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Langchain-Chatchat-win10本地安装部署成功笔记（CPU）_langchain本地部署

作者：空白诗007 | 2024-07-30 00:13:44

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langchain本地部署

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

最近因工作需要，想体验一下ChatGLM的功能，就用手头的think P70笔记本安装部署了一下，自己记录一下，因为网上大部分的作者可能是NLP大咖，所以会忽略一些基础的东西，自己花了不少时间踩坑，分享一下自己的安装日志。

一、硬件环境

笔记本：Thinkpad P70 （二手），内存：64G，硬盘：1G固态，win10, 带有8G显存的显卡NVIDIA RTX

二、安装步骤

1、安装 Anaconda软件，用于管理python虚拟环境

官网地址： Anaconda | The World’s Most Popular Data Science Platform，下载free版的anaconda，按导航默认安装即可。

参考文章：Anaconda安装和入门(超级简单详细的安装步骤)-CSDN博客

安装后，命令行运行 conda --version


D:\opt\l2>conda --version
conda 23.7.4

2、创建python运行虚拟环境

执行命令：conda create -n l2 python=3.10.12


D:\opt\l2>conda create -n l2 python=3.10.12
...
 
done
#
# To activate this environment, use
#
#     $ conda activate l2
#
# To deactivate an active environment, use
#
#     $ conda deactivate

激活虚拟环境: conda activate l2


D:\opt\l2>conda activate l2
 
(l2) D:\opt\l2>python --version
Python 3.10.12
 
(l2) D:\opt\l2>

3、安装pytorch

安装pytorch版本是比较麻烦的事情，有一个比较简单的方法：访问url: Start Locally | PyTorch，自动判断当前系统可安装的版本。如下图：

运行推荐的命令安装pytorch，用清华源：


(l2) D:\opt\l2>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/fa/47/1a7daf04f40715fc1cdc6f1cc3200228a556d06c843e6ceb58883b745e1b/torch-2.1.0-cp310-cp310-win_amd64.whl (192.3 MB)
     ---------------------------------------- 192.3/192.3 MB 4.2 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/59/af/426c2b90f5c4f8aba778746465af9e662680570e950e02379e91c6138285/torchvision-0.16.0-cp310-cp310-win_amd64.whl (1.3 MB)
     ---------------------------------------- 1.3/1.3 MB 4.5 MB/s eta 0:00:00
Collecting torchaudio
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/6b/ba/0e26883fd90f280452bed7edc7906ef9253255f395702751f65fa02afb5c/torchaudio-2.1.0-cp310-cp310-win_amd64.whl (2.3 MB)
     ---------------------------------------- 2.3/2.3 MB 3.7 MB/s eta 0:00:00
Collecting filelock (from torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl (11 kB)
Collecting typing-extensions (from torch)
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/24/21/7d397a4b7934ff4028987914ac1044d3b7d52712f30e2ac7a2ae5bc86dd0/typing_extensions-4.8.0-py3-none-any.whl (31 kB)
Collecting sympy (from torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/d2/05/e6600db80270777c4a64238a98d442f0fd07cc8915be2a1c16da7f2b9e74/sympy-1.12-py3-none-any.whl (5.7 MB)
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Collecting networkx (from torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/d5/f0/8fbc882ca80cf077f1b246c0e3c3465f7f415439bdea6b899f6b19f61f70/networkx-3.2.1-py3-none-any.whl (1.6 MB)
     ---------------------------------------- 1.6/1.6 MB 5.2 MB/s eta 0:00:00
Collecting jinja2 (from torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/bc/c3/f068337a370801f372f2f8f6bad74a5c140f6fda3d9de154052708dd3c65/Jinja2-3.1.2-py3-none-any.whl (133 kB)
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Collecting fsspec (from torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/e8/f6/3eccfb530aac90ad1301c582da228e4763f19e719ac8200752a4841b0b2d/fsspec-2023.10.0-py3-none-any.whl (166 kB)
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Collecting numpy (from torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/57/09/fe9282ffb0217176b0185900945189b6beaec4f94ff46afb76bcd9b68e30/numpy-1.26.1-cp310-cp310-win_amd64.whl (15.8 MB)
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Collecting requests (from torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/70/8e/0e2d847013cb52cd35b38c009bb167a1a26b2ce6cd6965bf26b47bc0bf44/requests-2.31.0-py3-none-any.whl (62 kB)
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Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/2d/7e/18ffce67b6e7637eead295b8a78d293d170d404a633010c3549da9a5e674/Pillow-10.1.0-cp310-cp310-win_amd64.whl (2.6 MB)
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Collecting MarkupSafe>=2.0 (from jinja2->torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/84/a8/c4aebb8a14a1d39d5135eb8233a0b95831cdc42c4088358449c3ed657044/MarkupSafe-2.1.3-cp310-cp310-win_amd64.whl (17 kB)
Collecting charset-normalizer<4,>=2 (from requests->torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/a2/a0/4af29e22cb5942488cf45630cbdd7cefd908768e69bdd90280842e4e8529/charset_normalizer-3.3.2-cp310-cp310-win_amd64.whl (100 kB)
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Collecting idna<4,>=2.5 (from requests->torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/fc/34/3030de6f1370931b9dbb4dad48f6ab1015ab1d32447850b9fc94e60097be/idna-3.4-py3-none-any.whl (61 kB)
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Collecting urllib3<3,>=1.21.1 (from requests->torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/d2/b2/b157855192a68541a91ba7b2bbcb91f1b4faa51f8bae38d8005c034be524/urllib3-2.0.7-py3-none-any.whl (124 kB)
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Collecting certifi>=2017.4.17 (from requests->torchvision)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/4c/dd/2234eab22353ffc7d94e8d13177aaa050113286e93e7b40eae01fbf7c3d9/certifi-2023.7.22-py3-none-any.whl (158 kB)
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Collecting mpmath>=0.19 (from sympy->torch)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl (536 kB)
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Installing collected packages: mpmath, urllib3, typing-extensions, sympy, pillow, numpy, networkx, MarkupSafe, idna, fsspec, filelock, charset-normalizer, certifi, requests, jinja2, torch, torchvision, torchaudio
Successfully installed MarkupSafe-2.1.3 certifi-2023.7.22 charset-normalizer-3.3.2 filelock-3.13.1 fsspec-2023.10.0 idna-3.4 jinja2-3.1.2 mpmath-1.3.0 networkx-3.2.1 numpy-1.26.1 pillow-10.1.0 requests-2.31.0 sympy-1.12 torch-2.1.0 torchaudio-2.1.0 torchvision-0.16.0 typing-extensions-4.8.0 urllib3-2.0.7

