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feat(transformers): merge sentencetransformers backend (#4624)
* merge sentencetransformers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add alias to silently redirect sentencetransformers to transformers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add alias also for transformers-musicgen Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop from makefile Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Move tests from sentencetransformers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Remove sentencetransformers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Remove tests from CI (part of transformers) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Do not always try to load the tokenizer Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Adapt tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fix typo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Tiny adjustments Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
GitHub
parent
4bd8434ae0
commit
1e9bf19c8d
24
.github/workflows/test-extra.yml
vendored
24
.github/workflows/test-extra.yml
vendored
@ -35,30 +35,6 @@ jobs:
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run: |
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make --jobs=5 --output-sync=target -C backend/python/transformers
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make --jobs=5 --output-sync=target -C backend/python/transformers test
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tests-sentencetransformers:
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runs-on: ubuntu-latest
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steps:
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- name: Clone
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uses: actions/checkout@v4
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with:
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submodules: true
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- name: Dependencies
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run: |
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sudo apt-get update
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sudo apt-get install build-essential ffmpeg
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# Install UV
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curl -LsSf https://astral.sh/uv/install.sh | sh
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sudo apt-get install -y ca-certificates cmake curl patch python3-pip
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sudo apt-get install -y libopencv-dev
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pip install --user --no-cache-dir grpcio-tools==1.64.1
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- name: Test sentencetransformers
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run: |
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make --jobs=5 --output-sync=target -C backend/python/sentencetransformers
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make --jobs=5 --output-sync=target -C backend/python/sentencetransformers test
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tests-rerankers:
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runs-on: ubuntu-latest
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steps:
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3
.github/workflows/test.yml
vendored
3
.github/workflows/test.yml
vendored
@ -100,8 +100,7 @@ jobs:
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# The python3-grpc-tools package in 22.04 is too old
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pip install --user grpcio-tools
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sudo rm -rfv /usr/bin/conda || true
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PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
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make -C backend/python/transformers
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# Pre-build piper before we start tests in order to have shared libraries in place
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make sources/go-piper && \
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@ -15,7 +15,7 @@ ARG TARGETARCH
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ARG TARGETVARIANT
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ENV DEBIAN_FRONTEND=noninteractive
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ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,openvoice:/build/backend/python/openvoice/run.sh,kokoro:/build/backend/python/kokoro/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
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ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,transformers:/build/backend/python/transformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,openvoice:/build/backend/python/openvoice/run.sh,kokoro:/build/backend/python/kokoro/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
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RUN apt-get update && \
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@ -456,9 +456,6 @@ RUN if [[ ( "${EXTRA_BACKENDS}" =~ "kokoro" || -z "${EXTRA_BACKENDS}" ) && "$IMA
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if [[ ( "${EXTRA_BACKENDS}" =~ "openvoice" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
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make -C backend/python/openvoice \
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; fi && \
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if [[ ( "${EXTRA_BACKENDS}" =~ "sentencetransformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
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make -C backend/python/sentencetransformers \
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; fi && \
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if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
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make -C backend/python/exllama2 \
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; fi && \
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15
Makefile
15
Makefile
@ -497,7 +497,7 @@ test: prepare test-models/testmodel.ggml grpcs
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@echo 'Running tests'
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export GO_TAGS="tts stablediffusion debug"
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$(MAKE) prepare-test
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HUGGINGFACE_GRPC=$(abspath ./)/backend/python/sentencetransformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
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HUGGINGFACE_GRPC=$(abspath ./)/backend/python/transformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
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$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!llama && !llama-gguf" --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
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$(MAKE) test-llama
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$(MAKE) test-llama-gguf
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@ -583,10 +583,10 @@ protogen-go-clean:
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$(RM) bin/*
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.PHONY: protogen-python
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protogen-python: autogptq-protogen bark-protogen coqui-protogen diffusers-protogen exllama2-protogen mamba-protogen rerankers-protogen sentencetransformers-protogen transformers-protogen parler-tts-protogen kokoro-protogen vllm-protogen openvoice-protogen
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protogen-python: autogptq-protogen bark-protogen coqui-protogen diffusers-protogen exllama2-protogen mamba-protogen rerankers-protogen transformers-protogen parler-tts-protogen kokoro-protogen vllm-protogen openvoice-protogen
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.PHONY: protogen-python-clean
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protogen-python-clean: autogptq-protogen-clean bark-protogen-clean coqui-protogen-clean diffusers-protogen-clean exllama2-protogen-clean mamba-protogen-clean sentencetransformers-protogen-clean rerankers-protogen-clean transformers-protogen-clean parler-tts-protogen-clean kokoro-protogen-clean vllm-protogen-clean openvoice-protogen-clean
