import gradio as gr
import os
def generate_html(training_text, iterations, gen_length, layer1, layer2):
safe_text = training_text.replace("\\", "\\\\").replace("\"", "\\\"").replace("\n", "\\n")
html_content = f"""
Live LSTM Training Output (updates every 10s)
Starting training...
"""
# Save the HTML to the /tmp directory (accessible in Hugging Face Spaces)
html_path = "/tmp/train.html"
with open(html_path, "w") as f:
f.write(html_content)
# Return iframe HTML to embed the file
iframe_code = f''
return iframe_code
with gr.Blocks() as demo:
gr.Markdown("## 🧠Live recurrent.js LSTM Trainer (in-browser training)")
training_text = gr.Textbox(label="Training Text", lines=6, placeholder="Paste text here")
iterations = gr.Slider(10, 200, value=50, step=10, label="Training Epochs")
gen_length = gr.Slider(20, 500, value=100, step=10, label="Characters to Generate")
layer1 = gr.Slider(16, 256, value=128, step=16, label="Neurons in Layer 1")
layer2 = gr.Slider(16, 256, value=128, step=16, label="Neurons in Layer 2")
run_button = gr.Button("Start Training")
html_output = gr.HTML()
run_button.click(fn=generate_html,
inputs=[training_text, iterations, gen_length, layer1, layer2],
outputs=html_output)
demo.launch()