chatGLM+LangChain（部署版）：基于本地知识库的自动问答系统

sockstack / 219 / 2023-11-05 12:13:10

<p><span style="color: red; font-size: 18px">ChatGPT 可用网址，仅供交流学习使用，如对您有所帮助，请收藏并推荐给需要的朋友。</span><br><a href="https://ckai.xyz/?sockstack&section=detail" target="__blank">https://ckai.xyz</a><br><br></p> <div class="notebook-project-preview-content" data-active="true" data-type="notebook"><div class="ai-np"><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><p>项目依赖PaddlePaddle develolop版本和最新的PaddleNLP</p>
</div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h1>0 官方视频</h1>
<h3></h3>
<iframe border="0" src="//player.bilibili.com/player.html?aid=911759112&amp;bvid=BV13M4y1e7cN&amp;cid=1149491440&amp;page=1" style="width:98%;height: 450px;"> </iframe>
<h1>1 可以直接部署，不用安装下面的包</h1>
<h2>1.1gradio文件部署路径</h2>
<p>LangChain-ChatGLM-Webui/paddlepaddle**/untitled.gradio.py**</p>
<p><strong>总共部署需要25分钟以上，以下是第一条日志和最后一条日志。</strong></p>
<p>2023-06-01T09:49:15.375725800Z start deploy...</p>
<p>2023-06-01T10:15:09.812367777Z [33m[2023-06-01 10:15:09,812] [ WARNING][0m - Some weights of ChatGLMForConditionalGeneration were not initialized from the model</p>
<h2>1.2 部署后测试文件</h2>
<p><strong>根目录下文件：知识库.txt</strong></p>
<p><img referrerpolicy="no-referrer"  alt="" src="https://ai-studio-static-online.cdn.bcebos.com/ed519a5ae050417fae8ca0ea83d7e4c416b9820b7fdd46a3b8ad895893a69822"></p>
</div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h1>2 原理介绍</h1>
<p>【官方官方教程】ChatGLM + LangChain 实践培训
B站视频，感兴趣请自行搜索。</p>
<h2>2.1 应用背景及需求特点</h2>
<p><img referrerpolicy="no-referrer"  alt="" src="https://ai-studio-static-online.cdn.bcebos.com/9c6e533d6fdf4432870283e2838238eeaa9cdd4e505e4c75b6b6858bb2282fa2"></p>
</div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h2>2.2 LangChain及ChatGLM简单介绍</h2>
<h3>2.2.1 LangChain简介</h3>
<p>LangChain是一个强大的框架，旨在帮助开发人员使用语言模型构建端到端的应用程序。</p>
<ol>
<li>
<p>它提供了一套工具、组件和接口，可简化创建由大型语言模型(LLM) 和聊天模型提供支持的应用程序的过程。</p>
</li>
<li>
<p>LangChain 可以轻松管理与语言模型的交互，将多个组件链接在一起，并集成额外的资源，例如API 和数据库。</p>
</li>
</ol>
<p><strong>核心概念：</strong></p>
<p>• Components and Chains</p>
<p>• Prompt Templates and Values</p>
<p>• Example Selectors</p>
<p>• Output Parsers</p>
<p>• Indexes and Retrievers</p>
<p>• Chat Message History</p>
<p>• Agents and Toolkits</p>
<h3>2.2.2 ChatGLM-6B简绍</h3>
<ul>
<li>
<p>ChatGLM-6B 是一个开源的、支持中英双语的对话语言模型，基于General LanguageModel (GLM) 架构，具有62 亿参数。</p>
</li>
<li>
<p>结合模型量化技术，用户可以在消费级的显卡上进行本地部署（INT4 量化级别下最低只需6GB 显存）。</p>
</li>
</ul>
<p><img referrerpolicy="no-referrer"  alt="" src="https://ai-studio-static-online.cdn.bcebos.com/c89c2c8e1f33461bb4ebe2d7a886b01c59558fe1fdd04c858fcd2e84eaae3554"></p>
<ul>
<li>ChatGLM-6B 自3月14号发布以来受到了广大开发者和用户的喜爱，截至4月23号GitHub 的star 数达到2 万，累计下载量过100 万，并连续12 天居Hugging Face (HF) 全球大模型下载榜第一名。</li>
</ul>
<p><img referrerpolicy="no-referrer"  alt="" src="https://ai-studio-static-online.cdn.bcebos.com/31abe91c1b654524b9bdfce51121fa562fd1f9bc885848589bf74ad7d7e12f8c"></p>
</div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h2>2.3 Langchain+ChatGLM的原理解析</h2>
<p><img referrerpolicy="no-referrer"  alt="" src="https://ai-studio-static-online.cdn.bcebos.com/bc7c3c7412354f3c8ba4d8c54bcdfffb51b2946afc9f4374afb4e281b0d3e2ef"></p>
</div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h1>3 下面是支持本地安装和调试</h1>
<h2>3.1 安装最新版paddlenlp</h2>
</div></div><div class="ai-np-code"><div class="ai-np-code-in">In [1]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 安装paddlepaddle-gpu develop版本</span>
!python -m pip install paddlepaddle-gpu==<span class="hljs-number">0.0</span><span class="hljs-number">.0</span>.post112 -f https://www.paddlepaddle.org.cn/whl/linux/gpu/develop.html</code></pre><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Looking in links: https://www.paddlepaddle.org.cn/whl/linux/gpu/develop.html
Collecting paddlepaddle-gpu==0.0.0.post112
  Downloading https://paddle-wheel.bj.bcebos.com/develop/linux/linux-gpu-cuda11.2-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-0.0.0.post112-cp39-cp39-linux_x86_64.whl (575.0 MB)
     <span style="color:rgb(85,85,85)">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style="color:rgb(0,187,0)">575.0/575.0 MB</span> <span style="color:rgb(187,0,0)">1.9 MB/s</span> eta <span style="color:rgb(0,187,187)">0:00:00</span>00:0100:01
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Installing collected packages: paddlepaddle-gpu
  Attempting uninstall: paddlepaddle-gpu
    Found existing installation: paddlepaddle-gpu 2.4.1.post112
    Uninstalling paddlepaddle-gpu-2.4.1.post112:
      Successfully uninstalled paddlepaddle-gpu-2.4.1.post112
Successfully installed paddlepaddle-gpu-0.0.0.post112

