Update llamaindex ut (#10338)
* add test_llamaindex of gpu * add llamaindex gpu tests bash * add llamaindex cpu tests bash * update name of Run LLM langchain GPU test * import llama_index in llamaindex gpu ut * update the dependency of test_llamaindex * add Run LLM llamaindex GPU test * modify import dependency of llamaindex cpu test * add Run LLM llamaindex test * update llama_model_path * delete unused model path * add LLAMA2_7B_ORIGIN_PATH in llamaindex cpu test
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5 changed files with 136 additions and 21 deletions
27
.github/workflows/llm_unit_tests.yml
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27
.github/workflows/llm_unit_tests.yml
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@ -102,6 +102,7 @@ jobs:
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echo "ORIGINAL_REPLIT_CODE_PATH=${ORIGIN_DIR}/replit-code-v1-3b" >> "$GITHUB_ENV"
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echo "ORIGINAL_WHISPER_TINY_PATH=${ORIGIN_DIR}/whisper-tiny" >> "$GITHUB_ENV"
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echo "MISTRAL_ORIGIN_PATH=${ORIGIN_DIR}/Mistral-7B-v0.1" >> "$GITHUB_ENV"
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echo "LLAMA2_7B_ORIGIN_PATH=${ORIGIN_DIR}/Llama-2-7b-chat-hf" >> "$GITHUB_ENV"
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echo "LLAMA_INT4_CKPT_PATH=${INT4_CKPT_DIR}/bigdl_llm_llama_7b_q4_0.bin" >> "$GITHUB_ENV"
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echo "GPTNEOX_INT4_CKPT_PATH=${INT4_CKPT_DIR}/bigdl_llm_redpajama_7b_q4_0.bin" >> "$GITHUB_ENV"
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@ -190,6 +191,10 @@ jobs:
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echo "wget -r -nH --no-verbose --cut-dirs=2 $LLM_FTP_URL/llm/datasets/common_voice -P $DATASET_DIR"
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wget -r -nH --no-verbose --cut-dirs=2 $LLM_FTP_URL/llm/datasets/common_voice -P $DATASET_DIR
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fi
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if [ ! -d $LLAMA2_7B_ORIGIN_PATH ]; then
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echo "Directory $LLAMA2_7B_ORIGIN_PATH not found. Downloading from FTP server..."
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wget -r -nH --no-verbose --cut-dirs=1 $LLM_FTP_URL/llm/Llama-2-7b-chat-hf -P $ORIGIN_DIR
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fi
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- name: Run LLM cli test (Linux)
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if: runner.os == 'Linux'
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@ -209,6 +214,12 @@ jobs:
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pip install -U chromadb==0.3.25
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pip install -U pandas==2.0.3
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bash python/llm/test/run-llm-langchain-tests.sh
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- name: Run LLM llamaindex test
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shell: bash
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run: |
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pip install llama-index-readers-file llama-index-vector-stores-postgres llama-index-embeddings-huggingface
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pip install transformers==4.31.0
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bash python/llm/test/run-llm-llamaindex-tests.sh
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llm-unit-test-on-arc:
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needs: [setup-python-version, llm-cpp-build]
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strategy:
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@ -347,7 +358,7 @@ jobs:
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fi
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bash python/llm/test/run-llm-example-tests-gpu.sh
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- name: Run LLM langchain test
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- name: Run LLM langchain GPU test
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shell: bash
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run: |
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pip install -U langchain==0.0.184
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@ -360,3 +371,17 @@ jobs:
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source /home/arda/intel/oneapi/setvars.sh
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fi
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bash python/llm/test/run-llm-langchain-tests-gpu.sh
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- name: Run LLM llamaindex GPU test
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shell: bash
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run: |
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pip install llama-index-readers-file llama-index-vector-stores-postgres llama-index-embeddings-huggingface
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# Specific oneapi position on arc ut test machines
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if [[ '${{ matrix.pytorch-version }}' == '2.1' ]]; then
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pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
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source /opt/intel/oneapi/setvars.sh
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elif [[ '${{ matrix.pytorch-version }}' == '2.0' ]]; then
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pip install --pre --upgrade bigdl-llm[xpu_2.0] -f https://developer.intel.com/ipex-whl-stable-xpu
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source /home/arda/intel/oneapi/setvars.sh
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fi
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bash python/llm/test/run-llm-llamaindex-tests-gpu.sh
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@ -14,22 +14,6 @@
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# limitations under the License.
