion()
return err == nil
}
func AMDDriverVersion() (string, error) {
_, err := os.Stat(DriverVersionFile)
if err != nil {
return "", err
}
fp, err := os.Open(DriverVersionFile)
if err != nil {
return "", err
}
defer fp.Close()
verString, err := io.ReadAll(fp)
if err != nil {
return "", err
}
return strings.TrimSpace(string(verString)), nil
}
func AMDGFXVersions() []Version {
res := []Version{}
matches, _ := filepath.Glob(GPUPropertiesFileGlob)
for _, match := range matches {
fp, err := os.Open(match)
if err != nil {
slog.Debug(fmt.Sprintf("failed to open sysfs node file %s: %s", match, err))
continue
}
defer fp.Close()
scanner := bufio.NewScanner(fp)
// optionally, resize scanner's capacity for lines over 64K, see next example
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
if strings.HasPrefix(line, "gfx_target_version") {
ver := strings.Fields(line)
if len(ver) != 2 || len(ver[1]) < 5 {
slog.Debug("malformed " + line)
continue
}
l := len(ver[1])
patch, err1 := strconv.ParseUint(ver[1][l-2:l], 10, 32)
minor, err2 := strconv.ParseUint(ver[1][l-4:l-2], 10, 32)
major, err3 := strconv.ParseUint(ver[1][:l-4], 10, 32)
if err1 != nil || err2 != nil || err3 != nil {
slog.Debug("malformed int " + line)
continue
}
res = append(res, Version{
Major: uint(major),
Minor: uint(minor),
Patch: uint(patch),
})
}
}
}
return res
}
func (v Version) ToGFXString() string {
return fmt.Sprintf("gfx%d%d%d", v.Major, v.Minor, v.Patch)
}

View File

@@ -16,7 +16,6 @@ import (
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"sync"
"unsafe"
@@ -30,8 +29,8 @@ type handles struct {
var gpuMutex sync.Mutex
var gpuHandles *handles = nil
// With our current CUDA compile flags, older than 5.0 will not work properly
var CudaComputeMin = [2]C.int{5, 0}
// With our current CUDA compile flags, 5.2 and older will not work properly
const CudaComputeMajorMin = 6
// Possible locations for the nvidia-ml library
var CudaLinuxGlobs = []string{
@@ -39,15 +38,12 @@ var CudaLinuxGlobs = []string{
"/usr/lib/x86_64-linux-gnu/nvidia/current/libnvidia-ml.so*",
"/usr/lib/x86_64-linux-gnu/libnvidia-ml.so*",
"/usr/lib/wsl/lib/libnvidia-ml.so*",
"/usr/lib/wsl/drivers/*/libnvidia-ml.so*",
"/opt/cuda/lib64/libnvidia-ml.so*",
"/opt/cuda/targets/x86_64-linux/lib/stubs/libnvidia-ml.so*",
"/usr/lib*/libnvidia-ml.so*",
"/usr/local/lib*/libnvidia-ml.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libnvidia-ml.so*",
"/usr/lib/aarch64-linux-gnu/libnvidia-ml.so*",
// TODO: are these stubs ever valid?
"/opt/cuda/targets/x86_64-linux/lib/stubs/libnvidia-ml.so*",
}
var CudaWindowsGlobs = []string{
@@ -122,96 +118,49 @@ func GetGPUInfo() GpuInfo {
initGPUHandles()
}
// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
cpuVariant := GetCPUVariant()
if cpuVariant == "" && runtime.GOARCH == "amd64" {
slog.Warn("CPU does not have AVX or AVX2, disabling GPU support.")
}
var memInfo C.mem_info_t
resp := GpuInfo{}
if gpuHandles.cuda != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
if gpuHandles.cuda != nil {
C.cuda_check_vram(*gpuHandles.cuda, &memInfo)
if memInfo.err != nil {
slog.Info(fmt.Sprintf("error looking up CUDA GPU memory: %s", C.GoString(memInfo.err)))
C.free(unsafe.Pointer(memInfo.err))
} else if memInfo.count > 0 {
} else {
// Verify minimum compute capability
var cc C.cuda_compute_capability_t
C.cuda_compute_capability(*gpuHandles.cuda, &cc)
if cc.err != nil {
slog.Info(fmt.Sprintf("error looking up CUDA GPU compute capability: %s", C.GoString(cc.err)))
C.free(unsafe.Pointer(cc.err))
} else if cc.major > CudaComputeMin[0] || (cc.major == CudaComputeMin[0] && cc.minor >= CudaComputeMin[1]) {
} else if cc.major >= CudaComputeMajorMin {
slog.Info(fmt.Sprintf("CUDA Compute Capability detected: %d.%d", cc.major, cc.minor))
resp.Library = "cuda"
} else {
slog.Info(fmt.Sprintf("CUDA GPU is too old. Falling back to CPU mode. Compute Capability detected: %d.%d", cc.major, cc.minor))
}
}
} else if AMDDetected() && gpuHandles.rocm != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
ver, err := AMDDriverVersion()
if err == nil {
slog.Info("AMD Driver: " + ver)
}
gfx := AMDGFXVersions()
tooOld := false
for _, v := range gfx {
if v.Major < 9 {
slog.Info("AMD GPU too old, falling back to CPU " + v.ToGFXString())
tooOld = true
break
}
// TODO - remap gfx strings for unsupporetd minor/patch versions to supported for the same major
// e.g. gfx1034 works if we map it to gfx1030 at runtime
}
if !tooOld {
// TODO - this algo can be shifted over to use sysfs instead of the rocm info library...
C.rocm_check_vram(*gpuHandles.rocm, &memInfo)
if memInfo.err != nil {
slog.Info(fmt.Sprintf("error looking up ROCm GPU memory: %s", C.GoString(memInfo.err)))
C.free(unsafe.Pointer(memInfo.err))
} else if memInfo.igpu_index >= 0 && memInfo.count == 1 {
// Only one GPU detected and it appears to be an integrated GPU - skip it
slog.Info("ROCm unsupported integrated GPU detected")
} else if memInfo.count > 0 {
if memInfo.igpu_index >= 0 {
// We have multiple GPUs reported, and one of them is an integrated GPU
// so we have to set the env var to bypass it
// If the user has specified their own ROCR_VISIBLE_DEVICES, don't clobber it
val := os.Getenv("ROCR_VISIBLE_DEVICES")
if val == "" {
devices := []string{}
for i := 0; i < int(memInfo.count); i++ {
if i == int(memInfo.igpu_index) {
continue
}
devices = append(devices, strconv.Itoa(i))
}
val = strings.Join(devices, ",")
os.Setenv("ROCR_VISIBLE_DEVICES", val)
}
slog.Info(fmt.Sprintf("ROCm integrated GPU detected - ROCR_VISIBLE_DEVICES=%s", val))
}
resp.Library = "rocm"
var version C.rocm_version_resp_t
C.rocm_get_version(*gpuHandles.rocm, &version)
verString := C.GoString(version.str)
if version.status == 0 {
resp.Variant = "v" + verString
} else {
slog.Info(fmt.Sprintf("failed to look up ROCm version: %s", verString))
}
C.free(unsafe.Pointer(version.str))
} else if gpuHandles.rocm != nil {
C.rocm_check_vram(*gpuHandles.rocm, &memInfo)
if memInfo.err != nil {
slog.Info(fmt.Sprintf("error looking up ROCm GPU memory: %s", C.GoString(memInfo.err)))
C.free(unsafe.Pointer(memInfo.err))
} else {
resp.Library = "rocm"
var version C.rocm_version_resp_t
C.rocm_get_version(*gpuHandles.rocm, &version)
verString := C.GoString(version.str)
if version.status == 0 {
resp.Variant = "v" + verString
} else {
slog.Info(fmt.Sprintf("failed to look up ROCm version: %s", verString))
}
C.free(unsafe.Pointer(version.str))
}
}
if resp.Library == "" {
C.cpu_check_ram(&memInfo)
resp.Library = "cpu"
resp.Variant = cpuVariant
resp.Variant = GetCPUVariant()
}
if memInfo.err != nil {
slog.Info(fmt.Sprintf("error looking up CPU memory: %s", C.GoString(memInfo.err)))
@@ -241,15 +190,7 @@ func getCPUMem() (memInfo, error) {
func CheckVRAM() (int64, error) {
gpuInfo := GetGPUInfo()
if gpuInfo.FreeMemory > 0 && (gpuInfo.Library == "cuda" || gpuInfo.Library == "rocm") {
// leave 10% or 1024MiB of VRAM free per GPU to handle unaccounted for overhead
overhead := gpuInfo.FreeMemory / 10
gpus := uint64(gpuInfo.DeviceCount)
if overhead < gpus*1024*1024*1024 {
overhead = gpus * 1024 * 1024 * 1024
}
avail := int64(gpuInfo.FreeMemory - overhead)
slog.Debug(fmt.Sprintf("%s detected %d devices with %dM available memory", gpuInfo.Library, gpuInfo.DeviceCount, avail/1024/1024))
return avail, nil
return int64(gpuInfo.FreeMemory), nil
}
return 0, fmt.Errorf("no GPU detected") // TODO - better handling of CPU based memory determiniation
@@ -311,7 +252,6 @@ func FindGPULibs(baseLibName string, patterns []string) []string {
func LoadCUDAMgmt(cudaLibPaths []string) *C.cuda_handle_t {
var resp C.cuda_init_resp_t
resp.ch.verbose = getVerboseState()
for _, libPath := range cudaLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
@@ -328,7 +268,6 @@ func LoadCUDAMgmt(cudaLibPaths []string) *C.cuda_handle_t {
func LoadROCMMgmt(rocmLibPaths []string) *C.rocm_handle_t {
var resp C.rocm_init_resp_t
resp.rh.verbose = getVerboseState()
for _, libPath := range rocmLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
@@ -342,10 +281,3 @@ func LoadROCMMgmt(rocmLibPaths []string) *C.rocm_handle_t {
}
return nil
}
func getVerboseState() C.uint16_t {
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
return C.uint16_t(1)
}
return C.uint16_t(0)
}

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@@ -27,13 +27,6 @@
#endif
#define LOG(verbose, ...) \
do { \
if (verbose) { \
fprintf(stderr, __VA_ARGS__); \
} \
} while (0)
#ifdef __cplusplus
extern "C" {
#endif
@@ -42,7 +35,6 @@ typedef struct mem_info {
uint64_t total;
uint64_t free;
unsigned int count;
int igpu_index; // If >= 0, we detected an integrated GPU to ignore
char *err; // If non-nill, caller responsible for freeing
} mem_info_t;

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@@ -4,6 +4,8 @@
#include <string.h>
#define CUDA_LOOKUP_SIZE 6
void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
nvmlReturn_t ret;
resp->err = NULL;
@@ -14,26 +16,18 @@ void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
struct lookup {
char *s;
void **p;
} l[] = {
{"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
{"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
{"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
{"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
{"nvmlDeviceGetCount_v2", (void *)&resp->ch.nvmlDeviceGetCount_v2},
{"nvmlDeviceGetCudaComputeCapability", (void *)&resp->ch.nvmlDeviceGetCudaComputeCapability},
{"nvmlSystemGetDriverVersion", (void *)&resp->ch.nvmlSystemGetDriverVersion},
{"nvmlDeviceGetName", (void *)&resp->ch.nvmlDeviceGetName},
{"nvmlDeviceGetSerial", (void *)&resp->ch.nvmlDeviceGetSerial},
{"nvmlDeviceGetVbiosVersion", (void *)&resp->ch.nvmlDeviceGetVbiosVersion},
{"nvmlDeviceGetBoardPartNumber", (void *)&resp->ch.nvmlDeviceGetBoardPartNumber},
{"nvmlDeviceGetBrand", (void *)&resp->ch.nvmlDeviceGetBrand},
{NULL, NULL},
} l[CUDA_LOOKUP_SIZE] = {
{"nvmlInit_v2", (void *)&resp->ch.initFn},
{"nvmlShutdown", (void *)&resp->ch.shutdownFn},
{"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.getHandle},
{"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.getMemInfo},
{"nvmlDeviceGetCount_v2", (void *)&resp->ch.getCount},
{"nvmlDeviceGetCudaComputeCapability", (void *)&resp->ch.getComputeCapability},
};
resp->ch.handle = LOAD_LIBRARY(cuda_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", cuda_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
cuda_lib_path, msg);
@@ -42,19 +36,12 @@ void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
return;
}
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", cuda_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
for (i = 0; i < CUDA_LOOKUP_SIZE; i++) { // TODO - fix this to use a null terminated list
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!l[i].p) {
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
@@ -63,23 +50,15 @@ void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
}
}
ret = (*resp->ch.nvmlInit_v2)();
ret = (*resp->ch.initFn)();
if (ret != NVML_SUCCESS) {
LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "nvml vram init failure: %d", ret);
resp->err = strdup(buf);
return;
}
// Report driver version if we're in verbose mode, ignore errors
ret = (*resp->ch.nvmlSystemGetDriverVersion)(buf, buflen);
if (ret != NVML_SUCCESS) {
LOG(resp->ch.verbose, "nvmlSystemGetDriverVersion failed: %d\n", ret);
} else {
LOG(resp->ch.verbose, "CUDA driver version: %s\n", buf);
}
return;
}
void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
@@ -96,7 +75,7 @@ void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
return;
}
ret = (*h.nvmlDeviceGetCount_v2)(&resp->count);
ret = (*h.getCount)(&resp->count);
if (ret != NVML_SUCCESS) {
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
@@ -106,57 +85,19 @@ void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
resp->total = 0;
resp->free = 0;
for (i = 0; i < resp->count; i++) {
ret = (*h.nvmlDeviceGetHandleByIndex)(i, &device);
ret = (*h.getHandle)(i, &device);
if (ret != NVML_SUCCESS) {
snprintf(buf, buflen, "unable to get device handle %d: %d", i, ret);
resp->err = strdup(buf);
return;
}
ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
ret = (*h.getMemInfo)(device, &memInfo);
if (ret != NVML_SUCCESS) {
snprintf(buf, buflen, "device memory info lookup failure %d: %d", i, ret);
resp->err = strdup(buf);
return;
}
if (h.verbose) {
nvmlBrandType_t brand = 0;
// When in verbose mode, report more information about
// the card we discover, but don't fail on error
ret = (*h.nvmlDeviceGetName)(device, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "nvmlDeviceGetName failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] CUDA device name: %s\n", i, buf);
}
ret = (*h.nvmlDeviceGetBoardPartNumber)(device, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "nvmlDeviceGetBoardPartNumber failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] CUDA part number: %s\n", i, buf);
}
ret = (*h.nvmlDeviceGetSerial)(device, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "nvmlDeviceGetSerial failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] CUDA S/N: %s\n", i, buf);
}
ret = (*h.nvmlDeviceGetVbiosVersion)(device, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "nvmlDeviceGetVbiosVersion failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] CUDA vbios version: %s\n", i, buf);
}
ret = (*h.nvmlDeviceGetBrand)(device, &brand);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "nvmlDeviceGetBrand failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] CUDA brand: %d\n", i, brand);
}
}
LOG(h.verbose, "[%d] CUDA totalMem %ld\n", i, memInfo.total);
LOG(h.verbose, "[%d] CUDA usedMem %ld\n", i, memInfo.free);
resp->total += memInfo.total;
resp->free += memInfo.free;
@@ -181,7 +122,7 @@ void cuda_compute_capability(cuda_handle_t h, cuda_compute_capability_t *resp) {
}
unsigned int devices;
ret = (*h.nvmlDeviceGetCount_v2)(&devices);
ret = (*h.getCount)(&devices);
if (ret != NVML_SUCCESS) {
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
@@ -189,14 +130,14 @@ void cuda_compute_capability(cuda_handle_t h, cuda_compute_capability_t *resp) {
}
for (i = 0; i < devices; i++) {
ret = (*h.nvmlDeviceGetHandleByIndex)(i, &device);
ret = (*h.getHandle)(i, &device);
if (ret != NVML_SUCCESS) {
snprintf(buf, buflen, "unable to get device handle %d: %d", i, ret);
resp->err = strdup(buf);
return;
}
ret = (*h.nvmlDeviceGetCudaComputeCapability)(device, &major, &minor);
ret = (*h.getComputeCapability)(device, &major, &minor);
if (ret != NVML_SUCCESS) {
snprintf(buf, buflen, "device compute capability lookup failure %d: %d", i, ret);
resp->err = strdup(buf);