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protogen-python-clean: autogptq-protogen-clean bark-protogen-clean coqui-protogen-clean diffusers-protogen-clean exllama2-protogen-clean mamba-protogen-clean rerankers-protogen-clean transformers-protogen-clean parler-tts-protogen-clean kokoro-protogen-clean vllm-protogen-clean openvoice-protogen-clean
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.PHONY: autogptq-protogen
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autogptq-protogen:
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@ -644,14 +644,6 @@ rerankers-protogen:
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rerankers-protogen-clean:
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$(MAKE) -C backend/python/rerankers protogen-clean
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.PHONY: sentencetransformers-protogen
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sentencetransformers-protogen:
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$(MAKE) -C backend/python/sentencetransformers protogen
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.PHONY: sentencetransformers-protogen-clean
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sentencetransformers-protogen-clean:
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$(MAKE) -C backend/python/sentencetransformers protogen-clean
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.PHONY: transformers-protogen
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transformers-protogen:
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$(MAKE) -C backend/python/transformers protogen
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@ -701,7 +693,6 @@ prepare-extra-conda-environments: protogen-python
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$(MAKE) -C backend/python/diffusers
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$(MAKE) -C backend/python/vllm
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$(MAKE) -C backend/python/mamba
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$(MAKE) -C backend/python/sentencetransformers
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$(MAKE) -C backend/python/rerankers
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$(MAKE) -C backend/python/transformers
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$(MAKE) -C backend/python/parler-tts
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@ -1,31 +0,0 @@
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.PHONY: sentencetransformers
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sentencetransformers: protogen
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bash ./install.sh
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.PHONY: run
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run: protogen
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@echo "Running sentencetransformers..."
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bash run.sh
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@echo "sentencetransformers run."
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# It is not working well by using command line. It only6 works with IDE like VSCode.
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.PHONY: test
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test: protogen
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@echo "Testing sentencetransformers..."
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bash test.sh
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@echo "sentencetransformers tested."
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.PHONY: protogen
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protogen: backend_pb2_grpc.py backend_pb2.py
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.PHONY: protogen-clean
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protogen-clean:
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$(RM) backend_pb2_grpc.py backend_pb2.py
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backend_pb2_grpc.py backend_pb2.py:
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python3 -m grpc_tools.protoc -I../.. --python_out=. --grpc_python_out=. backend.proto
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.PHONY: clean
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clean: protogen-clean
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rm -rf venv __pycache__
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@ -1,5 +0,0 @@
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# Creating a separate environment for the sentencetransformers project
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```
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make sentencetransformers
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```
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@ -1,114 +0,0 @@
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#!/usr/bin/env python3
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"""
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Extra gRPC server for HuggingFace SentenceTransformer models.
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"""
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from concurrent import futures
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import argparse
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import signal
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import sys
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import os
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import time
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import backend_pb2
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import backend_pb2_grpc
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import grpc
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from sentence_transformers import SentenceTransformer
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_ONE_DAY_IN_SECONDS = 60 * 60 * 24
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# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
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MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
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# Implement the BackendServicer class with the service methods
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class BackendServicer(backend_pb2_grpc.BackendServicer):
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"""
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A gRPC servicer for the backend service.
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This class implements the gRPC methods for the backend service, including Health, LoadModel, and Embedding.
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"""
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def Health(self, request, context):
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"""
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A gRPC method that returns the health status of the backend service.
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Args:
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request: A HealthRequest object that contains the request parameters.
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context: A grpc.ServicerContext object that provides information about the RPC.
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Returns:
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A Reply object that contains the health status of the backend service.
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"""
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return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
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def LoadModel(self, request, context):
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"""
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A gRPC method that loads a model into memory.
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Args:
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request: A LoadModelRequest object that contains the request parameters.
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context: A grpc.ServicerContext object that provides information about the RPC.
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Returns:
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A Result object that contains the result of the LoadModel operation.
