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import gradio as gr
import uuid
from datetime import datetime
import pandas as pd
from model_handler import ModelHandler
from tab_chat import create_chat_tab
from tab_code import create_code_tab
from tab_smart_writer import create_smart_writer_tab
from tab_test import run_model_handler_test, run_clear_chat_test
def get_history_df(history):
if not history:
return pd.DataFrame({'ID': [], '对话': []})
df = pd.DataFrame(history)
return df[['id', 'title']].rename(columns={'id': 'ID', 'title': '对话'})
def on_app_load(history, conv_id):
"""
Handles the application's initial state on load.
- If no history exists, creates a new conversation.
- If the last conversation ID is invalid, loads the most recent one.
- Otherwise, loads the last active conversation.
"""
if not history:
# First time ever loading, create a new chat
conv_id = str(uuid.uuid4())
new_convo = { "id": conv_id, "title": "(新对话)", "messages": [], "timestamp": datetime.now().isoformat() }
history = [new_convo]
return conv_id, history, gr.update(value=get_history_df(history)), []
# Check if the last used conv_id is valid
if conv_id and any(c["id"] == conv_id for c in history):
# It's valid, load it
for convo in history:
if convo["id"] == conv_id:
return conv_id, history, gr.update(value=get_history_df(history)), convo["messages"]
# Last used conv_id is invalid or doesn't exist, load the most recent conversation
most_recent_convo = history[0] # Assumes history is sorted by timestamp desc
conv_id = most_recent_convo["id"]
return conv_id, history, gr.update(value=get_history_df(history)), most_recent_convo["messages"]
CSS = """
#chatbot {
height: calc(100vh - 21px - 16px);
max-height: 1500px;
}
footer {
display: none !important;
}
/* Disable transition and animation for no-transition class */
.no-transition, .no-transition * {
transition: none !important;
animation: none !important;
animation-play-state: paused !important;
}
"""
if __name__ == "__main__":
# Instantiate the model handler with the configuration
model_handler = ModelHandler()
with gr.Blocks(theme=gr.themes.Soft(),
css=CSS,
head="",
head_paths=['./static/toastify.html', './static/app.html'],
fill_height=True,
fill_width=True) as demo:
with gr.Tabs(elem_id='indicator-space-app') as tabs:
with gr.TabItem("文本聊天") as chat_tab:
conversation_store, current_conversation_id, history_df, chatbot = create_chat_tab()
chat_tab.select(
fn=None,
js="() => {window.dispatchEvent(new CustomEvent('tabSelect.chat')); console.log('this'); return null;}",
)
with gr.TabItem("代码生成") as code_tab:
create_code_tab()
code_tab.select(
fn=None,
js="() => {window.dispatchEvent(new CustomEvent('tabSelect.code')); return null;}",
)
with gr.TabItem("写作助手") as writer_tab:
create_smart_writer_tab()
writer_tab.select(
fn=None,
js="() => {window.dispatchEvent(new CustomEvent('tabSelect.writing')); return null;}",
)
with gr.TabItem("测试"):
gr.Markdown("# 功能测试")
with gr.Column():
test_log_output = gr.Textbox(label="测试日志", interactive=False, lines=10)
gr.Button("运行 ModelHandler 测试").click(run_model_handler_test, outputs=test_log_output)
gr.Button("运行 清除聊天 测试").click(run_clear_chat_test, outputs=test_log_output)
# Bind on_app_load to demo.load
demo.load(
on_app_load,
inputs=[conversation_store, current_conversation_id],
outputs=[current_conversation_id, conversation_store, history_df, chatbot],
js="() => {window.dispatchEvent(new CustomEvent('appStart')); console.log('appStart'); return {};}"
)
# Launch the Gradio application
demo.launch()
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