* Add files via upload

* Update README.md

* use lru_cache to optimize loading of local vector store

---------

Co-authored-by: imClumsyPanda <littlepanda0716@gmail.com>
Co-authored-by: liunux <liunux@office>

Co-authored-by: imClumsyPanda <littlepanda0716@gmail.com>

删除文档的时候重新生成知识库（FAISS）内的数据

* update QR Code

* Add files via upload

* Update README.md

* add streamlit ui including all functions of webui

---------

Co-authored-by: imClumsyPanda <littlepanda0716@gmail.com>

Fixes # None

Before submitting
If you want to review, please refer to the quick start example provided in langchain/chains/dialogue_answering/main.py. You may need to set the openaikey and the following startup parameters: --dialogue-path: the location of the dialogue file, --embedding-model: the HuggingFaceEmbeddings model to use (defaults to GanymedeNil/text2vec-large-chinese) if not specified.

Regarding the format of the dialogue file, please refer to the following information:

```text
sun:
Has the offline model been run?

glide-the:
Yes, it has been run, but the results are not very satisfactory.

glide-the:
It lacks chat intelligence and falls far behind in terms of logic and reasoning.

sun:
Are you available for voice chat?

glide-the:
I'm considering using this offline model: https://huggingface.co/chat

glide-the:
voice chat okay.

glide-the:
You can take a look at the dev_agent branch of the langchain-chatglm project.

glide-the:
There's a dialogue model question-answering example under the agent.

sun:
Alright.

glide-the:
The specified chat record file is exported from WeChat.
```

Build an abstract dialogue model using classes and methods to represent different dialogue elements.
This class serves as a fundamental framework for constructing dialogue models.