View File

@@ -15,26 +15,14 @@ typedef struct nvmlMemory_st {
unsigned long long used;
} nvmlMemory_t;
typedef enum nvmlBrandType_enum
{
NVML_BRAND_UNKNOWN = 0,
} nvmlBrandType_t;
typedef struct cuda_handle {
void *handle;
uint16_t verbose;
nvmlReturn_t (*nvmlInit_v2)(void);
nvmlReturn_t (*nvmlShutdown)(void);
nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
nvmlReturn_t (*nvmlDeviceGetCount_v2)(unsigned int *);
nvmlReturn_t (*nvmlDeviceGetCudaComputeCapability)(nvmlDevice_t, int* major, int* minor);
nvmlReturn_t (*nvmlSystemGetDriverVersion) (char* version, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetName) (nvmlDevice_t device, char* name, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetSerial) (nvmlDevice_t device, char* serial, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetVbiosVersion) (nvmlDevice_t device, char* version, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetBoardPartNumber) (nvmlDevice_t device, char* partNumber, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetBrand) (nvmlDevice_t device, nvmlBrandType_t* type);
nvmlReturn_t (*initFn)(void);
nvmlReturn_t (*shutdownFn)(void);
nvmlReturn_t (*getHandle)(unsigned int, nvmlDevice_t *);
nvmlReturn_t (*getMemInfo)(nvmlDevice_t, nvmlMemory_t *);
nvmlReturn_t (*getCount)(unsigned int *);
nvmlReturn_t (*getComputeCapability)(nvmlDevice_t, int* major, int* minor);
} cuda_handle_t;
typedef struct cuda_init_resp {

View File

@@ -4,6 +4,8 @@
#include <string.h>
#define ROCM_LOOKUP_SIZE 5
void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp) {
rsmi_status_t ret;
resp->err = NULL;
@@ -13,22 +15,13 @@ void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp) {
struct lookup {
char *s;
void **p;
} l[] = {
{"rsmi_init", (void *)&resp->rh.rsmi_init},
{"rsmi_shut_down", (void *)&resp->rh.rsmi_shut_down},
{"rsmi_dev_memory_total_get", (void *)&resp->rh.rsmi_dev_memory_total_get},
{"rsmi_dev_memory_usage_get", (void *)&resp->rh.rsmi_dev_memory_usage_get},
{"rsmi_version_get", (void *)&resp->rh.rsmi_version_get},
{"rsmi_num_monitor_devices", (void*)&resp->rh.rsmi_num_monitor_devices},
{"rsmi_dev_id_get", (void*)&resp->rh.rsmi_dev_id_get},
{"rsmi_dev_name_get", (void *)&resp->rh.rsmi_dev_name_get},
{"rsmi_dev_brand_get", (void *)&resp->rh.rsmi_dev_brand_get},
{"rsmi_dev_vendor_name_get", (void *)&resp->rh.rsmi_dev_vendor_name_get},
{"rsmi_dev_vram_vendor_get", (void *)&resp->rh.rsmi_dev_vram_vendor_get},
{"rsmi_dev_serial_number_get", (void *)&resp->rh.rsmi_dev_serial_number_get},
{"rsmi_dev_subsystem_name_get", (void *)&resp->rh.rsmi_dev_subsystem_name_get},
{"rsmi_dev_vbios_version_get", (void *)&resp->rh.rsmi_dev_vbios_version_get},
{NULL, NULL},
} l[ROCM_LOOKUP_SIZE] = {
{"rsmi_init", (void *)&resp->rh.initFn},
{"rsmi_shut_down", (void *)&resp->rh.shutdownFn},
{"rsmi_dev_memory_total_get", (void *)&resp->rh.totalMemFn},
{"rsmi_dev_memory_usage_get", (void *)&resp->rh.usageMemFn},
{"rsmi_version_get", (void *)&resp->rh.versionGetFn},
// { "rsmi_dev_id_get", (void*)&resp->rh.getHandle },
};
resp->rh.handle = LOAD_LIBRARY(rocm_lib_path, RTLD_LAZY);
@@ -42,19 +35,12 @@ void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp) {
return;
}
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->rh.verbose, "wiring rocm management library functions in %s\n", rocm_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->rh.verbose, "dlsym: %s\n", l[i].s);
for (i = 0; i < ROCM_LOOKUP_SIZE; i++) {
*l[i].p = LOAD_SYMBOL(resp->rh.handle, l[i].s);
if (!l[i].p) {
UNLOAD_LIBRARY(resp->rh.handle);
resp->rh.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->rh.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->rh.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
@@ -63,9 +49,8 @@ void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp) {
}
}
ret = (*resp->rh.rsmi_init)(0);
ret = (*resp->rh.initFn)(0);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(resp->rh.verbose, "rsmi_init err: %d\n", ret);
UNLOAD_LIBRARY(resp->rh.handle);
resp->rh.handle = NULL;
snprintf(buf, buflen, "rocm vram init failure: %d", ret);
@@ -77,7 +62,8 @@ void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp) {
void rocm_check_vram(rocm_handle_t h, mem_info_t *resp) {
resp->err = NULL;
resp->igpu_index = -1;
// uint32_t num_devices;
// uint16_t device;
uint64_t totalMem = 0;
uint64_t usedMem = 0;
rsmi_status_t ret;
@@ -90,101 +76,47 @@ void rocm_check_vram(rocm_handle_t h, mem_info_t *resp) {
return;
}
ret = (*h.rsmi_num_monitor_devices)(&resp->count);
// TODO - iterate through devices... ret =
// rsmi_num_monitor_devices(&num_devices);
// ret = (*h.getHandle)(0, &device);
// if (ret != RSMI_STATUS_SUCCESS) {
// printf("rocm vram device lookup failure: %d\n", ret);
// return -1;
// }
// Get total memory - used memory for available memory
ret = (*h.totalMemFn)(0, RSMI_MEM_TYPE_VRAM, &totalMem);
if (ret != RSMI_STATUS_SUCCESS) {
snprintf(buf, buflen, "unable to get device count: %d", ret);
snprintf(buf, buflen, "rocm total mem lookup failure: %d", ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d ROCm GPU Devices\n", resp->count);
resp->total = 0;
resp->free = 0;
for (i = 0; i < resp->count; i++) {
if (h.verbose) {
// When in verbose mode, report more information about
// the card we discover, but don't fail on error
ret = (*h.rsmi_dev_name_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_name_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm device name: %s\n", i, buf);
}
ret = (*h.rsmi_dev_brand_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_brand_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm brand: %s\n", i, buf);
}
ret = (*h.rsmi_dev_vendor_name_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_vendor_name_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm vendor: %s\n", i, buf);
}
ret = (*h.rsmi_dev_vram_vendor_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_vram_vendor_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm VRAM vendor: %s\n", i, buf);
}
ret = (*h.rsmi_dev_serial_number_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_serial_number_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm S/N: %s\n", i, buf);
}
ret = (*h.rsmi_dev_subsystem_name_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_subsystem_name_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm subsystem name: %s\n", i, buf);
}
ret = (*h.rsmi_dev_vbios_version_get)(i, buf, buflen);
if (ret != RSMI_STATUS_SUCCESS) {
LOG(h.verbose, "rsmi_dev_vbios_version_get failed: %d\n", ret);
} else {
LOG(h.verbose, "[%d] ROCm vbios version: %s\n", i, buf);
}
}
// Get total memory - used memory for available memory
ret = (*h.rsmi_dev_memory_total_get)(i, RSMI_MEM_TYPE_VRAM, &totalMem);
if (ret != RSMI_STATUS_SUCCESS) {
snprintf(buf, buflen, "rocm total mem lookup failure: %d", ret);
resp->err = strdup(buf);
return;
}
ret = (*h.rsmi_dev_memory_usage_get)(i, RSMI_MEM_TYPE_VRAM, &usedMem);
if (ret != RSMI_STATUS_SUCCESS) {
snprintf(buf, buflen, "rocm usage mem lookup failure: %d", ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "[%d] ROCm totalMem %ld\n", i, totalMem);
LOG(h.verbose, "[%d] ROCm usedMem %ld\n", i, usedMem);
if (totalMem < 1024 * 1024 * 1024) {
// Do not add up integrated GPU memory capacity, it's a bogus 512M, and actually uses system memory
LOG(h.verbose, "[%d] ROCm integrated GPU\n", i);
resp->igpu_index = i;
} else {
resp->total += totalMem;
resp->free += totalMem - usedMem;
}
ret = (*h.usageMemFn)(0, RSMI_MEM_TYPE_VRAM, &usedMem);
if (ret != RSMI_STATUS_SUCCESS) {
snprintf(buf, buflen, "rocm usage mem lookup failure: %d", ret);
resp->err = strdup(buf);
return;
}
// TODO: set this to the actual number of devices
resp->count = 1;
resp->total = totalMem;
resp->free = totalMem - usedMem;
return;
}
void rocm_get_version(rocm_handle_t h, rocm_version_resp_t *resp) {
const int buflen = 256;
char buf[buflen + 1];
if (h.handle == NULL) {
resp->str = strdup("rocm handle not initialized");
resp->str = strdup("nvml handle not initialized");
resp->status = 1;
return;
}
rsmi_version_t ver;
rsmi_status_t ret;
ret = h.rsmi_version_get(&ver);
ret = h.versionGetFn(&ver);
if (ret != RSMI_STATUS_SUCCESS) {
snprintf(buf, buflen, "unexpected response on version lookup %d", ret);
resp->status = 1;
@@ -195,4 +127,4 @@ void rocm_get_version(rocm_handle_t h, rocm_version_resp_t *resp) {
resp->str = strdup(buf);
}
#endif // __APPLE__
#endif // __APPLE__

View File

@@ -24,21 +24,12 @@ typedef enum rsmi_memory_type {
typedef struct rocm_handle {
void *handle;
uint16_t verbose;
rsmi_status_t (*rsmi_init)(uint64_t);
rsmi_status_t (*rsmi_shut_down)(void);
rsmi_status_t (*rsmi_dev_memory_total_get)(uint32_t, rsmi_memory_type_t, uint64_t *);
rsmi_status_t (*rsmi_dev_memory_usage_get)(uint32_t, rsmi_memory_type_t, uint64_t *);
rsmi_status_t (*rsmi_version_get) (rsmi_version_t *version);
rsmi_status_t (*rsmi_num_monitor_devices) (uint32_t *);
rsmi_status_t (*rsmi_dev_id_get)(uint32_t, uint16_t *);
rsmi_status_t (*rsmi_dev_name_get) (uint32_t,char *,size_t);
rsmi_status_t (*rsmi_dev_brand_get) (uint32_t, char *, uint32_t);
rsmi_status_t (*rsmi_dev_vendor_name_get) (uint32_t, char *, uint32_t);
rsmi_status_t (*rsmi_dev_vram_vendor_get) (uint32_t, char *, uint32_t);
rsmi_status_t (*rsmi_dev_serial_number_get) (uint32_t, char *, uint32_t);
rsmi_status_t (*rsmi_dev_subsystem_name_get) (uint32_t, char *, uint32_t);
rsmi_status_t (*rsmi_dev_vbios_version_get) (uint32_t, char *, uint32_t);
rsmi_status_t (*initFn)(uint64_t);
rsmi_status_t (*shutdownFn)(void);
rsmi_status_t (*totalMemFn)(uint32_t, rsmi_memory_type_t, uint64_t *);
rsmi_status_t (*usageMemFn)(uint32_t, rsmi_memory_type_t, uint64_t *);
rsmi_status_t (*versionGetFn) (rsmi_version_t *version);
// rsmi_status_t (*getHandle)(uint32_t, uint16_t *);
} rocm_handle_t;
typedef struct rocm_init_resp {

View File

@@ -16,9 +16,3 @@ type GpuInfo struct {
// TODO add other useful attributes about the card here for discovery information
}
type Version struct {
Major uint
Minor uint
Patch uint
}

View File

@@ -59,7 +59,7 @@ void dyn_init(const char *libPath, struct dynamic_llama_server *s,
};
printf("loading library %s\n", libPath);
s->handle = LOAD_LIBRARY(libPath, RTLD_LOCAL|RTLD_NOW);
s->handle = LOAD_LIBRARY(libPath, RTLD_GLOBAL|RTLD_NOW);
if (!s->handle) {
err->id = -1;
char *msg = LOAD_ERR();

