Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM 等语言模型的本地知识库问答 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM) QA app with langchain。

        开源网址：https://github.com/chatchat-space/Langchain-Chatchat

​        因为这是自己毕设项目所需，利用虚拟机实验一下是否能成功部署。项目参考：Langchain-Chatchat-win10本地安装部署成功笔记（CPU）_file "d:\ai\virtual-digital-human\langchain-chatch-CSDN博客

其中有些是自己遇到的坑也会在这里说一下。

一、实验环境

可以查看目前使用的系统版本信息。

cat /proc/version

Linux version 5.15.133.1-microsoft-standard-WSL2 (root@1c602f52c2e4) (gcc (GCC) 11.2.0, GNU ld (GNU Binutils) 2.37) #1 SMP Thu Oct 5 21:02:42 UTC 2023

如果安装有显卡驱动，可以使用下面的代码来查看显卡信息。

nvidia-smi  #查看显卡信息  Sat Mar  9 19:31:33 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 550.40.06              Driver Version: 551.23         CUDA Version: 12.4     | |-----------------------------------------+------------------------+----------------------+ | GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC | | Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. | |                                         |                        |               MIG M. | |=========================================+========================+======================| |   0  NVIDIA GeForce RTX 3090        On  |   00000000:AF:00.0 Off |                  N/A | | 32%   25C    P8              6W /  350W |     134MiB /  24576MiB |      0%      Default | |                                         |                        |                  N/A | +-----------------------------------------+------------------------+----------------------+ |   1  NVIDIA GeForce RTX 3090        On  |   00000000:D8:00.0 Off |                  N/A | | 32%   24C    P8             11W /  350W |     144MiB /  24576MiB |      0%      Default | |                                         |                        |                  N/A | +-----------------------------------------+------------------------+----------------------+                                                                                     +-----------------------------------------------------------------------------------------+ | Processes:                                                                              | |  GPU   GI   CI        PID   Type   Process name                              GPU Memory | |        ID   ID                                                               Usage      | |=========================================================================================| |    0   N/A  N/A       227      G   /Xwayland                                   N/A      | |    1   N/A  N/A       227      G   /Xwayland                                   N/A      | +-----------------------------------------------------------------------------------------+ 

二、安装步骤

1、安装 Anaconda软件，用于管理python虚拟环境

自己使用的是清华镜像：Index of /anaconda/archive/ | 清华大学开源软件镜像站 | Tsinghua Open Source Mirror

wget下载命令如下：

 wget -c 'https://repo.anaconda.com/archive/Anaconda3-2023.09-0-Linux-x86_64.sh' -P <下载到的文件的位置>

 2、创建python运行虚拟环境

​

创建 conda 环境

conda create -n chatchat python=3.11.7

可以通过 conda info --envs 检查环境是否创建完成。

# conda environments: # base                     /home/david/anaconda3 NAD                      /home/david/anaconda3/envs/NAD chat                     /home/david/anaconda3/envs/chat chat_demo                /home/david/anaconda3/envs/chat_demo 

进入已经创建好的虚拟环境：conda activate 环境名称 或 source activate 环境名称

$ conda activate chat_demo (chat_demo) $ python --version Python 3.11.7 

3、安装pytorch

~$ pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 -i https://pypi.tuna.tsinghua.edu.cn/simple

Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting torch   Downloading https://pypi.tuna.tsinghua.edu.cn/packages/2c/df/5810707da6f2fd4be57f0cc417987c0fa16a2eecf0b1b71f82ea555dc619/torch-2.2.1-cp311-cp311-manylinux1_x86_64.whl (755.6 MB)      ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 755.6/755.6 MB 2.4 MB/s eta 0:00:00 Collecting torchvision   Downloading https://pypi.tuna.tsinghua.edu.cn/packages/3a/49/12fc5188602c68a789a0fdaee63d176a71ad5c1e34d25aeb8554abe46089/torchvision-0.17.1-cp311-cp311-manylinux1_x86_64.whl (6.9 MB)      ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.9/6.9 MB 6.6 MB/s eta 0:00:00 Collecting torchaudio   Downloading https://pypi.tuna.tsinghua.edu.cn/packages/a6/57/ccebdda4db80e384166c70d8645fa998637051b3b19aca1fd8de80602afb/torchaudio-2.2.1-cp311-cp311-manylinux1_x86_64.whl (3.3 MB)      ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.3/3.3 MB 6.7 MB/s eta 0:00:00 Collecting filelock (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl (11 kB) Collecting typing-extensions>=4.8.0 (from torch)   Downloading https://pypi.tuna.tsinghua.edu.cn/packages/f9/de/dc04a3ea60b22624b51c703a84bbe0184abcd1d0b9bc8074b5d6b7ab90bb/typing_extensions-4.10.0-py3-none-any.whl (33 kB) Collecting sympy (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/d2/05/e6600db80270777c4a64238a98d442f0fd07cc8915be2a1c16da7f2b9e74/sympy-1.12-py3-none-any.whl (5.7 MB) Collecting networkx (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/d5/f0/8fbc882ca80cf077f1b246c0e3c3465f7f415439bdea6b899f6b19f61f70/networkx-3.2.1-py3-none-any.whl (1.6 MB) Collecting jinja2 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/30/6d/6de6be2d02603ab56e72997708809e8a5b0fbfee080735109b40a3564843/Jinja2-3.1.3-py3-none-any.whl (133 kB) Collecting fsspec (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/ad/30/2281c062222dc39328843bd1ddd30ff3005ef8e30b2fd09c4d2792766061/fsspec-2024.2.0-py3-none-any.whl (170 kB) Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b6/9f/c64c03f49d6fbc56196664d05dba14e3a561038a81a638eeb47f4d4cfd48/nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB) Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/eb/d5/c68b1d2cdfcc59e72e8a5949a37ddb22ae6cade80cd4a57a84d4c8b55472/nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB) Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7e/00/6b218edd739ecfc60524e585ba8e6b00554dd908de2c9c66c1af3e44e18d/nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB) Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/ff/74/a2e2be7fb83aaedec84f391f082cf765dfb635e7caa9b49065f73e4835d8/nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB) Collecting nvidia-cublas-cu12==12.1.3.1 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/37/6d/121efd7382d5b0284239f4ab1fc1590d86d34ed4a4a2fdb13b30ca8e5740/nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB) Collecting nvidia-cufft-cu12==11.0.2.54 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/86/94/eb540db023ce1d162e7bea9f8f5aa781d57c65aed513c33ee9a5123ead4d/nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB) Collecting nvidia-curand-cu12==10.3.2.106 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/44/31/4890b1c9abc496303412947fc7dcea3d14861720642b49e8ceed89636705/nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB) Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB) Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB) Collecting nvidia-nccl-cu12==2.19.3 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/38/00/d0d4e48aef772ad5aebcf70b73028f88db6e5640b36c38e90445b7a57c45/nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB) Collecting nvidia-nvtx-cu12==12.1.105 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/da/d3/8057f0587683ed2fcd4dbfbdfdfa807b9160b809976099d36b8f60d08f03/nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB) Collecting triton==2.2.0 (from torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/bd/ac/3974caaa459bf2c3a244a84be8d17561f631f7d42af370fc311defeca2fb/triton-2.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (167.9 MB) Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch)   Downloading https://pypi.tuna.tsinghua.edu.cn/packages/58/d1/d1c80553f9d5d07b6072bc132607d75a0ef3600e28e1890e11c0f55d7346/nvidia_nvjitlink_cu12-12.4.99-py3-none-manylinux2014_x86_64.whl (21.1 MB)      ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 21.1/21.1 MB 6.6 MB/s eta 0:00:00 Collecting numpy (from torchvision)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/3a/d0/edc009c27b406c4f9cbc79274d6e46d634d139075492ad055e3d68445925/numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.3 MB) Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/66/9c/2e1877630eb298bbfd23f90deeec0a3f682a4163d5ca9f178937de57346c/pillow-10.2.0-cp311-cp311-manylinux_2_28_x86_64.whl (4.5 MB) Collecting MarkupSafe>=2.0 (from jinja2->torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/97/18/c30da5e7a0e7f4603abfc6780574131221d9148f323752c2755d48abad30/MarkupSafe-2.1.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (28 kB) Collecting mpmath>=0.19 (from sympy->torch)   Using cached https://pypi.tuna.tsinghua.edu.cn/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl (536 kB) Installing collected packages: mpmath, typing-extensions, sympy, pillow, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, networkx, MarkupSafe, fsspec, filelock, triton, nvidia-cusparse-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch, torchvision, torchaudio Successfully installed MarkupSafe-2.1.5 filelock-3.13.1 fsspec-2024.2.0 jinja2-3.1.3 mpmath-1.3.0 networkx-3.2.1 numpy-1.26.4 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.99 nvidia-nvtx-cu12-12.1.105 pillow-10.2.0 sympy-1.12 torch-2.2.1 torchaudio-2.2.1 torchvision-0.17.1 triton-2.2.0 typing-extensions-4.10.0 

