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v0.4.0
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parth/disa
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2
.github/workflows/test.yaml
vendored
2
.github/workflows/test.yaml
vendored
@@ -281,7 +281,7 @@ jobs:
|
||||
shell: bash
|
||||
- uses: golangci/golangci-lint-action@v6
|
||||
with:
|
||||
args: --timeout 8m0s -v
|
||||
args: --timeout 10m0s -v
|
||||
test:
|
||||
strategy:
|
||||
matrix:
|
||||
|
||||
66
Dockerfile
66
Dockerfile
@@ -5,6 +5,8 @@ ARG CUDA_V11_ARCHITECTURES="50;52;53;60;61;62;70;72;75;80;86"
|
||||
ARG CUDA_VERSION_12=12.4.0
|
||||
ARG CUDA_V12_ARCHITECTURES="60;61;62;70;72;75;80;86;87;89;90;90a"
|
||||
ARG ROCM_VERSION=6.1.2
|
||||
ARG JETPACK_6=r36.2.0
|
||||
ARG JETPACK_5=r35.4.1
|
||||
|
||||
### To create a local image for building linux binaries on mac or windows with efficient incremental builds
|
||||
#
|
||||
@@ -13,7 +15,7 @@ ARG ROCM_VERSION=6.1.2
|
||||
#
|
||||
### Then incremental builds will be much faster in this container
|
||||
#
|
||||
# make -C llama -j 10 && go build -trimpath -o dist/linux-amd64/ollama .
|
||||
# make -j 10 && go build -trimpath -o dist/linux-amd64/ollama .
|
||||
#
|
||||
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS unified-builder-amd64
|
||||
ARG CMAKE_VERSION
|
||||
@@ -76,9 +78,9 @@ ARG CUDA_V12_ARCHITECTURES
|
||||
ARG OLLAMA_FAST_BUILD
|
||||
RUN --mount=type=cache,target=/root/.ccache \
|
||||
if grep "^flags" /proc/cpuinfo|grep avx>/dev/null; then \
|
||||
make -C llama -j $(expr $(nproc) / 2 ) ; \
|
||||
make -j $(expr $(nproc) / 2 ) ; \
|
||||
else \
|
||||
make -C llama -j 5 ; \
|
||||
make -j 5 ; \
|
||||
fi
|
||||
|
||||
FROM --platform=linux/arm64 unified-builder-arm64 AS runners-arm64
|
||||
@@ -90,7 +92,46 @@ ARG CUDA_V11_ARCHITECTURES
|
||||
ARG CUDA_V12_ARCHITECTURES
|
||||
ARG OLLAMA_FAST_BUILD
|
||||
RUN --mount=type=cache,target=/root/.ccache \
|
||||
make -C llama -j 8
|
||||
make -j 5
|
||||
|
||||
# Jetsons need to be built in discrete stages
|
||||
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_5} AS runners-jetpack5-arm64
|
||||
ARG GOLANG_VERSION
|
||||
RUN apt-get update && apt-get install -y git curl ccache && \
|
||||
curl -s -L https://dl.google.com/go/go${GOLANG_VERSION}.linux-arm64.tar.gz | tar xz -C /usr/local && \
|
||||
ln -s /usr/local/go/bin/go /usr/local/bin/go && \
|
||||
ln -s /usr/local/go/bin/gofmt /usr/local/bin/gofmt && \
|
||||
apt-get clean && rm -rf /var/lib/apt/lists/*
|
||||
WORKDIR /go/src/github.com/ollama/ollama/
|
||||
COPY . .
|
||||
ARG CGO_CFLAGS
|
||||
ENV GOARCH arm64
|
||||
RUN --mount=type=cache,target=/root/.ccache \
|
||||
make -j 5 cuda_v11 \
|
||||
CUDA_ARCHITECTURES="72;87" \
|
||||
GPU_RUNNER_VARIANT=_jetpack5 \
|
||||
CGO_EXTRA_LDFLAGS_LINUX=-L/usr/local/cuda/lib64/stubs \
|
||||
DIST_LIB_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ollama \
|
||||
DIST_GPU_RUNNER_DEPS_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ollama/cuda_jetpack5
|
||||
|
||||
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_6} AS runners-jetpack6-arm64
|
||||
ARG GOLANG_VERSION
|
||||
RUN apt-get update && apt-get install -y git curl ccache && \
|
||||
curl -s -L https://dl.google.com/go/go${GOLANG_VERSION}.linux-arm64.tar.gz | tar xz -C /usr/local && \
|
||||
ln -s /usr/local/go/bin/go /usr/local/bin/go && \
|
||||
ln -s /usr/local/go/bin/gofmt /usr/local/bin/gofmt && \
|
||||
apt-get clean && rm -rf /var/lib/apt/lists/*
|
||||
WORKDIR /go/src/github.com/ollama/ollama/
|
||||
COPY . .
|
||||
ARG CGO_CFLAGS
|
||||
ENV GOARCH arm64
|
||||
RUN --mount=type=cache,target=/root/.ccache \
|
||||
make -j 5 cuda_v12 \
|
||||
CUDA_ARCHITECTURES="87" \
|
||||
GPU_RUNNER_VARIANT=_jetpack6 \
|
||||
CGO_EXTRA_LDFLAGS_LINUX=-L/usr/local/cuda/lib64/stubs \
|
||||
DIST_LIB_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ollama \
|
||||
DIST_GPU_RUNNER_DEPS_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ollama/cuda_jetpack6
|
||||
|
||||
|
||||
# Intermediate stages used for ./scripts/build_linux.sh
|
||||
@@ -134,12 +175,20 @@ FROM --platform=linux/arm64 builder-arm64 AS build-arm64
|
||||
COPY . .
|
||||
COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/build/ build/
|
||||
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/build/ build/
|
||||
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/build/ build/
|
||||
ARG GOFLAGS
|
||||
ARG CGO_CFLAGS
|
||||
RUN --mount=type=cache,target=/root/.ccache \
|
||||
go build -trimpath -o dist/linux-arm64/bin/ollama .
|
||||
RUN cd dist/linux-$GOARCH && \
|
||||
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
|
||||
RUN cd dist/linux-$GOARCH-jetpack5 && \
|
||||
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH-jetpack5.tgz
|
||||
RUN cd dist/linux-$GOARCH-jetpack6 && \
|
||||
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH-jetpack6.tgz
|
||||
|
||||
FROM --platform=linux/amd64 scratch AS dist-amd64
|
||||
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
|
||||
@@ -180,16 +229,19 @@ RUN rm -rf \
|
||||
FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-amd64
|
||||
RUN apt-get update && \
|
||||
apt-get install -y ca-certificates && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
apt-get clean && rm -rf /var/lib/apt/lists/*
|
||||
COPY --from=container-build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
|
||||
COPY --from=runners-cuda-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
|
||||
|
||||
FROM --platform=linux/arm64 ubuntu:22.04 AS runtime-arm64
|
||||
RUN apt-get update && \
|
||||
apt-get install -y ca-certificates && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
apt-get clean && rm -rf /var/lib/apt/lists/*
|
||||
COPY --from=container-build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/bin/ /bin/
|
||||
COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
|
||||
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ /lib/
|
||||
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ /lib/
|
||||
|
||||
|
||||
# ROCm libraries larger so we keep it distinct from the CPU/CUDA image
|
||||
FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-rocm
|
||||
@@ -198,7 +250,7 @@ FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-rocm
|
||||
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64-rocm/lib/ /lib/
|
||||
RUN apt-get update && \
|
||||
apt-get install -y ca-certificates && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
apt-get clean && rm -rf /var/lib/apt/lists/*
|
||||
COPY --from=container-build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
|
||||
COPY --from=runners-rocm-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
|
||||
|
||||
|
||||
53
README.md
53
README.md
@@ -47,26 +47,28 @@ Ollama supports a list of models available on [ollama.com/library](https://ollam
|
||||
|
||||
Here are some example models that can be downloaded:
|
||||
|
||||
| Model | Parameters | Size | Download |
|
||||
| ------------------ | ---------- | ----- | ------------------------------ |
|
||||
| Llama 3.2 | 3B | 2.0GB | `ollama run llama3.2` |
|
||||
| Llama 3.2 | 1B | 1.3GB | `ollama run llama3.2:1b` |
|
||||
| Llama 3.1 | 8B | 4.7GB | `ollama run llama3.1` |
|
||||
| Llama 3.1 | 70B | 40GB | `ollama run llama3.1:70b` |
|
||||
| Llama 3.1 | 405B | 231GB | `ollama run llama3.1:405b` |
|
||||
| Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` |
|
||||
| Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` |
|
||||
| Gemma 2 | 2B | 1.6GB | `ollama run gemma2:2b` |
|
||||
| Gemma 2 | 9B | 5.5GB | `ollama run gemma2` |
|
||||
| Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` |
|
||||
| Mistral | 7B | 4.1GB | `ollama run mistral` |
|
||||
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
|
||||
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
|
||||
| Starling | 7B | 4.1GB | `ollama run starling-lm` |
|
||||
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
|
||||
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
|
||||
| LLaVA | 7B | 4.5GB | `ollama run llava` |
|
||||
| Solar | 10.7B | 6.1GB | `ollama run solar` |
|
||||
| Model | Parameters | Size | Download |
|
||||
| ------------------ | ---------- | ----- | -------------------------------- |
|
||||
| Llama 3.2 | 3B | 2.0GB | `ollama run llama3.2` |
|
||||
| Llama 3.2 | 1B | 1.3GB | `ollama run llama3.2:1b` |
|
||||
| Llama 3.2 Vision | 11B | 7.9GB | `ollama run llama3.2-vision` |
|
||||
| Llama 3.2 Vision | 90B | 55GB | `ollama run llama3.2-vision:90b` |
|
||||
| Llama 3.1 | 8B | 4.7GB | `ollama run llama3.1` |
|
||||
| Llama 3.1 | 70B | 40GB | `ollama run llama3.1:70b` |
|
||||
| Llama 3.1 | 405B | 231GB | `ollama run llama3.1:405b` |
|
||||
| Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` |
|
||||
| Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` |
|
||||
| Gemma 2 | 2B | 1.6GB | `ollama run gemma2:2b` |
|
||||
| Gemma 2 | 9B | 5.5GB | `ollama run gemma2` |
|
||||
| Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` |
|
||||
| Mistral | 7B | 4.1GB | `ollama run mistral` |
|
||||
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
|
||||
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
|
||||
| Starling | 7B | 4.1GB | `ollama run starling-lm` |
|
||||
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
|
||||
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
|
||||
| LLaVA | 7B | 4.5GB | `ollama run llava` |
|
||||
| Solar | 10.7B | 6.1GB | `ollama run solar` |
|
||||
|
||||
> [!NOTE]
|
||||
> You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
|
||||
@@ -331,8 +333,11 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
||||
- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG on Mac/Windows/Linux)
|
||||
- [G1](https://github.com/bklieger-groq/g1) (Prototype of using prompting strategies to improve the LLM's reasoning through o1-like reasoning chains.)
|
||||
- [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
|
||||
- [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard and said in the meetings)
|
||||
- [Hexabot](https://github.com/hexastack/hexabot) (A conversational AI builder)
|
||||
- [Reddit Rate]((https://github.com/rapidarchitect/reddit_analyzer)) (Search and Rate Reddit topics with a weighted summation)
|
||||
- [Reddit Rate](https://github.com/rapidarchitect/reddit_analyzer) (Search and Rate Reddit topics with a weighted summation)
|
||||
- [VT](https://github.com/vinhnx/vt.ai) (A minimal multimodal AI chat app, with dynamic conversation routing. Supports local models via Ollama)
|
||||
- [Witsy](https://github.com/nbonamy/witsy) (An AI Desktop application avaiable for Mac/Windows/Linux)
|
||||
|
||||
### Terminal
|
||||
|
||||
@@ -359,6 +364,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
||||
- [Ollama eBook Summary](https://github.com/cognitivetech/ollama-ebook-summary/)
|
||||
- [Ollama Mixture of Experts (MOE) in 50 lines of code](https://github.com/rapidarchitect/ollama_moe)
|
||||
- [vim-intelligence-bridge](https://github.com/pepo-ec/vim-intelligence-bridge) Simple interaction of "Ollama" with the Vim editor
|
||||
- [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
|
||||
|
||||
### Apple Vision Pro
|
||||
- [Enchanted](https://github.com/AugustDev/enchanted)
|
||||
@@ -415,6 +421,9 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
||||
- [Ollama PHP](https://github.com/ArdaGnsrn/ollama-php)
|
||||
- [Agents-Flex for Java](https://github.com/agents-flex/agents-flex) with [example](https://github.com/agents-flex/agents-flex/tree/main/agents-flex-llm/agents-flex-llm-ollama/src/test/java/com/agentsflex/llm/ollama)
|
||||
- [Ollama for Swift](https://github.com/mattt/ollama-swift)
|
||||
- [GoLamify](https://github.com/prasad89/golamify)
|
||||
- [Ollama for Haskell](https://github.com/tusharad/ollama-haskell)
|
||||
- [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in unified API)
|
||||
|
||||
### Mobile
|
||||
|
||||
@@ -452,11 +461,13 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
||||
- [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation)
|
||||
- [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities.
