GitLab

On OpenSUSE, ollama needs to be a member of the video group
to access the GPU

Allow overriding the platform, image name, and tag latest for
standard and rocm images.

* remove `-w -s` linker flags on windows

* use `zip` for windows installer compression

Also fixes a few fit-and-finish items for better developer experience

This will be useful for our automated test riggig, and may be useful for
advanced users who want to "roll their own" system service

This focuses on Windows first, but coudl be used for Mac
and possibly linux in the future.

This adds ROCm support back as a discrete image.

If a VERSION is not specified, this will generate a version string that
represents the state of the repo.  For example `0.1.21-12-gffaf52e1-dirty`
representing 12 commits away from 0.1.21 tag, on commit gffaf52e1
and the tree is dirty.

The linux build now support parallel CPU builds to speed things up.
This also exposes AMD GPU targets as an optional setting for advaced
users who want to alter our default set.

This renames Dockerfile.build to Dockerfile, and adds some new stages
to support 2 modes of building - the build_linux.sh script uses
intermediate stages to extract the artifacts for ./dist, and the default
build generates a container image usable by both cuda and rocm cards.
This required transitioniing the x86 base to the rocm image to avoid
layer bloat.

This also refines the build process for the ext_server build.

repos for fedora 38 and newer do not exist as of this commit

```
$ dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/fedora38/x86_64/cuda-fedora38.repo
Adding repo from: https://developer.download.nvidia.com/compute/cuda/repos/fedora38/x86_64/cuda-fedora38.repo
Status code: 404 for https://developer.download.nvidia.com/compute/cuda/repos/fedora38/x86_64/cuda-fedora38.repo (IP: 152.195.19.142)
Error: Configuration of repo failed
```

This reduces the built-in linux version to not use any vector extensions
which enables the resulting builds to run under Rosetta on MacOS in
Docker.  Then at runtime it checks for the actual CPU vector
extensions and loads the best CPU library available

This can help speed up incremental builds when you're only testing one
archicture, like amd64.  E.g.
BUILD_ARCH=amd64 ./scripts/build_linux.sh && scp ./dist/ollama-linux-amd64 test-system:

This prevents users from accidentally installing on WSL1 with instructions
guiding how to upgrade their WSL instance to version 2.  Once running WSL2
if you have an NVIDIA card, you can follow their instructions to set up
GPU passthrough and run models on the GPU.  This is not possible on WSL1.

For the ROCm libraries to access the driver, we need to add the ollama user
to the render group.

This should help CI avoid running the integration test logic in a
container where it's not currently possible.

By default builds will now produce non-debug and non-verbose binaries.
To enable verbose logs in llama.cpp and debug symbols in the
native code, set `CGO_CFLAGS=-g`

If someone checks out the ollama repo and doesn't install the CUDA
library, this will ensure they can build a CPU only version

A simple test case that verifies llava:7b can read text in an image

Run the server.cpp directly inside the Go runtime via cgo
while retaining the LLM Go abstractions.

Co-authored-by: Cloud User <azureuser@testgpu2.hqzwom21okjenksna4y3c4ymjd.phxx.internal.cloudapp.net>