Upload 4 files

app.py

@@ -438,7 +438,7 @@ def load_model(checkpoint_path=None):
 
 # ============== Gradio Interface ==============
 
-def generate_chart(prompt, num_steps, guidance_scale, seed, progress=gr.Progress()):
+def generate_chart(prompt, num_steps, guidance_scale, seed):
     global MODEL, TEXT_ENCODER, DIFFUSION, DEVICE, CONFIG
     
     if MODEL is None:
@@ -453,9 +453,6 @@ def generate_chart(prompt, num_steps, guidance_scale, seed, progress=gr.Progress
             if DEVICE.type == "cuda":
                 torch.cuda.manual_seed(seed)
         
-        def update_progress(p):
-            progress(p, desc="Generating...")
-        
         with torch.no_grad():
             context = TEXT_ENCODER([prompt], DEVICE)
             context_uncond = TEXT_ENCODER.get_uncond(1, DEVICE)
@@ -465,7 +462,7 @@ def generate_chart(prompt, num_steps, guidance_scale, seed, progress=gr.Progress
                 shape=(1, 3, CONFIG["image_size"], CONFIG["image_size"]),
                 steps=num_steps,
                 guidance_scale=guidance_scale,
-                progress_callback=update_progress
+                progress_callback=None
             )
         
         # Convert to image
@@ -481,7 +478,7 @@ def generate_chart(prompt, num_steps, guidance_scale, seed, progress=gr.Progress
         return None, f"❌ Error: {str(e)}"
 
 
-def train_model(data_path, epochs, batch_size, learning_rate, image_size, save_name, progress=gr.Progress()):
+def train_model(data_path, epochs, batch_size, learning_rate, image_size, save_name):
     global MODEL, TEXT_ENCODER, DIFFUSION, DEVICE, CONFIG
     
     try:
@@ -545,7 +542,6 @@ def train_model(data_path, epochs, batch_size, learning_rate, image_size, save_n
                 
                 epoch_loss += loss.item()
                 current_step += 1
-                progress(current_step / total_steps, desc=f"Epoch {epoch+1}/{epochs}")
             
             avg_loss = epoch_loss / len(train_loader)
             logs.append(f"Epoch {epoch+1}/{epochs}: loss = {avg_loss:.4f}")
@@ -583,7 +579,7 @@ def load_checkpoint(checkpoint_file):
 # ============== Gradio UI ==============
 
 def create_demo():
-    with gr.Blocks(title="Candlestick Chart Generator", theme=gr.themes.Soft()) as demo:
+    with gr.Blocks(title="Candlestick Chart Generator") as demo:
         gr.Markdown("""
         # 📈 Candlestick Chart Diffusion Generator
         

requirements.txt

@@ -1,7 +1,6 @@
 torch>=2.0.0
 torchvision>=0.15.0
-gradio==4.31.0
-huggingface_hub>=0.22.0
+gradio==3.50.2
 Pillow>=9.5.0
 numpy>=1.24.0
 einops>=0.6.1