View File

@@ -4,7 +4,7 @@ package llm
#cgo CFLAGS: -I${SRCDIR}/ext_server -I${SRCDIR}/llama.cpp -I${SRCDIR}/llama.cpp/common -I${SRCDIR}/llama.cpp/examples/server
#cgo CFLAGS: -DNDEBUG -DLLAMA_SERVER_LIBRARY=1 -D_XOPEN_SOURCE=600 -DACCELERATE_NEW_LAPACK -DACCELERATE_LAPACK_ILP64
#cgo CFLAGS: -Wmissing-noreturn -Wextra -Wcast-qual -Wno-unused-function -Wno-array-bounds
#cgo CPPFLAGS: -Ofast -Wextra -Wno-unused-function -Wno-unused-variable -Wno-deprecated-declarations
#cgo CPPFLAGS: -Ofast -Wextra -Wno-unused-function -Wno-unused-variable -Wno-deprecated-declarations -Wno-unused-but-set-variable
#cgo darwin CFLAGS: -D_DARWIN_C_SOURCE
#cgo darwin CPPFLAGS: -DGGML_USE_ACCELERATE
#cgo darwin CPPFLAGS: -DGGML_USE_METAL -DGGML_METAL_NDEBUG
@@ -136,21 +136,12 @@ func newDynExtServer(library, model string, adapters, projectors []string, opts
sparams.n_threads = C.uint(opts.NumThread)
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
sparams.verbose_logging = C.bool(true)
} else {
sparams.verbose_logging = C.bool(false)
}
slog.Info("Initializing llama server")
initResp := newExtServerResp(128)
defer freeExtServerResp(initResp)
C.dyn_llama_server_init(llm.s, &sparams, &initResp)
if initResp.id < 0 {
mutex.Unlock()
err := extServerResponseToErr(initResp)
slog.Debug(fmt.Sprintf("failure during initialization: %s", err))
return nil, err
return nil, extServerResponseToErr(initResp)
}
slog.Info("Starting llama main loop")
@@ -161,10 +152,13 @@ func newDynExtServer(library, model string, adapters, projectors []string, opts
func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn func(PredictResult)) error {
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
var imageData []ImageData
if len(predict.Images) > 0 {
slog.Info(fmt.Sprintf("loaded %d images", len(predict.Images)))
for cnt, i := range predict.Images {
imageData = append(imageData, ImageData{Data: i, ID: cnt})
}
}
slog.Info(fmt.Sprintf("loaded %d images", len(imageData)))
request := map[string]any{
"prompt": predict.Prompt,
@@ -186,8 +180,7 @@ func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn fu
"penalize_nl": predict.Options.PenalizeNewline,
"seed": predict.Options.Seed,
"stop": predict.Options.Stop,
"image_data": predict.Images,
"cache_prompt": true,
"image_data": imageData,
}
if predict.Format == "json" {
@@ -258,7 +251,7 @@ func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn fu
})
}
if p.Stop || bool(result.stop) {
if p.Stop {
fn(PredictResult{
Done: true,
PromptEvalCount: p.Timings.PromptN,

View File

@@ -1,63 +1,24 @@
#include "ext_server.h"
#include <atomic>
// Necessary evil since the server types are not defined in a header
#include "server.cpp"
// Low level API access to verify GPU access
#if defined(GGML_USE_CUBLAS)
#if defined(GGML_USE_HIPBLAS)
#include <hip/hip_runtime.h>
#include <hipblas/hipblas.h>
#include <hip/hip_fp16.h>
#ifdef __HIP_PLATFORM_AMD__
// for rocblas_initialize()
#include "rocblas/rocblas.h"
#endif // __HIP_PLATFORM_AMD__
#define cudaGetDevice hipGetDevice
#define cudaError_t hipError_t
#define cudaSuccess hipSuccess
#define cudaGetErrorString hipGetErrorString
#else
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cuda_fp16.h>
#endif // defined(GGML_USE_HIPBLAS)
#endif // GGML_USE_CUBLAS
// Expose the llama server as a callable extern "C" API
llama_server_context *llama = NULL;
std::atomic<bool> ext_server_running(false);
std::thread ext_server_thread;
bool shutting_down = false;
std::atomic_int recv_counter;
// RAII wrapper for tracking in-flight recv calls
class atomicRecv {
public:
atomicRecv(std::atomic<int> &atomic) : atomic(atomic) {
++this->atomic;
}
~atomicRecv() {
--this->atomic;
}
private:
std::atomic<int> &atomic;
};
void llama_server_init(ext_server_params *sparams, ext_server_resp_t *err) {
recv_counter = 0;
#if SERVER_VERBOSE != 1
log_disable();
#endif
LOG_TEE("system info: %s", llama_print_system_info());
assert(err != NULL && sparams != NULL);
log_set_target(stderr);
if (!sparams->verbose_logging) {
server_verbose = true;
log_disable();
}
LOG_TEE("system info: %s\n", llama_print_system_info());
err->id = 0;
err->msg[0] = '\0';
try {
llama = new llama_server_context;
log_set_target(stdout);
gpt_params params;
params.n_ctx = sparams->n_ctx;
params.n_batch = sparams->n_batch;
@@ -99,18 +60,6 @@ void llama_server_init(ext_server_params *sparams, ext_server_resp_t *err) {
params.mmproj = std::string(sparams->mmproj);
}
#if defined(GGML_USE_CUBLAS)
// Before attempting to init the backend which will assert on error, verify the CUDA/ROCM GPU is accessible
LOG_TEE("Performing pre-initialization of GPU\n");
int id;
cudaError_t cudaErr = cudaGetDevice(&id);
if (cudaErr != cudaSuccess) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unable to init GPU: %s", cudaGetErrorString(cudaErr));
return;
}
#endif
llama_backend_init(params.numa);
// load the model
@@ -139,23 +88,18 @@ void llama_server_start() {
assert(llama != NULL);
// TODO mutex to protect thread creation
ext_server_thread = std::thread([&]() {
ext_server_running = true;
try {
LOG_TEE("llama server main loop starting\n");
ggml_time_init();
llama->queue_tasks.on_new_task(std::bind(
&llama_server_context::process_single_task, llama, std::placeholders::_1));
llama->queue_tasks.on_finish_multitask(std::bind(
&llama_server_context::on_finish_multitask, llama, std::placeholders::_1));
llama->queue_tasks.on_all_tasks_finished(std::bind(
&llama_server_context::run_on_all_tasks_finished, llama));
llama->queue_results.on_multitask_update(std::bind(
&llama_server_queue::update_multitask,
&llama->queue_tasks,
std::placeholders::_1,
std::placeholders::_2,
std::placeholders::_3
));
llama->queue_tasks.start_loop();
while (ext_server_running.load()) {
if (!llama->update_slots()) {
LOG_TEE(
"unexpected error in llama server update_slots - exiting main "
"loop\n");
break;
}
}
} catch (std::exception &e) {
LOG_TEE("caught exception in llama server main loop: %s\n", e.what());
} catch (...) {
@@ -168,22 +112,17 @@ void llama_server_start() {
void llama_server_stop() {
assert(llama != NULL);
// Shutdown any in-flight requests and block incoming requests.
LOG_TEE("\ninitiating shutdown - draining remaining tasks...\n");
shutting_down = true;
// TODO - too verbose, remove once things are solid
LOG_TEE("requesting llama server shutdown\n");
ext_server_running = false;
while (recv_counter.load() > 0) {
std::this_thread::sleep_for(std::chrono::milliseconds(50));
}
// unblocks the update_slots() loop so it can clean up and exit
llama->request_cancel(0);
// This may take a while for any pending tasks to drain
// TODO - consider a timeout to cancel tasks if it's taking too long
llama->queue_tasks.terminate();
ext_server_thread.join();
delete llama;
llama = NULL;
LOG_TEE("llama server shutdown complete\n");
shutting_down = false;
}
void llama_server_completion(const char *json_req, ext_server_resp_t *resp) {
@@ -191,13 +130,8 @@ void llama_server_completion(const char *json_req, ext_server_resp_t *resp) {
resp->id = -1;
resp->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
json data = json::parse(json_req);
resp->id = llama->queue_tasks.get_new_id();
llama->queue_results.add_waiting_task_id(resp->id);
llama->request_completion(resp->id, data, false, false, -1);
resp->id = llama->request_completion(data, false, false, -1);
} catch (std::exception &e) {
snprintf(resp->msg, resp->msg_len, "exception %s", e.what());
} catch (...) {
@@ -215,28 +149,16 @@ void llama_server_completion_next_result(const int task_id,
resp->json_resp = NULL;
std::string result_json;
try {
atomicRecv ar(recv_counter);
task_result result = llama->queue_results.recv(task_id);
task_result result = llama->next_result(task_id);
result_json =
result.result_json.dump(-1, ' ', false, json::error_handler_t::replace);
resp->id = result.id;
resp->stop = result.stop;
resp->error = result.error;
if (result.error) {
LOG_TEE("next result cancel on error\n");
llama->request_cancel(task_id);
LOG_TEE("next result removing waiting tak ID: %d\n", task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} else if (result.stop) {
LOG_TEE("next result cancel on stop\n");
llama->request_cancel(task_id);
LOG_TEE("next result removing waiting task ID: %d\n", task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} else if (shutting_down) {
LOG_TEE("aborting completion due to shutdown %d\n", task_id);
llama->request_cancel(task_id);
llama->queue_results.remove_waiting_task_id(task_id);
resp->stop = true;
}
} catch (std::exception &e) {
resp->error = true;
@@ -267,7 +189,6 @@ void llama_server_completion_cancel(const int task_id, ext_server_resp_t *err) {
err->msg[0] = '\0';
try {
llama->request_cancel(task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
@@ -285,9 +206,6 @@ void llama_server_tokenize(const char *json_req, char **json_resp,
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
std::vector<llama_token> tokens;
if (body.count("content") != 0) {
@@ -321,9 +239,6 @@ void llama_server_detokenize(const char *json_req, char **json_resp,
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
std::string content;
if (body.count("tokens") != 0) {
@@ -351,9 +266,6 @@ void llama_server_embedding(const char *json_req, char **json_resp,
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
json prompt;
if (body.count("content") != 0) {
@@ -361,16 +273,13 @@ void llama_server_embedding(const char *json_req, char **json_resp,
} else {
prompt = "";
}
const int task_id = llama->queue_tasks.get_new_id();
llama->queue_results.add_waiting_task_id(task_id);
llama->request_completion(task_id, {{"prompt", prompt}, {"n_predict", 0}}, false, true, -1);
atomicRecv ar(recv_counter);
task_result result = llama->queue_results.recv(task_id);
const int task_id = llama->request_completion(
{{"prompt", prompt}, {"n_predict", 0}}, false, true, -1);
task_result result = llama->next_result(task_id);
std::string result_json = result.result_json.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
llama->queue_results.remove_waiting_task_id(task_id);
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());

View File

@@ -45,7 +45,6 @@ typedef struct ext_server_params {
bool embedding; // get only sentence embedding
ext_server_lora_adapter_t *lora_adapters;
char *mmproj;
bool verbose_logging; // Enable verbose logging of the server
} ext_server_params_t;
typedef struct ext_server_task_result {

View File

@@ -39,9 +39,6 @@ init_vars() {
*)
;;
esac
if [ -z "${CMAKE_CUDA_ARCHITECTURES}" ] ; then
CMAKE_CUDA_ARCHITECTURES="50;52;61;70;75;80"
fi
}
git_module_setup() {
@@ -64,19 +61,6 @@ apply_patches() {
if ! grep ollama ${LLAMACPP_DIR}/examples/server/CMakeLists.txt; then
echo 'include (../../../ext_server/CMakeLists.txt) # ollama' >>${LLAMACPP_DIR}/examples/server/CMakeLists.txt
fi
if [ -n "$(ls -A ../patches/*.diff)" ]; then
# apply temporary patches until fix is upstream
for patch in ../patches/*.diff; do
for file in $(grep "^+++ " ${patch} | cut -f2 -d' ' | cut -f2- -d/); do
(cd ${LLAMACPP_DIR}; git checkout ${file})
done
done
for patch in ../patches/*.diff; do
(cd ${LLAMACPP_DIR} && git apply ${patch})
done
fi
# Avoid duplicate main symbols when we link into the cgo binary
sed -e 's/int main(/int __main(/g' <${LLAMACPP_DIR}/examples/server/server.cpp >${LLAMACPP_DIR}/examples/server/server.cpp.tmp &&
mv ${LLAMACPP_DIR}/examples/server/server.cpp.tmp ${LLAMACPP_DIR}/examples/server/server.cpp
@@ -99,9 +83,8 @@ build() {
compress_libs() {
echo "Compressing payloads to reduce overall binary size..."
pids=""
rm -rf ${BUILD_DIR}/lib/*.${LIB_EXT}*.gz
for lib in ${BUILD_DIR}/lib/*.${LIB_EXT}* ; do
gzip --best -f ${lib} &
gzip --best ${lib} &
pids+=" $!"
done
echo
@@ -114,12 +97,4 @@ compress_libs() {
# Keep the local tree clean after we're done with the build
cleanup() {
(cd ${LLAMACPP_DIR}/examples/server/ && git checkout CMakeLists.txt server.cpp)
if [ -n "$(ls -A ../patches/*.diff)" ]; then
for patch in ../patches/*.diff; do
for file in $(grep "^+++ " ${patch} | cut -f2 -d' ' | cut -f2- -d/); do
(cd ${LLAMACPP_DIR}; git checkout ${file})
done
done
fi
}

View File

@@ -12,13 +12,7 @@ init_vars
git_module_setup
apply_patches
sign() {
if [ -n "$APPLE_IDENTITY" ]; then
codesign -f --timestamp --deep --options=runtime --sign "$APPLE_IDENTITY" --identifier ai.ollama.ollama $1
fi
}
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.0 -DCMAKE_SYSTEM_NAME=Darwin"
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.0 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_ACCELERATE=off"
case "${GOARCH}" in
"amd64")
@@ -27,11 +21,10 @@ case "${GOARCH}" in
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu"
echo "Building LCD CPU"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu/lib/libext_server.dylib
compress_libs
#
@@ -39,11 +32,10 @@ case "${GOARCH}" in
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx/lib/libext_server.dylib
compress_libs
#
@@ -51,20 +43,17 @@ case "${GOARCH}" in
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx2/lib/libext_server.dylib
compress_libs
;;
"arm64")
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on -DLLAMA_ACCELERATE=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/metal"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/metal/lib/libext_server.dylib
compress_libs
;;
*)

