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2 Commits
jmorganca/
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bmizerany/
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60
.github/ISSUE_TEMPLATE/10_bug_report.yml
vendored
60
.github/ISSUE_TEMPLATE/10_bug_report.yml
vendored
@@ -1,60 +0,0 @@
|
||||
name: Bug report
|
||||
labels: [bug]
|
||||
description: Something isn't working right.
|
||||
body:
|
||||
- type: textarea
|
||||
id: description
|
||||
attributes:
|
||||
label: What is the issue?
|
||||
description: What happened? What did you expect to happen?
|
||||
validations:
|
||||
required: true
|
||||
- type: dropdown
|
||||
id: os
|
||||
attributes:
|
||||
label: OS
|
||||
description: Which operating system are you using?
|
||||
multiple: true
|
||||
options:
|
||||
- Linux
|
||||
- macOS
|
||||
- Windows
|
||||
- Docker
|
||||
- WSL2
|
||||
validations:
|
||||
required: false
|
||||
- type: dropdown
|
||||
id: gpu
|
||||
attributes:
|
||||
label: GPU
|
||||
description: Which GPU are you using?
|
||||
multiple: true
|
||||
options:
|
||||
- Nvidia
|
||||
- AMD
|
||||
- Intel
|
||||
- Apple
|
||||
- Other
|
||||
validations:
|
||||
required: false
|
||||
- type: dropdown
|
||||
id: cpu
|
||||
attributes:
|
||||
label: CPU
|
||||
description: Which CPU are you using?
|
||||
multiple: true
|
||||
options:
|
||||
- Intel
|
||||
- AMD
|
||||
- Apple
|
||||
- Other
|
||||
validations:
|
||||
required: false
|
||||
- type: input
|
||||
id: version
|
||||
attributes:
|
||||
label: Ollama version
|
||||
description: What version of Ollama are you using? (`ollama --version`)
|
||||
placeholder: e.g., 0.1.32
|
||||
validations:
|
||||
required: false
|
||||
18
.github/ISSUE_TEMPLATE/10_model_request.yml
vendored
Normal file
18
.github/ISSUE_TEMPLATE/10_model_request.yml
vendored
Normal file
@@ -0,0 +1,18 @@
|
||||
name: Model request
|
||||
description: Request a new model for the library
|
||||
labels: [mr]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Please check if your Model request is [already available](https://ollama.com/search) or that you cannot [import it](https://github.com/ollama/ollama/blob/main/docs/import.md#import-a-model) yourself.
|
||||
Tell us about which Model you'd like to see in the library!
|
||||
- type: textarea
|
||||
id: problem
|
||||
attributes:
|
||||
label: What model would you like?
|
||||
description: Please provide a link to the model.
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for filing a model request!
|
||||
6
.github/ISSUE_TEMPLATE/20_feature_request.md
vendored
6
.github/ISSUE_TEMPLATE/20_feature_request.md
vendored
@@ -1,6 +0,0 @@
|
||||
---
|
||||
name: Feature request
|
||||
about: Request a new feature
|
||||
labels: feature request
|
||||
---
|
||||
|
||||
41
.github/ISSUE_TEMPLATE/20_feature_request.yml
vendored
Normal file
41
.github/ISSUE_TEMPLATE/20_feature_request.yml
vendored
Normal file
@@ -0,0 +1,41 @@
|
||||
name: Feature request
|
||||
description: Propose a new feature
|
||||
labels: [needs-triage, fr]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Please check if your feature request is [already filed](https://github.com/ollama/ollama/issues).
|
||||
Tell us about your idea!
|
||||
- type: textarea
|
||||
id: problem
|
||||
attributes:
|
||||
label: What are you trying to do?
|
||||
description: Tell us about the problem you're trying to solve.
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: solution
|
||||
attributes:
|
||||
label: How should we solve this?
|
||||
description: If you have an idea of how you'd like to see this feature work, let us know.
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: alternative
|
||||
attributes:
|
||||
label: What is the impact of not solving this?
|
||||
description: (How) Are you currently working around the issue?