|
||||
- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)
|
||||
- [Local AI Helper](https://github.com/ivostoykov/localAI) (Chrome and Firefox extensions that enable interactions with the active tab and customisable API endpoints. Includes secure storage for user prompts.)
|
||||
- [vnc-lm](https://github.com/jk011ru/vnc-lm) (A containerized Discord bot with support for attachments and web links)
|
||||
- [LSP-AI](https://github.com/SilasMarvin/lsp-ai) (Open-source language server for AI-powered functionality)
|
||||
- [QodeAssist](https://github.com/Palm1r/QodeAssist) (AI-powered coding assistant plugin for Qt Creator)
|
||||
- [Obsidian Quiz Generator plugin](https://github.com/ECuiDev/obsidian-quiz-generator)
|
||||
- [TextCraft](https://github.com/suncloudsmoon/TextCraft) (Copilot in Word alternative using Ollama)
|
||||
- [Alfred Ollama](https://github.com/zeitlings/alfred-ollama) (Alfred Workflow)
|
||||
|
||||
### Supported backends
|
||||
|
||||
|
||||
@@ -55,7 +55,7 @@ func checkError(resp *http.Response, body []byte) error {
|
||||
|
||||
// ClientFromEnvironment creates a new [Client] using configuration from the
|
||||
// environment variable OLLAMA_HOST, which points to the network host and
|
||||
// port on which the ollama service is listenting. The format of this variable
|
||||
// port on which the ollama service is listening. The format of this variable
|
||||
// is:
|
||||
//
|
||||
// <scheme>://<host>:<port>
|
||||
|
||||
15
api/types.go
15
api/types.go
@@ -12,7 +12,7 @@ import (
|
||||
"time"
|
||||
)
|
||||
|
||||
// StatusError is an error with and HTTP status code.
|
||||
// StatusError is an error with an HTTP status code and message.
|
||||
type StatusError struct {
|
||||
StatusCode int
|
||||
Status string
|
||||
@@ -57,7 +57,7 @@ type GenerateRequest struct {
|
||||
Template string `json:"template"`
|
||||
|
||||
// Context is the context parameter returned from a previous call to
|
||||
// Generate call. It can be used to keep a short conversational memory.
|
||||
// [Client.Generate]. It can be used to keep a short conversational memory.
|
||||
Context []int `json:"context,omitempty"`
|
||||
|
||||
// Stream specifies whether the response is streaming; it is true by default.
|
||||
@@ -90,14 +90,14 @@ type ChatRequest struct {
|
||||
// Messages is the messages of the chat - can be used to keep a chat memory.
|
||||
Messages []Message `json:"messages"`
|
||||
|
||||
// Stream enable streaming of returned response; true by default.
|
||||
// Stream enables streaming of returned responses; true by default.
|
||||
Stream *bool `json:"stream,omitempty"`
|
||||
|
||||
// Format is the format to return the response in (e.g. "json").
|
||||
Format string `json:"format"`
|
||||
|
||||
// KeepAlive controls how long the model will stay loaded into memory
|
||||
// followin the request.
|
||||
// following the request.
|
||||
KeepAlive *Duration `json:"keep_alive,omitempty"`
|
||||
|
||||
// Tools is an optional list of tools the model has access to.
|
||||
@@ -203,8 +203,8 @@ type Metrics struct {
|
||||
EvalDuration time.Duration `json:"eval_duration,omitempty"`
|
||||
}
|
||||
|
||||
// Options specified in [GenerateRequest], if you add a new option here add it
|
||||
// to the API docs also.
|
||||
// Options specified in [GenerateRequest]. If you add a new option here, also
|
||||
// add it to the API docs.
|
||||
type Options struct {
|
||||
Runner
|
||||
|
||||
@@ -236,7 +236,7 @@ type Runner struct {
|
||||
NumGPU int `json:"num_gpu,omitempty"`
|
||||
MainGPU int `json:"main_gpu,omitempty"`
|
||||
LowVRAM bool `json:"low_vram,omitempty"`
|
||||
F16KV bool `json:"f16_kv,omitempty"`
|
||||
F16KV bool `json:"f16_kv,omitempty"` // Deprecated: This option is ignored
|
||||
LogitsAll bool `json:"logits_all,omitempty"`
|
||||
VocabOnly bool `json:"vocab_only,omitempty"`
|
||||
UseMMap *bool `json:"use_mmap,omitempty"`
|
||||
@@ -613,7 +613,6 @@ func DefaultOptions() Options {
|
||||
NumGPU: -1, // -1 here indicates that NumGPU should be set dynamically
|
||||
NumThread: 0, // let the runtime decide
|
||||
LowVRAM: false,
|
||||
F16KV: true,
|
||||
UseMLock: false,
|
||||
UseMMap: nil,
|
||||
},
|
||||
|
||||
@@ -136,7 +136,7 @@ Type: filesandordirs; Name: "{%TEMP}\ollama*"
|
||||
Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
|
||||
|
||||
[Messages]
|
||||
WizardReady=Ollama Windows Preview
|
||||
WizardReady=Ollama
|
||||
ReadyLabel1=%nLet's get you up and running with your own large language models.
|
||||
SetupAppRunningError=Another Ollama installer is running.%n%nPlease cancel or finish the other installer, then click OK to continue with this install, or Cancel to exit.
|
||||
|
||||
|
||||
@@ -361,7 +361,7 @@ func (t *winTray) showMenu() error {
|
||||
|
||||
boolRet, _, err = pTrackPopupMenu.Call(
|
||||
uintptr(t.menus[0]),
|
||||
TPM_BOTTOMALIGN|TPM_LEFTALIGN,
|
||||
TPM_BOTTOMALIGN|TPM_LEFTALIGN|TPM_RIGHTBUTTON,
|
||||
uintptr(p.X),
|
||||
uintptr(p.Y),
|
||||
0,
|
||||
|
||||
@@ -67,6 +67,7 @@ const (
|
||||
SW_HIDE = 0
|
||||
TPM_BOTTOMALIGN = 0x0020
|
||||
TPM_LEFTALIGN = 0x0000
|
||||
TPM_RIGHTBUTTON = 0x0002
|
||||
WM_CLOSE = 0x0010
|
||||
WM_USER = 0x0400
|
||||
WS_CAPTION = 0x00C00000
|
||||
|
||||
@@ -800,9 +800,9 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
|
||||
case "parameters":
|
||||
fmt.Println(resp.Parameters)
|
||||
case "system":
|
||||
fmt.Println(resp.System)
|
||||
fmt.Print(resp.System)
|
||||
case "template":
|
||||
fmt.Println(resp.Template)
|
||||
fmt.Print(resp.Template)
|
||||
}
|
||||
|
||||
return nil
|
||||
|
||||
@@ -350,7 +350,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
|
||||
return nil, err
|
||||
}
|
||||
}
|
||||
gpuInfo.DependencyPath = libDir
|
||||
gpuInfo.DependencyPath = []string{libDir}
|
||||
|
||||
if gfxOverride == "" {
|
||||
// Only load supported list once
|
||||
|
||||
@@ -111,7 +111,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
|
||||
UnreliableFreeMemory: true,
|
||||
|
||||
ID: strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
|
||||
DependencyPath: libDir,
|
||||
DependencyPath: []string{libDir},
|
||||
MinimumMemory: rocmMinimumMemory,
|
||||
Name: name,
|
||||
Compute: gfx,
|
||||
|
||||
@@ -240,7 +240,7 @@ func GetGPUInfo() GpuInfoList {
|
||||
Library: "cpu",
|
||||
Variant: cpuCapability.String(),
|
||||
ID: "0",
|
||||
DependencyPath: depPath,
|
||||
DependencyPath: []string{depPath},
|
||||
},
|
||||
CPUs: details,
|
||||
},
|
||||
@@ -293,11 +293,11 @@ func GetGPUInfo() GpuInfoList {
|
||||
gpuInfo.DriverMinor = driverMinor
|
||||
variant := cudaVariant(gpuInfo)
|
||||
if depPath != "" {
|
||||
gpuInfo.DependencyPath = depPath
|
||||
gpuInfo.DependencyPath = []string{depPath}
|
||||
// Check for variant specific directory
|
||||
if variant != "" {
|
||||
if _, err := os.Stat(filepath.Join(depPath, "cuda_"+variant)); err == nil {
|
||||
gpuInfo.DependencyPath = filepath.Join(depPath, "cuda_"+variant)
|
||||
gpuInfo.DependencyPath = []string{filepath.Join(depPath, "cuda_"+variant), depPath}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -370,7 +370,7 @@ func GetGPUInfo() GpuInfoList {
|
||||
gpuInfo.FreeMemory = uint64(memInfo.free)
|
||||
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
|
||||
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
|
||||
gpuInfo.DependencyPath = depPath
|
||||
gpuInfo.DependencyPath = []string{depPath}
|
||||
oneapiGPUs = append(oneapiGPUs, gpuInfo)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -4,6 +4,7 @@
|
||||
#include "gpu_info_nvcuda.h"
|
||||
|
||||
void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
|
||||
LOG(resp->ch.verbose, "initializing %s\n", nvcuda_lib_path);
|
||||
CUresult ret;
|
||||
resp->err = NULL;
|
||||
resp->num_devices = 0;
|
||||
@@ -57,8 +58,10 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
|
||||
resp->cudaErr = -1;
|
||||
return;
|
||||
}
|
||||
LOG(resp->ch.verbose, "dlsym: %s - %p\n", l[i].s, *l[i].p);
|
||||
}
|
||||
|
||||
LOG(resp->ch.verbose, "calling cuInit\n");
|
||||
ret = (*resp->ch.cuInit)(0);
|
||||
if (ret != CUDA_SUCCESS) {
|
||||
LOG(resp->ch.verbose, "cuInit err: %d\n", ret);
|
||||
@@ -75,15 +78,18 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
|
||||
resp->ch.driver_minor = 0;
|
||||
|
||||
// Report driver version if we're in verbose mode, ignore errors
|
||||
LOG(resp->ch.verbose, "calling cuDriverGetVersion\n");
|
||||
ret = (*resp->ch.cuDriverGetVersion)(&version);
|
||||
if (ret != CUDA_SUCCESS) {
|
||||
LOG(resp->ch.verbose, "cuDriverGetVersion failed: %d\n", ret);
|
||||
} else {
|
||||
LOG(resp->ch.verbose, "raw version 0x%x\n", version);
|
||||
resp->ch.driver_major = version / 1000;
|
||||
resp->ch.driver_minor = (version - (resp->ch.driver_major * 1000)) / 10;
|
||||
LOG(resp->ch.verbose, "CUDA driver version: %d.%d\n", resp->ch.driver_major, resp->ch.driver_minor);
|
||||
}
|
||||
|
||||
LOG(resp->ch.verbose, "calling cuDeviceGetCount\n");
|
||||
ret = (*resp->ch.cuDeviceGetCount)(&resp->num_devices);
|
||||
if (ret != CUDA_SUCCESS) {
|
||||
LOG(resp->ch.verbose, "cuDeviceGetCount err: %d\n", ret);
|
||||
@@ -94,6 +100,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
|
||||
resp->cudaErr = ret;
|
||||
return;
|
||||
}
|
||||
LOG(resp->ch.verbose, "device count %d\n", resp->num_devices);
|
||||
}
|
||||
|
||||
const int buflen = 256;
|
||||
|
||||
@@ -25,7 +25,7 @@ type GpuInfo struct { // TODO better name maybe "InferenceProcessor"?
