Update app.py

app.py

@@ -13,10 +13,6 @@ import yaml
 with open('config.yaml', 'r') as file:
     config = yaml.safe_load(file)
 
-# Debug: Print the structure of the config
-print("Config structure:")
-print(yaml.dump(config, default_flow_style=False))
-
 # Authenticate using the token stored in Hugging Face Spaces secrets
 if 'HF_TOKEN' in os.environ:
     login(token=os.environ['HF_TOKEN'])
@@ -24,22 +20,12 @@ else:
     raise ValueError("HF_TOKEN not found in environment variables. Please add it to your Space's secrets.")
 
 # Correctly access the config values
-try:
-    base_model = config['config']['model']['name_or_path']
-except KeyError:
-    print("Could not find 'config' -> 'model' -> 'name_or_path' in the config file.")
-    print("Available keys in config:", list(config.keys()))
-    if 'config' in config:
-        print("Available keys in config['config']:", list(config['config'].keys()))
-    base_model = "FLUX.1-dev"  # Default value
+process_config = config['config']['process'][0]  # Assuming the first process is the one we want
 
+base_model = process_config['model']['name_or_path']
 lora_model = "sagar007/sagar_flux"  # This isn't in the config, so we're keeping it as is
+trigger_word = process_config['trigger_word']
 
-try:
-    trigger_word = config['config']['trigger_word']
-except KeyError:
-    print("Could not find 'config' -> 'trigger_word' in the config file.")
-    trigger_word = "sagar" 
 # Global variables
 pipe = None
 cache = {}
@@ -143,9 +129,9 @@ load_cache()
 # Pre-generate and cache example images
 def cache_example_images():
     for prompt in example_prompts:
-        run_lora(prompt, config['config']['sample']['guidance_scale'], config['config']['sample']['sample_steps'], 
-                 config['config']['sample']['walk_seed'], config['config']['sample']['seed'], 
-                 config['config']['sample']['width'], config['config']['sample']['height'], 0.75)
+        run_lora(prompt, process_config['sample']['guidance_scale'], process_config['sample']['sample_steps'], 
+                 process_config['sample']['walk_seed'], process_config['sample']['seed'], 
+                 process_config['sample']['width'], process_config['sample']['height'], 0.75)
 
 # Gradio interface setup
 with gr.Blocks() as app:
@@ -158,14 +144,14 @@ with gr.Blocks() as app:
         with gr.Column():
             result = gr.Image(label="Result")
     with gr.Row():
-        cfg_scale = gr.Slider(minimum=1, maximum=20, value=config['config']['sample']['guidance_scale'], step=0.1, label="CFG Scale")
-        steps = gr.Slider(minimum=1, maximum=100, value=config['config']['sample']['sample_steps'], step=1, label="Steps")
+        cfg_scale = gr.Slider(minimum=1, maximum=20, value=process_config['sample']['guidance_scale'], step=0.1, label="CFG Scale")
+        steps = gr.Slider(minimum=1, maximum=100, value=process_config['sample']['sample_steps'], step=1, label="Steps")
     with gr.Row():
-        width = gr.Slider(minimum=128, maximum=1024, value=config['config']['sample']['width'], step=64, label="Width")
-        height = gr.Slider(minimum=128, maximum=1024, value=config['config']['sample']['height'], step=64, label="Height")
+        width = gr.Slider(minimum=128, maximum=1024, value=process_config['sample']['width'], step=64, label="Width")
+        height = gr.Slider(minimum=128, maximum=1024, value=process_config['sample']['height'], step=64, label="Height")
     with gr.Row():
-        seed = gr.Number(label="Seed", value=config['config']['sample']['seed'], precision=0)
-        randomize_seed = gr.Checkbox(label="Randomize seed", value=config['config']['sample']['walk_seed'])
+        seed = gr.Number(label="Seed", value=process_config['sample']['seed'], precision=0)
+        randomize_seed = gr.Checkbox(label="Randomize seed", value=process_config['sample']['walk_seed'])
     lora_scale = gr.Slider(minimum=0, maximum=1, value=0.75, step=0.01, label="LoRA Scale")
 
     example_dropdown.change(update_prompt, inputs=[example_dropdown], outputs=[prompt])