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: context
|
||||
attributes:
|
||||
label: Anything else?
|
||||
description: Any additional context to share, e.g., links
|
||||
validations:
|
||||
required: false
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for filing a feature request!
|
||||
5
.github/ISSUE_TEMPLATE/30_model_request.md
vendored
5
.github/ISSUE_TEMPLATE/30_model_request.md
vendored
@@ -1,5 +0,0 @@
|
||||
---
|
||||
name: Model request
|
||||
about: Request support for a new model to be added to Ollama
|
||||
labels: model request
|
||||
---
|
||||
125
.github/ISSUE_TEMPLATE/90_bug_report.yml
vendored
Normal file
125
.github/ISSUE_TEMPLATE/90_bug_report.yml
vendored
Normal file
@@ -0,0 +1,125 @@
|
||||
name: Bug report
|
||||
description: File a bug report. If you need help, please join our Discord server.
|
||||
labels: [needs-triage, bug]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Please check if your bug is [already filed](https://github.com/ollama/ollama/issues) before filing a new one.
|
||||
- type: textarea
|
||||
id: what-happened
|
||||
attributes:
|
||||
label: What is the issue?
|
||||
description: What happened? What did you expect to happen?
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: what-was-expected
|
||||
attributes:
|
||||
label: What did you expect to see?
|
||||
description: What did you expect to see/happen instead?
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: steps
|
||||
attributes:
|
||||
label: Steps to reproduce
|
||||
description: What are the steps you took that hit this issue?
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: changes
|
||||
attributes:
|
||||
label: Are there any recent changes that introduced the issue?
|
||||
description: If so, what are those changes?
|
||||
validations:
|
||||
required: false
|
||||
- type: dropdown
|
||||
id: os
|
||||
attributes:
|
||||
label: OS
|
||||
description: What OS are you using? You may select more than one.
|
||||
multiple: true
|
||||
options:
|
||||
- Linux
|
||||
- macOS
|
||||
- Windows
|
||||
- Other
|
||||
validations:
|
||||
required: false
|
||||
- type: dropdown
|
||||
id: architecture
|
||||
attributes:
|
||||
label: Architecture
|
||||
description: What architecture are you using? You may select more than one.
|
||||
multiple: true
|
||||
options:
|
||||
- arm64
|
||||
- amd64
|
||||
- x86
|
||||
- Other
|
||||
- type: dropdown
|
||||
id: platform
|
||||
attributes:
|
||||
label: Platform
|
||||
description: What platform are you using? You may select more than one.
|
||||
multiple: true
|
||||
options:
|
||||
- Docker
|
||||
- WSL
|
||||
- WSL2
|
||||
validations:
|
||||
required: false
|
||||
- type: input
|
||||
id: ollama-version
|
||||
attributes:
|
||||
label: Ollama version
|
||||
description: What Ollama version are you using? (`ollama --version`)
|
||||
placeholder: e.g., 1.14.4
|
||||
validations:
|
||||
required: false
|
||||
- type: dropdown
|
||||
id: gpu
|
||||
attributes:
|
||||
label: GPU
|
||||
description: What GPU, if any, are you using? You may select more than one.
|
||||
multiple: true
|
||||
options:
|
||||
- Nvidia
|
||||
- AMD
|
||||
- Intel
|
||||
- Apple
|
||||
- Other
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: gpu-info
|
||||
attributes:
|
||||
label: GPU info
|
||||
description: What GPU info do you have? (`nvidia-smi`, `rocminfo`, `system_profiler SPDisplaysDataType`, etc.)
|
||||
validations:
|
||||
required: false
|
||||
- type: dropdown
|
||||
id: cpu
|
||||
attributes:
|
||||
label: CPU
|
||||
description: What CPU are you using? You may select more than one.
|
||||
multiple: true
|
||||
options:
|
||||
- Intel
|
||||
- AMD
|
||||
- Apple
|
||||
- Other
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: other-software
|
||||
attributes:
|
||||
label: Other software
|
||||
description: What other software are you using that might be related to this issue?
|
||||
validations:
|
||||
required: false
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for filing a bug report!