<span style="font-weight:bold">[</span><span style="color:rgb(0,0,187)">notice</span><span style="font-weight:bold">]</span> A new release of pip available: <span style="color:rgb(187,0,0)">22.1.2</span> -&gt; <span style="color:rgb(0,187,0)">23.1.2</span>
<span style="font-weight:bold">[</span><span style="color:rgb(0,0,187)">notice</span><span style="font-weight:bold">]</span> To update, run: <span style="color:rgb(0,187,0)">pip install --upgrade pip</span>
</pre></div></div></div><div class="ai-np-code"><div class="ai-np-code-in">In [2]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 用镜像直接安装</span>
%cd /home/aistudio/LangChain-ChatGLM-Webui/paddlepaddle
!pip install ./paddlenlp<span class="hljs-number">-2.5</span><span class="hljs-number">.2</span>.post0-py3-none-<span class="hljs-built_in">any</span>.whl --user</code></pre><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">/home/aistudio/LangChain-ChatGLM-Webui/paddlepaddle
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Processing ./paddlenlp-2.5.2.post0-py3-none-any.whl
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paddlenlp is already installed with the same version as the provided wheel. Use --force-reinstall to force an installation of the wheel.

[2023-06-17 08:32:02,298] [    INFO] - Downloading model_state.pdparams from https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/model_state.pdparams
</pre></div><div class="ai-np-output-wrapper"><div class="ai-np-execute-result"><div><pre class="ai-np-pre">  0%|          | 0.00/12.5G [00:00&lt;?, ?B/s]</pre></div></div></div><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">W0617 08:34:25.528139   755 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.2, Runtime API Version: 11.2
W0617 08:34:25.532923   755 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
[2023-06-17 08:34:40,902] [ WARNING] - Some weights of the model checkpoint at THUDM/chatglm-6b-v1.1 were not used when initializing ChatGLMForConditionalGeneration: ['transformer.layers.1.attention.rotary_emb.inv_freq', 'transformer.layers.12.attention.rotary_emb.inv_freq', 'transformer.layers.22.attention.rotary_emb.inv_freq', 'transformer.layers.23.attention.rotary_emb.inv_freq', 'transformer.layers.16.attention.rotary_emb.inv_freq', 'transformer.layers.26.attention.rotary_emb.inv_freq', 'transformer.layers.27.attention.rotary_emb.inv_freq', 'transformer.layers.18.attention.rotary_emb.inv_freq', 'transformer.layers.13.attention.rotary_emb.inv_freq', 'transformer.layers.7.attention.rotary_emb.inv_freq', 'transformer.layers.15.attention.rotary_emb.inv_freq', 'transformer.layers.4.attention.rotary_emb.inv_freq', 'transformer.layers.5.attention.rotary_emb.inv_freq', 'transformer.layers.19.attention.rotary_emb.inv_freq', 'transformer.layers.0.attention.rotary_emb.inv_freq', 'transformer.
- This IS expected if you are initializing ChatGLMForConditionalGeneration from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing ChatGLMForConditionalGeneration from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
[2023-06-17 08:34:40,906] [ WARNING] - Some weights of ChatGLMForConditionalGeneration were not initialized from the model checkpoint at THUDM/chatglm-6b-v1.1 and are newly initialized: ['transformer.layers.22.attention.rotary_embeddings.inv_freq', 'transformer.layers.21.attention.rotary_embeddings.inv_freq', 'transformer.layers.15.attention.rotary_embeddings.inv_freq', 'transformer.layers.16.attention.rotary_embeddings.inv_freq', 'transformer.layers.17.attention.rotary_embeddings.inv_freq', 'transformer.layers.5.attention.rotary_embeddings.inv_freq', 'transformer.layers.8.attention.rotary_embeddings.inv_freq', 'transformer.layers.18.attention.rotary_embeddings.inv_freq', 'transformer.layers.12.attention.rotary_embeddings.inv_freq', 'transformer.layers.10.attention.rotary_embeddings.inv_freq', 'transformer.layers.20.attention.rotary_embeddings.inv_freq', 'transformer.layers.25.attention.rotary_embeddings.inv_freq', 'transformer.layers.1.attention.rotary_embeddings.inv_freq', 'transform
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
</pre></div><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">{'result': ['您好!有什么需要帮助的吗?', '你好!我也很高兴认识你。作为一名人工智能助手,我很高兴能够与你交流和回答你的问题。请问有什么我可以为你效劳的吗?']}
</pre></div></div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h2>3.3 安装与LangChian相关的包</h2>
</div></div><div class="ai-np-code"><div class="ai-np-code-in">In [2]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 安装依赖（时间较长）</span>
%cd /home/aistudio/LangChain-ChatGLM-Webui/paddlepaddle
!pip install -r requirements.txt </code></pre><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">/home/aistudio/LangChain-ChatGLM-Webui/paddlepaddle
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Collecting typing-inspect&gt;=0.4.0
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Collecting marshmallow-enum&lt;2.0.0,&gt;=1.5.1
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Collecting deprecated~=1.2.0
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Collecting pandas
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Collecting wrapt&lt;1.15,&gt;=1.13
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Collecting monotonic
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Collecting pydantic&lt;2,&gt;=1
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Collecting backoff
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Requirement already satisfied: pytz&gt;=2020.1 in /opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages (from pandas-&gt;unstructured[local-inference]-&gt;-r requirements.txt (line 2)) (2022.7.1)
Collecting pycocotools&gt;=2.0.2
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Collecting omegaconf&gt;=2.0
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Collecting timm&gt;=0.9.2
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Collecting nvidia-cuda-cupti-cu11==11.7.101