View File

@@ -16,11 +16,8 @@ set -o pipefail
# See https://llvm.org/docs/AMDGPUUsage.html#processors for reference
amdGPUs() {
if [ -n "${AMDGPU_TARGETS}" ]; then
echo "${AMDGPU_TARGETS}"
return
fi
GPU_LIST=(
"gfx803"
"gfx900"
"gfx906:xnack-"
"gfx908:xnack-"
@@ -76,42 +73,36 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
# -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off"
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu" ]; then
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu"
echo "Building LCD CPU"
build
compress_libs
fi
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu"
echo "Building LCD CPU"
build
compress_libs
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx" ]; then
#
# ~2011 CPU Dynamic library with more capabilities turned on to optimize performance
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
compress_libs
fi
#
# ~2011 CPU Dynamic library with more capabilities turned on to optimize performance
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
compress_libs
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx2" ]; then
#
# ~2013 CPU Dynamic library
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
compress_libs
fi
#
# ~2013 CPU Dynamic library
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
compress_libs
fi
else
echo "Skipping CPU generation step as requested"
@@ -127,11 +118,6 @@ if [ -z "${CUDA_LIB_DIR}" ] && [ -d /opt/cuda/targets/x86_64-linux/lib ]; then
CUDA_LIB_DIR=/opt/cuda/targets/x86_64-linux/lib
fi
# Allow override in case libcudart is in the wrong place
if [ -z "${CUDART_LIB_DIR}" ]; then
CUDART_LIB_DIR="${CUDA_LIB_DIR}"
fi
if [ -d "${CUDA_LIB_DIR}" ]; then
echo "CUDA libraries detected - building dynamic CUDA library"
init_vars
@@ -139,7 +125,7 @@ if [ -d "${CUDA_LIB_DIR}" ]; then
if [ -n "${CUDA_MAJOR}" ]; then
CUDA_VARIANT=_v${CUDA_MAJOR}
fi
CMAKE_DEFS="-DLLAMA_CUBLAS=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${COMMON_CMAKE_DEFS} ${CMAKE_DEFS}"
CMAKE_DEFS="-DLLAMA_CUBLAS=on ${COMMON_CMAKE_DEFS} ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cuda${CUDA_VARIANT}"
EXTRA_LIBS="-L${CUDA_LIB_DIR} -lcudart -lcublas -lcublasLt -lcuda"
build
@@ -155,8 +141,6 @@ if [ -d "${CUDA_LIB_DIR}" ]; then
cp "${CUDA_LIB_DIR}/${DEP}" "${BUILD_DIR}/lib/"
elif [ -e "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" ]; then
cp "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" "${BUILD_DIR}/lib/"
elif [ -e "${CUDART_LIB_DIR}/${lib}" ]; then
cp -d ${CUDART_LIB_DIR}/${lib}* "${BUILD_DIR}/lib/"
else
cp -d "${CUDA_LIB_DIR}/${lib}*" "${BUILD_DIR}/lib/"
fi

View File

@@ -25,11 +25,6 @@ function init_vars {
}
$script:GZIP=(get-command -ea 'silentlycontinue' gzip).path
$script:DUMPBIN=(get-command -ea 'silentlycontinue' dumpbin).path
if ($null -eq $env:CMAKE_CUDA_ARCHITECTURES) {
$script:CMAKE_CUDA_ARCHITECTURES="50;52;61;70;75;80"
} else {
$script:CMAKE_CUDA_ARCHITECTURES=$env:CMAKE_CUDA_ARCHITECTURES
}
}
function git_module_setup {
@@ -45,29 +40,6 @@ function apply_patches {
if (!(Select-String -Path "${script:llamacppDir}/examples/server/CMakeLists.txt" -Pattern 'ollama')) {
Add-Content -Path "${script:llamacppDir}/examples/server/CMakeLists.txt" -Value 'include (../../../ext_server/CMakeLists.txt) # ollama'
}
# Apply temporary patches until fix is upstream
$patches = Get-ChildItem "../patches/*.diff"
foreach ($patch in $patches) {
# Extract file paths from the patch file
$filePaths = Get-Content $patch.FullName | Where-Object { $_ -match '^\+\+\+ ' } | ForEach-Object {
$parts = $_ -split ' '
($parts[1] -split '/', 2)[1]
}
# Checkout each file
foreach ($file in $filePaths) {
Set-Location -Path ${script:llamacppDir}
git checkout $file
}
}
# Apply each patch
foreach ($patch in $patches) {
Set-Location -Path ${script:llamacppDir}
git apply $patch.FullName
}
# Avoid duplicate main symbols when we link into the cgo binary
$content = Get-Content -Path "${script:llamacppDir}/examples/server/server.cpp"
$content = $content -replace 'int main\(', 'int __main('
@@ -104,7 +76,7 @@ function compress_libs {
write-host "Compressing dlls..."
$libs = dir "${script:buildDir}/lib/*.dll"
foreach ($file in $libs) {
& "$script:GZIP" --best -f $file
& "$script:GZIP" --best $file
}
}
@@ -156,7 +128,7 @@ if ($null -ne $script:CUDA_LIB_DIR) {
}
init_vars
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @("-DLLAMA_CUBLAS=ON", "-DLLAMA_AVX=on", "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}")
$script:cmakeDefs += @("-DLLAMA_CUBLAS=ON", "-DLLAMA_AVX=on")
build
install
cp "${script:CUDA_LIB_DIR}/cudart64_*.dll" "${script:buildDir}/lib"

View File

@@ -69,65 +69,12 @@ type tensor struct {
name string
kind uint32
offset uint64
size uint64
// shape is the number of elements in each dimension
shape [4]uint64
}
func (t tensor) blockSize() uint64 {
switch {
case t.kind < 2:
return 1
case t.kind < 10:
return 32
default:
return 256
}
}
func (t tensor) typeSize() uint64 {
blockSize := t.blockSize()
switch t.kind {
case 0: // FP32
return 4
case 1: // FP16
return 2
case 2: // Q4_0
return 2 + blockSize/2
case 3: // Q4_1
return 2 + 2 + blockSize/2
case 6: // Q5_0
return 2 + 4 + blockSize/2
case 7: // Q5_1
return 2 + 2 + 4 + blockSize/2
case 8: // Q8_0
return 2 + blockSize
case 9: // Q8_1
return 4 + 4 + blockSize
case 10: // Q2_K
return blockSize/16 + blockSize/4 + 2 + 2
case 11: // Q3_K
return blockSize/8 + blockSize/4 + 12 + 2
case 12: // Q4_K
return 2 + 2 + 12 + blockSize/2
case 13: // Q5_K
return 2 + 2 + 12 + blockSize/8 + blockSize/2
case 14: // Q6_K
return blockSize/2 + blockSize/4 + blockSize/16 + 2
default:
return 0
}
}
func (t tensor) parameters() uint64 {
return t.shape[0] * t.shape[1] * t.shape[2] * t.shape[3]
}
func (t tensor) size() uint64 {
return t.parameters() * t.typeSize() / t.blockSize()
}
type ggufModel struct {
*containerGGUF
@@ -254,15 +201,61 @@ func (llm *ggufModel) Decode(rso *readSeekOffset) error {
shape[i] = llm.readU64(rso)
}
tensor := tensor{
name: name,
kind: llm.readU32(rso),
offset: llm.readU64(rso),
shape: shape,
kind := llm.readU32(rso)
offset := llm.readU64(rso)
var blockSize uint64
switch {
case kind < 2:
blockSize = 1
case kind < 10:
blockSize = 32
default:
blockSize = 256
}
llm.tensors = append(llm.tensors, tensor)
llm.parameters += tensor.parameters()
var typeSize uint64
switch kind {
case 0: // FP32
typeSize = 4
case 1: // FP16
typeSize = 2
case 2: // Q4_0
typeSize = 2 + blockSize/2
case 3: // Q4_1
typeSize = 2 + 2 + blockSize/2
case 6: // Q5_0
typeSize = 2 + 4 + blockSize/2
case 7: // Q5_1
typeSize = 2 + 2 + 4 + blockSize/2
case 8: // Q8_0
typeSize = 2 + blockSize
case 9: // Q8_1
typeSize = 4 + 4 + blockSize
case 10: // Q2_K
typeSize = blockSize/16 + blockSize/4 + 2 + 2
case 11: // Q3_K
typeSize = blockSize/8 + blockSize/4 + 12 + 2
case 12: // Q4_K
typeSize = 2 + 2 + 12 + blockSize/2
case 13: // Q5_K
typeSize = 2 + 2 + 12 + blockSize/8 + blockSize/2
case 14: // Q6_K
typeSize = blockSize/2 + blockSize/4 + blockSize/16 + 2
}
parameters := shape[0] * shape[1] * shape[2] * shape[3]
size := parameters * typeSize / blockSize
llm.tensors = append(llm.tensors, tensor{
name: name,
kind: kind,
offset: offset,
size: size,
shape: shape,
})
llm.parameters += parameters
}
alignment, ok := llm.kv["general.alignment"].(uint32)
@@ -272,7 +265,7 @@ func (llm *ggufModel) Decode(rso *readSeekOffset) error {
rso.Seek(int64(alignment)-rso.offset%int64(alignment), io.SeekCurrent)
for _, tensor := range llm.tensors {
padded := (int64(tensor.size()) + int64(alignment) - 1) & ^(int64(alignment) - 1)
padded := (int64(tensor.size) + int64(alignment) - 1) & ^(int64(alignment) - 1)
rso.Seek(padded, io.SeekCurrent)
}

View File

@@ -62,7 +62,7 @@ const maxRetries = 3
type PredictOpts struct {
Prompt string
Format string
Images []ImageData
Images []api.ImageData
Options api.Options
}

View File

@@ -50,10 +50,10 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options)
// fp16 k,v matrices require = n_ctx * n_layer * n_embd / n_head * n_head_kv * 2 bytes each * 2 key and value
kv := 2 * 2 * int64(opts.NumCtx) * int64(ggml.NumLayers()) * int64(ggml.NumEmbed()) * int64(ggml.NumHeadKv()) / int64(ggml.NumHead())
// this amount is the overhead + tensors in memory
// TODO: get this from the llama.cpp's graph calculations instead of
// estimating it's 1/6 * kv_cache_size * num_gqa
graph := int64(ggml.NumGQA()) * kv / 6
// rough estimation for scratch space based on context size, batch size and number of layers in the model
// TODO: instead call llama.cpp's alloc functions to measure required memory
// TODO: account for quantization levels
scratch := 8*int64(opts.NumCtx)*int64(opts.NumBatch)*int64(ggml.NumLayers()) + 1536*1024*1024 // 1536MiB overhead
info := gpu.GetGPUInfo()
switch runtime.GOOS {
@@ -62,7 +62,7 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options)
break
}
if size+kv+graph > vram {
if size+kv+scratch > vram {
slog.Info("not enough vram available, falling back to CPU only")
info.Library = "cpu"
info.Variant = gpu.GetCPUVariant()
@@ -70,8 +70,7 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options)
break
}
// TODO: implement layer splitting on macOS
opts.NumGPU = 999
opts.NumGPU = 1
default:
if info.Library == "cpu" {
slog.Info("GPU not available, falling back to CPU")
@@ -100,13 +99,13 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options)
maxlayers := int64(ggml.NumLayers()) + 1
devices := int64(info.DeviceCount)
avg := vram / devices
layers := maxlayers * (avg - graph) / (kv + size/devices)
layers := maxlayers * (avg - scratch) / (kv + size/devices)
if layers > maxlayers {
layers = maxlayers
}
// 1 + 2 must fit on the main gpu
min := graph + kv*layers/maxlayers
min := scratch + kv*layers/maxlayers
if layers <= 0 || min > avg {
slog.Info("not enough vram available, falling back to CPU only")
info.Library = "cpu"
@@ -120,7 +119,7 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options)
opts.RopeFrequencyBase = 0.0
opts.RopeFrequencyScale = 0.0
return newLlmServer(info, workDir, model, adapters, projectors, opts)
return newLlmServer(info, model, adapters, projectors, opts)
}
// Give any native cgo implementations an opportunity to initialize
@@ -128,7 +127,7 @@ func Init(workdir string) error {
return nativeInit(workdir)
}
func newLlmServer(gpuInfo gpu.GpuInfo, workDir, model string, adapters, projectors []string, opts api.Options) (LLM, error) {
func newLlmServer(gpuInfo gpu.GpuInfo, model string, adapters, projectors []string, opts api.Options) (LLM, error) {
dynLibs := getDynLibs(gpuInfo)
// Check to see if the user has requested a specific library instead of auto-detecting
@@ -143,16 +142,6 @@ func newLlmServer(gpuInfo gpu.GpuInfo, workDir, model string, adapters, projecto
}
}
// We stage into a temp directory, and if we've been idle for a while, it may have been reaped
_, err := os.Stat(dynLibs[0])
if err != nil {
slog.Info(fmt.Sprintf("%s has disappeared, reloading libraries", dynLibs[0]))
err = nativeInit(workDir)
if err != nil {
return nil, err
}
}
err2 := fmt.Errorf("unable to locate suitable llm library")
for _, dynLib := range dynLibs {
srv, err := newDynExtServer(dynLib, model, adapters, projectors, opts)

View File

@@ -1,21 +0,0 @@
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index d86d7e04..2694e92e 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -901,13 +901,15 @@ struct llama_server_context
slot.sent_count += result.text_to_send.size();
// add the token to slot queue and cache
}
- slot.add_token_string(result);
+
if (slot.params.stream)
{
send_partial_response(slot, result);
}
}
+ slot.add_token_string(result);
+
if (incomplete)
{
slot.has_next_token = true;