验证是否安装成功：


(l2) D:\opt\l2>python
Python 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:34:57) [MSC v.1936 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
False
>>> x = torch.rand(5, 3)
>>> print(x)
tensor([[0.8827, 0.8297, 0.5390],
        [0.4590, 0.8473, 0.4074],
        [0.4045, 0.0082, 0.4121],
        [0.7649, 0.3901, 0.1535],
        [0.5408, 0.8168, 0.8615]])
>>>

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 v0.2.6 https://github.com/chatchat-space/Langchain-Chatchat.git


(l2) D:\opt\l2>git clone https://github.com/chatchat-space/Langchain-Chatchat.git
Cloning into 'Langchain-Chatchat'...
remote: Enumerating objects: 8144, done.
remote: Counting objects: 100% (902/902), done.
remote: Compressing objects: 100% (450/450), done.
remote: Total 8144 (delta 594), reused 690 (delta 449), pack-reused 7242Receiving objects: 100% (8144/8144), 54.07 MiB |
 
Resolving deltas: 100% (4900/4900), done.

5、安装依赖包


cd Langchain-Chatchat
 
# 安装全部依赖 用清华源
pip3 install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple/


(l2) D:\opt\l2\Langchain-Chatchat>pip3 install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple/
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple/
Ignoring vllm: markers 'sys_platform == "linux"' don't match your environment
Collecting langchain>=0.0.319 (from -r requirements.txt (line 1))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/6a/b6/b8687bf07dfd272a62a9b655de96d9e1e5e9199de1a2dc4f6989ace2e9d5/langchain-0.0.330-py3-none-any.whl (2.0 MB)
     ---------------------------------------- 2.0/2.0 MB 5.4 MB/s eta 0:00:00
Collecting langchain-experimental>=0.0.30 (from -r requirements.txt (line 2))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/69/71/c7ace3f7b6580c7cad29549cc5d4a5ee7bb14d5c373b8005862c844b92f4/langchain_experimental-0.0.37-py3-none-any.whl (154 kB)
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Collecting fschat==0.2.31 (from fschat[model_worker]==0.2.31->-r requirements.txt (line 3))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/9c/d1/22b82506f8c0120e25469ce27142ee001ed55da7e917076df278ab777d1e/fschat-0.2.31-py3-none-any.whl (208 kB)
Collecting xformers>=0.0.22.post4 (from -r requirements.txt (line 4))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/71/de/4511904f5e60682b417ac6978cc8393cacb778ab9d9e301d3afd475a3d30/xformers-0.0.22.post7-cp310-cp310-win_amd64.whl (202.1 MB)
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Collecting openai>=0.28.1 (from -r requirements.txt (line 5))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/1e/9f/385c25502f437686e4aa715969e5eaf5c2cb5e5ffa7c5cdd52f3c6ae967a/openai-0.28.1-py3-none-any.whl (76 kB)
Collecting sentence_transformers (from -r requirements.txt (line 6))
  Using cached sentence_transformers-2.2.2-py3-none-any.whl
Collecting transformers>=4.34 (from -r requirements.txt (line 7))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/9a/06/e4ec2a321e57c03b7e9345d709d554a52c33760e5015fdff0919d9459af0/transformers-4.35.0-py3-none-any.whl (7.9 MB)
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Requirement already satisfied: torch>=2.0.1 in c:\users\chenjd\.conda\envs\l2\lib\site-packages (from -r requirements.txt (line 8)) (2.1.0)
Requirement already satisfied: torchvision in c:\users\chenjd\.conda\envs\l2\lib\site-packages (from -r requirements.txt (line 9)) (0.16.0)
Requirement already satisfied: torchaudio in c:\users\chenjd\.conda\envs\l2\lib\site-packages (from -r requirements.txt (line 10)) (2.1.0)
