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* add build to .dockerignore * test: only build one arch * add build to .gitignore * fix ccache path * filter amdgpu targets * only filter if autodetecting * Don't clobber gpu list for default runner This ensures the GPU specific environment variables are set properly * explicitly set CXX compiler for HIP * Update build_windows.ps1 This isn't complete, but is close. Dependencies are missing, and it only builds the "default" preset. * build: add ollama subdir * add .git to .dockerignore * docs: update development.md * update build_darwin.sh * remove unused scripts * llm: add cwd and build/lib/ollama to library paths * default DYLD_LIBRARY_PATH to LD_LIBRARY_PATH in runner on macOS * add additional cmake output vars for msvc * interim edits to make server detection logic work with dll directories like lib/ollama/cuda_v12 * remove unncessary filepath.Dir, cleanup * add hardware-specific directory to path * use absolute server path * build: linux arm * cmake install targets * remove unused files * ml: visit each library path once * build: skip cpu variants on arm * build: install cpu targets * build: fix workflow * shorter names * fix rocblas install * docs: clean up development.md * consistent build dir removal in development.md * silence -Wimplicit-function-declaration build warnings in ggml-cpu * update readme * update development readme * llm: update library lookup logic now that there is one runner (#8587) * tweak development.md * update docs * add windows cuda/rocm tests --------- Co-authored-by: jmorganca <jmorganca@gmail.com> Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
120 lines
2.4 KiB
Markdown
120 lines
2.4 KiB
Markdown
# Development
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Install prerequisites:
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- [Go](https://go.dev/doc/install)
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- C/C++ Compiler e.g. Clang on macOS, [TDM-GCC](https://jmeubank.github.io/tdm-gcc/download/) (Windows amd64) or [llvm-mingw](https://github.com/mstorsjo/llvm-mingw) (Windows arm64), GCC/Clang on Linux.
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Then build and run Ollama from the root directory of the repository:
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```
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go run . serve
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```
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## macOS (Apple Silicon)
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macOS Apple Silicon supports Metal which is built-in to the Ollama binary. No additional steps are required.
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## macOS (Intel)
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Install prerequisites:
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- [CMake](https://cmake.org/download/) or `brew install cmake`
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Then, configure and build the project:
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```
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cmake -B build
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cmake --build build
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```
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Lastly, run Ollama:
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```
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go run . serve
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```
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## Windows
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Install prerequisites:
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- [CMake](https://cmake.org/download/)
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- [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) including the Native Desktop Workload
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- (Optional) AMD GPU support
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- [ROCm](https://rocm.github.io/install.html)
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- [Ninja](https://github.com/ninja-build/ninja/releases)
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- (Optional) NVIDIA GPU support
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- [CUDA SDK](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=11&target_type=exe_network)
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> [!IMPORTANT]
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> Ensure prerequisites are in `PATH` before running CMake.
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> [!IMPORTANT]
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> ROCm is not compatible with Visual Studio CMake generators. Use `-GNinja` when configuring the project.
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> [!IMPORTANT]
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> CUDA is only compatible with Visual Studio CMake generators.
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Then, configure and build the project:
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```
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cmake -B build
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cmake --build build --config Release
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```
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Lastly, run Ollama:
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```
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go run . serve
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```
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## Windows (ARM)
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Windows ARM does not support additional acceleration libraries at this time.
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## Linux
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Install prerequisites:
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- [CMake](https://cmake.org/download/) or `sudo apt install cmake` or `sudo dnf install cmake`
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- (Optional) AMD GPU support
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- [ROCm](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)
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- (Optional) NVIDIA GPU support
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- [CUDA SDK](https://developer.nvidia.com/cuda-downloads)
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> [!IMPORTANT]
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> Ensure prerequisites are in `PATH` before running CMake.
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Then, configure and build the project:
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```
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cmake -B build
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cmake --build build
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```
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Lastly, run Ollama:
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```
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go run . serve
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```
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## Docker
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```
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docker build .
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```
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### ROCm
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```
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docker build --build-arg FLAVOR=rocm .
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```
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## Running tests
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To run tests, use `go test`:
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```
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go test ./...
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```
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