验证是否安装成功：

~$ python Python 3.11.7 (main, Dec 15 2023, 18:12:31) [GCC 11.2.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import torch >>> x = torch.rand(5,3) >>> print(x) tensor([[0.8278, 0.8746, 0.1025],         [0.7528, 0.6855, 0.7386],         [0.6271, 0.1371, 0.1849],         [0.4098, 0.3203, 0.7615],         [0.5088, 0.7645, 0.8044]]) 

4、拉取Langchain-Chatchat源代码

 有两种方式获取源代码，一种是获取最新代码，一种是获取指定版本的源代码。

# 拉取仓库

git clone https://github.com/chatchat-space/Langchain-Chatchat.git

# 指定版本获取代码

git clone -b v0.2.9 https://github.com/chatchat-space/Langchain-Chatchat.git

在拉取源代码之前先安装 git

5、安装依赖包

cd Langchain-Chatchat  pip3 install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple/ 

Found existing installation: triton 2.2.0     Uninstalling triton-2.2.0:       Successfully uninstalled triton-2.2.0   Attempting uninstall: pillow     Found existing installation: pillow 10.2.0     Uninstalling pillow-10.2.0:       Successfully uninstalled pillow-10.2.0   Attempting uninstall: nvidia-nccl-cu12     Found existing installation: nvidia-nccl-cu12 2.19.3     Uninstalling nvidia-nccl-cu12-2.19.3:       Successfully uninstalled nvidia-nccl-cu12-2.19.3   Attempting uninstall: numpy     Found existing installation: numpy 1.26.4     Uninstalling numpy-1.26.4:       Successfully uninstalled numpy-1.26.4   Attempting uninstall: torch     Found existing installation: torch 2.2.1     Uninstalling torch-2.2.1:       Successfully uninstalled torch-2.2.1   Attempting uninstall: torchvision     Found existing installation: torchvision 0.17.1     Uninstalling torchvision-0.17.1:       Successfully uninstalled torchvision-0.17.1   Attempting uninstall: torchaudio     Found existing installation: torchaudio 2.2.1     Uninstalling torchaudio-2.2.1:       Successfully uninstalled torchaudio-2.2.1 Successfully installed PyMuPDF-1.23.16 PyMuPDFb-1.23.9 SQLAlchemy-2.0.25 Shapely-2.0.3 XlsxWriter-3.2.0 accelerate-0.24.1 aiofiles-23.2.1 aiohttp-3.9.3 aioprometheus-23.12.0 aiosignal-1.3.1 altair-5.2.0 antlr4-python3-runtime-4.9.3 anyio-4.3.0 arxiv-2.1.0 attrs-23.2.0 backoff-2.2.1 beautifulsoup4-4.12.3 blinker-1.7.0 blis-0.7.11 brotli-1.1.0 cachetools-5.3.3 catalogue-2.0.10 certifi-2024.2.2 cffi-1.16.0 chardet-5.2.0 charset-normalizer-3.3.2 click-8.1.7 cloudpathlib-0.16.0 coloredlogs-15.0.1 confection-0.1.4 contourpy-1.2.0 cryptography-42.0.5 cycler-0.12.1 cymem-2.0.8 dataclasses-json-0.6.4 deepdiff-6.7.1 deprecated-1.2.14 deprecation-2.1.0 distro-1.9.0 duckduckgo-search-3.9.9 effdet-0.4.1 einops-0.7.0 emoji-2.10.1 et-xmlfile-1.1.0 faiss-cpu-1.7.4 fastapi-0.109.0 feedparser-6.0.10 filetype-1.2.0 flatbuffers-24.3.7 fonttools-4.49.0 frozenlist-1.4.1 fschat-0.2.35 gitdb-4.0.11 gitpython-3.1.42 greenlet-3.0.3 h11-0.14.0 h2-4.1.0 hpack-4.0.0 httpcore-1.0.4 httptools-0.6.1 httpx-0.26.0 httpx_sse-0.4.0 huggingface-hub-0.21.4 humanfriendly-10.0 hyperframe-6.0.1 idna-3.6 importlib-metadata-7.0.2 