|
||||
14
Dockerfile
14
Dockerfile
@@ -18,7 +18,7 @@ ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
|
||||
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
|
||||
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
|
||||
ARG CGO_CFLAGS
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
|
||||
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
|
||||
|
||||
FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION-devel-rockylinux8 AS cuda-build-arm64
|
||||
ARG CMAKE_VERSION
|
||||
@@ -28,7 +28,7 @@ ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
|
||||
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
|
||||
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
|
||||
ARG CGO_CFLAGS
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
|
||||
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
|
||||
|
||||
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS rocm-build-amd64
|
||||
ARG CMAKE_VERSION
|
||||
@@ -40,7 +40,7 @@ COPY --from=llm-code / /go/src/github.com/ollama/ollama/
|
||||
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
|
||||
ARG CGO_CFLAGS
|
||||
ARG AMDGPU_TARGETS
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
|
||||
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
|
||||
RUN mkdir /tmp/scratch && \
|
||||
for dep in $(zcat /go/src/github.com/ollama/ollama/llm/build/linux/x86_64/rocm*/bin/deps.txt.gz) ; do \
|
||||
cp ${dep} /tmp/scratch/ || exit 1 ; \
|
||||
@@ -64,11 +64,11 @@ WORKDIR /go/src/github.com/ollama/ollama/llm/generate
|
||||
FROM --platform=linux/amd64 cpu-builder-amd64 AS static-build-amd64
|
||||
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
|
||||
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
|
||||
RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
|
||||
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
|
||||
RUN OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
|
||||
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
|
||||
RUN OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
|
||||
|
||||
FROM --platform=linux/arm64 centos:7 AS cpu-builder-arm64
|
||||
ARG CMAKE_VERSION
|
||||
@@ -84,7 +84,7 @@ WORKDIR /go/src/github.com/ollama/ollama/llm/generate
|
||||
FROM --platform=linux/arm64 cpu-builder-arm64 AS static-build-arm64
|
||||
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
|
||||
FROM --platform=linux/arm64 cpu-builder-arm64 AS cpu-build-arm64
|
||||
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
|
||||
RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
|
||||
|
||||
|
||||
# Intermediate stage used for ./scripts/build_linux.sh
|
||||
|
||||
31
README.md
31
README.md
@@ -35,10 +35,10 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla
|
||||
|
||||
## Quickstart
|
||||
|
||||
To run and chat with [Llama 3](https://ollama.com/library/llama3):
|
||||
To run and chat with [Llama 2](https://ollama.com/library/llama2):
|
||||
|
||||
```
|
||||
ollama run llama3
|
||||
ollama run llama2
|
||||
```
|
||||
|
||||
## Model library
|
||||
@@ -49,8 +49,7 @@ Here are some example models that can be downloaded:
|
||||
|
||||
| Model | Parameters | Size | Download |
|
||||
| ------------------ | ---------- | ----- | ------------------------------ |
|
||||
| Llama 3 | 8B | 4.7GB | `ollama run llama3` |
|
||||
| Llama 3 | 70B | 40GB | `ollama run llama3:70b` |
|
||||
| Llama 2 | 7B | 3.8GB | `ollama run llama2` |
|
||||
| Mistral | 7B | 4.1GB | `ollama run mistral` |
|
||||
| Dolphin Phi | 2.7B | 1.6GB | `ollama run dolphin-phi` |
|
||||
| Phi-2 | 2.7B | 1.7GB | `ollama run phi` |
|
||||
@@ -61,6 +60,7 @@ Here are some example models that can be downloaded:
|
||||
| Llama 2 13B | 13B | 7.3GB | `ollama run llama2:13b` |
|
||||
| Llama 2 70B | 70B | 39GB | `ollama run llama2:70b` |
|
||||
| Orca Mini | 3B | 1.9GB | `ollama run orca-mini` |
|
||||
| Vicuna | 7B | 3.8GB | `ollama run vicuna` |
|
||||
| LLaVA | 7B | 4.5GB | `ollama run llava` |
|
||||
| Gemma | 2B | 1.4GB | `ollama run gemma:2b` |
|
||||
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
|
||||
@@ -98,16 +98,16 @@ See the [guide](docs/import.md) on importing models for more information.
|
||||
|
||||
### Customize a prompt
|
||||
|
||||
Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3` model:
|
||||
Models from the Ollama library can be customized with a prompt. For example, to customize the `llama2` model:
|
||||
|
||||
```
|
||||
ollama pull llama3
|
||||
ollama pull llama2
|
||||
```
|
||||
|
||||
Create a `Modelfile`:
|
||||
|
||||
```
|
||||
FROM llama3
|
||||
FROM llama2
|
||||
|
||||
# set the temperature to 1 [higher is more creative, lower is more coherent]
|
||||
PARAMETER temperature 1
|
||||
@@ -142,7 +142,7 @@ ollama create mymodel -f ./Modelfile
|
||||
### Pull a model
|
||||
|
||||
```
|
||||
ollama pull llama3
|
||||
ollama pull llama2
|
||||
```
|
||||
|
||||
> This command can also be used to update a local model. Only the diff will be pulled.