|
||||
MinimumMemory uint64 `json:"-"`
|
||||
|
||||
// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
|
||||
DependencyPath string `json:"lib_path,omitempty"`
|
||||
DependencyPath []string `json:"lib_path,omitempty"`
|
||||
|
||||
// Extra environment variables specific to the GPU as list of [key,value]
|
||||
EnvWorkarounds [][2]string `json:"envs,omitempty"`
|
||||
|
||||
75
docs/api.md
75
docs/api.md
@@ -355,7 +355,6 @@ curl http://localhost:11434/api/generate -d '{
|
||||
"num_gpu": 1,
|
||||
"main_gpu": 0,
|
||||
"low_vram": false,
|
||||
"f16_kv": true,
|
||||
"vocab_only": false,
|
||||
"use_mmap": true,
|
||||
"use_mlock": false,
|
||||
@@ -831,10 +830,30 @@ Create a model from a [`Modelfile`](./modelfile.md). It is recommended to set `m
|
||||
|
||||
### Parameters
|
||||
|
||||
- `name`: name of the model to create
|
||||
- `model`: name of the model to create
|
||||
- `modelfile` (optional): contents of the Modelfile
|
||||
- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
|
||||
- `path` (optional): path to the Modelfile
|
||||
- `quantize` (optional): quantize a non-quantized (e.g. float16) model
|
||||
|
||||
#### Quantization types
|
||||
|
||||
| Type | Recommended |
|
||||
| --- | :-: |
|
||||
| q2_K | |
|
||||
| q3_K_L | |
|
||||
| q3_K_M | |
|
||||
| q3_K_S | |
|
||||
| q4_0 | |
|
||||
| q4_1 | |
|
||||
| q4_K_M | * |
|
||||
| q4_K_S | |
|
||||
| q5_0 | |
|
||||
| q5_1 | |
|
||||
| q5_K_M | |
|
||||
| q5_K_S | |
|
||||
| q6_K | |
|
||||
| q8_0 | * |
|
||||
|
||||
### Examples
|
||||
|
||||
@@ -846,14 +865,14 @@ Create a new model from a `Modelfile`.
|
||||
|
||||
```shell
|
||||
curl http://localhost:11434/api/create -d '{
|
||||
"name": "mario",
|
||||
"model": "mario",
|
||||
"modelfile": "FROM llama3\nSYSTEM You are mario from Super Mario Bros."
|
||||
}'
|
||||
```
|
||||
|
||||
##### Response
|
||||
|
||||
A stream of JSON objects. Notice that the final JSON object shows a `"status": "success"`.
|
||||
A stream of JSON objects is returned:
|
||||
|
||||
```json
|
||||
{"status":"reading model metadata"}
|
||||
@@ -869,13 +888,43 @@ A stream of JSON objects. Notice that the final JSON object shows a `"status": "
|
||||
{"status":"success"}
|
||||
```
|
||||
|
||||
#### Quantize a model
|
||||
|
||||
Quantize a non-quantized model.
|
||||
|
||||
##### Request
|
||||
|
||||
```shell
|
||||
curl http://localhost:11434/api/create -d '{
|
||||
"model": "llama3.1:quantized",
|
||||
"modelfile": "FROM llama3.1:8b-instruct-fp16",
|
||||
"quantize": "q4_K_M"
|
||||
}'
|
||||
```
|
||||
|
||||
##### Response
|
||||
|
||||
A stream of JSON objects is returned:
|
||||
|
||||
```
|
||||
{"status":"quantizing F16 model to Q4_K_M"}
|
||||
{"status":"creating new layer sha256:667b0c1932bc6ffc593ed1d03f895bf2dc8dc6df21db3042284a6f4416b06a29"}
|
||||
{"status":"using existing layer sha256:11ce4ee3e170f6adebac9a991c22e22ab3f8530e154ee669954c4bc73061c258"}
|
||||
{"status":"using existing layer sha256:0ba8f0e314b4264dfd19df045cde9d4c394a52474bf92ed6a3de22a4ca31a177"}
|
||||
{"status":"using existing layer sha256:56bb8bd477a519ffa694fc449c2413c6f0e1d3b1c88fa7e3c9d88d3ae49d4dcb"}
|
||||
{"status":"creating new layer sha256:455f34728c9b5dd3376378bfb809ee166c145b0b4c1f1a6feca069055066ef9a"}
|
||||
{"status":"writing manifest"}
|
||||
{"status":"success"}
|
||||
```
|
||||
|
||||
|
||||
### Check if a Blob Exists
|
||||
|
||||
```shell
|
||||
HEAD /api/blobs/:digest
|
||||
```
|
||||
|
||||
Ensures that the file blob used for a FROM or ADAPTER field exists on the server. This is checking your Ollama server and not Ollama.ai.
|
||||
Ensures that the file blob used for a FROM or ADAPTER field exists on the server. This is checking your Ollama server and not ollama.com.
|
||||
|
||||
#### Query Parameters
|
||||
|
||||
@@ -980,7 +1029,7 @@ Show information about a model including details, modelfile, template, parameter
|
||||
|
||||
### Parameters
|
||||
|
||||
- `name`: name of the model to show
|
||||
- `model`: name of the model to show
|
||||
- `verbose`: (optional) if set to `true`, returns full data for verbose response fields
|
||||
|
||||
### Examples
|
||||
@@ -989,7 +1038,7 @@ Show information about a model including details, modelfile, template, parameter
|
||||
|
||||
```shell
|
||||
curl http://localhost:11434/api/show -d '{
|
||||
"name": "llama3.2"
|
||||
"model": "llama3.2"
|
||||
}'
|
||||
```
|
||||
|
||||
@@ -1069,7 +1118,7 @@ Delete a model and its data.
|
||||
|
||||
### Parameters
|
||||
|
||||
- `name`: model name to delete
|
||||
- `model`: model name to delete
|
||||
|
||||
### Examples
|
||||
|
||||
@@ -1077,7 +1126,7 @@ Delete a model and its data.
|
||||
|
||||
```shell
|
||||
curl -X DELETE http://localhost:11434/api/delete -d '{
|
||||
"name": "llama3:13b"
|
||||
"model": "llama3:13b"
|
||||
}'
|
||||
```
|
||||
|
||||
@@ -1095,7 +1144,7 @@ Download a model from the ollama library. Cancelled pulls are resumed from where
|
||||
|
||||
### Parameters
|
||||
|
||||
- `name`: name of the model to pull
|
||||
- `model`: name of the model to pull
|
||||
- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pulling from your own library during development.
|
||||
- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
|
||||
|
||||
@@ -1105,7 +1154,7 @@ Download a model from the ollama library. Cancelled pulls are resumed from where
|
||||
|
||||
```shell
|
||||
curl http://localhost:11434/api/pull -d '{
|
||||
"name": "llama3.2"
|
||||
"model": "llama3.2"
|
||||
}'
|
||||
```
|
||||
|
||||
@@ -1167,7 +1216,7 @@ Upload a model to a model library. Requires registering for ollama.ai and adding
|
||||
|
||||
### Parameters
|
||||
|
||||
- `name`: name of the model to push in the form of `<namespace>/<model>:<tag>`
|
||||
- `model`: name of the model to push in the form of `<namespace>/<model>:<tag>`
|
||||
- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pushing to your library during development.
|
||||
- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
|
||||
|
||||
@@ -1177,7 +1226,7 @@ Upload a model to a model library. Requires registering for ollama.ai and adding
|
||||
|
||||
```shell
|
||||
curl http://localhost:11434/api/push -d '{
|
||||
"name": "mattw/pygmalion:latest"
|
||||
"model": "mattw/pygmalion:latest"
|
||||
}'
|
||||
```
|
||||
|
||||
|
||||
@@ -108,7 +108,7 @@ Custom CPU settings are not currently supported in the new Go server build but w
|
||||
|
||||
#### Containerized Linux Build
|
||||
|
||||
If you have Docker available, you can build linux binaries with `OLLAMA_NEW_RUNNERS=1 ./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
|
||||
If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
|
||||
|
||||
### Windows
|
||||
|
||||
|
||||
@@ -50,6 +50,9 @@ sudo systemctl restart docker
|
||||
docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
|
||||
```
|
||||
|
||||
> [!NOTE]
|
||||
> If you're running on an NVIDIA JetPack system, Ollama can't automatically discover the correct JetPack version. Pass the environment variable JETSON_JETPACK=5 or JETSON_JETPACK=6 to the container to select version 5 or 6.
|
||||
|
||||
### AMD GPU
|
||||
|
||||
To run Ollama using Docker with AMD GPUs, use the `rocm` tag and the following command:
|
||||
|
||||
@@ -32,7 +32,7 @@ ollama run my-model
|
||||
|
||||
Ollama supports importing adapters based on several different model architectures including:
|
||||
|
||||
* Llama (including Llama 2, Llama 3, and Llama 3.1);
|
||||
* Llama (including Llama 2, Llama 3, Llama 3.1, and Llama 3.2);
|
||||
* Mistral (including Mistral 1, Mistral 2, and Mixtral); and
|
||||
* Gemma (including Gemma 1 and Gemma 2)
|
||||
|
||||
@@ -67,14 +67,12 @@ ollama run my-model
|
||||
|
||||
Ollama supports importing models for several different architectures including:
|
||||
|
||||
* Llama (including Llama 2, Llama 3, and Llama 3.1);
|
||||
* Llama (including Llama 2, Llama 3, Llama 3.1, and Llama 3.2);
|
||||
* Mistral (including Mistral 1, Mistral 2, and Mixtral);
|
||||
* Gemma (including Gemma 1 and Gemma 2); and
|
||||
* Phi3
|
||||
|
||||
This includes importing foundation models as well as any fine tuned models which which have been _fused_ with a foundation model.
|
||||
|
||||
|
||||
This includes importing foundation models as well as any fine tuned models which have been _fused_ with a foundation model.
|
||||
## Importing a GGUF based model or adapter
|
||||
|
||||
If you have a GGUF based model or adapter it is possible to import it into Ollama. You can obtain a GGUF model or adapter by:
|
||||
|
||||
@@ -112,6 +112,21 @@ sudo systemctl status ollama
|
||||
> https://www.amd.com/en/support/linux-drivers for best support of your Radeon
|
||||
> GPU.
|
||||
|
||||
## Customizing
|
||||
|
||||
To customize the installation of Ollama, you can edit the systemd service file or the environment variables by running:
|
||||
|
||||
```
|
||||
sudo systemctl edit ollama
|
||||
```
|
||||
|
||||
Alternatively, create an override file manually in `/etc/systemd/system/ollama.service.d/override.conf`:
|
||||
|
||||
```ini
|
||||
[Service]
|
||||
Environment="OLLAMA_DEBUG=1"
|
||||
```
|
||||
|
||||
## Updating
|
||||
|
||||
Update Ollama by running the install script again:
|
||||
@@ -129,7 +144,7 @@ sudo tar -C /usr -xzf ollama-linux-amd64.tgz
|
||||
|
||||
## Installing specific versions
|
||||
|
||||
Use `OLLAMA_VERSION` environment variable with the install script to install a specific version of Ollama, including pre-releases. You can find the version numbers in the [releases page](https://github.com/ollama/ollama/releases).
|
||||
Use `OLLAMA_VERSION` environment variable with the install script to install a specific version of Ollama, including pre-releases. You can find the version numbers in the [releases page](https://github.com/ollama/ollama/releases).
|
||||
|
||||
For example:
|
||||
|
||||
|
||||
@@ -120,7 +120,7 @@ FROM <model directory>
|
||||
The model directory should contain the Safetensors weights for a supported architecture.
|
||||
|
||||
Currently supported model architectures:
|
||||
* Llama (including Llama 2, Llama 3, and Llama 3.1)
|
||||
* Llama (including Llama 2, Llama 3, Llama 3.1, and Llama 3.2)
|
||||
* Mistral (including Mistral 1, Mistral 2, and Mixtral)
|
||||
* Gemma (including Gemma 1 and Gemma 2)
|
||||
* Phi3
|
||||
|
||||
@@ -95,7 +95,9 @@ If none of those resolve the problem, gather additional information and file an
|
||||
|
||||
On linux, AMD GPU access typically requires `video` and/or `render` group membership to access the `/dev/kfd` device. If permissions are not set up correctly, Ollama will detect this and report an error in the server log.