Collecting fastapi>=0.104 (from -r requirements.txt (line 11))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/f3/4f/0ce34195b63240b6693086496c9bab4ef23999112184399a3e88854c7674/fastapi-0.104.1-py3-none-any.whl (92 kB)
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Collecting nltk>=3.8.1 (from -r requirements.txt (line 12))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a6/0a/0d20d2c0f16be91b9fa32a77b76c60f9baf6eba419e5ef5deca17af9c582/nltk-3.8.1-py3-none-any.whl (1.5 MB)
Collecting uvicorn~=0.23.1 (from -r requirements.txt (line 13))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/79/96/b0882a1c3f7ef3dd86879e041212ae5b62b4bd352320889231cc735a8e8f/uvicorn-0.23.2-py3-none-any.whl (59 kB)
Collecting starlette~=0.27.0 (from -r requirements.txt (line 14))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/58/f8/e2cca22387965584a409795913b774235752be4176d276714e15e1a58884/starlette-0.27.0-py3-none-any.whl (66 kB)
Collecting pydantic~=1.10.11 (from -r requirements.txt (line 15))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/87/34/d2dc31739fd781daa4581705f0c2ee5fec9daf258aeed6da1ca0149d1da0/pydantic-1.10.13-cp310-cp310-win_amd64.whl (2.1 MB)
Collecting unstructured>=0.10.12 (from unstructured[all-docs]>=0.10.12->-r requirements.txt (line 16))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/18/47/2a75cf709607f33ad448daaf8a273cb0834c8cb4eaea0819bb17ed926525/unstructured-0.10.28-py3-none-any.whl (1.7 MB)
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Collecting python-magic-bin (from -r requirements.txt (line 17))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/07/c2/094e3d62b906d952537196603a23aec4bcd7c6126bf80eb14e6f9f4be3a2/python_magic_bin-0.4.14-py2.py3-none-win_amd64.whl (409 kB)
Collecting SQLAlchemy==2.0.19 (from -r requirements.txt (line 18))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/71/41/eb74f55dfe9305736430051fc2a77d0479ff80d46aabd832dd583d242ad8/SQLAlchemy-2.0.19-cp310-cp310-win_amd64.whl (2.0 MB)
Collecting faiss-cpu (from -r requirements.txt (line 19))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0a/3d/d5e431cf7f6c55580581ce965baa56de02be374de838791db9d2a81c20e0/faiss_cpu-1.7.4-cp310-cp310-win_amd64.whl (10.8 MB)
Collecting accelerate (from -r requirements.txt (line 20))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/13/9e/ee987874058f2d93006961f6ff49e0bcb60ab9c26709ebe06bfa8707a4d8/accelerate-0.24.1-py3-none-any.whl (261 kB)
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Collecting spacy (from -r requirements.txt (line 21))
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Collecting PyMuPDF (from -r requirements.txt (line 22))
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Collecting rapidocr_onnxruntime (from -r requirements.txt (line 23))
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Requirement already satisfied: requests in c:\users\chenjd\.conda\envs\l2\lib\site-packages (from -r requirements.txt (line 25)) (2.31.0)
Collecting pathlib (from -r requirements.txt (line 26))
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Collecting pytest (from -r requirements.txt (line 27))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/f3/8c/f16efd81ca8e293b2cc78f111190a79ee539d0d5d36ccd49975cb3beac60/pytest-7.4.3-py3-none-any.whl (325 kB)
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Collecting scikit-learn (from -r requirements.txt (line 28))
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Collecting numexpr (from -r requirements.txt (line 29))
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Collecting numpy~=1.24.4 (from -r requirements.txt (line 42))