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"""
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model_name = request.Model
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try:
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self.model = SentenceTransformer(model_name, trust_remote_code=request.TrustRemoteCode)
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except Exception as err:
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return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
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# Implement your logic here for the LoadModel service
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# Replace this with your desired response
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return backend_pb2.Result(message="Model loaded successfully", success=True)
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def Embedding(self, request, context):
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"""
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A gRPC method that calculates embeddings for a given sentence.
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Args:
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request: An EmbeddingRequest object that contains the request parameters.
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context: A grpc.ServicerContext object that provides information about the RPC.
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Returns:
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An EmbeddingResult object that contains the calculated embeddings.
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"""
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# Implement your logic here for the Embedding service
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# Replace this with your desired response
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print("Calculated embeddings for: " + request.Embeddings, file=sys.stderr)
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sentence_embeddings = self.model.encode(request.Embeddings)
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return backend_pb2.EmbeddingResult(embeddings=sentence_embeddings)
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def serve(address):
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server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))
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backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
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server.add_insecure_port(address)
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server.start()
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print("Server started. Listening on: " + address, file=sys.stderr)
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# Define the signal handler function
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def signal_handler(sig, frame):
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print("Received termination signal. Shutting down...")
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server.stop(0)
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sys.exit(0)
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# Set the signal handlers for SIGINT and SIGTERM
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signal.signal(signal.SIGINT, signal_handler)
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signal.signal(signal.SIGTERM, signal_handler)
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try:
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while True:
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time.sleep(_ONE_DAY_IN_SECONDS)
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except KeyboardInterrupt:
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server.stop(0)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Run the gRPC server.")
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parser.add_argument(
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"--addr", default="localhost:50051", help="The address to bind the server to."
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)
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args = parser.parse_args()
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serve(args.addr)
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@ -1,14 +0,0 @@
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#!/bin/bash
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set -e
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source $(dirname $0)/../common/libbackend.sh
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# This is here because the Intel pip index is broken and returns 200 status codes for every package name, it just doesn't return any package links.
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# This makes uv think that the package exists in the Intel pip index, and by default it stops looking at other pip indexes once it finds a match.
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# We need uv to continue falling through to the pypi default index to find optimum[openvino] in the pypi index
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# the --upgrade actually allows us to *downgrade* torch to the version provided in the Intel pip index
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if [ "x${BUILD_PROFILE}" == "xintel" ]; then
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EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
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fi
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installRequirements
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@ -1,6 +0,0 @@
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torch==2.4.1
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accelerate
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transformers
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bitsandbytes
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sentence-transformers==3.3.1
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transformers
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@ -1,5 +0,0 @@
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--extra-index-url https://download.pytorch.org/whl/cu118
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torch==2.4.1+cu118
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accelerate
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sentence-transformers==3.3.1
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transformers
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@ -1,4 +0,0 @@
