Readme in English

Knowledge Base Generation and Question Answering System based on LLM

Create a virtual environment

Python 3.11 requires CUDA version 12 or above

Install all dependencies

$ cd 2024lmcbise $ pip install -r requirements.txt

Download models

Required models include:

chatGLM2-6b text2vec You can download common open-source LLM and embedding models from the HuggingFace mirror website hf-mirror.com. To download models, you need to install Git LFS first, and then run the following commands:

$ git lfs install $ git clone https://hf-mirror.com/THUDM/chatglm2-6b $ git clone https://hf-mirror.com/GanymedeNil/text2vec-large-chinese

Modify configuration files

Add the absolute path of the model in model_config.py.

Run the program

cd 2024lmcbise

Execute the cli_demo.py script to experience command-line interaction:

$ python cli_demo.py

Or execute the webui.py script to experience Web interaction:

$ python webui.py

Or deploy an API using fastapi:

$ python api.py

Experience the VUE-based front-end page after successfully deploying the API:

$ cd views $ pnpm i $ npm run dev

Project Reference: https://github.com/chatchat-space/Langchain-Chatchat

Readme in Chinese

Knowledge base generation and question answering system based on LLM

创建虚拟环境

python 3.11 cuda版本需要12及以上

安装全部依赖

$ cd 2024lmcbise $ pip install -r requirements.txt

模型下载

需要用到的模型有 chatGLM2-6b text2vec #可以去通常开源 LLM 与 Embedding 模型可以从 HuggingFace 的镜像网站hf-mirror.com下载。 #下载模型需要先安装 Git LFS ，然后运行

$ git lfs install $ git clone https://hf-mirror.com/THUDM/chatglm2-6b $ git clone https://hf-mirror.com/GanymedeNil/text2vec-large-chinese

修改configs配置文件

#在model_config.py中添加模型绝对目录。

运行程序