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Collecting nvidia-cusparse-cu11==11.7.4.91
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Collecting nvidia-cuda-runtime-cu11==11.7.99
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Collecting nvidia-cublas-cu11==11.10.3.66
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Collecting nvidia-cufft-cu11==10.9.0.58
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Collecting nvidia-nvtx-cu11==11.7.91
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Collecting nvidia-nccl-cu11==2.14.3
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Collecting triton==2.0.0
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Collecting nvidia-cuda-nvrtc-cu11==11.7.99
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Collecting nvidia-curand-cu11==10.2.10.91
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Requirement already satisfied: wheel in /opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages (from nvidia-cublas-cu11==11.10.3.66-&gt;torch-&gt;layoutparser[layoutmodels,tesseract]-&gt;-r requirements.txt (line 3)) (0.36.2)
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Collecting lit
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Collecting cmake
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Collecting portalocker
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Collecting antlr4-python3-runtime==4.9.*
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Collecting safetensors
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Collecting tokenizers!=0.11.3,&lt;0.14,&gt;=0.11.1
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Collecting huggingface-hub
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Collecting regex!=2019.12.17
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Collecting flatbuffers
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Requirement already satisfied: anyio&lt;5.0,&gt;=3.0 in /opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages (from httpcore&lt;0.17.0,&gt;=0.15.0-&gt;httpx&lt;0.24,&gt;=0.15-&gt;argilla-&gt;unstructured[local-inference]-&gt;-r requirements.txt (line 2)) (3.6.1)
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Collecting humanfriendly&gt;=9.1
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Building wheels for collected packages: iopath, python-pptx, olefile, antlr4-python3-runtime, pycocotools, lit
  Building wheel for iopath (setup.py) ... done
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  Created wheel for lit: filename=lit-16.0.6-py3-none-any.whl size=93582 sha256=3a507c41cd2f1fc5bdcc2e4385f6aead4101a8a7f649ccacfb8685f894933625
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Successfully built iopath python-pptx olefile antlr4-python3-runtime pycocotools lit
Installing collected packages: tokenizers, safetensors, monotonic, lit, flatbuffers, filetype, cpm_kernels, cmake, antlr4-python3-runtime, XlsxWriter, wrapt, tenacity, regex, PyYAML, python-magic, pypandoc, pydantic, protobuf, portalocker, olefile, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, numexpr, mypy-extensions, humanfriendly, backoff, typing-inspect, python-pptx, pytesseract, pandas, openapi-schema-pydantic, omegaconf, nvidia-cusolver-cu11, nvidia-cudnn-cu11, msg-parser, iopath, huggingface-hub, deprecated, coloredlogs, transformers, pycocotools, onnxruntime, marshmallow-enum, dataclasses-json, argilla, unstructured, layoutparser, langchain, triton, torch, torchvision, timm, effdet, unstructured-inference, icetk
  Attempting uninstall: wrapt
    Found existing installation: wrapt 1.12.1
    Uninstalling wrapt-1.12.1:
      Successfully uninstalled wrapt-1.12.1
  Attempting uninstall: tenacity
    Found existing installation: tenacity 8.0.1
    Uninstalling tenacity-8.0.1:
      Successfully uninstalled tenacity-8.0.1
  Attempting uninstall: PyYAML
    Found existing installation: PyYAML 5.1.2
    Uninstalling PyYAML-5.1.2:
      Successfully uninstalled PyYAML-5.1.2
  Attempting uninstall: pydantic
    Found existing installation: pydantic 1.10.4
    Uninstalling pydantic-1.10.4:
      Successfully uninstalled pydantic-1.10.4
  Attempting uninstall: protobuf
    Found existing installation: protobuf 3.20.2
    Uninstalling protobuf-3.20.2:
      Successfully uninstalled protobuf-3.20.2
  Attempting uninstall: pandas
    Found existing installation: pandas 2.0.1
    Uninstalling pandas-2.0.1:
      Successfully uninstalled pandas-2.0.1
  Attempting uninstall: huggingface-hub
    Found existing installation: huggingface-hub 0.12.0
    Uninstalling huggingface-hub-0.12.0:
      Successfully uninstalled huggingface-hub-0.12.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
pymilvus 2.2.8 requires protobuf&gt;=3.20.0, but you have protobuf 3.18.3 which is incompatible.
paddlenlp 2.5.2.post0 requires protobuf==3.20.2, but you have protobuf 3.18.3 which is incompatible.
sahi 0.10.1 requires click==8.0.4, but you have click 8.0.0 which is incompatible.
parl 1.4.1 requires pyzmq==18.1.1, but you have pyzmq 23.2.1 which is incompatible.
paddlepaddle-gpu 0.0.0.post112 requires protobuf&gt;=3.20.2; platform_system != "Windows", but you have protobuf 3.18.3 which is incompatible.
Successfully installed PyYAML-6.0 XlsxWriter-3.1.2 antlr4-python3-runtime-4.9.3 argilla-1.10.0 backoff-2.2.1 cmake-3.26.4 coloredlogs-15.0.1 cpm_kernels-1.0.11 dataclasses-json-0.5.8 deprecated-1.2.14 effdet-0.4.1 filetype-1.2.0 flatbuffers-23.5.26 huggingface-hub-0.15.1 humanfriendly-10.0 icetk-0.0.7 iopath-0.1.10 langchain-0.0.147 layoutparser-0.3.4 lit-16.0.6 marshmallow-enum-1.5.1 monotonic-1.6 msg-parser-1.2.0 mypy-extensions-1.0.0 numexpr-2.8.4 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 olefile-0.46 omegaconf-2.3.0 onnxruntime-1.15.1 openapi-schema-pydantic-1.2.4 pandas-1.5.3 portalocker-2.7.0 protobuf-3.20.0 pycocotools-2.0.6 pydantic-1.10.9 pypandoc-1.11 pytesseract-0.3.10 python-magic-0.4.27 python-pptx-