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Collecting pandas~=2.0.3 (from -r requirements.txt (line 43))
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Collecting streamlit>=1.26.0 (from -r requirements.txt (line 44))
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/df/e2/e1c8e3abce0e819a4ef3c6a5af4ddbb1eadbca0cf2ebd5e58853edcd58bd/streamlit-1.28.1-py2.py3-none-any.whl (8.4 MB)
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Collecting streamlit-option-menu>=0.3.6 (from -r requirements.txt (line 45))
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Collecting streamlit-chatbox==1.1.10 (from -r requirements.txt (line 47))
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/41/d7/6aaee22ec408fc5c3f87023429c63c8b0b97104bceac45e3a726b6c5255b/streamlit_chatbox-1.1.10-py3-none-any.whl (9.6 kB)
Collecting streamlit-aggrid>=0.3.4.post3 (from -r requirements.txt (line 48))
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Collecting cycler>=0.10 (from matplotlib>=2.1.0->pycocotools>=2.0.2->effdet->layoutparser[layoutmodels,tesseract]->unstructured-inference==0.7.10->unstructured[all-docs]>=0.10.12->-r requirements.txt (line 16))
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Collecting kiwisolver>=1.3.1 (from matplotlib>=2.1.0->pycocotools>=2.0.2->effdet->layoutparser[layoutmodels,tesseract]->unstructured-inference==0.7.10->unstructured[all-docs]>=0.10.12->-r requirements.txt (line 16))
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Installing collected packages: wcwidth, sentencepiece, pywin32, pytz, python-magic-bin, python-decouple, pyreadline3, pyclipper, pathlib, nh3, flatbuffers, filetype, faiss-cpu, cymem, antlr4-python3-runtime, zipp, XlsxWriter, xlrd, websockets, watchdog, validators, tzdata, tornado, toolz, tomli, toml, threadpoolctl, tenacity, tabulate, svgwrite, spacy-loggers, spacy-legacy, soupsieve, sniffio, smmap, smart-open, six, simplejson, shortuuid, safetensors, rpds-py, regex, rapidfuzz, PyYAML, python-multipart, python-magic, python-iso639, pypdfium2, pyparsing, pypandoc, PyMuPDFb, pygments, pydantic, pycparser, psutil, protobuf, prompt-toolkit, portalocker, pluggy, pillow, packaging, olefile, numpy, mypy-extensions, murmurhash, multidict, mdurl, markdown2, markdown, lxml, langcodes, kiwisolver, jsonpointer, joblib, iniconfig, humanfriendly, h11, greenlet, frozenlist, fonttools, exceptiongroup, et-xmlfile, emoji, einops, cycler, colorama, cloudpathlib, chardet, catalogue, cachetools, blinker, backoff, attrs, async-timeout, yarl, wavedrom, wasabi, unstructured.pytesseract, tzlocal, typing-inspect, tqdm, tiktoken, srsly, SQLAlchemy, Shapely, scipy, referencing, python-pptx, python-docx, python-dateutil, pytest, pytesseract, PyMuPDF, pydeck, pyarrow, preshed, pdf2image, openpyxl, opencv-python, onnx, omegaconf, numexpr, msg-parser, marshmallow, markdown-it-py, langsmith, langdetect, jsonpatch, importlib-metadata, gitdb, contourpy, coloredlogs, click, cffi, blis, beautifulsoup4, anyio, aiosignal, xformers, uvicorn, typer, starlette, scikit-learn, rich, pandas, onnxruntime, nltk, matplotlib, jsonschema-specifications, iopath, huggingface-hub, httpcore, gitpython, dataclasses-json, cryptography, confection, aiohttp, weasel, unstructured, tokenizers, timm, thinc, rapidocr_onnxruntime, pycocotools, pdfminer.six, openai, langchain, jsonschema, httpx, fastapi, accelerate, transformers, spacy, pdfplumber, langchain-experimental, fschat, effdet, altair, transformers_stream_generator, streamlit, sentence_transformers, peft, layoutparser, streamlit-option-menu, streamlit-chatbox, streamlit-antd-components, streamlit-aggrid, unstructured-inference