|
||||
@@ -150,13 +150,13 @@ ollama pull llama3
|
||||
### Remove a model
|
||||
|
||||
```
|
||||
ollama rm llama3
|
||||
ollama rm llama2
|
||||
```
|
||||
|
||||
### Copy a model
|
||||
|
||||
```
|
||||
ollama cp llama3 my-model
|
||||
ollama cp llama2 my-llama2
|
||||
```
|
||||
|
||||
### Multiline input
|
||||
@@ -180,7 +180,7 @@ The image features a yellow smiley face, which is likely the central focus of th
|
||||
### Pass in prompt as arguments
|
||||
|
||||
```
|
||||
$ ollama run llama3 "Summarize this file: $(cat README.md)"
|
||||
$ ollama run llama2 "Summarize this file: $(cat README.md)"
|
||||
Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
|
||||
```
|
||||
|
||||
@@ -227,7 +227,7 @@ Next, start the server:
|
||||
Finally, in a separate shell, run a model:
|
||||
|
||||
```
|
||||
./ollama run llama3
|
||||
./ollama run llama2
|
||||
```
|
||||
|
||||
## REST API
|
||||
@@ -238,7 +238,7 @@ Ollama has a REST API for running and managing models.
|
||||
|
||||
```
|
||||
curl http://localhost:11434/api/generate -d '{
|
||||
"model": "llama3",
|
||||
"model": "llama2",
|
||||
"prompt":"Why is the sky blue?"
|
||||
}'
|
||||
```
|
||||
@@ -247,7 +247,7 @@ curl http://localhost:11434/api/generate -d '{
|
||||
|
||||
```
|
||||
curl http://localhost:11434/api/chat -d '{
|
||||
"model": "llama3",
|
||||
"model": "mistral",
|
||||
"messages": [
|
||||
{ "role": "user", "content": "why is the sky blue?" }
|
||||
]
|
||||
@@ -378,6 +378,3 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
||||
- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
|
||||
- [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend)
|
||||
- [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)
|
||||
|
||||
### Supported backends
|
||||
- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.
|
||||
|
||||
@@ -2,7 +2,6 @@ package api
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"math"
|
||||
"os"
|
||||
@@ -308,7 +307,7 @@ func (m *Metrics) Summary() {
|
||||
}
|
||||
}
|
||||
|
||||
var ErrInvalidOpts = errors.New("invalid options")
|
||||
var ErrInvalidOpts = fmt.Errorf("invalid options")
|
||||
|
||||
func (opts *Options) FromMap(m map[string]interface{}) error {
|
||||
valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
|
||||
|
||||
@@ -90,7 +90,7 @@ The final response in the stream also includes additional data about the generat
|
||||
- `load_duration`: time spent in nanoseconds loading the model
|
||||
- `prompt_eval_count`: number of tokens in the prompt
|
||||
- `prompt_eval_duration`: time spent in nanoseconds evaluating the prompt
|
||||
- `eval_count`: number of tokens in the response
|
||||
- `eval_count`: number of tokens the response
|
||||
- `eval_duration`: time in nanoseconds spent generating the response
|
||||
- `context`: an encoding of the conversation used in this response, this can be sent in the next request to keep a conversational memory
|
||||
- `response`: empty if the response was streamed, if not streamed, this will contain the full response
|
||||
|
||||
@@ -1,15 +1,38 @@
|
||||
# Running Ollama on NVIDIA Jetson Devices
|
||||
|
||||
Ollama runs well on [NVIDIA Jetson Devices](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/) and should run out of the box with the standard installation instructions.
|
||||
With some minor configuration, Ollama runs well on [NVIDIA Jetson Devices](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/). The following has been tested on [JetPack 5.1.2](https://developer.nvidia.com/embedded/jetpack).
|
||||
|
||||
The following has been tested on [JetPack 5.1.2](https://developer.nvidia.com/embedded/jetpack), but should also work on JetPack 6.0.
|
||||
NVIDIA Jetson devices are Linux-based embedded AI computers that are purpose-built for AI applications.
|
||||
|
||||
Jetsons have an integrated GPU that is wired directly to the memory controller of the machine. For this reason, the `nvidia-smi` command is unrecognized, and Ollama proceeds to operate in "CPU only"
|
||||
mode. This can be verified by using a monitoring tool like jtop.
|
||||
|
||||
In order to address this, we simply pass the path to the Jetson's pre-installed CUDA libraries into `ollama serve` (while in a tmux session). We then hardcode the num_gpu parameters into a cloned
|
||||
version of our target model.