[notice] A new release of pip available: 22.1.2 -&gt; 23.1.2
[notice] To update, run: pip install --upgrade pip
</pre></div></div></div><div class="ai-np-code"><div class="ai-np-code-in">In [1]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 运行LangChain版本的本地知识库进行文本匹配自动问答</span>
<span class="hljs-comment"># !git clone https://openi.pcl.ac.cn/Learning-Develop-Union/LangChain-ChatGLM-Webui.git</span></code></pre></div></div><div class="ai-np-code"><div class="ai-np-code-in">In [7]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 安装numpy，否则会报错</span>
!pip uninstall numpy -y --user
!pip install numpy --user</code></pre><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">
Usage:   
  pip uninstall [options] &lt;package&gt; ...
  pip uninstall [options] -r &lt;requirements file&gt; ...

no such option: --user
WARNING: Ignoring invalid distribution -umpy (/opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -umpy (/opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages)
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Requirement already satisfied: numpy in /opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages (1.23.5)
WARNING: Ignoring invalid distribution -umpy (/opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -umpy (/opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -umpy (/opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -umpy (/opt/conda/envs/python35-paddle120-env/lib/python3.9/site-packages)

[notice] A new release of pip available: 22.1.2 -&gt; 23.1.2
[notice] To update, run: pip install --upgrade pip
</pre></div></div></div><div class="ai-np-markdown"><div class="ai-np-markdown-cell-content"><h2>3.4 测试LangChain程序</h2>
</div></div><div class="ai-np-code"><div class="ai-np-code-in">In [1]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 这块视频没运行</span>
<span class="hljs-comment"># 运行非LangChain版本的本地知识库自动问答</span>
%cd /home/aistudio
!python chat_documents.py</code></pre><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">/home/aistudio
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:25,671] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/ice_text.model
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:25,671] [    INFO]</span> - Downloading https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/added_tokens.json and saved to /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1
<span style="color:rgb(187,187,0)">[2023-06-17 09:27:25,711] [ WARNING]</span> - file&lt;https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/added_tokens.json&gt; not exist
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:25,711] [    INFO]</span> - Downloading https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/special_tokens_map.json and saved to /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1
<span style="color:rgb(187,187,0)">[2023-06-17 09:27:25,747] [ WARNING]</span> - file&lt;https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/special_tokens_map.json&gt; not exist
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:25,747] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/tokenizer_config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:26,101] [    INFO]</span> - Found /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:26,102] [    INFO]</span> - loading configuration file /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:26,103] [    INFO]</span> - Model config ChatGLMConfig {
  "_name_or_path": "THUDM/chatglm-6b",
  "activation": "gelu",
  "architectures": [
    "ChatGLMModel"
  ],
  "attention_scale": true,
  "auto_map": {
    "AutoConfig": "configuration_chatglm.ChatGLMConfig",
    "AutoModel": "modeling_chatglm.ChatGLMForConditionalGeneration",
    "AutoModelForSeq2SeqLM": "modeling_chatglm.ChatGLMForConditionalGeneration"
  },
  "bos_token_id": 130004,
  "dtype": "float16",
  "eos_token_id": 130005,
  "gmask_token_id": 130001,
  "hidden_size": 4096,
  "inner_hidden_size": 16384,
  "layernorm_epsilon": 1e-05,
  "mask_token_id": 130000,
  "max_sequence_length": 2048,
  "model_type": "chatglm",
  "num_attention_heads": 32,
  "num_hidden_layers": 28,
  "num_image_tokens": 0,
  "output_predict": true,
  "pad_token_id": 3,
  "paddlenlp_version": null,
  "position_encoding_2d": true,
  "pre_seq_len": null,
  "prefix_projection": false,
  "quantization_bit": 0,
  "recompute": false,
  "transformers_version": "4.23.1",
  "use_cache": true,
  "vocab_size": 130528
}