  Attempting uninstall: pillow
    Found existing installation: Pillow 10.1.0
    Uninstalling Pillow-10.1.0:
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  Attempting uninstall: numpy
    Found existing installation: numpy 1.26.1
    Uninstalling numpy-1.26.1:
      Successfully uninstalled numpy-1.26.1
Successfully installed PyMuPDF-1.23.5 PyMuPDFb-1.23.5 PyYAML-6.0.1 SQLAlchemy-2.0.19 Shapely-2.0.2 XlsxWriter-3.1.9 accelerate-0.24.1 aiohttp-3.8.6 aiosignal-1.3.1 altair-5.1.2 antlr4-python3-runtime-4.9.3 anyio-3.7.1 async-timeout-4.0.3 attrs-23.1.0 backoff-2.2.1 beautifulsoup4-4.12.2 blinker-1.7.0 blis-0.7.11 cachetools-5.3.2 catalogue-2.0.10 cffi-1.16.0 chardet-5.2.0 click-8.1.7 cloudpathlib-0.16.0 colorama-0.4.6 coloredlogs-15.0.1 confection-0.1.3 contourpy-1.2.0 cryptography-41.0.5 cycler-0.12.1 cymem-2.0.8 dataclasses-json-0.6.1 effdet-0.4.1 einops-0.7.0 emoji-2.8.0 et-xmlfile-1.1.0 exceptiongroup-1.1.3 faiss-cpu-1.7.4 fastapi-0.104.1 filetype-1.2.0 flatbuffers-23.5.26 fonttools-4.44.0 frozenlist-1.4.0 fschat-0.2.31 gitdb-4.0.11 gitpython-3.1.40 greenlet-3.0.1 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 huggingface-hub-0.17.3 humanfriendly-10.0 importlib-metadata-6.8.0 iniconfig-2.0.0 iopath-0.1.10 joblib-1.3.2 jsonpatch-1.33 jsonpointer-2.4 jsonschema-4.19.2 jsonschema-specifications-2023.7.1 kiwisolver-1.4.5 langchain-0.0.330 langchain-experimental-0.0.37 langcodes-3.3.0 langdetect-1.0.9 langsmith-0.0.57 layoutparser-0.3.4 lxml-4.9.3 markdown-3.5.1 markdown-it-py-3.0.0 markdown2-2.4.10 marshmallow-3.20.1 matplotlib-3.8.1 mdurl-0.1.2 msg-parser-1.2.0 multidict-6.0.4 murmurhash-1.0.10 mypy-extensions-1.0.0 nh3-0.2.14 nltk-3.8.1 numexpr-2.8.7 numpy-1.24.4 olefile-0.46 omegaconf-2.3.0 onnx-1.15.0 onnxruntime-1.15.1 openai-0.28.1 opencv-python-4.8.1.78 openpyxl-3.1.2 packaging-23.2 pandas-2.0.3 pathlib-1.0.1 pdf2image-1.16.3 pdfminer.six-20221105 pdfplumber-0.10.3 peft-0.6.0 pillow-9.5.0 pluggy-1.3.0 portalocker-2.8.2 preshed-3.0.9 prompt-toolkit-3.0.39 protobuf-4.25.0 psutil-5.9.6 pyarrow-14.0.0 pyclipper-1.3.0.post5 pycocotools-2.0.7 pycparser-2.21 pydantic-1.10.13 pydeck-0.8.1b0 pygments-2.16.1 pypandoc-1.12 pyparsing-3.1.1 pypdfium2-4.23.1 pyreadline3-3.4.1 pytesseract-0.3.10 pytest-7.4.3 python-dateutil-2.8.2 python-decouple-3.8 python-docx-1.1.0 python-iso639-2023.6.15 python-magic-0.4.27 python-magic-bin-0.4.14 python-multipart-0.0.6 python-pptx-0.6.21 pytz-2023.3.post1 pywin32-306 rapidfuzz-3.5.2 rapidocr_onnxruntime-1.3.8 referencing-0.30.2 regex-2023.10.3 rich-13.6.0 rpds-py-0.12.0 safetensors-0.4.0 scikit-learn-1.3.2 scipy-1.11.3 sentence_transformers-2.2.2 sentencepiece-0.1.99 shortuuid-1.0.11 simplejson-3.19.2 six-1.16.0 smart-open-6.4.0 smmap-5.0.1 sniffio-1.3.0 soupsieve-2.5 spacy-3.7.2 spacy-legacy-3.0.12 spacy-loggers-1.0.5 srsly-2.4.8 starlette-0.27.0 streamlit-1.28.1 streamlit-aggrid-0.3.4.post3 streamlit-antd-components-0.2.3 streamlit-chatbox-1.1.10 streamlit-option-menu-0.3.6 svgwrite-1.4.3 tabulate-0.9.0 tenacity-8.2.3 thinc-8.2.1 threadpoolctl-3.2.0 tiktoken-0.5.1 timm-0.9.10 tokenizers-0.14.1 toml-0.10.2 tomli-2.0.1 toolz-0.12.0 tornado-6.3.3 tqdm-4.66.1 transformers-4.35.0 transformers_stream_generator-0.0.4 typer-0.9.0 typing-inspect-0.9.0 tzdata-2023.3 tzlocal-5.2 unstructured-0.10.28 unstructured-inference-0.7.10 unstructured.pytesseract-0.3.12 uvicorn-0.23.2 validators-0.22.0 wasabi-1.1.2 watchdog-3.0.0 wavedrom-2.0.3.post3 wcwidth-0.2.9 weasel-0.3.3 websockets-12.0 xformers-0.0.22.post7 xlrd-2.0.1 yarl-1.9.2 zipp-3.17.0
 