|
||||
|
||||
When running in a container, in some Linux distributions and container runtimes, the ollama process may be unable to access the GPU. Use `ls -ld /dev/kfd /dev/dri /dev/dri/*` on the host system to determine the group assignments on your system, and pass additional `--group-add ...` arguments to the container so it can access the required devices.
|
||||
When running in a container, in some Linux distributions and container runtimes, the ollama process may be unable to access the GPU. Use `ls -lnd /dev/kfd /dev/dri /dev/dri/*` on the host system to determine the **numeric** group IDs on your system, and pass additional `--group-add ...` arguments to the container so it can access the required devices. For example, in the following output `crw-rw---- 1 0 44 226, 0 Sep 16 16:55 /dev/dri/card0` the group ID column is `44`
|
||||
|
||||
If Ollama initially works on the GPU in a docker container, but then switches to running on CPU after some period of time with errors in the server log reporting GPU discovery failures, this can be resolved by disabling systemd cgroup management in Docker. Edit `/etc/docker/daemon.json` on the host and add `"exec-opts": ["native.cgroupdriver=cgroupfs"]` to the docker configuration.
|
||||
|
||||
If you are experiencing problems getting Ollama to correctly discover or use your GPU for inference, the following may help isolate the failure.
|
||||
- `AMD_LOG_LEVEL=3` Enable info log levels in the AMD HIP/ROCm libraries. This can help show more detailed error codes that can help troubleshoot problems
|
||||
|
||||
@@ -10,7 +10,7 @@ This sounds like a typical censored response, but even llama2-uncensored gives a
|
||||
|
||||
So let's figure out how we can use **LangChain** with Ollama to ask our question to the actual document, the Odyssey by Homer, using Python.
|
||||
|
||||
Let's start by asking a simple question that we can get an answer to from the **Llama2** model using **Ollama**. First, we need to install the **LangChain** package:
|
||||
Let's start by asking a simple question that we can get an answer to from the **Llama3** model using **Ollama**. First, we need to install the **LangChain** package:
|
||||
|
||||
`pip install langchain_community`
|
||||
|
||||
|
||||
6
go.mod
6
go.mod
@@ -12,7 +12,7 @@ require (
|
||||
github.com/spf13/cobra v1.7.0
|
||||
github.com/stretchr/testify v1.9.0
|
||||
github.com/x448/float16 v0.8.4
|
||||
golang.org/x/sync v0.3.0
|
||||
golang.org/x/sync v0.9.0
|
||||
)
|
||||
|
||||
require (
|
||||
@@ -22,7 +22,7 @@ require (
|
||||
github.com/mattn/go-runewidth v0.0.14
|
||||
github.com/nlpodyssey/gopickle v0.3.0
|
||||
github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
|
||||
golang.org/x/image v0.14.0
|
||||
golang.org/x/image v0.22.0
|
||||
)
|
||||
|
||||
require (
|
||||
@@ -73,7 +73,7 @@ require (
|
||||
golang.org/x/net v0.25.0 // indirect
|
||||
golang.org/x/sys v0.20.0
|
||||
golang.org/x/term v0.20.0
|
||||
golang.org/x/text v0.15.0
|
||||
golang.org/x/text v0.20.0
|
||||
google.golang.org/protobuf v1.34.1
|
||||
gopkg.in/yaml.v3 v3.0.1 // indirect
|
||||
)
|
||||
|
||||
6
go.sum
6
go.sum
@@ -232,6 +232,8 @@ golang.org/x/image v0.0.0-20201208152932-35266b937fa6/go.mod h1:FeLwcggjj3mMvU+o
|
||||
golang.org/x/image v0.0.0-20210216034530-4410531fe030/go.mod h1:FeLwcggjj3mMvU+oOTbSwawSJRM1uh48EjtB4UJZlP0=
|
||||
golang.org/x/image v0.14.0 h1:tNgSxAFe3jC4uYqvZdTr84SZoM1KfwdC9SKIFrLjFn4=
|
||||
golang.org/x/image v0.14.0/go.mod h1:HUYqC05R2ZcZ3ejNQsIHQDQiwWM4JBqmm6MKANTp4LE=
|
||||
golang.org/x/image v0.22.0 h1:UtK5yLUzilVrkjMAZAZ34DXGpASN8i8pj8g+O+yd10g=
|
||||
golang.org/x/image v0.22.0/go.mod h1:9hPFhljd4zZ1GNSIZJ49sqbp45GKK9t6w+iXvGqZUz4=
|
||||
golang.org/x/lint v0.0.0-20181026193005-c67002cb31c3/go.mod h1:UVdnD1Gm6xHRNCYTkRU2/jEulfH38KcIWyp/GAMgvoE=
|
||||
golang.org/x/lint v0.0.0-20190227174305-5b3e6a55c961/go.mod h1:wehouNa3lNwaWXcvxsM5YxQ5yQlVC4a0KAMCusXpPoU=
|
||||
golang.org/x/lint v0.0.0-20190313153728-d0100b6bd8b3/go.mod h1:6SW0HCj/g11FgYtHlgUYUwCkIfeOF89ocIRzGO/8vkc=
|
||||
@@ -267,6 +269,8 @@ golang.org/x/sync v0.0.0-20201020160332-67f06af15bc9/go.mod h1:RxMgew5VJxzue5/jJ
|
||||
golang.org/x/sync v0.0.0-20210220032951-036812b2e83c/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
|
||||
golang.org/x/sync v0.3.0 h1:ftCYgMx6zT/asHUrPw8BLLscYtGznsLAnjq5RH9P66E=
|
||||
golang.org/x/sync v0.3.0/go.mod h1:FU7BRWz2tNW+3quACPkgCx/L+uEAv1htQ0V83Z9Rj+Y=
|
||||
golang.org/x/sync v0.9.0 h1:fEo0HyrW1GIgZdpbhCRO0PkJajUS5H9IFUztCgEo2jQ=
|
||||
golang.org/x/sync v0.9.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
|
||||
golang.org/x/sys v0.0.0-20180830151530-49385e6e1522/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
|
||||
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
|
||||
golang.org/x/sys v0.0.0-20190312061237-fead79001313/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
@@ -293,6 +297,8 @@ golang.org/x/text v0.3.5/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
|
||||
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
|
||||
golang.org/x/text v0.15.0 h1:h1V/4gjBv8v9cjcR6+AR5+/cIYK5N/WAgiv4xlsEtAk=
|
||||
golang.org/x/text v0.15.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
|
||||
golang.org/x/text v0.20.0 h1:gK/Kv2otX8gz+wn7Rmb3vT96ZwuoxnQlY+HlJVj7Qug=
|
||||
golang.org/x/text v0.20.0/go.mod h1:D4IsuqiFMhST5bX19pQ9ikHC2GsaKyk/oF+pn3ducp4=
|
||||
golang.org/x/tools v0.0.0-20180525024113-a5b4c53f6e8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
|
||||
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
|
||||
golang.org/x/tools v0.0.0-20190114222345-bf090417da8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
|
||||
|
||||
@@ -21,6 +21,8 @@ package llama
|
||||
#cgo cuda CFLAGS: -fPIE -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
|
||||
#cgo cuda CXXFLAGS: -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
|
||||
#cgo cuda CXXFLAGS: -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
|
||||
#cgo cuda_jetpack5 LDFLAGS: -lggml_cuda_jetpack5 -L/usr/local/cuda-11/lib64
|
||||
#cgo cuda_jetpack6 LDFLAGS: -lggml_cuda_jetpack6 -L/usr/local/cuda-12/lib64
|
||||
#cgo cuda_v11 LDFLAGS: -lggml_cuda_v11 -L/usr/local/cuda-11/lib64
|
||||
#cgo cuda_v12 LDFLAGS: -lggml_cuda_v12 -L/usr/local/cuda-12/lib64
|
||||
#cgo darwin,amd64 CFLAGS: -Wno-incompatible-pointer-types-discards-qualifiers
|
||||
@@ -36,8 +38,8 @@ package llama
|
||||
#cgo linux CXXFLAGS: -D_GNU_SOURCE
|
||||
#cgo linux,amd64 LDFLAGS: -L${SRCDIR}/build/Linux/amd64
|
||||
#cgo linux,amd64 LDFLAGS: -L${SRCDIR}/build/Linux/amd64
|
||||
#cgo linux,arm64 CFLAGS: -D__aarch64__ -D__ARM_NEON -D__ARM_FEATURE_FMA -D__ARM_FEATURE_MATMUL_INT8
|
||||
#cgo linux,arm64 CXXFLAGS: -D__aarch64__ -D__ARM_NEON -D__ARM_FEATURE_FMA -D__ARM_FEATURE_MATMUL_INT8
|
||||
#cgo linux,arm64 CFLAGS: -D__aarch64__ -D__ARM_NEON -D__ARM_FEATURE_FMA
|
||||
#cgo linux,arm64 CXXFLAGS: -D__aarch64__ -D__ARM_NEON -D__ARM_FEATURE_FMA
|
||||
#cgo linux,arm64 LDFLAGS: -L${SRCDIR}/build/Linux/arm64
|
||||
#cgo linux,arm64,sve CFLAGS: -march=armv8.6-a+sve
|
||||
#cgo linux,arm64,sve CXXFLAGS: -march=armv8.6-a+sve
|
||||
@@ -382,6 +384,8 @@ func (b *Batch) Add(token int, embed []float32, pos int, logits bool, seqIds ...
|
||||
|
||||
if logits {
|
||||
unsafe.Slice(b.c.logits, b.allocSize())[b.c.n_tokens] = 1
|
||||
} else {
|
||||
unsafe.Slice(b.c.logits, b.allocSize())[b.c.n_tokens] = 0
|
||||
}
|
||||
|
||||
b.c.n_tokens += 1
|
||||
@@ -598,6 +602,10 @@ func (c *Context) SetCrossAttention(state bool) {
|
||||
C.llama_set_cross_attention(c.c, C.bool(state))
|
||||
}
|
||||
|
||||
func (c *Context) Synchronize() {
|
||||
C.llama_synchronize(c.c)
|
||||
}
|
||||
|
||||
// sampling
|
||||
// TODO: this is a temporary wrapper to allow calling C++ code from CGo
|
||||
type SamplingContext struct {
|
||||
|
||||
@@ -58,6 +58,8 @@ endif
|
||||
GPU_COMPILER_CUFLAGS = \
|
||||
$(GPU_COMPILER_FPIC) \
|
||||
$(addprefix -m,$(GPU_RUNNER_CPU_FLAGS)) \
|
||||
-mf16c \
|
||||
-mfma \
|
||||
-parallel-jobs=2 \
|
||||
-c \
|
||||
-O3 \
|
||||
@@ -77,6 +79,9 @@ GPU_COMPILER_CUFLAGS = \
|
||||
-D_CRT_SECURE_NO_WARNINGS \
|
||||
-D_GNU_SOURCE \
|
||||
-D_XOPEN_SOURCE=600 \
|
||||
-DUSE_PROF_API=1 \
|
||||
-std=gnu++14 \
|
||||
-x hip \
|
||||
-mllvm=-amdgpu-early-inline-all=true \
|
||||
-mllvm=-amdgpu-function-calls=false \
|
||||
-Wno-expansion-to-defined \
|
||||
@@ -87,6 +92,12 @@ GPU_COMPILER_CUFLAGS = \
|
||||
-Wno-unused-result \
|
||||
-I.