View File

@@ -1,85 +0,0 @@
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 11dd82c3..311495a8 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -28,6 +28,7 @@
#include <chrono>
#include <condition_variable>
#include <atomic>
+#include <signal.h>
using json = nlohmann::json;
@@ -2394,6 +2395,9 @@ static void append_to_generated_text_from_generated_token_probs(llama_server_con
}
}
+std::function<void(int)> shutdown_handler;
+inline void signal_handler(int signal) { shutdown_handler(signal); }
+
int main(int argc, char **argv)
{
#if SERVER_VERBOSE != 1
@@ -3014,8 +3018,14 @@ int main(int argc, char **argv)
std::placeholders::_2,
std::placeholders::_3
));
- llama.queue_tasks.start_loop();
+ shutdown_handler = [&](int) {
+ llama.queue_tasks.terminate();
+ };
+ signal(SIGTERM, signal_handler);
+ signal(SIGINT, signal_handler);
+ llama.queue_tasks.start_loop();
+ svr.stop();
t.join();
llama_backend_free();
diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp
index 70cce072..9124869a 100644
--- a/examples/server/utils.hpp
+++ b/examples/server/utils.hpp
@@ -190,6 +190,7 @@ inline std::string format_chatml(std::vector<json> messages)
struct llama_server_queue {
int id = 0;
std::mutex mutex_tasks;
+ bool running;
// queues
std::vector<task_server> queue_tasks;
std::vector<task_server> queue_tasks_deferred;
@@ -248,9 +249,18 @@ struct llama_server_queue {
queue_tasks_deferred.clear();
}
- // Start the main loop. This call is blocking
- [[noreturn]]
+ // end the start_loop routine
+ void terminate() {
+ {
+ std::unique_lock<std::mutex> lock(mutex_tasks);
+ running = false;
+ }
+ condition_tasks.notify_all();
+ }
+
+ // Start the main loop.
void start_loop() {
+ running = true;
while (true) {
// new task arrived
LOG_VERBOSE("have new task", {});
@@ -294,8 +304,12 @@ struct llama_server_queue {
{
std::unique_lock<std::mutex> lock(mutex_tasks);
if (queue_tasks.empty()) {
+ if (!running) {
+ LOG_VERBOSE("ending start_loop", {});
+ return;
+ }
condition_tasks.wait(lock, [&]{
- return !queue_tasks.empty();
+ return (!queue_tasks.empty() || !running);
});
}
}

View File

@@ -90,7 +90,6 @@ func getDynLibs(gpuInfo gpu.GpuInfo) []string {
if len(dynLibs) == 0 {
dynLibs = []string{availableDynLibs["cpu"]}
}
slog.Debug(fmt.Sprintf("ordered list of LLM libraries to try %v", dynLibs))
return dynLibs
}

View File

@@ -1,322 +0,0 @@
// openai package provides middleware for partial compatibility with the OpenAI REST API
package openai
import (
"bytes"
"encoding/json"
"fmt"
"io"
"math/rand"
"net/http"
"time"
"github.com/gin-gonic/gin"
"github.com/jmorganca/ollama/api"
)
type Error struct {
Message string `json:"message"`
Type string `json:"type"`
Param interface{} `json:"param"`
Code *string `json:"code"`
}
type ErrorResponse struct {
Error Error `json:"error"`
}
type Message struct {
Role string `json:"role"`
Content string `json:"content"`
}
type Choice struct {
Index int `json:"index"`
Message Message `json:"message"`
FinishReason *string `json:"finish_reason"`
}
type ChunkChoice struct {
Index int `json:"index"`
Delta Message `json:"delta"`
FinishReason *string `json:"finish_reason"`
}
type Usage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
type ResponseFormat struct {
Type string `json:"type"`
}
type ChatCompletionRequest struct {
Model string `json:"model"`
Messages []Message `json:"messages"`
Stream bool `json:"stream"`
MaxTokens *int `json:"max_tokens"`
Seed *int `json:"seed"`
Stop any `json:"stop"`
Temperature *float64 `json:"temperature"`
FrequencyPenalty *float64 `json:"frequency_penalty"`
PresencePenalty *float64 `json:"presence_penalty_penalty"`
TopP *float64 `json:"top_p"`
ResponseFormat *ResponseFormat `json:"response_format"`
}
type ChatCompletion struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Model string `json:"model"`
SystemFingerprint string `json:"system_fingerprint"`
Choices []Choice `json:"choices"`
Usage Usage `json:"usage,omitempty"`
}
type ChatCompletionChunk struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Model string `json:"model"`
SystemFingerprint string `json:"system_fingerprint"`
Choices []ChunkChoice `json:"choices"`
}
func NewError(code int, message string) ErrorResponse {
var etype string
switch code {
case http.StatusBadRequest:
etype = "invalid_request_error"
case http.StatusNotFound:
etype = "not_found_error"
default:
etype = "api_error"
}
return ErrorResponse{Error{Type: etype, Message: message}}
}
func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
return ChatCompletion{
Id: id,
Object: "chat.completion",
Created: r.CreatedAt.Unix(),
Model: r.Model,
SystemFingerprint: "fp_ollama",
Choices: []Choice{{
Index: 0,
Message: Message{Role: r.Message.Role, Content: r.Message.Content},
FinishReason: func(done bool) *string {
if done {
reason := "stop"
return &reason
}
return nil
}(r.Done),
}},
Usage: Usage{
// TODO: ollama returns 0 for prompt eval if the prompt was cached, but openai returns the actual count
PromptTokens: r.PromptEvalCount,
CompletionTokens: r.EvalCount,
TotalTokens: r.PromptEvalCount + r.EvalCount,
},
}
}
func toChunk(id string, r api.ChatResponse) ChatCompletionChunk {
return ChatCompletionChunk{
Id: id,
Object: "chat.completion.chunk",
Created: time.Now().Unix(),
Model: r.Model,
SystemFingerprint: "fp_ollama",
Choices: []ChunkChoice{
{
Index: 0,
Delta: Message{Role: "assistant", Content: r.Message.Content},
FinishReason: func(done bool) *string {
if done {
reason := "stop"
return &reason
}
return nil
}(r.Done),
},
},
}
}
func fromRequest(r ChatCompletionRequest) api.ChatRequest {
var messages []api.Message
for _, msg := range r.Messages {
messages = append(messages, api.Message{Role: msg.Role, Content: msg.Content})
}
options := make(map[string]interface{})
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []interface{}:
var stops []string
for _, s := range stop {
if str, ok := s.(string); ok {
stops = append(stops, str)
}
}
options["stop"] = stops
}
if r.MaxTokens != nil {
options["num_predict"] = *r.MaxTokens
}
if r.Temperature != nil {
options["temperature"] = *r.Temperature * 2.0
} else {
options["temperature"] = 1.0
}
if r.Seed != nil {
options["seed"] = *r.Seed
// temperature=0 is required for reproducible outputs
options["temperature"] = 0.0
}
if r.FrequencyPenalty != nil {
options["frequency_penalty"] = *r.FrequencyPenalty * 2.0
}
if r.PresencePenalty != nil {
options["presence_penalty"] = *r.PresencePenalty * 2.0
}
if r.TopP != nil {
options["top_p"] = *r.TopP
} else {
options["top_p"] = 1.0
}
var format string
if r.ResponseFormat != nil && r.ResponseFormat.Type == "json_object" {
format = "json"
}
return api.ChatRequest{
Model: r.Model,
Messages: messages,
Format: format,
Options: options,
Stream: &r.Stream,
}
}
type writer struct {
stream bool
id string
gin.ResponseWriter
}
func (w *writer) writeError(code int, data []byte) (int, error) {
var serr api.StatusError
err := json.Unmarshal(data, &serr)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(NewError(http.StatusInternalServerError, serr.Error()))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *writer) writeResponse(data []byte) (int, error) {
var chatResponse api.ChatResponse
err := json.Unmarshal(data, &chatResponse)
if err != nil {
return 0, err
}
// chat chunk
if w.stream {
d, err := json.Marshal(toChunk(w.id, chatResponse))
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "text/event-stream")
_, err = w.ResponseWriter.Write([]byte(fmt.Sprintf("data: %s\n\n", d)))
if err != nil {
return 0, err
}
if chatResponse.Done {
_, err = w.ResponseWriter.Write([]byte("data: [DONE]\n\n"))
if err != nil {
return 0, err
}
}
return len(data), nil
}
// chat completion
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toChatCompletion(w.id, chatResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *writer) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func Middleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req ChatCompletionRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
if len(req.Messages) == 0 {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, "[] is too short - 'messages'"))
return
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(fromRequest(req)); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &writer{
ResponseWriter: c.Writer,
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
}
c.Writer = w
c.Next()
}
}

View File

@@ -7,7 +7,6 @@ import (
"fmt"
"io"
"log/slog"
"slices"
)
type Command struct {
@@ -57,16 +56,6 @@ func Parse(reader io.Reader) ([]Command, error) {
command.Args = string(bytes.TrimSpace(fields[1]))
case "EMBED":
return nil, fmt.Errorf("deprecated command: EMBED is no longer supported, use the /embed API endpoint instead")
case "MESSAGE":
command.Name = string(bytes.ToLower(fields[0]))
fields = bytes.SplitN(fields[1], []byte(" "), 2)
if len(fields) < 2 {
return nil, fmt.Errorf("should be in the format <role> <message>")
}
if !slices.Contains([]string{"system", "user", "assistant"}, string(bytes.ToLower(fields[0]))) {
return nil, fmt.Errorf("role must be one of \"system\", \"user\", or \"assistant\"")
}
command.Args = fmt.Sprintf("%s: %s", string(bytes.ToLower(fields[0])), string(fields[1]))
default:
if !bytes.HasPrefix(fields[0], []byte("#")) {
// log a warning for unknown commands

View File

@@ -61,38 +61,3 @@ PARAMETER param1
assert.ErrorContains(t, err, "missing value for [param1]")
}
func Test_Parser_Messages(t *testing.T) {
input := `
FROM foo
MESSAGE system You are a Parser. Always Parse things.
MESSAGE user Hey there!
MESSAGE assistant Hello, I want to parse all the things!
`
reader := strings.NewReader(input)
commands, err := Parse(reader)
assert.Nil(t, err)
expectedCommands := []Command{
{Name: "model", Args: "foo"},
{Name: "message", Args: "system: You are a Parser. Always Parse things."},
{Name: "message", Args: "user: Hey there!"},
{Name: "message", Args: "assistant: Hello, I want to parse all the things!"},
}
assert.Equal(t, expectedCommands, commands)
}
func Test_Parser_Messages_BadRole(t *testing.T) {
input := `
FROM foo
MESSAGE badguy I'm a bad guy!
`
reader := strings.NewReader(input)
_, err := Parse(reader)
assert.ErrorContains(t, err, "role must be one of \"system\", \"user\", or \"assistant\"")
}

View File

@@ -133,6 +133,13 @@ func (b *Buffer) Size() int {
return b.Buf.Size()
}
func min(n, m int) int {
if n > m {
return m
}
return n
}
func (b *Buffer) Add(r rune) {
if b.Pos == b.Buf.Size() {
fmt.Printf("%c", r)

View File

@@ -32,8 +32,6 @@ func (p *Prompt) placeholder() string {
type Terminal struct {
outchan chan rune
rawmode bool
termios any
}
type Instance struct {
@@ -62,16 +60,6 @@ func New(prompt Prompt) (*Instance, error) {
}
func (i *Instance) Readline() (string, error) {
if !i.Terminal.rawmode {
fd := int(syscall.Stdin)
termios, err := SetRawMode(fd)
if err != nil {
return "", err
}
i.Terminal.rawmode = true
i.Terminal.termios = termios
}
prompt := i.Prompt.prompt()
if i.Pasting {
// force alt prompt when pasting
@@ -79,12 +67,13 @@ func (i *Instance) Readline() (string, error) {
}
fmt.Print(prompt)
defer func() {
fd := int(syscall.Stdin)
// nolint: errcheck
UnsetRawMode(fd, i.Terminal.termios)
i.Terminal.rawmode = false
}()
fd := int(syscall.Stdin)
termios, err := SetRawMode(fd)
if err != nil {
return "", err
}
// nolint: errcheck
defer UnsetRawMode(fd, termios)
buf, _ := NewBuffer(i.Prompt)
@@ -216,8 +205,7 @@ func (i *Instance) Readline() (string, error) {
case CharCtrlW:
buf.DeleteWord()
case CharCtrlZ:
fd := int(syscall.Stdin)
return handleCharCtrlZ(fd, i.Terminal.termios)
return handleCharCtrlZ(fd, termios)
case CharEnter:
output := buf.String()
if output != "" {
@@ -248,16 +236,8 @@ func (i *Instance) HistoryDisable() {
}
func NewTerminal() (*Terminal, error) {
fd := int(syscall.Stdin)
termios, err := SetRawMode(fd)
if err != nil {
return nil, err
}
t := &Terminal{
outchan: make(chan rune),
rawmode: true,
termios: termios,
}
go t.ioloop()

View File

@@ -6,9 +6,8 @@ import (
"syscall"
)
func handleCharCtrlZ(fd int, termios any) (string, error) {
t := termios.(*Termios)
if err := UnsetRawMode(fd, t); err != nil {
func handleCharCtrlZ(fd int, termios *Termios) (string, error) {
if err := UnsetRawMode(fd, termios); err != nil {
return "", err
}

View File

@@ -1,6 +1,6 @@
package readline
func handleCharCtrlZ(fd int, state any) (string, error) {
func handleCharCtrlZ(fd int, state *State) (string, error) {
// not supported
return "", nil
}

View File

@@ -25,9 +25,8 @@ func SetRawMode(fd int) (*Termios, error) {
return termios, setTermios(fd, &newTermios)
}
func UnsetRawMode(fd int, termios any) error {
t := termios.(*Termios)
return setTermios(fd, t)
func UnsetRawMode(fd int, termios *Termios) error {
return setTermios(fd, termios)
}
// IsTerminal returns true if the given file descriptor is a terminal.

View File

@@ -56,8 +56,7 @@ func SetRawMode(fd int) (*State, error) {
return &State{st}, nil
}
func UnsetRawMode(fd int, state any) error {
s := state.(*State)
_, _, err := syscall.SyscallN(procSetConsoleMode.Addr(), uintptr(fd), uintptr(s.mode), 0)
func UnsetRawMode(fd int, state *State) error {
_, _, err := syscall.SyscallN(procSetConsoleMode.Addr(), uintptr(fd), uintptr(state.mode), 0)
return err
}

View File

@@ -2,7 +2,7 @@
set -e
export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
export VERSION=${VERSION:-0.0.0}
export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version=$VERSION\" \"-X=github.com/jmorganca/ollama/server.mode=release\"'"
mkdir -p dist

View File

@@ -2,7 +2,7 @@
set -eu
export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
export VERSION=${VERSION:-0.0.0}
export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version=$VERSION\" \"-X=github.com/jmorganca/ollama/server.mode=release\"'"
docker build \
@@ -13,13 +13,3 @@ docker build \
-f Dockerfile \
-t ollama/ollama:$VERSION \
.
docker build \
--load \
--platform=linux/amd64 \
--build-arg=VERSION \
--build-arg=GOFLAGS \
--target runtime-rocm \
-f Dockerfile \
-t ollama/ollama:$VERSION-rocm \
.

