Unverified 提交 63453f23 作者: Bob Chang 提交者: GitHub

webui优化:解决每次页面刷新后都需要重新选择知识库的问题,增加Flagging收集问答效果。 (#250)

Co-authored-by: Bob Chang <bob.chang@amway.com>
上级 0d9db37f
......@@ -4,17 +4,21 @@ import shutil
from chains.local_doc_qa import LocalDocQA
from configs.model_config import *
import nltk
import uuid
nltk.data.path = [NLTK_DATA_PATH] + nltk.data.path
def get_vs_list():
lst_default = ["新建知识库"]
if not os.path.exists(VS_ROOT_PATH):
return []
return os.listdir(VS_ROOT_PATH)
return lst_default
lst= os.listdir(VS_ROOT_PATH)
if not lst:
return lst_default
lst.sort(reverse=True)
return lst+ lst_default
vs_list = ["新建知识库"] + get_vs_list()
vs_list =get_vs_list()
embedding_model_dict_list = list(embedding_model_dict.keys())
......@@ -22,6 +26,8 @@ llm_model_dict_list = list(llm_model_dict.keys())
local_doc_qa = LocalDocQA()
logger = gr.CSVLogger()
username = uuid.uuid4().hex
def get_answer(query, vs_path, history, mode,
streaming: bool = STREAMING):
......@@ -46,7 +52,7 @@ def get_answer(query, vs_path, history, mode,
history[-1][-1] = resp + (
"\n\n当前知识库为空,如需基于知识库进行问答,请先加载知识库后,再进行提问。" if mode == "知识库问答" else "")
yield history, ""
logger.flag([query, vs_path, history, mode],username=username)
def init_model():
try:
......@@ -105,11 +111,12 @@ def get_vector_store(vs_id, files, history):
return vs_path, None, history + [[None, file_status]]
def change_vs_name_input(vs_id):
def change_vs_name_input(vs_id,history):
if vs_id == "新建知识库":
return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), None
return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), None,history
else:
return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), os.path.join(VS_ROOT_PATH, vs_id)
file_status = f"已加载知识库{vs_id},请开始提问"
return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), os.path.join(VS_ROOT_PATH, vs_id),history + [[None, file_status]]
def change_mode(mode):
......@@ -129,7 +136,6 @@ def add_vs_name(vs_name, vs_list, chatbot):
chatbot = chatbot + [[None, vs_status]]
return gr.update(visible=True, choices=vs_list + [vs_name], value=vs_name), vs_list + [vs_name], chatbot
block_css = """.importantButton {
background: linear-gradient(45deg, #7e0570,#5d1c99, #6e00ff) !important;
border: none !important;
......@@ -146,20 +152,21 @@ webui_title = """
👍 [https://github.com/imClumsyPanda/langchain-ChatGLM](https://github.com/imClumsyPanda/langchain-ChatGLM)
"""
init_message = """欢迎使用 langchain-ChatGLM Web UI!
default_vs = vs_list[0] if len(vs_list) > 1 else "为空"
init_message = f"""欢迎使用 langchain-ChatGLM Web UI!
请在右侧切换模式,目前支持直接与 LLM 模型对话或基于本地知识库问答。
知识库问答模式中,选择知识库名称后,即可开始问答,如有需要可以在选择知识库名称后上传文件/文件夹至知识库。
知识库问答模式,选择知识库名称后,即可开始问答,当前知识库{default_vs},如有需要可以在选择知识库名称后上传文件/文件夹至知识库。
知识库暂不支持文件删除,该功能将在后续版本中推出。
"""
model_status = init_model()
default_path = os.path.join(VS_ROOT_PATH, vs_list[0]) if len(vs_list) > 1 else ""
with gr.Blocks(css=block_css) as demo:
vs_path, file_status, model_status, vs_list = gr.State(""), gr.State(""), gr.State(model_status), gr.State(vs_list)
vs_path, file_status, model_status, vs_list = gr.State(default_path), gr.State(""), gr.State(model_status), gr.State(vs_list)
gr.Markdown(webui_title)
with gr.Tab("对话"):
with gr.Row():
......@@ -168,8 +175,7 @@ with gr.Blocks(css=block_css) as demo:
elem_id="chat-box",
show_label=False).style(height=750)
query = gr.Textbox(show_label=False,
placeholder="请输入提问内容,按回车进行提交",
).style(container=False)
placeholder="请输入提问内容,按回车进行提交").style(container=False)
with gr.Column(scale=5):
mode = gr.Radio(["LLM 对话", "知识库问答"],
label="请选择使用模式",
......@@ -212,8 +218,8 @@ with gr.Blocks(css=block_css) as demo:
load_folder_button = gr.Button("上传文件夹并加载知识库")
# load_vs.click(fn=)
select_vs.change(fn=change_vs_name_input,
inputs=select_vs,
outputs=[vs_name, vs_add, file2vs, vs_path])
inputs=[select_vs,chatbot],
outputs=[vs_name, vs_add, file2vs, vs_path, chatbot])
# 将上传的文件保存到content文件夹下,并更新下拉框
load_file_button.click(get_vector_store,
show_progress=True,
......@@ -225,10 +231,10 @@ with gr.Blocks(css=block_css) as demo:
inputs=[select_vs, folder_files, chatbot],
outputs=[vs_path, folder_files, chatbot],
)
logger.setup([query, vs_path, chatbot, mode], "flagged")
query.submit(get_answer,
[query, vs_path, chatbot, mode],
[chatbot, query],
)
[chatbot, query])
with gr.Tab("模型配置"):
llm_model = gr.Radio(llm_model_dict_list,
label="LLM 模型",
......
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