 
(l2) D:\opt\l2\Langchain-Chatchat>

6、下载模型

下载两个模型：M3e-base内置模型和chatglm2-6b-int4模型。


https://huggingface.co/moka-ai/m3e-base
#备选
https://aistudio.baidu.com/datasetdetail/234251/0


#配置文件
https://huggingface.co/THUDM/chatglm2-6b-int4

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


(l2) D:\opt\l2\Langchain-Chatchat>python copy_config_example.py
 
(l2) D:\opt\l2\Langchain-Chatchat>

执行命令后：

修改model_config.py文件

修改m3e-base的模型本地路径：


MODEL_PATH = {
    "embed_model": {
        "ernie-tiny": "nghuyong/ernie-3.0-nano-zh",
        "ernie-base": "nghuyong/ernie-3.0-base-zh",
        "text2vec-base": "shibing624/text2vec-base-chinese",
        "text2vec": "GanymedeNil/text2vec-large-chinese",
        "text2vec-paraphrase": "shibing624/text2vec-base-chinese-paraphrase",
        "text2vec-sentence": "shibing624/text2vec-base-chinese-sentence",
        "text2vec-multilingual": "shibing624/text2vec-base-multilingual",
        "text2vec-bge-large-chinese": "shibing624/text2vec-bge-large-chinese",
        "m3e-small": "moka-ai/m3e-small",
       # "m3e-base": "moka-ai/m3e-base",
       # 修改为本地的 路径
        "m3e-base": "E:\\llm_models\\m3e-base",
        "m3e-large": "moka-ai/m3e-large",
        "bge-small-zh": "BAAI/bge-small-zh",
        "bge-base-zh": "BAAI/bge-base-zh",
        "bge-large-zh": "BAAI/bge-large-zh",
        "bge-large-zh-noinstruct": "BAAI/bge-large-zh-noinstruct",
        "bge-base-zh-v1.5": "BAAI/bge-base-zh-v1.5",
        "bge-large-zh-v1.5": "BAAI/bge-large-zh-v1.5",
        "piccolo-base-zh": "sensenova/piccolo-base-zh",
        "piccolo-large-zh": "sensenova/piccolo-large-zh",
        "text-embedding-ada-002": "your OPENAI_API_KEY",
    },

