Update app.py

app.py

@@ -3,7 +3,10 @@ import numpy as np
 import random
 import os
 
+# Fetch the API token from environment variable
 hf_token = os.getenv("HF_TOKEN")
+
+# Load the model from Hugging Face Inference API
 interface = gr.load("models/ZB-Tech/Text-to-Image", token=hf_token)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -11,29 +14,32 @@ MAX_IMAGE_SIZE = 1024
 
 def infer(
     prompt,
-    negative_prompt,
-    seed,
+    negative_prompt,  # May not be supported
+    seed,             # May not be supported
     randomize_seed,
-    width,
-    height,
-    guidance_scale,
-    num_inference_steps,
+    width,            # May not be supported
+    height,           # May not be supported
+    guidance_scale,   # May not be supported
+    num_inference_steps,  # May not be supported
     progress=gr.Progress(track_tqdm=True),
 ):
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
-    # Use the loaded interface to generate the image
-    # Note: Parameters depend on what the ZB-Tech/Text-to-Image model supports via the API
-    image = interface(
-        prompt=prompt,
-        negative_prompt=negative_prompt if negative_prompt else None,
-        seed=seed,
-        width=width,
-        height=height,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-    )
+    # Minimal call to the interface with just the prompt
+    # Add other parameters only if the model supports them
+    image = interface(prompt=prompt)
+
+    # If the model supports additional parameters, you can uncomment and test:
+    # image = interface(
+    #     prompt=prompt,
+    #     negative_prompt=negative_prompt if negative_prompt else None,
+    #     seed=seed,
+    #     width=width,
+    #     height=height,
+    #     guidance_scale=guidance_scale,
+    #     num_inference_steps=num_inference_steps,
+    # )
 
     return image, seed
 
@@ -72,7 +78,7 @@ with gr.Blocks(css=css) as demo:
                 label="Negative prompt",
                 max_lines=1,
                 placeholder="Enter a negative prompt",
-                visible=True,  # Assuming the API supports it
+                visible=True,
             )
 
             seed = gr.Slider(
@@ -91,7 +97,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=512,  # Reasonable default for API
+                    value=512,
                 )
 
                 height = gr.Slider(
@@ -99,7 +105,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=512,  # Reasonable default for API
+                    value=512,
                 )
 
             with gr.Row():
@@ -108,7 +114,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=1.0,  # Default may vary by model
+                    value=1.0,
                 )
 
                 num_inference_steps = gr.Slider(
@@ -116,7 +122,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=10,  # Default may vary by model
+                    value=10,
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])