<span style="color:rgb(0,187,0)">[2023-06-17 09:27:26,144] [    INFO]</span> - Found /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/model_state.pdparams
W0617 09:27:35.560508  6170 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.2, Runtime API Version: 11.2
W0617 09:27:35.565218  6170 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
<span style="color:rgb(187,187,0)">[2023-06-17 09:27:50,454] [ WARNING]</span> - Some weights of the model checkpoint at THUDM/chatglm-6b-v1.1 were not used when initializing ChatGLMForConditionalGeneration: ['transformer.layers.1.attention.rotary_emb.inv_freq', 'transformer.layers.22.attention.rotary_emb.inv_freq', 'transformer.layers.16.attention.rotary_emb.inv_freq', 'transformer.layers.23.attention.rotary_emb.inv_freq', 'transformer.layers.5.attention.rotary_emb.inv_freq', 'transformer.layers.15.attention.rotary_emb.inv_freq', 'transformer.layers.26.attention.rotary_emb.inv_freq', 'transformer.layers.11.attention.rotary_emb.inv_freq', 'transformer.layers.24.attention.rotary_emb.inv_freq', 'transformer.layers.2.attention.rotary_emb.inv_freq', 'transformer.layers.14.attention.rotary_emb.inv_freq', 'transformer.layers.12.attention.rotary_emb.inv_freq', 'transformer.layers.21.attention.rotary_emb.inv_freq', 'transformer.layers.0.attention.rotary_emb.inv_freq', 'transformer.layers.6.attention.rotary_emb.inv_freq', 'tra
- This IS expected if you are initializing ChatGLMForConditionalGeneration from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing ChatGLMForConditionalGeneration from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
<span style="color:rgb(187,187,0)">[2023-06-17 09:27:50,454] [ WARNING]</span> - Some weights of ChatGLMForConditionalGeneration were not initialized from the model checkpoint at THUDM/chatglm-6b-v1.1 and are newly initialized: ['transformer.layers.3.attention.rotary_embeddings.inv_freq', 'transformer.layers.25.attention.rotary_embeddings.inv_freq', 'transformer.layers.27.attention.rotary_embeddings.inv_freq', 'transformer.layers.8.attention.rotary_embeddings.inv_freq', 'transformer.layers.15.attention.rotary_embeddings.inv_freq', 'transformer.layers.12.attention.rotary_embeddings.inv_freq', 'transformer.layers.13.attention.rotary_embeddings.inv_freq', 'transformer.layers.14.attention.rotary_embeddings.inv_freq', 'transformer.layers.7.attention.rotary_embeddings.inv_freq', 'transformer.layers.24.attention.rotary_embeddings.inv_freq', 'transformer.layers.22.attention.rotary_embeddings.inv_freq', 'transformer.layers.9.attention.rotary_embeddings.inv_freq', 'transformer.layers.16.attention.rotary_embeddings.inv_freq', 't
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
INFO - pipelines.utils.common_utils -  Using devices: PLACE(GPU:0)
INFO - pipelines.utils.common_utils -  Number of GPUs: 1
Loading Parameters from:rocketqa-zh-dureader-cross-encoder
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,209] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-cross-encoder/rocketqa-zh-dureader-vocab.txt
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,219] [    INFO]</span> - tokenizer config file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-cross-encoder/tokenizer_config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,219] [    INFO]</span> - Special tokens file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-cross-encoder/special_tokens_map.json
INFO - pipelines.document_stores.faiss -  document_cnt:0	embedding_cnt:0
INFO - pipelines.utils.common_utils -  Using devices: PLACE(GPU:0)
INFO - pipelines.utils.common_utils -  Number of GPUs: 1
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,297] [    INFO]</span> - We are using (&lt;class 'paddlenlp.transformers.ernie.tokenizer.ErnieTokenizer'&gt;, False) to load 'rocketqa-zh-base-query-encoder'.
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,298] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/rocketqa-zh-base-query-encoder/ernie_3.0_base_zh_vocab.txt
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,318] [    INFO]</span> - tokenizer config file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-base-query-encoder/tokenizer_config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:53,318] [    INFO]</span> - Special tokens file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-base-query-encoder/special_tokens_map.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:55,167] [    INFO]</span> - We are using (&lt;class 'paddlenlp.transformers.ernie.tokenizer.ErnieTokenizer'&gt;, False) to load 'rocketqa-zh-base-query-encoder'.
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:55,167] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/rocketqa-zh-base-query-encoder/ernie_3.0_base_zh_vocab.txt
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:55,187] [    INFO]</span> - tokenizer config file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-base-query-encoder/tokenizer_config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:27:55,187] [    INFO]</span> - Special tokens file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-base-query-encoder/special_tokens_map.json
Writing Documents: 1000it [00:00, 96787.91it/s]                                 
[2023/06/17 09:27:57] ppocr DEBUG: Namespace(help='==SUPPRESS==', use_gpu=True, use_xpu=False, use_npu=False, ir_optim=True, use_tensorrt=False, min_subgraph_size=15, precision='fp32', gpu_mem=500, image_dir=None, page_num=0, det_algorithm='DB', det_model_dir='/home/aistudio/.paddleocr/whl/det/ch/ch_PP-OCRv3_det_infer', det_limit_side_len=960, det_limit_type='max', det_box_type='quad', det_db_thresh=0.3, det_db_box_thresh=0.6, det_db_unclip_ratio=1.5, max_batch_size=10, use_dilation=False, det_db_score_mode='fast', det_east_score_thresh=0.8, det_east_cover_thresh=0.1, det_east_nms_thresh=0.2, det_sast_score_thresh=0.5, det_sast_nms_thresh=0.2, det_pse_thresh=0, det_pse_box_thresh=0.85, det_pse_min_area=16, det_pse_scale=1, scales=[8, 16, 32], alpha=1.0, beta=1.0, fourier_degree=5, rec_algorithm='SVTR_LCNet', rec_model_dir='/home/aistudio/.paddleocr/whl/rec/ch/ch_PP-OCRv3_rec_infer', rec_image_inverse=True, rec_image_shape='3, 48, 320', rec_batch_num=6, max_text_length=25, rec_char_dict
INFO - pipelines.nodes.llm.chatglm -  基于以下已知信息，请简洁并专业地回答用户的问题。
                如果无法从中得到答案，请说 "根据已知信息无法回答该问题" 或 "没有提供足够的相关信息"。不允许在答案中添加编造成分。另外，答案请使用中文。