|
||||
|
||||
# Workaround buggy P2P copy on some windows multi-GPU setups
|
||||
# This workaround breaks linux systems with small system RAM, so only enable on windows
|
||||
ifeq ($(OS),windows)
|
||||
GPU_COMPILER_CUFLAGS += -DGGML_CUDA_NO_PEER_COPY=1
|
||||
endif
|
||||
|
||||
include make/gpu.make
|
||||
|
||||
# Adjust the rules from gpu.make to handle the ROCm dependencies properly
|
||||
|
||||
@@ -20,7 +20,7 @@ GPU_COMPILER_CFLAGS_LINUX = $(CFLAGS) -Xcompiler -fPIC -D_GNU_SOURCE
|
||||
GPU_COMPILER_CXXFLAGS_WIN = $(CXXFLAGS) -D_WIN32_WINNT=0x602
|
||||
GPU_COMPILER_CXXFLAGS_LINUX = $(CXXFLAGS) -Xcompiler -fPIC -D_GNU_SOURCE
|
||||
GPU_LIBS = $(sort $(wildcard $(addsuffix *.$(SHARED_EXT)*,$(addprefix $(GPU_LIB_DIR)/$(SHARED_PREFIX),$(GPU_RUNNER_LIBS_SHORT)))))
|
||||
GPU_DIST_DEPS_LIBS= $(sort $(addprefix $(DIST_LIB_DIR)/,$(notdir $(GPU_LIBS))))
|
||||
GPU_DIST_DEPS_LIBS= $(sort $(addprefix $(DIST_GPU_RUNNER_DEPS_DIR)/,$(notdir $(GPU_LIBS))))
|
||||
|
||||
ifeq ($(OS),linux)
|
||||
CUDA_PATH?=/usr/local/cuda
|
||||
|
||||
@@ -85,7 +85,7 @@ $(RUNNERS_BUILD_DIR)/$(GPU_RUNNER_NAME)/ollama_llama_server$(EXE_EXT): $(RUNNERS
|
||||
GOARCH=$(ARCH) CGO_LDFLAGS="$(TARGET_CGO_LDFLAGS)" go build -buildmode=pie $(GPU_GOFLAGS) -trimpath -tags $(subst $(space),$(comma),$(GPU_RUNNER_CPU_FLAGS) $(GPU_RUNNER_GO_TAGS)) -o $@ ./runner
|
||||
$(RUNNERS_BUILD_DIR)/$(GPU_RUNNER_NAME)/$(SHARED_PREFIX)ggml_$(GPU_RUNNER_NAME).$(SHARED_EXT): $(GPU_RUNNER_OBJS) $(DIST_GPU_RUNNER_LIB_DEPS) $(COMMON_HDRS) $(GPU_RUNNER_HDRS)
|
||||
@-mkdir -p $(dir $@)
|
||||
$(CCACHE) $(GPU_COMPILER) --shared $(GPU_RUNNER_DRIVER_LIB_LINK) -L${DIST_GPU_RUNNER_DEPS_DIR} $(foreach lib, $(GPU_RUNNER_LIBS_SHORT), -l$(lib)) $(GPU_RUNNER_OBJS) -o $@
|
||||
$(CCACHE) $(GPU_COMPILER) --shared -L$(GPU_LIB_DIR) $(GPU_RUNNER_DRIVER_LIB_LINK) -L${DIST_GPU_RUNNER_DEPS_DIR} $(foreach lib, $(GPU_RUNNER_LIBS_SHORT), -l$(lib)) $(GPU_RUNNER_OBJS) -o $@
|
||||
|
||||
# Distribution targets
|
||||
$(RUNNERS_DIST_DIR)/%: $(RUNNERS_BUILD_DIR)/%
|
||||
|
||||
@@ -2,6 +2,7 @@ package main
|
||||
|
||||
import (
|
||||
"errors"
|
||||
"fmt"
|
||||
"log/slog"
|
||||
"reflect"
|
||||
"time"
|
||||
@@ -22,7 +23,11 @@ type InputCache struct {
|
||||
lc *llama.Context
|
||||
}
|
||||
|
||||
func NewInputCache(lc *llama.Context, kvSize int, numSlots int, multiUserCache bool) *InputCache {
|
||||
func NewInputCache(lc *llama.Context, kvSize int, numSlots int, multiUserCache bool) (*InputCache, error) {
|
||||
if kvSize/numSlots < 1 {
|
||||
return nil, fmt.Errorf("must have at least one kv cache entry per parallel sequence (kv: %v parallel: %v)", kvSize, numSlots)
|
||||
}
|
||||
|
||||
slots := make([]InputCacheSlot, numSlots)
|
||||
|
||||
for i := range slots {
|
||||
@@ -37,7 +42,7 @@ func NewInputCache(lc *llama.Context, kvSize int, numSlots int, multiUserCache b
|
||||
slots: slots,
|
||||
multiUserCache: multiUserCache,
|
||||
lc: lc,
|
||||
}
|
||||
}, nil
|
||||
}
|
||||
|
||||
// Locking: Operations on InputCacheSlot (including finding one
|
||||
@@ -58,7 +63,7 @@ type InputCacheSlot struct {
|
||||
lastUsed time.Time
|
||||
}
|
||||
|
||||
func (c *InputCache) LoadCacheSlot(prompt []input, cachePrompt bool) (*InputCacheSlot, []input, int, error) {
|
||||
func (c *InputCache) LoadCacheSlot(prompt []input, cachePrompt bool) (*InputCacheSlot, []input, error) {
|
||||
var slot *InputCacheSlot
|
||||
var numPast int
|
||||
var err error
|
||||
@@ -75,7 +80,7 @@ func (c *InputCache) LoadCacheSlot(prompt []input, cachePrompt bool) (*InputCach
|
||||
slot, numPast, err = c.findBestCacheSlot(prompt)
|
||||
}
|
||||
if err != nil {
|
||||
return nil, nil, 0, err
|
||||
return nil, nil, err
|
||||
}
|
||||
|
||||
if !cachePrompt {
|
||||
@@ -102,7 +107,7 @@ func (c *InputCache) LoadCacheSlot(prompt []input, cachePrompt bool) (*InputCach
|
||||
prompt = prompt[numPast:]
|
||||
slot.Inputs = slot.Inputs[:numPast]
|
||||
|
||||
return slot, prompt, numPast, nil
|
||||
return slot, prompt, nil
|
||||
}
|
||||
|
||||
func (c *InputCache) findLongestCacheSlot(prompt []input) (*InputCacheSlot, int, error) {
|
||||
@@ -194,14 +199,30 @@ func countCommonPrefix(a []input, b []input) int {
|
||||
return count
|
||||
}
|
||||
|
||||
func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int, numDiscard int, numPast int) {
|
||||
// TODO (jessegross): KV cache removal can fail for certain types of models
|
||||
// server.cpp doesn't handle this, though we can be more graceful
|
||||
c.lc.KvCacheSeqRm(slot.Id, numKeep, numKeep+numDiscard)
|
||||
c.lc.KvCacheSeqAdd(slot.Id, numKeep+numDiscard, numPast, -numDiscard)
|
||||
// Frees up space in the KV cache by deleting the oldest half of history and shifting
|
||||
// the newest half into that space (saving numKeep inputs at the beginning).
|
||||
//
|
||||
// Assumes that at least 1 entry can be freed up by shifting (i.e. numKeep < numCtx)
|
||||
func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) {
|
||||
targetFree := (c.numCtx - numKeep) / 2
|
||||
targetFree = max(targetFree, 1)
|
||||
|
||||
for i := numKeep + numDiscard; i < len(slot.Inputs); i++ {
|
||||
slot.Inputs[i-numDiscard] = slot.Inputs[i]
|
||||
currentFree := c.numCtx - len(slot.Inputs)
|
||||
discard := targetFree - currentFree
|
||||
|
||||
if discard <= 0 {
|
||||
return
|
||||
}
|
||||
slot.Inputs = slot.Inputs[:len(slot.Inputs)-numDiscard]
|
||||
|
||||
slog.Debug("context limit hit - shifting", "limit", c.numCtx, "input", len(slot.Inputs),
|
||||
"keep", numKeep, "discard", discard)
|
||||
|
||||
// TODO (jessegross): KV cache removal can fail for certain types of models
|
||||
c.lc.KvCacheSeqRm(slot.Id, numKeep, numKeep+discard)
|
||||
c.lc.KvCacheSeqAdd(slot.Id, numKeep+discard, len(slot.Inputs), -discard)
|
||||
|
||||
for i := numKeep + discard; i < len(slot.Inputs); i++ {
|
||||
slot.Inputs[i-discard] = slot.Inputs[i]
|
||||
}
|
||||
slot.Inputs = slot.Inputs[:len(slot.Inputs)-discard]
|
||||
}
|
||||
|
||||
@@ -68,6 +68,10 @@ func (c *ImageContext) NewEmbed(llamaContext *llama.Context, data []byte, aspect
|
||||
return nil, nil
|
||||
}
|
||||
|
||||
if len(data) <= 0 {
|
||||
return nil, errors.New("received zero length image")
|
||||
}
|
||||
|
||||
hash := c.hashImage(data)
|
||||
|
||||
c.mu.Lock()
|
||||
|
||||
@@ -20,6 +20,8 @@ import (
|
||||
"time"
|
||||
"unicode/utf8"
|
||||
|
||||
"golang.org/x/sync/semaphore"
|
||||
|
||||
"github.com/ollama/ollama/api"
|
||||
"github.com/ollama/ollama/llama"
|
||||
)
|
||||
@@ -34,9 +36,6 @@ type input struct {
|
||||
}
|
||||
|
||||
type Sequence struct {
|
||||
// number of inputs evaluated
|
||||
numPast int
|
||||
|
||||
// batch index
|
||||
iBatch int
|
||||
|
||||
@@ -112,21 +111,15 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
|
||||
params.numKeep = len(inputs)
|
||||
}
|
||||
|
||||
if !params.embedding {
|
||||
// Subtracting 4 ensures that at least 1 input can be discarded during shift
|
||||
params.numKeep = min(params.numKeep, s.cache.numCtx-4)
|
||||
params.numKeep += s.bosToken
|
||||
} else {
|
||||
// Embeddings are 1 shot - just truncate to the context window, without ever shifting
|
||||
params.numKeep = min(params.numKeep, s.cache.numCtx)
|
||||
if s.model.AddBOSToken() {
|
||||
params.numKeep += 1
|
||||
}
|
||||
|
||||
// truncate to fit in context window
|
||||
// Ensure that at least 1 input can be discarded during shift
|
||||
params.numKeep = min(params.numKeep, s.cache.numCtx-1)
|
||||
|
||||
if len(inputs) > s.cache.numCtx {
|
||||
slog.Warn("truncating input prompt", "limit", s.cache.numCtx, "prompt", len(inputs), "numKeep", params.numKeep)
|
||||
newInputs := inputs[:params.numKeep]
|
||||
newInputs = append(newInputs, inputs[len(inputs)-s.cache.numCtx+params.numKeep:]...)
|
||||
inputs = newInputs
|
||||
slog.Warn("input exceeds context length", "prompt", len(inputs), "limit", s.cache.numCtx)
|
||||
}
|
||||
|
||||
var sc *llama.SamplingContext
|
||||
@@ -170,15 +163,13 @@ func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
|
||||
|
||||
for i, part := range parts {
|
||||
// text - tokenize
|
||||
if strings.TrimSpace(part) != "" {
|
||||
tokens, err := s.lc.Model().Tokenize(part, i == 0, true)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
tokens, err := s.lc.Model().Tokenize(part, i == 0, true)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
for _, t := range tokens {
|
||||
inputs = append(inputs, input{token: t})
|
||||
}
|
||||
for _, t := range tokens {
|
||||
inputs = append(inputs, input{token: t})
|
||||
}
|
||||
|
||||
// image - generate image embedding
|
||||
@@ -212,41 +203,51 @@ func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
|
||||
}
|
||||
|
||||
type Server struct {
|
||||
model *llama.Model
|
||||
lc *llama.Context
|
||||
// is the server ready to process requests?
|
||||
// protects access to model and image
|
||||
ready sync.WaitGroup
|
||||
|
||||
// required for image embeddings
|
||||
// loaded model
|
||||
model *llama.Model
|
||||
|
||||
// image model context for multi-modal models
|
||||
image *ImageContext
|
||||
|
||||
// status for external health reporting - loading, ready to serve, etc.
