* Remove pip install command in windows installation guide * fix chatglm3 installation guide * Fix gemma cpu example * Apply on other examples * fix
		
			
				
	
	
		
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			125 lines
		
	
	
		
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			3.2 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
# Langchain examples
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The examples in this folder shows how to use [LangChain](https://www.langchain.com/) with `ipex-llm` on Intel GPU.
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### 1. Install ipex-llm
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Follow the instructions in [GPU Install Guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Overview/install_gpu.html) to install ipex-llm
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### 2. Install Required Dependencies for langchain examples. 
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```bash
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pip install langchain==0.0.184
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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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```
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### 3. Configures OneAPI environment variables for Linux
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> [!NOTE]
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> Skip this step if you are running on Windows.
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This is a required step on Linux for APT or offline installed oneAPI. Skip this step for PIP-installed oneAPI.
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```bash
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source /opt/intel/oneapi/setvars.sh
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```
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### 4. Runtime Configurations
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For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
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#### 4.1 Configurations for Linux
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<details>
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<summary>For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series</summary>
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```bash
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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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export SYCL_CACHE_PERSISTENT=1
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```
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</details>
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<details>
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<summary>For Intel Data Center GPU Max Series</summary>
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```bash
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export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
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export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
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export SYCL_CACHE_PERSISTENT=1
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export ENABLE_SDP_FUSION=1
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```
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> Note: Please note that `libtcmalloc.so` can be installed by `conda install -c conda-forge -y gperftools=2.10`.
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</details>
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<details>
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<summary>For Intel iGPU</summary>
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```bash
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export SYCL_CACHE_PERSISTENT=1
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export BIGDL_LLM_XMX_DISABLED=1
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```
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</details>
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#### 4.2 Configurations for Windows
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<details>
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<summary>For Intel iGPU</summary>
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```cmd
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set SYCL_CACHE_PERSISTENT=1
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set BIGDL_LLM_XMX_DISABLED=1
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```
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</details>
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<details>
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<summary>For Intel Arc™ A-Series Graphics</summary>
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```cmd
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set SYCL_CACHE_PERSISTENT=1
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```
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</details>
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> [!NOTE]
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> 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.
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### 5. Run the examples
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#### 5.1. Streaming Chat
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```bash
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python chat.py -m MODEL_PATH -q QUESTION
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```
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arguments info:
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- `-m MODEL_PATH`: **required**, path to the model
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- `-q QUESTION`: question to ask. Default is `What is AI?`.
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#### 5.2. RAG (Retrival Augmented Generation)
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```bash
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python rag.py -m <path_to_model> [-q QUESTION] [-i INPUT_PATH]
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```
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arguments info:
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- `-m MODEL_PATH`: **required**, path to the model.
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- `-q QUESTION`: question to ask. Default is `What is IPEX?`.
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- `-i INPUT_PATH`: path to the input doc.
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#### 5.2. Low Bit
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The low_bit example ([low_bit.py](./low_bit.py)) showcases how to use use langchain with low_bit optimized model.
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By `save_low_bit` we save the weights of low_bit model into the target folder.
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> Note: `save_low_bit` only saves the weights of the model. 
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> Users could copy the tokenizer model into the target folder or specify `tokenizer_id` during initialization. 
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```bash
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python low_bit.py -m <path_to_model> -t <path_to_target> [-q <your question>]
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```
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**Runtime Arguments Explained**:
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- `-m MODEL_PATH`: **Required**, the path to the model
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- `-t TARGET_PATH`: **Required**, the path to save the low_bit model
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- `-q QUESTION`: the question |