View File

@@ -2,24 +2,14 @@
set -eu
export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
export VERSION=${VERSION:-0.0.0}
export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version=$VERSION\" \"-X=github.com/jmorganca/ollama/server.mode=release\"'"
BUILD_ARCH=${BUILD_ARCH:-"amd64 arm64"}
export AMDGPU_TARGETS=${AMDGPU_TARGETS:=""}
mkdir -p dist
for TARGETARCH in ${BUILD_ARCH}; do
docker build \
--platform=linux/$TARGETARCH \
--build-arg=GOFLAGS \
--build-arg=CGO_CFLAGS \
--build-arg=OLLAMA_CUSTOM_CPU_DEFS \
--build-arg=AMDGPU_TARGETS \
--target build-$TARGETARCH \
-f Dockerfile \
-t builder:$TARGETARCH \
.
docker build --platform=linux/$TARGETARCH --build-arg=GOFLAGS --build-arg=CGO_CFLAGS --build-arg=OLLAMA_CUSTOM_CPU_DEFS -f Dockerfile.build -t builder:$TARGETARCH .
docker create --platform linux/$TARGETARCH --name builder-$TARGETARCH builder:$TARGETARCH
docker cp builder-$TARGETARCH:/go/src/github.com/jmorganca/ollama/ollama ./dist/ollama-linux-$TARGETARCH
docker rm builder-$TARGETARCH

View File

@@ -61,7 +61,7 @@ if [ -n "$NEEDS" ]; then
fi
status "Downloading ollama..."
curl --fail --show-error --location --progress-bar -o $TEMP_DIR/ollama "https://ollama.com/download/ollama-linux-$ARCH"
curl --fail --show-error --location --progress-bar -o $TEMP_DIR/ollama "https://ollama.ai/download/ollama-linux-$ARCH"
for BINDIR in /usr/local/bin /usr/bin /bin; do
echo $PATH | grep -q $BINDIR && break || continue

View File

@@ -111,14 +111,8 @@ func getAuthToken(ctx context.Context, redirData AuthRedirect) (string, error) {
defer resp.Body.Close()
if resp.StatusCode >= http.StatusBadRequest {
responseBody, err := io.ReadAll(resp.Body)
if err != nil {
return "", fmt.Errorf("%d: %v", resp.StatusCode, err)
} else if len(responseBody) > 0 {
return "", fmt.Errorf("%d: %s", resp.StatusCode, responseBody)
}
return "", fmt.Errorf("%s", resp.Status)
body, _ := io.ReadAll(resp.Body)
return "", fmt.Errorf("on pull registry responded with code %d: %s", resp.StatusCode, body)
}
respBody, err := io.ReadAll(resp.Body)
@@ -153,7 +147,12 @@ func (s SignatureData) Bytes() []byte {
// SignData takes a SignatureData object and signs it with a raw private key
func (s SignatureData) Sign(rawKey []byte) (string, error) {
signer, err := ssh.ParsePrivateKey(rawKey)
privateKey, err := ssh.ParseRawPrivateKey(rawKey)
if err != nil {
return "", err
}
signer, err := ssh.NewSignerFromKey(privateKey)
if err != nil {
return "", err
}

View File

@@ -25,11 +25,6 @@ import (
"github.com/jmorganca/ollama/format"
)
const maxRetries = 6
var errMaxRetriesExceeded = errors.New("max retries exceeded")
var errPartStalled = errors.New("part stalled")
var blobDownloadManager sync.Map
type blobDownload struct {
@@ -49,11 +44,10 @@ type blobDownload struct {
}
type blobDownloadPart struct {
N int
Offset int64
Size int64
Completed int64
lastUpdated time.Time
N int
Offset int64
Size int64
Completed int64
*blobDownload `json:"-"`
}
@@ -78,13 +72,6 @@ func (p *blobDownloadPart) StopsAt() int64 {
return p.Offset + p.Size
}
func (p *blobDownloadPart) Write(b []byte) (n int, err error) {
n = len(b)
p.blobDownload.Completed.Add(int64(n))
p.lastUpdated = time.Now()
return n, nil
}
func (b *blobDownload) Prepare(ctx context.Context, requestURL *url.URL, opts *RegistryOptions) error {
partFilePaths, err := filepath.Glob(b.Name + "-partial-*")
if err != nil {
@@ -170,9 +157,6 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *Regis
case errors.Is(err, context.Canceled), errors.Is(err, syscall.ENOSPC):
// return immediately if the context is canceled or the device is out of space
return err
case errors.Is(err, errPartStalled):
try--
continue
case err != nil:
sleep := time.Second * time.Duration(math.Pow(2, float64(try)))
slog.Info(fmt.Sprintf("%s part %d attempt %d failed: %v, retrying in %s", b.Digest[7:19], part.N, try, err, sleep))
@@ -211,54 +195,28 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *Regis
}
func (b *blobDownload) downloadChunk(ctx context.Context, requestURL *url.URL, w io.Writer, part *blobDownloadPart, opts *RegistryOptions) error {
g, ctx := errgroup.WithContext(ctx)
g.Go(func() error {
headers := make(http.Header)
headers.Set("Range", fmt.Sprintf("bytes=%d-%d", part.StartsAt(), part.StopsAt()-1))
resp, err := makeRequestWithRetry(ctx, http.MethodGet, requestURL, headers, nil, opts)
if err != nil {
return err
}
defer resp.Body.Close()
n, err := io.Copy(w, io.TeeReader(resp.Body, part))
if err != nil && !errors.Is(err, context.Canceled) && !errors.Is(err, io.ErrUnexpectedEOF) {
// rollback progress
b.Completed.Add(-n)
return err
}
part.Completed += n
if err := b.writePart(part.Name(), part); err != nil {
return err
}
// return nil or context.Canceled or UnexpectedEOF (resumable)
headers := make(http.Header)
headers.Set("Range", fmt.Sprintf("bytes=%d-%d", part.StartsAt(), part.StopsAt()-1))
resp, err := makeRequestWithRetry(ctx, http.MethodGet, requestURL, headers, nil, opts)
if err != nil {
return err
})
}
defer resp.Body.Close()
g.Go(func() error {
ticker := time.NewTicker(time.Second)
for {
select {
case <-ticker.C:
if part.Completed >= part.Size {
return nil
}
n, err := io.Copy(w, io.TeeReader(resp.Body, b))
if err != nil && !errors.Is(err, context.Canceled) && !errors.Is(err, io.ErrUnexpectedEOF) {
// rollback progress
b.Completed.Add(-n)
return err
}
if !part.lastUpdated.IsZero() && time.Since(part.lastUpdated) > 5*time.Second {
slog.Info(fmt.Sprintf("%s part %d stalled; retrying", b.Digest[7:19], part.N))
// reset last updated
part.lastUpdated = time.Time{}
return errPartStalled
}
case <-ctx.Done():
return ctx.Err()
}
}
})
part.Completed += n
if err := b.writePart(part.Name(), part); err != nil {
return err
}
return g.Wait()
// return nil or context.Canceled or UnexpectedEOF (resumable)
return err
}
func (b *blobDownload) newPart(offset, size int64) error {
@@ -297,6 +255,12 @@ func (b *blobDownload) writePart(partName string, part *blobDownloadPart) error
return json.NewEncoder(partFile).Encode(part)
}
func (b *blobDownload) Write(p []byte) (n int, err error) {
n = len(p)
b.Completed.Add(int64(n))
return n, nil
}
func (b *blobDownload) acquire() {
b.references.Add(1)
}
@@ -315,19 +279,20 @@ func (b *blobDownload) Wait(ctx context.Context, fn func(api.ProgressResponse))
for {
select {
case <-ticker.C:
fn(api.ProgressResponse{
Status: fmt.Sprintf("pulling %s", b.Digest[7:19]),
Digest: b.Digest,
Total: b.Total,
Completed: b.Completed.Load(),
})
if b.done || b.err != nil {
return b.err
}
case <-ctx.Done():
return ctx.Err()
}
fn(api.ProgressResponse{
Status: fmt.Sprintf("pulling %s", b.Digest[7:19]),
Digest: b.Digest,
Total: b.Total,
Completed: b.Completed.Load(),
})
if b.done || b.err != nil {
return b.err
}
}
}
@@ -338,6 +303,10 @@ type downloadOpts struct {
fn func(api.ProgressResponse)
}
const maxRetries = 6
var errMaxRetriesExceeded = errors.New("max retries exceeded")
// downloadBlob downloads a blob from the registry and stores it in the blobs directory
func downloadBlob(ctx context.Context, opts downloadOpts) error {
fp, err := GetBlobsPath(opts.digest)

View File

@@ -19,6 +19,7 @@ import (
"strconv"
"strings"
"text/template"
"text/template/parse"
"golang.org/x/exp/slices"
@@ -40,7 +41,7 @@ type Model struct {
Config ConfigV2
ShortName string
ModelPath string
ParentModel string
OriginalModel string
AdapterPaths []string
ProjectorPaths []string
Template string
@@ -49,12 +50,156 @@ type Model struct {
Digest string
Size int64
Options map[string]interface{}
Messages []Message
}
type Message struct {
Role string `json:"role"`
Content string `json:"content"`
type PromptVars struct {
System string
Prompt string
Response string
First bool
}
// extractParts extracts the parts of the template before and after the {{.Response}} node.
func extractParts(tmplStr string) (pre string, post string, err error) {
tmpl, err := template.New("").Parse(tmplStr)
if err != nil {
return "", "", err
}
var foundResponse bool
for _, node := range tmpl.Tree.Root.Nodes {
if node.Type() == parse.NodeAction && node.String() == "{{.Response}}" {
foundResponse = true
}
if !foundResponse {
pre += node.String()
} else {
post += node.String()
}
}
return pre, post, nil
}
func Prompt(promptTemplate string, p PromptVars) (string, error) {
var prompt strings.Builder
// Use the "missingkey=zero" option to handle missing variables without panicking
tmpl, err := template.New("").Option("missingkey=zero").Parse(promptTemplate)
if err != nil {
return "", err
}
vars := map[string]any{
"System": p.System,
"Prompt": p.Prompt,
"Response": p.Response,
"First": p.First,
}
var sb strings.Builder
if err := tmpl.Execute(&sb, vars); err != nil {
return "", err
}
prompt.WriteString(sb.String())
if !strings.Contains(prompt.String(), p.Response) {
// if the response is not in the prompt template, append it to the end
prompt.WriteString(p.Response)
}
return prompt.String(), nil
}
// PreResponsePrompt returns the prompt before the response tag
func (m *Model) PreResponsePrompt(p PromptVars) (string, error) {
if p.System == "" {
// use the default system prompt for this model if one is not specified
p.System = m.System
}
pre, _, err := extractParts(m.Template)
if err != nil {
return "", err
}
return Prompt(pre, p)
}
// PostResponseTemplate returns the template after the response tag
func (m *Model) PostResponseTemplate(p PromptVars) (string, error) {
if p.System == "" {
// use the default system prompt for this model if one is not specified
p.System = m.System
}
_, post, err := extractParts(m.Template)
if err != nil {
return "", err
}
if post == "" {
// if there is no post-response template, return the provided response
return p.Response, nil
}
return Prompt(post, p)
}
func (m *Model) ChatPrompt(msgs []api.Message) (string, []api.ImageData, error) {
// build the prompt from the list of messages
var prompt strings.Builder
var currentImages []api.ImageData
currentVars := PromptVars{
First: true,
System: m.System,
}
writePrompt := func() error {
p, err := Prompt(m.Template, currentVars)
if err != nil {
return err
}
prompt.WriteString(p)
currentVars = PromptVars{}
return nil
}
for _, msg := range msgs {
switch strings.ToLower(msg.Role) {
case "system":
if currentVars.System != "" {
if err := writePrompt(); err != nil {
return "", nil, err
}
}
currentVars.System = msg.Content
case "user":
if currentVars.Prompt != "" {
if err := writePrompt(); err != nil {
return "", nil, err
}
}
currentVars.Prompt = msg.Content
currentImages = msg.Images
case "assistant":
currentVars.Response = msg.Content
if err := writePrompt(); err != nil {
return "", nil, err
}
default:
return "", nil, fmt.Errorf("invalid role: %s, role must be one of [system, user, assistant]", msg.Role)
}
}
// Append the last set of vars if they are non-empty
if currentVars.Prompt != "" || currentVars.System != "" {
p, err := m.PreResponsePrompt(currentVars)
if err != nil {
return "", nil, fmt.Errorf("pre-response template: %w", err)
}
prompt.WriteString(p)
}
return prompt.String(), currentImages, nil
}
type ManifestV2 struct {
@@ -188,7 +333,7 @@ func GetModel(name string) (*Model, error) {
switch layer.MediaType {
case "application/vnd.ollama.image.model":
model.ModelPath = filename
model.ParentModel = layer.From
model.OriginalModel = layer.From
case "application/vnd.ollama.image.embed":
// Deprecated in versions > 0.1.2
// TODO: remove this warning in a future version
@@ -229,16 +374,6 @@ func GetModel(name string) (*Model, error) {
if err = json.NewDecoder(params).Decode(&model.Options); err != nil {
return nil, err
}
case "application/vnd.ollama.image.messages":
msgs, err := os.Open(filename)
if err != nil {
return nil, err
}
defer msgs.Close()
if err = json.NewDecoder(msgs).Decode(&model.Messages); err != nil {
return nil, err
}
case "application/vnd.ollama.image.license":
bts, err := os.ReadFile(filename)
if err != nil {
@@ -277,13 +412,6 @@ func realpath(mfDir, from string) string {
}
func CreateModel(ctx context.Context, name, modelFileDir string, commands []parser.Command, fn func(resp api.ProgressResponse)) error {
deleteMap := make(map[string]struct{})
if manifest, _, err := GetManifest(ParseModelPath(name)); err == nil {
for _, layer := range append(manifest.Layers, manifest.Config) {
deleteMap[layer.Digest] = struct{}{}
}
}
config := ConfigV2{
OS: "linux",
Architecture: "amd64",
@@ -292,13 +420,15 @@ func CreateModel(ctx context.Context, name, modelFileDir string, commands []pars
},
}
deleteMap := make(map[string]struct{})
var layers Layers
messages := []string{}
params := make(map[string][]string)
fromParams := make(map[string]any)
for _, c := range commands {
slog.Info(fmt.Sprintf("[%s] - %s", c.Name, c.Args))
mediatype := fmt.Sprintf("application/vnd.ollama.image.%s", c.Name)
switch c.Name {
@@ -472,37 +602,11 @@ func CreateModel(ctx context.Context, name, modelFileDir string, commands []pars
}
layers.Replace(layer)
case "message":
messages = append(messages, c.Args)
default:
params[c.Name] = append(params[c.Name], c.Args)
}
}
if len(messages) > 0 {
fn(api.ProgressResponse{Status: "creating parameters layer"})
msgs := make([]api.Message, 0)
for _, m := range messages {
// todo: handle images
msg := strings.SplitN(m, ": ", 2)
msgs = append(msgs, api.Message{Role: msg[0], Content: msg[1]})
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(msgs); err != nil {
return err
}
layer, err := NewLayer(&b, "application/vnd.ollama.image.messages")
if err != nil {
return err
}
layers.Replace(layer)
}
if len(params) > 0 {
fn(api.ProgressResponse{Status: "creating parameters layer"})
@@ -799,8 +903,8 @@ func ShowModelfile(model *Model) (string, error) {
mt.Model = model
mt.From = model.ModelPath
if model.ParentModel != "" {
mt.From = model.ParentModel
if model.OriginalModel != "" {
mt.From = model.OriginalModel
}
modelFile := `# Modelfile generated by "ollama show"

