Llama_Difu / app.py
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Update app.py
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import gradio as gr
import os
from llama_func import *
from utils import *
from presets import *
os.environ['OPENAI_API_KEY'] = ""
title = """<h1 align="center">🦙Llama_Difu</h1><h3 align="center">Llama Do it for you —— 让Llama来帮你读代码、论文、书籍</h3>"""
description = """<div align=center>
由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) 和 [明昭MZhao](https://space.bilibili.com/24807452)开发
</div>
"""
customCSS = """
code {
display: inline;
white-space: break-spaces;
border-radius: 6px;
margin: 0 2px 0 2px;
padding: .2em .4em .1em .4em;
background-color: rgba(175,184,193,0.2);
}
pre {
display: block;
white-space: pre;
background-color: hsla(0, 0%, 0%, 72%);
border: solid 5px var(--color-border-primary) !important;
border-radius: 8px;
padding: 0 1.2rem 1.2rem;
margin-top: 1em !important;
color: #FFF;
box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
}
pre code, pre code code {
background-color: transparent !important;
margin: 0;
padding: 0;
}
"""
with gr.Blocks() as llama_difu:
chat_context = gr.State([])
new_google_chat_context = gr.State([])
gr.HTML(title)
gr.HTML('''<center><a href="https://huggingface.co/spaces/MZhaovo/Llama_Difu?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="复制 Space"></a>强烈建议点击上面的按钮复制一份这个Space,在你自己的Space里运行,响应更迅速、也更安全👆</center>''')
with gr.Row():
with gr.Column(scale=1):
with gr.Box():
gr.Markdown("**OpenAI API-Key**")
api_key = gr.Textbox(show_label=False, placeholder="Please enter your OpenAI API-key",label="OpenAI API-Key", value="", type="password").style(container=False)
with gr.Column(scale=3):
with gr.Box():
gr.Markdown("**Select Index**")
with gr.Row():
with gr.Column(scale=12):
index_select = gr.Dropdown(choices=refresh_json_list(plain=True), show_label=False).style(container=False)
with gr.Column(min_width=30, scale=1):
index_refresh_btn = gr.Button("🔄").style()
with gr.Tab("Ask"):
with gr.Box():
with gr.Column():
gr.Markdown("## Ask")
with gr.Column():
with gr.Accordion("Prompt Template", open=False):
with gr.Row():
sim_k = gr.Slider(1, 10, 1, step=1, label="The Number of Similarity chunks", interactive=True, show_label=True)
tempurature = gr.Slider(0, 2, 0.5, step=0.1, label="Temperature", interactive=True, show_label=True)
tmpl_select = gr.Radio(prompt_tmpl_list, value="Default", label="pre-prompt-template", interactive=True)
prompt_tmpl = gr.Textbox(value=prompt_tmpl_dict["Default"], show_label=False)
query_box = gr.Textbox(lines=3, show_label=False).style(container=False)
query_btn = gr.Button("🚀", variant="primary")
with gr.Box():
gr.Markdown("## Result")
answer = gr.Markdown("")
with gr.Tab("New Google"):
with gr.Row():
chat_tone = gr.Radio(["Creative", "Balanced", "Precise"], label="Chatbot Tone", type="index", value="Balanced")
search_options_checkbox = gr.CheckboxGroup(label="Search Options", choices=["🔍 Search Google", "🔍 Search Baidu", "🔍 Manual Search"])
chatbot = gr.Chatbot()
with gr.Row():
with gr.Column(min_width=50, scale=1):
chat_empty_btn = gr.Button("🧹", variant="secondary")
with gr.Column(scale=12):
chat_input = gr.Textbox(show_label=False, placeholder="Type here...").style(container=False)
with gr.Column(min_width=50, scale=1):
chat_submit_btn = gr.Button("🚀", variant="primary")
suggested_user_turns = gr.Dropdown(choices=[], label="Suggested User Turns")
with gr.Tab("Construct"):
with gr.Row():
with gr.Column():
upload_file = gr.Files(label="Upload Files(Support .txt, .pdf, .epub, .docx)")
with gr.Row():
max_input_size = gr.Slider(256, 4096, 4096, step=1, label="Max Input Size", interactive=True, show_label=True)
num_outputs = gr.Slider(256, 4096, 512, step=1, label="Num Outputs", interactive=True, show_label=True)
with gr.Row():
max_chunk_overlap = gr.Slider(0, 100, 20, step=1, label="Max Chunk Overlap", interactive=True, show_label=True)
chunk_size_limit = gr.Slider(256, 4096, 512, step=1, label="Chunk Size Limit", interactive=True, show_label=True)
new_index_name = gr.Textbox(placeholder="New Index Name", show_label=False).style(container=False)
construct_btn = gr.Button("Construct", variant="primary")
with gr.Row():
with gr.Column():
with gr.Row():
with gr.Column(min_width=50, scale=1):
json_refresh_btn = gr.Button("🔄")
with gr.Column(scale=7):
json_select = gr.Dropdown(choices=refresh_json_list(plain=True), show_label=False, multiselect=False).style(container=False)
with gr.Column(min_width=50, scale=1):
json_confirm_btn = gr.Button("🔎")
json_display = gr.JSON(label="View index json")
gr.Markdown(description)
index_refresh_btn.click(refresh_json_list, None, [index_select])
query_btn.click(ask_ai, [api_key, index_select, query_box, prompt_tmpl, sim_k, tempurature], [answer])
tmpl_select.change(change_prompt_tmpl, [tmpl_select], [prompt_tmpl])
chat_input.submit(chat_ai, [api_key, index_select, chat_input, prompt_tmpl, sim_k, chat_tone, chat_context, chatbot, search_options_checkbox, suggested_user_turns], [chat_context, chatbot, suggested_user_turns])
chat_input.submit(reset_textbox, [], [chat_input])
chat_submit_btn.click(chat_ai, [api_key, index_select, chat_input, prompt_tmpl, sim_k, chat_tone, chat_context, chatbot, search_options_checkbox, suggested_user_turns], [chat_context, chatbot, suggested_user_turns])
chat_submit_btn.click(reset_textbox, [], [chat_input])
chat_empty_btn.click(lambda: ([], []), None, [chat_context, chatbot])
construct_btn.click(construct_index, [api_key, upload_file, new_index_name, max_input_size, num_outputs, max_chunk_overlap], [index_select, json_select])
json_confirm_btn.click(display_json, [json_select], [json_display])
json_refresh_btn.click(refresh_json_list, None, [json_select])
if __name__ == '__main__':
llama_difu.queue().launch()