* Rename bigdl/llm to ipex_llm * rm python/llm/src/bigdl * from bigdl.llm to from ipex_llm  | 
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| .. | ||
| chat.py | ||
| rag.py | ||
| README.md | ||
Langchain examples
The examples in this folder shows how to use LangChain with bigdl-llm on Intel GPU.
1. Install bigdl-llm
Follow the instructions in GPU Install Guide to install bigdl-llm
2. Install Required Dependencies for langchain examples.
pip install langchain==0.0.184
pip install -U chromadb==0.3.25
pip install -U pandas==2.0.3
3. Configures OneAPI environment variables
3.1 Configurations for Linux
source /opt/intel/oneapi/setvars.sh
3.2 Configurations for Windows
call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat"
Note: Please make sure you are using CMD (Anaconda Prompt if using conda) to run the command as PowerShell is not supported.
4. Runtime Configurations
For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
4.1 Configurations for Linux
For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series
export USE_XETLA=OFF
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
For Intel Data Center GPU Max Series
export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
export ENABLE_SDP_FUSION=1
Note: Please note that
libtcmalloc.socan be installed byconda install -c conda-forge -y gperftools=2.10.
4.2 Configurations for Windows
For Intel iGPU
set SYCL_CACHE_PERSISTENT=1
set BIGDL_LLM_XMX_DISABLED=1
For Intel Arc™ A300-Series or Pro A60
set SYCL_CACHE_PERSISTENT=1
For other Intel dGPU Series
There is no need to set further environment variables.
Note: For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile.
5. Run the examples
5.1. Streaming Chat
python chat.py -m MODEL_PATH -q QUESTION
arguments info:
-m MODEL_PATH: required, path to the model-q QUESTION: question to ask. Default isWhat is AI?.
5.1. RAG (Retrival Augmented Generation)
python rag.py -m <path_to_model> [-q QUESTION] [-i INPUT_PATH]
arguments info:
-m MODEL_PATH: required, path to the model.-q QUESTION: question to ask. Default isWhat is BigDL?.-i INPUT_PATH: path to the input doc.