|
||||
|
||||
Prerequisites:
|
||||
|
||||
- curl
|
||||
- tmux
|
||||
|
||||
Here are the steps:
|
||||
|
||||
- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.com/install.sh | sh`
|
||||
- Stop the Ollama service: `sudo systemctl stop ollama`
|
||||
- Start Ollama serve in a tmux session called ollama_jetson and reference the CUDA libraries path: `tmux has-session -t ollama_jetson 2>/dev/null || tmux new-session -d -s ollama_jetson
|
||||
'LD_LIBRARY_PATH=/usr/local/cuda/lib64 ollama serve'`
|
||||
- Pull the model you want to use (e.g. mistral): `ollama pull mistral`
|
||||
- Start an interactive session: `ollama run mistral`
|
||||
- Create a new Modelfile specifically for enabling GPU support on the Jetson: `touch ModelfileMistralJetson`
|
||||
- In the ModelfileMistralJetson file, specify the FROM model and the num_gpu PARAMETER as shown below:
|
||||
|
||||
```
|
||||
FROM mistral
|
||||
PARAMETER num_gpu 999
|
||||
```
|
||||
|
||||
- Create a new model from your Modelfile: `ollama create mistral-jetson -f ./ModelfileMistralJetson`
|
||||
- Run the new model: `ollama run mistral-jetson`
|
||||
|
||||
If you run a monitoring tool like jtop you should now see that Ollama is using the Jetson's integrated GPU.
|
||||
|
||||
And that's it!
|
||||
|
||||
# Running Ollama in Docker
|
||||
|
||||
When running GPU accelerated applications in Docker, it is highly recommended to use [dusty-nv jetson-containers repo](https://github.com/dusty-nv/jetson-containers).
|
||||
@@ -55,6 +55,6 @@ func getCPUMem() (memInfo, error) {
|
||||
return memInfo{
|
||||
TotalMemory: uint64(C.getPhysicalMemory()),
|
||||
FreeMemory: 0,
|
||||
DeviceCount: 1,
|
||||
DeviceCount: 0,
|
||||
}, nil
|
||||
}
|
||||
|
||||
33
llm/ext_server/server.cpp
vendored
33
llm/ext_server/server.cpp
vendored
@@ -39,10 +39,6 @@
|
||||
#include "httplib.h"
|
||||
#include "json.hpp"
|
||||
|
||||
#if defined(_WIN32)
|
||||
#include <windows.h>
|
||||
#endif
|
||||
|
||||
#include <cstddef>
|
||||
#include <thread>
|
||||
#include <chrono>
|
||||
@@ -2774,28 +2770,8 @@ inline void signal_handler(int signal) {
|
||||
shutdown_handler(signal);
|
||||
}
|
||||
|
||||
#if defined(_WIN32)
|
||||
char* wchar_to_char(const wchar_t* wstr) {
|
||||
if (wstr == nullptr) return nullptr;
|
||||
|
||||
// Determine the number of bytes needed for the UTF-8 string
|
||||
int bytes = WideCharToMultiByte(CP_UTF8, 0, wstr, -1, nullptr, 0, nullptr, nullptr);
|
||||
char* str = new char[bytes];
|
||||
|
||||
// Convert the wide-character string to a UTF-8 string
|
||||
WideCharToMultiByte(CP_UTF8, 0, wstr, -1, str, bytes, nullptr, nullptr);
|
||||
return str;
|
||||
}
|
||||
|
||||
int wmain(int argc, wchar_t **wargv) {
|
||||
char** argv = new char*[argc];
|
||||
for (int i = 0; i < argc; ++i) {
|
||||
argv[i] = wchar_to_char(wargv[i]);
|
||||
}
|
||||
#else
|
||||
int main(int argc, char **argv) {
|
||||
#endif
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
#if SERVER_VERBOSE != 1
|
||||
log_disable();
|
||||
#endif
|
||||
@@ -3306,11 +3282,6 @@ int main(int argc, char **argv) {
|
||||
return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
|
||||
};
|
||||
SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
|
||||
|
||||
for (int i = 0; i < argc; ++i) {
|
||||
delete[] argv[i];
|
||||
}
|
||||
delete[] argv;
|
||||
#endif
|
||||
llama.queue_tasks.start_loop();
|
||||
svr.stop();
|
||||
|
||||
@@ -57,21 +57,21 @@ init_vars
|
||||
git_module_setup
|
||||
apply_patches
|
||||
|
||||
init_vars
|
||||
if [ -z "${OLLAMA_SKIP_STATIC_GENERATE}" -o "${OLLAMA_CPU_TARGET}" = "static" ]; then
|
||||
# Builds by default, allows skipping, forces build if OLLAMA_CPU_TARGET="static"
|
||||
# Enables optimized Dockerfile builds using a blanket skip and targeted overrides
|
||||
# Static build for linking into the Go binary
|
||||
init_vars
|
||||
CMAKE_TARGETS="--target llama --target ggml"
|
||||
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
|
||||
BUILD_DIR="../build/linux/${ARCH}_static"
|
||||
echo "Building static library"
|
||||
build
|
||||
fi
|
||||
|
||||
init_vars
|
||||
if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
|
||||
|
||||
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "static" ]; then
|
||||
# Static build for linking into the Go binary
|
||||
init_vars
|
||||
CMAKE_TARGETS="--target llama --target ggml"
|
||||
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
|
||||
BUILD_DIR="../build/linux/${ARCH}_static"
|
||||
echo "Building static library"
|
||||
build
|
||||
fi
|
||||
|
||||
|
||||
# Users building from source can tune the exact flags we pass to cmake for configuring
|
||||
# llama.cpp, and we'll build only 1 CPU variant in that case as the default.
|
||||
if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
|
||||
|
||||
@@ -164,8 +164,7 @@ func (ts Tensors) Layers() map[string]Layer {
|
||||
for _, t := range ts {
|
||||
parts := strings.Split(t.Name, ".")