iniconfig-2.0.0 iopath-0.1.10 joblib-1.3.2 jsonpatch-1.33 jsonpath-python-1.0.6 jsonpointer-2.4 jsonschema-4.21.1 jsonschema-specifications-2023.12.1 kiwisolver-1.4.5 langchain-0.0.354 langchain-community-0.0.20 langchain-core-0.1.23 langchain-experimental-0.0.47 langcodes-3.3.0 langdetect-1.0.9 langsmith-0.0.87 layoutparser-0.3.4 llama-index-0.9.35 lxml-5.1.0 markdown-3.5.2 markdown-it-py-3.0.0 markdown2-2.4.13 markdownify-0.11.6 marshmallow-3.21.1 matplotlib-3.8.3 mdurl-0.1.2 metaphor-python-0.1.23 msg-parser-1.2.0 msgpack-1.0.8 multidict-6.0.5 murmurhash-1.0.10 mypy-extensions-1.0.0 nest-asyncio-1.6.0 nh3-0.2.15 ninja-1.11.1.1 nltk-3.8.1 numexpr-2.8.6 numpy-1.24.4 nvidia-nccl-cu12-2.18.1 olefile-0.47 omegaconf-2.3.0 onnx-1.15.0 onnxruntime-1.15.1 openai-1.9.0 opencv-python-4.9.0.80 openpyxl-3.1.2 ordered-set-4.1.0 orjson-3.9.15 packaging-23.2 pandas-2.0.3 pathlib-1.0.1 pdf2image-1.17.0 pdfminer.six-20231228 pdfplumber-0.11.0 pikepdf-8.4.1 pillow-9.5.0 pillow-heif-0.15.0 pluggy-1.4.0 portalocker-2.8.2 preshed-3.0.9 prompt-toolkit-3.0.43 protobuf-4.25.3 psutil-5.9.8 pyarrow-15.0.1 pyclipper-1.3.0.post5 pycocotools-2.0.7 pycparser-2.21 pydantic-1.10.13 pydeck-0.8.1b0 pygments-2.17.2 pyjwt-2.8.0 pypandoc-1.13 pyparsing-3.1.2 pypdf-4.1.0 pypdfium2-4.27.0 pytesseract-0.3.10 pytest-7.4.3 python-dateutil-2.9.0.post0 python-decouple-3.8 python-docx-1.1.0 python-dotenv-1.0.1 python-iso639-2024.2.7 python-magic-0.4.27 python-multipart-0.0.9 python-pptx-0.6.23 pytz-2024.1 pyyaml-6.0.1 quantile-python-1.1 rapidfuzz-3.6.2 rapidocr_onnxruntime-1.3.8 ray-2.9.3 referencing-0.33.0 regex-2023.12.25 requests-2.31.0 rich-13.7.1 rpds-py-0.18.0 safetensors-0.4.2 scikit-learn-1.4.1.post1 scipy-1.12.0 sentence_transformers-2.2.2 sentencepiece-0.2.0 sgmllib3k-1.0.0 shortuuid-1.0.12 simplejson-3.19.2 six-1.16.0 smart-open-6.4.0 smmap-5.0.1 sniffio-1.3.1 socksio-1.0.0 soupsieve-2.5 spacy-3.7.2 spacy-legacy-3.0.12 spacy-loggers-1.0.5 srsly-2.4.8 sse_starlette-1.8.2 starlette-0.35.0 streamlit-1.30.0 streamlit-aggrid-0.3.4.post3 streamlit-antd-components-0.3.1 streamlit-chatbox-1.1.11 streamlit-feedback-0.1.3 streamlit-modal-0.1.0 streamlit-option-menu-0.3.12 strsimpy-0.2.1 svgwrite-1.4.3 tabulate-0.9.0 tenacity-8.2.3 thinc-8.2.3 threadpoolctl-3.3.0 tiktoken-0.5.2 timm-0.9.16 tokenizers-0.15.2 toml-0.10.2 toolz-0.12.1 torch-2.1.2 torchaudio-2.1.2 torchvision-0.16.2 tornado-6.4 tqdm-4.66.1 transformers-4.37.2 transformers_stream_generator-0.0.4 triton-2.1.0 typer-0.9.0 typing-inspect-0.9.0 tzdata-2024.1 tzlocal-5.2 unstructured-0.12.5 unstructured-client-0.21.1 unstructured-inference-0.7.23 unstructured.pytesseract-0.3.12 urllib3-2.2.1 uvicorn-0.28.0 uvloop-0.19.0 validators-0.22.0 vllm-0.2.7 wasabi-1.1.2 watchdog-3.0.0 watchfiles-0.21.0 wavedrom-2.0.3.post3 wcwidth-0.2.13 weasel-0.3.4 websockets-12.0 wrapt-1.16.0 xformers-0.0.23.post1 xlrd-2.0.1 yarl-1.9.4 youtube-search-2.1.2 zipp-3.17.0 