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torch==2.4.1
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accelerate
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sentence-transformers==3.3.1
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transformers
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@ -1,5 +0,0 @@
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--extra-index-url https://download.pytorch.org/whl/rocm6.0
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torch==2.4.1+rocm6.0
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accelerate
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sentence-transformers==3.3.1
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transformers
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@ -1,9 +0,0 @@
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--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
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intel-extension-for-pytorch==2.3.110+xpu
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torch==2.3.1+cxx11.abi
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oneccl_bind_pt==2.3.100+xpu
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optimum[openvino]
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setuptools
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accelerate
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sentence-transformers==3.3.1
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transformers
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@ -1,5 +0,0 @@
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grpcio==1.69.0
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protobuf
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certifi
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datasets
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einops
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@ -1,4 +0,0 @@
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#!/bin/bash
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source $(dirname $0)/../common/libbackend.sh
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startBackend $@
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@ -1,81 +0,0 @@
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"""
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A test script to test the gRPC service
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"""
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import unittest
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import subprocess
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import time
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import backend_pb2
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import backend_pb2_grpc
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|
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import grpc
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|
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|
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class TestBackendServicer(unittest.TestCase):
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"""
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TestBackendServicer is the class that tests the gRPC service
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"""
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def setUp(self):
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"""
|
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This method sets up the gRPC service by starting the server
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"""
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self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
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time.sleep(10)
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|
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def tearDown(self) -> None:
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"""
|
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This method tears down the gRPC service by terminating the server
|
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"""
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self.service.kill()
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self.service.wait()
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def test_server_startup(self):
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"""
|
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This method tests if the server starts up successfully
|
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"""
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.Health(backend_pb2.HealthMessage())
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self.assertEqual(response.message, b'OK')
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except Exception as err:
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print(err)
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self.fail("Server failed to start")
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finally:
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self.tearDown()
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|
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def test_load_model(self):
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"""
|
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This method tests if the model is loaded successfully
|
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"""
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
|
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response = stub.LoadModel(backend_pb2.ModelOptions(Model="bert-base-nli-mean-tokens"))
|
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self.assertTrue(response.success)
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self.assertEqual(response.message, "Model loaded successfully")
|
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except Exception as err:
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print(err)
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self.fail("LoadModel service failed")
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finally:
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self.tearDown()
|
||||
|
||||
def test_embedding(self):
|
||||
"""
|
||||
This method tests if the embeddings are generated successfully
|
||||
"""
|
||||
try:
|
||||
self.setUp()
|
||||
with grpc.insecure_channel("localhost:50051") as channel:
|
||||
stub = backend_pb2_grpc.BackendStub(channel)
|
||||
response = stub.LoadModel(backend_pb2.ModelOptions(Model="bert-base-nli-mean-tokens"))