347
server/images_test.go Normal file
View File

@@ -0,0 +1,347 @@
package server
import (
"strings"
"testing"
"github.com/jmorganca/ollama/api"
)
func TestPrompt(t *testing.T) {
tests := []struct {
name string
template string
vars PromptVars
want string
wantErr bool
}{
{
name: "System Prompt",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
vars: PromptVars{
System: "You are a Wizard.",
Prompt: "What are the potion ingredients?",
},
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]",
},
{
name: "System Prompt with Response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
vars: PromptVars{
System: "You are a Wizard.",
Prompt: "What are the potion ingredients?",
Response: "I don't know.",
},
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST] I don't know.",
},
{
name: "Conditional Logic Nodes",
template: "[INST] {{if .First}}Hello!{{end}} {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
vars: PromptVars{
First: true,
System: "You are a Wizard.",
Prompt: "What are the potion ingredients?",
Response: "I don't know.",
},
want: "[INST] Hello! You are a Wizard. What are the potion ingredients? [/INST] I don't know.",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got, err := Prompt(tt.template, tt.vars)
if (err != nil) != tt.wantErr {
t.Errorf("Prompt() error = %v, wantErr %v", err, tt.wantErr)
return
}
if got != tt.want {
t.Errorf("Prompt() got = %v, want %v", got, tt.want)
}
})
}
}
func TestModel_PreResponsePrompt(t *testing.T) {
tests := []struct {
name string
template string
vars PromptVars
want string
wantErr bool
}{
{
name: "No Response in Template",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
vars: PromptVars{
System: "You are a Wizard.",
Prompt: "What are the potion ingredients?",
},
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]",
},
{
name: "Response in Template",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
vars: PromptVars{
System: "You are a Wizard.",
Prompt: "What are the potion ingredients?",
},
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST] ",
},
{
name: "Response in Template with Trailing Formatting",
template: "<|im_start|>user\n{{ .Prompt }}<|im_end|><|im_start|>assistant\n{{ .Response }}<|im_end|>",
vars: PromptVars{
Prompt: "What are the potion ingredients?",
},
want: "<|im_start|>user\nWhat are the potion ingredients?<|im_end|><|im_start|>assistant\n",
},
{
name: "Response in Template with Alternative Formatting",
template: "<|im_start|>user\n{{.Prompt}}<|im_end|><|im_start|>assistant\n{{.Response}}<|im_end|>",
vars: PromptVars{
Prompt: "What are the potion ingredients?",
},
want: "<|im_start|>user\nWhat are the potion ingredients?<|im_end|><|im_start|>assistant\n",
},
}
for _, tt := range tests {
m := Model{Template: tt.template}
t.Run(tt.name, func(t *testing.T) {
got, err := m.PreResponsePrompt(tt.vars)
if (err != nil) != tt.wantErr {
t.Errorf("PreResponsePrompt() error = %v, wantErr %v", err, tt.wantErr)
return
}
if got != tt.want {
t.Errorf("PreResponsePrompt() got = %v, want %v", got, tt.want)
}
})
}
}
func TestModel_PostResponsePrompt(t *testing.T) {
tests := []struct {
name string
template string
vars PromptVars
want string
wantErr bool
}{
{
name: "No Response in Template",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
vars: PromptVars{
Response: "I don't know.",
},
want: "I don't know.",
},
{
name: "Response in Template",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
vars: PromptVars{
Response: "I don't know.",
},
want: "I don't know.",
},
{
name: "Response in Template with Trailing Formatting",
template: "<|im_start|>user\n{{ .Prompt }}<|im_end|><|im_start|>assistant\n{{ .Response }}<|im_end|>",
vars: PromptVars{
Response: "I don't know.",
},
want: "I don't know.<|im_end|>",
},
{
name: "Response in Template with Alternative Formatting",
template: "<|im_start|>user\n{{.Prompt}}<|im_end|><|im_start|>assistant\n{{.Response}}<|im_end|>",
vars: PromptVars{
Response: "I don't know.",
},
want: "I don't know.<|im_end|>",
},
}
for _, tt := range tests {
m := Model{Template: tt.template}
t.Run(tt.name, func(t *testing.T) {
got, err := m.PostResponseTemplate(tt.vars)
if (err != nil) != tt.wantErr {
t.Errorf("PostResponseTemplate() error = %v, wantErr %v", err, tt.wantErr)
return
}
if got != tt.want {
t.Errorf("PostResponseTemplate() got = %v, want %v", got, tt.want)
}
})
}
}
func TestModel_PreResponsePrompt_PostResponsePrompt(t *testing.T) {
tests := []struct {
name string
template string
preVars PromptVars
postVars PromptVars
want string
wantErr bool
}{
{
name: "Response in Template",
template: "<|im_start|>user\n{{.Prompt}}<|im_end|><|im_start|>assistant\n{{.Response}}<|im_end|>",
preVars: PromptVars{
Prompt: "What are the potion ingredients?",
},
postVars: PromptVars{
Prompt: "What are the potion ingredients?",
Response: "Sugar.",
},
want: "<|im_start|>user\nWhat are the potion ingredients?<|im_end|><|im_start|>assistant\nSugar.<|im_end|>",
},
{
name: "No Response in Template",
template: "<|im_start|>user\n{{.Prompt}}<|im_end|><|im_start|>assistant\n",
preVars: PromptVars{
Prompt: "What are the potion ingredients?",
},
postVars: PromptVars{
Prompt: "What are the potion ingredients?",
Response: "Spice.",
},
want: "<|im_start|>user\nWhat are the potion ingredients?<|im_end|><|im_start|>assistant\nSpice.",
},
}
for _, tt := range tests {
m := Model{Template: tt.template}
t.Run(tt.name, func(t *testing.T) {
pre, err := m.PreResponsePrompt(tt.preVars)
if (err != nil) != tt.wantErr {
t.Errorf("PreResponsePrompt() error = %v, wantErr %v", err, tt.wantErr)
return
}
post, err := m.PostResponseTemplate(tt.postVars)
if err != nil {
t.Errorf("PostResponseTemplate() error = %v, wantErr %v", err, tt.wantErr)
return
}
result := pre + post
if result != tt.want {
t.Errorf("Prompt() got = %v, want %v", result, tt.want)
}
})
}
}
func TestChat(t *testing.T) {
tests := []struct {
name string
template string
msgs []api.Message
want string
wantErr string
}{
{
name: "Single Message",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
msgs: []api.Message{
{
Role: "system",
Content: "You are a Wizard.",
},
{
Role: "user",
Content: "What are the potion ingredients?",
},
},
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]",
},
{
name: "First Message",
template: "[INST] {{if .First}}Hello!{{end}} {{ .System }} {{ .Prompt }} [/INST]",
msgs: []api.Message{
{
Role: "system",
Content: "You are a Wizard.",
},
{
Role: "user",
Content: "What are the potion ingredients?",
},
{
Role: "assistant",
Content: "eye of newt",
},
{
Role: "user",
Content: "Anything else?",
},
},
want: "[INST] Hello! You are a Wizard. What are the potion ingredients? [/INST]eye of newt[INST] Anything else? [/INST]",
},
{
name: "Message History",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
msgs: []api.Message{
{
Role: "system",
Content: "You are a Wizard.",
},
{
Role: "user",
Content: "What are the potion ingredients?",
},
{
Role: "assistant",
Content: "sugar",
},
{
Role: "user",
Content: "Anything else?",
},
},
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]sugar[INST] Anything else? [/INST]",
},
{
name: "Assistant Only",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
msgs: []api.Message{
{
Role: "assistant",
Content: "everything nice",
},
},
want: "[INST] [/INST]everything nice",
},
{
name: "Invalid Role",
msgs: []api.Message{
{
Role: "not-a-role",
Content: "howdy",
},
},
wantErr: "invalid role: not-a-role",
},
}
for _, tt := range tests {
m := Model{
Template: tt.template,
}
t.Run(tt.name, func(t *testing.T) {
got, _, err := m.ChatPrompt(tt.msgs)
if tt.wantErr != "" {
if err == nil {
t.Errorf("ChatPrompt() expected error, got nil")
}
if !strings.Contains(err.Error(), tt.wantErr) {
t.Errorf("ChatPrompt() error = %v, wantErr %v", err, tt.wantErr)
}
}
if got != tt.want {
t.Errorf("ChatPrompt() got = %v, want %v", got, tt.want)
}
})
}
}

View File

@@ -1,224 +0,0 @@
package server
import (
"fmt"
"log/slog"
"strings"
"text/template"
"text/template/parse"
"github.com/jmorganca/ollama/api"
)
// isResponseNode checks if the node contains .Response
func isResponseNode(node *parse.ActionNode) bool {
for _, cmd := range node.Pipe.Cmds {
for _, arg := range cmd.Args {
if fieldNode, ok := arg.(*parse.FieldNode); ok && len(fieldNode.Ident) > 0 {
if fieldNode.Ident[0] == "Response" {
return true
}
}
}
}
return false
}
// formatTemplateForResponse formats the template AST to:
// 1. remove all nodes after the first .Response (if generate=true)
// 2. add a .Response node to the end if it doesn't exist
// TODO(jmorganca): this should recursively cut the template before the first .Response
func formatTemplateForResponse(tmpl *template.Template, generate bool) {
var found bool
for i, node := range tmpl.Tree.Root.Nodes {
if actionNode, ok := node.(*parse.ActionNode); ok {
if isResponseNode(actionNode) {
found = true
if generate {
tmpl.Tree.Root.Nodes = tmpl.Tree.Root.Nodes[:i+1]
break
}
}
}
}
if !found {
// add the response node if it doesn't exist
responseFieldNode := &parse.FieldNode{NodeType: parse.NodeField, Ident: []string{"Response"}}
responsePipeNode := &parse.PipeNode{NodeType: parse.NodePipe, Cmds: []*parse.CommandNode{{NodeType: parse.NodeCommand, Args: []parse.Node{responseFieldNode}}}}
responseActionNode := &parse.ActionNode{NodeType: parse.NodeAction, Pipe: responsePipeNode}
tmpl.Tree.Root.Nodes = append(tmpl.Tree.Root.Nodes, responseActionNode)
}
}
// Prompt renders a prompt from a template. If generate is set to true,
// the response and parts of the template following it are not rendered
func Prompt(tmpl, system, prompt, response string, generate bool) (string, error) {
parsed, err := template.New("").Option("missingkey=zero").Parse(tmpl)
if err != nil {
return "", err
}
formatTemplateForResponse(parsed, generate)
vars := map[string]any{
"System": system,
"Prompt": prompt,
"Response": response,
}
var sb strings.Builder
if err := parsed.Execute(&sb, vars); err != nil {
return "", err
}
return sb.String(), nil
}
func countTokens(tmpl string, system string, prompt string, response string, encode func(string) ([]int, error)) (int, error) {
rendered, err := Prompt(tmpl, system, prompt, response, false)
if err != nil {
return 0, err
}
tokens, err := encode(rendered)
if err != nil {
slog.Error("failed to encode prompt", "err", err)
return 0, err
}
return len(tokens), err
}
// ChatPrompt builds up a prompt from a series of messages, truncating based on context window size
func ChatPrompt(tmpl string, system string, messages []api.Message, window int, encode func(string) ([]int, error)) (string, error) {
type prompt struct {
System string
Prompt string
Response string
images []int
tokens int
}
var p prompt
// Set the first system prompt to the model's system prompt
if system != "" {
p.System = system
}
// iterate through messages to build up {system,user,response} prompts
var imgId int
var prompts []prompt
for _, msg := range messages {
switch strings.ToLower(msg.Role) {
case "system":
if p.System != "" || p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.System = msg.Content
case "user":
if p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.Prompt = msg.Content
for range msg.Images {
p.Prompt += fmt.Sprintf(" [img-%d]", imgId)
p.images = append(p.images, imgId)
imgId += 1
}
case "assistant":
if p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.Response = msg.Content
default:
return "", fmt.Errorf("invalid role: %s, role must be one of [system, user, assistant]", msg.Role)
}
}
// add final prompt
if p.System != "" || p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
}
// calculate token lengths for each prompt, estimating 768 tokens per images
for i, p := range prompts {
tokens, err := countTokens(tmpl, p.System, p.Prompt, p.Response, encode)
if err != nil {
return "", err
}
prompts[i].tokens = tokens + len(prompts[i].images)*768
}
// truncate images and prompts starting from the beginning of the list
// until either one prompt remains or the total tokens fits the context window
// TODO (jmorganca): this doesn't account for the context window room required for the response
for {
var required int
for _, p := range prompts {
required += p.tokens
}
required += 1 // for bos token
if required <= window {
slog.Debug("prompt now fits in context window", "required", required, "window", window)
break
}
prompt := &prompts[0]
if len(prompt.images) > 1 {
img := prompt.images[0]
slog.Debug("prompt longer than context window, removing image", "id", img, "required", required, "window", window)
prompt.images = prompt.images[1:]
prompt.Prompt = strings.Replace(prompt.Prompt, fmt.Sprintf(" [img-%d]", img), "", 1)
prompt.tokens -= 768
continue
}
if len(prompts) > 1 {
slog.Debug("required tokens longer than context window, removing first prompt", "prompt", prompts[0].tokens, "required", required, "window", window)
system := prompt.System
prompts = prompts[1:]
if system != "" && prompts[0].System == "" {
prompts[0].System = system
tokens, err := countTokens(tmpl, prompts[0].System, prompts[0].Prompt, prompts[0].Response, encode)
if err != nil {
return "", err
}
prompts[0].tokens = tokens + len(prompts[0].images)*768
}
continue
}
// stop truncating if there's only one prompt left
break
}
var sb strings.Builder
for i, p := range prompts {
// last prompt should leave the response unrendered (for completion)
rendered, err := Prompt(tmpl, p.System, p.Prompt, p.Response, i == len(prompts)-1)
if err != nil {
return "", err
}
sb.WriteString(rendered)
}
return sb.String(), nil
}