|
||||
if parts[0] == "blk" {
|
||||
// join first and second part, e.g. blk.%d
|
||||
parts = append([]string{fmt.Sprintf("%s.%s", parts[0], parts[1])}, parts[2:]...)
|
||||
parts = parts[1:]
|
||||
}
|
||||
|
||||
if _, ok := layers[parts[0]]; !ok {
|
||||
@@ -381,12 +380,6 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
|
||||
)
|
||||
|
||||
partialOffload = 4*batch*(2*embedding+vocab) + embedding*vocab*105/128
|
||||
case "stablelm":
|
||||
fullOffload = 4 * batch * (context*(1+heads) + 3*embedding + 2)
|
||||
partialOffload = max(
|
||||
4*batch*(vocab+2*embedding),
|
||||
fullOffload,
|
||||
)
|
||||
}
|
||||
|
||||
return
|
||||
|
||||
21
llm/gguf.go
21
llm/gguf.go
@@ -248,17 +248,13 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
|
||||
}
|
||||
|
||||
padding := llm.padding(offset, int64(alignment))
|
||||
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
|
||||
if _, err := rs.Seek(padding-offset, io.SeekCurrent); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, tensor := range llm.tensors {
|
||||
if _, err := rs.Seek(int64(tensor.size()), io.SeekCurrent); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
padding := llm.padding(int64(tensor.size()), int64(alignment))
|
||||
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
|
||||
padded := (int64(tensor.size()) + int64(alignment) - 1) & ^(int64(alignment) - 1)
|
||||
if _, err := rs.Seek(padded, io.SeekCurrent); err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
@@ -627,9 +623,8 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
|
||||
return err
|
||||
}
|
||||
|
||||
var alignment int64 = 32
|
||||
padding := llm.padding(offset, alignment)
|
||||
if err := binary.Write(ws, llm.ByteOrder, bytes.Repeat([]byte{0}, int(padding))); err != nil {
|
||||
padding := llm.padding(offset, 32)
|
||||
if err := binary.Write(ws, llm.ByteOrder, bytes.Repeat([]byte{0}, int(padding-offset))); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
@@ -643,8 +638,8 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
|
||||
return err
|
||||
}
|
||||
|
||||
padding := llm.padding(offset, alignment)
|
||||
if err := binary.Write(ws, llm.ByteOrder, bytes.Repeat([]byte{0}, int(padding))); err != nil {
|
||||
padding := llm.padding(offset, 32)
|
||||
if err := binary.Write(ws, llm.ByteOrder, bytes.Repeat([]byte{0}, int(padding-offset))); err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
@@ -653,5 +648,5 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
|
||||
}
|
||||
|
||||
func (gguf) padding(offset, align int64) int64 {
|
||||
return (align - offset%align) % align
|
||||
return (offset + align - 1) / align * align
|
||||
}
|
||||
|
||||
Submodule llm/llama.cpp updated: 8960fe86ae...7593639ce3
@@ -17,7 +17,7 @@ import (
|
||||
"github.com/ollama/ollama/gpu"
|
||||
)
|
||||
|
||||
var errPayloadMissing = errors.New("expected payloads not included in this build of ollama")
|
||||
var errPayloadMissing = fmt.Errorf("expected payloads not included in this build of ollama")
|
||||
|
||||
func Init() error {
|
||||
payloadsDir, err := gpu.PayloadsDir()
|
||||
|
||||
@@ -79,9 +79,6 @@ func NewLlamaServer(model string, adapters, projectors []string, opts api.Option
|
||||
graphFullOffload = graphPartialOffload
|
||||
}
|
||||
|
||||
graphFullOffload *= uint64(info.DeviceCount)
|
||||
graphPartialOffload *= uint64(info.DeviceCount)
|
||||
|
||||
// memoryRequiredTotal represents the memory required for full GPU offloading (all layers)
|
||||
memoryRequiredTotal := memoryMinimum + graphFullOffload
|
||||
|
||||