|
||||
self.assertTrue(response.success)
|
||||
embedding_request = backend_pb2.PredictOptions(Embeddings="This is a test sentence.")
|
||||
embedding_response = stub.Embedding(embedding_request)
|
||||
self.assertIsNotNone(embedding_response.embeddings)
|
||||
except Exception as err:
|
||||
print(err)
|
||||
self.fail("Embedding service failed")
|
||||
finally:
|
||||
self.tearDown()
|
||||
@ -1,6 +0,0 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
source $(dirname $0)/../common/libbackend.sh
|
||||
|
||||
runUnittests
|
||||
@ -25,6 +25,8 @@ from transformers import AutoTokenizer, AutoModel, set_seed, TextIteratorStreame
|
||||
from transformers import AutoProcessor, MusicgenForConditionalGeneration
|
||||
from scipy.io import wavfile
|
||||
import outetts
|
||||
from sentence_transformers import SentenceTransformer
|
||||
|
||||
|
||||
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
|
||||
|
||||
@ -88,10 +90,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
self.CUDA = torch.cuda.is_available()
|
||||
self.OV=False
|
||||
self.OuteTTS=False
|
||||
self.SentenceTransformer = False
|
||||
|
||||
device_map="cpu"
|
||||
|
||||
quantization = None
|
||||
autoTokenizer = True
|
||||
|
||||
if self.CUDA:
|
||||
from transformers import BitsAndBytesConfig, AutoModelForCausalLM
|
||||
@ -195,9 +199,11 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
device=device_map)
|
||||
self.OV = True
|
||||
elif request.Type == "MusicgenForConditionalGeneration":
|
||||
autoTokenizer = False
|
||||
self.processor = AutoProcessor.from_pretrained(model_name)
|
||||
self.model = MusicgenForConditionalGeneration.from_pretrained(model_name)
|
||||
elif request.Type == "OuteTTS":
|
||||
autoTokenizer = False
|
||||
options = request.Options
|
||||
MODELNAME = "OuteAI/OuteTTS-0.3-1B"
|
||||
TOKENIZER = "OuteAI/OuteTTS-0.3-1B"
|
||||
@ -235,6 +241,10 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
self.speaker = self.interface.create_speaker(audio_path=self.AudioPath)
|
||||
else:
|
||||
self.speaker = self.interface.load_default_speaker(name=SPEAKER)
|
||||
elif request.Type == "SentenceTransformer":
|
||||
autoTokenizer = False
|
||||
self.model = SentenceTransformer(model_name, trust_remote_code=request.TrustRemoteCode)
|
||||
self.SentenceTransformer = True
|
||||
else:
|
||||
print("Automodel", file=sys.stderr)
|
||||
self.model = AutoModel.from_pretrained(model_name,
|
||||
@ -250,7 +260,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
else:
|
||||
self.max_tokens = 512
|
||||
|
||||
if request.Type != "MusicgenForConditionalGeneration":
|
||||
if autoTokenizer:
|
||||
self.tokenizer = AutoTokenizer.from_pretrained(model_name, use_safetensors=True)
|
||||
self.XPU = False
|
||||
|
||||
@ -286,18 +296,26 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
max_length = 512
|
||||
if request.Tokens != 0:
|
||||
max_length = request.Tokens
|
||||
encoded_input = self.tokenizer(request.Embeddings, padding=True, truncation=True, max_length=max_length, return_tensors="pt")
|
||||
|
||||
# Create word embeddings
|
||||
if self.CUDA:
|
||||
encoded_input = encoded_input.to("cuda")
|
||||
embeds = None
|
||||
|
||||
with torch.no_grad():
|
||||
model_output = self.model(**encoded_input)
|
||||
if self.SentenceTransformer:
|
||||
print("Calculated embeddings for: " + request.Embeddings, file=sys.stderr)
|
||||
embeds = self.model.encode(request.Embeddings)
|
||||
else:
|
||||
encoded_input = self.tokenizer(request.Embeddings, padding=True, truncation=True, max_length=max_length, return_tensors="pt")
|
||||
|
||||
# Pool to get sentence embeddings; i.e. generate one 1024 vector for the entire sentence
|
||||
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
|
||||
return backend_pb2.EmbeddingResult(embeddings=sentence_embeddings[0])
|
||||
# Create word embeddings
|
||||
if self.CUDA:
|
||||
encoded_input = encoded_input.to("cuda")
|
||||
|
||||
with torch.no_grad():
|
||||
model_output = self.model(**encoded_input)
|
||||
|
||||
# Pool to get sentence embeddings; i.e. generate one 1024 vector for the entire sentence
|
||||
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
|
||||
embeds = sentence_embeddings[0]
|
||||
return backend_pb2.EmbeddingResult(embeddings=embeds)
|
||||
|
||||
async def _predict(self, request, context, streaming=False):
|
||||
set_seed(request.Seed)
|
||||
|
||||
@ -3,4 +3,5 @@ llvmlite==0.43.0
|
||||
accelerate
|
||||
transformers
|
||||
bitsandbytes
|
||||
outetts
|
||||
outetts
|
||||
sentence-transformers==3.3.1
|
||||
|
||||
@ -4,4 +4,5 @@ llvmlite==0.43.0
|
||||
accelerate
|
||||
transformers
|
||||
bitsandbytes
|
||||
outetts
|
||||
outetts
|
||||
sentence-transformers==3.3.1
|
||||
|
||||
@ -3,4 +3,5 @@ accelerate
|
||||
llvmlite==0.43.0
|
||||
transformers
|
||||
bitsandbytes
|
||||
outetts
|
||||
outetts
|
||||
sentence-transformers==3.3.1
|
||||
|
||||
@ -4,4 +4,6 @@ accelerate
|
||||
transformers
|
||||
llvmlite==0.43.0
|
||||
bitsandbytes
|
||||
outetts
|
||||
outetts
|
||||
bitsandbytes
|
||||
sentence-transformers==3.3.1
|
||||
|
||||
@ -6,4 +6,5 @@ optimum[openvino]
|
||||
llvmlite==0.43.0
|
||||
intel-extension-for-transformers
|
||||
bitsandbytes
|
||||
outetts
|
||||
outetts
|
||||
sentence-transformers==3.3.1
|
||||
|
||||
@ -133,5 +133,41 @@ class TestBackendServicer(unittest.TestCase):
|
||||
except Exception as err:
|
||||
print(err)
|
||||
self.fail("SoundGeneration service failed")
|
||||
finally:
|
||||
self.tearDown()
|
||||
|
||||
def test_embed_load_model(self):
|
||||
"""
|
||||
This method tests if the model is loaded successfully
|
||||
"""
|
||||
try:
|
||||
self.setUp()
|
||||
with grpc.insecure_channel("localhost:50051") as channel:
|
||||
stub = backend_pb2_grpc.BackendStub(channel)
|
||||
response = stub.LoadModel(backend_pb2.ModelOptions(Model="bert-base-nli-mean-tokens",Type="SentenceTransformer"))
|
||||
self.assertTrue(response.success)
|
||||
self.assertEqual(response.message, "Model loaded successfully")
|
||||
except Exception as err:
|
||||
print(err)
|
||||
self.fail("LoadModel service failed")
|
||||
finally:
|
||||
self.tearDown()
|
||||
|
||||
def test_sentencetransformers_embedding(self):
|
||||
"""
|
||||
This method tests if the embeddings are generated successfully
|
||||
"""
|
||||
try:
|
||||
self.setUp()
|
||||
with grpc.insecure_channel("localhost:50051") as channel:
|
||||
stub = backend_pb2_grpc.BackendStub(channel)
|
||||
response = stub.LoadModel(backend_pb2.ModelOptions(Model="bert-base-nli-mean-tokens",Type="SentenceTransformer"))
|
||||
self.assertTrue(response.success)
|
||||
embedding_request = backend_pb2.PredictOptions(Embeddings="This is a test sentence.")
