提交 0a4dd198 作者: imClumsyPanda

update webui.py

上级 63453f23
......@@ -8,17 +8,19 @@ import uuid
nltk.data.path = [NLTK_DATA_PATH] + nltk.data.path
def get_vs_list():
lst_default = ["新建知识库"]
lst_default = ["新建知识库"]
if not os.path.exists(VS_ROOT_PATH):
return lst_default
lst= os.listdir(VS_ROOT_PATH)
if not lst:
lst = os.listdir(VS_ROOT_PATH)
if not lst:
return lst_default
lst.sort(reverse=True)
return lst+ lst_default
return lst + lst_default
vs_list =get_vs_list()
vs_list = get_vs_list()
embedding_model_dict_list = list(embedding_model_dict.keys())
......@@ -29,6 +31,7 @@ local_doc_qa = LocalDocQA()
logger = gr.CSVLogger()
username = uuid.uuid4().hex
def get_answer(query, vs_path, history, mode,
streaming: bool = STREAMING):
if mode == "知识库问答" and vs_path:
......@@ -51,8 +54,9 @@ def get_answer(query, vs_path, history, mode,
streaming=streaming):
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)
yield history, ""
logger.flag([query, vs_path, history, mode], username=username)
def init_model():
try:
......@@ -78,8 +82,8 @@ def reinit_model(llm_model, embedding_model, llm_history_len, use_ptuning_v2, us
embedding_model=embedding_model,
llm_history_len=llm_history_len,
use_ptuning_v2=use_ptuning_v2,
use_lora = use_lora,
top_k=top_k,)
use_lora=use_lora,
top_k=top_k, )
model_status = """模型已成功重新加载,可以开始对话,或从右侧选择模式后开始对话"""
print(model_status)
except Exception as e:
......@@ -111,12 +115,14 @@ def get_vector_store(vs_id, files, history):
return vs_path, None, history + [[None, file_status]]
def change_vs_name_input(vs_id,history):
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,history
return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), None, history
else:
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]]
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):
......@@ -136,6 +142,7 @@ 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;
......@@ -163,10 +170,11 @@ init_message = f"""欢迎使用 langchain-ChatGLM Web UI!
"""
model_status = init_model()
default_path = os.path.join(VS_ROOT_PATH, vs_list[0]) if len(vs_list) > 1 else ""
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(default_path), 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():
......@@ -175,7 +183,7 @@ 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",
......@@ -218,7 +226,7 @@ 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,chatbot],
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,
......@@ -230,11 +238,11 @@ with gr.Blocks(css=block_css) as demo:
show_progress=True,
inputs=[select_vs, folder_files, chatbot],
outputs=[vs_path, folder_files, chatbot],
)
logger.setup([query, vs_path, chatbot, mode], "flagged")
)
logger.setup([query, vs_path, chatbot, mode], "flagged")
query.submit(get_answer,
[query, vs_path, chatbot, mode],
[chatbot, query])
[query, vs_path, chatbot, mode],
[chatbot, query])
with gr.Tab("模型配置"):
llm_model = gr.Radio(llm_model_dict_list,
label="LLM 模型",
......@@ -250,8 +258,8 @@ with gr.Blocks(css=block_css) as demo:
label="使用p-tuning-v2微调过的模型",
interactive=True)
use_lora = gr.Checkbox(USE_LORA,
label="使用lora微调的权重",
interactive=True)
label="使用lora微调的权重",
interactive=True)
embedding_model = gr.Radio(embedding_model_dict_list,
label="Embedding 模型",
value=EMBEDDING_MODEL,
......@@ -265,7 +273,8 @@ with gr.Blocks(css=block_css) as demo:
load_model_button = gr.Button("重新加载模型")
load_model_button.click(reinit_model,
show_progress=True,
inputs=[llm_model, embedding_model, llm_history_len, use_ptuning_v2, use_lora, top_k, chatbot],
inputs=[llm_model, embedding_model, llm_history_len, use_ptuning_v2, use_lora, top_k,
chatbot],
outputs=chatbot
)
......
Markdown 格式
0%
您添加了 0 到此讨论。请谨慎行事。
请先完成此评论的编辑!
注册 或者 后发表评论