Update app.py

app.py

@@ -15,7 +15,7 @@ API_TOKEN = os.getenv("HF_READ_TOKEN")
 headers = {"Authorization": f"Bearer {API_TOKEN}"}
 timeout = 100
 
-# Function to query the API and return the generated image
+# Function to query the API and return the generated image as PNG
 def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
     if prompt == "" or prompt is None:
         return None
@@ -25,15 +25,15 @@ def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Ka
     API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
     headers = {"Authorization": f"Bearer {API_TOKEN}"}
     
-    # Translate the prompt from Russian to English if necessary
+    # Translate the prompt from Indonesian to English
     prompt = GoogleTranslator(source='id', target='en').translate(prompt)
     print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
 
-    # Add some extra flair to the prompt
+    # Enhance the prompt
     prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
     print(f'\033[1mGeneration {key}:\033[0m {prompt}')
     
-    # Prepare the payload for the API call, including width and height
+    # Prepare the payload
     payload = {
         "inputs": prompt,
         "is_negative": is_negative,
@@ -42,12 +42,12 @@ def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Ka
         "seed": seed if seed != -1 else random.randint(1, 1000000000),
         "strength": strength,
         "parameters": {
-            "width": width,  # Pass the width to the API
-            "height": height  # Pass the height to the API
+            "width": width,
+            "height": height
         }
     }
 
-    # Send the request to the API and handle the response
+    # API request
     response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
     if response.status_code != 200:
         print(f"Error: Failed to get image. Response status: {response.status_code}")
@@ -57,16 +57,23 @@ def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Ka
         raise gr.Error(f"{response.status_code}")
     
     try:
-        # Convert the response content into an image
+        # Convert to PNG
         image_bytes = response.content
-        image = Image.open(io.BytesIO(image_bytes))
+        img = Image.open(io.BytesIO(image_bytes))
+        
+        # Create PNG in memory
+        png_buffer = io.BytesIO()
+        img.save(png_buffer, format="PNG")
+        png_buffer.seek(0)
+        png_image = Image.open(png_buffer)
+        
         print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
-        return image
+        return png_image
     except Exception as e:
         print(f"Error when trying to open the image: {e}")
         return None
 
-# CSS to style the app
+# CSS styling
 css = """
 #app-container {
     max-width: 800px;
@@ -75,42 +82,54 @@ css = """
 }
 """
 
-# Build the Gradio UI with Blocks
+# Gradio UI
 with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
-    # Add a title to the app
     gr.HTML("<center><h1>FLUX.1-Dev</h1></center>")
     
-    # Container for all the UI elements
     with gr.Column(elem_id="app-container"):
-        # Add a text input for the main prompt
         with gr.Row():
             with gr.Column(elem_id="prompt-container"):
                 with gr.Row():
-                    text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
+                    text_prompt = gr.Textbox(
+                        label="Prompt", 
+                        placeholder="Enter a prompt here", 
+                        lines=2, 
+                        elem_id="prompt-text-input"
+                    )
                 
-                # Accordion for advanced settings
                 with gr.Row():
                     with gr.Accordion("Advanced Settings", open=False):
-                        negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
+                        negative_prompt = gr.Textbox(
+                            label="Negative Prompt", 
+                            placeholder="What should not be in the image", 
+                            value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", 
+                            lines=3, 
+                            elem_id="negative-prompt-text-input"
+                        )
                         with gr.Row():
                             width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
                             height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
                         steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
                         cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
                         strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
-                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) # Setting the seed to -1 will make it random
-                        method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
+                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
+                        method = gr.Radio(
+                            label="Sampling method", 
+                            value="DPM++ 2M Karras", 
+                            choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"]
+                        )
 
-        # Add a button to trigger the image generation
         with gr.Row():
             text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
         
-        # Image output area to display the generated image
         with gr.Row():
             image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
         
-        # Bind the button to the query function with the added width and height inputs
-        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)
+        text_button.click(
+            query, 
+            inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], 
+            outputs=image_output
+        )
 
-# Launch the Gradio app
+# Launch the app
 app.launch(show_api=True, share=True)