|
||||
embedding_response = stub.Embedding(embedding_request)
|
||||
self.assertIsNotNone(embedding_response.embeddings)
|
||||
except Exception as err:
|
||||
print(err)
|
||||
self.fail("Embedding service failed")
|
||||
finally:
|
||||
self.tearDown()
|
||||
@ -822,7 +822,7 @@ var _ = Describe("API test", func() {
|
||||
|
||||
application, err := application.New(
|
||||
append(commonOpts,
|
||||
config.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
|
||||
config.WithExternalBackend("transformers", os.Getenv("HUGGINGFACE_GRPC")),
|
||||
config.WithContext(c),
|
||||
config.WithModelPath(modelPath),
|
||||
)...)
|
||||
|
||||
@ -22,11 +22,19 @@ import (
|
||||
)
|
||||
|
||||
var Aliases map[string]string = map[string]string{
|
||||
"go-llama": LLamaCPP,
|
||||
"llama": LLamaCPP,
|
||||
"embedded-store": LocalStoreBackend,
|
||||
"langchain-huggingface": LCHuggingFaceBackend,
|
||||
"transformers-musicgen": TransformersBackend,
|
||||
"go-llama": LLamaCPP,
|
||||
"llama": LLamaCPP,
|
||||
"embedded-store": LocalStoreBackend,
|
||||
"huggingface-embeddings": TransformersBackend,
|
||||
"langchain-huggingface": LCHuggingFaceBackend,
|
||||
"transformers-musicgen": TransformersBackend,
|
||||
"sentencetransformers": TransformersBackend,
|
||||
}
|
||||
|
||||
var TypeAlias map[string]string = map[string]string{
|
||||
"sentencetransformers": "SentenceTransformer",
|
||||
"huggingface-embeddings": "SentenceTransformer",
|
||||
"transformers-musicgen": "MusicgenForConditionalGeneration",
|
||||
}
|
||||
|
||||
var AutoDetect = os.Getenv("DISABLE_AUTODETECT") != "true"
|
||||
@ -396,6 +404,7 @@ func (ml *ModelLoader) grpcModel(backend string, autodetect bool, o *Options) fu
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Wait for the service to start up")
|
||||
log.Debug().Msgf("Options: %+v", o.gRPCOptions)
|
||||
|
||||
// Wait for the service to start up
|
||||
ready := false
|
||||
@ -460,8 +469,15 @@ func (ml *ModelLoader) backendLoader(opts ...Option) (client grpc.Backend, err e
|
||||
|
||||
backend := strings.ToLower(o.backendString)
|
||||
if realBackend, exists := Aliases[backend]; exists {
|
||||
typeAlias, exists := TypeAlias[backend]
|
||||
if exists {
|
||||
log.Debug().Msgf("'%s' is a type alias of '%s' (%s)", backend, realBackend, typeAlias)
|
||||
o.gRPCOptions.Type = typeAlias
|
||||
} else {
|
||||
log.Debug().Msgf("'%s' is an alias of '%s'", backend, realBackend)
|
||||
}
|
||||
|
||||
backend = realBackend
|
||||
log.Debug().Msgf("%s is an alias of %s", backend, realBackend)
|
||||
}
|
||||
|
||||
ml.stopActiveBackends(o.modelID, o.singleActiveBackend)
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
name: code-search-ada-code-001
|
||||
backend: huggingface
|
||||
backend: sentencetransformers
|
||||
embeddings: true
|
||||
parameters:
|
||||
model: all-MiniLM-L6-v2
|
||||
Loading…
Reference in New Issue
Block a user