View File

@@ -1,234 +0,0 @@
package server
import (
"strings"
"testing"
"github.com/jmorganca/ollama/api"
)
func TestPrompt(t *testing.T) {
tests := []struct {
name string
template string
system string
prompt string
response string
generate bool
want string
}{
{
name: "simple prompt",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]",
},
{
name: "implicit response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]I don't know.",
},
{
name: "response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST] I don't know.",
},
{
name: "cut",
template: "<system>{{ .System }}</system><user>{{ .Prompt }}</user><assistant>{{ .Response }}</assistant>",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
generate: true,
want: "<system>You are a Wizard.</system><user>What are the potion ingredients?</user><assistant>I don't know.",
},
{
name: "nocut",
template: "<system>{{ .System }}</system><user>{{ .Prompt }}</user><assistant>{{ .Response }}</assistant>",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "<system>You are a Wizard.</system><user>What are the potion ingredients?</user><assistant>I don't know.</assistant>",
},
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := Prompt(tc.template, tc.system, tc.prompt, tc.response, tc.generate)
if err != nil {
t.Errorf("error = %v", err)
}
if got != tc.want {
t.Errorf("got = %v, want %v", got, tc.want)
}
})
}
}
func TestChatPrompt(t *testing.T) {
tests := []struct {
name string
template string
system string
messages []api.Message
window int
want string
}{
{
name: "simple prompt",
template: "[INST] {{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "user", Content: "Hello"},
},
window: 1024,
want: "[INST] Hello [/INST]",
},
{
name: "with default system message",
system: "You are a Wizard.",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "user", Content: "Hello"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]",
},
{
name: "with system message",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]",
},
{
name: "with response",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST] I am?",
},
{
name: "with implicit response",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]I am?",
},
{
name: "with conversation",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }} ",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "What are the potion ingredients?"},
{Role: "assistant", Content: "sugar"},
{Role: "user", Content: "Anything else?"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> What are the potion ingredients? [/INST] sugar [INST] Anything else? [/INST] ",
},
{
name: "with truncation",
template: "{{ .System }} {{ .Prompt }} {{ .Response }} ",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
{Role: "user", Content: "Why is the sky blue?"},
{Role: "assistant", Content: "The sky is blue from rayleigh scattering"},
},
window: 10,
want: "You are a Wizard. Why is the sky blue? The sky is blue from rayleigh scattering",
},
{
name: "images",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello", Images: []api.ImageData{[]byte("base64")}},
},
window: 1024,
want: "You are a Wizard. Hello [img-0]",
},
{
name: "images truncated",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello", Images: []api.ImageData{[]byte("img1"), []byte("img2")}},
},
window: 1024,
want: "You are a Wizard. Hello [img-1]",
},
{
name: "empty list",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{},
window: 1024,
want: "",
},
{
name: "empty list default system",
system: "You are a Wizard.",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{},
window: 1024,
want: "You are a Wizard. ",
},
{
name: "empty user message",
system: "You are a Wizard.",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "user", Content: ""},
},
window: 1024,
want: "You are a Wizard. ",
},
{
name: "empty prompt",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }} ",
messages: []api.Message{
{Role: "user", Content: ""},
},
window: 1024,
want: "",
},
}
encode := func(s string) ([]int, error) {
words := strings.Fields(s)
return make([]int, len(words)), nil
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := ChatPrompt(tc.template, tc.system, tc.messages, tc.window, encode)
if err != nil {
t.Errorf("error = %v", err)
}
if got != tc.want {
t.Errorf("got = %v, want %v", got, tc.want)
}
})
}
}

View File

@@ -22,12 +22,10 @@ import (
"github.com/gin-contrib/cors"
"github.com/gin-gonic/gin"
"golang.org/x/exp/slices"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/gpu"
"github.com/jmorganca/ollama/llm"
"github.com/jmorganca/ollama/openai"
"github.com/jmorganca/ollama/parser"
"github.com/jmorganca/ollama/version"
)
@@ -137,12 +135,6 @@ func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options
return opts, nil
}
func isSupportedImageType(image []byte) bool {
contentType := http.DetectContentType(image)
allowedTypes := []string{"image/jpeg", "image/jpg", "image/png"}
return slices.Contains(allowedTypes, contentType)
}
func GenerateHandler(c *gin.Context) {
loaded.mu.Lock()
defer loaded.mu.Unlock()
@@ -173,13 +165,6 @@ func GenerateHandler(c *gin.Context) {
return
}
for _, img := range req.Images {
if !isSupportedImageType(img) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "unsupported image format"})
return
}
}
model, err := GetModel(req.Model)
if err != nil {
var pErr *fs.PathError
@@ -201,21 +186,13 @@ func GenerateHandler(c *gin.Context) {
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = defaultSessionDuration
} else {
sessionDuration = req.KeepAlive.Duration
}
sessionDuration := defaultSessionDuration
if err := load(c, model, opts, sessionDuration); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
// an empty request loads the model
// note: for a short while template was used in lieu
// of `raw` mode so we need to check for it too
if req.Prompt == "" && req.Template == "" && req.System == "" {
c.JSON(http.StatusOK, api.GenerateResponse{
CreatedAt: time.Now().UTC(),
@@ -228,52 +205,43 @@ func GenerateHandler(c *gin.Context) {
checkpointLoaded := time.Now()
var prompt string
var promptVars PromptVars
switch {
case req.Raw:
prompt = req.Prompt
case req.Prompt != "":
if req.Template == "" {
req.Template = model.Template
if req.Template != "" {
// override the default model template
model.Template = req.Template
}
if req.System == "" {
req.System = model.System
}
slog.Debug("generate handler", "prompt", req.Prompt)
slog.Debug("generate handler", "template", req.Template)
slog.Debug("generate handler", "system", req.System)
var sb strings.Builder
var rebuild strings.Builder
if req.Context != nil {
prev, err := loaded.runner.Decode(c.Request.Context(), req.Context)
// TODO: context is deprecated, at some point the context logic within this conditional should be removed
prevCtx, err := loaded.runner.Decode(c.Request.Context(), req.Context)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
sb.WriteString(prev)
// Remove leading spaces from prevCtx if present
prevCtx = strings.TrimPrefix(prevCtx, " ")
rebuild.WriteString(prevCtx)
}
// write image tags
// TODO: limit the number of images to fit in the context similar to the chat endpoint
for i := range req.Images {
req.Prompt += fmt.Sprintf(" [img-%d]", i)
promptVars = PromptVars{
System: req.System,
Prompt: req.Prompt,
First: len(req.Context) == 0,
}
p, err := Prompt(req.Template, req.System, req.Prompt, "", true)
p, err := model.PreResponsePrompt(promptVars)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
sb.WriteString(p)
prompt = sb.String()
rebuild.WriteString(p)
prompt = rebuild.String()
}
slog.Debug("generate handler", "prompt", prompt)
ch := make(chan any)
var generated strings.Builder
go func() {
@@ -308,39 +276,30 @@ func GenerateHandler(c *gin.Context) {
resp.LoadDuration = checkpointLoaded.Sub(checkpointStart)
if !req.Raw {
p, err := Prompt(req.Template, req.System, req.Prompt, generated.String(), false)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
// TODO (jmorganca): encode() should not strip special tokens
tokens, err := loaded.runner.Encode(c.Request.Context(), p)
// append the generated text to the history and template it if needed
promptVars.Response = generated.String()
result, err := model.PostResponseTemplate(promptVars)
if err != nil {
ch <- gin.H{"error": err.Error()}
return
}
resp.Context = append(req.Context, tokens...)
embd, err := loaded.runner.Encode(c.Request.Context(), prompt+result)
if err != nil {
ch <- gin.H{"error": err.Error()}
return
}
resp.Context = embd
}
}
ch <- resp
}
var images []llm.ImageData
for i := range req.Images {
images = append(images, llm.ImageData{
ID: i,
Data: req.Images[i],
})
}
// Start prediction
predictReq := llm.PredictOpts{
Prompt: prompt,
Format: req.Format,
Images: images,
Images: req.Images,
Options: opts,
}
if err := loaded.runner.Predict(c.Request.Context(), predictReq, fn); err != nil {
@@ -419,14 +378,7 @@ func EmbeddingHandler(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = defaultSessionDuration
} else {
sessionDuration = req.KeepAlive.Duration
}
sessionDuration := defaultSessionDuration
if err := load(c, model, opts, sessionDuration); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
@@ -707,7 +659,6 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
}
modelDetails := api.ModelDetails{
ParentModel: model.ParentModel,
Format: model.Config.ModelFormat,
Family: model.Config.ModelFamily,
Families: model.Config.ModelFamilies,
@@ -723,17 +674,11 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
model.Template = req.Template
}
msgs := make([]api.Message, 0)
for _, msg := range model.Messages {
msgs = append(msgs, api.Message{Role: msg.Role, Content: msg.Content})
}
resp := &api.ShowResponse{
License: strings.Join(model.License, "\n"),
System: model.System,
Template: model.Template,
Details: modelDetails,
Messages: msgs,
}
var params []string
@@ -951,9 +896,6 @@ func (s *Server) GenerateRoutes() http.Handler {
r.POST("/api/blobs/:digest", CreateBlobHandler)
r.HEAD("/api/blobs/:digest", HeadBlobHandler)
// Compatibility endpoints
r.POST("/v1/chat/completions", openai.Middleware(), ChatHandler)
for _, method := range []string{http.MethodGet, http.MethodHead} {
r.Handle(method, "/", func(c *gin.Context) {
c.String(http.StatusOK, "Ollama is running")
@@ -969,26 +911,13 @@ func (s *Server) GenerateRoutes() http.Handler {
}
func Serve(ln net.Listener) error {
level := slog.LevelInfo
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
level = slog.LevelDebug
var programLevel = new(slog.LevelVar)
h := slog.NewTextHandler(os.Stderr, &slog.HandlerOptions{Level: programLevel, AddSource: true})
slog.SetDefault(slog.New(h))
programLevel.Set(slog.LevelDebug)
slog.Debug("Debug logging enabled")
}
handler := slog.NewTextHandler(os.Stderr, &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))
if noprune := os.Getenv("OLLAMA_NOPRUNE"); noprune == "" {
// clean up unused layers and manifests
if err := PruneLayers(); err != nil {
@@ -1091,20 +1020,6 @@ func streamResponse(c *gin.Context, ch chan any) {
})
}
// ChatPrompt builds up a prompt from a series of messages for the currently `loaded` model
func chatPrompt(ctx context.Context, messages []api.Message) (string, error) {
encode := func(s string) ([]int, error) {
return loaded.runner.Encode(ctx, s)
}
prompt, err := ChatPrompt(loaded.Model.Template, loaded.Model.System, messages, loaded.Options.NumCtx, encode)
if err != nil {
return "", err
}
return prompt, nil
}
func ChatHandler(c *gin.Context) {
loaded.mu.Lock()
defer loaded.mu.Unlock()
@@ -1152,58 +1067,26 @@ func ChatHandler(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = defaultSessionDuration
} else {
sessionDuration = req.KeepAlive.Duration
}
sessionDuration := defaultSessionDuration
if err := load(c, model, opts, sessionDuration); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
// an empty request loads the model
if len(req.Messages) == 0 {
c.JSON(http.StatusOK, api.ChatResponse{CreatedAt: time.Now().UTC(), Model: req.Model, Done: true, Message: api.Message{Role: "assistant"}})
return
}
checkpointLoaded := time.Now()
prompt, err := chatPrompt(c.Request.Context(), req.Messages)
prompt, images, err := model.ChatPrompt(req.Messages)
if err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
// an empty request loads the model
if len(req.Messages) == 0 || prompt == "" {
resp := api.ChatResponse{
CreatedAt: time.Now().UTC(),
Model: req.Model,
Done: true,
Message: api.Message{Role: "assistant"},
}
c.JSON(http.StatusOK, resp)
return
}
// only send images that are in the prompt
var i int
var images []llm.ImageData
for _, m := range req.Messages {
for _, img := range m.Images {
if !isSupportedImageType(img) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "unsupported image format"})
return
}
if strings.Contains(prompt, fmt.Sprintf("[img-%d]", i)) {
images = append(images, llm.ImageData{Data: img, ID: i})
}
i += 1
}
}
slog.Debug("chat handler", "prompt", prompt, "images", len(images))
ch := make(chan any)
go func() {

View File

@@ -16,7 +16,6 @@ import (
"github.com/stretchr/testify/assert"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/llm"
"github.com/jmorganca/ollama/parser"
"github.com/jmorganca/ollama/version"
)
@@ -240,27 +239,3 @@ func Test_Routes(t *testing.T) {
}
}
type MockLLM struct {
encoding []int
}
func (llm *MockLLM) Predict(ctx context.Context, pred llm.PredictOpts, fn func(llm.PredictResult)) error {
return nil
}
func (llm *MockLLM) Encode(ctx context.Context, prompt string) ([]int, error) {
return llm.encoding, nil
}
func (llm *MockLLM) Decode(ctx context.Context, tokens []int) (string, error) {
return "", nil
}
func (llm *MockLLM) Embedding(ctx context.Context, input string) ([]float64, error) {
return []float64{}, nil
}
func (llm *MockLLM) Close() {
// do nothing
}