|
||||
status ServerStatus
|
||||
|
||||
// current progress on loading the model
|
||||
progress float32
|
||||
|
||||
// number of simultaneous requests to handle
|
||||
parallel int
|
||||
|
||||
// maximum number of elements in a batch (per sequence)
|
||||
// TODO (jmorganca): make this n_batch
|
||||
batchSize int
|
||||
|
||||
// parallel is the number of parallel requests to handle
|
||||
parallel int
|
||||
// protects access to everything below this line
|
||||
// this is context state needed for decoding
|
||||
mu sync.Mutex
|
||||
|
||||
// seqs is the list of parallel sequences being evaluated
|
||||
// TODO (jmorganca): this can probably be moved into run()
|
||||
// indicates that data is ready for processing
|
||||
cond *sync.Cond
|
||||
|
||||
// decoding state
|
||||
lc *llama.Context
|
||||
|
||||
// the list of simultaneous sequences being evaluated
|
||||
seqs []*Sequence
|
||||
|
||||
// seqs can have a maximum of parallel entries, which
|
||||
// is enfoced by seqSem
|
||||
seqsSem *semaphore.Weighted
|
||||
|
||||
// KV cache
|
||||
cache *InputCache
|
||||
|
||||
// does this model require a beginning of sequence token?
|
||||
bosToken int
|
||||
|
||||
// next sequence for prompt processing to avoid starvation
|
||||
nextSeq int
|
||||
|
||||
// is the server ready to process requests?
|
||||
ready sync.WaitGroup
|
||||
|
||||
mu sync.Mutex
|
||||
|
||||
cond *sync.Cond
|
||||
|
||||
progress float32
|
||||
|
||||
status ServerStatus
|
||||
}
|
||||
|
||||
func (s *Server) allNil() bool {
|
||||
@@ -258,18 +259,6 @@ func (s *Server) allNil() bool {
|
||||
return true
|
||||
}
|
||||
|
||||
func (s *Server) shiftContext(seq *Sequence) {
|
||||
numLeft := seq.numPast - seq.numKeep
|
||||
numDiscard := numLeft / 2
|
||||
|
||||
slog.Debug("context limit hit - shifting", "limit", s.cache.numCtx, "numPast", seq.numPast,
|
||||
"numKeep", seq.numKeep, "numLeft", numLeft, "numDiscard", numDiscard)
|
||||
|
||||
s.cache.ShiftCacheSlot(seq.cache, seq.numKeep, numDiscard, seq.numPast)
|
||||
|
||||
seq.numPast -= numDiscard
|
||||
}
|
||||
|
||||
func flushPending(seq *Sequence) bool {
|
||||
joined := strings.Join(seq.pendingResponses, "")
|
||||
seq.pendingResponses = []string{}
|
||||
@@ -368,18 +357,33 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
|
||||
continue
|
||||
}
|
||||
|
||||
// If an error occurred during the processing of a previous batch then we may have emptied the inputs
|
||||
// without adding a new one. In this case, end the sequence rather than infinite looping.
|
||||
if len(seq.inputs) == 0 {
|
||||
slog.Error("removing sequence due to no input tokens", "index", seqIdx, "cache id", seq.cache.Id)
|
||||
s.removeSequence(seqIdx, "error")
|
||||
continue
|
||||
}
|
||||
|
||||
// if past the num predict limit
|
||||
if seq.numPredict > 0 && seq.numPredicted > seq.numPredict {
|
||||
if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
|
||||
s.removeSequence(seqIdx, "limit")
|
||||
continue
|
||||
}
|
||||
|
||||
if seq.numPast+len(seq.inputs) > s.cache.numCtx {
|
||||
s.shiftContext(seq)
|
||||
}
|
||||
|
||||
var numInputsProcessed int
|
||||
shifted := false
|
||||
|
||||
for i, input := range seq.inputs {
|
||||
if len(seq.cache.Inputs)+1 > s.cache.numCtx {
|
||||
if !shifted {
|
||||
s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
|
||||
shifted = true
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
embedding := input.embed != nil
|
||||
|
||||
// If we don't currently have a batch, use one of the correct type and
|
||||
@@ -403,13 +407,12 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
|
||||
}
|
||||
|
||||
crossAttention = seq.crossAttention
|
||||
batch.Add(input.token, input.embed, seq.numPast, numInputsProcessed+1 == len(seq.inputs), seq.cache.Id)
|
||||
seq.numPast++
|
||||
batch.Add(input.token, input.embed, len(seq.cache.Inputs), i+1 == len(seq.inputs), seq.cache.Id)
|
||||
seq.cache.Inputs = append(seq.cache.Inputs, input)
|
||||
numInputsProcessed++
|
||||
}
|
||||
|
||||
if numInputsProcessed > 0 {
|
||||
seq.cache.Inputs = append(seq.cache.Inputs, seq.inputs[:numInputsProcessed]...)
|
||||
seq.inputs = seq.inputs[numInputsProcessed:]
|
||||
seq.iBatch = batch.NumTokens() - 1
|
||||
}
|
||||
@@ -427,6 +430,13 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
|
||||
return
|
||||
}
|
||||
|
||||
if crossAttention {
|
||||
// synchronize state to ensure the cross attention batch is complete.
|
||||
// needed specifically for multi-GPU systems otherwise an inflight
|
||||
// task may be incorrectly invalidated causing a crash
|
||||
s.lc.Synchronize()
|
||||
}
|
||||
|
||||
for i, seq := range s.seqs {
|
||||
if seq == nil {
|
||||
continue
|
||||
@@ -627,12 +637,17 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
|
||||
return
|
||||
}
|
||||
|
||||
// TODO (jmorganca): add to sequence queue instead of
|
||||
// failing if a slot isn't available
|
||||
// Ensure that a place to put the sequence is available
|
||||
if err := s.seqsSem.Acquire(r.Context(), 1); err != nil {
|
||||
slog.Error("Failed to acquire semaphore", "error", err)
|
||||
return
|
||||
}
|
||||
defer s.seqsSem.Release(1)
|
||||
|
||||
s.mu.Lock()
|
||||
for i, sq := range s.seqs {
|
||||
if sq == nil {
|
||||
seq.cache, seq.inputs, seq.numPast, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
|
||||
seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
|
||||
if err != nil {
|
||||
s.mu.Unlock()
|
||||
http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
|
||||
@@ -711,11 +726,17 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
|
||||
return
|
||||
}
|
||||
|
||||
// TODO (jessegross): Wait for a free slot instead of failing and blocking forever
|
||||
// Ensure that a place to put the sequence is available
|
||||
if err := s.seqsSem.Acquire(r.Context(), 1); err != nil {
|
||||
slog.Error("Failed to acquire semaphore", "error", err)
|
||||
return
|
||||
}
|
||||
defer s.seqsSem.Release(1)
|
||||
|
||||
s.mu.Lock()
|
||||
for i, sq := range s.seqs {
|
||||
if sq == nil {
|
||||
seq.cache, seq.inputs, seq.numPast, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
|
||||
seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
|
||||
if err != nil {
|
||||
s.mu.Unlock()
|
||||
http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
|
||||
@@ -802,10 +823,6 @@ func (s *Server) loadModel(
|
||||
}
|
||||
}
|
||||
|
||||
if s.model.AddBOSToken() {
|
||||
s.bosToken = 1
|
||||
}
|
||||
|
||||
if ppath != "" {
|
||||
var err error
|
||||
s.image, err = NewImageContext(s.lc, ppath)
|
||||
@@ -814,7 +831,10 @@ func (s *Server) loadModel(
|
||||
}
|
||||
}
|
||||
|
||||
s.cache = NewInputCache(s.lc, kvSize, s.parallel, multiUserCache)
|
||||
s.cache, err = NewInputCache(s.lc, kvSize, s.parallel, multiUserCache)
|
||||
if err != nil {
|
||||
panic(err)
|
||||
}
|
||||
|
||||
s.status = ServerStatusReady
|
||||
s.ready.Done()
|
||||
@@ -837,14 +857,8 @@ func main() {
|
||||
mlock := flag.Bool("mlock", false, "force system to keep model in RAM rather than swapping or compressing")
|
||||
tensorSplit := flag.String("tensor-split", "", "fraction of the model to offload to each GPU, comma-separated list of proportions")
|
||||
multiUserCache := flag.Bool("multiuser-cache", false, "optimize input cache algorithm for multiple users")
|
||||
// Expose requirements as a JSON output to stdout
|
||||
requirements := flag.Bool("requirements", false, "print json requirement information")
|
||||
|
||||
// These are either ignored by llama.cpp or have no significance to us
|
||||
_ = flag.Bool("embedding", false, "enable embedding vector output (default: disabled)")
|
||||
_ = flag.Bool("log-disable", false, "disables logging to a file")
|
||||
_ = flag.Bool("memory-f32", false, "use f32 instead of f16 for memory key+value (default: disabled) not recommended: doubles context memory required and no measurable increase in quality")
|
||||
|
||||
flag.Parse()
|
||||
if *requirements {
|
||||
printRequirements(os.Stdout)
|
||||
@@ -873,6 +887,7 @@ func main() {
|
||||
batchSize: *batchSize,
|
||||
parallel: *parallel,
|
||||
seqs: make([]*Sequence, *parallel),
|
||||
seqsSem: semaphore.NewWeighted(int64(*parallel)),
|
||||
status: ServerStatusLoadingModel,
|
||||
}
|
||||
|
||||
|
||||
@@ -186,7 +186,6 @@ func NewLlamaServer(gpus discover.GpuInfoList, model string, ggml *GGML, adapter
|
||||
"--model", model,
|
||||
"--ctx-size", strconv.Itoa(opts.NumCtx),
|
||||
"--batch-size", strconv.Itoa(opts.NumBatch),
|
||||
"--embedding",
|
||||
}
|
||||
|
||||
if opts.NumGPU >= 0 {
|
||||
@@ -218,10 +217,6 @@ func NewLlamaServer(gpus discover.GpuInfoList, model string, ggml *GGML, adapter
|
||||
params = append(params, "--threads", strconv.Itoa(defaultThreads))
|
||||
}
|
||||
|
||||
if !opts.F16KV {
|
||||
params = append(params, "--memory-f32")
|
||||
}
|
||||
|
||||
flashAttnEnabled := envconfig.FlashAttention()
|
||||
|
||||
for _, g := range gpus {
|
||||
@@ -311,9 +306,9 @@ func NewLlamaServer(gpus discover.GpuInfoList, model string, ggml *GGML, adapter
|
||||
|
||||
// Note: we always put the dependency path first
|
||||
// since this was the exact version we compiled/linked against
|
||||
if gpus[0].DependencyPath != "" {
|
||||
if gpus[0].DependencyPath != nil {
|
||||
// assume gpus from the same library have the same dependency path
|
||||
libraryPaths = append([]string{gpus[0].DependencyPath}, libraryPaths...)
|
||||
libraryPaths = append(gpus[0].DependencyPath, libraryPaths...)