已知内容：ChatGLM-6B   🌐 Blog • 🤗 HF Repo • 🐦 Twitter • 📃 [GLM@ACL 22] [GitHub] • 📃 [GLM-130B@ICLR 23] [GitHub]     👋 加入我们的 Slack 和 WeChat介绍ChatGLM-6B 是一个开源的、支持中英双语的对话语言模型，基于 General Language Model (GLM) 架构，具有 62 亿参数。结合模型量化技术，用户可以在消费级的显卡上进行本地部署（INT4 量化级别下最低只需 6GB 显存）。ChatGLM-6B 使用了和 ChatGPT 相似的技术，针对中文问答和对话进行了优化。经过约 1T 标识符的中英双语训练，辅以监督微调、反馈自助、人类反馈强化学习等技术的加持，62 亿参数的 ChatGLM-6B 已经能生成相当符合人类偏好的回答，更多信息请参考我们的博客。为了方便下游开发者针对自己的应用场景定制模型，我们同时实现了基于 P-Tuning v2 的高效参数微调方法 (使用指南) ，INT4 量化级别下最低只需 7GB 显存即可启动微调。不过，由于 ChatGLM-6B 的规模较小，目前已知其具有相当多的局限性，如事实性/数学逻辑错误，可能生成有害/有偏见内容，较弱的上下文能力，自我认知混乱，以及对英文指示生成与中文指示完全矛盾的内容。请大家在使用前了解这些问题，以免产生误解。更大的基于 1300 亿参数 GLM-130B 的 ChatGLM 正在内测开发中。Read this in English.友情链接对 ChatGLM 进行加速的开源项目：* ChatGLM-MNN: 一个基于 MNN 的 ChatGLM-6B C++ 推理实现，支持根据显存大小自动分配计算任务给 GPU 和 CPU* JittorLLMs：最低3G显存或者没有显卡都可运行 ChatGLM-6B FP16， 支持Linux、windows、Mac部署基于或使用了 ChatGLM-6B 的开源项目：* langchain-ChatGLM：基于 langchain 的 ChatGLM 应用，实现基于可扩展知识库的问答* 闻达：大型语言模型调用平台，基于 ChatGLM-6B 实现了类 ChatPDF 功能* chatg
                