6、下载模型

下载两个模型：M3e-base 内置模型和 chatglm3-6b 模型。

sudo apt-get install git-lfs  git clone https://gitee.com/hf-models/m3e-base.git  git clone https://gitee.com/hf-models/chatglm-6b.git

如果需要上 huggingface.co 获取模型可能需要科学上网工具。

7、修改配置文件

批量修改配置文件名

批量复制configs目录下所有的配置文件，去掉example后缀：

# cd Langchain-Chatchat # 批量复制configs目录下所有配置文件，去掉example python copy_config_example.py

修改model_config.py文件

修改m3e-base的模型本地路径(注意是双反斜杠"\\")：

修改server_config.py

0.2.6之前版本，需要修改0.0.0.0为127.0.0.1不然会报错。

# 各服务器默认绑定host。如改为"0.0.0.0"需要修改下方所有XX_SERVER的host DEFAULT_BIND_HOST = "127.0.0.1" if sys.platform != "win32" else "127.0.0.1"

8、初始化数据库

python init_database.py --recreate-vs

配置里面模型的运行设置设置为 auto （还是建议用显卡跑）

9、一键启动项目

运行：

python startup.py -a

==============================Langchain-Chatchat Configuration============================== 操作系统：Linux-5.15.133.1-microsoft-standard-WSL2-x86_64-with-glibc2.35. python版本：3.11.7 (main, Dec 15 2023, 18:12:31) [GCC 11.2.0] 项目版本：v0.2.10 langchain版本：0.0.354. fastchat版本：0.2.35   当前使用的分词器：ChineseRecursiveTextSplitter 当前启动的LLM模型：['chatglm3-6b'] @ cuda {'device': 'cuda',  'host': '127.0.0.1',  'infer_turbo': False,  'model_path': 'model/chatglm3-6b',  'model_path_exists': True,  'port': 20002} 当前Embbedings模型： m3e-base @ cuda ==============================Langchain-Chatchat Configuration==============================   2024-03-09 20:18:03,837 - startup.py[line:655] - INFO: 正在启动服务： 2024-03-09 20:18:03,838 - startup.py[line:656] - INFO: 如需查看 llm_api 日志，请前往 /home/david/20240207/Langchain-Chatchat/logs /home/david/anaconda3/envs/chat_demo/lib/python3.11/site-packages/langchain_core/_api/deprecation.py:117: LangChainDeprecationWarning: 模型启动功能将于 Langchain-Chatchat 0.3.x重写,支持更多模式和加速启动，0.2.x中相关功能将废弃   warn_deprecated( 2024-03-09 20:18:10 | ERROR | stderr | INFO:     Started server process [329625] 2024-03-09 20:18:10 | ERROR | stderr | INFO:     Waiting for application startup. 2024-03-09 20:18:10 | ERROR | stderr | INFO:     Application startup complete. 2024-03-09 20:18:10 | ERROR | stderr | INFO:     Uvicorn running on http://127.0.0.1:20000 (Press CTRL+C to quit) 2024-03-09 20:18:10 | INFO | model_worker | Loading the model ['chatglm3-6b'] on worker 7b784767 ... Loading checkpoint shards:   0%|                                                                                               | 0/7 [00:00

ssh -L 8501:127.0.0.1:8501 llama@172.17.135.6 -N 

AttributeError: 'NoneType' object has no attribute 'int4WeightExtractionHalf'

pip install cpm_kernels