|
||||
}
|
||||
|
||||
server := filepath.Join(dir, "ollama_llama_server")
|
||||
@@ -1097,7 +1092,9 @@ func (s *llmServer) EstimatedTotal() uint64 {
|
||||
func (s *llmServer) EstimatedVRAMByGPU(gpuID string) uint64 {
|
||||
for i, gpu := range s.gpus {
|
||||
if gpu.ID == gpuID {
|
||||
return s.estimate.GPUSizes[i]
|
||||
if i < len(s.estimate.GPUSizes) {
|
||||
return s.estimate.GPUSizes[i]
|
||||
}
|
||||
}
|
||||
}
|
||||
return 0
|
||||
|
||||
@@ -65,9 +65,22 @@ var (
|
||||
errInvalidCommand = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
|
||||
)
|
||||
|
||||
type ParserError struct {
|
||||
LineNumber int
|
||||
Msg string
|
||||
}
|
||||
|
||||
func (e *ParserError) Error() string {
|
||||
if e.LineNumber > 0 {
|
||||
return fmt.Sprintf("(line %d): %s", e.LineNumber, e.Msg)
|
||||
}
|
||||
return e.Msg
|
||||
}
|
||||
|
||||
func ParseFile(r io.Reader) (*File, error) {
|
||||
var cmd Command
|
||||
var curr state
|
||||
var currLine int = 1
|
||||
var b bytes.Buffer
|
||||
var role string
|
||||
|
||||
@@ -84,11 +97,18 @@ func ParseFile(r io.Reader) (*File, error) {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
if isNewline(r) {
|
||||
currLine++
|
||||
}
|
||||
|
||||
next, r, err := parseRuneForState(r, curr)
|
||||
if errors.Is(err, io.ErrUnexpectedEOF) {
|
||||
return nil, fmt.Errorf("%w: %s", err, b.String())
|
||||
} else if err != nil {
|
||||
return nil, err
|
||||
return nil, &ParserError{
|
||||
LineNumber: currLine,
|
||||
Msg: err.Error(),
|
||||
}
|
||||
}
|
||||
|
||||
// process the state transition, some transitions need to be intercepted and redirected
|
||||
@@ -96,7 +116,10 @@ func ParseFile(r io.Reader) (*File, error) {
|
||||
switch curr {
|
||||
case stateName:
|
||||
if !isValidCommand(b.String()) {
|
||||
return nil, errInvalidCommand
|
||||
return nil, &ParserError{
|
||||
LineNumber: currLine,
|
||||
Msg: errInvalidCommand.Error(),
|
||||
}
|
||||
}
|
||||
|
||||
// next state sometimes depends on the current buffer value
|
||||
@@ -117,7 +140,10 @@ func ParseFile(r io.Reader) (*File, error) {
|
||||
cmd.Name = b.String()
|
||||
case stateMessage:
|
||||
if !isValidMessageRole(b.String()) {
|
||||
return nil, errInvalidMessageRole
|
||||
return nil, &ParserError{
|
||||
LineNumber: currLine,
|
||||
Msg: errInvalidMessageRole.Error(),
|
||||
}
|
||||
}
|
||||
|
||||
role = b.String()
|
||||
|
||||
@@ -3,6 +3,7 @@ package parser
|
||||
import (
|
||||
"bytes"
|
||||
"encoding/binary"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
||||
"strings"
|
||||
@@ -180,8 +181,15 @@ func TestParseFileBadCommand(t *testing.T) {
|
||||
FROM foo
|
||||
BADCOMMAND param1 value1
|
||||
`
|
||||
parserError := &ParserError{
|
||||
LineNumber: 3,
|
||||
Msg: errInvalidCommand.Error(),
|
||||
}
|
||||
|
||||
_, err := ParseFile(strings.NewReader(input))
|
||||
require.ErrorIs(t, err, errInvalidCommand)
|
||||
if !errors.As(err, &parserError) {
|
||||
t.Errorf("unexpected error: expected: %s, actual: %s", parserError.Error(), err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
func TestParseFileMessages(t *testing.T) {
|
||||
@@ -245,7 +253,10 @@ FROM foo
|
||||
MESSAGE badguy I'm a bad guy!
|
||||
`,
|
||||
nil,
|
||||
errInvalidMessageRole,
|
||||
&ParserError{
|
||||
LineNumber: 3,
|
||||
Msg: errInvalidMessageRole.Error(),
|
||||
},
|
||||
},
|
||||
{
|
||||
`
|
||||
@@ -264,13 +275,35 @@ MESSAGE system`,
|
||||
},
|
||||
}
|
||||
|
||||
for _, c := range cases {
|
||||
for _, tt := range cases {
|
||||
t.Run("", func(t *testing.T) {
|
||||
modelfile, err := ParseFile(strings.NewReader(c.input))
|
||||
require.ErrorIs(t, err, c.err)
|
||||
modelfile, err := ParseFile(strings.NewReader(tt.input))
|
||||
|
||||
if modelfile != nil {
|
||||
assert.Equal(t, c.expected, modelfile.Commands)
|
||||
assert.Equal(t, tt.expected, modelfile.Commands)
|
||||
}
|
||||
|
||||
if tt.err == nil {
|
||||
if err != nil {
|
||||
t.Fatalf("expected no error, but got %v", err)
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
switch tt.err.(type) {
|
||||
case *ParserError:
|
||||
var pErr *ParserError
|
||||
if errors.As(err, &pErr) {
|
||||
// got the correct type of error
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
if errors.Is(err, tt.err) {
|
||||
return
|
||||
}
|
||||
|
||||
t.Fatalf("unexpected error: expected: %v, actual: %v", tt.err, err)
|
||||
})
|
||||
}
|
||||
}
|
||||
@@ -440,7 +473,6 @@ func TestParseFileParameters(t *testing.T) {
|
||||
"num_gpu 1": {"num_gpu", "1"},
|
||||
"main_gpu 1": {"main_gpu", "1"},
|
||||
"low_vram true": {"low_vram", "true"},
|
||||
"f16_kv true": {"f16_kv", "true"},
|
||||
"logits_all true": {"logits_all", "true"},
|
||||
"vocab_only true": {"vocab_only", "true"},
|
||||
"use_mmap true": {"use_mmap", "true"},
|
||||
|
||||
@@ -6,17 +6,18 @@ set -e
|
||||
|
||||
mkdir -p dist
|
||||
|
||||
# These require Xcode v13 or older to target MacOS v11
|
||||
# If installed to an alternate location use the following to enable
|
||||
# export SDKROOT=/Applications/Xcode_12.5.1.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
|
||||
# export DEVELOPER_DIR=/Applications/Xcode_12.5.1.app/Contents/Developer
|
||||
export CGO_CFLAGS=-mmacosx-version-min=11.3
|
||||
export CGO_CXXFLAGS=-mmacosx-version-min=11.3
|
||||
export CGO_LDFLAGS=-mmacosx-version-min=11.3
|
||||
|
||||
for TARGETARCH in arm64 amd64; do
|
||||
echo "Building Go runner darwin $TARGETARCH"
|
||||
rm -rf llama/build
|
||||
GOOS=darwin ARCH=$TARGETARCH GOARCH=$TARGETARCH make -C llama -j 8
|
||||
# These require Xcode v13 or older to target MacOS v11
|
||||
# If installed to an alternate location use the following to enable
|
||||
# export SDKROOT=/Applications/Xcode_12.5.1.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
|
||||
# export DEVELOPER_DIR=/Applications/Xcode_12.5.1.app/Contents/Developer
|
||||
export CGO_CFLAGS=-mmacosx-version-min=11.3
|
||||
export CGO_CXXFLAGS=-mmacosx-version-min=11.3
|
||||
export CGO_LDFLAGS=-mmacosx-version-min=11.3
|
||||
CGO_ENABLED=1 GOOS=darwin GOARCH=$TARGETARCH go build -trimpath -o dist/ollama-darwin-$TARGETARCH
|
||||
CGO_ENABLED=1 GOOS=darwin GOARCH=$TARGETARCH go build -trimpath -cover -o dist/ollama-darwin-$TARGETARCH-cov
|
||||
done
|
||||
|
||||
@@ -4,9 +4,12 @@
|
||||
|
||||
set -eu
|
||||
|
||||
red="$( (/usr/bin/tput bold || :; /usr/bin/tput setaf 1 || :) 2>&-)"
|
||||
plain="$( (/usr/bin/tput sgr0 || :) 2>&-)"
|
||||
|
||||
status() { echo ">>> $*" >&2; }
|
||||
error() { echo "ERROR $*"; exit 1; }
|
||||
warning() { echo "WARNING: $*"; }
|
||||
error() { echo "${red}ERROR:${plain} $*"; exit 1; }
|
||||
warning() { echo "${red}WARNING:${plain} $*"; }
|
||||
|
||||
TEMP_DIR=$(mktemp -d)
|
||||
cleanup() { rm -rf $TEMP_DIR; }
|
||||
@@ -93,6 +96,22 @@ else
|
||||
fi
|
||||
fi
|
||||
|
||||
# Check for NVIDIA JetPack systems with additional downloads
|
||||
if [ -f /etc/nv_tegra_release ] ; then
|
||||
if grep R36 /etc/nv_tegra_release > /dev/null ; then
|
||||
status "Downloading JetPack 6 components"
|
||||
curl --fail --show-error --location --progress-bar \
|
||||
"https://ollama.com/download/ollama-linux-${ARCH}-jetpack6.tgz${VER_PARAM}" | \
|
||||
$SUDO tar -xzf - -C "$OLLAMA_INSTALL_DIR"
|
||||
elif grep R35 /etc/nv_tegra_release > /dev/null ; then
|
||||
status "Downloading JetPack 5 components"
|
||||
curl --fail --show-error --location --progress-bar \
|
||||
"https://ollama.com/download/ollama-linux-${ARCH}-jetpack5.tgz${VER_PARAM}" | \
|
||||
$SUDO tar -xzf - -C "$OLLAMA_INSTALL_DIR"
|
||||
else
|
||||
warning "Unsupported JetPack version detected. GPU may not be supported"
|
||||
fi
|
||||
fi
|
||||
|
||||
install_success() {
|
||||
status 'The Ollama API is now available at 127.0.0.1:11434.'
|
||||
@@ -146,6 +165,12 @@ EOF
|
||||
start_service() { $SUDO systemctl restart ollama; }
|
||||
trap start_service EXIT
|
||||
;;
|
||||
*)
|
||||
warning "systemd is not running"
|
||||
if [ "$IS_WSL2" = true ]; then
|
||||
warning "see https://learn.microsoft.com/en-us/windows/wsl/systemd#how-to-enable-systemd to enable it"
|
||||
fi
|
||||
;;
|
||||
esac
|
||||
}
|
||||
|
||||
@@ -163,6 +188,13 @@ if [ "$IS_WSL2" = true ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Don't attempt to install drivers on Jetson systems
|
||||
if [ -f /etc/nv_tegra_release ] ; then
|
||||
status "NVIDIA JetPack ready."
|
||||
install_success
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Install GPU dependencies on Linux
|
||||
if ! available lspci && ! available lshw; then
|
||||
warning "Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies."
|
||||
|
||||
@@ -13,6 +13,7 @@ import (
|
||||
"io"
|
||||
"log"
|
||||
"log/slog"
|
||||
"net"
|
||||
"net/http"
|
||||
"net/url"
|
||||
"os"
|
||||
@@ -1071,6 +1072,21 @@ func makeRequestWithRetry(ctx context.Context, method string, requestURL *url.UR
|
||||
return nil, errUnauthorized
|
||||
}
|
||||
|
||||
// testMakeRequestDialContext specifies the dial function for the http client in
|
||||
// makeRequest. It can be used to resolve hosts in model names to local
|
||||
// addresses for testing. For example, the model name ("example.com/my/model")
|
||||
// can be directed to push/pull from "127.0.0.1:1234".
|
||||
//
|
||||
// This is not safe to set across goroutines. It should be set in
|
||||
// the main test goroutine, and not by tests marked to run in parallel with
|
||||
// t.Parallel().
|
||||
//
|
||||
// It should be cleared after use, otherwise it will affect other tests.
|
||||
//
|
||||
// Ideally we would have some set this up the stack, but the code is not
|
||||
// structured in a way that makes this easy, so this will have to do for now.
|
||||
var testMakeRequestDialContext func(ctx context.Context, network, addr string) (net.Conn, error)
|
||||
|
||||
func makeRequest(ctx context.Context, method string, requestURL *url.URL, headers http.Header, body io.Reader, regOpts *registryOptions) (*http.Response, error) {
|
||||
if requestURL.Scheme != "http" && regOpts != nil && regOpts.Insecure {
|
||||
requestURL.Scheme = "http"
|
||||
@@ -1105,6 +1121,9 @@ func makeRequest(ctx context.Context, method string, requestURL *url.URL, header
|
||||
}
|
||||
|
||||
resp, err := (&http.Client{
|
||||
Transport: &http.Transport{
|
||||
DialContext: testMakeRequestDialContext,
|
||||
},
|
||||
CheckRedirect: regOpts.CheckRedirect,
|
||||
}).Do(req)
|
||||
if err != nil {
|
||||
|
||||
@@ -32,7 +32,7 @@ func TestChatPrompt(t *testing.T) {
|
||||
mllamaModel := Model{Template: tmpl, ProjectorPaths: []string{"vision"}, Config: ConfigV2{ModelFamilies: []string{"mllama"}}}
|
||||
|
||||
createImg := func(width, height int) ([]byte, error) {
|
||||
img := image.NewRGBA(image.Rect(0, 0, 5, 5))
|
||||
img := image.NewRGBA(image.Rect(0, 0, width, height))
|
||||
var buf bytes.Buffer
|
||||
|
||||
if err := png.Encode(&buf, img); err != nil {
|
||||
|
||||
@@ -540,7 +540,8 @@ func (s *Server) PullHandler(c *gin.Context) {
|
||||
return
|
||||
}
|
||||
|
||||
if err := checkNameExists(name); err != nil {
|
||||
name, err = getExistingName(name)
|
||||
if err != nil {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
@@ -621,19 +622,20 @@ func (s *Server) PushHandler(c *gin.Context) {
|
||||
streamResponse(c, ch)
|
||||
}
|
||||
|
||||
func checkNameExists(name model.Name) error {
|
||||
names, err := Manifests(true)
|
||||
// getExistingName returns the original, on disk name if the input name is a
|
||||
// case-insensitive match, otherwise it returns the input name.