                问题：什么是ChatGLM-6B？他的局限性在哪里？如何改进？
user: 什么是ChatGLM-6B？他的局限性在哪里？如何改进？
assistant: ['根据已知信息,可以简洁和专业地回答用户的问题。ChatGLM-6B 是一个开源的、支持中英双语的对话语言模型,基于 General Language Model (GLM) 架构,具有 62 亿参数。结合模型量化技术,用户可以在消费级的显卡上进行本地部署(INT4 量化级别下最低只需 6GB 显存)。ChatGLM-6B 使用了和 ChatGPT 相似的技术,针对中文问答和对话进行了优化。经过约 1T 标识符的中英双语训练,辅以监督微调、反馈自助、人类反馈强化学习等技术的加持,62 亿参数的 ChatGLM-6B 已经能生成相当符合人类偏好的回答。但由于其规模较小,目前已知其具有相当多的局限性,如事实性/数学逻辑错误,可能生成有害/有偏见内容,较弱的上下文能力,自我认知混乱,以及对英文指示生成与中文指示完全矛盾的内容。因此,在使用前了解这些问题,以免产生误解。更大的基于 1300 亿参数 GLM-130B 的 ChatGLM 正在内测开发中。']
[('什么是ChatGLM-6B？他的局限性在哪里？如何改进？', '根据已知信息,可以简洁和专业地回答用户的问题。ChatGLM-6B 是一个开源的、支持中英双语的对话语言模型,基于 General Language Model (GLM) 架构,具有 62 亿参数。结合模型量化技术,用户可以在消费级的显卡上进行本地部署(INT4 量化级别下最低只需 6GB 显存)。ChatGLM-6B 使用了和 ChatGPT 相似的技术,针对中文问答和对话进行了优化。经过约 1T 标识符的中英双语训练,辅以监督微调、反馈自助、人类反馈强化学习等技术的加持,62 亿参数的 ChatGLM-6B 已经能生成相当符合人类偏好的回答。但由于其规模较小,目前已知其具有相当多的局限性,如事实性/数学逻辑错误,可能生成有害/有偏见内容,较弱的上下文能力,自我认知混乱,以及对英文指示生成与中文指示完全矛盾的内容。因此,在使用前了解这些问题,以免产生误解。更大的基于 1300 亿参数 GLM-130B 的 ChatGLM 正在内测开发中。')]
</pre></div></div></div><div class="ai-np-code"><div class="ai-np-code-in">In [ ]</div><div class="ai-np-code-main"><pre><code class="hljs"><span class="hljs-comment"># 执行命令行脚本</span>

%cd /home/aistudio/LangChain-ChatGLM-Webui/paddlepaddle
!python cli.py</code></pre><div class="ai-np-output-wrapper"><pre class="ai-np-output-stream">/home/aistudio/LangChain-ChatGLM-Webui/paddlepaddle
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:43,806] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/ice_text.model
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:43,807] [    INFO]</span> - Downloading https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/added_tokens.json and saved to /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1
<span style="color:rgb(187,187,0)">[2023-06-17 09:33:44,022] [ WARNING]</span> - file&lt;https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/added_tokens.json&gt; not exist
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:44,023] [    INFO]</span> - Downloading https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/special_tokens_map.json and saved to /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1
<span style="color:rgb(187,187,0)">[2023-06-17 09:33:44,062] [ WARNING]</span> - file&lt;https://bj.bcebos.com/paddlenlp/models/community/THUDM/chatglm-6b-v1.1/special_tokens_map.json&gt; not exist
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:44,063] [    INFO]</span> - Already cached /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/tokenizer_config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:44,371] [    INFO]</span> - Found /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:44,372] [    INFO]</span> - loading configuration file /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:33:44,373] [    INFO]</span> - Model config ChatGLMConfig {
  "_name_or_path": "THUDM/chatglm-6b",
  "activation": "gelu",
  "architectures": [
    "ChatGLMModel"
  ],
  "attention_scale": true,
  "auto_map": {
    "AutoConfig": "configuration_chatglm.ChatGLMConfig",
    "AutoModel": "modeling_chatglm.ChatGLMForConditionalGeneration",
    "AutoModelForSeq2SeqLM": "modeling_chatglm.ChatGLMForConditionalGeneration"
  },
  "bos_token_id": 130004,
  "dtype": "float16",
  "eos_token_id": 130005,
  "gmask_token_id": 130001,
  "hidden_size": 4096,
  "inner_hidden_size": 16384,
  "layernorm_epsilon": 1e-05,
  "mask_token_id": 130000,
  "max_sequence_length": 2048,
  "model_type": "chatglm",
  "num_attention_heads": 32,
  "num_hidden_layers": 28,
  "num_image_tokens": 0,
  "output_predict": true,
  "pad_token_id": 3,
  "paddlenlp_version": null,
  "position_encoding_2d": true,
  "pre_seq_len": null,
  "prefix_projection": false,
  "quantization_bit": 0,
  "recompute": false,
  "transformers_version": "4.23.1",
  "use_cache": true,
  "vocab_size": 130528
}