修改chatglm2-6b-int4模型本地路径：


"llm_model": {
        # 以下部分模型并未完全测试，仅根据fastchat和vllm模型的模型列表推定支持
        "chatglm-6b": "THUDM/chatglm-6b",
        "chatglm2-6b": "THUDM/chatglm2-6b",
        "chatglm2-6b-int4": "E:\\llm_models\\chatglm2-6b-int4", #"THUDM/chatglm2-6b-int4",
        "chatglm2-6b-32k": "THUDM/chatglm2-6b-32k",

修改LLM模型为chatglm2-6b-int4：


# LLM 名称 ,修改为chatglm2-6b-int4
LLM_MODEL = "chatglm2-6b-int4"

修改LLM_DEVICE运行设备，看使用cpu、cuda（带GPU）或mps( mac本）


# 选用的 Embedding 名称
EMBEDDING_MODEL = "m3e-base" # 可以尝试最新的嵌入式sota模型：bge-large-zh-v1.5
 
 
# Embedding 模型运行设备。设为"auto"会自动检测，也可手动设定为"cuda","mps","cpu"其中之一。
EMBEDDING_DEVICE = "cpu"
 
# LLM 名称
LLM_MODEL = "chatglm2-6b-int4"
 
# LLM 运行设备。设为"auto"会自动检测，也可手动设定为"cuda","mps","cpu"其中之一。
LLM_DEVICE = "cpu"

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"

8、初始化数据库


(l2) D:\opt\l2\Langchain-Chatchat>python init_database.py --recreate-vs
database talbes reseted
recreating all vector stores
2023-11-06 18:21:06,059 - faiss_cache.py[line:75] - INFO: loading vector store in 'samples/vector_store' from disk.
2023-11-06 18:21:06,566 - SentenceTransformer.py[line:66] - INFO: Load pretrained SentenceTransformer: E:\llm_models\m3e-base
Batches: 100%|███████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11.15it/s]
2023-11-06 18:21:11,388 - loader.py[line:54] - INFO: Loading faiss with AVX2 support.
2023-11-06 18:21:11,389 - loader.py[line:58] - INFO: Could not load library with AVX2 support due to:
ModuleNotFoundError("No module named 'faiss.swigfaiss_avx2'")
2023-11-06 18:21:11,397 - loader.py[line:64] - INFO: Loading faiss.
2023-11-06 18:21:11,472 - loader.py[line:66] - INFO: Successfully loaded faiss.
2023-11-06 18:21:11,561 - faiss_cache.py[line:75] - INFO: loading vector store in 'samples/vector_store' from disk.
Batches: 100%|███████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12.99it/s]
2023-11-06 18:21:11,713 - utils.py[line:287] - INFO: UnstructuredFileLoader used for D:\opt\l2\Langchain-Chatchat\knowledge_base\samples\content\test.txt
2023-11-06 18:21:17,676 - utils.py[line:160] - INFO: NumExpr defaulting to 8 threads.
2023-11-06 18:21:21,338 - font_manager.py[line:1578] - INFO: generated new fontManager
文档切分示例：page_content='ChatGPT是OpenAI开发的一个大型语言模型，可以提供各种主题的信息，\n# 如何向 ChatGPT 提问以获得高质量答案：提示技巧工程完全指南\n## 介绍\n我很高兴欢迎您阅读我的最新书籍《The Art of Asking ChatGPT for High-Quality Answers: A complete Guide to Prompt Engineering Techniques》。本书是一本全面指南，介绍了各种提示技术，用于从ChatGPT中生成 高质量的答案。\n我们将探讨如何使用不同的提示工程技术来实现不同的目标。ChatGPT是一款最先进的语言模型，能够生成类似人类的 文本。然而，理解如何正确地向ChatGPT提问以获得我们所需的高质量输出非常重要。而这正是本书的目的。' metadata={'source': 'D:\\opt\\l2\\Langchain-Chatchat\\knowledge_base\\samples\\content\\test.txt'}
正在将 samples/test.txt 添加到向量库，共包含66条文档
Batches: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:48<00:00, 16.10s/it]
2023-11-06 18:22:17,663 - faiss_cache.py[line:20] - INFO: 已将向量库 ('samples', 'vector_store') 保存到磁盘
总计用时： 0:01:11.719423
 