|
||||
func getExistingName(n model.Name) (model.Name, error) {
|
||||
var zero model.Name
|
||||
existing, err := Manifests(true)
|
||||
if err != nil {
|
||||
return err
|
||||
return zero, err
|
||||
}
|
||||
|
||||
for n := range names {
|
||||
if strings.EqualFold(n.Filepath(), name.Filepath()) && n != name {
|
||||
return errors.New("a model with that name already exists")
|
||||
for e := range existing {
|
||||
if n.EqualFold(e) {
|
||||
return e, nil
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
return n, nil
|
||||
}
|
||||
|
||||
func (s *Server) CreateHandler(c *gin.Context) {
|
||||
@@ -652,7 +654,8 @@ func (s *Server) CreateHandler(c *gin.Context) {
|
||||
return
|
||||
}
|
||||
|
||||
if err := checkNameExists(name); err != nil {
|
||||
name, err := getExistingName(name)
|
||||
if err != nil {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
@@ -958,14 +961,19 @@ func (s *Server) CopyHandler(c *gin.Context) {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("source %q is invalid", r.Source)})
|
||||
return
|
||||
}
|
||||
src, err := getExistingName(src)
|
||||
if err != nil {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
|
||||
dst := model.ParseName(r.Destination)
|
||||
if !dst.IsValid() {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("destination %q is invalid", r.Destination)})
|
||||
return
|
||||
}
|
||||
|
||||
if err := checkNameExists(dst); err != nil {
|
||||
dst, err = getExistingName(dst)
|
||||
if err != nil {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
@@ -1390,6 +1398,12 @@ func (s *Server) ChatHandler(c *gin.Context) {
|
||||
return
|
||||
}
|
||||
|
||||
// Error if streaming is enabled and tools are present
|
||||
if req.Stream != nil && *req.Stream && len(req.Tools) > 0 {
|
||||
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "streaming is not supported with tools"})
|
||||
return
|
||||
}
|
||||
|
||||
// expire the runner
|
||||
if len(req.Messages) == 0 && req.KeepAlive != nil && int(req.KeepAlive.Seconds()) == 0 {
|
||||
model, err := GetModel(req.Model)
|
||||
|
||||
@@ -7,13 +7,18 @@ import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io"
|
||||
"io/fs"
|
||||
"math"
|
||||
"math/rand/v2"
|
||||
"net"
|
||||
"net/http"
|
||||
"net/http/httptest"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"sort"
|
||||
"strings"
|
||||
"testing"
|
||||
"unicode"
|
||||
|
||||
"github.com/ollama/ollama/api"
|
||||
"github.com/ollama/ollama/llm"
|
||||
@@ -473,83 +478,129 @@ func Test_Routes(t *testing.T) {
|
||||
}
|
||||
}
|
||||
|
||||
func TestCase(t *testing.T) {
|
||||
func casingShuffle(s string) string {
|
||||
rr := []rune(s)
|
||||
for i := range rr {
|
||||
if rand.N(2) == 0 {
|
||||
rr[i] = unicode.ToUpper(rr[i])
|
||||
} else {
|
||||
rr[i] = unicode.ToLower(rr[i])
|
||||
}
|
||||
}
|
||||
return string(rr)
|
||||
}
|
||||
|
||||
func TestManifestCaseSensitivity(t *testing.T) {
|
||||
t.Setenv("OLLAMA_MODELS", t.TempDir())
|
||||
|
||||
cases := []string{
|
||||
"mistral",
|
||||
"llama3:latest",
|
||||
"library/phi3:q4_0",
|
||||
"registry.ollama.ai/library/gemma:q5_K_M",
|
||||
// TODO: host:port currently fails on windows (#4107)
|
||||
// "localhost:5000/alice/bob:latest",
|
||||
r := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
|
||||
w.WriteHeader(http.StatusOK)
|
||||
io.WriteString(w, `{}`) //nolint:errcheck
|
||||
}))
|
||||
defer r.Close()
|
||||
|
||||
nameUsed := make(map[string]bool)
|
||||
name := func() string {
|
||||
const fqmn = "example/namespace/model:tag"
|
||||
for {
|
||||
v := casingShuffle(fqmn)
|
||||
if nameUsed[v] {
|
||||
continue
|
||||
}
|
||||
nameUsed[v] = true
|
||||
return v
|
||||
}
|
||||
}
|
||||
|
||||
wantStableName := name()
|
||||
|
||||
// checkManifestList tests that there is strictly one manifest in the
|
||||
// models directory, and that the manifest is for the model under test.
|
||||
checkManifestList := func() {
|
||||
t.Helper()
|
||||
|
||||
mandir := filepath.Join(os.Getenv("OLLAMA_MODELS"), "manifests/")
|
||||
var entries []string
|
||||
t.Logf("dir entries:")
|
||||
fsys := os.DirFS(mandir)
|
||||
err := fs.WalkDir(fsys, ".", func(path string, info fs.DirEntry, err error) error {
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
t.Logf(" %s", fs.FormatDirEntry(info))
|
||||
if info.IsDir() {
|
||||
return nil
|
||||
}
|
||||
path = strings.TrimPrefix(path, mandir)
|
||||
entries = append(entries, path)
|
||||
return nil
|
||||
})
|
||||
if err != nil {
|
||||
t.Fatalf("failed to walk directory: %v", err)
|
||||
}
|
||||
|
||||
if len(entries) != 1 {
|
||||
t.Errorf("len(got) = %d, want 1", len(entries))
|
||||
return // do not use Fatal so following steps run
|
||||
}
|
||||
|
||||
g := entries[0] // raw path
|
||||
g = filepath.ToSlash(g)
|
||||
w := model.ParseName(wantStableName).Filepath()
|
||||
w = filepath.ToSlash(w)
|
||||
if g != w {
|
||||
t.Errorf("\ngot: %s\nwant: %s", g, w)
|
||||
}
|
||||
}
|
||||
|
||||
checkOK := func(w *httptest.ResponseRecorder) {
|
||||
t.Helper()
|
||||
if w.Code != http.StatusOK {
|
||||
t.Errorf("code = %d, want 200", w.Code)
|
||||
t.Logf("body: %s", w.Body.String())
|
||||
}
|
||||
}
|
||||
|
||||
var s Server
|
||||
for _, tt := range cases {
|
||||
t.Run(tt, func(t *testing.T) {
|
||||
w := createRequest(t, s.CreateHandler, api.CreateRequest{
|
||||
Name: tt,
|
||||
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, nil, nil)),
|
||||
Stream: &stream,
|
||||
})
|
||||
|
||||
if w.Code != http.StatusOK {
|
||||
t.Fatalf("expected status 200 got %d", w.Code)
|
||||
}
|
||||
|
||||
expect, err := json.Marshal(map[string]string{"error": "a model with that name already exists"})
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
|
||||
t.Run("create", func(t *testing.T) {
|
||||
w = createRequest(t, s.CreateHandler, api.CreateRequest{
|
||||
Name: strings.ToUpper(tt),
|
||||
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, nil, nil)),
|
||||
Stream: &stream,
|
||||
})
|
||||
|
||||
if w.Code != http.StatusBadRequest {
|
||||
t.Fatalf("expected status 500 got %d", w.Code)
|
||||
}
|
||||
|
||||
if !bytes.Equal(w.Body.Bytes(), expect) {
|
||||
t.Fatalf("expected error %s got %s", expect, w.Body.String())
|
||||
}
|
||||
})
|
||||
|
||||
t.Run("pull", func(t *testing.T) {
|
||||
w := createRequest(t, s.PullHandler, api.PullRequest{
|
||||
Name: strings.ToUpper(tt),
|
||||
Stream: &stream,
|
||||
})
|
||||
|
||||
if w.Code != http.StatusBadRequest {
|
||||
t.Fatalf("expected status 500 got %d", w.Code)
|
||||
}
|
||||
|
||||
if !bytes.Equal(w.Body.Bytes(), expect) {
|
||||
t.Fatalf("expected error %s got %s", expect, w.Body.String())
|
||||
}
|
||||
})
|
||||
|
||||
t.Run("copy", func(t *testing.T) {
|
||||
w := createRequest(t, s.CopyHandler, api.CopyRequest{
|
||||
Source: tt,
|
||||
Destination: strings.ToUpper(tt),
|
||||
})
|
||||
|
||||
if w.Code != http.StatusBadRequest {
|
||||
t.Fatalf("expected status 500 got %d", w.Code)
|
||||
}
|
||||
|
||||
if !bytes.Equal(w.Body.Bytes(), expect) {
|
||||
t.Fatalf("expected error %s got %s", expect, w.Body.String())
|
||||
}
|
||||
})
|
||||
})
|
||||
testMakeRequestDialContext = func(ctx context.Context, _, _ string) (net.Conn, error) {
|
||||
var d net.Dialer
|
||||
return d.DialContext(ctx, "tcp", r.Listener.Addr().String())
|
||||
}
|
||||
t.Cleanup(func() { testMakeRequestDialContext = nil })
|
||||
|
||||
t.Logf("creating")
|
||||
checkOK(createRequest(t, s.CreateHandler, api.CreateRequest{
|
||||
// Start with the stable name, and later use a case-shuffled
|
||||
// version.
|
||||
Name: wantStableName,
|
||||
|
||||
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, nil, nil)),
|
||||
Stream: &stream,
|
||||
}))
|
||||
checkManifestList()
|
||||
|
||||
t.Logf("creating (again)")
|
||||
checkOK(createRequest(t, s.CreateHandler, api.CreateRequest{
|
||||
Name: name(),
|
||||
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, nil, nil)),
|
||||
Stream: &stream,
|
||||
}))
|
||||
checkManifestList()
|
||||
|
||||
t.Logf("pulling")
|
||||
checkOK(createRequest(t, s.PullHandler, api.PullRequest{
|
||||
Name: name(),
|
||||
Stream: &stream,
|
||||
Insecure: true,
|
||||
}))
|
||||
checkManifestList()
|
||||
|
||||
t.Logf("copying")
|
||||
checkOK(createRequest(t, s.CopyHandler, api.CopyRequest{
|
||||
Source: name(),
|
||||
Destination: name(),
|
||||
}))
|
||||
checkManifestList()
|
||||
}
|
||||
|
||||
func TestShow(t *testing.T) {
|
||||
|
||||
@@ -130,11 +130,11 @@ func (s *Scheduler) processPending(ctx context.Context) {
|
||||
continue
|
||||
}
|
||||
numParallel := int(envconfig.NumParallel())
|
||||
// TODO (jmorganca): multimodal models don't support parallel yet
|
||||
// TODO (jmorganca): mllama doesn't support parallel yet
|
||||
// see https://github.com/ollama/ollama/issues/4165
|
||||
if len(pending.model.ProjectorPaths) > 0 && numParallel != 1 {
|
||||
if checkMllamaModelFamily(pending.model) && numParallel != 1 {
|
||||
numParallel = 1
|
||||
slog.Warn("multimodal models don't support parallel requests yet")
|
||||
slog.Warn("mllama doesn't support parallel requests yet")
|
||||
}
|
||||
|
||||
for {
|
||||
|
||||
@@ -298,6 +298,13 @@ func (n Name) LogValue() slog.Value {
|
||||
return slog.StringValue(n.String())
|
||||
}
|
||||
|
||||
func (n Name) EqualFold(o Name) bool {
|
||||
return strings.EqualFold(n.Host, o.Host) &&
|
||||
strings.EqualFold(n.Namespace, o.Namespace) &&
|
||||
strings.EqualFold(n.Model, o.Model) &&
|
||||
strings.EqualFold(n.Tag, o.Tag)
|
||||
}
|
||||
|
||||
func isValidLen(kind partKind, s string) bool {
|
||||
switch kind {
|
||||
case kindHost:
|
||||
|
||||
Reference in New Issue
Block a user