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#
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from bigdl.llm.langchain.llms import TransformersLLM, TransformersPipelineLLM, \
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LlamaLLM, BloomLLM
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from bigdl.llm.langchain.embeddings import TransformersEmbeddings, LlamaEmbeddings, \
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BloomEmbeddings
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from langchain.document_loaders import WebBaseLoader
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from langchain.indexes import VectorstoreIndexCreator
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from langchain.chains.question_answering import load_qa_chain
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from langchain.chains.chat_vector_db.prompts import (CONDENSE_QUESTION_PROMPT,
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QA_PROMPT)
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.vectorstores import Chroma
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import pytest
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from unittest import TestCase
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import os
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@ -37,10 +21,7 @@ from bigdl.llm.llamaindex.llms import BigdlLLM
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class Test_LlamaIndex_Transformers_API(TestCase):
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def setUp(self):
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self.auto_model_path = os.environ.get('ORIGINAL_CHATGLM2_6B_PATH')
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self.auto_causal_model_path = os.environ.get('ORIGINAL_REPLIT_CODE_PATH')
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self.llama_model_path = os.environ.get('LLAMA_ORIGIN_PATH')
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self.bloom_model_path = os.environ.get('BLOOM_ORIGIN_PATH')
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self.llama_model_path = os.environ.get('LLAMA2_7B_ORIGIN_PATH')
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thread_num = os.environ.get('THREAD_NUM')
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if thread_num is not None:
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self.n_threads = int(thread_num)
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70
python/llm/test/llamaindex_gpu/test_llamaindex.py
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python/llm/test/llamaindex_gpu/test_llamaindex.py
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@ -0,0 +1,70 @@
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#
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# Copyright 2016 The BigDL Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import torch
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import pytest
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from unittest import TestCase
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import os
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from bigdl.llm.llamaindex.llms import BigdlLLM
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class Test_LlamaIndex_Transformers_API(TestCase):
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def setUp(self):
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self.llama_model_path = os.environ.get('LLAMA2_7B_ORIGIN_PATH')
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thread_num = os.environ.get('THREAD_NUM')
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if thread_num is not None:
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self.n_threads = int(thread_num)
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else:
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self.n_threads = 2
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def completion_to_prompt(completion):
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return f"<|system|>\n</s>\n<|user|>\n{completion}</s>\n<|assistant|>\n"
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def messages_to_prompt(messages):
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prompt = ""
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for message in messages:
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if message.role == "system":
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prompt += f"<|system|>\n{message.content}</s>\n"
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elif message.role == "user":
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prompt += f"<|user|>\n{message.content}</s>\n"
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elif message.role == "assistant":
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prompt += f"<|assistant|>\n{message.content}</s>\n"
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# ensure we start with a system prompt, insert blank if needed
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if not prompt.startswith("<|system|>\n"):
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prompt = "<|system|>\n</s>\n" + prompt
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# add final assistant prompt
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prompt = prompt + "<|assistant|>\n"
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return prompt
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def test_bigdl_llm(self):
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llm = BigdlLLM(
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model_name=self.llama_model_path,
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tokenizer_name=self.llama_model_path,
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context_window=512,
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max_new_tokens=32,
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model_kwargs={},
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generate_kwargs={"temperature": 0.7, "do_sample": False},
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messages_to_prompt=self.messages_to_prompt,
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completion_to_prompt=self.completion_to_prompt,
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device_map="xpu",
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)
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res = llm.complete("What is AI?")
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assert res!=None
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if __name__ == '__main__':
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pytest.main([__file__])
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21
python/llm/test/run-llm-llamaindex-tests-gpu.sh
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21
python/llm/test/run-llm-llamaindex-tests-gpu.sh
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@ -0,0 +1,21 @@
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#!/bin/bash
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export ANALYTICS_ZOO_ROOT=${ANALYTICS_ZOO_ROOT}
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export LLM_HOME=${ANALYTICS_ZOO_ROOT}/python/llm/src
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export LLM_INFERENCE_TEST_DIR=${ANALYTICS_ZOO_ROOT}/python/llm/test/llamaindex_gpu
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export USE_XETLA=OFF
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export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
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set -e
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echo "# Start testing inference"
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start=$(date "+%s")
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python -m pytest -s ${LLM_INFERENCE_TEST_DIR}
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now=$(date "+%s")
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time=$((now-start))
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echo "Bigdl-llm llamaindex gpu tests finished"
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echo "Time used:$time seconds"
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18
python/llm/test/run-llm-llamaindex-tests.sh
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18
python/llm/test/run-llm-llamaindex-tests.sh
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#!/bin/bash
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export ANALYTICS_ZOO_ROOT=${ANALYTICS_ZOO_ROOT}
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export LLM_HOME=${ANALYTICS_ZOO_ROOT}/python/llm/src
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export LLM_INFERENCE_TEST_DIR=${ANALYTICS_ZOO_ROOT}/python/llm/test/llamaindex
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set -e
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echo "# Start testing inference"
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start=$(date "+%s")
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python -m pytest -s ${LLM_INFERENCE_TEST_DIR}
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now=$(date "+%s")
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time=$((now-start))
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echo "Bigdl-llm llamaindex tests finished"
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echo "Time used:$time seconds"
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