 
(l2) D:\opt\l2\Langchain-Chatchat>

9、一键启动项目

运行：

python startup.py -a


(l2) D:\opt\l2\Langchain-Chatchat>python startup.py -a
 
==============================Langchain-Chatchat Configuration==============================
操作系统：Windows-10-10.0.19044-SP0.
python版本：3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:34:57) [MSC v.1936 64 bit (AMD64)]
项目版本：v0.2.6
langchain版本：0.0.330. fastchat版本：0.2.31
 
 
当前使用的分词器：ChineseRecursiveTextSplitter
当前启动的LLM模型：['chatglm2-6b-int4'] @ cpu
{'device': 'cpu',
 'host': '127.0.0.1',
 'infer_turbo': False,
 'model_path': 'E:\\llm_models\\chatglm2-6b-int4',
 'port': 20002}
当前Embbedings模型： m3e-base @ cpu
==============================Langchain-Chatchat Configuration==============================
 
 
2023-11-06 18:35:19,714 - startup.py[line:626] - INFO: 正在启动服务：
2023-11-06 18:35:19,714 - startup.py[line:627] - INFO: 如需查看 llm_api 日志，请前往 D:\opt\l2\Langchain-Chatchat\logs
2023-11-06 18:35:27 | ERROR | stderr | [32mINFO[0m:     Started server process [[36m16092[0m]
2023-11-06 18:35:27 | ERROR | stderr | [32mINFO[0m:     Waiting for application startup.
2023-11-06 18:35:27 | ERROR | stderr | [32mINFO[0m:     Application startup complete.
2023-11-06 18:35:27 | ERROR | stderr | [32mINFO[0m:     Uvicorn running on [1mhttp://127.0.0.1:20000[0m (Press CTRL+C to quit)
2023-11-06 18:35:35 | INFO | model_worker | Register to controller
2023-11-06 18:35:35 | INFO | model_worker | Loading the model ['chatglm2-6b-int4'] on worker f816f43b ...
2023-11-06 18:35:45 | INFO | model_worker | Register to controller
INFO:     Started server process [18388]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on http://127.0.0.1:7861 (Press CTRL+C to quit)
 
 
==============================Langchain-Chatchat Configuration==============================
操作系统：Windows-10-10.0.19044-SP0.
python版本：3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:34:57) [MSC v.1936 64 bit (AMD64)]
项目版本：v0.2.6
langchain版本：0.0.330. fastchat版本：0.2.31
 
 
当前使用的分词器：ChineseRecursiveTextSplitter
当前启动的LLM模型：['chatglm2-6b-int4'] @ cpu
{'device': 'cpu',
 'host': '127.0.0.1',
 'infer_turbo': False,
 'model_path': 'E:\\llm_models\\chatglm2-6b-int4',
 'port': 20002}
当前Embbedings模型： m3e-base @ cpu
 
 
服务端运行信息：
    OpenAI API Server: http://127.0.0.1:20000/v1
    Chatchat  API  Server: http://127.0.0.1:7861
    Chatchat WEBUI Server: http://127.0.0.1:8501
==============================Langchain-Chatchat Configuration==============================
 
 
 
  You can now view your Streamlit app in your browser.
 
  URL: http://127.0.0.1:8501

10、浏览器访问使用

http://127.0.0.1:8501

11、安装成功

继续研究。

三、FAQ

1、Q：Failed to load cpm_kernels:No module named 'cpm_kernels'


2023-11-06 18:26:44 | INFO | model_worker | Loading the model ['chatglm2-6b-int4'] on worker ac9ad6b5 ...
2023-11-06 18:26:44 | INFO | model_worker | Register to controller
2023-11-06 18:26:49 | WARNING | transformers_modules.chatglm2-6b-int4.quantization | Failed to load cpm_kernels:No module named 'cpm_kernels'

A：pip3 install cpm_kernels -i https://pypi.tuna.tsinghua.edu.cn/simple/


(l2) D:\opt\l2\Langchain-Chatchat>pip3 install cpm_kernels -i https://pypi.tuna.tsinghua.edu.cn/simple/
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple/
Collecting cpm_kernels
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/af/84/1831ce6ffa87b8fd4d9673c3595d0fc4e6631c0691eb43f406d3bf89b951/cpm_kernels-1.0.11-py3-none-any.whl (416 kB)
Installing collected packages: cpm_kernels
Successfully installed cpm_kernels-1.0.11

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