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import json
import time
import gradio as gr
from web.utils.monitor import TrainingMonitor
from web.train_tab import create_train_tab
from web.eval_tab import create_eval_tab
from web.download_tab import create_download_tab
from web.predict_tab import create_predict_tab
from web.manual_tab import create_manual_tab
def load_constant():
"""Load constant values from config files"""
try:
return json.load(open("src/constant.json"))
except Exception as e:
return {"error": f"Failed to load constant.json: {str(e)}"}
def create_ui():
monitor = TrainingMonitor()
constant = load_constant()
def update_output():
try:
if monitor.is_training:
messages = monitor.get_messages()
loss_plot = monitor.get_loss_plot()
metrics_plot = monitor.get_metrics_plot()
return messages, loss_plot, metrics_plot
else:
if monitor.error_message:
return f"Training stopped with error:\n{monitor.error_message}", None, None
return "Click Start to begin training!", None, None
except Exception as e:
return f"Error in UI update: {str(e)}", None, None
with gr.Blocks() as demo:
gr.Markdown("# VenusFactory")
# Create tabs
with gr.Tabs():
try:
train_components = {"output_text": None, "loss_plot": None, "metrics_plot": None}
train_tab = create_train_tab(constant)
if train_components["output_text"] is not None and train_components["loss_plot"] is not None and train_components["metrics_plot"] is not None:
train_components["output_text"] = train_tab["output_text"]
train_components["loss_plot"] = train_tab["loss_plot"]
train_components["metrics_plot"] = train_tab["metrics_plot"]
eval_components = create_eval_tab(constant)
predict_components = create_predict_tab(constant)
download_components = create_download_tab(constant)
manual_components = create_manual_tab(constant)
except Exception as e:
gr.Markdown(f"Error creating UI components: {str(e)}")
train_components = {"output_text": None, "loss_plot": None, "metrics_plot": None}
if train_components["output_text"] is not None and train_components["loss_plot"] is not None and train_components["metrics_plot"] is not None:
demo.load(
fn=update_output,
inputs=None,
outputs=[
train_components["output_text"],
train_components["loss_plot"],
train_components["metrics_plot"]
]
)
return demo
if __name__ == "__main__":
try:
demo = create_ui()
demo.launch(server_name="0.0.0.0", share=True, allowed_paths=["img"])
except Exception as e:
print(f"Failed to launch UI: {str(e)}") |