<span style="color:rgb(0,187,0)">[2023-06-17 09:33:44,415] [    INFO]</span> - Found /home/aistudio/.paddlenlp/models/THUDM/chatglm-6b-v1.1/model_state.pdparams
W0617 09:33:52.847257  6771 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.2, Runtime API Version: 11.2
W0617 09:33:52.851541  6771 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
<span style="color:rgb(187,187,0)">[2023-06-17 09:34:08,135] [ WARNING]</span> - Some weights of the model checkpoint at THUDM/chatglm-6b-v1.1 were not used when initializing ChatGLMForConditionalGeneration: ['transformer.layers.2.attention.rotary_emb.inv_freq', 'transformer.layers.15.attention.rotary_emb.inv_freq', 'transformer.layers.4.attention.rotary_emb.inv_freq', 'transformer.layers.3.attention.rotary_emb.inv_freq', 'transformer.layers.8.attention.rotary_emb.inv_freq', 'transformer.layers.24.attention.rotary_emb.inv_freq', 'transformer.layers.18.attention.rotary_emb.inv_freq', 'transformer.layers.1.attention.rotary_emb.inv_freq', 'transformer.layers.25.attention.rotary_emb.inv_freq', 'transformer.layers.27.attention.rotary_emb.inv_freq', 'transformer.layers.26.attention.rotary_emb.inv_freq', 'transformer.layers.22.attention.rotary_emb.inv_freq', 'transformer.layers.19.attention.rotary_emb.inv_freq', 'transformer.layers.16.attention.rotary_emb.inv_freq', 'transformer.layers.0.attention.rotary_emb.inv_freq', 'tran
- This IS expected if you are initializing ChatGLMForConditionalGeneration from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing ChatGLMForConditionalGeneration from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
<span style="color:rgb(187,187,0)">[2023-06-17 09:34:08,136] [ WARNING]</span> - Some weights of ChatGLMForConditionalGeneration were not initialized from the model checkpoint at THUDM/chatglm-6b-v1.1 and are newly initialized: ['transformer.layers.8.attention.rotary_embeddings.inv_freq', 'transformer.layers.21.attention.rotary_embeddings.inv_freq', 'transformer.layers.12.attention.rotary_embeddings.inv_freq', 'transformer.layers.2.attention.rotary_embeddings.inv_freq', 'transformer.layers.18.attention.rotary_embeddings.inv_freq', 'transformer.layers.15.attention.rotary_embeddings.inv_freq', 'transformer.layers.3.attention.rotary_embeddings.inv_freq', 'transformer.layers.16.attention.rotary_embeddings.inv_freq', 'transformer.layers.7.attention.rotary_embeddings.inv_freq', 'transformer.layers.20.attention.rotary_embeddings.inv_freq', 'transformer.layers.24.attention.rotary_embeddings.inv_freq', 'transformer.layers.26.attention.rotary_embeddings.inv_freq', 'transformer.layers.22.attention.rotary_embeddings.inv_freq', 't
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,193] [    INFO]</span> - We are using (&lt;class 'paddlenlp.transformers.ernie.tokenizer.ErnieTokenizer'&gt;, False) to load 'rocketqa-zh-dureader-query-encoder'.
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,193] [    INFO]</span> - Downloading https://bj.bcebos.com/paddlenlp/models/transformers/rocketqa/rocketqa-zh-dureader-vocab.txt and saved to /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-query-encoder
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,244] [    INFO]</span> - Downloading rocketqa-zh-dureader-vocab.txt from https://bj.bcebos.com/paddlenlp/models/transformers/rocketqa/rocketqa-zh-dureader-vocab.txt
100%|██████████████████████████████████████| 89.0k/89.0k [00:00&lt;00:00, 31.8MB/s]
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,398] [    INFO]</span> - tokenizer config file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-query-encoder/tokenizer_config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,398] [    INFO]</span> - Special tokens file saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-query-encoder/special_tokens_map.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,400] [    INFO]</span> - Model config ErnieConfig {
  "attention_probs_dropout_prob": 0.1,
  "enable_recompute": false,
  "fuse": false,
  "hidden_act": "relu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 513,
  "model_type": "ernie",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "paddlenlp_version": null,
  "pool_act": "tanh",
  "task_id": 0,
  "task_type_vocab_size": 3,
  "type_vocab_size": 2,
  "use_task_id": false,
  "vocab_size": 18000
}

<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,400] [    INFO]</span> - Configuration saved in /home/aistudio/.paddlenlp/models/rocketqa-zh-dureader-query-encoder/config.json
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:08,401] [    INFO]</span> - Downloading rocketqa_zh_dureader_query_encoder.pdparams from https://bj.bcebos.com/paddlenlp/models/transformers/rocketqa/rocketqa_zh_dureader_query_encoder.pdparams
100%|█████████████████████████████████████████| 379M/379M [00:03&lt;00:00, 100MB/s]
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:13,465] [    INFO]</span> - All model checkpoint weights were used when initializing ErnieEncoder.

<span style="color:rgb(187,187,0)">[2023-06-17 09:34:13,465] [ WARNING]</span> - Some weights of ErnieEncoder were not initialized from the model checkpoint at rocketqa-zh-dureader-query-encoder and are newly initialized: ['classifier.weight', 'classifier.bias', 'ernie.pooler.dense.bias', 'ernie.pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:13,466] [    INFO]</span> - Converting to the inference model cost a little time.
I0617 09:34:16.770787  6771 interpretercore.cc:294] New Executor is Running.
<span style="color:rgb(0,187,0)">[2023-06-17 09:34:18,386] [    INFO]</span> - The inference model save in the path:/home/aistudio/.paddlenlp/taskflow/rocketqa-zh-dureader-query-encoder/static/inference
提问:</pre></div></div></div><div class="ai-np-code"><div class="ai-np-code-in">In [ ]</div><div class="ai-np-code-main"><pre><code class="hljs"></code></pre></div></div></div></div>

chatGLM+LangChain（部署版）：基于本地知识库的自动问答系统

作者

sockstack

许可协议

CC BY 4.0

发布于

2023-11-05

修改于

2024-12-23

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chatGLM+LangChain（部署版）：基于本地知识库的自动问答系统

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