@@ -97,7 +94,7 @@ func NewLlamaServer(model string, adapters, projectors []string, opts api.Option
|
||||
var layerCount int
|
||||
layers := ggml.Tensors().Layers()
|
||||
for i := 0; i < int(ggml.KV().BlockCount()); i++ {
|
||||
memoryLayer := layers[fmt.Sprintf("blk.%d", i)].size()
|
||||
memoryLayer := layers[fmt.Sprintf("%d", i)].size()
|
||||
|
||||
// KV is proportional to the number of layers
|
||||
memoryLayer += kv / ggml.KV().BlockCount()
|
||||
@@ -109,13 +106,7 @@ func NewLlamaServer(model string, adapters, projectors []string, opts api.Option
|
||||
}
|
||||
}
|
||||
|
||||
var memoryLayerOutput uint64
|
||||
for k, v := range layers {
|
||||
if !strings.HasPrefix(k, "blk.") {
|
||||
memoryLayerOutput += v.size()
|
||||
}
|
||||
}
|
||||
|
||||
memoryLayerOutput := layers["output"].size()
|
||||
memoryRequiredTotal += memoryLayerOutput
|
||||
|
||||
if info.Library == "metal" && memoryRequiredTotal > info.TotalMemory {
|
||||
@@ -130,47 +121,16 @@ func NewLlamaServer(model string, adapters, projectors []string, opts api.Option
|
||||
opts.NumGPU = layerCount
|
||||
}
|
||||
|
||||
memoryWeights := memoryRequiredTotal - memoryMinimum - graphFullOffload - kv
|
||||
|
||||
slog.Info(
|
||||
"offload to gpu",
|
||||
slog.Group(
|
||||
"layers",
|
||||
// actual number of layers offloaded
|
||||
"real", opts.NumGPU,
|
||||
// estimated number of layers that can be offloaded
|
||||
"estimate", layerCount,
|
||||
),
|
||||
slog.Group(
|
||||
"memory",
|
||||
// memory available for offloading
|
||||
"available", format.HumanBytes2(memoryAvailable),
|
||||
slog.Group(
|
||||
"required",
|
||||
// memory required for full offloading
|
||||
"full", format.HumanBytes2(memoryRequiredTotal),
|
||||
// memory required to offload layers.estimate layers
|
||||
"partial", format.HumanBytes2(memoryRequiredPartial),
|
||||
// memory of KV cache
|
||||
"kv", format.HumanBytes2(kv),
|
||||
),
|
||||
slog.Group(
|
||||
"weights",
|
||||
// memory of the weights
|
||||
"total", format.HumanBytes2(memoryWeights),
|
||||
// memory of repeating layers
|
||||
"repeating", format.HumanBytes2(memoryWeights-memoryLayerOutput),
|
||||
// memory of non-repeating layers
|
||||
"nonrepeating", format.HumanBytes2(memoryLayerOutput),
|
||||
),
|
||||
slog.Group(
|
||||
"graph",
|
||||
// memory of graph when fully offloaded
|
||||
"full", format.HumanBytes2(graphFullOffload),
|
||||
// memory of graph when not fully offloaded
|
||||
"partial", format.HumanBytes2(graphPartialOffload),
|
||||
),
|
||||
),
|
||||
"reallayers", opts.NumGPU,
|
||||
"layers", layerCount,
|
||||
"required", format.HumanBytes2(memoryRequiredTotal),
|
||||
"used", format.HumanBytes2(memoryRequiredPartial),
|
||||
"available", format.HumanBytes2(memoryAvailable),
|
||||
"kv", format.HumanBytes2(kv),
|
||||
"fulloffload", format.HumanBytes2(graphFullOffload),
|
||||
"partialoffload", format.HumanBytes2(graphPartialOffload),
|
||||
)
|
||||
|
||||
if len(adapters) > 1 {
|
||||
|
||||
@@ -1137,7 +1137,7 @@ func GetSHA256Digest(r io.Reader) (string, int64) {
|
||||
return fmt.Sprintf("sha256:%x", h.Sum(nil)), n
|
||||
}
|
||||
|
||||
var errUnauthorized = errors.New("unauthorized")
|
||||
var errUnauthorized = fmt.Errorf("unauthorized")
|
||||
|
||||
func makeRequestWithRetry(ctx context.Context, method string, requestURL *url.URL, headers http.Header, body io.ReadSeeker, regOpts *registryOptions) (*http.Response, error) {
|
||||
for i := 0; i < 2; i++ {
|
||||
@@ -1255,7 +1255,7 @@ func parseRegistryChallenge(authStr string) registryChallenge {
|
