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Langchain-Chatchat
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update webui.py

This commit is contained in:
imClumsyPanda 2023-04-14 23:30:37 +08:00
parent 6bb9dcccce
commit 12f5458374
1 changed files with 32 additions and 27 deletions
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59
webui.py
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@ -31,9 +31,12 @@ def upload_file(file):
def get_answer(query, vs_path, history):
resp, history = local_doc_qa.get_knowledge_based_answer(
query=query, vs_path=vs_path, chat_history=history)
return history, history
if vs_path:
resp, history = local_doc_qa.get_knowledge_based_answer(
query=query, vs_path=vs_path, chat_history=history)
else:
history = history + [[None, "请先加载文件后，再进行提问。"]]
return history
def update_status(history, status):
@ -50,26 +53,30 @@ def init_model():
return """模型未成功加载，请重新选择后点击"加载模型"按钮"""
def reinit_model(llm_model, embedding_model, llm_history_len, top_k):
def reinit_model(llm_model, embedding_model, llm_history_len, top_k, history):
try:
local_doc_qa.init_cfg(llm_model=llm_model,
embedding_model=embedding_model,
llm_history_len=llm_history_len,
top_k=top_k)
return """模型已成功重新加载，请选择文件后点击"加载文件"按钮"""
model_status = """模型已成功重新加载，请选择文件后点击"加载文件"按钮"""
except:
return """模型未成功重新加载，请重新选择后点击"加载模型"按钮"""
model_status = """模型未成功重新加载，请重新选择后点击"加载模型"按钮"""
return history + [[None, model_status]]
def get_vector_store(filepath):
vs_path = local_doc_qa.init_knowledge_vector_store(["content/" + filepath])
if vs_path:
file_status = "文件已成功加载，请开始提问"
def get_vector_store(filepath, history):
if local_doc_qa.llm and local_doc_qa.llm:
vs_path = local_doc_qa.init_knowledge_vector_store(["content/" + filepath])
if vs_path:
file_status = "文件已成功加载，请开始提问"
else:
file_status = "文件未成功加载，请重新上传文件"
else:
file_status = "文件未成功加载，请重新上传文件"
print(file_status)
return vs_path, file_status
file_status = "模型未完成加载，请先在加载模型后再导入文件"
vs_path = None
return vs_path, history + [[None, file_status]]
block_css = """.importantButton {
@ -98,7 +105,7 @@ init_message = """欢迎使用 langchain-ChatGLM Web UI，开始提问前，请
model_status = init_model()
with gr.Blocks(css=block_css) as demo:
vs_path, history, file_status, model_status = gr.State(""), gr.State([]), gr.State(""), gr.State(model_status)
vs_path, file_status, model_status = gr.State(""), gr.State(""), gr.State(model_status)
gr.Markdown(webui_title)
with gr.Row():
with gr.Column(scale=2):
@ -106,9 +113,9 @@ 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="请提问",
lines=1,
value="用200字总结一下"
placeholder="请输入提问内容，按回车进行提交",
# lines=1,
# value="用200字总结一下"
).style(container=False)
with gr.Column(scale=1):
@ -144,26 +151,24 @@ with gr.Blocks(css=block_css) as demo:
file = gr.File(label="content file",
file_types=['.txt', '.md', '.docx', '.pdf']
) # .style(height=100)
load_file_button = gr.Button("重新加载文件")
load_file_button = gr.Button("加载文件")
load_model_button.click(reinit_model,
show_progress=True,
inputs=[llm_model, embedding_model, llm_history_len, top_k],
outputs=model_status
).then(update_status, [chatbot, model_status], chatbot)
inputs=[llm_model, embedding_model, llm_history_len, top_k, chatbot],
outputs=chatbot
)
# 将上传的文件保存到content文件夹下,并更新下拉框
file.upload(upload_file,
inputs=file,
outputs=selectFile)
load_file_button.click(get_vector_store,
show_progress=True,
inputs=selectFile,
outputs=[vs_path, file_status],
).then(
update_status, [chatbot, file_status], chatbot
)
inputs=[selectFile, chatbot],
outputs=[vs_path, chatbot],
)
query.submit(get_answer,
[query, vs_path, chatbot],
[chatbot, history],
[chatbot],
)
demo.queue(concurrency_count=3).launch(