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build(Makefile): add back single target to build native llama-cpp (#2448)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2024-05-31 18:35:33 +02:00 committed by GitHub
parent 10c64dbb55
commit ff8a6962cd
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2 changed files with 17 additions and 4 deletions
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8
Makefile
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@ -672,6 +672,14 @@ else
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/${VARIANT} grpc-server
endif
# This target is for manually building a variant with-auto detected flags
backend-assets/grpc/llama-cpp: backend-assets/grpc
cp -rf backend/cpp/llama backend/cpp/llama-cpp
$(MAKE) -C backend/cpp/llama-cpp purge
$(info ${GREEN}I llama-cpp build info:avx2${RESET})
$(MAKE) VARIANT="llama-cpp" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-cpp/grpc-server backend-assets/grpc/llama-cpp
backend-assets/grpc/llama-cpp-avx2: backend-assets/grpc
cp -rf backend/cpp/llama backend/cpp/llama-avx2
$(MAKE) -C backend/cpp/llama-avx2 purge

13
docs/content/docs/advanced/advanced-usage.md
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@ -351,7 +351,7 @@ For example, to start vllm manually after compiling LocalAI (also assuming runni
./local-ai --external-grpc-backends "vllm:$PWD/backend/python/vllm/run.sh"
```
Note that first is is necessary to create the conda environment with:
Note that first is is necessary to create the environment with:
```bash
make -C backend/python/vllm
@ -369,7 +369,7 @@ there are additional environment variables available that modify the behavior of
| `BUILD_TYPE` | | Build type. Available: `cublas`, `openblas`, `clblas` |
| `GO_TAGS` | | Go tags. Available: `stablediffusion` |
| `HUGGINGFACEHUB_API_TOKEN` | | Special token for interacting with HuggingFace Inference API, required only when using the `langchain-huggingface` backend |
| `EXTRA_BACKENDS` | | A space separated list of backends to prepare. For example `EXTRA_BACKENDS="backend/python/diffusers backend/python/transformers"` prepares the conda environment on start |
| `EXTRA_BACKENDS` | | A space separated list of backends to prepare. For example `EXTRA_BACKENDS="backend/python/diffusers backend/python/transformers"` prepares the python environment on start |
| `DISABLE_AUTODETECT` | `false` | Disable autodetect of CPU flagset on start |
| `LLAMACPP_GRPC_SERVERS` | | A list of llama.cpp workers to distribute the workload. For example `LLAMACPP_GRPC_SERVERS="address1:port,address2:port"` |
@ -475,7 +475,7 @@ If you wish to build a custom container image with extra backends, you can use t
```Dockerfile
FROM quay.io/go-skynet/local-ai:master-ffmpeg-core
RUN PATH=$PATH:/opt/conda/bin make -C backend/python/diffusers
RUN make -C backend/python/diffusers
```
Remember also to set the `EXTERNAL_GRPC_BACKENDS` environment variable (or `--external-grpc-backends` as CLI flag) to point to the backends you are using (`EXTERNAL_GRPC_BACKENDS="backend_name:/path/to/backend"`), for example with diffusers:
@ -483,7 +483,7 @@ Remember also to set the `EXTERNAL_GRPC_BACKENDS` environment variable (or `--ex
```Dockerfile
FROM quay.io/go-skynet/local-ai:master-ffmpeg-core
RUN PATH=$PATH:/opt/conda/bin make -C backend/python/diffusers
RUN make -C backend/python/diffusers
ENV EXTERNAL_GRPC_BACKENDS="diffusers:/build/backend/python/diffusers/run.sh"
```
@ -525,3 +525,8 @@ A list of the environment variable that tweaks parallelism is the following:
Note that, for llama.cpp you need to set accordingly `LLAMACPP_PARALLEL` to the number of parallel processes your GPU/CPU can handle. For python-based backends (like vLLM) you can set `PYTHON_GRPC_MAX_WORKERS` to the number of parallel requests.
### Disable CPU flagset auto detection in llama.cpp
LocalAI will automatically discover the CPU flagset available in your host and will use the most optimized version of the backends.
If you want to disable this behavior, you can set `DISABLE_AUTODETECT` to `true` in the environment variables.