||||
}
|
||||
}
|
||||
|
||||
var errDigestMismatch = errors.New("digest mismatch, file must be downloaded again")
|
||||
var errDigestMismatch = fmt.Errorf("digest mismatch, file must be downloaded again")
|
||||
|
||||
func verifyBlob(digest string) error {
|
||||
fp, err := GetBlobsPath(digest)
|
||||
|
||||
@@ -156,7 +156,7 @@ func ParseName(s, fill string) Name {
|
||||
r = Name{}
|
||||
return false
|
||||
}
|
||||
if kind == PartExtraneous || !IsValidNamePart(kind, part) {
|
||||
if kind == PartExtraneous || !isValidPart(kind, part) {
|
||||
r = Name{}
|
||||
return false
|
||||
}
|
||||
@@ -176,7 +176,7 @@ func parseMask(s string) Name {
|
||||
// mask part; treat as empty but valid
|
||||
return true
|
||||
}
|
||||
if !IsValidNamePart(kind, part) {
|
||||
if !isValidPart(kind, part) {
|
||||
panic(fmt.Errorf("invalid mask part %s: %q", kind, part))
|
||||
}
|
||||
r.parts[kind] = part
|
||||
@@ -521,8 +521,6 @@ func parts(s string) iter_Seq2[PartKind, string] {
|
||||
return
|
||||
}
|
||||
state, j, partLen = PartModel, i, 0
|
||||
case PartHost:
|
||||
// noop: support for host:port
|
||||
default:
|
||||
yield(PartExtraneous, s[i+1:j])
|
||||
return
|
||||
@@ -608,7 +606,7 @@ func ParseNameFromFilepath(s, fill string) Name {
|
||||
var r Name
|
||||
for i := range PartBuild + 1 {
|
||||
part, rest, _ := strings.Cut(s, string(filepath.Separator))
|
||||
if !IsValidNamePart(i, part) {
|
||||
if !isValidPart(i, part) {
|
||||
return Name{}
|
||||
}
|
||||
r.parts[i] = part
|
||||
@@ -654,12 +652,9 @@ func (r Name) FilepathNoBuild() string {
|
||||
return filepath.Join(r.parts[:PartBuild]...)
|
||||
}
|
||||
|
||||
// IsValidNamePart reports if s contains all valid characters for the given
|
||||
// part kind and is under MaxNamePartLen bytes.
|
||||
func IsValidNamePart(kind PartKind, s string) bool {
|
||||
if len(s) > MaxNamePartLen {
|
||||
return false
|
||||
}
|
||||
// isValidPart reports if s contains all valid characters for the given
|
||||
// part kind.
|
||||
func isValidPart(kind PartKind, s string) bool {
|
||||
if s == "" {
|
||||
return false
|
||||
}
|
||||
@@ -683,9 +678,6 @@ func isValidByteFor(kind PartKind, c byte) bool {
|
||||
if kind == PartNamespace && c == '.' {
|
||||
return false
|
||||
}
|
||||
if kind == PartHost && c == ':' {
|
||||
return true
|
||||
}
|
||||
if c == '.' || c == '-' {
|
||||
return true
|
||||
}
|
||||
|
||||
@@ -40,7 +40,6 @@ var testNames = map[string]fields{
|
||||
"user/model": {namespace: "user", model: "model"},
|
||||
"example.com/ns/mistral:7b+Q4_0": {host: "example.com", namespace: "ns", model: "mistral", tag: "7b", build: "Q4_0"},
|
||||
"example.com/ns/mistral:7b+X": {host: "example.com", namespace: "ns", model: "mistral", tag: "7b", build: "X"},
|
||||
"localhost:5000/ns/mistral": {host: "localhost:5000", namespace: "ns", model: "mistral"},
|
||||
|
||||
// invalid digest
|
||||
"mistral:latest@invalid256-": {},
|
||||
@@ -105,12 +104,6 @@ var testNames = map[string]fields{
|
||||
strings.Repeat("a", MaxNamePartLen+1): {},
|
||||
}
|
||||
|
||||
func TestIsValidNameLen(t *testing.T) {
|
||||
if IsValidNamePart(PartNamespace, strings.Repeat("a", MaxNamePartLen+1)) {
|
||||
t.Errorf("unexpectedly valid long name")
|
||||
}
|
||||
}
|
||||
|
||||
// TestConsecutiveDots tests that consecutive dots are not allowed in any
|
||||
// part, to avoid path traversal. There also are some tests in testNames, but
|
||||
// this test is more exhaustive and exists to emphasize the importance of
|
||||
|
||||
Reference in New Issue
Block a user